From 5465eae74c450bac35195ec43e59c1d9a7c25551 Mon Sep 17 00:00:00 2001 From: Mario G <63501500+gronert-m@users.noreply.github.com> Date: Thu, 10 Oct 2024 12:15:13 -0400 Subject: [PATCH 1/3] Update GH Code --- .../ARM_2014_LFS_V01_M_V03_A_GLD_ALL.do | 1835 ++++++++++++++++ .../ARM_2015_LFS_V01_M_V03_A_GLD_ALL.do | 1843 ++++++++++++++++ .../ARM_2016_LFS_V01_M_V03_A_GLD_ALL.do | 1846 +++++++++++++++++ .../ARM_2017_LFS_V01_M_V03_A_GLD_ALL.do | 1840 ++++++++++++++++ .../ARM_2018_LFS_V01_M_V03_A_GLD_ALL.do | 1796 ++++++++++++++++ .../ARM_2019_LFS_V01_M_V03_A_GLD_ALL.do | 1807 ++++++++++++++++ .../ARM_2020_LFS_V01_M_V03_A_GLD_ALL.do | 1785 ++++++++++++++++ .../ARM_2021_LFS_V01_M_V03_A_GLD_ALL.do | 1795 ++++++++++++++++ .../ARM_2022_LFS_V01_M_V03_A_GLD_ALL.do | 1794 ++++++++++++++++ 9 files changed, 16341 insertions(+) create mode 100644 GLD/ARM/ARM_2014_LFS/ARM_2014_LFS_V01_M_V03_A_GLD/Programs/ARM_2014_LFS_V01_M_V03_A_GLD_ALL.do create mode 100644 GLD/ARM/ARM_2015_LFS/ARM_2015_LFS_V01_M_V03_A_GLD/Programs/ARM_2015_LFS_V01_M_V03_A_GLD_ALL.do create mode 100644 GLD/ARM/ARM_2016_LFS/ARM_2016_LFS_V01_M_V03_A_GLD/Programs/ARM_2016_LFS_V01_M_V03_A_GLD_ALL.do create mode 100644 GLD/ARM/ARM_2017_LFS/ARM_2017_LFS_V01_M_V03_A_GLD/Programs/ARM_2017_LFS_V01_M_V03_A_GLD_ALL.do create mode 100644 GLD/ARM/ARM_2018_LFS/ARM_2018_LFS_V01_M_V03_A_GLD/Programs/ARM_2018_LFS_V01_M_V03_A_GLD_ALL.do create mode 100644 GLD/ARM/ARM_2019_LFS/ARM_2019_LFS_V01_M_V03_A_GLD/Programs/ARM_2019_LFS_V01_M_V03_A_GLD_ALL.do create mode 100644 GLD/ARM/ARM_2020_LFS/ARM_2020_LFS_V01_M_V03_A_GLD/Programs/ARM_2020_LFS_V01_M_V03_A_GLD_ALL.do create mode 100644 GLD/ARM/ARM_2021_LFS/ARM_2021_LFS_V01_M_V03_A_GLD/Programs/ARM_2021_LFS_V01_M_V03_A_GLD_ALL.do create mode 100644 GLD/ARM/ARM_2022_LFS/ARM_2022_LFS_V01_M_V03_A_GLD/Programs/ARM_2022_LFS_V01_M_V03_A_GLD_ALL.do diff --git a/GLD/ARM/ARM_2014_LFS/ARM_2014_LFS_V01_M_V03_A_GLD/Programs/ARM_2014_LFS_V01_M_V03_A_GLD_ALL.do b/GLD/ARM/ARM_2014_LFS/ARM_2014_LFS_V01_M_V03_A_GLD/Programs/ARM_2014_LFS_V01_M_V03_A_GLD_ALL.do new file mode 100644 index 000000000..5218b540a --- /dev/null +++ b/GLD/ARM/ARM_2014_LFS/ARM_2014_LFS_V01_M_V03_A_GLD/Programs/ARM_2014_LFS_V01_M_V03_A_GLD_ALL.do @@ -0,0 +1,1835 @@ + +/*%%============================================================================================= + 0: GLD Harmonization Preamble +================================================================================================*/ + +/* ----------------------------------------------------------------------- +<_Program name_> ARM_2014_LFS_V01_M_V03_A_GLD_ALL.do +<_Application_> Stata SE 16.1 <_Application_> +<_Author(s)_> Wolrd Bank Job's Group +<_Date created_> 2023-12-16 +------------------------------------------------------------------------- +<_Country_> Armenia (ARM) +<_Survey Title_> National Labour Force Survey +<_Survey Year_> 2014 +<_Study ID_> ARM_2014_LFS_v01_M +<_Data collection from (M/Y)_> [01/2014] +<_Data collection to (M/Y)_> [12/2014] +<_Source of dataset_> The Armenian 2014 to 2021 data is downloaded from + the website of Statistical Committee of the + Republic of Armenia:https://armstat.am/en/?nid=212 + The data is publicly available. +<_Sample size (HH)_> 7,679 (vs 7,680 planned) +<_Sample size (IND)_> 29,453 +<_Sampling method_> A stratified two-stage probability sample design + with 14 domains as the primary strata and 18,000 + households as the SSU. +<_Geographic coverage_> All 11 regions/marzes. +<_Currency_> Armenian Dram +----------------------------------------------------------------------- +<_ICLS Version_> ICLS 13 +<_ISCED Version_> ISCED-2011 +<_ISCO Version_> ISCO 08 +<_OCCUP National_> NSCO +<_ISIC Version_> ISIC Rev.4 +<_INDUS National_> ISIC Rev.4 +----------------------------------------------------------------------- + +<_Version Control_> + +* Date: [YYYY-MM-DD] File: [As in Program name above] - [Description of changes] +* Date: [YYYY-MM-DD] File: [As in Program name above] - [Description of changes] +* Date: 2024-09-24 - Update vars educy, educat7 +* Date: 2024-10-09 - Include weight by quarter, correct contract variable + + + +-------------------------------------------------------------------------*/ + + +/*%%============================================================================================= + 1: Setting up of program environment, dataset +================================================================================================*/ + +*----------1.1: Initial commands------------------------------* + +clear +set more off +set mem 800m + +*----------1.2: Set directories------------------------------* + +* Define path sections +local server "Y:/GLD" +local country "ARM" +local year "2014" +local survey "LFS" +local vermast "V01" +local veralt "V03" + +* From the definitions, set path chunks +local level_1 "`country'_`year'_`survey'" +local level_2_mast "`level_1'_`vermast'_M" +local level_2_harm "`level_1'_`vermast'_M_`veralt'_A_GLD" + +* From chunks, define path_in, path_output folder +local path_in_stata "`server'/`country'/`level_1'/`level_2_mast'/Data/Stata" +local path_in_other "`server'/`country'/`level_1'/`level_2_mast'/Data/Original" +local path_output "`server'/`country'/`level_1'/`level_2_harm'/Data/Harmonized" + +* Define Output file name +local out_file "`level_2_harm'_ALL.dta" + + +*----------1.3: Database assembly------------------------------* + +* All steps necessary to merge datasets (if several) to have all elements needed to produce +* harmonized output in a single file + + use "`path_in_stata'/ARM_LFS_2014_raw.dta", clear + +/*%%============================================================================================= + 2: Survey & ID +================================================================================================*/ + +{ + +*<_countrycode_> + gen str4 countrycode="`country'" + label var countrycode "Country code" +* + + +*<_survname_> + gen survname="LFS" + label var survname "Survey acronym" +* + + +*<_survey_> + gen survey="LFS" + label var survey "Survey type" +* + + +*<_icls_v_> + gen icls_v="ICLS-13" + label var icls_v "ICLS version underlying questionnaire questions" +* + + +*<_isced_version_> + gen isced_version="isced_2011" + label var isced_version "Version of ISCED used for educat_isced" +* + + +*<_isco_version_> + gen isco_version="" + label var isco_version "Version of ISCO used" +* + + +*<_isic_version_> + gen isic_version="" + label var isic_version "Version of ISIC used" +* + + +*<_year_> + gen int year=`year' + label var year "Year of survey" +* + + +*<_vermast_> + gen str3 vermast="`vermast'" + label var vermast "Version of master data" +* + + +*<_veralt_> + gen str3 veralt="`veralt'" + label var veralt "Version of the alt/harmonized data" +* + + +*<_harmonization_> + gen harmonization="GLD" + label var harmonization "Type of harmonization" +* + + +*<_int_year_> + gen int_year=`year' + label var int_year "Year of the interview" +* + + +*<_int_month_> + gen int_month=A6_Month + label de lblint_month 1 "January" 2 "February" 3 "March" 4 "April" 5 "May" 6 "June" 7 "July" 8 "August" 9 "September" 10 "October" 11 "November" 12 "December" + label value int_month lblint_month + label var int_month "Month of the interview" +* + + +*<_hhid_> + tostring A1, gen(hid) format(%03.0f) + tostring A6_Month, gen(month) format(%03.0f) + egen hhid=concat(month hid) + label var hhid "Household id" +* + + +*<_pid_> + sort hhid B12 + bys hhid: gen memberid=_n + tostring memberid, gen(id_str) format(%02.0f) + egen pid=concat(hhid id_str), punct("-") + label var pid "Individual ID" +* + + +*<_weight_> + gen weight=Weigths_Year + label var weight "Household sampling weight" +* + + +*<_weight_m_> + gen weight_m = . + label var weight_m "Survey sampling weight to obtain national estimates for each month" +* + + +*<_weight_q_> + egen weight_q = rowtotal(Weights_1 Weights_2 Weights_3 Weigths_4) + label var weight_q "Survey sampling weight to obtain national estimates for each quarter" +* + + +*<_psu_> + gen psu=. + label var psu "Primary sampling units" +* + + +*<_ssu_> + gen ssu=hhid + label var ssu "Secondary sampling units" +* + + +*<_strata_> + decode A3, gen(marzname) + decode A5, gen(urbanstat) + gen strata=marzname+" "+urbanstat + label var strata "Strata" +* + + +*<_wave_> + gen wave=. + replace wave=1 if inrange(int_month,1,3) + replace wave=2 if inrange(int_month,4,6) + replace wave=3 if inrange(int_month,7,9) + replace wave=4 if inrange(int_month,10,12) + label var wave "Survey wave" +* + + +*<_panel_> + gen panel="" + label var panel "Panel individual belongs to" +* + + +*<_visit_no_> + gen visit_no=. + label var visit_no "Visit number in panel" +* +} + +/*%%============================================================================================= + 3: Geography +================================================================================================*/ + +{ + +*<_urban_> + gen urban=A5 + recode urban (2=0) + la de lblurban 1 "Urban" 0 "Rural" + label values urban lblurban + label var urban "Location is urban" +* + + +*<_subnatid1_> + gen subnatid1=A3 + tostring subnatid1, replace + replace subnatid1=subnatid1+" - "+marzname + + * Unite names to entire series + replace subnatid1 = "5 - Gegharkunik" if subnatid1 == "5 - Gegharquniq" + replace subnatid1 = "6 - Lori" if subnatid1 == "6 - Lory" + replace subnatid1 = "7 - Kotayk" if subnatid1 == "7 - Kotayq" + replace subnatid1 = "9 - Syunik" if subnatid1 == "9 - Sjuniq" + replace subnatid1 = "10 - Vayoc Dzor" if subnatid1 == "10 - Vajoc Dzor" + + label var subnatid1 "Subnational ID at First Administrative Level" +* + + +*<_subnatid2_> + gen subnatid2=. + label var subnatid2 "Subnational ID at Second Administrative Level" +* + + +*<_subnatid3_> + gen subnatid3=. + label var subnatid3 "Subnational ID at Third Administrative Level" +* + + +*<_subnatidsurvey_> + gen subnatidsurvey=subnatid1+" "+urbanstat + label var subnatidsurvey "Administrative level at which survey is representative" +* + + +*<_subnatid1_prev_> + +/* <_subnatid1_prev_note_> +subnatid1_prev is coded as missing unless the classification used for subnatid1 has changed since the previous survey. + */ + + gen subnatid1_prev=. + label var subnatid1_prev "Classification used for subnatid1 from previous survey" +* + + +*<_subnatid2_prev_> + gen subnatid2_prev=. + label var subnatid2_prev "Classification used for subnatid2 from previous survey" +* + + +*<_subnatid3_prev_> + gen subnatid3_prev=. + label var subnatid3_prev "Classification used for subnatid3 from previous survey" +* + + +*<_gaul_adm1_code_> + gen gaul_adm1_code=. + label var gaul_adm1_code "Global Administrative Unit Layers (GAUL) Admin 1 code" +* + + +*<_gaul_adm2_code_> + gen gaul_adm2_code=. + label var gaul_adm2_code "Global Administrative Unit Layers (GAUL) Admin 2 code" +* + + +*<_gaul_adm3_code_> + gen gaul_adm3_code=. + label var gaul_adm3_code "Global Administrative Unit Layers (GAUL) Admin 3 code" +* + +} + +/*%%============================================================================================= + 4: Demography +================================================================================================*/ + +{ + +*<_hsize_> + bys hhid: egen hsize=max(memberid) + label var hsize "Household size" +* + + +*<_age_> + +/*<_age_note_> + +3 observations in the raw data set have negative (-1) age values. +They were coded as missing values in the harmonization. + +*<_age_note_>*/ + + gen age=Age + replace age=. if Age<0 + replace age=98 if age>98 & age!=. + label var age "Individual age" +* + + +*<_male_> + gen male=B11 + recode male 2=0 + label var male "Sex - Ind is male" + la de lblmale 1 "Male" 0 "Female" + label values male lblmale +* + + +*<_relationharm_> + +/*<_relationharm_note_> + +6 households (18 observations) in the raw data set do not have household heads. +Their household IDs are: + +001376 +002376 +003502 +004083 +006371 +007438 + +During the harmonization, we did not assign household heads to these households. +But users can assign household heads based on their relationship to the head and +other characteristics such as gender and age. + +*<_relationharm_note_>*/ + + gen byte relationharm=B12 + recode relationharm (6 9=3) (7 8=4) (10=5) (11=6) + label var relationharm "Relationship to the head of household - Harmonized" + la de lblrelationharm 1 "Head of household" 2 "Spouse" 3 "Children" 4 "Parents" 5 "Other relatives" 6 "Other and non-relatives" + label values relationharm lblrelationharm +*<_relationharm_> + + +*<_relationcs_> + gen relationcs=B12 + label var relationcs "Relationship to the head of household - Country original" +* + + +*<_marital_> + gen marital=B16 + recode marital (1=2) (2=1) (3=5) + label var marital "Marital status" + la de lblmarital 1 "Married" 2 "Never Married" 3 "Living together" 4 "Divorced/Separated" 5 "Widowed" + label values marital lblmarital +* + + +*<_eye_dsablty_> + gen eye_dsablty=. + la de lbleye_dsablty 1 "No" 2 "Yes-some" 3 "Yes-a lot" 4 "Cannot at all" + label values eye_dsablty lbleye_dsablty + label var eye_dsablty "Disability related to eyesight" +* + + +*<_hear_dsablty_> + gen hear_dsablty=. + la de lblhear_dsablty 1 "No" 2 "Yes-some" 3 "Yes-a lot" 4 "Cannot at all" + label values hear_dsablty lblhear_dsablty + label var hear_dsablty "Disability related to hearing" +* + + +*<_walk_dsablty_> + gen walk_dsablty=. + la de lblwalk_dsablty 1 "No" 2 "Yes-some" 3 "Yes-a lot" 4 "Cannot at all" + label values walk_dsablty lblwalk_dsablty + label var walk_dsablty "Disability related to walking or climbing stairs" +* + + +*<_conc_dsord_> + gen conc_dsord=. + la de lblconc_dsord 1 "No" 2 "Yes-some" 3 "Yes-a lot" 4 "Cannot at all" + label values conc_dsord lblconc_dsord + label var conc_dsord "Disability related to concentration or remembering" +* + + +*<_slfcre_dsablty_> + gen slfcre_dsablty=. + la de lblslfcre_dsablty 1 "No" 2 "Yes-some" 3 "Yes-a lot" 4 "Cannot at all" + label values slfcre_dsablty lblslfcre_dsablty + label var eye_dsablty "Disability related to selfcare" +* + + +*<_comm_dsablty_> + gen comm_dsablty=. + la de lblcomm_dsablty 1 "No" 2 "Yes-some" 3 "Yes-a lot" 4 "Cannot at all" + label values comm_dsablty lblcomm_dsablty + label var eye_dsablty "Disability related to communicating" +* + +} + + +/*%%============================================================================================= + 5: Migration +================================================================================================*/ + +{ +*<_migrated_mod_age_> + gen migrated_mod_age = . + label var migrated_mod_age "Migration module application age" +* + + +*<_migrated_ref_time_> + gen migrated_ref_time = . + label var migrated_ref_time "Reference time applied to migration questions (in years)" +* + + +*<_migrated_binary_> + gen migrated_binary = . + label de lblmigrated_binary 0 "No" 1 "Yes" + replace migrated_binary=. if age + +*<_migrated_years_> + gen migrated_years = . + replace migrated_years=. if migrated_binary!=1 + replace migrated_years=. if age + + +*<_migrated_from_urban_> + gen migrated_from_urban = . + replace migrated_from_urban = . if age + + +*<_migrated_from_cat_> + gen migrated_from_cat = . + replace migrated_from_cat = . if age + + +*<_migrated_from_code_> + gen migrated_from_code = "" + replace migrated_from_code = "" if age + + +*<_migrated_from_country_> + gen migrated_from_country = "" + replace migrated_from_country = "" if migrated_binary!=1 + replace migrated_from_country = "" if age + + +*<_migrated_reason_> + gen migrated_reason = . + replace migrated_reason = . if migrated_binary!=1 + replace migrated_reason = . if age +} + + +/*%%============================================================================================= + 6: Education +================================================================================================*/ + + +{ +*<_ed_mod_age_> + gen byte ed_mod_age=6 + label var ed_mod_age "Education module application age" +* + + +*<_school_> + gen school=. + replace school=. if age + + +*<_literacy_> + gen byte literacy=. + replace literacy=0 if B15==1 + replace literacy=1 if inrange(B15,2,9) + replace literacy=. if age + + +*<_educy_> + gen byte educy=. + replace educy = 0 if B15 == 1 | B15 == 2 + replace educy = 4 if B15 == 3 + replace educy = 9 if B15 == 4 + replace educy = 12 if B15 == 5 + replace educy = 11 if B15 == 6 + replace educy = 15 if B15 == 7 + replace educy = 16 if B15 == 8 + replace educy = 20 if B15 == 9 + replace educy=. if ageage & !mi(educy) & !mi(age) + label var educy "Years of education" +* + + +*<_educat7_> + gen byte educat7= B15 + recode educat7 (6=5) (7=6) (8/9=7) + replace educat7=. if age + + +*<_educat5_> + gen byte educat5=educat7 + recode educat5 (4=3) (5=4) (6 7=5) + replace educat5=. if age + + +*<_educat4_> + gen byte educat4=educat5 + replace educat4=. if age + + +*<_educat_orig_> + gen educat_orig=B15 + label var educat_orig "Original survey education code" +* + + +*<_educat_isced_> + gen educat_isced=. + label var educat_isced "ISCED standardised level of education" +* + + +*<_educat_isced_v_> + gen educat_isced_v="ISCED-2011" + label var educat_isced_v "Version of the ISCED used" +* + +*----------6.1: Education cleanup------------------------------* + +*<_% Correction min age_> + +** Drop info for cases under the age for which questions to be asked (do not need a variable for this) +local ed_var school literacy educy educat7 educat5 educat4 educat_isced +foreach v of local ed_var { + replace `v'=. if ( age < ed_mod_age & !missing(age) ) +} +replace educat_isced_v="." if ( age < ed_mod_age & !missing(age) ) +* + +} + +/*%%============================================================================================= + 7: Training +================================================================================================*/ + +{ + +*<_vocational_> + gen vocational=. + la de vocationallbl 1 "Yes" 0 "No" + la values vocational vocationallbl + label var vocational "Ever received vocational training" +* + + +*<_vocational_type_> + gen vocational_type=. + label de lblvocational_type 1 "Inside Enterprise" 2 "External" + label values vocational_type lblvocational_type + label var vocational_type "Type of vocational training" +* + + +*<_vocational_length_l_> + gen vocational_length_l=. + replace vocational_length_l=. if vocational!=1 + label var vocational_length_l "Length of training in months, lower limit" +* + + +*<_vocational_length_u_> + gen vocational_length_u=. + replace vocational_length_u=. if vocational!=1 + label var vocational_length_u "Length of training in months, upper limit" +* + + +*<_vocational_field_orig_> + gen vocational_field_orig=. + replace vocational_field_orig=. if vocational!=1 + label var vocational_field_orig "Original field of training information" +* + + +*<_vocational_financed_> + gen vocational_financed=. + label de lblvocational_financed 1 "Employer" 2 "Government" 3 "Mixed Employer/Government" 4 "Own funds" 5 "Other" + label var vocational_financed "How training was financed" +* + +} + +/*%%============================================================================================= + 8: Labour +================================================================================================*/ + +*<_minlaborage_> + +/*<_minlaborage_note_> + +The age range for the labor section is 15-75. + +*<_minlaborage_note_>*/ + + gen byte minlaborage=15 + label var minlaborage "Labor module application age" +* + + +*----------8.1: 7 day reference overall------------------------------* + +{ +*<_lstatus_> + gen byte lstatus=. + replace lstatus=1 if G1==1|inrange(G3,1,5)|inrange(G4,1,2) + replace lstatus=2 if lstatus==.&inrange(Z57,1,2) + replace lstatus=3 if lstatus==.&!mi(Z49_4group) + replace lstatus=. if age75&!mi(age)] + label var lstatus "Labor status" + la de lbllstatus 1 "Employed" 2 "Unemployed" 3 "Non-LF" + label values lstatus lbllstatus +* + + +*<_potential_lf_> + +/*<_potential_lf_note_> +Note: var "potential_lf" only takes value if the respondent is not in labor force. (lstatus==3) + +"potential_lf"=1 if the person is +1)available but not searching or inrange(E45,1,3) & (Z57==2) +2)searching but not immediately available to work or Z57==1 & inlist(E45,4,6) + +*/ + + gen potential_lf=. + replace potential_lf=1 if [inrange(E45,1,3) & (Z57==2)] | [Z57==1 & inlist(E45,4,6)] + replace potential_lf=0 if [inrange(E45,1,3) & (Z57==1)] | [Z57==1 & inrange(E45,1,3)] + replace potential_lf=. if age75&!mi(age)] + replace potential_lf=. if lstatus!=3 + label var potential_lf "Potential labour force status" + la de lblpotential_lf 0 "No" 1 "Yes" + label values potential_lf lblpotential_lf +* + + +*<_underemployment_> + gen byte underemployment=E41 + replace underemployment=1 if inrange(E41,1,3) + replace underemployment=0 if E41==4 + replace underemployment=. if age75&!mi(age)] + replace underemployment=. if lstatus!=1 + label var underemployment "Underemployment status" + la de lblunderemployment 0 "No" 1 "Yes" + label values underemployment lblunderemployment +* + + +*<_nlfreason_> + gen byte nlfreason=Z49_4group + recode nlfreason (4=5) + replace nlfreason=. if age75&!mi(age)] + replace nlfreason=. if lstatus!=3 + label var nlfreason "Reason not in the labor force" + la de lblnlfreason 1 "Student" 2 "Housekeeper" 3 "Retired" 4 "Disabled" 5 "Other" + label values nlfreason lblnlfreason +* + + +*<_unempldur_l_> + gen byte unempldur_l=Z52 + recode unempldur_l (1=0) (2=3) (3=12) (4=24) (5=36) + replace unempldur_l=. if age75&!mi(age)] + replace unempldur_l=. if lstatus!=2 + label var unempldur_l "Unemployment duration (months) lower bracket" +* + + +*<_unempldur_u_> + gen byte unempldur_u=Z52 + recode unempldur_u (1=3) (2=12) (3=24) (4=36) (5=.) + replace unempldur_u=. if age75&!mi(age)] + replace unempldur_u=. if lstatus!=2 + label var unempldur_u "Unemployment duration (months) upper bracket" +* +} + + +*----------8.2: 7 day reference main job------------------------------* + + +{ +*<_empstat_> + gen byte empstat=D8 + recode empstat (2 7=1) (5=4) (6=2) (8=5) + replace empstat=. if lstatus!=1|age + + +*<_ocusec_> + gen byte ocusec=D11 + recode ocusec (3 4=2) + replace ocusec=. if lstatus!=1|age + + +*<_industry_orig_> + gen industry_orig=D6_21group + replace industry_orig=. if lstatus!=1 + label var industry_orig "Original survey industry code, main job 7 day recall" +* + + +*<_industrycat_isic_> + gen industrycat_isic="" +quietly +{ + replace industrycat_isic="A" if D6_21group==1 + replace industrycat_isic="B" if D6_21group==2 + replace industrycat_isic="C" if D6_21group==3 + replace industrycat_isic="D" if D6_21group==4 + replace industrycat_isic="E" if D6_21group==5 + replace industrycat_isic="F" if D6_21group==6 + replace industrycat_isic="G" if D6_21group==7 + replace industrycat_isic="H" if D6_21group==8 + replace industrycat_isic="I" if D6_21group==9 + replace industrycat_isic="J" if D6_21group==10 + replace industrycat_isic="K" if D6_21group==11 + replace industrycat_isic="L" if D6_21group==12 + replace industrycat_isic="M" if D6_21group==13 + replace industrycat_isic="N" if D6_21group==14 + replace industrycat_isic="O" if D6_21group==15 + replace industrycat_isic="P" if D6_21group==16 + replace industrycat_isic="Q" if D6_21group==17 + replace industrycat_isic="R" if D6_21group==18 + replace industrycat_isic="S" if D6_21group==19 + replace industrycat_isic="T" if D6_21group==20 + replace industrycat_isic="U" if D6_21group==21 +} + + replace industrycat_isic="" if industrycat_isic=="."|lstatus!=1 + label var industrycat_isic "ISIC code of primary job 7 day recall" +* + + +*<_industrycat10_> + gen industrycat10=D6_21group + recode industrycat10 (5=4) (6=5) (7 9=6) (8 10=7) (11/14=8) (15=9) (16/21=10) + replace industrycat10=. if lstatus!=1 + label var industrycat10 "1 digit industry classification, primary job 7 day recall" + la de lblindustrycat10 1 "Agriculture" 2 "Mining" 3 "Manufacturing" 4 "Public utilities" 5 "Construction" 6 "Commerce" 7 "Transport and Comnunications" 8 "Financial and Business Services" 9 "Public Administration" 10 "Other Services, Unspecified" + label values industrycat10 lblindustrycat10 +* + + +*<_industrycat4_> + gen byte industrycat4=industrycat10 + recode industrycat4 (3/5=2)(6/9=3)(10=4) + label var industrycat4 "1 digit industry classification (Broad Economic Activities), primary job 7 day recall" + la de lblindustrycat4 1 "Agriculture" 2 "Industry" 3 "Services" 4 "Other" + label values industrycat4 lblindustrycat4 +* + + +*<_occup_orig_> + gen occup_orig=D5_9group + replace occup_orig=. if lstatus!=1|[age>75&!mi(age)] + label var occup_orig "Original occupation record primary job 7 day recall" +* + + +*<_occup_isco_> + gen occup_isco="" + replace occup_isco="" if lstatus!=1 | occup_isco=="." + label var occup_isco "ISCO code of primary job 7 day recall" +* + + +*<_occup_skill_> + gen occup_skill=D5_9group + replace occup_skill=1 if D5_9group==9 + replace occup_skill=2 if inrange(D5_9group, 4, 8) + replace occup_skill=3 if inrange(D5_9group, 1, 3) + replace occup_skill=. if lstatus!=1 + la de lblskill 1 "Low skill" 2 "Medium skill" 3 "High skill" + label values occup_skill lblskill + label var occup_skill "Skill based on ISCO standard primary job 7 day recall" +* + + +*<_occup_> + gen occup=D5_9group + replace occup=. if lstatus!=1|[age>75&!mi(age)] + label var occup "1 digit occupational classification, primary job 7 day recall" + la de lbloccup 1 "Managers" 2 "Professionals" 3 "Technicians" 4 "Clerks" 5 "Service and market sales workers" 6 "Skilled agricultural" 7 "Craft workers" 8 "Machine operators" 9 "Elementary occupations" 10 "Armed forces" 99 "Others" + label values occup lbloccup +* + + +*<_wage_no_compen_> + +/*<_wage_no_compen_note_> + +The wage questions in the questionnare are organized into to parts: the first part +asks for the specific number of income if the given respondent could recall and was +willing to answer; the second part provides different categories of income range +if the given respondent could not recall or was not willing to answer the first part. + +The general logic here is to impute wage values for people who only answered an income +range. We used industry, occupation, income categories and gender to estimate their +specific income values. + +16.32% of total non-missing wage values were imputed using this method. + +*<_wage_no_compen_note_>*/ + + * Overall --> wage info (here the variable, for us it should be wage_no_compen) + * to missing if value is 0. + gen wage14=D14_1+D14_2 + replace wage14=. if wage14==0 + + * First replace outliers by + winsor2 wage14, suffix(_w) cuts(1 99) + + * Create salary categories based on winsor values + gen salary_cat=. + replace salary_cat=1 if inrange(wage14_w, 1, 45000) + replace salary_cat=2 if wage14_w==45000 + replace salary_cat=3 if inrange(wage14_w, 45001, 90000) + replace salary_cat=4 if inrange(wage14_w, 90000, 180000) + replace salary_cat=5 if inrange(wage14_w, 180000, 360000) + replace salary_cat=6 if inrange(wage14_w, 360000, 500000) + replace salary_cat=7 if inrange(wage14_w, 500000, 700000) + replace salary_cat=8 if inrange(wage14_w, 700000, 3450000) + + * Preserve to collapse, so we can merge the info in + preserve + + * Collpase by industry, sex, and salary categories + collapse (mean)wage14_w[iw=weight], by(industrycat10 occup male urban salary_cat) + + * Rename variable, otherwise when merging in, master version of an equally name one will be kept + rename wage14_w wage_group_estimate + + * Rename salary_cat to D15 since this is what we want the info to latch on to + rename salary_cat D15 + tempfile salary_helper + save "`salary_helper'" + + * Restore, merge in + restore + merge m:1 industrycat10 occup male urban D15 using "`salary_helper'", keep(master matched) nogen + + * Create wage variable + gen wage_no_compen=. + + * Fill it first with values that are accurate + replace wage_no_compen=wage14 if !mi(wage14)&mi(D15) + + * Now add the categorised means + replace wage_no_compen=wage_group_estimate if inrange(D15,1,8)&!mi(wage_group_estimate) + + * Keep only for employed employees, label + replace wage_no_compen=. if lstatus!=1|empstat==2 + label var wage_no_compen "Last wage payment primary job 7 day recall" + +* + + +*<_unitwage_> + gen byte unitwage=D16 + recode unitwage (4=5) (5=7) (6=8) (7=10) + replace unitwage=. if lstatus!=1 | empstat==2 + label var unitwage "Last wages' time unit primary job 7 day recall" + la de lblunitwage 1 "Daily" 2 "Weekly" 3 "Every two weeks" 4 "Bimonthly" 5 "Monthly" 6 "Trimester" 7 "Biannual" 8 "Annually" 9 "Hourly" 10 "Other" + label values unitwage lblunitwage +* + + +*<_whours_> + gen whours=E39_1 + replace whours=. if lstatus!=1|E39_1==0 + label var whours "Hours of work in last week primary job 7 day recall" +* + + +*<_wmonths_> + gen wmonths=. + label var wmonths "Months of work in past 12 months primary job 7 day recall" +* + + +*<_wage_total_> + gen wage_total=. + label var wage_total "Annualized total wage primary job 7 day recall" +* + + +*<_contract_> + +/*<_contract_note_> + +There is no separate contract question in the questionnaire. +This contract variable was coded based on employment status question which asks +wether an employed respondent had a contract or not. + +*<_contract_note_>*/ + + gen byte contract = . + replace contract = (D8 == 1) + replace contract=. if lstatus != 1 + label var contract "Employment has contract primary job 7 day recall" + la de lblcontract 0 "Without contract" 1 "With contract" + label values contract lblcontract +* + + +*<_healthins_> + gen byte healthins=. + replace healthins=1 if D9_6==1 + replace healthins=0 if D9_6==2 + replace healthins=. if lstatus!=1 + label var healthins "Employment has health insurance primary job 7 day recall" + la de lblhealthins 0 "Without health insurance" 1 "With health insurance" + label values healthins lblhealthins +* + + +*<_socialsec_> + gen byte socialsec=. + replace socialsec=. if lstatus!=1 + label var socialsec "Employment has social security insurance primary job 7 day recall" + la de lblsocialsec 1 "With social security" 0 "Without social secturity" + label values socialsec lblsocialsec +* + + +*<_union_> + gen byte union=. + replace union=1 if D23==1 + replace union=0 if D23==2 + replace union=. if lstatus!=1 + label var union "Union membership at primary job 7 day recall" + la de lblunion 0 "Not union member" 1 "Union member" + label values union lblunion +* + + +*<_firmsize_l_> + gen byte firmsize_l=. + replace firmsize_l=. if lstatus!=1 + label var firmsize_l "Firm size (lower bracket) primary job 7 day recall" +* + + +*<_firmsize_u_> + gen byte firmsize_u=. + replace firmsize_u=. if lstatus!=1 + label var firmsize_u "Firm size (upper bracket) primary job 7 day recall" +* + +} + + +*----------8.3: 7 day reference secondary job------------------------------* +* Since labels are the same as main job, values are labelled using main job labels + +{ +*<_empstat_2_> + gen byte empstat_2=E27 + recode empstat_2 (2 7=1) (5=4) (6=2) + replace empstat_2=. if lstatus!=1|E24!=1 + label var empstat_2 "Employment status during past week secondary job 7 day recall" + la de lblempstat_2 1 "Paid employee" 2 "Non-paid employee" 3 "Employer" 4 "Self-employed" 5 "Other, workers not classifiable by status" + label values empstat_2 lblempstat +* + + +*<_ocusec_2_> + gen byte ocusec_2=E29 + recode ocusec_2 (3 4=2) + replace ocusec_2=. if lstatus!=1|E24!=1 + label var ocusec_2 "Sector of activity secondary job 7 day recall" + la de lblocusec_2 1 "Public Sector, Central Government, Army" 2 "Private, NGO" 3 "State owned" 4 "Public or State-owned, but cannot distinguish" + label values ocusec_2 lblocusec_2 +* + + +*<_industry_orig_2_> + gen industry_orig_2=E26_21group + replace industry_orig_2=. if lstatus!=1|E24!=1 + label var industry_orig_2 "Original survey industry code, secondary job 7 day recall" +* + + +*<_industrycat_isic_2_> + gen industrycat_isic_2="" +quietly +{ + replace industrycat_isic_2="A" if E26_21group==1 + replace industrycat_isic_2="B" if E26_21group==2 + replace industrycat_isic_2="C" if E26_21group==3 + replace industrycat_isic_2="D" if E26_21group==4 + replace industrycat_isic_2="E" if E26_21group==5 + replace industrycat_isic_2="F" if E26_21group==6 + replace industrycat_isic_2="G" if E26_21group==7 + replace industrycat_isic_2="H" if E26_21group==8 + replace industrycat_isic_2="I" if E26_21group==9 + replace industrycat_isic_2="J" if E26_21group==10 + replace industrycat_isic_2="K" if E26_21group==11 + replace industrycat_isic_2="L" if E26_21group==12 + replace industrycat_isic_2="M" if E26_21group==13 + replace industrycat_isic_2="N" if E26_21group==14 + replace industrycat_isic_2="O" if E26_21group==15 + replace industrycat_isic_2="P" if E26_21group==16 + replace industrycat_isic_2="Q" if E26_21group==17 + replace industrycat_isic_2="R" if E26_21group==18 + replace industrycat_isic_2="S" if E26_21group==19 + replace industrycat_isic_2="T" if E26_21group==20 + replace industrycat_isic_2="U" if E26_21group==21 +} + + replace industrycat_isic_2="" if industrycat_isic_2=="."|E24!=1 + label var industrycat_isic_2 "ISIC code of secondary job 7 day recall" +* + + +*<_industrycat10_2_> + gen industrycat10_2=E26_21group + recode industrycat10_2 (5=4) (6=5) (7 9=6) (8 10=7) (11/14=8) (15=9) (16/21=10) + replace industrycat10_2=. if lstatus!=1|E24!=1 + label var industrycat10_2 "1 digit industry classification, secondary job 7 day recall" + label values industrycat10_2 lblindustrycat10 +* + + +*<_industrycat4_2_> + gen byte industrycat4_2=industrycat10_2 + recode industrycat4_2 (3/5=2)(6/9=3)(10=4) + label var industrycat4_2 "1 digit industry classification (Broad Economic Activities), secondary job 7 day recall" + label values industrycat4_2 lblindustrycat4 +* + + +*<_occup_orig_2_> + gen occup_orig_2=E25_9group + replace occup_orig_2=. if lstatus!=1|E24!=1 + label var occup_orig_2 "Original occupation record secondary job 7 day recall" +* + + +*<_occup_isco_2_> + gen occup_isco_2="" + replace occup_isco_2="" if lstatus!=1 | occup_isco_2=="."|E24!=1 + label var occup_isco_2 "ISCO code of secondary job 7 day recall" +* + + +*<_occup_skill_2_> + gen occup_skill_2=E25_9group + replace occup_skill_2=1 if E25_9group==9 + replace occup_skill_2=2 if inrange(E25_9group,4,8) + replace occup_skill_2=3 if inrange(E25_9group,1,3) + replace occup_skill_2=. if E25_9group==0|lstatus!=1|E24!=1 + label var occup_skill_2 "Skill based on ISCO standard secondary job 7 day recall" +* + + +*<_occup_2_> + gen occup_2=E25_9group + replace occup_2=. if lstatus!=1|E24!=1 + label var occup_2 "1 digit occupational classification secondary job 7 day recall" + label values occup_2 lbloccup +* + + +*<_wage_no_compen_2_> + + gen wage32=E32_1+E32_2 + replace wage32=. if wage32==0 + + * First replace outliers by + winsor2 wage32, suffix(_w) cuts(1 99) + + * Create salary categories based on winsor values + gen salary_cat2=. + replace salary_cat2=1 if inrange(wage32_w, 1, 45000) + replace salary_cat2=2 if wage32_w==45000 + replace salary_cat2=3 if inrange(wage32_w, 45001, 90000) + replace salary_cat2=4 if inrange(wage32_w, 90000, 180000) + replace salary_cat2=5 if inrange(wage32_w, 180000, 360000) + + * Preserve to collapse, so we can merge the info in + preserve + + * Collpase by industry, sex, and salary categories + collapse (mean)wage32_w[iw=weight], by(industrycat10_2 occup_2 male urban salary_cat2) + + * Rename variable, otherwise when merging in, master version of an equally name one will be kept + rename wage32_w wage_group_estimate2 + + * Rename salary_cat to D15 since this is what we want the info to latch on to + rename salary_cat2 E33 + tempfile salary_helper2 + save "`salary_helper2'" + + * Restore, merge in + restore + merge m:1 industrycat10_2 occup_2 male urban E33 using "`salary_helper2'", keep(matched master) nogen + + * Create wage variable + gen wage_no_compen_2=. + + * Fill it first with values that are accurate + replace wage_no_compen_2=wage32 if !mi(wage32)&mi(E33) + + * Now add the categorised means + replace wage_no_compen_2=wage_group_estimate2 if inrange(E33,1,5)&!mi(wage_group_estimate2) + + * Keep only for employed employees, label + replace wage_no_compen_2=. if E24!=1|empstat_2==2 + label var wage_no_compen_2 "Last wage payment secondary job 7 day recall" +* + + +*<_unitwage_2_> + gen byte unitwage_2=E34 + recode unitwage_2 (4=5) (5=7) (6=8) (7=10) + replace unitwage_2=. if lstatus!=1|E24!=1 + label var unitwage_2 "Last wages' time unit secondary job 7 day recall" + label values unitwage_2 lblunitwage +* + + +*<_whours_2_> + gen whours_2=E38_2 + replace whours_2=. if E38_2==0|E24!=1 + label var whours_2 "Hours of work in last week secondary job 7 day recall" +* + + +*<_wmonths_2_> + gen wmonths_2=. + label var wmonths_2 "Months of work in past 12 months secondary job 7 day recall" +* + + +*<_wage_total_2_> + gen wage_total_2=. + label var wage_total_2 "Annualized total wage secondary job 7 day recall" +* + + +*<_firmsize_l_2_> + gen byte firmsize_l_2=. + label var firmsize_l_2 "Firm size (lower bracket) secondary job 7 day recall" +* + + +*<_firmsize_u_2_> + gen byte firmsize_u_2=. + label var firmsize_u_2 "Firm size (upper bracket) secondary job 7 day recall" +* + +} + +*----------8.4: 7 day reference additional jobs------------------------------* + +*<_t_hours_others_> + gen t_hours_others=. + label var t_hours_others "Annualized hours worked in all but primary and secondary jobs 7 day recall" +* + + +*<_t_wage_nocompen_others_> + gen t_wage_nocompen_others=. + label var t_wage_nocompen_others "Annualized wage in all but primary & secondary jobs excl. bonuses, etc. 7 day recall" +* + + +*<_t_wage_others_> + gen t_wage_others=. + label var t_wage_others "Annualized wage in all but primary and secondary jobs (12-mon ref period)" +* + + +*----------8.5: 7 day reference total summary------------------------------* + + +*<_t_hours_total_> + gen t_hours_total=. + label var t_hours_total "Annualized hours worked in all jobs 7 day recall" +* + + +*<_t_wage_nocompen_total_> + gen t_wage_nocompen_total=. + label var t_wage_nocompen_total "Annualized wage in all jobs excl. bonuses, etc. 7 day recall" +* + + +*<_t_wage_total_> + gen t_wage_total=. + label var t_wage_total "Annualized total wage for all jobs 7 day recall" +* + + +*----------8.6: 12 month reference overall------------------------------* + +{ +*<_lstatus_year_> + gen byte lstatus_year=. + replace lstatus_year=. if age + + +*<_potential_lf_year_> + gen byte potential_lf_year=. + replace potential_lf_year=. if age + + +*<_underemployment_year_> + gen byte underemployment_year=. + replace underemployment_year=. if age + + +*<_nlfreason_year_> + gen byte nlfreason_year=. + label var nlfreason_year "Reason not in the labor force" + la de lblnlfreason_year 1 "Student" 2 "Housekeeper" 3 "Retired" 4 "Disable" 5 "Other" + label values nlfreason_year lblnlfreason_year +* + + +*<_unempldur_l_year_> + gen byte unempldur_l_year=. + label var unempldur_l_year "Unemployment duration (months) lower bracket" +* + + +*<_unempldur_u_year_> + gen byte unempldur_u_year=. + label var unempldur_u_year "Unemployment duration (months) upper bracket" +* + +} + +*----------8.7: 12 month reference main job------------------------------* + +{ +*<_empstat_year_> + gen byte empstat_year=. + label var empstat_year "Employment status during past week primary job 12 month recall" + la de lblempstat_year 1 "Paid employee" 2 "Non-paid employee" 3 "Employer" 4 "Self-employed" 5 "Other, workers not classifiable by status" + label values empstat_year lblempstat_year +* + + +*<_ocusec_year_> + gen byte ocusec_year=. + label var ocusec_year "Sector of activity primary job 12 day recall" + la de lblocusec_year 1 "Public Sector, Central Government, Army" 2 "Private, NGO" 3 "State owned" 4 "Public or State-owned, but cannot distinguish" + label values ocusec_year lblocusec_year +* + + +*<_industry_orig_year_> + gen industry_orig_year=. + label var industry_orig_year "Original industry record main job 12 month recall" +* + + +*<_industrycat_isic_year_> + gen industrycat_isic_year="" + replace industrycat_isic_year="" if industrycat_isic_year=="." + label var industrycat_isic_year "ISIC code of primary job 12 month recall" +* + + +*<_industrycat10_year_> + gen byte industrycat10_year=. + label var industrycat10_year "1 digit industry classification, primary job 12 month recall" + la de lblindustrycat10_year 1 "Agriculture" 2 "Mining" 3 "Manufacturing" 4 "Public utilities" 5 "Construction" 6 "Commerce" 7 "Transport and Comnunications" 8 "Financial and Business Services" 9 "Public Administration" 10 "Other Services, Unspecified" + label values industrycat10_year lblindustrycat10_year +* + + +*<_industrycat4_year_> + gen byte industrycat4_year=industrycat10_year + recode industrycat4_year (1=1)(2 3 4 5 =2)(6 7 8 9=3)(10=4) + label var industrycat4_year "1 digit industry classification (Broad Economic Activities), primary job 12 month recall" + la de lblindustrycat4_year 1 "Agriculture" 2 "Industry" 3 "Services" 4 "Other" + label values industrycat4_year lblindustrycat4_year +* + + +*<_occup_orig_year_> + gen occup_orig_year=. + label var occup_orig_year "Original occupation record primary job 12 month recall" +* + + +*<_occup_isco_year_> + gen str4 occup_isco_year="" + label var occup_isco_year "ISCO code of primary job 12 month recall" +* + + +*<_occup_skill_year_> + gen skill_level_year=substr(occup_isco_year,1,1) + destring skill_level_year, replace + gen occup_skill_year=. + replace occup_skill_year=1 if skill_level_year==9 + replace occup_skill_year=2 if inrange(skill_level_year,4,8) + replace occup_skill_year=3 if inrange(skill_level_year,1,3) + replace occup_skill_year=. if skill_level_year==0 + label var occup_skill_year "Skill based on ISCO standard primary job 12 month recall" +* + + +*<_occup_year_> + gen byte occup_year=. + label var occup_year "1 digit occupational classification, primary job 12 month recall" + la de lbloccup_year 1 "Managers" 2 "Professionals" 3 "Technicians" 4 "Clerks" 5 "Service and market sales workers" 6 "Skilled agricultural" 7 "Craft workers" 8 "Machine operators" 9 "Elementary occupations" 10 "Armed forces" 99 "Others" + label values occup_year lbloccup_year +* + + +*<_wage_no_compen_year_> + gen double wage_no_compen_year=. + label var wage_no_compen_year "Last wage payment primary job 12 month recall" +* + + +*<_unitwage_year_> + gen byte unitwage_year=. + label var unitwage_year "Last wages' time unit primary job 12 month recall" + la de lblunitwage_year 1 "Daily" 2 "Weekly" 3 "Every two weeks" 4 "Bimonthly" 5 "Monthly" 6 "Trimester" 7 "Biannual" 8 "Annually" 9 "Hourly" 10 "Other" + label values unitwage_year lblunitwage_year +* + + +*<_whours_year_> + gen whours_year=. + label var whours_year "Hours of work in last week primary job 12 month recall" +* + + +*<_wmonths_year_> + gen wmonths_year=. + label var wmonths_year "Months of work in past 12 months primary job 12 month recall" +* + + +*<_wage_total_year_> + gen wage_total_year=. + label var wage_total_year "Annualized total wage primary job 12 month recall" +* + + +*<_contract_year_> + gen byte contract_year=. + label var contract_year "Employment has contract primary job 12 month recall" + la de lblcontract_year 0 "Without contract" 1 "With contract" + label values contract_year lblcontract_year +* + + +*<_healthins_year_> + gen byte healthins_year=. + label var healthins_year "Employment has health insurance primary job 12 month recall" + la de lblhealthins_year 0 "Without health insurance" 1 "With health insurance" + label values healthins_year lblhealthins_year +* + + +*<_socialsec_year_> + gen byte socialsec_year=. + label var socialsec_year "Employment has social security insurance primary job 7 day recall" + la de lblsocialsec_year 1 "With social security" 0 "Without social secturity" + label values socialsec_year lblsocialsec_year +* + + +*<_union_year_> + gen byte union_year=. + label var union_year "Union membership at primary job 12 month recall" + la de lblunion_year 0 "Not union member" 1 "Union member" + label values union_year lblunion_year +* + + +*<_firmsize_l_year_> + gen byte firmsize_l_year=. + label var firmsize_l_year "Firm size (lower bracket) primary job 12 month recall" +* + + +*<_firmsize_u_year_> + gen byte firmsize_u_year=. + label var firmsize_u_year "Firm size (upper bracket) primary job 12 month recall" +* + +} + + +*----------8.8: 12 month reference secondary job------------------------------* + +{ + +*<_empstat_2_year_> + gen byte empstat_2_year=. + label var empstat_2_year "Employment status during past week secondary job 12 month recall" + label values empstat_2_year lblempstat_year +* + + +*<_ocusec_2_year_> + gen byte ocusec_2_year=. + label var ocusec_2_year "Sector of activity secondary job 12 day recall" + la de lblocusec_2_year 1 "Public Sector, Central Government, Army" 2 "Private, NGO" 3 "State owned" 4 "Public or State-owned, but cannot distinguish" + label values ocusec_2_year lblocusec_2_year +* + + + +*<_industry_orig_2_year_> + gen industry_orig_2_year=. + label var industry_orig_2_year "Original survey industry code, secondary job 12 month recall" +* + + + +*<_industrycat_isic_2_year_> + gen industrycat_isic_2_year=. + label var industrycat_isic_2_year "ISIC code of secondary job 12 month recall" +* + + +*<_industrycat10_2_year_> + gen byte industrycat10_2_year=. + label var industrycat10_2_year "1 digit industry classification, secondary job 12 month recall" + label values industrycat10_2_year lblindustrycat10_year +* + + +*<_industrycat4_2_year_> + gen byte industrycat4_2_year=industrycat10_2_year + recode industrycat4_2_year (1=1)(2 3 4 5 =2)(6 7 8 9=3)(10=4) + label var industrycat4_2_year "1 digit industry classification (Broad Economic Activities), secondary job 12 month recall" + label values industrycat4_2_year lblindustrycat4_year +* + + +*<_occup_orig_2_year_> + gen occup_orig_2_year=. + label var occup_orig_2_year "Original occupation record secondary job 12 month recall" +* + + +*<_occup_isco_2_year_> + gen occup_isco_2_year=. + label var occup_isco_2_year "ISCO code of secondary job 12 month recall" +* + + +*<_occup_skill_2_year_> + gen occup_skill_2_year=. + label var occup_skill_2_year "Skill based on ISCO standard secondary job 12 month recall" +* + + +*<_occup_2_year_> + gen byte occup_2_year=. + label var occup_2_year "1 digit occupational classification, secondary job 12 month recall" + label values occup_2_year lbloccup_year +* + + +*<_wage_no_compen_2_year_> + gen double wage_no_compen_2_year=. + label var wage_no_compen_2_year "Last wage payment secondary job 12 month recall" +* + + +*<_unitwage_2_year_> + gen byte unitwage_2_year=. + label var unitwage_2_year "Last wages' time unit secondary job 12 month recall" + label values unitwage_2_year lblunitwage_year +* + + +*<_whours_2_year_> + gen whours_2_year=. + label var whours_2_year "Hours of work in last week secondary job 12 month recall" +* + + +*<_wmonths_2_year_> + gen wmonths_2_year=. + label var wmonths_2_year "Months of work in past 12 months secondary job 12 month recall" +* + + +*<_wage_total_2_year_> + gen wage_total_2_year=. + label var wage_total_2_year "Annualized total wage secondary job 12 month recall" +* + + +*<_firmsize_l_2_year_> + gen byte firmsize_l_2_year=. + label var firmsize_l_2_year "Firm size (lower bracket) secondary job 12 month recall" +* + + +*<_firmsize_u_2_year_> + gen byte firmsize_u_2_year=. + label var firmsize_u_2_year "Firm size (upper bracket) secondary job 12 month recall" +* + +} + + +*----------8.9: 12 month reference additional jobs------------------------------* + + +*<_t_hours_others_year_> + gen t_hours_others_year=. + label var t_hours_others_year "Annualized hours worked in all but primary and secondary jobs 12 month recall" +* + + +*<_t_wage_nocompen_others_year_> + gen t_wage_nocompen_others_year=. + label var t_wage_nocompen_others_year "Annualized wage in all but primary & secondary jobs excl. bonuses, etc. 12 month recall)" +* + + +*<_t_wage_others_year_> + gen t_wage_others_year=. + label var t_wage_others_year "Annualized wage in all but primary and secondary jobs 12 month recall" +* + + +*----------8.10: 12 month total summary------------------------------* + + +*<_t_hours_total_year_> + gen t_hours_total_year=. + label var t_hours_total_year "Annualized hours worked in all jobs 12 month month recall" +* + + +*<_t_wage_nocompen_total_year_> + gen t_wage_nocompen_total_year=. + label var t_wage_nocompen_total_year "Annualized wage in all jobs excl. bonuses, etc. 12 month recall" +* + + +*<_t_wage_total_year_> + gen t_wage_total_year=. + label var t_wage_total_year "Annualized total wage for all jobs 12 month recall" +* + + +*----------8.11: Overall across reference periods------------------------------* + + +*<_njobs_> + gen njobs=. + replace njobs=1 if lstatus==1&E24!=1 + replace njobs=2 if lstatus==1&E24==1 + replace njobs=. if lstatus!=1 + label var njobs "Total number of jobs" +* + + +*<_t_hours_annual_> + gen t_hours_annual=. + label var t_hours_annual "Total hours worked in all jobs in the previous 12 months" +* + + +*<_linc_nc_> + gen linc_nc=. + label var linc_nc "Total annual wage income in all jobs, excl. bonuses, etc." +* + + +*<_laborincome_> + gen laborincome=. + label var laborincome "Total annual individual labor income in all jobs, incl. bonuses, etc." +* + + +*----------8.13: Labour cleanup------------------------------* + +{ +*<_% Correction min age_> + +** Drop info for cases under the age for which questions to be asked (do not need a variable for this) + local lab_var "minlaborage lstatus nlfreason unempldur_l unempldur_u empstat ocusec industry_orig industrycat_isic industrycat10 industrycat4 occup_orig occup_isco occup_skill occup wage_no_compen unitwage whours wmonths wage_total contract healthins socialsec union firmsize_l firmsize_u empstat_2 ocusec_2 industry_orig_2 industrycat_isic_2 industrycat10_2 industrycat4_2 occup_orig_2 occup_isco_2 occup_skill_2 occup_2 wage_no_compen_2 unitwage_2 whours_2 wmonths_2 wage_total_2 firmsize_l_2 firmsize_u_2 t_hours_others t_wage_nocompen_others t_wage_others t_hours_total t_wage_nocompen_total t_wage_total lstatus_year nlfreason_year unempldur_l_year unempldur_u_year empstat_year ocusec_year industry_orig_year industrycat_isic_year industrycat10_year industrycat4_year occup_orig_year occup_isco_year occup_skill_year occup_year unitwage_year whours_year wmonths_year wage_total_year contract_year healthins_year socialsec_year union_year firmsize_l_year firmsize_u_year empstat_2_year ocusec_2_year industry_orig_2_year industrycat_isic_2_year industrycat10_2_year industrycat4_2_year occup_orig_2_year occup_isco_2_year occup_skill_2_year occup_2_year wage_no_compen_2_year unitwage_2_year whours_2_year wmonths_2_year wage_total_2_year firmsize_l_2_year firmsize_u_2_year t_hours_others_year t_wage_nocompen_others_year t_wage_others_year t_hours_total_year t_wage_nocompen_total_year t_wage_total_year njobs t_hours_annual linc_nc laborincome" + + foreach v of local lab_var { + cap confirm numeric variable `v' + if _rc == 0 { // is indeed numeric + replace `v'=. if ( age < minlaborage & !missing(age) ) + } + else { // is not + replace `v'= "" if ( age < minlaborage & !missing(age) ) + } + + } + +* +} + + +/*%%============================================================================================= + 9: Final steps +==============================================================================================%%*/ + +quietly{ + +*<_% KEEP VARIABLES - ALL_> + + keep countrycode survname survey icls_v isced_version isco_version isic_version year vermast veralt harmonization int_year int_month hhid pid weight weight_m weight_q psu ssu strata wave panel visit_no urban subnatid1 subnatid2 subnatid3 subnatidsurvey subnatid1_prev subnatid2_prev subnatid3_prev gaul_adm1_code gaul_adm2_code gaul_adm3_code hsize age male relationharm relationcs marital eye_dsablty hear_dsablty walk_dsablty conc_dsord slfcre_dsablty comm_dsablty migrated_mod_age migrated_ref_time migrated_binary migrated_years migrated_from_urban migrated_from_cat migrated_from_code migrated_from_country migrated_reason ed_mod_age school literacy educy educat7 educat5 educat4 educat_orig educat_isced vocational vocational_type vocational_length_l vocational_length_u vocational_field_orig vocational_financed minlaborage lstatus potential_lf underemployment nlfreason unempldur_l unempldur_u empstat ocusec industry_orig industrycat_isic industrycat10 industrycat4 occup_orig occup_isco occup_skill occup wage_no_compen unitwage whours wmonths wage_total contract healthins socialsec union firmsize_l firmsize_u empstat_2 ocusec_2 industry_orig_2 industrycat_isic_2 industrycat10_2 industrycat4_2 occup_orig_2 occup_isco_2 occup_skill_2 occup_2 wage_no_compen_2 unitwage_2 whours_2 wmonths_2 wage_total_2 firmsize_l_2 firmsize_u_2 t_hours_others t_wage_nocompen_others t_wage_others t_hours_total t_wage_nocompen_total t_wage_total lstatus_year potential_lf_year underemployment_year nlfreason_year unempldur_l_year unempldur_u_year empstat_year ocusec_year industry_orig_year industrycat_isic_year industrycat10_year industrycat4_year occup_orig_year occup_isco_year occup_skill_year occup_year wage_no_compen_year unitwage_year whours_year wmonths_year wage_total_year contract_year healthins_year socialsec_year union_year firmsize_l_year firmsize_u_year empstat_2_year ocusec_2_year industry_orig_2_year industrycat_isic_2_year industrycat10_2_year industrycat4_2_year occup_orig_2_year occup_isco_2_year occup_skill_2_year occup_2_year wage_no_compen_2_year unitwage_2_year whours_2_year wmonths_2_year wage_total_2_year firmsize_l_2_year firmsize_u_2_year t_hours_others_year t_wage_nocompen_others_year t_wage_others_year t_hours_total_year t_wage_nocompen_total_year t_wage_total_year njobs t_hours_annual linc_nc laborincome + +* + +*<_% ORDER VARIABLES_> + + order countrycode survname survey icls_v isced_version isco_version isic_version year vermast veralt harmonization int_year int_month hhid pid weight weight_m weight_q psu ssu strata wave panel visit_no urban subnatid1 subnatid2 subnatid3 subnatidsurvey subnatid1_prev subnatid2_prev subnatid3_prev gaul_adm1_code gaul_adm2_code gaul_adm3_code hsize age male relationharm relationcs marital eye_dsablty hear_dsablty walk_dsablty conc_dsord slfcre_dsablty comm_dsablty migrated_mod_age migrated_ref_time migrated_binary migrated_years migrated_from_urban migrated_from_cat migrated_from_code migrated_from_country migrated_reason ed_mod_age school literacy educy educat7 educat5 educat4 educat_orig educat_isced vocational vocational_type vocational_length_l vocational_length_u vocational_field_orig vocational_financed minlaborage lstatus potential_lf underemployment nlfreason unempldur_l unempldur_u empstat ocusec industry_orig industrycat_isic industrycat10 industrycat4 occup_orig occup_isco occup_skill occup wage_no_compen unitwage whours wmonths wage_total contract healthins socialsec union firmsize_l firmsize_u empstat_2 ocusec_2 industry_orig_2 industrycat_isic_2 industrycat10_2 industrycat4_2 occup_orig_2 occup_isco_2 occup_skill_2 occup_2 wage_no_compen_2 unitwage_2 whours_2 wmonths_2 wage_total_2 firmsize_l_2 firmsize_u_2 t_hours_others t_wage_nocompen_others t_wage_others t_hours_total t_wage_nocompen_total t_wage_total lstatus_year potential_lf_year underemployment_year nlfreason_year unempldur_l_year unempldur_u_year empstat_year ocusec_year industry_orig_year industrycat_isic_year industrycat10_year industrycat4_year occup_orig_year occup_isco_year occup_skill_year occup_year wage_no_compen_year unitwage_year whours_year wmonths_year wage_total_year contract_year healthins_year socialsec_year union_year firmsize_l_year firmsize_u_year empstat_2_year ocusec_2_year industry_orig_2_year industrycat_isic_2_year industrycat10_2_year industrycat4_2_year occup_orig_2_year occup_isco_2_year occup_skill_2_year occup_2_year wage_no_compen_2_year unitwage_2_year whours_2_year wmonths_2_year wage_total_2_year firmsize_l_2_year firmsize_u_2_year t_hours_others_year t_wage_nocompen_others_year t_wage_others_year t_hours_total_year t_wage_nocompen_total_year t_wage_total_year njobs t_hours_annual linc_nc laborincome + +* + +*<_% DROP UNUSED LABELS_> + + * Store all labels in data + label dir + local all_lab `r(names)' + + * Store all variables with a label, extract value label names + local used_lab = "" + ds, has(vallabel) + + local labelled_vars `r(varlist)' + + foreach varName of local labelled_vars { + local y : value label `varName' + local used_lab `"`used_lab' `y'"' + } + + * Compare lists, `notused' is list of labels in directory but not used in final variables + local notused : list all_lab - used_lab // local `notused' defines value labs not in remaining vars + local notused_len : list sizeof notused // store size of local + + * drop labels if the length of the notused vector is 1 or greater, otherwise nothing to drop + if `notused_len' >= 1 { + label drop `notused' + } + else { + di "There are no unused labels to drop. No value labels dropped." + } + + +* + +} + +*<_% DELETE MISSING VARIABLES_> + +quietly: describe, varlist +local kept_vars `r(varlist)' + +foreach var of local kept_vars { + + capture assert missing(`var') + if !_rc drop `var' +} + +* + + +*<_% COMPRESS_> + +compress + +* + + +*<_% SAVE_> + +save "`path_output'/`level_2_harm'_ALL.dta", replace + +* diff --git a/GLD/ARM/ARM_2015_LFS/ARM_2015_LFS_V01_M_V03_A_GLD/Programs/ARM_2015_LFS_V01_M_V03_A_GLD_ALL.do b/GLD/ARM/ARM_2015_LFS/ARM_2015_LFS_V01_M_V03_A_GLD/Programs/ARM_2015_LFS_V01_M_V03_A_GLD_ALL.do new file mode 100644 index 000000000..fabd08876 --- /dev/null +++ b/GLD/ARM/ARM_2015_LFS/ARM_2015_LFS_V01_M_V03_A_GLD/Programs/ARM_2015_LFS_V01_M_V03_A_GLD_ALL.do @@ -0,0 +1,1843 @@ + +/*%%============================================================================================= + 0: GLD Harmonization Preamble +================================================================================================*/ + +/* ----------------------------------------------------------------------- +<_Program name_> ARM_2015_LFS_V01_M_V03_A_GLD_ALL.do +<_Application_> Stata SE 18 <_Application_> +<_Author(s)_> Wolrd Bank Job's Group +<_Date created_> 2023-12-20 +------------------------------------------------------------------------- +<_Country_> Armenia (ARM) +<_Survey Title_> National Labour Force Survey +<_Survey Year_> 2015 +<_Study ID_> ARM_2015_LFS_v01_M +<_Data collection from (M/Y)_> [01/2015] +<_Data collection to (M/Y)_> [12/2015] +<_Source of dataset_> The Armenian 2015 to 2021 data is downloaded from + the website of Statistical Committee of the + Republic of Armenia:https://armstat.am/en/?nid=212 + The data is publicly available. +<_Sample size (HH)_> 7,788 +<_Sample size (IND)_> 29,662 +<_Sampling method_> A stratified two-stage probability sample design + with 14 domains as the primary strata and 18,000 + households as the SSU. +<_Geographic coverage_> All 11 regions/marzes. +<_Currency_> Armenian Dram +----------------------------------------------------------------------- +<_ICLS Version_> ICLS 13 +<_ISCED Version_> ISCED-2011 +<_ISCO Version_> ISCO 08 +<_OCCUP National_> NSCO +<_ISIC Version_> ISIC Rev.4 +<_INDUS National_> ISIC Rev.4 +----------------------------------------------------------------------- + +<_Version Control_> + +* Date: [YYYY-MM-DD] File: [As in Program name above] - [Description of changes] +* Date: [YYYY-MM-DD] File: [As in Program name above] - [Description of changes] +* Date: 2024-09-24 - Update vars educy, educat7 +* Date: 2024-10-09 - Include weight by quarter, correct contract variable + + + +-------------------------------------------------------------------------*/ + + +/*%%============================================================================================= + 1: Setting up of program environment, dataset +================================================================================================*/ + +*----------1.1: Initial commands------------------------------* + +clear +set more off +set mem 800m + +*----------1.2: Set directories------------------------------* + +* Define path sections +local server "Y:/GLD" +local country "ARM" +local year "2015" +local survey "LFS" +local vermast "V01" +local veralt "V03" + +* From the definitions, set path chunks +local level_1 "`country'_`year'_`survey'" +local level_2_mast "`level_1'_`vermast'_M" +local level_2_harm "`level_1'_`vermast'_M_`veralt'_A_GLD" + +* From chunks, define path_in, path_output folder +local path_in_stata "`server'/`country'/`level_1'/`level_2_mast'/Data/Stata" +local path_in_other "`server'/`country'/`level_1'/`level_2_mast'/Data/Original" +local path_output "`server'/`country'/`level_1'/`level_2_harm'/Data/Harmonized" + +* Define Output file name +local out_file "`level_2_harm'_ALL.dta" + + +*----------1.3: Database assembly------------------------------* + +* All steps necessary to merge datasets (if several) to have all elements needed to produce +* harmonized output in a single file + + use "`path_in_stata'/ARM_LFS_2015_raw.dta", clear + +/*%%============================================================================================= + 2: Survey & ID +================================================================================================*/ + +{ + +*<_countrycode_> + gen str4 countrycode="`country'" + label var countrycode "Country code" +* + + +*<_survname_> + gen survname="LFS" + label var survname "Survey acronym" +* + + +*<_survey_> + gen survey="LFS" + label var survey "Survey type" +* + + +*<_icls_v_> + gen icls_v="ICLS-13" + label var icls_v "ICLS version underlying questionnaire questions" +* + + +*<_isced_version_> + gen isced_version="isced_2011" + label var isced_version "Version of ISCED used for educat_isced" +* + + +*<_isco_version_> + gen isco_version="" + label var isco_version "Version of ISCO used" +* + + +*<_isic_version_> + gen isic_version="" + label var isic_version "Version of ISIC used" +* + + +*<_year_> + gen int year=`year' + label var year "Year of survey" +* + + +*<_vermast_> + gen str3 vermast="`vermast'" + label var vermast "Version of master data" +* + + +*<_veralt_> + gen str3 veralt="`veralt'" + label var veralt "Version of the alt/harmonized data" +* + + +*<_harmonization_> + gen harmonization="GLD" + label var harmonization "Type of harmonization" +* + + +*<_int_year_> + gen int_year=`year' + label var int_year "Year of the interview" +* + + +*<_int_month_> + gen int_month=A6_Month + label de lblint_month 1 "January" 2 "February" 3 "March" 4 "April" 5 "May" 6 "June" 7 "July" 8 "August" 9 "September" 10 "October" 11 "November" 12 "December" + label value int_month lblint_month + label var int_month "Month of the interview" +* + + +*<_hhid_> + tostring A1, gen(hid) format(%03.0f) + tostring A6_Month, gen(month) format(%03.0f) + egen hhid=concat(month hid) + label var hhid "Household id" +* + + +*<_pid_> + sort hhid B12 + bys hhid: gen memberid=_n + tostring memberid, gen(id_str) format(%02.0f) + egen pid=concat(hhid id_str), punct("-") + label var pid "Individual ID" +* + + +*<_weight_> + gen weight=Weights_year + label var weight "Household sampling weight" +* + + +*<_weight_m_> + gen weight_m = . + label var weight_m "Survey sampling weight to obtain national estimates for each month" +* + + +*<_weight_q_> + egen weight_q = rowtotal(Weights_1 Weights_2 Weights_3 Weights_4) + label var weight_q "Survey sampling weight to obtain national estimates for each quarter" +* + + +*<_psu_> + gen psu=. + label var psu "Primary sampling units" +* + + +*<_ssu_> + gen ssu=hhid + label var ssu "Secondary sampling units" +* + + +*<_strata_> + decode A3, gen(marzname) + decode A5, gen(urbanstat) + gen strata=marzname+" "+urbanstat + label var strata "Strata" +* + + +*<_wave_> + gen wave=. + replace wave=1 if inrange(int_month,1,3) + replace wave=2 if inrange(int_month,4,6) + replace wave=3 if inrange(int_month,7,9) + replace wave=4 if inrange(int_month,10,12) + label var wave "Survey wave" +* + + +*<_panel_> + gen panel="" + label var panel "Panel individual belongs to" +* + + +*<_visit_no_> + gen visit_no=. + label var visit_no "Visit number in panel" +* +} + + +/*%%============================================================================================= + 3: Geography +================================================================================================*/ + +{ + +*<_urban_> + gen urban=A5 + recode urban (2=0) + la de lblurban 1 "Urban" 0 "Rural" + label values urban lblurban + label var urban "Location is urban" +* + + +*<_subnatid1_> + gen subnatid1=A3 + tostring subnatid1, replace + replace subnatid1=subnatid1+" - "+marzname + + * Unite names to entire series + replace subnatid1 = "5 - Gegharkunik" if subnatid1 == "5 - Gegharquniq" + replace subnatid1 = "6 - Lori" if subnatid1 == "6 - Lory" + replace subnatid1 = "7 - Kotayk" if subnatid1 == "7 - Kotayq" + replace subnatid1 = "9 - Syunik" if subnatid1 == "9 - Syuniq" + + label var subnatid1 "Subnational ID at First Administrative Level" +* + + +*<_subnatid2_> + gen subnatid2=. + label var subnatid2 "Subnational ID at Second Administrative Level" +* + + +*<_subnatid3_> + gen subnatid3=. + label var subnatid3 "Subnational ID at Third Administrative Level" +* + + +*<_subnatidsurvey_> + gen subnatidsurvey=subnatid1+" "+urbanstat + label var subnatidsurvey "Administrative level at which survey is representative" +* + + +*<_subnatid1_prev_> + +/* <_subnatid1_prev_note_> +subnatid1_prev is coded as missing unless the classification used for subnatid1 has changed since the previous survey. + */ + + gen subnatid1_prev=. + label var subnatid1_prev "Classification used for subnatid1 from previous survey" +* + + +*<_subnatid2_prev_> + gen subnatid2_prev=. + label var subnatid2_prev "Classification used for subnatid2 from previous survey" +* + + +*<_subnatid3_prev_> + gen subnatid3_prev=. + label var subnatid3_prev "Classification used for subnatid3 from previous survey" +* + + +*<_gaul_adm1_code_> + gen gaul_adm1_code=. + label var gaul_adm1_code "Global Administrative Unit Layers (GAUL) Admin 1 code" +* + + +*<_gaul_adm2_code_> + gen gaul_adm2_code=. + label var gaul_adm2_code "Global Administrative Unit Layers (GAUL) Admin 2 code" +* + + +*<_gaul_adm3_code_> + gen gaul_adm3_code=. + label var gaul_adm3_code "Global Administrative Unit Layers (GAUL) Admin 3 code" +* + +} + +/*%%============================================================================================= + 4: Demography +================================================================================================*/ + +{ + +*<_hsize_> + bys hhid: egen hsize=max(memberid) + label var hsize "Household size" +* + + +*<_age_> + +/*<_age_note_> + +3 observations in the raw data set have negative (-1) age values. +They were coded as missing values in the harmonization. + +*<_age_note_>*/ + + gen age=Age + replace age=. if Age<0 + replace age=98 if age>98 & age!=. + label var age "Individual age" +* + + +*<_male_> + gen male=B11 + recode male 2=0 + label var male "Sex - Ind is male" + la de lblmale 1 "Male" 0 "Female" + label values male lblmale +* + + +*<_relationharm_> + +/*<_relationharm_note_> + +1 household (3 observations) in the raw data set does not have household head: 004318 + +During the harmonization, we did not assign household head to the household. +But users can assign household heads based on their relationship to the head and +other characteristics such as gender and age. + +*<_relationharm_note_>*/ + + gen byte relationharm=B12 + recode relationharm (6 9=3) (7 8=4) (10=5) (11=6) + label var relationharm "Relationship to the head of household - Harmonized" + la de lblrelationharm 1 "Head of household" 2 "Spouse" 3 "Children" 4 "Parents" 5 "Other relatives" 6 "Other and non-relatives" + label values relationharm lblrelationharm +*<_relationharm_> + + +*<_relationcs_> + gen relationcs=B12 + label var relationcs "Relationship to the head of household - Country original" +* + + +*<_marital_> + gen marital=B16 + recode marital (1=2) (2=1) (3=5) + label var marital "Marital status" + la de lblmarital 1 "Married" 2 "Never Married" 3 "Living together" 4 "Divorced/Separated" 5 "Widowed" + label values marital lblmarital +* + + +*<_eye_dsablty_> + gen eye_dsablty=. + la de lbleye_dsablty 1 "No" 2 "Yes-some" 3 "Yes-a lot" 4 "Cannot at all" + label values eye_dsablty lbleye_dsablty + label var eye_dsablty "Disability related to eyesight" +* + + +*<_hear_dsablty_> + gen hear_dsablty=. + la de lblhear_dsablty 1 "No" 2 "Yes-some" 3 "Yes-a lot" 4 "Cannot at all" + label values hear_dsablty lblhear_dsablty + label var hear_dsablty "Disability related to hearing" +* + + +*<_walk_dsablty_> + gen walk_dsablty=. + la de lblwalk_dsablty 1 "No" 2 "Yes-some" 3 "Yes-a lot" 4 "Cannot at all" + label values walk_dsablty lblwalk_dsablty + label var walk_dsablty "Disability related to walking or climbing stairs" +* + + +*<_conc_dsord_> + gen conc_dsord=. + la de lblconc_dsord 1 "No" 2 "Yes-some" 3 "Yes-a lot" 4 "Cannot at all" + label values conc_dsord lblconc_dsord + label var conc_dsord "Disability related to concentration or remembering" +* + + +*<_slfcre_dsablty_> + gen slfcre_dsablty=. + la de lblslfcre_dsablty 1 "No" 2 "Yes-some" 3 "Yes-a lot" 4 "Cannot at all" + label values slfcre_dsablty lblslfcre_dsablty + label var eye_dsablty "Disability related to selfcare" +* + + +*<_comm_dsablty_> + gen comm_dsablty=. + la de lblcomm_dsablty 1 "No" 2 "Yes-some" 3 "Yes-a lot" 4 "Cannot at all" + label values comm_dsablty lblcomm_dsablty + label var eye_dsablty "Disability related to communicating" +* + +} + + +/*%%============================================================================================= + 5: Migration +================================================================================================*/ + +{ +*<_migrated_mod_age_> + gen migrated_mod_age=. + label var migrated_mod_age "Migration module application age" +* + + +*<_migrated_ref_time_> + gen migrated_ref_time=. + label var migrated_ref_time "Reference time applied to migration questions (in years)" +* + + +*<_migrated_binary_> + gen migrated_binary=. + label de lblmigrated_binary 0 "No" 1 "Yes" + replace migrated_binary=. if age + +*<_migrated_years_> + gen migrated_years=. + replace migrated_years=. if migrated_binary!=1 + replace migrated_years=. if age + + +*<_migrated_from_urban_> + gen migrated_from_urban=. + replace migrated_from_urban=. if age + + +*<_migrated_from_cat_> + gen migrated_from_cat=. + replace migrated_from_cat=. if age + + +*<_migrated_from_code_> + gen migrated_from_code="" + replace migrated_from_code="" if age + + +*<_migrated_from_country_> + gen migrated_from_country="" + replace migrated_from_country="" if migrated_binary!=1 + replace migrated_from_country="" if age + + +*<_migrated_reason_> + gen migrated_reason=. + replace migrated_reason=. if migrated_binary!=1 + replace migrated_reason=. if age +} + + +/*%%============================================================================================= + 6: Education +================================================================================================*/ + + +{ +*<_ed_mod_age_> + gen byte ed_mod_age=6 + label var ed_mod_age "Education module application age" +* + + +*<_school_> + gen school=. + replace school=. if age + + +*<_literacy_> + gen byte literacy=. + replace literacy=0 if B15==1 + replace literacy=1 if inrange(B15,2,9) + replace literacy=. if age + + +*<_educy_> + gen byte educy=. + replace educy = 0 if B15 == 1 | B15 == 2 + replace educy = 4 if B15 == 3 + replace educy = 9 if B15 == 4 + replace educy = 12 if B15 == 5 + replace educy = 11 if B15 == 6 + replace educy = 15 if B15 == 7 + replace educy = 16 if B15 == 8 + replace educy = 20 if B15 == 9 + replace educy=. if ageage & !mi(educy) & !mi(age) + label var educy "Years of education" +* + + +*<_educat7_> + gen byte educat7= B15 + recode educat7 (6=5) (7=6) (8/9=7) + replace educat7=. if age + + +*<_educat5_> + gen byte educat5=educat7 + recode educat5 (4=3) (5=4) (6 7=5) + replace educat5=. if age + + +*<_educat4_> + gen byte educat4=educat5 + replace educat4=. if age + + +*<_educat_orig_> + gen educat_orig=B15 + label var educat_orig "Original survey education code" +* + + +*<_educat_isced_> + gen educat_isced=. + label var educat_isced "ISCED standardised level of education" +* + + +*<_educat_isced_v_> + gen educat_isced_v="ISCED-2011" + label var educat_isced_v "Version of the ISCED used" +* + +*----------6.1: Education cleanup------------------------------* + +*<_% Correction min age_> + +** Drop info for cases under the age for which questions to be asked (do not need a variable for this) +local ed_var school literacy educy educat7 educat5 educat4 educat_isced +foreach v of local ed_var { + replace `v'=. if ( age < ed_mod_age & !missing(age) ) +} +replace educat_isced_v="." if ( age < ed_mod_age & !missing(age) ) +* + +} + +/*%%============================================================================================= + 7: Training +================================================================================================*/ + +{ + +*<_vocational_> + gen vocational=. + la de vocationallbl 1 "Yes" 0 "No" + la values vocational vocationallbl + label var vocational "Ever received vocational training" +* + + +*<_vocational_type_> + gen vocational_type=. + label de lblvocational_type 1 "Inside Enterprise" 2 "External" + label values vocational_type lblvocational_type + label var vocational_type "Type of vocational training" +* + + +*<_vocational_length_l_> + gen vocational_length_l=. + replace vocational_length_l=. if vocational!=1 + label var vocational_length_l "Length of training in months, lower limit" +* + + +*<_vocational_length_u_> + gen vocational_length_u=. + replace vocational_length_u=. if vocational!=1 + label var vocational_length_u "Length of training in months, upper limit" +* + + +*<_vocational_field_orig_> + gen vocational_field_orig=. + replace vocational_field_orig=. if vocational!=1 + label var vocational_field_orig "Original field of training information" +* + + +*<_vocational_financed_> + gen vocational_financed=. + label de lblvocational_financed 1 "Employer" 2 "Government" 3 "Mixed Employer/Government" 4 "Own funds" 5 "Other" + label var vocational_financed "How training was financed" +* + +} + +/*%%============================================================================================= + 8: Labour +================================================================================================*/ + +*<_minlaborage_> + +/*<_minlaborage_note_> + +The age range for the labor section is 15-75. + +*<_minlaborage_note_>*/ + + gen byte minlaborage=15 + label var minlaborage "Labor module application age" +* + + +*----------8.1: 7 day reference overall------------------------------* + +{ +*<_lstatus_> + +/*<_lstatus_note> + +According to the national definition of Armenia, the economically inavtive population +includes + +1)full-time pupils and students +2)housekeepers +3)pensioners +4)other jobless peope including conscripts + +And the economically inavtive population also needs to be within the age range of +15 and 75. +*<_lstatus_note>*/ + + gen byte lstatus=. + replace lstatus=1 if G1==1|inrange(G3,1,5)|inrange(G4,1,2) + replace lstatus=2 if lstatus==.&inrange(Z57,1,2) + replace lstatus=3 if !mi(Z49_4groups)&lstatus==. + replace lstatus=. if !inrange(age,15,75) + label var lstatus "Labor status" + la de lbllstatus 1 "Employed" 2 "Unemployed" 3 "Non-LF" + label values lstatus lbllstatus +* + + +*<_potential_lf_> + +/*<_potential_lf_note_> +Note: var "potential_lf" only takes value if the respondent is not in labor force. (lstatus==3) + +"potential_lf"=1 if the person is +1)available but not searching or inrange(E45,1,3) & (Z57==2) +2)searching but not immediately available to work or Z57==1 & inlist(E45,4,6) + +*/ + + gen potential_lf=. + replace potential_lf=1 if [inrange(E45,1,3) & (Z57==2)] | [Z57==1 & inlist(E45,4,6)] + replace potential_lf=0 if [inrange(E45,1,3) & (Z57==1)] | [Z57==1 & inrange(E45,1,3)] + replace potential_lf=. if age75&!mi(age)] + replace potential_lf=. if lstatus!=3 + label var potential_lf "Potential labour force status" + la de lblpotential_lf 0 "No" 1 "Yes" + label values potential_lf lblpotential_lf +* + + +*<_underemployment_> + gen byte underemployment=E41 + replace underemployment=1 if inrange(E41,1,3) + replace underemployment=0 if E41==4 + replace underemployment=. if age75&!mi(age)] + replace underemployment=. if lstatus!=1 + label var underemployment "Underemployment status" + la de lblunderemployment 0 "No" 1 "Yes" + label values underemployment lblunderemployment +* + + +*<_nlfreason_> + gen byte nlfreason=Z49_4groups + recode nlfreason (4=5) + replace nlfreason=. if age75&!mi(age)] + replace nlfreason=. if lstatus!=3 + label var nlfreason "Reason not in the labor force" + la de lblnlfreason 1 "Student" 2 "Housekeeper" 3 "Retired" 4 "Disabled" 5 "Other" + label values nlfreason lblnlfreason +* + + +*<_unempldur_l_> + gen byte unempldur_l=Z52 + recode unempldur_l (1=0) (2=3) (3=12) (4=24) (5=36) + replace unempldur_l=. if age75&!mi(age)] + replace unempldur_l=. if lstatus!=2 + label var unempldur_l "Unemployment duration (months) lower bracket" +* + + +*<_unempldur_u_> + gen byte unempldur_u=Z52 + recode unempldur_u (1=3) (2=12) (3=24) (4=36) (5=.) + replace unempldur_u=. if age75&!mi(age)] + replace unempldur_u=. if lstatus!=2 + label var unempldur_u "Unemployment duration (months) upper bracket" +* +} + + +*----------8.2: 7 day reference main job------------------------------* + + +{ +*<_empstat_> + gen byte empstat=D8 + recode empstat (2 7=1) (5=4) (6=2) (8=5) + replace empstat=. if lstatus!=1|age + + +*<_ocusec_> + gen byte ocusec=D11 + recode ocusec (3 4=2) + replace ocusec=. if lstatus!=1|age + + +*<_industry_orig_> + gen industry_orig=D6_21groups + replace industry_orig=. if lstatus!=1 + label var industry_orig "Original survey industry code, main job 7 day recall" +* + + +*<_industrycat_isic_> + gen industrycat_isic="" +quietly +{ + replace industrycat_isic="A" if D6_21groups==1 + replace industrycat_isic="B" if D6_21groups==2 + replace industrycat_isic="C" if D6_21groups==3 + replace industrycat_isic="D" if D6_21groups==4 + replace industrycat_isic="E" if D6_21groups==5 + replace industrycat_isic="F" if D6_21groups==6 + replace industrycat_isic="G" if D6_21groups==7 + replace industrycat_isic="H" if D6_21groups==8 + replace industrycat_isic="I" if D6_21groups==9 + replace industrycat_isic="J" if D6_21groups==10 + replace industrycat_isic="K" if D6_21groups==11 + replace industrycat_isic="L" if D6_21groups==12 + replace industrycat_isic="M" if D6_21groups==13 + replace industrycat_isic="N" if D6_21groups==14 + replace industrycat_isic="O" if D6_21groups==15 + replace industrycat_isic="P" if D6_21groups==16 + replace industrycat_isic="Q" if D6_21groups==17 + replace industrycat_isic="R" if D6_21groups==18 + replace industrycat_isic="S" if D6_21groups==19 + replace industrycat_isic="T" if D6_21groups==20 + replace industrycat_isic="U" if D6_21groups==21 +} + + replace industrycat_isic="" if industrycat_isic=="."|lstatus!=1 + label var industrycat_isic "ISIC code of primary job 7 day recall" +* + + +*<_industrycat10_> + gen industrycat10=D6_21groups + recode industrycat10 (5=4) (6=5) (7 9=6) (8 10=7) (11/14=8) (15=9) (16/21=10) + replace industrycat10=. if lstatus!=1 + label var industrycat10 "1 digit industry classification, primary job 7 day recall" + la de lblindustrycat10 1 "Agriculture" 2 "Mining" 3 "Manufacturing" 4 "Public utilities" 5 "Construction" 6 "Commerce" 7 "Transport and Comnunications" 8 "Financial and Business Services" 9 "Public Administration" 10 "Other Services, Unspecified" + label values industrycat10 lblindustrycat10 +* + + +*<_industrycat4_> + gen byte industrycat4=industrycat10 + recode industrycat4 (3/5=2)(6/9=3)(10=4) + label var industrycat4 "1 digit industry classification (Broad Economic Activities), primary job 7 day recall" + la de lblindustrycat4 1 "Agriculture" 2 "Industry" 3 "Services" 4 "Other" + label values industrycat4 lblindustrycat4 +* + + +*<_occup_orig_> + gen occup_orig=D5_9group + replace occup_orig=. if lstatus!=1|[age>75&!mi(age)] + label var occup_orig "Original occupation record primary job 7 day recall" +* + + +*<_occup_isco_> + gen occup_isco="" + replace occup_isco="" if lstatus!=1 | occup_isco=="." + label var occup_isco "ISCO code of primary job 7 day recall" +* + + +*<_occup_skill_> + gen occup_skill=D5_9group + replace occup_skill=1 if D5_9group==9 + replace occup_skill=2 if inrange(D5_9group, 4, 8) + replace occup_skill=3 if inrange(D5_9group, 1, 3) + replace occup_skill=. if lstatus!=1 + la de lblskill 1 "Low skill" 2 "Medium skill" 3 "High skill" + label values occup_skill lblskill + label var occup_skill "Skill based on ISCO standard primary job 7 day recall" +* + + +*<_occup_> + gen occup=D5_9group + replace occup=. if lstatus!=1|[age>75&!mi(age)] + label var occup "1 digit occupational classification, primary job 7 day recall" + la de lbloccup 1 "Managers" 2 "Professionals" 3 "Technicians" 4 "Clerks" 5 "Service and market sales workers" 6 "Skilled agricultural" 7 "Craft workers" 8 "Machine operators" 9 "Elementary occupations" 10 "Armed forces" 99 "Others" + label values occup lbloccup +* + + +*<_wage_no_compen_> + +/*<_wage_no_compen_note_> + +The wage questions in the questionnare are organized into to parts: the first part +asks for the specific number of income if the given respondent could recall and was +willing to answer; the second part provides different categories of income range +if the given respondent could not recall or was not willing to answer the first part. + +The general logic here is to impute wage values for people who only answered an income +range. We used industry, occupation, income categories and gender to estimate their +specific income values. + +15.16% of total non-missing wage values were imputed using this method. + +*<_wage_no_compen_note_>*/ + + * Overall --> wage info (here the variable, for us it should be wage_no_compen) + * to missing if value is 0. + gen wage14=D14_1+D14_2 + replace wage14=. if wage14==0 + + * First replace outliers by + winsor2 wage14, suffix(_w) cuts(1 99) + + * Create salary categories based on winsor values + gen salary_cat=. + replace salary_cat=1 if inrange(wage14_w, 1, 45000) + replace salary_cat=2 if wage14_w==45000 + replace salary_cat=3 if inrange(wage14_w, 45001, 90000) + replace salary_cat=4 if inrange(wage14_w, 90000, 180000) + replace salary_cat=5 if inrange(wage14_w, 180000, 360000) + replace salary_cat=6 if inrange(wage14_w, 360000, 500000) + replace salary_cat=7 if inrange(wage14_w, 500000, 700000) + replace salary_cat=8 if inrange(wage14_w, 700000, 3450000) + + * Preserve to collapse, so we can merge the info in + preserve + + * Collpase by industry, sex, and salary categories + collapse (mean)wage14_w[iw=weight], by(industrycat10 occup male urban salary_cat) + drop if mi(salary_cat) + + * Rename variable, otherwise when merging in, master version of an equally name one will be kept + rename wage14_w wage_group_estimate + + * Rename salary_cat to D15 since this is what we want the info to latch on to + rename salary_cat D15 + tempfile salary_helper + save "`salary_helper'" + + * Restore, merge in + restore + merge m:1 industrycat10 occup male urban D15 using "`salary_helper'", keep(matched master) nogen + + * Create wage variable + gen wage_no_compen=. + + * Fill it first with values that are accurate + replace wage_no_compen=wage14 if !mi(wage14)&mi(D15) + + * Now add the categorised means + replace wage_no_compen=wage_group_estimate if inrange(D15,1,8)&!mi(wage_group_estimate) + + * Keep only for employed employees, label + replace wage_no_compen=. if lstatus!=1|empstat==2 + label var wage_no_compen "Last wage payment primary job 7 day recall" + +* + + +*<_unitwage_> + gen byte unitwage=D16 + recode unitwage (4=5) (5=7) (6=8) (7=10) + replace unitwage=. if lstatus!=1 | empstat==2 + label var unitwage "Last wages' time unit primary job 7 day recall" + la de lblunitwage 1 "Daily" 2 "Weekly" 3 "Every two weeks" 4 "Bimonthly" 5 "Monthly" 6 "Trimester" 7 "Biannual" 8 "Annually" 9 "Hourly" 10 "Other" + label values unitwage lblunitwage +* + + +*<_whours_> + gen whours=E39_1 + replace whours=. if lstatus!=1|E39_1==0 + label var whours "Hours of work in last week primary job 7 day recall" +* + + +*<_wmonths_> + gen wmonths=. + label var wmonths "Months of work in past 12 months primary job 7 day recall" +* + + +*<_wage_total_> + gen wage_total=. + label var wage_total "Annualized total wage primary job 7 day recall" +* + + +*<_contract_> + +/*<_contract_note_> + +There is no separate contract question in the questionnaire. +This contract variable was coded based on employment status question which asks +wether an employed respondent had a contract or not. + +*<_contract_note_>*/ + + gen byte contract = . + replace contract = (D8 == 1) + replace contract=. if lstatus != 1 + label var contract "Employment has contract primary job 7 day recall" + la de lblcontract 0 "Without contract" 1 "With contract" + label values contract lblcontract +* + + +*<_healthins_> + gen byte healthins=. + replace healthins=1 if D9_6==1 + replace healthins=0 if D9_6==2 + replace healthins=. if lstatus!=1 + label var healthins "Employment has health insurance primary job 7 day recall" + la de lblhealthins 0 "Without health insurance" 1 "With health insurance" + label values healthins lblhealthins +* + + +*<_socialsec_> + gen byte socialsec=. + replace socialsec=. if lstatus!=1 + label var socialsec "Employment has social security insurance primary job 7 day recall" + la de lblsocialsec 1 "With social security" 0 "Without social secturity" + label values socialsec lblsocialsec +* + + +*<_union_> + gen byte union=. + replace union=1 if D23==1 + replace union=0 if D23==2 + replace union=. if lstatus!=1 + label var union "Union membership at primary job 7 day recall" + la de lblunion 0 "Not union member" 1 "Union member" + label values union lblunion +* + + +*<_firmsize_l_> + gen byte firmsize_l=. + replace firmsize_l=. if lstatus!=1 + label var firmsize_l "Firm size (lower bracket) primary job 7 day recall" +* + + +*<_firmsize_u_> + gen byte firmsize_u=. + replace firmsize_u=. if lstatus!=1 + label var firmsize_u "Firm size (upper bracket) primary job 7 day recall" +* + +} + + +*----------8.3: 7 day reference secondary job------------------------------* +* Since labels are the same as main job, values are labelled using main job labels + +{ +*<_empstat_2_> + gen byte empstat_2=E27 + recode empstat_2 (2 7=1) (5=4) (6=2) + replace empstat_2=. if lstatus!=1|E24!=1 + label var empstat_2 "Employment status during past week secondary job 7 day recall" + la de lblempstat_2 1 "Paid employee" 2 "Non-paid employee" 3 "Employer" 4 "Self-employed" 5 "Other, workers not classifiable by status" + label values empstat_2 lblempstat +* + + +*<_ocusec_2_> + gen byte ocusec_2=E29 + recode ocusec_2 (3 4=2) + replace ocusec_2=. if lstatus!=1|E24!=1 + label var ocusec_2 "Sector of activity secondary job 7 day recall" + la de lblocusec_2 1 "Public Sector, Central Government, Army" 2 "Private, NGO" 3 "State owned" 4 "Public or State-owned, but cannot distinguish" + label values ocusec_2 lblocusec_2 +* + + +*<_industry_orig_2_> + gen industry_orig_2=E26_21group + replace industry_orig_2=. if lstatus!=1|E24!=1 + label var industry_orig_2 "Original survey industry code, secondary job 7 day recall" +* + + +*<_industrycat_isic_2_> + gen industrycat_isic_2="" +quietly +{ + replace industrycat_isic_2="A" if E26_21group==1 + replace industrycat_isic_2="B" if E26_21group==2 + replace industrycat_isic_2="C" if E26_21group==3 + replace industrycat_isic_2="D" if E26_21group==4 + replace industrycat_isic_2="E" if E26_21group==5 + replace industrycat_isic_2="F" if E26_21group==6 + replace industrycat_isic_2="G" if E26_21group==7 + replace industrycat_isic_2="H" if E26_21group==8 + replace industrycat_isic_2="I" if E26_21group==9 + replace industrycat_isic_2="J" if E26_21group==10 + replace industrycat_isic_2="K" if E26_21group==11 + replace industrycat_isic_2="L" if E26_21group==12 + replace industrycat_isic_2="M" if E26_21group==13 + replace industrycat_isic_2="N" if E26_21group==14 + replace industrycat_isic_2="O" if E26_21group==15 + replace industrycat_isic_2="P" if E26_21group==16 + replace industrycat_isic_2="Q" if E26_21group==17 + replace industrycat_isic_2="R" if E26_21group==18 + replace industrycat_isic_2="S" if E26_21group==19 + replace industrycat_isic_2="T" if E26_21group==20 + replace industrycat_isic_2="U" if E26_21group==21 +} + + replace industrycat_isic_2="" if industrycat_isic_2=="."|E24!=1 + label var industrycat_isic_2 "ISIC code of secondary job 7 day recall" +* + + +*<_industrycat10_2_> + gen industrycat10_2=E26_21group + recode industrycat10_2 (5=4) (6=5) (7 9=6) (8 10=7) (11/14=8) (15=9) (16/21=10) + replace industrycat10_2=. if lstatus!=1|E24!=1 + label var industrycat10_2 "1 digit industry classification, secondary job 7 day recall" + label values industrycat10_2 lblindustrycat10 +* + + +*<_industrycat4_2_> + gen byte industrycat4_2=industrycat10_2 + recode industrycat4_2 (3/5=2)(6/9=3)(10=4) + label var industrycat4_2 "1 digit industry classification (Broad Economic Activities), secondary job 7 day recall" + label values industrycat4_2 lblindustrycat4 +* + + +*<_occup_orig_2_> + gen occup_orig_2=E25_9group + replace occup_orig_2=. if lstatus!=1|E24!=1 + label var occup_orig_2 "Original occupation record secondary job 7 day recall" +* + + +*<_occup_isco_2_> + gen occup_isco_2="" + replace occup_isco_2="" if lstatus!=1 | occup_isco_2=="."|E24!=1 + label var occup_isco_2 "ISCO code of secondary job 7 day recall" +* + + +*<_occup_skill_2_> + gen occup_skill_2=E25_9group + replace occup_skill_2=1 if E25_9group==9 + replace occup_skill_2=2 if inrange(E25_9group,4,8) + replace occup_skill_2=3 if inrange(E25_9group,1,3) + replace occup_skill_2=. if E25_9group==0|lstatus!=1|E24!=1 + label var occup_skill_2 "Skill based on ISCO standard secondary job 7 day recall" +* + + +*<_occup_2_> + gen occup_2=E25_9group + replace occup_2=. if lstatus!=1|E24!=1 + label var occup_2 "1 digit occupational classification secondary job 7 day recall" + label values occup_2 lbloccup +* + + +*<_wage_no_compen_2_> + + gen wage32=E32_1+E32_2 + replace wage32=. if wage32==0 + + * First replace outliers by + winsor2 wage32, suffix(_w) cuts(1 99) + + * Create salary categories based on winsor values + gen salary_cat2=. + replace salary_cat2=1 if inrange(wage32_w, 1, 45000) + replace salary_cat2=2 if wage32_w==45000 + replace salary_cat2=3 if inrange(wage32_w, 45001, 90000) + replace salary_cat2=4 if inrange(wage32_w, 90000, 180000) + replace salary_cat2=5 if inrange(wage32_w, 180000, 360000) + + * Preserve to collapse, so we can merge the info in + preserve + + * Collpase by industry, sex, and salary categories + collapse (mean)wage32_w[iw=weight], by(industrycat10_2 occup_2 male urban salary_cat2) + + * Rename variable, otherwise when merging in, master version of an equally name one will be kept + rename wage32_w wage_group_estimate2 + + * Rename salary_cat to D15 since this is what we want the info to latch on to + rename salary_cat2 E33 + tempfile salary_helper2 + save "`salary_helper2'" + + * Restore, merge in + restore + merge m:1 industrycat10_2 occup_2 male urban E33 using "`salary_helper2'", keep(matched master) nogen + + * Create wage variable + gen wage_no_compen_2=. + + * Fill it first with values that are accurate + replace wage_no_compen_2=wage32 if !mi(wage32)&mi(E33) + + * Now add the categorised means + replace wage_no_compen_2=wage_group_estimate2 if inrange(E33,1,5)&!mi(wage_group_estimate2) + + * Keep only for employed employees, label + replace wage_no_compen_2=. if E24!=1|empstat_2==2 + label var wage_no_compen_2 "Last wage payment secondary job 7 day recall" +* + + +*<_unitwage_2_> + gen byte unitwage_2=E34 + recode unitwage_2 (4=5) (5=7) (6=8) (7=10) + replace unitwage_2=. if lstatus!=1|E24!=1 + label var unitwage_2 "Last wages' time unit secondary job 7 day recall" + label values unitwage_2 lblunitwage +* + + +*<_whours_2_> + gen whours_2=E38_2 + replace whours_2=. if E38_2==0|E24!=1 + label var whours_2 "Hours of work in last week secondary job 7 day recall" +* + + +*<_wmonths_2_> + gen wmonths_2=. + label var wmonths_2 "Months of work in past 12 months secondary job 7 day recall" +* + + +*<_wage_total_2_> + gen wage_total_2=. + label var wage_total_2 "Annualized total wage secondary job 7 day recall" +* + + +*<_firmsize_l_2_> + gen byte firmsize_l_2=. + label var firmsize_l_2 "Firm size (lower bracket) secondary job 7 day recall" +* + + +*<_firmsize_u_2_> + gen byte firmsize_u_2=. + label var firmsize_u_2 "Firm size (upper bracket) secondary job 7 day recall" +* + +} + +*----------8.4: 7 day reference additional jobs------------------------------* + +*<_t_hours_others_> + gen t_hours_others=. + label var t_hours_others "Annualized hours worked in all but primary and secondary jobs 7 day recall" +* + + +*<_t_wage_nocompen_others_> + gen t_wage_nocompen_others=. + label var t_wage_nocompen_others "Annualized wage in all but primary & secondary jobs excl. bonuses, etc. 7 day recall" +* + + +*<_t_wage_others_> + gen t_wage_others=. + label var t_wage_others "Annualized wage in all but primary and secondary jobs (12-mon ref period)" +* + + +*----------8.5: 7 day reference total summary------------------------------* + + +*<_t_hours_total_> + gen t_hours_total=. + label var t_hours_total "Annualized hours worked in all jobs 7 day recall" +* + + +*<_t_wage_nocompen_total_> + gen t_wage_nocompen_total=. + label var t_wage_nocompen_total "Annualized wage in all jobs excl. bonuses, etc. 7 day recall" +* + + +*<_t_wage_total_> + gen t_wage_total=. + label var t_wage_total "Annualized total wage for all jobs 7 day recall" +* + + +*----------8.6: 12 month reference overall------------------------------* + +{ +*<_lstatus_year_> + gen byte lstatus_year=. + replace lstatus_year=. if age + + +*<_potential_lf_year_> + gen byte potential_lf_year=. + replace potential_lf_year=. if age + + +*<_underemployment_year_> + gen byte underemployment_year=. + replace underemployment_year=. if age + + +*<_nlfreason_year_> + gen byte nlfreason_year=. + label var nlfreason_year "Reason not in the labor force" + la de lblnlfreason_year 1 "Student" 2 "Housekeeper" 3 "Retired" 4 "Disable" 5 "Other" + label values nlfreason_year lblnlfreason_year +* + + +*<_unempldur_l_year_> + gen byte unempldur_l_year=. + label var unempldur_l_year "Unemployment duration (months) lower bracket" +* + + +*<_unempldur_u_year_> + gen byte unempldur_u_year=. + label var unempldur_u_year "Unemployment duration (months) upper bracket" +* + +} + +*----------8.7: 12 month reference main job------------------------------* + +{ +*<_empstat_year_> + gen byte empstat_year=. + label var empstat_year "Employment status during past week primary job 12 month recall" + la de lblempstat_year 1 "Paid employee" 2 "Non-paid employee" 3 "Employer" 4 "Self-employed" 5 "Other, workers not classifiable by status" + label values empstat_year lblempstat_year +* + + +*<_ocusec_year_> + gen byte ocusec_year=. + label var ocusec_year "Sector of activity primary job 12 day recall" + la de lblocusec_year 1 "Public Sector, Central Government, Army" 2 "Private, NGO" 3 "State owned" 4 "Public or State-owned, but cannot distinguish" + label values ocusec_year lblocusec_year +* + + +*<_industry_orig_year_> + gen industry_orig_year=. + label var industry_orig_year "Original industry record main job 12 month recall" +* + + +*<_industrycat_isic_year_> + gen industrycat_isic_year="" + replace industrycat_isic_year="" if industrycat_isic_year=="." + label var industrycat_isic_year "ISIC code of primary job 12 month recall" +* + + +*<_industrycat10_year_> + gen byte industrycat10_year=. + label var industrycat10_year "1 digit industry classification, primary job 12 month recall" + la de lblindustrycat10_year 1 "Agriculture" 2 "Mining" 3 "Manufacturing" 4 "Public utilities" 5 "Construction" 6 "Commerce" 7 "Transport and Comnunications" 8 "Financial and Business Services" 9 "Public Administration" 10 "Other Services, Unspecified" + label values industrycat10_year lblindustrycat10_year +* + + +*<_industrycat4_year_> + gen byte industrycat4_year=industrycat10_year + recode industrycat4_year (1=1)(2 3 4 5 =2)(6 7 8 9=3)(10=4) + label var industrycat4_year "1 digit industry classification (Broad Economic Activities), primary job 12 month recall" + la de lblindustrycat4_year 1 "Agriculture" 2 "Industry" 3 "Services" 4 "Other" + label values industrycat4_year lblindustrycat4_year +* + + +*<_occup_orig_year_> + gen occup_orig_year=. + label var occup_orig_year "Original occupation record primary job 12 month recall" +* + + +*<_occup_isco_year_> + gen str4 occup_isco_year="" + label var occup_isco_year "ISCO code of primary job 12 month recall" +* + + +*<_occup_skill_year_> + gen skill_level_year=substr(occup_isco_year,1,1) + destring skill_level_year, replace + gen occup_skill_year=. + replace occup_skill_year=1 if skill_level_year==9 + replace occup_skill_year=2 if inrange(skill_level_year,4,8) + replace occup_skill_year=3 if inrange(skill_level_year,1,3) + replace occup_skill_year=. if skill_level_year==0 + label var occup_skill_year "Skill based on ISCO standard primary job 12 month recall" +* + + +*<_occup_year_> + gen byte occup_year=. + label var occup_year "1 digit occupational classification, primary job 12 month recall" + la de lbloccup_year 1 "Managers" 2 "Professionals" 3 "Technicians" 4 "Clerks" 5 "Service and market sales workers" 6 "Skilled agricultural" 7 "Craft workers" 8 "Machine operators" 9 "Elementary occupations" 10 "Armed forces" 99 "Others" + label values occup_year lbloccup_year +* + + +*<_wage_no_compen_year_> + gen double wage_no_compen_year=. + label var wage_no_compen_year "Last wage payment primary job 12 month recall" +* + + +*<_unitwage_year_> + gen byte unitwage_year=. + label var unitwage_year "Last wages' time unit primary job 12 month recall" + la de lblunitwage_year 1 "Daily" 2 "Weekly" 3 "Every two weeks" 4 "Bimonthly" 5 "Monthly" 6 "Trimester" 7 "Biannual" 8 "Annually" 9 "Hourly" 10 "Other" + label values unitwage_year lblunitwage_year +* + + +*<_whours_year_> + gen whours_year=. + label var whours_year "Hours of work in last week primary job 12 month recall" +* + + +*<_wmonths_year_> + gen wmonths_year=. + label var wmonths_year "Months of work in past 12 months primary job 12 month recall" +* + + +*<_wage_total_year_> + gen wage_total_year=. + label var wage_total_year "Annualized total wage primary job 12 month recall" +* + + +*<_contract_year_> + gen byte contract_year=. + label var contract_year "Employment has contract primary job 12 month recall" + la de lblcontract_year 0 "Without contract" 1 "With contract" + label values contract_year lblcontract_year +* + + +*<_healthins_year_> + gen byte healthins_year=. + label var healthins_year "Employment has health insurance primary job 12 month recall" + la de lblhealthins_year 0 "Without health insurance" 1 "With health insurance" + label values healthins_year lblhealthins_year +* + + +*<_socialsec_year_> + gen byte socialsec_year=. + label var socialsec_year "Employment has social security insurance primary job 7 day recall" + la de lblsocialsec_year 1 "With social security" 0 "Without social secturity" + label values socialsec_year lblsocialsec_year +* + + +*<_union_year_> + gen byte union_year=. + label var union_year "Union membership at primary job 12 month recall" + la de lblunion_year 0 "Not union member" 1 "Union member" + label values union_year lblunion_year +* + + +*<_firmsize_l_year_> + gen byte firmsize_l_year=. + label var firmsize_l_year "Firm size (lower bracket) primary job 12 month recall" +* + + +*<_firmsize_u_year_> + gen byte firmsize_u_year=. + label var firmsize_u_year "Firm size (upper bracket) primary job 12 month recall" +* + +} + + +*----------8.8: 12 month reference secondary job------------------------------* + +{ + +*<_empstat_2_year_> + gen byte empstat_2_year=. + label var empstat_2_year "Employment status during past week secondary job 12 month recall" + label values empstat_2_year lblempstat_year +* + + +*<_ocusec_2_year_> + gen byte ocusec_2_year=. + label var ocusec_2_year "Sector of activity secondary job 12 day recall" + la de lblocusec_2_year 1 "Public Sector, Central Government, Army" 2 "Private, NGO" 3 "State owned" 4 "Public or State-owned, but cannot distinguish" + label values ocusec_2_year lblocusec_2_year +* + + + +*<_industry_orig_2_year_> + gen industry_orig_2_year=. + label var industry_orig_2_year "Original survey industry code, secondary job 12 month recall" +* + + + +*<_industrycat_isic_2_year_> + gen industrycat_isic_2_year=. + label var industrycat_isic_2_year "ISIC code of secondary job 12 month recall" +* + + +*<_industrycat10_2_year_> + gen byte industrycat10_2_year=. + label var industrycat10_2_year "1 digit industry classification, secondary job 12 month recall" + label values industrycat10_2_year lblindustrycat10_year +* + + +*<_industrycat4_2_year_> + gen byte industrycat4_2_year=industrycat10_2_year + recode industrycat4_2_year (1=1)(2 3 4 5 =2)(6 7 8 9=3)(10=4) + label var industrycat4_2_year "1 digit industry classification (Broad Economic Activities), secondary job 12 month recall" + label values industrycat4_2_year lblindustrycat4_year +* + + +*<_occup_orig_2_year_> + gen occup_orig_2_year=. + label var occup_orig_2_year "Original occupation record secondary job 12 month recall" +* + + +*<_occup_isco_2_year_> + gen occup_isco_2_year=. + label var occup_isco_2_year "ISCO code of secondary job 12 month recall" +* + + +*<_occup_skill_2_year_> + gen occup_skill_2_year=. + label var occup_skill_2_year "Skill based on ISCO standard secondary job 12 month recall" +* + + +*<_occup_2_year_> + gen byte occup_2_year=. + label var occup_2_year "1 digit occupational classification, secondary job 12 month recall" + label values occup_2_year lbloccup_year +* + + +*<_wage_no_compen_2_year_> + gen double wage_no_compen_2_year=. + label var wage_no_compen_2_year "Last wage payment secondary job 12 month recall" +* + + +*<_unitwage_2_year_> + gen byte unitwage_2_year=. + label var unitwage_2_year "Last wages' time unit secondary job 12 month recall" + label values unitwage_2_year lblunitwage_year +* + + +*<_whours_2_year_> + gen whours_2_year=. + label var whours_2_year "Hours of work in last week secondary job 12 month recall" +* + + +*<_wmonths_2_year_> + gen wmonths_2_year=. + label var wmonths_2_year "Months of work in past 12 months secondary job 12 month recall" +* + + +*<_wage_total_2_year_> + gen wage_total_2_year=. + label var wage_total_2_year "Annualized total wage secondary job 12 month recall" +* + + +*<_firmsize_l_2_year_> + gen byte firmsize_l_2_year=. + label var firmsize_l_2_year "Firm size (lower bracket) secondary job 12 month recall" +* + + +*<_firmsize_u_2_year_> + gen byte firmsize_u_2_year=. + label var firmsize_u_2_year "Firm size (upper bracket) secondary job 12 month recall" +* + +} + + +*----------8.9: 12 month reference additional jobs------------------------------* + + +*<_t_hours_others_year_> + gen t_hours_others_year=. + label var t_hours_others_year "Annualized hours worked in all but primary and secondary jobs 12 month recall" +* + + +*<_t_wage_nocompen_others_year_> + gen t_wage_nocompen_others_year=. + label var t_wage_nocompen_others_year "Annualized wage in all but primary & secondary jobs excl. bonuses, etc. 12 month recall)" +* + + +*<_t_wage_others_year_> + gen t_wage_others_year=. + label var t_wage_others_year "Annualized wage in all but primary and secondary jobs 12 month recall" +* + + +*----------8.10: 12 month total summary------------------------------* + + +*<_t_hours_total_year_> + gen t_hours_total_year=. + label var t_hours_total_year "Annualized hours worked in all jobs 12 month month recall" +* + + +*<_t_wage_nocompen_total_year_> + gen t_wage_nocompen_total_year=. + label var t_wage_nocompen_total_year "Annualized wage in all jobs excl. bonuses, etc. 12 month recall" +* + + +*<_t_wage_total_year_> + gen t_wage_total_year=. + label var t_wage_total_year "Annualized total wage for all jobs 12 month recall" +* + + +*----------8.11: Overall across reference periods------------------------------* + + +*<_njobs_> + gen njobs=. + replace njobs=1 if lstatus==1&E24!=1 + replace njobs=2 if lstatus==1&E24==1 + replace njobs=. if lstatus!=1 + label var njobs "Total number of jobs" +* + + +*<_t_hours_annual_> + gen t_hours_annual=. + label var t_hours_annual "Total hours worked in all jobs in the previous 12 months" +* + + +*<_linc_nc_> + gen linc_nc=. + label var linc_nc "Total annual wage income in all jobs, excl. bonuses, etc." +* + + +*<_laborincome_> + gen laborincome=. + label var laborincome "Total annual individual labor income in all jobs, incl. bonuses, etc." +* + + +*----------8.13: Labour cleanup------------------------------* + +{ +*<_% Correction min age_> + +** Drop info for cases under the age for which questions to be asked (do not need a variable for this) + local lab_var "minlaborage lstatus nlfreason unempldur_l unempldur_u empstat ocusec industry_orig industrycat_isic industrycat10 industrycat4 occup_orig occup_isco occup_skill occup wage_no_compen unitwage whours wmonths wage_total contract healthins socialsec union firmsize_l firmsize_u empstat_2 ocusec_2 industry_orig_2 industrycat_isic_2 industrycat10_2 industrycat4_2 occup_orig_2 occup_isco_2 occup_skill_2 occup_2 wage_no_compen_2 unitwage_2 whours_2 wmonths_2 wage_total_2 firmsize_l_2 firmsize_u_2 t_hours_others t_wage_nocompen_others t_wage_others t_hours_total t_wage_nocompen_total t_wage_total lstatus_year nlfreason_year unempldur_l_year unempldur_u_year empstat_year ocusec_year industry_orig_year industrycat_isic_year industrycat10_year industrycat4_year occup_orig_year occup_isco_year occup_skill_year occup_year unitwage_year whours_year wmonths_year wage_total_year contract_year healthins_year socialsec_year union_year firmsize_l_year firmsize_u_year empstat_2_year ocusec_2_year industry_orig_2_year industrycat_isic_2_year industrycat10_2_year industrycat4_2_year occup_orig_2_year occup_isco_2_year occup_skill_2_year occup_2_year wage_no_compen_2_year unitwage_2_year whours_2_year wmonths_2_year wage_total_2_year firmsize_l_2_year firmsize_u_2_year t_hours_others_year t_wage_nocompen_others_year t_wage_others_year t_hours_total_year t_wage_nocompen_total_year t_wage_total_year njobs t_hours_annual linc_nc laborincome" + + foreach v of local lab_var { + cap confirm numeric variable `v' + if _rc == 0 { // is indeed numeric + replace `v'=. if ( age < minlaborage & !missing(age) ) + } + else { // is not + replace `v'= "" if ( age < minlaborage & !missing(age) ) + } + + } + +* +} + + +/*%%============================================================================================= + 9: Final steps +==============================================================================================%%*/ + +quietly{ + +*<_% KEEP VARIABLES - ALL_> + + keep countrycode survname survey icls_v isced_version isco_version isic_version year vermast veralt harmonization int_year int_month hhid pid weight weight_m weight_q psu ssu strata wave panel visit_no urban subnatid1 subnatid2 subnatid3 subnatidsurvey subnatid1_prev subnatid2_prev subnatid3_prev gaul_adm1_code gaul_adm2_code gaul_adm3_code hsize age male relationharm relationcs marital eye_dsablty hear_dsablty walk_dsablty conc_dsord slfcre_dsablty comm_dsablty migrated_mod_age migrated_ref_time migrated_binary migrated_years migrated_from_urban migrated_from_cat migrated_from_code migrated_from_country migrated_reason ed_mod_age school literacy educy educat7 educat5 educat4 educat_orig educat_isced vocational vocational_type vocational_length_l vocational_length_u vocational_field_orig vocational_financed minlaborage lstatus potential_lf underemployment nlfreason unempldur_l unempldur_u empstat ocusec industry_orig industrycat_isic industrycat10 industrycat4 occup_orig occup_isco occup_skill occup wage_no_compen unitwage whours wmonths wage_total contract healthins socialsec union firmsize_l firmsize_u empstat_2 ocusec_2 industry_orig_2 industrycat_isic_2 industrycat10_2 industrycat4_2 occup_orig_2 occup_isco_2 occup_skill_2 occup_2 wage_no_compen_2 unitwage_2 whours_2 wmonths_2 wage_total_2 firmsize_l_2 firmsize_u_2 t_hours_others t_wage_nocompen_others t_wage_others t_hours_total t_wage_nocompen_total t_wage_total lstatus_year potential_lf_year underemployment_year nlfreason_year unempldur_l_year unempldur_u_year empstat_year ocusec_year industry_orig_year industrycat_isic_year industrycat10_year industrycat4_year occup_orig_year occup_isco_year occup_skill_year occup_year wage_no_compen_year unitwage_year whours_year wmonths_year wage_total_year contract_year healthins_year socialsec_year union_year firmsize_l_year firmsize_u_year empstat_2_year ocusec_2_year industry_orig_2_year industrycat_isic_2_year industrycat10_2_year industrycat4_2_year occup_orig_2_year occup_isco_2_year occup_skill_2_year occup_2_year wage_no_compen_2_year unitwage_2_year whours_2_year wmonths_2_year wage_total_2_year firmsize_l_2_year firmsize_u_2_year t_hours_others_year t_wage_nocompen_others_year t_wage_others_year t_hours_total_year t_wage_nocompen_total_year t_wage_total_year njobs t_hours_annual linc_nc laborincome + +* + +*<_% ORDER VARIABLES_> + + order countrycode survname survey icls_v isced_version isco_version isic_version year vermast veralt harmonization int_year int_month hhid pid weight weight_m weight_q psu ssu strata wave panel visit_no urban subnatid1 subnatid2 subnatid3 subnatidsurvey subnatid1_prev subnatid2_prev subnatid3_prev gaul_adm1_code gaul_adm2_code gaul_adm3_code hsize age male relationharm relationcs marital eye_dsablty hear_dsablty walk_dsablty conc_dsord slfcre_dsablty comm_dsablty migrated_mod_age migrated_ref_time migrated_binary migrated_years migrated_from_urban migrated_from_cat migrated_from_code migrated_from_country migrated_reason ed_mod_age school literacy educy educat7 educat5 educat4 educat_orig educat_isced vocational vocational_type vocational_length_l vocational_length_u vocational_field_orig vocational_financed minlaborage lstatus potential_lf underemployment nlfreason unempldur_l unempldur_u empstat ocusec industry_orig industrycat_isic industrycat10 industrycat4 occup_orig occup_isco occup_skill occup wage_no_compen unitwage whours wmonths wage_total contract healthins socialsec union firmsize_l firmsize_u empstat_2 ocusec_2 industry_orig_2 industrycat_isic_2 industrycat10_2 industrycat4_2 occup_orig_2 occup_isco_2 occup_skill_2 occup_2 wage_no_compen_2 unitwage_2 whours_2 wmonths_2 wage_total_2 firmsize_l_2 firmsize_u_2 t_hours_others t_wage_nocompen_others t_wage_others t_hours_total t_wage_nocompen_total t_wage_total lstatus_year potential_lf_year underemployment_year nlfreason_year unempldur_l_year unempldur_u_year empstat_year ocusec_year industry_orig_year industrycat_isic_year industrycat10_year industrycat4_year occup_orig_year occup_isco_year occup_skill_year occup_year wage_no_compen_year unitwage_year whours_year wmonths_year wage_total_year contract_year healthins_year socialsec_year union_year firmsize_l_year firmsize_u_year empstat_2_year ocusec_2_year industry_orig_2_year industrycat_isic_2_year industrycat10_2_year industrycat4_2_year occup_orig_2_year occup_isco_2_year occup_skill_2_year occup_2_year wage_no_compen_2_year unitwage_2_year whours_2_year wmonths_2_year wage_total_2_year firmsize_l_2_year firmsize_u_2_year t_hours_others_year t_wage_nocompen_others_year t_wage_others_year t_hours_total_year t_wage_nocompen_total_year t_wage_total_year njobs t_hours_annual linc_nc laborincome + +* + +*<_% DROP UNUSED LABELS_> + + * Store all labels in data + label dir + local all_lab `r(names)' + + * Store all variables with a label, extract value label names + local used_lab = "" + ds, has(vallabel) + + local labelled_vars `r(varlist)' + + foreach varName of local labelled_vars { + local y : value label `varName' + local used_lab `"`used_lab' `y'"' + } + + * Compare lists, `notused' is list of labels in directory but not used in final variables + local notused : list all_lab - used_lab // local `notused' defines value labs not in remaining vars + local notused_len : list sizeof notused // store size of local + + * drop labels if the length of the notused vector is 1 or greater, otherwise nothing to drop + if `notused_len' >= 1 { + label drop `notused' + } + else { + di "There are no unused labels to drop. No value labels dropped." + } + + +* + +} + +*<_% DELETE MISSING VARIABLES_> + +quietly: describe, varlist +local kept_vars `r(varlist)' + +foreach var of local kept_vars { + + capture assert missing(`var') + if !_rc drop `var' +} + +* + + +*<_% COMPRESS_> + +compress + +* + + +*<_% SAVE_> + +save "`path_output'/`level_2_harm'_ALL.dta", replace + +* diff --git a/GLD/ARM/ARM_2016_LFS/ARM_2016_LFS_V01_M_V03_A_GLD/Programs/ARM_2016_LFS_V01_M_V03_A_GLD_ALL.do b/GLD/ARM/ARM_2016_LFS/ARM_2016_LFS_V01_M_V03_A_GLD/Programs/ARM_2016_LFS_V01_M_V03_A_GLD_ALL.do new file mode 100644 index 000000000..ab7a2f04d --- /dev/null +++ b/GLD/ARM/ARM_2016_LFS/ARM_2016_LFS_V01_M_V03_A_GLD/Programs/ARM_2016_LFS_V01_M_V03_A_GLD_ALL.do @@ -0,0 +1,1846 @@ + +/*%%============================================================================================= + 0: GLD Harmonization Preamble +================================================================================================*/ + +/* ----------------------------------------------------------------------- +<_Program name_> ARM_2016_LFS_V01_M_V03_A_GLD_ALL.do +<_Application_> Stata SE 18 <_Application_> +<_Author(s)_> Wolrd Bank Job's Group +<_Date created_> 2023-12-20 +------------------------------------------------------------------------- +<_Country_> Armenia (ARM) +<_Survey Title_> National Labour Force Survey +<_Survey Year_> 2016 +<_Study ID_> ARM_2016_LFS_v01_M +<_Data collection from (M/Y)_> [01/2016] +<_Data collection to (M/Y)_> [12/2016] +<_Source of dataset_> The Armenian 2016 to 2021 data is downloaded from + the website of Statistical Committee of the + Republic of Armenia:https://armstat.am/en/?nid=212 + The data is publicly available. +<_Sample size (HH)_> 7,788 +<_Sample size (IND)_> 28,516 +<_Sampling method_> A stratified two-stage probability sample design + with 14 domains as the primary strata and 18,000 + households as the SSU. +<_Geographic coverage_> All 11 regions/marzes. +<_Currency_> Armenian Dram +----------------------------------------------------------------------- +<_ICLS Version_> ICLS 13 +<_ISCED Version_> ISCED-2011 +<_ISCO Version_> ISCO 08 +<_OCCUP National_> NSCO +<_ISIC Version_> ISIC Rev.4 +<_INDUS National_> ISIC Rev.4 +----------------------------------------------------------------------- + +<_Version Control_> + +* Date: 2024-09-24 - Update vars educy, educat7 +* Date: 2024-10-09 - Include weight by quarter, correct contract variable + + + +-------------------------------------------------------------------------*/ + + +/*%%============================================================================================= + 1: Setting up of program environment, dataset +================================================================================================*/ + +*----------1.1: Initial commands------------------------------* + +clear +set more off +set mem 800m + +*----------1.2: Set directories------------------------------* + +* Define path sections +local server "Y:/GLD" +local country "ARM" +local year "2016" +local survey "LFS" +local vermast "V01" +local veralt "V03" + +* From the definitions, set path chunks +local level_1 "`country'_`year'_`survey'" +local level_2_mast "`level_1'_`vermast'_M" +local level_2_harm "`level_1'_`vermast'_M_`veralt'_A_GLD" + +* From chunks, define path_in, path_output folder +local path_in_stata "`server'/`country'/`level_1'/`level_2_mast'/Data/Stata" +local path_in_other "`server'/`country'/`level_1'/`level_2_mast'/Data/Original" +local path_output "`server'/`country'/`level_1'/`level_2_harm'/Data/Harmonized" + +* Define Output file name +local out_file "`level_2_harm'_ALL.dta" + + +*----------1.3: Database assembly------------------------------* + +* All steps necessary to merge datasets (if several) to have all elements needed to produce +* harmonized output in a single file + + use "`path_in_stata'/ARM_LFS_2016_raw.dta", clear + +/*%%============================================================================================= + 2: Survey & ID +================================================================================================*/ + +{ + +*<_countrycode_> + gen str4 countrycode="`country'" + label var countrycode "Country code" +* + + +*<_survname_> + gen survname="LFS" + label var survname "Survey acronym" +* + + +*<_survey_> + gen survey="LFS" + label var survey "Survey type" +* + + +*<_icls_v_> + gen icls_v="ICLS-13" + label var icls_v "ICLS version underlying questionnaire questions" +* + + +*<_isced_version_> + gen isced_version="isced_2011" + label var isced_version "Version of ISCED used for educat_isced" +* + + +*<_isco_version_> + gen isco_version="" + label var isco_version "Version of ISCO used" +* + + +*<_isic_version_> + gen isic_version="" + label var isic_version "Version of ISIC used" +* + + +*<_year_> + gen int year=`year' + label var year "Year of survey" +* + + +*<_vermast_> + gen str3 vermast="`vermast'" + label var vermast "Version of master data" +* + + +*<_veralt_> + gen str3 veralt="`veralt'" + label var veralt "Version of the alt/harmonized data" +* + + +*<_harmonization_> + gen harmonization="GLD" + label var harmonization "Type of harmonization" +* + + +*<_int_year_> + gen int_year=`year' + label var int_year "Year of the interview" +* + + +*<_int_month_> + gen int_month=A6_Month + label de lblint_month 1 "January" 2 "February" 3 "March" 4 "April" 5 "May" 6 "June" 7 "July" 8 "August" 9 "September" 10 "October" 11 "November" 12 "December" + label value int_month lblint_month + label var int_month "Month of the interview" +* + + +*<_hhid_> + tostring A1, gen(hid) format(%03.0f) + tostring A6_Month, gen(month) format(%03.0f) + egen hhid=concat(month hid) + label var hhid "Household id" +* + + +*<_pid_> + sort hhid B12 + bys hhid: gen memberid=_n + tostring memberid, gen(id_str) format(%02.0f) + egen pid=concat(hhid id_str), punct("-") + label var pid "Individual ID" +* + + +*<_weight_> + gen weight=Weights_Year + label var weight "Household sampling weight" +* + + +*<_weight_m_> + gen weight_m = . + label var weight_m "Survey sampling weight to obtain national estimates for each month" +* + + +*<_weight_q_> + egen weight_q = rowtotal(Weights_1 Weights_2 Weights_3 Weights_4) + label var weight_q "Survey sampling weight to obtain national estimates for each quarter" +* + + +*<_psu_> + gen psu=. + label var psu "Primary sampling units" +* + + +*<_ssu_> + gen ssu=hhid + label var ssu "Secondary sampling units" +* + + +*<_strata_> + decode A3, gen(marzname) + decode A5, gen(urbanstat) + gen strata=marzname+" "+urbanstat + label var strata "Strata" +* + + +*<_wave_> + gen wave=. + replace wave=1 if inrange(int_month,1,3) + replace wave=2 if inrange(int_month,4,6) + replace wave=3 if inrange(int_month,7,9) + replace wave=4 if inrange(int_month,10,12) + label var wave "Survey wave" +* + + +*<_panel_> + gen panel="" + label var panel "Panel individual belongs to" +* + + +*<_visit_no_> + gen visit_no=. + label var visit_no "Visit number in panel" +* +} + +/*%%============================================================================================= + 3: Geography +================================================================================================*/ + +{ + +*<_urban_> + gen urban=A5 + recode urban (2=0) + la de lblurban 1 "Urban" 0 "Rural" + label values urban lblurban + label var urban "Location is urban" +* + + +*<_subnatid1_> + gen subnatid1=A3 + tostring subnatid1, replace + replace subnatid1=subnatid1+" - "+marzname + + * Unite names to entire series + replace subnatid1 = "5 - Gegharkunik" if subnatid1 == "5 - Gegharquniq" + replace subnatid1 = "6 - Lori" if subnatid1 == "6 - Lory" + replace subnatid1 = "7 - Kotayk" if subnatid1 == "7 - Kotayq" + replace subnatid1 = "9 - Syunik" if subnatid1 == "9 - Syuniq" + + label var subnatid1 "Subnational ID at First Administrative Level" +* + + +*<_subnatid2_> + gen subnatid2=. + label var subnatid2 "Subnational ID at Second Administrative Level" +* + + +*<_subnatid3_> + gen subnatid3=. + label var subnatid3 "Subnational ID at Third Administrative Level" +* + + +*<_subnatidsurvey_> + gen subnatidsurvey=subnatid1+" "+urbanstat + label var subnatidsurvey "Administrative level at which survey is representative" +* + + +*<_subnatid1_prev_> + +/* <_subnatid1_prev_note_> +subnatid1_prev is coded as missing unless the classification used for subnatid1 has changed since the previous survey. + */ + + gen subnatid1_prev=. + label var subnatid1_prev "Classification used for subnatid1 from previous survey" +* + + +*<_subnatid2_prev_> + gen subnatid2_prev=. + label var subnatid2_prev "Classification used for subnatid2 from previous survey" +* + + +*<_subnatid3_prev_> + gen subnatid3_prev=. + label var subnatid3_prev "Classification used for subnatid3 from previous survey" +* + + +*<_gaul_adm1_code_> + gen gaul_adm1_code=. + label var gaul_adm1_code "Global Administrative Unit Layers (GAUL) Admin 1 code" +* + + +*<_gaul_adm2_code_> + gen gaul_adm2_code=. + label var gaul_adm2_code "Global Administrative Unit Layers (GAUL) Admin 2 code" +* + + +*<_gaul_adm3_code_> + gen gaul_adm3_code=. + label var gaul_adm3_code "Global Administrative Unit Layers (GAUL) Admin 3 code" +* + +} + +/*%%============================================================================================= + 4: Demography +================================================================================================*/ + +{ + +*<_hsize_> + bys hhid: egen hsize=max(memberid) + label var hsize "Household size" +* + + +*<_age_> + +/*<_age_note_> + +3 observations in the raw data set have negative (-1) age values. +They were coded as missing values in the harmonization. + +*<_age_note_>*/ + + gen age=Age + replace age=. if Age<0 + replace age=98 if age>98 & age!=. + label var age "Individual age" +* + + +*<_male_> + gen male=B11 + recode male 2=0 + label var male "Sex - Ind is male" + la de lblmale 1 "Male" 0 "Female" + label values male lblmale +* + + +*<_relationharm_> + +/*<_relationharm_note_> + +3 household (12 observations) in the raw data set do not have household heads: +012217 +012247 +012355 + +During the harmonization, we did not assign household head to the household. +But users can assign household heads based on their relationship to the head and +other characteristics such as gender and age. + +*<_relationharm_note_>*/ + + gen byte relationharm=B12 + recode relationharm (6 9=3) (7 8=4) (10=5) (11=6) + label var relationharm "Relationship to the head of household - Harmonized" + la de lblrelationharm 1 "Head of household" 2 "Spouse" 3 "Children" 4 "Parents" 5 "Other relatives" 6 "Other and non-relatives" + label values relationharm lblrelationharm +*<_relationharm_> + + +*<_relationcs_> + gen relationcs=B12 + label var relationcs "Relationship to the head of household - Country original" +* + + +*<_marital_> + gen marital=B16 + recode marital (1=2) (2=1) (3=5) + label var marital "Marital status" + la de lblmarital 1 "Married" 2 "Never Married" 3 "Living together" 4 "Divorced/Separated" 5 "Widowed" + label values marital lblmarital +* + + +*<_eye_dsablty_> + gen eye_dsablty=. + la de lbleye_dsablty 1 "No" 2 "Yes-some" 3 "Yes-a lot" 4 "Cannot at all" + label values eye_dsablty lbleye_dsablty + label var eye_dsablty "Disability related to eyesight" +* + + +*<_hear_dsablty_> + gen hear_dsablty=. + la de lblhear_dsablty 1 "No" 2 "Yes-some" 3 "Yes-a lot" 4 "Cannot at all" + label values hear_dsablty lblhear_dsablty + label var hear_dsablty "Disability related to hearing" +* + + +*<_walk_dsablty_> + gen walk_dsablty=. + la de lblwalk_dsablty 1 "No" 2 "Yes-some" 3 "Yes-a lot" 4 "Cannot at all" + label values walk_dsablty lblwalk_dsablty + label var walk_dsablty "Disability related to walking or climbing stairs" +* + + +*<_conc_dsord_> + gen conc_dsord=. + la de lblconc_dsord 1 "No" 2 "Yes-some" 3 "Yes-a lot" 4 "Cannot at all" + label values conc_dsord lblconc_dsord + label var conc_dsord "Disability related to concentration or remembering" +* + + +*<_slfcre_dsablty_> + gen slfcre_dsablty=. + la de lblslfcre_dsablty 1 "No" 2 "Yes-some" 3 "Yes-a lot" 4 "Cannot at all" + label values slfcre_dsablty lblslfcre_dsablty + label var eye_dsablty "Disability related to selfcare" +* + + +*<_comm_dsablty_> + gen comm_dsablty=. + la de lblcomm_dsablty 1 "No" 2 "Yes-some" 3 "Yes-a lot" 4 "Cannot at all" + label values comm_dsablty lblcomm_dsablty + label var eye_dsablty "Disability related to communicating" +* + +} + + +/*%%============================================================================================= + 5: Migration +================================================================================================*/ + +{ +*<_migrated_mod_age_> + gen migrated_mod_age=. + label var migrated_mod_age "Migration module application age" +* + + +*<_migrated_ref_time_> + gen migrated_ref_time=. + label var migrated_ref_time "Reference time applied to migration questions (in years)" +* + + +*<_migrated_binary_> + gen migrated_binary=. + label de lblmigrated_binary 0 "No" 1 "Yes" + replace migrated_binary=. if age + +*<_migrated_years_> + gen migrated_years=. + replace migrated_years=. if migrated_binary!=1 + replace migrated_years=. if age + + +*<_migrated_from_urban_> + gen migrated_from_urban=. + replace migrated_from_urban=. if age + + +*<_migrated_from_cat_> + gen migrated_from_cat=. + replace migrated_from_cat=. if age + + +*<_migrated_from_code_> + gen migrated_from_code="" + replace migrated_from_code="" if age + + +*<_migrated_from_country_> + gen migrated_from_country="" + replace migrated_from_country="" if migrated_binary!=1 + replace migrated_from_country="" if age + + +*<_migrated_reason_> + gen migrated_reason=. + replace migrated_reason=. if migrated_binary!=1 + replace migrated_reason=. if age +} + + +/*%%============================================================================================= + 6: Education +================================================================================================*/ + + +{ +*<_ed_mod_age_> + gen byte ed_mod_age=6 + label var ed_mod_age "Education module application age" +* + + +*<_school_> + gen school=. + replace school=. if age + + +*<_literacy_> + gen byte literacy=. + replace literacy=0 if B15==1 + replace literacy=1 if inrange(B15,2,9) + replace literacy=. if age + + +*<_educy_> + gen byte educy=. + replace educy = 0 if B15 == 1 | B15 == 2 + replace educy = 4 if B15 == 3 + replace educy = 9 if B15 == 4 + replace educy = 12 if B15 == 5 + replace educy = 11 if B15 == 6 + replace educy = 15 if B15 == 7 + replace educy = 16 if B15 == 8 + replace educy = 20 if B15 == 9 + replace educy=. if ageage & !mi(educy) & !mi(age) + label var educy "Years of education" +* + + +*<_educat7_> + gen byte educat7= B15 + recode educat7 (6=5) (7=6) (8/9=7) + replace educat7=. if age + + +*<_educat5_> + gen byte educat5=educat7 + recode educat5 (4=3) (5=4) (6 7=5) + replace educat5=. if age + + +*<_educat4_> + gen byte educat4=educat5 + replace educat4=. if age + + +*<_educat_orig_> + gen educat_orig=B15 + label var educat_orig "Original survey education code" +* + + +*<_educat_isced_> + gen educat_isced=. + label var educat_isced "ISCED standardised level of education" +* + + +*<_educat_isced_v_> + gen educat_isced_v="ISCED-2011" + label var educat_isced_v "Version of the ISCED used" +* + +*----------6.1: Education cleanup------------------------------* + +*<_% Correction min age_> + +** Drop info for cases under the age for which questions to be asked (do not need a variable for this) +local ed_var school literacy educy educat7 educat5 educat4 educat_isced +foreach v of local ed_var { + replace `v'=. if ( age < ed_mod_age & !missing(age) ) +} +replace educat_isced_v="." if ( age < ed_mod_age & !missing(age) ) +* + +} + +/*%%============================================================================================= + 7: Training +================================================================================================*/ + +{ + +*<_vocational_> + gen vocational=. + la de vocationallbl 1 "Yes" 0 "No" + la values vocational vocationallbl + label var vocational "Ever received vocational training" +* + + +*<_vocational_type_> + gen vocational_type=. + label de lblvocational_type 1 "Inside Enterprise" 2 "External" + label values vocational_type lblvocational_type + label var vocational_type "Type of vocational training" +* + + +*<_vocational_length_l_> + gen vocational_length_l=. + replace vocational_length_l=. if vocational!=1 + label var vocational_length_l "Length of training in months, lower limit" +* + + +*<_vocational_length_u_> + gen vocational_length_u=. + replace vocational_length_u=. if vocational!=1 + label var vocational_length_u "Length of training in months, upper limit" +* + + +*<_vocational_field_orig_> + gen vocational_field_orig=. + replace vocational_field_orig=. if vocational!=1 + label var vocational_field_orig "Original field of training information" +* + + +*<_vocational_financed_> + gen vocational_financed=. + label de lblvocational_financed 1 "Employer" 2 "Government" 3 "Mixed Employer/Government" 4 "Own funds" 5 "Other" + label var vocational_financed "How training was financed" +* + +} + +/*%%============================================================================================= + 8: Labour +================================================================================================*/ + +*<_minlaborage_> + +/*<_minlaborage_note_> + +The age range for the labor section is 15-75. + +*<_minlaborage_note_>*/ + + gen byte minlaborage=15 + label var minlaborage "Labor module application age" +* + + +*----------8.1: 7 day reference overall------------------------------* + +{ +*<_lstatus_> + +/*<_lstatus_note> + +According to the national definition of Armenia, the economically inavtive population +includes + +1)full-time pupils and students +2)housekeepers +3)pensioners +4)other jobless peope including conscripts + +And the economically inavtive population also needs to be within the age range of +15 and 75. +*<_lstatus_note>*/ + + gen byte lstatus=. + replace lstatus=1 if G1==1|inrange(G3,1,5)|inrange(G4,1,2) + replace lstatus=2 if lstatus==.&inrange(Z57,1,2) + replace lstatus=3 if !mi(Z49_4group)&lstatus==. + replace lstatus=. if !inrange(age,15,75) + label var lstatus "Labor status" + la de lbllstatus 1 "Employed" 2 "Unemployed" 3 "Non-LF" + label values lstatus lbllstatus +* + + +*<_potential_lf_> + +/*<_potential_lf_note_> +Note: var "potential_lf" only takes value if the respondent is not in labor force. (lstatus==3) + +"potential_lf"=1 if the person is +1)available but not searching or inrange(E45,1,3) & (Z57==2) +2)searching but not immediately available to work or Z57==1 & inlist(E45,4,6) + +*/ + + gen potential_lf=. + replace potential_lf=1 if [inrange(E45,1,3) & (Z57==2)] | [Z57==1 & inlist(E45,4,6)] + replace potential_lf=0 if [inrange(E45,1,3) & (Z57==1)] | [Z57==1 & inrange(E45,1,3)] + replace potential_lf=. if age75&!mi(age)] + replace potential_lf=. if lstatus!=3 + label var potential_lf "Potential labour force status" + la de lblpotential_lf 0 "No" 1 "Yes" + label values potential_lf lblpotential_lf +* + + +*<_underemployment_> + gen byte underemployment=E41 + replace underemployment=1 if inrange(E41,1,3) + replace underemployment=0 if E41==4 + replace underemployment=. if age75&!mi(age)] + replace underemployment=. if lstatus!=1 + label var underemployment "Underemployment status" + la de lblunderemployment 0 "No" 1 "Yes" + label values underemployment lblunderemployment +* + + +*<_nlfreason_> + gen byte nlfreason=Z49_4group + recode nlfreason (4=5) + replace nlfreason=. if age75&!mi(age)] + replace nlfreason=. if lstatus!=3 + label var nlfreason "Reason not in the labor force" + la de lblnlfreason 1 "Student" 2 "Housekeeper" 3 "Retired" 4 "Disabled" 5 "Other" + label values nlfreason lblnlfreason +* + + +*<_unempldur_l_> + gen byte unempldur_l=Z52 + recode unempldur_l (1=0) (2=3) (3=12) (4=24) (5=36) + replace unempldur_l=. if age75&!mi(age)] + replace unempldur_l=. if lstatus!=2 + label var unempldur_l "Unemployment duration (months) lower bracket" +* + + +*<_unempldur_u_> + gen byte unempldur_u=Z52 + recode unempldur_u (1=3) (2=12) (3=24) (4=36) (5=.) + replace unempldur_u=. if age75&!mi(age)] + replace unempldur_u=. if lstatus!=2 + label var unempldur_u "Unemployment duration (months) upper bracket" +* +} + + +*----------8.2: 7 day reference main job------------------------------* + + +{ +*<_empstat_> + gen byte empstat=D8 + recode empstat (2 7=1) (5=4) (6=2) (8=5) + replace empstat=. if lstatus!=1|age + + +*<_ocusec_> + gen byte ocusec=D11 + recode ocusec (3 4=2) + replace ocusec=. if lstatus!=1|age + + +*<_industry_orig_> + gen industry_orig=D6_21group + replace industry_orig=. if lstatus!=1 + label var industry_orig "Original survey industry code, main job 7 day recall" +* + + +*<_industrycat_isic_> + gen industrycat_isic="" +quietly +{ + replace industrycat_isic="A" if D6_21group==1 + replace industrycat_isic="B" if D6_21group==2 + replace industrycat_isic="C" if D6_21group==3 + replace industrycat_isic="D" if D6_21group==4 + replace industrycat_isic="E" if D6_21group==5 + replace industrycat_isic="F" if D6_21group==6 + replace industrycat_isic="G" if D6_21group==7 + replace industrycat_isic="H" if D6_21group==8 + replace industrycat_isic="I" if D6_21group==9 + replace industrycat_isic="J" if D6_21group==10 + replace industrycat_isic="K" if D6_21group==11 + replace industrycat_isic="L" if D6_21group==12 + replace industrycat_isic="M" if D6_21group==13 + replace industrycat_isic="N" if D6_21group==14 + replace industrycat_isic="O" if D6_21group==15 + replace industrycat_isic="P" if D6_21group==16 + replace industrycat_isic="Q" if D6_21group==17 + replace industrycat_isic="R" if D6_21group==18 + replace industrycat_isic="S" if D6_21group==19 + replace industrycat_isic="T" if D6_21group==20 + replace industrycat_isic="U" if D6_21group==21 +} + + replace industrycat_isic="" if industrycat_isic=="."|lstatus!=1 + label var industrycat_isic "ISIC code of primary job 7 day recall" +* + + +*<_industrycat10_> + gen industrycat10=D6_21group + recode industrycat10 (5=4) (6=5) (7 9=6) (8 10=7) (11/14=8) (15=9) (16/21=10) + replace industrycat10=. if lstatus!=1 + label var industrycat10 "1 digit industry classification, primary job 7 day recall" + la de lblindustrycat10 1 "Agriculture" 2 "Mining" 3 "Manufacturing" 4 "Public utilities" 5 "Construction" 6 "Commerce" 7 "Transport and Comnunications" 8 "Financial and Business Services" 9 "Public Administration" 10 "Other Services, Unspecified" + label values industrycat10 lblindustrycat10 +* + + +*<_industrycat4_> + gen byte industrycat4=industrycat10 + recode industrycat4 (3/5=2)(6/9=3)(10=4) + label var industrycat4 "1 digit industry classification (Broad Economic Activities), primary job 7 day recall" + la de lblindustrycat4 1 "Agriculture" 2 "Industry" 3 "Services" 4 "Other" + label values industrycat4 lblindustrycat4 +* + + +*<_occup_orig_> + gen occup_orig=D5_9group + replace occup_orig=. if lstatus!=1|[age>75&!mi(age)] + label var occup_orig "Original occupation record primary job 7 day recall" +* + + +*<_occup_isco_> + gen occup_isco="" + replace occup_isco="" if lstatus!=1 | occup_isco=="." + label var occup_isco "ISCO code of primary job 7 day recall" +* + + +*<_occup_skill_> + gen occup_skill=D5_9group + replace occup_skill=1 if D5_9group==9 + replace occup_skill=2 if inrange(D5_9group, 4, 8) + replace occup_skill=3 if inrange(D5_9group, 1, 3) + replace occup_skill=. if lstatus!=1 + la de lblskill 1 "Low skill" 2 "Medium skill" 3 "High skill" + label values occup_skill lblskill + label var occup_skill "Skill based on ISCO standard primary job 7 day recall" +* + + +*<_occup_> + gen occup=D5_9group + replace occup=. if lstatus!=1|[age>75&!mi(age)] + label var occup "1 digit occupational classification, primary job 7 day recall" + la de lbloccup 1 "Managers" 2 "Professionals" 3 "Technicians" 4 "Clerks" 5 "Service and market sales workers" 6 "Skilled agricultural" 7 "Craft workers" 8 "Machine operators" 9 "Elementary occupations" 10 "Armed forces" 99 "Others" + label values occup lbloccup +* + + +*<_wage_no_compen_> + +/*<_wage_no_compen_note_> + +The wage questions in the questionnare are organized into to parts: the first part +asks for the specific number of income if the given respondent could recall and was +willing to answer; the second part provides different categories of income range +if the given respondent could not recall or was not willing to answer the first part. + +The general logic here is to impute wage values for people who only answered an income +range. We used industry, occupation, income categories and gender to estimate their +specific income values. + +15.73% of total non-missing wage values were imputed using this method. + +*<_wage_no_compen_note_>*/ + + * Overall --> wage info (here the variable, for us it should be wage_no_compen) + * to missing if value is 0. + gen wage14=D14_1+D14_2 + replace wage14=. if wage14==0 + + * First replace outliers by + winsor2 wage14, suffix(_w) cuts(1 99) + + * Create salary categories based on winsor values + gen salary_cat=. + replace salary_cat=1 if inrange(wage14_w, 1, 55000) + replace salary_cat=2 if wage14_w==55000 + replace salary_cat=3 if inrange(wage14_w, 55001, 110000) + replace salary_cat=4 if inrange(wage14_w, 110001, 220000) + replace salary_cat=5 if inrange(wage14_w, 220001, 440000) + replace salary_cat=6 if inrange(wage14_w, 440001, 600000) + replace salary_cat=7 if inrange(wage14_w, 600001, 700000) + replace salary_cat=8 if inrange(wage14_w, 700000, 99999999) + + * Preserve to collapse, so we can merge the info in + preserve + + * Collpase by industry, sex, and salary categories + collapse (mean)wage14_w[iw=weight], by(industrycat10 occup male urban salary_cat) + + * Rename variable, otherwise when merging in, master version of an equally name one will be kept + rename wage14_w wage_group_estimate + + * Rename salary_cat to D15 since this is what we want the info to latch on to + rename salary_cat D15 + tempfile salary_helper + save "`salary_helper'" + + * Restore, merge in + restore + merge m:1 industrycat10 occup male urban D15 using "`salary_helper'", keep(matched master) nogen + + * Create wage variable + gen wage_no_compen=. + + * Fill it first with values that are accurate + replace wage_no_compen=wage14 if !mi(wage14)&mi(D15) + + * Now add the categorised means + replace wage_no_compen=wage_group_estimate if inrange(D15,1,8)&!mi(wage_group_estimate) + + * Keep only for employed employees, label + replace wage_no_compen=. if lstatus!=1|empstat==2 + label var wage_no_compen "Last wage payment primary job 7 day recall" + +* + + +*<_unitwage_> + gen byte unitwage=D16 + recode unitwage (4=5) (5=7) (6=8) (7=10) + replace unitwage=. if lstatus!=1 | empstat==2 + label var unitwage "Last wages' time unit primary job 7 day recall" + la de lblunitwage 1 "Daily" 2 "Weekly" 3 "Every two weeks" 4 "Bimonthly" 5 "Monthly" 6 "Trimester" 7 "Biannual" 8 "Annually" 9 "Hourly" 10 "Other" + label values unitwage lblunitwage +* + + +*<_whours_> + gen whours=E39_1 + replace whours=. if lstatus!=1|E39_1==0 + label var whours "Hours of work in last week primary job 7 day recall" +* + + +*<_wmonths_> + gen wmonths=. + label var wmonths "Months of work in past 12 months primary job 7 day recall" +* + + +*<_wage_total_> + gen wage_total=. + label var wage_total "Annualized total wage primary job 7 day recall" +* + + +*<_contract_> + +/*<_contract_note_> + +There is no separate contract question in the questionnaire. +This contract variable was coded based on employment status question which asks +wether an employed respondent had a contract or not. + +*<_contract_note_>*/ + + gen byte contract = . + replace contract = (D8 == 1) + replace contract=. if lstatus != 1 + label var contract "Employment has contract primary job 7 day recall" + la de lblcontract 0 "Without contract" 1 "With contract" + label values contract lblcontract +* + + +*<_healthins_> + gen byte healthins=. + replace healthins=1 if D9_6==1 + replace healthins=0 if D9_6==2 + replace healthins=. if lstatus!=1 + label var healthins "Employment has health insurance primary job 7 day recall" + la de lblhealthins 0 "Without health insurance" 1 "With health insurance" + label values healthins lblhealthins +* + + +*<_socialsec_> + gen byte socialsec=. + replace socialsec=. if lstatus!=1 + label var socialsec "Employment has social security insurance primary job 7 day recall" + la de lblsocialsec 1 "With social security" 0 "Without social secturity" + label values socialsec lblsocialsec +* + + +*<_union_> + gen byte union=. + replace union=1 if D23==1 + replace union=0 if D23==2 + replace union=. if lstatus!=1 + label var union "Union membership at primary job 7 day recall" + la de lblunion 0 "Not union member" 1 "Union member" + label values union lblunion +* + + +*<_firmsize_l_> + gen byte firmsize_l=D13a + recode firmsize_l (1=1) (2=5) (3=10) (4=20) (5=50) (6=100) (7=.) + replace firmsize_l=. if lstatus!=1 + label var firmsize_l "Firm size (lower bracket) primary job 7 day recall" +* + + +*<_firmsize_u_> + gen byte firmsize_u=D13a + recode firmsize_u (1=5) (2=9) (3=19) (4=49) (5=99) (6=.) + replace firmsize_u=. if lstatus!=1 + label var firmsize_u "Firm size (upper bracket) primary job 7 day recall" +* + +} + + +*----------8.3: 7 day reference secondary job------------------------------* +* Since labels are the same as main job, values are labelled using main job labels + +{ +*<_empstat_2_> + gen byte empstat_2=E27 + recode empstat_2 (2 7=1) (5=4) (6=2) + replace empstat_2=. if lstatus!=1|E24!=1 + label var empstat_2 "Employment status during past week secondary job 7 day recall" + la de lblempstat_2 1 "Paid employee" 2 "Non-paid employee" 3 "Employer" 4 "Self-employed" 5 "Other, workers not classifiable by status" + label values empstat_2 lblempstat +* + + +*<_ocusec_2_> + gen byte ocusec_2=E29 + recode ocusec_2 (3 4=2) + replace ocusec_2=. if lstatus!=1|E24!=1 + label var ocusec_2 "Sector of activity secondary job 7 day recall" + la de lblocusec_2 1 "Public Sector, Central Government, Army" 2 "Private, NGO" 3 "State owned" 4 "Public or State-owned, but cannot distinguish" + label values ocusec_2 lblocusec_2 +* + + +*<_industry_orig_2_> + gen industry_orig_2=E26_21group + replace industry_orig_2=. if lstatus!=1|E24!=1 + label var industry_orig_2 "Original survey industry code, secondary job 7 day recall" +* + + +*<_industrycat_isic_2_> + gen industrycat_isic_2="" +quietly +{ + replace industrycat_isic_2="A" if E26_21group==1 + replace industrycat_isic_2="B" if E26_21group==2 + replace industrycat_isic_2="C" if E26_21group==3 + replace industrycat_isic_2="D" if E26_21group==4 + replace industrycat_isic_2="E" if E26_21group==5 + replace industrycat_isic_2="F" if E26_21group==6 + replace industrycat_isic_2="G" if E26_21group==7 + replace industrycat_isic_2="H" if E26_21group==8 + replace industrycat_isic_2="I" if E26_21group==9 + replace industrycat_isic_2="J" if E26_21group==10 + replace industrycat_isic_2="K" if E26_21group==11 + replace industrycat_isic_2="L" if E26_21group==12 + replace industrycat_isic_2="M" if E26_21group==13 + replace industrycat_isic_2="N" if E26_21group==14 + replace industrycat_isic_2="O" if E26_21group==15 + replace industrycat_isic_2="P" if E26_21group==16 + replace industrycat_isic_2="Q" if E26_21group==17 + replace industrycat_isic_2="R" if E26_21group==18 + replace industrycat_isic_2="S" if E26_21group==19 + replace industrycat_isic_2="T" if E26_21group==20 + replace industrycat_isic_2="U" if E26_21group==21 +} + + replace industrycat_isic_2="" if industrycat_isic_2=="."|E24!=1 + label var industrycat_isic_2 "ISIC code of secondary job 7 day recall" +* + + +*<_industrycat10_2_> + gen industrycat10_2=E26_21group + recode industrycat10_2 (5=4) (6=5) (7 9=6) (8 10=7) (11/14=8) (15=9) (16/21=10) + replace industrycat10_2=. if lstatus!=1|E24!=1 + label var industrycat10_2 "1 digit industry classification, secondary job 7 day recall" + label values industrycat10_2 lblindustrycat10 +* + + +*<_industrycat4_2_> + gen byte industrycat4_2=industrycat10_2 + recode industrycat4_2 (3/5=2)(6/9=3)(10=4) + label var industrycat4_2 "1 digit industry classification (Broad Economic Activities), secondary job 7 day recall" + label values industrycat4_2 lblindustrycat4 +* + + +*<_occup_orig_2_> + gen occup_orig_2=E25_9group + replace occup_orig_2=. if lstatus!=1|E24!=1 + label var occup_orig_2 "Original occupation record secondary job 7 day recall" +* + + +*<_occup_isco_2_> + gen occup_isco_2="" + replace occup_isco_2="" if lstatus!=1 | occup_isco_2=="."|E24!=1 + label var occup_isco_2 "ISCO code of secondary job 7 day recall" +* + + +*<_occup_skill_2_> + gen occup_skill_2=E25_9group + replace occup_skill_2=1 if E25_9group==9 + replace occup_skill_2=2 if inrange(E25_9group,4,8) + replace occup_skill_2=3 if inrange(E25_9group,1,3) + replace occup_skill_2=. if E25_9group==0|lstatus!=1|E24!=1 + label var occup_skill_2 "Skill based on ISCO standard secondary job 7 day recall" +* + + +*<_occup_2_> + gen occup_2=E25_9group + replace occup_2=. if lstatus!=1|E24!=1 + label var occup_2 "1 digit occupational classification secondary job 7 day recall" + label values occup_2 lbloccup +* + + +*<_wage_no_compen_2_> + + gen wage32=E32_1+E32_2 + replace wage32=. if wage32==0 + + * First replace outliers by + winsor2 wage32, suffix(_w) cuts(1 99) + + * Create salary categories based on winsor values + gen salary_cat2=. + replace salary_cat2=1 if inrange(wage32_w, 1, 55000) + replace salary_cat2=2 if wage32_w==55000 + replace salary_cat2=3 if inrange(wage32_w, 55001, 110000) + replace salary_cat2=4 if inrange(wage32_w, 110001, 220000) + replace salary_cat2=5 if inrange(wage32_w, 220001, 440000) + + * Preserve to collapse, so we can merge the info in + preserve + + * Collpase by industry, sex, and salary categories + collapse (mean)wage32_w[iw=weight], by(industrycat10_2 occup_2 male urban salary_cat2) + + * Rename variable, otherwise when merging in, master version of an equally name one will be kept + rename wage32_w wage_group_estimate2 + + * Rename salary_cat to D15 since this is what we want the info to latch on to + rename salary_cat2 E33 + tempfile salary_helper2 + save "`salary_helper2'" + + * Restore, merge in + restore + merge m:1 industrycat10_2 occup_2 male urban E33 using "`salary_helper2'", keep(matched master) nogen + + * Create wage variable + gen wage_no_compen_2=. + + * Fill it first with values that are accurate + replace wage_no_compen_2=wage32 if !mi(wage32)&mi(E33) + + * Now add the categorised means + replace wage_no_compen_2=wage_group_estimate2 if inrange(E33,1,5)&!mi(wage_group_estimate2) + + * Keep only for employed employees, label + replace wage_no_compen_2=. if E24!=1|empstat_2==2 + label var wage_no_compen_2 "Last wage payment secondary job 7 day recall" +* + + +*<_unitwage_2_> + gen byte unitwage_2=E34 + recode unitwage_2 (4=5) (5=7) (6=8) (7=10) + replace unitwage_2=. if lstatus!=1|E24!=1 + label var unitwage_2 "Last wages' time unit secondary job 7 day recall" + label values unitwage_2 lblunitwage +* + + +*<_whours_2_> + gen whours_2=E38_2 + replace whours_2=. if E38_2==0|E24!=1 + label var whours_2 "Hours of work in last week secondary job 7 day recall" +* + + +*<_wmonths_2_> + gen wmonths_2=. + label var wmonths_2 "Months of work in past 12 months secondary job 7 day recall" +* + + +*<_wage_total_2_> + gen wage_total_2=. + label var wage_total_2 "Annualized total wage secondary job 7 day recall" +* + + +*<_firmsize_l_2_> + gen byte firmsize_l_2=E30a + recode firmsize_l_2 (1=1) (2=5) (3=10) (4=20) (5=50) (6=100) (7=.) + label var firmsize_l_2 "Firm size (lower bracket) secondary job 7 day recall" +* + + +*<_firmsize_u_2_> + gen byte firmsize_u_2=E30a + recode firmsize_u_2 (1=5) (2=9) (3=19) (4=49) (5=99) (6=.) + label var firmsize_u_2 "Firm size (upper bracket) secondary job 7 day recall" +* + +} + +*----------8.4: 7 day reference additional jobs------------------------------* + +*<_t_hours_others_> + gen t_hours_others=. + label var t_hours_others "Annualized hours worked in all but primary and secondary jobs 7 day recall" +* + + +*<_t_wage_nocompen_others_> + gen t_wage_nocompen_others=. + label var t_wage_nocompen_others "Annualized wage in all but primary & secondary jobs excl. bonuses, etc. 7 day recall" +* + + +*<_t_wage_others_> + gen t_wage_others=. + label var t_wage_others "Annualized wage in all but primary and secondary jobs (12-mon ref period)" +* + + +*----------8.5: 7 day reference total summary------------------------------* + + +*<_t_hours_total_> + gen t_hours_total=. + label var t_hours_total "Annualized hours worked in all jobs 7 day recall" +* + + +*<_t_wage_nocompen_total_> + gen t_wage_nocompen_total=. + label var t_wage_nocompen_total "Annualized wage in all jobs excl. bonuses, etc. 7 day recall" +* + + +*<_t_wage_total_> + gen t_wage_total=. + label var t_wage_total "Annualized total wage for all jobs 7 day recall" +* + + +*----------8.6: 12 month reference overall------------------------------* + +{ +*<_lstatus_year_> + gen byte lstatus_year=. + replace lstatus_year=. if age + + +*<_potential_lf_year_> + gen byte potential_lf_year=. + replace potential_lf_year=. if age + + +*<_underemployment_year_> + gen byte underemployment_year=. + replace underemployment_year=. if age + + +*<_nlfreason_year_> + gen byte nlfreason_year=. + label var nlfreason_year "Reason not in the labor force" + la de lblnlfreason_year 1 "Student" 2 "Housekeeper" 3 "Retired" 4 "Disable" 5 "Other" + label values nlfreason_year lblnlfreason_year +* + + +*<_unempldur_l_year_> + gen byte unempldur_l_year=. + label var unempldur_l_year "Unemployment duration (months) lower bracket" +* + + +*<_unempldur_u_year_> + gen byte unempldur_u_year=. + label var unempldur_u_year "Unemployment duration (months) upper bracket" +* + +} + +*----------8.7: 12 month reference main job------------------------------* + +{ +*<_empstat_year_> + gen byte empstat_year=. + label var empstat_year "Employment status during past week primary job 12 month recall" + la de lblempstat_year 1 "Paid employee" 2 "Non-paid employee" 3 "Employer" 4 "Self-employed" 5 "Other, workers not classifiable by status" + label values empstat_year lblempstat_year +* + + +*<_ocusec_year_> + gen byte ocusec_year=. + label var ocusec_year "Sector of activity primary job 12 day recall" + la de lblocusec_year 1 "Public Sector, Central Government, Army" 2 "Private, NGO" 3 "State owned" 4 "Public or State-owned, but cannot distinguish" + label values ocusec_year lblocusec_year +* + + +*<_industry_orig_year_> + gen industry_orig_year=. + label var industry_orig_year "Original industry record main job 12 month recall" +* + + +*<_industrycat_isic_year_> + gen industrycat_isic_year="" + replace industrycat_isic_year="" if industrycat_isic_year=="." + label var industrycat_isic_year "ISIC code of primary job 12 month recall" +* + + +*<_industrycat10_year_> + gen byte industrycat10_year=. + label var industrycat10_year "1 digit industry classification, primary job 12 month recall" + la de lblindustrycat10_year 1 "Agriculture" 2 "Mining" 3 "Manufacturing" 4 "Public utilities" 5 "Construction" 6 "Commerce" 7 "Transport and Comnunications" 8 "Financial and Business Services" 9 "Public Administration" 10 "Other Services, Unspecified" + label values industrycat10_year lblindustrycat10_year +* + + +*<_industrycat4_year_> + gen byte industrycat4_year=industrycat10_year + recode industrycat4_year (1=1)(2 3 4 5 =2)(6 7 8 9=3)(10=4) + label var industrycat4_year "1 digit industry classification (Broad Economic Activities), primary job 12 month recall" + la de lblindustrycat4_year 1 "Agriculture" 2 "Industry" 3 "Services" 4 "Other" + label values industrycat4_year lblindustrycat4_year +* + + +*<_occup_orig_year_> + gen occup_orig_year=. + label var occup_orig_year "Original occupation record primary job 12 month recall" +* + + +*<_occup_isco_year_> + gen str4 occup_isco_year="" + label var occup_isco_year "ISCO code of primary job 12 month recall" +* + + +*<_occup_skill_year_> + gen skill_level_year=substr(occup_isco_year,1,1) + destring skill_level_year, replace + gen occup_skill_year=. + replace occup_skill_year=1 if skill_level_year==9 + replace occup_skill_year=2 if inrange(skill_level_year,4,8) + replace occup_skill_year=3 if inrange(skill_level_year,1,3) + replace occup_skill_year=. if skill_level_year==0 + label var occup_skill_year "Skill based on ISCO standard primary job 12 month recall" +* + + +*<_occup_year_> + gen byte occup_year=. + label var occup_year "1 digit occupational classification, primary job 12 month recall" + la de lbloccup_year 1 "Managers" 2 "Professionals" 3 "Technicians" 4 "Clerks" 5 "Service and market sales workers" 6 "Skilled agricultural" 7 "Craft workers" 8 "Machine operators" 9 "Elementary occupations" 10 "Armed forces" 99 "Others" + label values occup_year lbloccup_year +* + + +*<_wage_no_compen_year_> + gen double wage_no_compen_year=. + label var wage_no_compen_year "Last wage payment primary job 12 month recall" +* + + +*<_unitwage_year_> + gen byte unitwage_year=. + label var unitwage_year "Last wages' time unit primary job 12 month recall" + la de lblunitwage_year 1 "Daily" 2 "Weekly" 3 "Every two weeks" 4 "Bimonthly" 5 "Monthly" 6 "Trimester" 7 "Biannual" 8 "Annually" 9 "Hourly" 10 "Other" + label values unitwage_year lblunitwage_year +* + + +*<_whours_year_> + gen whours_year=. + label var whours_year "Hours of work in last week primary job 12 month recall" +* + + +*<_wmonths_year_> + gen wmonths_year=. + label var wmonths_year "Months of work in past 12 months primary job 12 month recall" +* + + +*<_wage_total_year_> + gen wage_total_year=. + label var wage_total_year "Annualized total wage primary job 12 month recall" +* + + +*<_contract_year_> + gen byte contract_year=. + label var contract_year "Employment has contract primary job 12 month recall" + la de lblcontract_year 0 "Without contract" 1 "With contract" + label values contract_year lblcontract_year +* + + +*<_healthins_year_> + gen byte healthins_year=. + label var healthins_year "Employment has health insurance primary job 12 month recall" + la de lblhealthins_year 0 "Without health insurance" 1 "With health insurance" + label values healthins_year lblhealthins_year +* + + +*<_socialsec_year_> + gen byte socialsec_year=. + label var socialsec_year "Employment has social security insurance primary job 7 day recall" + la de lblsocialsec_year 1 "With social security" 0 "Without social secturity" + label values socialsec_year lblsocialsec_year +* + + +*<_union_year_> + gen byte union_year=. + label var union_year "Union membership at primary job 12 month recall" + la de lblunion_year 0 "Not union member" 1 "Union member" + label values union_year lblunion_year +* + + +*<_firmsize_l_year_> + gen byte firmsize_l_year=. + label var firmsize_l_year "Firm size (lower bracket) primary job 12 month recall" +* + + +*<_firmsize_u_year_> + gen byte firmsize_u_year=. + label var firmsize_u_year "Firm size (upper bracket) primary job 12 month recall" +* + +} + + +*----------8.8: 12 month reference secondary job------------------------------* + +{ + +*<_empstat_2_year_> + gen byte empstat_2_year=. + label var empstat_2_year "Employment status during past week secondary job 12 month recall" + label values empstat_2_year lblempstat_year +* + + +*<_ocusec_2_year_> + gen byte ocusec_2_year=. + label var ocusec_2_year "Sector of activity secondary job 12 day recall" + la de lblocusec_2_year 1 "Public Sector, Central Government, Army" 2 "Private, NGO" 3 "State owned" 4 "Public or State-owned, but cannot distinguish" + label values ocusec_2_year lblocusec_2_year +* + + + +*<_industry_orig_2_year_> + gen industry_orig_2_year=. + label var industry_orig_2_year "Original survey industry code, secondary job 12 month recall" +* + + + +*<_industrycat_isic_2_year_> + gen industrycat_isic_2_year=. + label var industrycat_isic_2_year "ISIC code of secondary job 12 month recall" +* + + +*<_industrycat10_2_year_> + gen byte industrycat10_2_year=. + label var industrycat10_2_year "1 digit industry classification, secondary job 12 month recall" + label values industrycat10_2_year lblindustrycat10_year +* + + +*<_industrycat4_2_year_> + gen byte industrycat4_2_year=industrycat10_2_year + recode industrycat4_2_year (1=1)(2 3 4 5 =2)(6 7 8 9=3)(10=4) + label var industrycat4_2_year "1 digit industry classification (Broad Economic Activities), secondary job 12 month recall" + label values industrycat4_2_year lblindustrycat4_year +* + + +*<_occup_orig_2_year_> + gen occup_orig_2_year=. + label var occup_orig_2_year "Original occupation record secondary job 12 month recall" +* + + +*<_occup_isco_2_year_> + gen occup_isco_2_year=. + label var occup_isco_2_year "ISCO code of secondary job 12 month recall" +* + + +*<_occup_skill_2_year_> + gen occup_skill_2_year=. + label var occup_skill_2_year "Skill based on ISCO standard secondary job 12 month recall" +* + + +*<_occup_2_year_> + gen byte occup_2_year=. + label var occup_2_year "1 digit occupational classification, secondary job 12 month recall" + label values occup_2_year lbloccup_year +* + + +*<_wage_no_compen_2_year_> + gen double wage_no_compen_2_year=. + label var wage_no_compen_2_year "Last wage payment secondary job 12 month recall" +* + + +*<_unitwage_2_year_> + gen byte unitwage_2_year=. + label var unitwage_2_year "Last wages' time unit secondary job 12 month recall" + label values unitwage_2_year lblunitwage_year +* + + +*<_whours_2_year_> + gen whours_2_year=. + label var whours_2_year "Hours of work in last week secondary job 12 month recall" +* + + +*<_wmonths_2_year_> + gen wmonths_2_year=. + label var wmonths_2_year "Months of work in past 12 months secondary job 12 month recall" +* + + +*<_wage_total_2_year_> + gen wage_total_2_year=. + label var wage_total_2_year "Annualized total wage secondary job 12 month recall" +* + + +*<_firmsize_l_2_year_> + gen byte firmsize_l_2_year=. + label var firmsize_l_2_year "Firm size (lower bracket) secondary job 12 month recall" +* + + +*<_firmsize_u_2_year_> + gen byte firmsize_u_2_year=. + label var firmsize_u_2_year "Firm size (upper bracket) secondary job 12 month recall" +* + +} + + +*----------8.9: 12 month reference additional jobs------------------------------* + + +*<_t_hours_others_year_> + gen t_hours_others_year=. + label var t_hours_others_year "Annualized hours worked in all but primary and secondary jobs 12 month recall" +* + + +*<_t_wage_nocompen_others_year_> + gen t_wage_nocompen_others_year=. + label var t_wage_nocompen_others_year "Annualized wage in all but primary & secondary jobs excl. bonuses, etc. 12 month recall)" +* + + +*<_t_wage_others_year_> + gen t_wage_others_year=. + label var t_wage_others_year "Annualized wage in all but primary and secondary jobs 12 month recall" +* + + +*----------8.10: 12 month total summary------------------------------* + + +*<_t_hours_total_year_> + gen t_hours_total_year=. + label var t_hours_total_year "Annualized hours worked in all jobs 12 month month recall" +* + + +*<_t_wage_nocompen_total_year_> + gen t_wage_nocompen_total_year=. + label var t_wage_nocompen_total_year "Annualized wage in all jobs excl. bonuses, etc. 12 month recall" +* + + +*<_t_wage_total_year_> + gen t_wage_total_year=. + label var t_wage_total_year "Annualized total wage for all jobs 12 month recall" +* + + +*----------8.11: Overall across reference periods------------------------------* + + +*<_njobs_> + gen njobs=. + replace njobs=1 if lstatus==1&E24!=1 + replace njobs=2 if lstatus==1&E24==1 + replace njobs=. if lstatus!=1 + label var njobs "Total number of jobs" +* + + +*<_t_hours_annual_> + gen t_hours_annual=. + label var t_hours_annual "Total hours worked in all jobs in the previous 12 months" +* + + +*<_linc_nc_> + gen linc_nc=. + label var linc_nc "Total annual wage income in all jobs, excl. bonuses, etc." +* + + +*<_laborincome_> + gen laborincome=. + label var laborincome "Total annual individual labor income in all jobs, incl. bonuses, etc." +* + + +*----------8.13: Labour cleanup------------------------------* + +{ +*<_% Correction min age_> + +** Drop info for cases under the age for which questions to be asked (do not need a variable for this) + local lab_var "minlaborage lstatus nlfreason unempldur_l unempldur_u empstat ocusec industry_orig industrycat_isic industrycat10 industrycat4 occup_orig occup_isco occup_skill occup wage_no_compen unitwage whours wmonths wage_total contract healthins socialsec union firmsize_l firmsize_u empstat_2 ocusec_2 industry_orig_2 industrycat_isic_2 industrycat10_2 industrycat4_2 occup_orig_2 occup_isco_2 occup_skill_2 occup_2 wage_no_compen_2 unitwage_2 whours_2 wmonths_2 wage_total_2 firmsize_l_2 firmsize_u_2 t_hours_others t_wage_nocompen_others t_wage_others t_hours_total t_wage_nocompen_total t_wage_total lstatus_year nlfreason_year unempldur_l_year unempldur_u_year empstat_year ocusec_year industry_orig_year industrycat_isic_year industrycat10_year industrycat4_year occup_orig_year occup_isco_year occup_skill_year occup_year unitwage_year whours_year wmonths_year wage_total_year contract_year healthins_year socialsec_year union_year firmsize_l_year firmsize_u_year empstat_2_year ocusec_2_year industry_orig_2_year industrycat_isic_2_year industrycat10_2_year industrycat4_2_year occup_orig_2_year occup_isco_2_year occup_skill_2_year occup_2_year wage_no_compen_2_year unitwage_2_year whours_2_year wmonths_2_year wage_total_2_year firmsize_l_2_year firmsize_u_2_year t_hours_others_year t_wage_nocompen_others_year t_wage_others_year t_hours_total_year t_wage_nocompen_total_year t_wage_total_year njobs t_hours_annual linc_nc laborincome" + + foreach v of local lab_var { + cap confirm numeric variable `v' + if _rc == 0 { // is indeed numeric + replace `v'=. if ( age < minlaborage & !missing(age) ) + } + else { // is not + replace `v'= "" if ( age < minlaborage & !missing(age) ) + } + + } + +* +} + + +/*%%============================================================================================= + 9: Final steps +==============================================================================================%%*/ + +quietly{ + +*<_% KEEP VARIABLES - ALL_> + + keep countrycode survname survey icls_v isced_version isco_version isic_version year vermast veralt harmonization int_year int_month hhid pid weight weight_m weight_q psu ssu strata wave panel visit_no urban subnatid1 subnatid2 subnatid3 subnatidsurvey subnatid1_prev subnatid2_prev subnatid3_prev gaul_adm1_code gaul_adm2_code gaul_adm3_code hsize age male relationharm relationcs marital eye_dsablty hear_dsablty walk_dsablty conc_dsord slfcre_dsablty comm_dsablty migrated_mod_age migrated_ref_time migrated_binary migrated_years migrated_from_urban migrated_from_cat migrated_from_code migrated_from_country migrated_reason ed_mod_age school literacy educy educat7 educat5 educat4 educat_orig educat_isced vocational vocational_type vocational_length_l vocational_length_u vocational_field_orig vocational_financed minlaborage lstatus potential_lf underemployment nlfreason unempldur_l unempldur_u empstat ocusec industry_orig industrycat_isic industrycat10 industrycat4 occup_orig occup_isco occup_skill occup wage_no_compen unitwage whours wmonths wage_total contract healthins socialsec union firmsize_l firmsize_u empstat_2 ocusec_2 industry_orig_2 industrycat_isic_2 industrycat10_2 industrycat4_2 occup_orig_2 occup_isco_2 occup_skill_2 occup_2 wage_no_compen_2 unitwage_2 whours_2 wmonths_2 wage_total_2 firmsize_l_2 firmsize_u_2 t_hours_others t_wage_nocompen_others t_wage_others t_hours_total t_wage_nocompen_total t_wage_total lstatus_year potential_lf_year underemployment_year nlfreason_year unempldur_l_year unempldur_u_year empstat_year ocusec_year industry_orig_year industrycat_isic_year industrycat10_year industrycat4_year occup_orig_year occup_isco_year occup_skill_year occup_year wage_no_compen_year unitwage_year whours_year wmonths_year wage_total_year contract_year healthins_year socialsec_year union_year firmsize_l_year firmsize_u_year empstat_2_year ocusec_2_year industry_orig_2_year industrycat_isic_2_year industrycat10_2_year industrycat4_2_year occup_orig_2_year occup_isco_2_year occup_skill_2_year occup_2_year wage_no_compen_2_year unitwage_2_year whours_2_year wmonths_2_year wage_total_2_year firmsize_l_2_year firmsize_u_2_year t_hours_others_year t_wage_nocompen_others_year t_wage_others_year t_hours_total_year t_wage_nocompen_total_year t_wage_total_year njobs t_hours_annual linc_nc laborincome + +* + +*<_% ORDER VARIABLES_> + + order countrycode survname survey icls_v isced_version isco_version isic_version year vermast veralt harmonization int_year int_month hhid pid weight weight_m weight_q psu ssu strata wave panel visit_no urban subnatid1 subnatid2 subnatid3 subnatidsurvey subnatid1_prev subnatid2_prev subnatid3_prev gaul_adm1_code gaul_adm2_code gaul_adm3_code hsize age male relationharm relationcs marital eye_dsablty hear_dsablty walk_dsablty conc_dsord slfcre_dsablty comm_dsablty migrated_mod_age migrated_ref_time migrated_binary migrated_years migrated_from_urban migrated_from_cat migrated_from_code migrated_from_country migrated_reason ed_mod_age school literacy educy educat7 educat5 educat4 educat_orig educat_isced vocational vocational_type vocational_length_l vocational_length_u vocational_field_orig vocational_financed minlaborage lstatus potential_lf underemployment nlfreason unempldur_l unempldur_u empstat ocusec industry_orig industrycat_isic industrycat10 industrycat4 occup_orig occup_isco occup_skill occup wage_no_compen unitwage whours wmonths wage_total contract healthins socialsec union firmsize_l firmsize_u empstat_2 ocusec_2 industry_orig_2 industrycat_isic_2 industrycat10_2 industrycat4_2 occup_orig_2 occup_isco_2 occup_skill_2 occup_2 wage_no_compen_2 unitwage_2 whours_2 wmonths_2 wage_total_2 firmsize_l_2 firmsize_u_2 t_hours_others t_wage_nocompen_others t_wage_others t_hours_total t_wage_nocompen_total t_wage_total lstatus_year potential_lf_year underemployment_year nlfreason_year unempldur_l_year unempldur_u_year empstat_year ocusec_year industry_orig_year industrycat_isic_year industrycat10_year industrycat4_year occup_orig_year occup_isco_year occup_skill_year occup_year wage_no_compen_year unitwage_year whours_year wmonths_year wage_total_year contract_year healthins_year socialsec_year union_year firmsize_l_year firmsize_u_year empstat_2_year ocusec_2_year industry_orig_2_year industrycat_isic_2_year industrycat10_2_year industrycat4_2_year occup_orig_2_year occup_isco_2_year occup_skill_2_year occup_2_year wage_no_compen_2_year unitwage_2_year whours_2_year wmonths_2_year wage_total_2_year firmsize_l_2_year firmsize_u_2_year t_hours_others_year t_wage_nocompen_others_year t_wage_others_year t_hours_total_year t_wage_nocompen_total_year t_wage_total_year njobs t_hours_annual linc_nc laborincome + +* + +*<_% DROP UNUSED LABELS_> + + * Store all labels in data + label dir + local all_lab `r(names)' + + * Store all variables with a label, extract value label names + local used_lab = "" + ds, has(vallabel) + + local labelled_vars `r(varlist)' + + foreach varName of local labelled_vars { + local y : value label `varName' + local used_lab `"`used_lab' `y'"' + } + + * Compare lists, `notused' is list of labels in directory but not used in final variables + local notused : list all_lab - used_lab // local `notused' defines value labs not in remaining vars + local notused_len : list sizeof notused // store size of local + + * drop labels if the length of the notused vector is 1 or greater, otherwise nothing to drop + if `notused_len' >= 1 { + label drop `notused' + } + else { + di "There are no unused labels to drop. No value labels dropped." + } + + +* + +} + +*<_% DELETE MISSING VARIABLES_> + +quietly: describe, varlist +local kept_vars `r(varlist)' + +foreach var of local kept_vars { + + capture assert missing(`var') + if !_rc drop `var' +} + +* + + +*<_% COMPRESS_> + +compress + +* + + +*<_% SAVE_> + +save "`path_output'/`level_2_harm'_ALL.dta", replace + +* diff --git a/GLD/ARM/ARM_2017_LFS/ARM_2017_LFS_V01_M_V03_A_GLD/Programs/ARM_2017_LFS_V01_M_V03_A_GLD_ALL.do b/GLD/ARM/ARM_2017_LFS/ARM_2017_LFS_V01_M_V03_A_GLD/Programs/ARM_2017_LFS_V01_M_V03_A_GLD_ALL.do new file mode 100644 index 000000000..ac8d49727 --- /dev/null +++ b/GLD/ARM/ARM_2017_LFS/ARM_2017_LFS_V01_M_V03_A_GLD/Programs/ARM_2017_LFS_V01_M_V03_A_GLD_ALL.do @@ -0,0 +1,1840 @@ + +/*%%============================================================================================= + 0: GLD Harmonization Preamble +================================================================================================*/ + +/* ----------------------------------------------------------------------- +<_Program name_> ARM_2017_LFS_V01_M_V03_A_GLD_ALL.do +<_Application_> Stata SE 18 <_Application_> +<_Author(s)_> Wolrd Bank Job's Group +<_Date created_> 2023-12-20 +------------------------------------------------------------------------- +<_Country_> Armenia (ARM) +<_Survey Title_> National Labour Force Survey +<_Survey Year_> 2017 +<_Study ID_> ARM_2017_LFS_v01_M +<_Data collection from (M/Y)_> [01/2017] +<_Data collection to (M/Y)_> [12/2017] +<_Source of dataset_> The Armenian 2017 to 2021 data is downloaded from + the website of Statistical Committee of the + Republic of Armenia:https://armstat.am/en/?nid=212 + The data is publicly available. +<_Sample size (HH)_> 7,783 +<_Sample size (IND)_> 28,463 +<_Sampling method_> A stratified two-stage probability sample design + with 14 domains as the primary strata and 18,000 + households as the SSU. +<_Geographic coverage_> All 11 regions/marzes. +<_Currency_> Armenian Dram +----------------------------------------------------------------------- +<_ICLS Version_> ICLS 13 +<_ISCED Version_> ISCED-2011 +<_ISCO Version_> ISCO 08 +<_OCCUP National_> NSCO +<_ISIC Version_> ISIC Rev.4 +<_INDUS National_> ISIC Rev.4 +----------------------------------------------------------------------- + +<_Version Control_> + +* Date: 2024-09-24 - Update vars educy, educat7 +* Date: 2024-10-09 - Include weight by quarter, correct contract variable + + + +-------------------------------------------------------------------------*/ + + +/*%%============================================================================================= + 1: Setting up of program environment, dataset +================================================================================================*/ + +*----------1.1: Initial commands------------------------------* + +clear +set more off +set mem 800m + +*----------1.2: Set directories------------------------------* + +* Define path sections +local server "Y:/GLD" +local country "ARM" +local year "2017" +local survey "LFS" +local vermast "V01" +local veralt "V03" + +* From the definitions, set path chunks +local level_1 "`country'_`year'_`survey'" +local level_2_mast "`level_1'_`vermast'_M" +local level_2_harm "`level_1'_`vermast'_M_`veralt'_A_GLD" + +* From chunks, define path_in, path_output folder +local path_in_stata "`server'/`country'/`level_1'/`level_2_mast'/Data/Stata" +local path_in_other "`server'/`country'/`level_1'/`level_2_mast'/Data/Original" +local path_output "`server'/`country'/`level_1'/`level_2_harm'/Data/Harmonized" + +* Define Output file name +local out_file "`level_2_harm'_ALL.dta" + + +*----------1.3: Database assembly------------------------------* + +* All steps necessary to merge datasets (if several) to have all elements needed to produce +* harmonized output in a single file + +use "`path_in_stata'/ARM_LFS_2017_raw.dta", clear + + +/*%%============================================================================================= + 2: Survey & ID +================================================================================================*/ + +{ + +*<_countrycode_> + gen str4 countrycode="`country'" + label var countrycode "Country code" +* + + +*<_survname_> + gen survname="LFS" + label var survname "Survey acronym" +* + + +*<_survey_> + gen survey="LFS" + label var survey "Survey type" +* + + +*<_icls_v_> + gen icls_v="ICLS-13" + label var icls_v "ICLS version underlying questionnaire questions" +* + + +*<_isced_version_> + gen isced_version="isced_2011" + label var isced_version "Version of ISCED used for educat_isced" +* + + +*<_isco_version_> + gen isco_version="" + label var isco_version "Version of ISCO used" +* + + +*<_isic_version_> + gen isic_version="" + label var isic_version "Version of ISIC used" +* + + +*<_year_> + gen int year=`year' + label var year "Year of survey" +* + + +*<_vermast_> + gen str3 vermast="`vermast'" + label var vermast "Version of master data" +* + + +*<_veralt_> + gen str3 veralt="`veralt'" + label var veralt "Version of the alt/harmonized data" +* + + +*<_harmonization_> + gen harmonization="GLD" + label var harmonization "Type of harmonization" +* + + +*<_int_year_> + gen int_year=`year' + label var int_year "Year of the interview" +* + + +*<_int_month_> + gen int_month=A6_Month + label de lblint_month 1 "January" 2 "February" 3 "March" 4 "April" 5 "May" 6 "June" 7 "July" 8 "August" 9 "September" 10 "October" 11 "November" 12 "December" + label value int_month lblint_month + label var int_month "Month of the interview" +* + + +*<_hhid_> + tostring A1, gen(hid) format(%03.0f) + tostring A6_Month, gen(month) format(%03.0f) + egen hhid=concat(month hid) + label var hhid "Household id" +* + + +*<_pid_> + sort hhid B12 + bys hhid: gen memberid=_n + tostring memberid, gen(id_str) format(%02.0f) + egen pid=concat(hhid id_str), punct("-") + label var pid "Individual ID" +* + + +*<_weight_> + gen weight=Weights_Year + label var weight "Household sampling weight" +* + + +*<_weight_m_> + gen weight_m = . + label var weight_m "Survey sampling weight to obtain national estimates for each month" +* + + +*<_weight_q_> + egen weight_q = rowtotal(Weight_1 Weight_2 Weight_3 Weight_4) + label var weight_q "Survey sampling weight to obtain national estimates for each quarter" +* + + +*<_psu_> + gen psu=. + label var psu "Primary sampling units" +* + + +*<_ssu_> + gen ssu=hhid + label var ssu "Secondary sampling units" +* + + +*<_strata_> + decode A3, gen(marzname) + decode A5, gen(urbanstat) + gen strata=marzname+" "+urbanstat + label var strata "Strata" +* + + +*<_wave_> + gen wave=. + replace wave=1 if inrange(int_month,1,3) + replace wave=2 if inrange(int_month,4,6) + replace wave=3 if inrange(int_month,7,9) + replace wave=4 if inrange(int_month,10,12) + label var wave "Survey wave" +* + + +*<_panel_> + gen panel="" + label var panel "Panel individual belongs to" +* + + +*<_visit_no_> + gen visit_no=. + label var visit_no "Visit number in panel" +* +} + +/*%%============================================================================================= + 3: Geography +================================================================================================*/ + +{ + +*<_urban_> + gen urban=A5 + recode urban (2=0) + la de lblurban 1 "Urban" 0 "Rural" + label values urban lblurban + label var urban "Location is urban" +* + + +*<_subnatid1_> + gen subnatid1=A3 + tostring subnatid1, replace + replace subnatid1=subnatid1+" - "+marzname + label var subnatid1 "Subnational ID at First Administrative Level" +* + + +*<_subnatid2_> + gen subnatid2=. + label var subnatid2 "Subnational ID at Second Administrative Level" +* + + +*<_subnatid3_> + gen subnatid3=. + label var subnatid3 "Subnational ID at Third Administrative Level" +* + + +*<_subnatidsurvey_> + gen subnatidsurvey=subnatid1+" "+urbanstat + label var subnatidsurvey "Administrative level at which survey is representative" +* + + +*<_subnatid1_prev_> + +/* <_subnatid1_prev_note_> +subnatid1_prev is coded as missing unless the classification used for subnatid1 has changed since the previous survey. + */ + + gen subnatid1_prev=. + label var subnatid1_prev "Classification used for subnatid1 from previous survey" +* + + +*<_subnatid2_prev_> + gen subnatid2_prev=. + label var subnatid2_prev "Classification used for subnatid2 from previous survey" +* + + +*<_subnatid3_prev_> + gen subnatid3_prev=. + label var subnatid3_prev "Classification used for subnatid3 from previous survey" +* + + +*<_gaul_adm1_code_> + gen gaul_adm1_code=. + label var gaul_adm1_code "Global Administrative Unit Layers (GAUL) Admin 1 code" +* + + +*<_gaul_adm2_code_> + gen gaul_adm2_code=. + label var gaul_adm2_code "Global Administrative Unit Layers (GAUL) Admin 2 code" +* + + +*<_gaul_adm3_code_> + gen gaul_adm3_code=. + label var gaul_adm3_code "Global Administrative Unit Layers (GAUL) Admin 3 code" +* + +} + +/*%%============================================================================================= + 4: Demography +================================================================================================*/ + +{ + +*<_hsize_> + bys hhid: egen hsize=max(memberid) + label var hsize "Household size" +* + + +*<_age_> + +/*<_age_note_> + +3 observations in the raw data set have negative (-1) age values. +They were coded as missing values in the harmonization. + +*<_age_note_>*/ + + gen age=Age + replace age=. if Age<0 + replace age=98 if age>98 & age!=. + label var age "Individual age" +* + + +*<_male_> + gen male=B11 + recode male 2=0 + label var male "Sex - Ind is male" + la de lblmale 1 "Male" 0 "Female" + label values male lblmale +* + + +*<_relationharm_> + +/*<_relationharm_note_> + +1 household (5 observations) in the raw data set does not have any household head: 002606 + +During the harmonization, we did not assign household head to the household. +But users can assign household heads based on their relationship to the head and +other characteristics such as gender and age. + +Household "009297" has two "First registered member", meaning it has two heads. +They are both female with close ages: one is 74 and the other is 76. We kept the +younger one as the householdhead and replaced the other one's relationharm to +"other relatives". + +*<_relationharm_note_>*/ + + gen byte relationharm=B12 + recode relationharm (6 9=3) (7 8=4) (10=5) (11=6) + replace relationharm=5 if pid=="009297-02" + + label var relationharm "Relationship to the head of household - Harmonized" + la de lblrelationharm 1 "Head of household" 2 "Spouse" 3 "Children" 4 "Parents" 5 "Other relatives" 6 "Other and non-relatives" + label values relationharm lblrelationharm +*<_relationharm_> + + +*<_relationcs_> + gen relationcs=B12 + label var relationcs "Relationship to the head of household - Country original" +* + + +*<_marital_> + gen marital=B16 + recode marital (1=2) (2=1) (3=5) + label var marital "Marital status" + la de lblmarital 1 "Married" 2 "Never Married" 3 "Living together" 4 "Divorced/Separated" 5 "Widowed" + label values marital lblmarital +* + + +*<_eye_dsablty_> + gen eye_dsablty=. + la de lbleye_dsablty 1 "No" 2 "Yes-some" 3 "Yes-a lot" 4 "Cannot at all" + label values eye_dsablty lbleye_dsablty + label var eye_dsablty "Disability related to eyesight" +* + + +*<_hear_dsablty_> + gen hear_dsablty=. + la de lblhear_dsablty 1 "No" 2 "Yes-some" 3 "Yes-a lot" 4 "Cannot at all" + label values hear_dsablty lblhear_dsablty + label var hear_dsablty "Disability related to hearing" +* + + +*<_walk_dsablty_> + gen walk_dsablty=. + la de lblwalk_dsablty 1 "No" 2 "Yes-some" 3 "Yes-a lot" 4 "Cannot at all" + label values walk_dsablty lblwalk_dsablty + label var walk_dsablty "Disability related to walking or climbing stairs" +* + + +*<_conc_dsord_> + gen conc_dsord=. + la de lblconc_dsord 1 "No" 2 "Yes-some" 3 "Yes-a lot" 4 "Cannot at all" + label values conc_dsord lblconc_dsord + label var conc_dsord "Disability related to concentration or remembering" +* + + +*<_slfcre_dsablty_> + gen slfcre_dsablty=. + la de lblslfcre_dsablty 1 "No" 2 "Yes-some" 3 "Yes-a lot" 4 "Cannot at all" + label values slfcre_dsablty lblslfcre_dsablty + label var eye_dsablty "Disability related to selfcare" +* + + +*<_comm_dsablty_> + gen comm_dsablty=. + la de lblcomm_dsablty 1 "No" 2 "Yes-some" 3 "Yes-a lot" 4 "Cannot at all" + label values comm_dsablty lblcomm_dsablty + label var eye_dsablty "Disability related to communicating" +* + +} + + +/*%%============================================================================================= + 5: Migration +================================================================================================*/ + +{ +*<_migrated_mod_age_> + gen migrated_mod_age=. + label var migrated_mod_age "Migration module application age" +* + + +*<_migrated_ref_time_> + gen migrated_ref_time=. + label var migrated_ref_time "Reference time applied to migration questions (in years)" +* + + +*<_migrated_binary_> + gen migrated_binary=. + label de lblmigrated_binary 0 "No" 1 "Yes" + replace migrated_binary=. if age + +*<_migrated_years_> + gen migrated_years=. + replace migrated_years=. if migrated_binary!=1 + replace migrated_years=. if age + + +*<_migrated_from_urban_> + gen migrated_from_urban=. + replace migrated_from_urban=. if age + + +*<_migrated_from_cat_> + gen migrated_from_cat=. + replace migrated_from_cat=. if age + + +*<_migrated_from_code_> + gen migrated_from_code="" + replace migrated_from_code="" if age + + +*<_migrated_from_country_> + gen migrated_from_country="" + replace migrated_from_country="" if migrated_binary!=1 + replace migrated_from_country="" if age + + +*<_migrated_reason_> + gen migrated_reason=. + replace migrated_reason=. if migrated_binary!=1 + replace migrated_reason=. if age +} + + +/*%%============================================================================================= + 6: Education +================================================================================================*/ + + +{ +*<_ed_mod_age_> + gen byte ed_mod_age=6 + label var ed_mod_age "Education module application age" +* + + +*<_school_> + gen school=. + replace school=. if age + + +*<_literacy_> + gen byte literacy=. + replace literacy=0 if B15==1 + replace literacy=1 if inrange(B15,2,9) + replace literacy=. if age + + +*<_educy_> + gen byte educy=. + replace educy = 0 if B15 == 1 | B15 == 2 + replace educy = 4 if B15 == 3 + replace educy = 9 if B15 == 4 + replace educy = 12 if B15 == 5 + replace educy = 11 if B15 == 6 + replace educy = 15 if B15 == 7 + replace educy = 16 if B15 == 8 + replace educy = 20 if B15 == 9 + replace educy=. if ageage & !mi(educy) & !mi(age) + label var educy "Years of education" +* + + +*<_educat7_> + gen byte educat7= B15 + recode educat7 (6=5) (7=6) (8/9=7) + replace educat7=. if age + + +*<_educat5_> + gen byte educat5=educat7 + recode educat5 (4=3) (5=4) (6 7=5) + replace educat5=. if age + + +*<_educat4_> + gen byte educat4=educat5 + replace educat4=. if age + + +*<_educat_orig_> + gen educat_orig=B15 + label var educat_orig "Original survey education code" +* + + +*<_educat_isced_> + gen educat_isced=. + label var educat_isced "ISCED standardised level of education" +* + + +*<_educat_isced_v_> + gen educat_isced_v="ISCED-2011" + label var educat_isced_v "Version of the ISCED used" +* + +*----------6.1: Education cleanup------------------------------* + +*<_% Correction min age_> + +** Drop info for cases under the age for which questions to be asked (do not need a variable for this) +local ed_var school literacy educy educat7 educat5 educat4 educat_isced +foreach v of local ed_var { + replace `v'=. if ( age < ed_mod_age & !missing(age) ) +} +replace educat_isced_v="." if ( age < ed_mod_age & !missing(age) ) +* + +} + +/*%%============================================================================================= + 7: Training +================================================================================================*/ + +{ + +*<_vocational_> + gen vocational=. + la de vocationallbl 1 "Yes" 0 "No" + la values vocational vocationallbl + label var vocational "Ever received vocational training" +* + + +*<_vocational_type_> + gen vocational_type=. + label de lblvocational_type 1 "Inside Enterprise" 2 "External" + label values vocational_type lblvocational_type + label var vocational_type "Type of vocational training" +* + + +*<_vocational_length_l_> + gen vocational_length_l=. + replace vocational_length_l=. if vocational!=1 + label var vocational_length_l "Length of training in months, lower limit" +* + + +*<_vocational_length_u_> + gen vocational_length_u=. + replace vocational_length_u=. if vocational!=1 + label var vocational_length_u "Length of training in months, upper limit" +* + + +*<_vocational_field_orig_> + gen vocational_field_orig=. + replace vocational_field_orig=. if vocational!=1 + label var vocational_field_orig "Original field of training information" +* + + +*<_vocational_financed_> + gen vocational_financed=. + label de lblvocational_financed 1 "Employer" 2 "Government" 3 "Mixed Employer/Government" 4 "Own funds" 5 "Other" + label var vocational_financed "How training was financed" +* + +} + +/*%%============================================================================================= + 8: Labour +================================================================================================*/ + +*<_minlaborage_> + +/*<_minlaborage_note_> + +The age range for the labor section is 15-75. + +*<_minlaborage_note_>*/ + + gen byte minlaborage=15 + label var minlaborage "Labor module application age" +* + + +*----------8.1: 7 day reference overall------------------------------* + +{ +*<_lstatus_> + +/*<_lstatus_note> + +According to the national definition of Armenia, the economically inavtive population +includes + +1)full-time pupils and students +2)housekeepers +3)pensioners +4)other jobless peope including conscripts + +And the economically inavtive population also needs to be within the age range of +15 and 75. +*<_lstatus_note>*/ + + gen byte lstatus=. + replace lstatus=1 if G1==1|inrange(G3,1,5)|inrange(G4,1,2) + replace lstatus=2 if lstatus==.&inrange(Z57,1,2) + replace lstatus=3 if !mi(Z49_4group)&lstatus==. + replace lstatus=. if !inrange(age,15,75) + label var lstatus "Labor status" + la de lbllstatus 1 "Employed" 2 "Unemployed" 3 "Non-LF" + label values lstatus lbllstatus +* + + +*<_potential_lf_> + +/*<_potential_lf_note_> +Note: var "potential_lf" only takes value if the respondent is not in labor force. (lstatus==3) + +"potential_lf"=1 if the person is +1)available but not searching or inrange(E45,1,3) & (Z57==2) +2)searching but not immediately available to work or Z57==1 & inlist(E45,4,6) + +*/ + + gen potential_lf=. + replace potential_lf=1 if [inrange(E45,1,3) & (Z57==2)] | [Z57==1 & inlist(E45,4,6)] + replace potential_lf=0 if [inrange(E45,1,3) & (Z57==1)] | [Z57==1 & inrange(E45,1,3)] + replace potential_lf=. if age75&!mi(age)] + replace potential_lf=. if lstatus!=3 + label var potential_lf "Potential labour force status" + la de lblpotential_lf 0 "No" 1 "Yes" + label values potential_lf lblpotential_lf +* + + +*<_underemployment_> + gen byte underemployment=E41 + replace underemployment=1 if inrange(E41,1,3) + replace underemployment=0 if E41==4 + replace underemployment=. if age75&!mi(age)] + replace underemployment=. if lstatus!=1 + label var underemployment "Underemployment status" + la de lblunderemployment 0 "No" 1 "Yes" + label values underemployment lblunderemployment +* + + +*<_nlfreason_> + gen byte nlfreason=Z49_4group + recode nlfreason (4=5) + replace nlfreason=. if age75&!mi(age)] + replace nlfreason=. if lstatus!=3 + label var nlfreason "Reason not in the labor force" + la de lblnlfreason 1 "Student" 2 "Housekeeper" 3 "Retired" 4 "Disabled" 5 "Other" + label values nlfreason lblnlfreason +* + + +*<_unempldur_l_> + gen byte unempldur_l=Z52 + recode unempldur_l (1=0) (2=3) (3=12) (4=24) (5=36) + replace unempldur_l=. if age75&!mi(age)] + replace unempldur_l=. if lstatus!=2 + label var unempldur_l "Unemployment duration (months) lower bracket" +* + + +*<_unempldur_u_> + gen byte unempldur_u=Z52 + recode unempldur_u (1=3) (2=12) (3=24) (4=36) (5=.) + replace unempldur_u=. if age75&!mi(age)] + replace unempldur_u=. if lstatus!=2 + label var unempldur_u "Unemployment duration (months) upper bracket" +* +} + + +*----------8.2: 7 day reference main job------------------------------* + + +{ +*<_empstat_> + gen byte empstat=D8 + recode empstat (2 7=1) (5=4) (6=2) (8=5) + replace empstat=. if lstatus!=1|age + + +*<_ocusec_> + gen byte ocusec=D11 + recode ocusec (3 4=2) + replace ocusec=. if lstatus!=1|age + + +*<_industry_orig_> + gen industry_orig=D6_21group + replace industry_orig=. if lstatus!=1 + label var industry_orig "Original survey industry code, main job 7 day recall" +* + + +*<_industrycat_isic_> + gen industrycat_isic="" +quietly +{ + replace industrycat_isic="A" if D6_21group==1 + replace industrycat_isic="B" if D6_21group==2 + replace industrycat_isic="C" if D6_21group==3 + replace industrycat_isic="D" if D6_21group==4 + replace industrycat_isic="E" if D6_21group==5 + replace industrycat_isic="F" if D6_21group==6 + replace industrycat_isic="G" if D6_21group==7 + replace industrycat_isic="H" if D6_21group==8 + replace industrycat_isic="I" if D6_21group==9 + replace industrycat_isic="J" if D6_21group==10 + replace industrycat_isic="K" if D6_21group==11 + replace industrycat_isic="L" if D6_21group==12 + replace industrycat_isic="M" if D6_21group==13 + replace industrycat_isic="N" if D6_21group==14 + replace industrycat_isic="O" if D6_21group==15 + replace industrycat_isic="P" if D6_21group==16 + replace industrycat_isic="Q" if D6_21group==17 + replace industrycat_isic="R" if D6_21group==18 + replace industrycat_isic="S" if D6_21group==19 + replace industrycat_isic="T" if D6_21group==20 + replace industrycat_isic="U" if D6_21group==21 +} + + replace industrycat_isic="" if industrycat_isic=="."|lstatus!=1 + label var industrycat_isic "ISIC code of primary job 7 day recall" +* + + +*<_industrycat10_> + gen industrycat10=D6_21group + recode industrycat10 (5=4) (6=5) (7 9=6) (8 10=7) (11/14=8) (15=9) (16/21=10) + replace industrycat10=. if lstatus!=1 + label var industrycat10 "1 digit industry classification, primary job 7 day recall" + la de lblindustrycat10 1 "Agriculture" 2 "Mining" 3 "Manufacturing" 4 "Public utilities" 5 "Construction" 6 "Commerce" 7 "Transport and Comnunications" 8 "Financial and Business Services" 9 "Public Administration" 10 "Other Services, Unspecified" + label values industrycat10 lblindustrycat10 +* + + +*<_industrycat4_> + gen byte industrycat4=industrycat10 + recode industrycat4 (3/5=2)(6/9=3)(10=4) + label var industrycat4 "1 digit industry classification (Broad Economic Activities), primary job 7 day recall" + la de lblindustrycat4 1 "Agriculture" 2 "Industry" 3 "Services" 4 "Other" + label values industrycat4 lblindustrycat4 +* + + +*<_occup_orig_> + gen occup_orig=D5_9group + replace occup_orig=. if lstatus!=1|[age>75&!mi(age)] + label var occup_orig "Original occupation record primary job 7 day recall" +* + + +*<_occup_isco_> + gen occup_isco="" + replace occup_isco="" if lstatus!=1 | occup_isco=="." + label var occup_isco "ISCO code of primary job 7 day recall" +* + + +*<_occup_skill_> + gen occup_skill=D5_9group + replace occup_skill=1 if D5_9group==9 + replace occup_skill=2 if inrange(D5_9group, 4, 8) + replace occup_skill=3 if inrange(D5_9group, 1, 3) + replace occup_skill=. if lstatus!=1 + la de lblskill 1 "Low skill" 2 "Medium skill" 3 "High skill" + label values occup_skill lblskill + label var occup_skill "Skill based on ISCO standard primary job 7 day recall" +* + + +*<_occup_> + gen occup=D5_9group + replace occup=. if lstatus!=1|[age>75&!mi(age)] + label var occup "1 digit occupational classification, primary job 7 day recall" + la de lbloccup 1 "Managers" 2 "Professionals" 3 "Technicians" 4 "Clerks" 5 "Service and market sales workers" 6 "Skilled agricultural" 7 "Craft workers" 8 "Machine operators" 9 "Elementary occupations" 10 "Armed forces" 99 "Others" + label values occup lbloccup +* + + +*<_wage_no_compen_> + +/*<_wage_no_compen_note_> + +The wage questions in the questionnare are organized into to parts: the first part +asks for the specific number of income if the given respondent could recall and was +willing to answer; the second part provides different categories of income range +if the given respondent could not recall or was not willing to answer the first part. + +The general logic here is to impute wage values for people who only answered an income +range. We used industry, occupation, income categories and gender to estimate their +specific income values. + +16.23% of total non-missing wage values were imputed using this method. + +*<_wage_no_compen_note_>*/ + + * Overall --> wage info (here the variable, for us it should be wage_no_compen) + * to missing if value is 0. + gen wage14=D14_1+D14_2 + replace wage14=. if wage14==0 + + * First replace outliers by + winsor2 wage14, suffix(_w) cuts(1 99) + + * Create salary categories based on winsor values + gen salary_cat=. + replace salary_cat=1 if inrange(wage14_w, 1, 55000) + replace salary_cat=2 if wage14_w==55000 + replace salary_cat=3 if inrange(wage14_w, 55001, 110000) + replace salary_cat=4 if inrange(wage14_w, 110001, 220000) + replace salary_cat=5 if inrange(wage14_w, 220001, 440000) + replace salary_cat=6 if inrange(wage14_w, 440001, 600000) + replace salary_cat=7 if inrange(wage14_w, 600001, 700000) + replace salary_cat=8 if inrange(wage14_w, 700000, 99999999) + + * Preserve to collapse, so we can merge the info in + preserve + + * Collpase by industry, sex, and salary categories + collapse (mean)wage14_w[iw=weight], by(industrycat10 occup male urban salary_cat) + + * Rename variable, otherwise when merging in, master version of an equally name one will be kept + rename wage14_w wage_group_estimate + + * Rename salary_cat to D15 since this is what we want the info to latch on to + rename salary_cat D15 + tempfile salary_helper + save "`salary_helper'" + + * Restore, merge in + restore + merge m:1 industrycat10 occup male urban D15 using "`salary_helper'", keep(matched master) nogen + + * Create wage variable + gen wage_no_compen=. + + * Fill it first with values that are accurate + replace wage_no_compen=wage14 if !mi(wage14)&mi(D15) + + * Now add the categorised means + replace wage_no_compen=wage_group_estimate if inrange(D15,1,8)&!mi(wage_group_estimate) + + * Keep only for employed employees, label + replace wage_no_compen=. if lstatus!=1|empstat==2 + label var wage_no_compen "Last wage payment primary job 7 day recall" + +* + + +*<_unitwage_> + gen byte unitwage=D16 + recode unitwage (4=5) (5=7) (6=8) (7=10) + replace unitwage=. if lstatus!=1 | empstat==2 + label var unitwage "Last wages' time unit primary job 7 day recall" + la de lblunitwage 1 "Daily" 2 "Weekly" 3 "Every two weeks" 4 "Bimonthly" 5 "Monthly" 6 "Trimester" 7 "Biannual" 8 "Annually" 9 "Hourly" 10 "Other" + label values unitwage lblunitwage +* + + +*<_whours_> + gen whours=E39_1 + replace whours=. if lstatus!=1|E39_1==0 + label var whours "Hours of work in last week primary job 7 day recall" +* + + +*<_wmonths_> + gen wmonths=. + label var wmonths "Months of work in past 12 months primary job 7 day recall" +* + + +*<_wage_total_> + gen wage_total=. + label var wage_total "Annualized total wage primary job 7 day recall" +* + + +*<_contract_> + +/*<_contract_note_> + +There is no separate contract question in the questionnaire. +This contract variable was coded based on employment status question which asks +wether an employed respondent had a contract or not. + +*<_contract_note_>*/ + + gen byte contract = . + replace contract = (D8 == 1) + replace contract=. if lstatus != 1 + label var contract "Employment has contract primary job 7 day recall" + la de lblcontract 0 "Without contract" 1 "With contract" + label values contract lblcontract +* + + +*<_healthins_> + gen byte healthins=. + replace healthins=1 if D9_6==1 + replace healthins=0 if D9_6==2 + replace healthins=. if lstatus!=1 + label var healthins "Employment has health insurance primary job 7 day recall" + la de lblhealthins 0 "Without health insurance" 1 "With health insurance" + label values healthins lblhealthins +* + + +*<_socialsec_> + gen byte socialsec=. + replace socialsec=. if lstatus!=1 + label var socialsec "Employment has social security insurance primary job 7 day recall" + la de lblsocialsec 1 "With social security" 0 "Without social secturity" + label values socialsec lblsocialsec +* + + +*<_union_> + gen byte union=. + replace union=1 if D23==1 + replace union=0 if D23==2 + replace union=. if lstatus!=1 + label var union "Union membership at primary job 7 day recall" + la de lblunion 0 "Not union member" 1 "Union member" + label values union lblunion +* + + +*<_firmsize_l_> + gen byte firmsize_l=D13a + recode firmsize_l (1=1) (2=5) (3=10) (4=20) (5=50) (6=100) (7=.) + replace firmsize_l=. if lstatus!=1 + label var firmsize_l "Firm size (lower bracket) primary job 7 day recall" +* + + +*<_firmsize_u_> + gen byte firmsize_u=D13a + recode firmsize_u (1=5) (2=9) (3=19) (4=49) (5=99) (6=.) + replace firmsize_u=. if lstatus!=1 + label var firmsize_u "Firm size (upper bracket) primary job 7 day recall" +* + +} + + +*----------8.3: 7 day reference secondary job------------------------------* +* Since labels are the same as main job, values are labelled using main job labels + +{ +*<_empstat_2_> + gen byte empstat_2=E27 + recode empstat_2 (2 7=1) (5=4) (6=2) + replace empstat_2=. if lstatus!=1|E24!=1 + label var empstat_2 "Employment status during past week secondary job 7 day recall" + la de lblempstat_2 1 "Paid employee" 2 "Non-paid employee" 3 "Employer" 4 "Self-employed" 5 "Other, workers not classifiable by status" + label values empstat_2 lblempstat +* + + +*<_ocusec_2_> + gen byte ocusec_2=E29 + recode ocusec_2 (3 4=2) + replace ocusec_2=. if lstatus!=1|E24!=1 + label var ocusec_2 "Sector of activity secondary job 7 day recall" + la de lblocusec_2 1 "Public Sector, Central Government, Army" 2 "Private, NGO" 3 "State owned" 4 "Public or State-owned, but cannot distinguish" + label values ocusec_2 lblocusec_2 +* + + +*<_industry_orig_2_> + gen industry_orig_2=E26_21group + replace industry_orig_2=. if lstatus!=1|E24!=1 + label var industry_orig_2 "Original survey industry code, secondary job 7 day recall" +* + + +*<_industrycat_isic_2_> + gen industrycat_isic_2="" +quietly +{ + replace industrycat_isic_2="A" if E26_21group==1 + replace industrycat_isic_2="B" if E26_21group==2 + replace industrycat_isic_2="C" if E26_21group==3 + replace industrycat_isic_2="D" if E26_21group==4 + replace industrycat_isic_2="E" if E26_21group==5 + replace industrycat_isic_2="F" if E26_21group==6 + replace industrycat_isic_2="G" if E26_21group==7 + replace industrycat_isic_2="H" if E26_21group==8 + replace industrycat_isic_2="I" if E26_21group==9 + replace industrycat_isic_2="J" if E26_21group==10 + replace industrycat_isic_2="K" if E26_21group==11 + replace industrycat_isic_2="L" if E26_21group==12 + replace industrycat_isic_2="M" if E26_21group==13 + replace industrycat_isic_2="N" if E26_21group==14 + replace industrycat_isic_2="O" if E26_21group==15 + replace industrycat_isic_2="P" if E26_21group==16 + replace industrycat_isic_2="Q" if E26_21group==17 + replace industrycat_isic_2="R" if E26_21group==18 + replace industrycat_isic_2="S" if E26_21group==19 + replace industrycat_isic_2="T" if E26_21group==20 + replace industrycat_isic_2="U" if E26_21group==21 +} + + replace industrycat_isic_2="" if industrycat_isic_2=="."|E24!=1 + label var industrycat_isic_2 "ISIC code of secondary job 7 day recall" +* + + +*<_industrycat10_2_> + gen industrycat10_2=E26_21group + recode industrycat10_2 (5=4) (6=5) (7 9=6) (8 10=7) (11/14=8) (15=9) (16/21=10) + replace industrycat10_2=. if lstatus!=1|E24!=1 + label var industrycat10_2 "1 digit industry classification, secondary job 7 day recall" + label values industrycat10_2 lblindustrycat10 +* + + +*<_industrycat4_2_> + gen byte industrycat4_2=industrycat10_2 + recode industrycat4_2 (3/5=2)(6/9=3)(10=4) + label var industrycat4_2 "1 digit industry classification (Broad Economic Activities), secondary job 7 day recall" + label values industrycat4_2 lblindustrycat4 +* + + +*<_occup_orig_2_> + gen occup_orig_2=E25_9group + replace occup_orig_2=. if lstatus!=1|E24!=1 + label var occup_orig_2 "Original occupation record secondary job 7 day recall" +* + + +*<_occup_isco_2_> + gen occup_isco_2="" + replace occup_isco_2="" if lstatus!=1 | occup_isco_2=="."|E24!=1 + label var occup_isco_2 "ISCO code of secondary job 7 day recall" +* + + +*<_occup_skill_2_> + gen occup_skill_2=E25_9group + replace occup_skill_2=1 if E25_9group==9 + replace occup_skill_2=2 if inrange(E25_9group,4,8) + replace occup_skill_2=3 if inrange(E25_9group,1,3) + replace occup_skill_2=. if E25_9group==0|lstatus!=1|E24!=1 + label var occup_skill_2 "Skill based on ISCO standard secondary job 7 day recall" +* + + +*<_occup_2_> + gen occup_2=E25_9group + replace occup_2=. if lstatus!=1|E24!=1 + label var occup_2 "1 digit occupational classification secondary job 7 day recall" + label values occup_2 lbloccup +* + + +*<_wage_no_compen_2_> + + gen wage32=E32_1+E32_2 + replace wage32=. if wage32==0 + + * First replace outliers by + winsor2 wage32, suffix(_w) cuts(1 99) + + * Create salary categories based on winsor values + gen salary_cat2=. + replace salary_cat2=1 if inrange(wage32_w, 1, 55000) + replace salary_cat2=3 if inrange(wage32_w, 55001, 110000) + replace salary_cat2=4 if inrange(wage32_w, 110001, 220000) + + * Preserve to collapse, so we can merge the info in + preserve + + * Collpase by industry, sex, and salary categories + collapse (mean)wage32_w[iw=weight], by(industrycat10_2 occup_2 male urban salary_cat2) + + * Rename variable, otherwise when merging in, master version of an equally name one will be kept + rename wage32_w wage_group_estimate2 + + * Rename salary_cat to D15 since this is what we want the info to latch on to + rename salary_cat2 E33 + tempfile salary_helper2 + save "`salary_helper2'" + + * Restore, merge in + restore + merge m:1 industrycat10_2 occup_2 male urban E33 using "`salary_helper2'", keep(matched master) nogen + + * Create wage variable + gen wage_no_compen_2=. + + * Fill it first with values that are accurate + replace wage_no_compen_2=wage32 if !mi(wage32)&mi(E33) + + * Now add the categorised means + replace wage_no_compen_2=wage_group_estimate2 if inrange(E33,1,5)&!mi(wage_group_estimate2) + + * Keep only for employed employees, label + replace wage_no_compen_2=. if E24!=1|empstat_2==2 + label var wage_no_compen_2 "Last wage payment secondary job 7 day recall" +* + + +*<_unitwage_2_> + gen byte unitwage_2=E34 + recode unitwage_2 (4=5) (5=7) (6=8) (7=10) + replace unitwage_2=. if lstatus!=1|E24!=1 + label var unitwage_2 "Last wages' time unit secondary job 7 day recall" + label values unitwage_2 lblunitwage +* + + +*<_whours_2_> + gen whours_2=E38_2 + replace whours_2=. if E38_2==0|E24!=1 + label var whours_2 "Hours of work in last week secondary job 7 day recall" +* + + +*<_wmonths_2_> + gen wmonths_2=. + label var wmonths_2 "Months of work in past 12 months secondary job 7 day recall" +* + + +*<_wage_total_2_> + gen wage_total_2=. + label var wage_total_2 "Annualized total wage secondary job 7 day recall" +* + + +*<_firmsize_l_2_> + gen byte firmsize_l_2=. + label var firmsize_l_2 "Firm size (lower bracket) secondary job 7 day recall" +* + + +*<_firmsize_u_2_> + gen byte firmsize_u_2=. + label var firmsize_u_2 "Firm size (upper bracket) secondary job 7 day recall" +* + +} + +*----------8.4: 7 day reference additional jobs------------------------------* + +*<_t_hours_others_> + gen t_hours_others=. + label var t_hours_others "Annualized hours worked in all but primary and secondary jobs 7 day recall" +* + + +*<_t_wage_nocompen_others_> + gen t_wage_nocompen_others=. + label var t_wage_nocompen_others "Annualized wage in all but primary & secondary jobs excl. bonuses, etc. 7 day recall" +* + + +*<_t_wage_others_> + gen t_wage_others=. + label var t_wage_others "Annualized wage in all but primary and secondary jobs (12-mon ref period)" +* + + +*----------8.5: 7 day reference total summary------------------------------* + + +*<_t_hours_total_> + gen t_hours_total=. + label var t_hours_total "Annualized hours worked in all jobs 7 day recall" +* + + +*<_t_wage_nocompen_total_> + gen t_wage_nocompen_total=. + label var t_wage_nocompen_total "Annualized wage in all jobs excl. bonuses, etc. 7 day recall" +* + + +*<_t_wage_total_> + gen t_wage_total=. + label var t_wage_total "Annualized total wage for all jobs 7 day recall" +* + + +*----------8.6: 12 month reference overall------------------------------* + +{ +*<_lstatus_year_> + gen byte lstatus_year=. + replace lstatus_year=. if age + + +*<_potential_lf_year_> + gen byte potential_lf_year=. + replace potential_lf_year=. if age + + +*<_underemployment_year_> + gen byte underemployment_year=. + replace underemployment_year=. if age + + +*<_nlfreason_year_> + gen byte nlfreason_year=. + label var nlfreason_year "Reason not in the labor force" + la de lblnlfreason_year 1 "Student" 2 "Housekeeper" 3 "Retired" 4 "Disable" 5 "Other" + label values nlfreason_year lblnlfreason_year +* + + +*<_unempldur_l_year_> + gen byte unempldur_l_year=. + label var unempldur_l_year "Unemployment duration (months) lower bracket" +* + + +*<_unempldur_u_year_> + gen byte unempldur_u_year=. + label var unempldur_u_year "Unemployment duration (months) upper bracket" +* + +} + +*----------8.7: 12 month reference main job------------------------------* + +{ +*<_empstat_year_> + gen byte empstat_year=. + label var empstat_year "Employment status during past week primary job 12 month recall" + la de lblempstat_year 1 "Paid employee" 2 "Non-paid employee" 3 "Employer" 4 "Self-employed" 5 "Other, workers not classifiable by status" + label values empstat_year lblempstat_year +* + + +*<_ocusec_year_> + gen byte ocusec_year=. + label var ocusec_year "Sector of activity primary job 12 day recall" + la de lblocusec_year 1 "Public Sector, Central Government, Army" 2 "Private, NGO" 3 "State owned" 4 "Public or State-owned, but cannot distinguish" + label values ocusec_year lblocusec_year +* + + +*<_industry_orig_year_> + gen industry_orig_year=. + label var industry_orig_year "Original industry record main job 12 month recall" +* + + +*<_industrycat_isic_year_> + gen industrycat_isic_year="" + replace industrycat_isic_year="" if industrycat_isic_year=="." + label var industrycat_isic_year "ISIC code of primary job 12 month recall" +* + + +*<_industrycat10_year_> + gen byte industrycat10_year=. + label var industrycat10_year "1 digit industry classification, primary job 12 month recall" + la de lblindustrycat10_year 1 "Agriculture" 2 "Mining" 3 "Manufacturing" 4 "Public utilities" 5 "Construction" 6 "Commerce" 7 "Transport and Comnunications" 8 "Financial and Business Services" 9 "Public Administration" 10 "Other Services, Unspecified" + label values industrycat10_year lblindustrycat10_year +* + + +*<_industrycat4_year_> + gen byte industrycat4_year=industrycat10_year + recode industrycat4_year (1=1)(2 3 4 5 =2)(6 7 8 9=3)(10=4) + label var industrycat4_year "1 digit industry classification (Broad Economic Activities), primary job 12 month recall" + la de lblindustrycat4_year 1 "Agriculture" 2 "Industry" 3 "Services" 4 "Other" + label values industrycat4_year lblindustrycat4_year +* + + +*<_occup_orig_year_> + gen occup_orig_year=. + label var occup_orig_year "Original occupation record primary job 12 month recall" +* + + +*<_occup_isco_year_> + gen str4 occup_isco_year="" + label var occup_isco_year "ISCO code of primary job 12 month recall" +* + + +*<_occup_skill_year_> + gen skill_level_year=substr(occup_isco_year,1,1) + destring skill_level_year, replace + gen occup_skill_year=. + replace occup_skill_year=1 if skill_level_year==9 + replace occup_skill_year=2 if inrange(skill_level_year,4,8) + replace occup_skill_year=3 if inrange(skill_level_year,1,3) + replace occup_skill_year=. if skill_level_year==0 + label var occup_skill_year "Skill based on ISCO standard primary job 12 month recall" +* + + +*<_occup_year_> + gen byte occup_year=. + label var occup_year "1 digit occupational classification, primary job 12 month recall" + la de lbloccup_year 1 "Managers" 2 "Professionals" 3 "Technicians" 4 "Clerks" 5 "Service and market sales workers" 6 "Skilled agricultural" 7 "Craft workers" 8 "Machine operators" 9 "Elementary occupations" 10 "Armed forces" 99 "Others" + label values occup_year lbloccup_year +* + + +*<_wage_no_compen_year_> + gen double wage_no_compen_year=. + label var wage_no_compen_year "Last wage payment primary job 12 month recall" +* + + +*<_unitwage_year_> + gen byte unitwage_year=. + label var unitwage_year "Last wages' time unit primary job 12 month recall" + la de lblunitwage_year 1 "Daily" 2 "Weekly" 3 "Every two weeks" 4 "Bimonthly" 5 "Monthly" 6 "Trimester" 7 "Biannual" 8 "Annually" 9 "Hourly" 10 "Other" + label values unitwage_year lblunitwage_year +* + + +*<_whours_year_> + gen whours_year=. + label var whours_year "Hours of work in last week primary job 12 month recall" +* + + +*<_wmonths_year_> + gen wmonths_year=. + label var wmonths_year "Months of work in past 12 months primary job 12 month recall" +* + + +*<_wage_total_year_> + gen wage_total_year=. + label var wage_total_year "Annualized total wage primary job 12 month recall" +* + + +*<_contract_year_> + gen byte contract_year=. + label var contract_year "Employment has contract primary job 12 month recall" + la de lblcontract_year 0 "Without contract" 1 "With contract" + label values contract_year lblcontract_year +* + + +*<_healthins_year_> + gen byte healthins_year=. + label var healthins_year "Employment has health insurance primary job 12 month recall" + la de lblhealthins_year 0 "Without health insurance" 1 "With health insurance" + label values healthins_year lblhealthins_year +* + + +*<_socialsec_year_> + gen byte socialsec_year=. + label var socialsec_year "Employment has social security insurance primary job 7 day recall" + la de lblsocialsec_year 1 "With social security" 0 "Without social secturity" + label values socialsec_year lblsocialsec_year +* + + +*<_union_year_> + gen byte union_year=. + label var union_year "Union membership at primary job 12 month recall" + la de lblunion_year 0 "Not union member" 1 "Union member" + label values union_year lblunion_year +* + + +*<_firmsize_l_year_> + gen byte firmsize_l_year=. + label var firmsize_l_year "Firm size (lower bracket) primary job 12 month recall" +* + + +*<_firmsize_u_year_> + gen byte firmsize_u_year=. + label var firmsize_u_year "Firm size (upper bracket) primary job 12 month recall" +* + +} + + +*----------8.8: 12 month reference secondary job------------------------------* + +{ + +*<_empstat_2_year_> + gen byte empstat_2_year=. + label var empstat_2_year "Employment status during past week secondary job 12 month recall" + label values empstat_2_year lblempstat_year +* + + +*<_ocusec_2_year_> + gen byte ocusec_2_year=. + label var ocusec_2_year "Sector of activity secondary job 12 day recall" + la de lblocusec_2_year 1 "Public Sector, Central Government, Army" 2 "Private, NGO" 3 "State owned" 4 "Public or State-owned, but cannot distinguish" + label values ocusec_2_year lblocusec_2_year +* + + + +*<_industry_orig_2_year_> + gen industry_orig_2_year=. + label var industry_orig_2_year "Original survey industry code, secondary job 12 month recall" +* + + + +*<_industrycat_isic_2_year_> + gen industrycat_isic_2_year=. + label var industrycat_isic_2_year "ISIC code of secondary job 12 month recall" +* + + +*<_industrycat10_2_year_> + gen byte industrycat10_2_year=. + label var industrycat10_2_year "1 digit industry classification, secondary job 12 month recall" + label values industrycat10_2_year lblindustrycat10_year +* + + +*<_industrycat4_2_year_> + gen byte industrycat4_2_year=industrycat10_2_year + recode industrycat4_2_year (1=1)(2 3 4 5 =2)(6 7 8 9=3)(10=4) + label var industrycat4_2_year "1 digit industry classification (Broad Economic Activities), secondary job 12 month recall" + label values industrycat4_2_year lblindustrycat4_year +* + + +*<_occup_orig_2_year_> + gen occup_orig_2_year=. + label var occup_orig_2_year "Original occupation record secondary job 12 month recall" +* + + +*<_occup_isco_2_year_> + gen occup_isco_2_year=. + label var occup_isco_2_year "ISCO code of secondary job 12 month recall" +* + + +*<_occup_skill_2_year_> + gen occup_skill_2_year=. + label var occup_skill_2_year "Skill based on ISCO standard secondary job 12 month recall" +* + + +*<_occup_2_year_> + gen byte occup_2_year=. + label var occup_2_year "1 digit occupational classification, secondary job 12 month recall" + label values occup_2_year lbloccup_year +* + + +*<_wage_no_compen_2_year_> + gen double wage_no_compen_2_year=. + label var wage_no_compen_2_year "Last wage payment secondary job 12 month recall" +* + + +*<_unitwage_2_year_> + gen byte unitwage_2_year=. + label var unitwage_2_year "Last wages' time unit secondary job 12 month recall" + label values unitwage_2_year lblunitwage_year +* + + +*<_whours_2_year_> + gen whours_2_year=. + label var whours_2_year "Hours of work in last week secondary job 12 month recall" +* + + +*<_wmonths_2_year_> + gen wmonths_2_year=. + label var wmonths_2_year "Months of work in past 12 months secondary job 12 month recall" +* + + +*<_wage_total_2_year_> + gen wage_total_2_year=. + label var wage_total_2_year "Annualized total wage secondary job 12 month recall" +* + + +*<_firmsize_l_2_year_> + gen byte firmsize_l_2_year=. + label var firmsize_l_2_year "Firm size (lower bracket) secondary job 12 month recall" +* + + +*<_firmsize_u_2_year_> + gen byte firmsize_u_2_year=. + label var firmsize_u_2_year "Firm size (upper bracket) secondary job 12 month recall" +* + +} + + +*----------8.9: 12 month reference additional jobs------------------------------* + + +*<_t_hours_others_year_> + gen t_hours_others_year=. + label var t_hours_others_year "Annualized hours worked in all but primary and secondary jobs 12 month recall" +* + + +*<_t_wage_nocompen_others_year_> + gen t_wage_nocompen_others_year=. + label var t_wage_nocompen_others_year "Annualized wage in all but primary & secondary jobs excl. bonuses, etc. 12 month recall)" +* + + +*<_t_wage_others_year_> + gen t_wage_others_year=. + label var t_wage_others_year "Annualized wage in all but primary and secondary jobs 12 month recall" +* + + +*----------8.10: 12 month total summary------------------------------* + + +*<_t_hours_total_year_> + gen t_hours_total_year=. + label var t_hours_total_year "Annualized hours worked in all jobs 12 month month recall" +* + + +*<_t_wage_nocompen_total_year_> + gen t_wage_nocompen_total_year=. + label var t_wage_nocompen_total_year "Annualized wage in all jobs excl. bonuses, etc. 12 month recall" +* + + +*<_t_wage_total_year_> + gen t_wage_total_year=. + label var t_wage_total_year "Annualized total wage for all jobs 12 month recall" +* + + +*----------8.11: Overall across reference periods------------------------------* + + +*<_njobs_> + gen njobs=. + replace njobs=1 if lstatus==1&E24!=1 + replace njobs=2 if lstatus==1&E24==1 + replace njobs=. if lstatus!=1 + label var njobs "Total number of jobs" +* + + +*<_t_hours_annual_> + gen t_hours_annual=. + label var t_hours_annual "Total hours worked in all jobs in the previous 12 months" +* + + +*<_linc_nc_> + gen linc_nc=. + label var linc_nc "Total annual wage income in all jobs, excl. bonuses, etc." +* + + +*<_laborincome_> + gen laborincome=. + label var laborincome "Total annual individual labor income in all jobs, incl. bonuses, etc." +* + + +*----------8.13: Labour cleanup------------------------------* + +{ +*<_% Correction min age_> + +** Drop info for cases under the age for which questions to be asked (do not need a variable for this) + local lab_var "minlaborage lstatus nlfreason unempldur_l unempldur_u empstat ocusec industry_orig industrycat_isic industrycat10 industrycat4 occup_orig occup_isco occup_skill occup wage_no_compen unitwage whours wmonths wage_total contract healthins socialsec union firmsize_l firmsize_u empstat_2 ocusec_2 industry_orig_2 industrycat_isic_2 industrycat10_2 industrycat4_2 occup_orig_2 occup_isco_2 occup_skill_2 occup_2 wage_no_compen_2 unitwage_2 whours_2 wmonths_2 wage_total_2 firmsize_l_2 firmsize_u_2 t_hours_others t_wage_nocompen_others t_wage_others t_hours_total t_wage_nocompen_total t_wage_total lstatus_year nlfreason_year unempldur_l_year unempldur_u_year empstat_year ocusec_year industry_orig_year industrycat_isic_year industrycat10_year industrycat4_year occup_orig_year occup_isco_year occup_skill_year occup_year unitwage_year whours_year wmonths_year wage_total_year contract_year healthins_year socialsec_year union_year firmsize_l_year firmsize_u_year empstat_2_year ocusec_2_year industry_orig_2_year industrycat_isic_2_year industrycat10_2_year industrycat4_2_year occup_orig_2_year occup_isco_2_year occup_skill_2_year occup_2_year wage_no_compen_2_year unitwage_2_year whours_2_year wmonths_2_year wage_total_2_year firmsize_l_2_year firmsize_u_2_year t_hours_others_year t_wage_nocompen_others_year t_wage_others_year t_hours_total_year t_wage_nocompen_total_year t_wage_total_year njobs t_hours_annual linc_nc laborincome" + + foreach v of local lab_var { + cap confirm numeric variable `v' + if _rc == 0 { // is indeed numeric + replace `v'=. if ( age < minlaborage & !missing(age) ) + } + else { // is not + replace `v'= "" if ( age < minlaborage & !missing(age) ) + } + + } + +* +} + + +/*%%============================================================================================= + 9: Final steps +==============================================================================================%%*/ + +quietly{ + +*<_% KEEP VARIABLES - ALL_> + + keep countrycode survname survey icls_v isced_version isco_version isic_version year vermast veralt harmonization int_year int_month hhid pid weight weight_m weight_q psu ssu strata wave panel visit_no urban subnatid1 subnatid2 subnatid3 subnatidsurvey subnatid1_prev subnatid2_prev subnatid3_prev gaul_adm1_code gaul_adm2_code gaul_adm3_code hsize age male relationharm relationcs marital eye_dsablty hear_dsablty walk_dsablty conc_dsord slfcre_dsablty comm_dsablty migrated_mod_age migrated_ref_time migrated_binary migrated_years migrated_from_urban migrated_from_cat migrated_from_code migrated_from_country migrated_reason ed_mod_age school literacy educy educat7 educat5 educat4 educat_orig educat_isced vocational vocational_type vocational_length_l vocational_length_u vocational_field_orig vocational_financed minlaborage lstatus potential_lf underemployment nlfreason unempldur_l unempldur_u empstat ocusec industry_orig industrycat_isic industrycat10 industrycat4 occup_orig occup_isco occup_skill occup wage_no_compen unitwage whours wmonths wage_total contract healthins socialsec union firmsize_l firmsize_u empstat_2 ocusec_2 industry_orig_2 industrycat_isic_2 industrycat10_2 industrycat4_2 occup_orig_2 occup_isco_2 occup_skill_2 occup_2 wage_no_compen_2 unitwage_2 whours_2 wmonths_2 wage_total_2 firmsize_l_2 firmsize_u_2 t_hours_others t_wage_nocompen_others t_wage_others t_hours_total t_wage_nocompen_total t_wage_total lstatus_year potential_lf_year underemployment_year nlfreason_year unempldur_l_year unempldur_u_year empstat_year ocusec_year industry_orig_year industrycat_isic_year industrycat10_year industrycat4_year occup_orig_year occup_isco_year occup_skill_year occup_year wage_no_compen_year unitwage_year whours_year wmonths_year wage_total_year contract_year healthins_year socialsec_year union_year firmsize_l_year firmsize_u_year empstat_2_year ocusec_2_year industry_orig_2_year industrycat_isic_2_year industrycat10_2_year industrycat4_2_year occup_orig_2_year occup_isco_2_year occup_skill_2_year occup_2_year wage_no_compen_2_year unitwage_2_year whours_2_year wmonths_2_year wage_total_2_year firmsize_l_2_year firmsize_u_2_year t_hours_others_year t_wage_nocompen_others_year t_wage_others_year t_hours_total_year t_wage_nocompen_total_year t_wage_total_year njobs t_hours_annual linc_nc laborincome + +* + +*<_% ORDER VARIABLES_> + + order countrycode survname survey icls_v isced_version isco_version isic_version year vermast veralt harmonization int_year int_month hhid pid weight weight_m weight_q psu ssu strata wave panel visit_no urban subnatid1 subnatid2 subnatid3 subnatidsurvey subnatid1_prev subnatid2_prev subnatid3_prev gaul_adm1_code gaul_adm2_code gaul_adm3_code hsize age male relationharm relationcs marital eye_dsablty hear_dsablty walk_dsablty conc_dsord slfcre_dsablty comm_dsablty migrated_mod_age migrated_ref_time migrated_binary migrated_years migrated_from_urban migrated_from_cat migrated_from_code migrated_from_country migrated_reason ed_mod_age school literacy educy educat7 educat5 educat4 educat_orig educat_isced vocational vocational_type vocational_length_l vocational_length_u vocational_field_orig vocational_financed minlaborage lstatus potential_lf underemployment nlfreason unempldur_l unempldur_u empstat ocusec industry_orig industrycat_isic industrycat10 industrycat4 occup_orig occup_isco occup_skill occup wage_no_compen unitwage whours wmonths wage_total contract healthins socialsec union firmsize_l firmsize_u empstat_2 ocusec_2 industry_orig_2 industrycat_isic_2 industrycat10_2 industrycat4_2 occup_orig_2 occup_isco_2 occup_skill_2 occup_2 wage_no_compen_2 unitwage_2 whours_2 wmonths_2 wage_total_2 firmsize_l_2 firmsize_u_2 t_hours_others t_wage_nocompen_others t_wage_others t_hours_total t_wage_nocompen_total t_wage_total lstatus_year potential_lf_year underemployment_year nlfreason_year unempldur_l_year unempldur_u_year empstat_year ocusec_year industry_orig_year industrycat_isic_year industrycat10_year industrycat4_year occup_orig_year occup_isco_year occup_skill_year occup_year wage_no_compen_year unitwage_year whours_year wmonths_year wage_total_year contract_year healthins_year socialsec_year union_year firmsize_l_year firmsize_u_year empstat_2_year ocusec_2_year industry_orig_2_year industrycat_isic_2_year industrycat10_2_year industrycat4_2_year occup_orig_2_year occup_isco_2_year occup_skill_2_year occup_2_year wage_no_compen_2_year unitwage_2_year whours_2_year wmonths_2_year wage_total_2_year firmsize_l_2_year firmsize_u_2_year t_hours_others_year t_wage_nocompen_others_year t_wage_others_year t_hours_total_year t_wage_nocompen_total_year t_wage_total_year njobs t_hours_annual linc_nc laborincome + +* + +*<_% DROP UNUSED LABELS_> + + * Store all labels in data + label dir + local all_lab `r(names)' + + * Store all variables with a label, extract value label names + local used_lab = "" + ds, has(vallabel) + + local labelled_vars `r(varlist)' + + foreach varName of local labelled_vars { + local y : value label `varName' + local used_lab `"`used_lab' `y'"' + } + + * Compare lists, `notused' is list of labels in directory but not used in final variables + local notused : list all_lab - used_lab // local `notused' defines value labs not in remaining vars + local notused_len : list sizeof notused // store size of local + + * drop labels if the length of the notused vector is 1 or greater, otherwise nothing to drop + if `notused_len' >= 1 { + label drop `notused' + } + else { + di "There are no unused labels to drop. No value labels dropped." + } + + +* + +} + +*<_% DELETE MISSING VARIABLES_> + +quietly: describe, varlist +local kept_vars `r(varlist)' + +foreach var of local kept_vars { + + capture assert missing(`var') + if !_rc drop `var' +} + +* + + +*<_% COMPRESS_> + +compress + +* + + +*<_% SAVE_> + +save "`path_output'/`level_2_harm'_ALL.dta", replace + +* diff --git a/GLD/ARM/ARM_2018_LFS/ARM_2018_LFS_V01_M_V03_A_GLD/Programs/ARM_2018_LFS_V01_M_V03_A_GLD_ALL.do b/GLD/ARM/ARM_2018_LFS/ARM_2018_LFS_V01_M_V03_A_GLD/Programs/ARM_2018_LFS_V01_M_V03_A_GLD_ALL.do new file mode 100644 index 000000000..27fae4b6f --- /dev/null +++ b/GLD/ARM/ARM_2018_LFS/ARM_2018_LFS_V01_M_V03_A_GLD/Programs/ARM_2018_LFS_V01_M_V03_A_GLD_ALL.do @@ -0,0 +1,1796 @@ + +/*%%============================================================================================= + 0: GLD Harmonization Preamble +================================================================================================*/ + +/* ----------------------------------------------------------------------- +<_Program name_> ARM_2018_LFS_V01_M_V03_A_GLD_ALL.do +<_Application_> Stata SE 18 <_Application_> +<_Author(s)_> Wolrd Bank Job's Group +<_Date created_> 2023-12-20 +------------------------------------------------------------------------- +<_Country_> Armenia (ARM) +<_Survey Title_> National Labour Force Survey +<_Survey Year_> 2018 +<_Study ID_> ARM_2018_LFS_v01_M +<_Data collection from (M/Y)_> [01/2018] +<_Data collection to (M/Y)_> [12/2018] +<_Source of dataset_> The Armenian 2018 to 2021 data is downloaded from + the website of Statistical Committee of the + Republic of Armenia:https://armstat.am/en/?nid=212 + The data is publicly available. +<_Sample size (HH)_> 7,788 +<_Sample size (IND)_> 28,296 +<_Sampling method_> A stratified two-stage probability sample design + with 14 domains as the primary strata and 18,000 + households as the SSU. +<_Geographic coverage_> All 11 regions/marzes. +<_Currency_> Armenian Dram +----------------------------------------------------------------------- +<_ICLS Version_> ICLS 19 +<_ISCED Version_> ISCED-2011 +<_ISCO Version_> ISCO 08 +<_OCCUP National_> NSCO +<_ISIC Version_> ISIC Rev.4 +<_INDUS National_> ISIC Rev.4 +----------------------------------------------------------------------- + +<_Version Control_> + +* Date: 2024-09-24 - Update vars educy, educat7, educat_isced +* Date: 2024-10-10 - Include weight by quarter, old weight variable, correct contract variable, drop migration + + + +-------------------------------------------------------------------------*/ + + +/*%%============================================================================================= + 1: Setting up of program environment, dataset +================================================================================================*/ + +*----------1.1: Initial commands------------------------------* + +clear +set more off +set mem 800m + +*----------1.2: Set directories------------------------------* + +* Define path sections +local server "Y:/GLD" +local country "ARM" +local year "2018" +local survey "LFS" +local vermast "V01" +local veralt "V03" + +* From the definitions, set path chunks +local level_1 "`country'_`year'_`survey'" +local level_2_mast "`level_1'_`vermast'_M" +local level_2_harm "`level_1'_`vermast'_M_`veralt'_A_GLD" + +* From chunks, define path_in, path_output folder +local path_in_stata "`server'/`country'/`level_1'/`level_2_mast'/Data/Stata" +local path_in_other "`server'/`country'/`level_1'/`level_2_mast'/Data/Original" +local path_output "`server'/`country'/`level_1'/`level_2_harm'/Data/Harmonized" + +* Define Output file name +local out_file "`level_2_harm'_ALL.dta" + + +*----------1.3: Database assembly------------------------------* + +* All steps necessary to merge datasets (if several) to have all elements needed to produce +* harmonized output in a single file + + use "`path_in_stata'/ARM_LFS_2018_raw.dta", clear + +/*%%============================================================================================= + 2: Survey & ID +================================================================================================*/ + +{ + +*<_countrycode_> + gen str4 countrycode="`country'" + label var countrycode "Country code" +* + + +*<_survname_> + gen survname="LFS" + label var survname "Survey acronym" +* + + +*<_survey_> + gen survey="LFS" + label var survey "Survey type" +* + + +*<_icls_v_> + gen icls_v="ICLS-19" + label var icls_v "ICLS version underlying questionnaire questions" +* + + +*<_isced_version_> + gen isced_version="isced_2011" + label var isced_version "Version of ISCED used for educat_isced" +* + + +*<_isco_version_> + gen isco_version="" + label var isco_version "Version of ISCO used" +* + + +*<_isic_version_> + gen isic_version="" + label var isic_version "Version of ISIC used" +* + + +*<_year_> + gen int year=`year' + label var year "Year of survey" +* + + +*<_vermast_> + gen str3 vermast="`vermast'" + label var vermast "Version of master data" +* + + +*<_veralt_> + gen str3 veralt="`veralt'" + label var veralt "Version of the alt/harmonized data" +* + + +*<_harmonization_> + gen harmonization="GLD" + label var harmonization "Type of harmonization" +* + + +*<_int_year_> + gen int_year=`year' + label var int_year "Year of the interview" +* + + +*<_int_month_> + gen int_month=A6_Month + label de lblint_month 1 "January" 2 "February" 3 "March" 4 "April" 5 "May" 6 "June" 7 "July" 8 "August" 9 "September" 10 "October" 11 "November" 12 "December" + label value int_month lblint_month + label var int_month "Month of the interview" +* + + +*<_hhid_> + tostring A1, gen(hid) format(%03.0f) + tostring A6_Month, gen(month) format(%03.0f) + egen hhid=concat(month hid) + label var hhid "Household id" +* + + +*<_pid_> + sort hhid B4 + bys hhid: gen memberid=_n + tostring memberid, gen(id_str) format(%02.0f) + egen pid=concat(hhid id_str), punct("-") + label var pid "Individual ID" +* + + +*<_weight_> + gen weight = WeightsCalib_Year + label var weight "Household sampling weight" +* + + +*<_weight_m_> + gen weight_m = . + label var weight_m "Survey sampling weight to obtain national estimates for each month" +* + + +*<_weight_q_> + egen weight_q = rowtotal(WeightsCalib_1 WeightsCalib_2 WeightsCalib_3 WeightsCalib_4) + label var weight_q "Survey sampling weight to obtain national estimates for each quarter" +* + + +*<_weight_old_series_> + gen weight_old_series = Weights_Year + label var weight_old_series "Household sampling weight - Old 2014-2017 series weight" +* + + +*<_weight_m_old_series_> + gen weight_m_old_series = . + label var weight_m_old_series "Survey sampling weight to obtain national estimates for each month - Old 2014-2017 series weight" +* + + +*<_weight_q_old_series_> + egen weight_q_old_series = rowtotal(Weights_1 Weights_2 Weights_3 Weights_4) + label var weight_q_old_series "Survey sampling weight to obtain national estimates for each quarter - Old 2014-2017 series weight" +* + + +*<_psu_> + gen psu=. + label var psu "Primary sampling units" +* + + +*<_ssu_> + gen ssu=hhid + label var ssu "Secondary sampling units" +* + + +*<_strata_> + decode A3, gen(marzname) + decode A5, gen(urbanstat) + gen strata=marzname+" "+urbanstat + label var strata "Strata" +* + + +*<_wave_> + gen wave=. + replace wave=1 if inrange(int_month,1,3) + replace wave=2 if inrange(int_month,4,6) + replace wave=3 if inrange(int_month,7,9) + replace wave=4 if inrange(int_month,10,12) + label var wave "Survey wave" +* + + +*<_panel_> + gen panel="" + label var panel "Panel individual belongs to" +* + + +*<_visit_no_> + gen visit_no=. + label var visit_no "Visit number in panel" +* +} + + +/*%%============================================================================================= + 3: Geography +================================================================================================*/ + +{ + +*<_urban_> + gen urban=A5 + recode urban (2=0) + la de lblurban 1 "Urban" 0 "Rural" + label values urban lblurban + label var urban "Location is urban" +* + + +*<_subnatid1_> + gen subnatid1=A3 + tostring subnatid1, replace + replace subnatid1=subnatid1+" - "+marzname + label var subnatid1 "Subnational ID at First Administrative Level" +* + + +*<_subnatid2_> + gen subnatid2=. + label var subnatid2 "Subnational ID at Second Administrative Level" +* + + +*<_subnatid3_> + gen subnatid3=. + label var subnatid3 "Subnational ID at Third Administrative Level" +* + + +*<_subnatidsurvey_> + gen subnatidsurvey=subnatid1+" "+urbanstat + label var subnatidsurvey "Administrative level at which survey is representative" +* + + +*<_subnatid1_prev_> + +/* <_subnatid1_prev_note_> +subnatid1_prev is coded as missing unless the classification used for subnatid1 has changed since the previous survey. + */ + + gen subnatid1_prev=. + label var subnatid1_prev "Classification used for subnatid1 from previous survey" +* + + +*<_subnatid2_prev_> + gen subnatid2_prev=. + label var subnatid2_prev "Classification used for subnatid2 from previous survey" +* + + +*<_subnatid3_prev_> + gen subnatid3_prev=. + label var subnatid3_prev "Classification used for subnatid3 from previous survey" +* + + +*<_gaul_adm1_code_> + gen gaul_adm1_code=. + label var gaul_adm1_code "Global Administrative Unit Layers (GAUL) Admin 1 code" +* + + +*<_gaul_adm2_code_> + gen gaul_adm2_code=. + label var gaul_adm2_code "Global Administrative Unit Layers (GAUL) Admin 2 code" +* + + +*<_gaul_adm3_code_> + gen gaul_adm3_code=. + label var gaul_adm3_code "Global Administrative Unit Layers (GAUL) Admin 3 code" +* + +} + +/*%%============================================================================================= + 4: Demography +================================================================================================*/ + +{ + +*<_hsize_> + bys hhid: egen hsize=max(memberid) + label var hsize "Household size" +* + + +*<_age_> + +/*<_age_note_> + +3 observations in the raw data set have negative (-1) age values. +They were coded as missing values in the harmonization. + +*<_age_note_>*/ + + gen age=Age + replace age=. if Age<0 + replace age=98 if age>98 & age!=. + label var age "Individual age" +* + + +*<_male_> + gen male=B3 + recode male 2=0 + label var male "Sex - Ind is male" + la de lblmale 1 "Male" 0 "Female" + label values male lblmale +* + + +*<_relationharm_> + gen byte relationharm=B4 + recode relationharm (6 9=3) (7 8=4) (10=5) (11=6) + label var relationharm "Relationship to the head of household - Harmonized" + la de lblrelationharm 1 "Head of household" 2 "Spouse" 3 "Children" 4 "Parents" 5 "Other relatives" 6 "Other and non-relatives" + label values relationharm lblrelationharm +*<_relationharm_> + + +*<_relationcs_> + gen relationcs=B4 + label var relationcs "Relationship to the head of household - Country original" +* + + +*<_marital_> + gen marital=B11 + recode marital (1=2) (2=1) (3=5) + label var marital "Marital status" + la de lblmarital 1 "Married" 2 "Never Married" 3 "Living together" 4 "Divorced/Separated" 5 "Widowed" + label values marital lblmarital +* + + +*<_eye_dsablty_> + gen eye_dsablty=. + la de lbleye_dsablty 1 "No" 2 "Yes-some" 3 "Yes-a lot" 4 "Cannot at all" + label values eye_dsablty lbleye_dsablty + label var eye_dsablty "Disability related to eyesight" +* + + +*<_hear_dsablty_> + gen hear_dsablty=. + la de lblhear_dsablty 1 "No" 2 "Yes-some" 3 "Yes-a lot" 4 "Cannot at all" + label values hear_dsablty lblhear_dsablty + label var hear_dsablty "Disability related to hearing" +* + + +*<_walk_dsablty_> + gen walk_dsablty=. + la de lblwalk_dsablty 1 "No" 2 "Yes-some" 3 "Yes-a lot" 4 "Cannot at all" + label values walk_dsablty lblwalk_dsablty + label var walk_dsablty "Disability related to walking or climbing stairs" +* + + +*<_conc_dsord_> + gen conc_dsord=. + la de lblconc_dsord 1 "No" 2 "Yes-some" 3 "Yes-a lot" 4 "Cannot at all" + label values conc_dsord lblconc_dsord + label var conc_dsord "Disability related to concentration or remembering" +* + + +*<_slfcre_dsablty_> + gen slfcre_dsablty=. + la de lblslfcre_dsablty 1 "No" 2 "Yes-some" 3 "Yes-a lot" 4 "Cannot at all" + label values slfcre_dsablty lblslfcre_dsablty + label var eye_dsablty "Disability related to selfcare" +* + + +*<_comm_dsablty_> + gen comm_dsablty=. + la de lblcomm_dsablty 1 "No" 2 "Yes-some" 3 "Yes-a lot" 4 "Cannot at all" + label values comm_dsablty lblcomm_dsablty + label var eye_dsablty "Disability related to communicating" +* + +} + + +/*%%============================================================================================= + 5: Migration +==============================================================================================%%*/ + + +{ + +*<_migrated_mod_age_> + gen migrated_mod_age = . + label var migrated_mod_age "Migration module application age" +* + + +*<_migrated_ref_time_> + gen migrated_ref_time = . + label var migrated_ref_time "Reference time applied to migration questions (in years)" +* + + +*<_migrated_binary_> + gen migrated_binary = . + label de lblmigrated_binary 0 "No" 1 "Yes" + label values migrated_binary lblmigrated_binary + label var migrated_binary "Individual has migrated" +* + + +*<_migrated_years_> + gen migrated_years = . + label var migrated_years "Years since latest migration" +* + + +*<_migrated_from_urban_> + gen migrated_from_urban = . + label de lblmigrated_from_urban 0 "Rural" 1 "Urban" + label values migrated_from_urban lblmigrated_from_urban + label var migrated_from_urban "Migrated from area" +* + + +*<_migrated_from_cat_> + gen migrated_from_cat = . + label de lblmigrated_from_cat 1 "From same admin3 area" 2 "From same admin2 area" 3 "From same admin1 area" 4 "From other admin1 area" 5 "From other country" + label values migrated_from_cat lblmigrated_from_cat + label var migrated_from_cat "Category of migration area" +* + + +*<_migrated_from_code_> + gen migrated_from_code = . + *label de lblmigrated_from_code + *label values migrated_from_code lblmigrated_from_code + label var migrated_from_code "Code of migration area as subnatid level of migrated_from_cat" +* + + +*<_migrated_from_country_> + gen migrated_from_country = . + label var migrated_from_country "Code of migration country (ISO 3 Letter Code)" +* + + +*<_migrated_reason_> + gen migrated_reason = . + label de lblmigrated_reason 1 "Family reasons" 2 "Educational reasons" 3 "Employment" 4 "Forced (political reasons, natural disaster, …)" 5 "Other reasons" + label values migrated_reason lblmigrated_reason + label var migrated_reason "Reason for migrating" +* + + +} + + +/*%%============================================================================================= + 6: Education +================================================================================================*/ + + +{ +*<_ed_mod_age_> + gen byte ed_mod_age=6 + label var ed_mod_age "Education module application age" +* + + +*<_school_> + gen school=B9 + recode school (2=0) (3/5=.) + replace school=. if age + + +*<_literacy_> + gen byte literacy=. + replace literacy=0 if B7==1 + replace literacy=1 if inrange(B7,2,11) + replace literacy=. if age + + +*<_educy_> + gen byte educy=. + replace educy = 0 if B7 == 1 | B7 == 2 + replace educy = 4 if B7 == 3 + replace educy = 9 if B7 == 4 + replace educy = 12 if B7 == 5 + replace educy = 11 if B7 == 6 + replace educy = 15 if B7 == 7 + replace educy = 16 if B7 == 8 + replace educy = 18 if B7 == 9 | B7 == 10 + replace educy = 20 if B7 == 11 + replace educy=. if ageage & !mi(educy) & !mi(age) + label var educy "Years of education" +* + + +*<_educat7_> + gen byte educat7= B7 + recode educat7 (6=5) (7=6) (8/11=7) + replace educat7=. if age + + +*<_educat5_> + gen byte educat5=educat7 + recode educat5 (4=3) (5=4) (6 7=5) + replace educat5=. if age + + +*<_educat4_> + gen byte educat4=educat5 + replace educat4=. if age + + +*<_educat_orig_> + gen educat_orig=B7 + label var educat_orig "Original survey education code" +* + + +*<_educat_isced_> + gen educat_isced=. + label var educat_isced "ISCED standardised level of education" +* + + +*<_educat_isced_v_> + gen educat_isced_v="ISCED-2011" + label var educat_isced_v "Version of the ISCED used" +* + +*----------6.1: Education cleanup------------------------------* + +*<_% Correction min age_> + +** Drop info for cases under the age for which questions to be asked (do not need a variable for this) +local ed_var school literacy educy educat7 educat5 educat4 educat_isced +foreach v of local ed_var { + replace `v'=. if ( age < ed_mod_age & !missing(age) ) +} +replace educat_isced_v="." if ( age < ed_mod_age & !missing(age) ) +* + +} + +/*%%============================================================================================= + 7: Training +================================================================================================*/ + +{ + +*<_vocational_> + gen vocational=. + la de vocationallbl 1 "Yes" 0 "No" + la values vocational vocationallbl + label var vocational "Ever received vocational training" +* + + +*<_vocational_type_> + gen vocational_type=. + label de lblvocational_type 1 "Inside Enterprise" 2 "External" + label values vocational_type lblvocational_type + label var vocational_type "Type of vocational training" +* + + +*<_vocational_length_l_> + gen vocational_length_l=. + replace vocational_length_l=. if vocational!=1 + label var vocational_length_l "Length of training in months, lower limit" +* + + +*<_vocational_length_u_> + gen vocational_length_u=. + replace vocational_length_u=. if vocational!=1 + label var vocational_length_u "Length of training in months, upper limit" +* + + +*<_vocational_field_orig_> + gen vocational_field_orig=. + replace vocational_field_orig=. if vocational!=1 + label var vocational_field_orig "Original field of training information" +* + + +*<_vocational_financed_> + gen vocational_financed=. + label de lblvocational_financed 1 "Employer" 2 "Government" 3 "Mixed Employer/Government" 4 "Own funds" 5 "Other" + label var vocational_financed "How training was financed" +* + +} + +/*%%============================================================================================= + 8: Labour +================================================================================================*/ + +*<_minlaborage_> + +/*<_minlaborage_note_> + +The age range for the labor section is 15-75. + +*<_minlaborage_note_>*/ + + gen byte minlaborage=15 + label var minlaborage "Labor module application age" +* + + +*----------8.1: 7 day reference overall------------------------------* + +{ +*<_lstatus_> + +/*<_lstatus_note> + +The economically inavtive population also needs to be within the age range of +15 and 75. + +*<_lstatus_note>*/ + + gen byte lstatus=. + replace lstatus=1 if D1==1|inrange(D3,1,5)|D4==1|D5==1 + replace lstatus=2 if lstatus==.&inrange(J9,1,3) + replace lstatus=3 if !mi(J1_4group)&lstatus==. + replace lstatus=. if !inrange(age,15,75) + label var lstatus "Labor status" + la de lbllstatus 1 "Employed" 2 "Unemployed" 3 "Non-LF" + label values lstatus lbllstatus +* + + +*<_potential_lf_> + +/*<_potential_lf_note_> +Note: var "potential_lf" only takes value if the respondent is not in labor force. (lstatus==3) + +"potential_lf"=1 if the person is +1)available but not searching or (J16==1)&J9==4 +2)searching but not immediately available to work or inrange(J9,1,3)&J16==2 + +*/ + + gen potential_lf=. + replace potential_lf=1 if [(J16==1)&J9==4] | [inrange(J9,1,3)&J16==2] + replace potential_lf=0 if [(J16==1)&inrange(J9,1,3)] | [inrange(J9,1,3)&J16==1] + replace potential_lf=. if age75&!mi(age)] + replace potential_lf=. if lstatus!=3 + label var potential_lf "Potential labour force status" + la de lblpotential_lf 0 "No" 1 "Yes" + label values potential_lf lblpotential_lf +* + + +*<_underemployment_> + gen byte underemployment=G4 + replace underemployment=1 if inrange(G4,1,3) + replace underemployment=0 if G4==4 + replace underemployment=. if age75&!mi(age)] + replace underemployment=. if lstatus!=1 + label var underemployment "Underemployment status" + la de lblunderemployment 0 "No" 1 "Yes" + label values underemployment lblunderemployment +* + + +*<_nlfreason_> + gen byte nlfreason=J1_4group + recode nlfreason (4=5) + replace nlfreason=. if age75&!mi(age)] + replace nlfreason=. if lstatus!=3 + label var nlfreason "Reason not in the labor force" + la de lblnlfreason 1 "Student" 2 "Housekeeper" 3 "Retired" 4 "Disabled" 5 "Other" + label values nlfreason lblnlfreason +* + + +*<_unempldur_l_> + gen byte unempldur_l=J4 + recode unempldur_l (1=0) (2=3) (3=6) (4=9) (5=12) (6=24) (7=36) + replace unempldur_l=. if age75&!mi(age)] + replace unempldur_l=. if lstatus!=2 + label var unempldur_l "Unemployment duration (months) lower bracket" +* + + +*<_unempldur_u_> + gen byte unempldur_u=J4 + recode unempldur_u (1=3) (2=6) (3=9) (4=12) (5=24) (6=36) (7=.) + replace unempldur_u=. if age75&!mi(age)] + replace unempldur_u=. if lstatus!=2 + label var unempldur_u "Unemployment duration (months) upper bracket" +* +} + + +*----------8.2: 7 day reference main job------------------------------* + + +{ +*<_empstat_> + gen byte empstat=E7 + recode empstat (2=1) (5=2) + replace empstat=. if lstatus!=1|age + + +*<_ocusec_> + gen byte ocusec=E10 + recode ocusec (3 4=2) + replace ocusec=. if lstatus!=1|age + + +*<_industry_orig_> + gen industry_orig=E4_21group + replace industry_orig=. if lstatus!=1 + label var industry_orig "Original survey industry code, main job 7 day recall" +* + + +*<_industrycat_isic_> + gen industrycat_isic="" +quietly +{ + replace industrycat_isic="A" if E4_21group==1 + replace industrycat_isic="B" if E4_21group==2 + replace industrycat_isic="C" if E4_21group==3 + replace industrycat_isic="D" if E4_21group==4 + replace industrycat_isic="E" if E4_21group==5 + replace industrycat_isic="F" if E4_21group==6 + replace industrycat_isic="G" if E4_21group==7 + replace industrycat_isic="H" if E4_21group==8 + replace industrycat_isic="I" if E4_21group==9 + replace industrycat_isic="J" if E4_21group==10 + replace industrycat_isic="K" if E4_21group==11 + replace industrycat_isic="L" if E4_21group==12 + replace industrycat_isic="M" if E4_21group==13 + replace industrycat_isic="N" if E4_21group==14 + replace industrycat_isic="O" if E4_21group==15 + replace industrycat_isic="P" if E4_21group==16 + replace industrycat_isic="Q" if E4_21group==17 + replace industrycat_isic="R" if E4_21group==18 + replace industrycat_isic="S" if E4_21group==19 + replace industrycat_isic="T" if E4_21group==20 + replace industrycat_isic="U" if E4_21group==21 +} + + replace industrycat_isic="" if industrycat_isic=="."|lstatus!=1 + label var industrycat_isic "ISIC code of primary job 7 day recall" +* + + +*<_industrycat10_> + gen industrycat10=E4_21group + recode industrycat10 (5=4) (6=5) (7 9=6) (8 10=7) (11/14=8) (15=9) (16/21=10) + replace industrycat10=. if lstatus!=1 + label var industrycat10 "1 digit industry classification, primary job 7 day recall" + la de lblindustrycat10 1 "Agriculture" 2 "Mining" 3 "Manufacturing" 4 "Public utilities" 5 "Construction" 6 "Commerce" 7 "Transport and Comnunications" 8 "Financial and Business Services" 9 "Public Administration" 10 "Other Services, Unspecified" + label values industrycat10 lblindustrycat10 +* + + +*<_industrycat4_> + gen byte industrycat4=industrycat10 + recode industrycat4 (3/5=2)(6/9=3)(10=4) + label var industrycat4 "1 digit industry classification (Broad Economic Activities), primary job 7 day recall" + la de lblindustrycat4 1 "Agriculture" 2 "Industry" 3 "Services" 4 "Other" + label values industrycat4 lblindustrycat4 +* + + +*<_occup_orig_> + gen occup_orig=E2_9group + replace occup_orig=. if lstatus!=1|[age>75&!mi(age)] + label var occup_orig "Original occupation record primary job 7 day recall" +* + + +*<_occup_isco_> + gen occup_isco="" + replace occup_isco="" if lstatus!=1 | occup_isco=="." + label var occup_isco "ISCO code of primary job 7 day recall" +* + + +*<_occup_skill_> + gen occup_skill=E2_9group + replace occup_skill=1 if E2_9group==9 + replace occup_skill=2 if inrange(E2_9group, 4, 8) + replace occup_skill=3 if inrange(E2_9group, 1, 3) + replace occup_skill=. if lstatus!=1 + la de lblskill 1 "Low skill" 2 "Medium skill" 3 "High skill" + label values occup_skill lblskill + label var occup_skill "Skill based on ISCO standard primary job 7 day recall" +* + + +*<_occup_> + gen occup=E2_9group + replace occup=. if lstatus!=1|[age>75&!mi(age)] + label var occup "1 digit occupational classification, primary job 7 day recall" + la de lbloccup 1 "Managers" 2 "Professionals" 3 "Technicians" 4 "Clerks" 5 "Service and market sales workers" 6 "Skilled agricultural" 7 "Craft workers" 8 "Machine operators" 9 "Elementary occupations" 10 "Armed forces" 99 "Others" + label values occup lbloccup +* + + +*<_wage_no_compen_> + +/*<_wage_no_compen_note_> + +The wage questions in the questionnare are organized into to parts: the first part +asks for the specific number of income if the given respondent could recall and was +willing to answer; the second part provides different categories of income range +if the given respondent could not recall or was not willing to answer the first part. + +The general logic here is to impute wage values for people who only answered an income +range. We used industry, occupation, income categories and gender to estimate their +specific income values. + +20.71% of total non-missing wage values were imputed using this method. +*<_wage_no_compen_note_>*/ + + * Overall --> wage info (here the variable, for us it should be wage_no_compen) + * to missing if value is 0. + gen wage14=E14_1+E14_2 + replace wage14=. if wage14==0 + + * First replace outliers by + winsor2 wage14, suffix(_w) cuts(1 99) + + * Create salary categories based on winsor values + gen salary_cat=. + replace salary_cat=1 if inrange(wage14_w, 1, 55000) + replace salary_cat=2 if wage14_w==55000 + replace salary_cat=3 if inrange(wage14_w, 55001, 110000) + replace salary_cat=4 if inrange(wage14_w, 110001, 220000) + replace salary_cat=5 if inrange(wage14_w, 220001, 440000) + replace salary_cat=6 if inrange(wage14_w, 440001, 600000) + replace salary_cat=7 if inrange(wage14_w, 600001, 700000) + replace salary_cat=8 if inrange(wage14_w, 700000, 99999999) + + * Preserve to collapse, so we can merge the info in + preserve + + * Collpase by industry, sex, and salary categories + collapse (mean)wage14_w[iw=weight], by(industrycat10 occup male urban salary_cat) + + * Rename variable, otherwise when merging in, master version of an equally name one will be kept + rename wage14_w wage_group_estimate + + * Rename salary_cat to D15 since this is what we want the info to latch on to + rename salary_cat E15 + tempfile salary_helper + save "`salary_helper'" + + * Restore, merge in + restore + merge m:1 industrycat10 occup male urban E15 using "`salary_helper'", keep(matched master) nogen + + * Create wage variable + gen wage_no_compen=. + + * Fill it first with values that are accurate + replace wage_no_compen=wage14 if !mi(wage14)&mi(E15) + + * Now add the categorised means + replace wage_no_compen=wage_group_estimate if inrange(E15,1,8)&!mi(wage_group_estimate) + + * Keep only for employed employees, label + replace wage_no_compen=. if lstatus!=1|empstat==2 + label var wage_no_compen "Last wage payment primary job 7 day recall" +* + + +*<_unitwage_> + gen byte unitwage=E16 + recode unitwage (4=5) (5=7) (6=8) (7=10) + replace unitwage=. if lstatus!=1 | empstat==2 + label var unitwage "Last wages' time unit primary job 7 day recall" + la de lblunitwage 1 "Daily" 2 "Weekly" 3 "Every two weeks" 4 "Bimonthly" 5 "Monthly" 6 "Trimester" 7 "Biannual" 8 "Annually" 9 "Hourly" 10 "Other" + label values unitwage lblunitwage +* + + +*<_whours_> + gen whours = G2_1 + replace whours=. if lstatus!=1|G2_1==0 + label var whours "Hours of work in last week primary job 7 day recall" +* + + +*<_wmonths_> + gen wmonths=. + label var wmonths "Months of work in past 12 months primary job 7 day recall" +* + + +*<_wage_total_> + gen wage_total=. + label var wage_total "Annualized total wage primary job 7 day recall" +* + + +*<_contract_> + +/*<_contract_note_> + +There is no separate contract question in the questionnaire. +This contract variable was coded based on employment status question which asks +wether an employed respondent had a contract or not. + +*<_contract_note_>*/ + + gen byte contract = . + replace contract = (E7 == 1) + replace contract=. if lstatus!=1 + label var contract "Employment has contract primary job 7 day recall" + la de lblcontract 0 "Without contract" 1 "With contract" + label values contract lblcontract +* + + +*<_healthins_> + gen byte healthins=. + replace healthins=1 if E8_f==1 + replace healthins=0 if E8_f==2 + replace healthins=. if lstatus!=1 + label var healthins "Employment has health insurance primary job 7 day recall" + la de lblhealthins 0 "Without health insurance" 1 "With health insurance" + label values healthins lblhealthins +* + + +*<_socialsec_> + gen byte socialsec=. + replace socialsec=. if lstatus!=1 + label var socialsec "Employment has social security insurance primary job 7 day recall" + la de lblsocialsec 1 "With social security" 0 "Without social secturity" + label values socialsec lblsocialsec +* + + +*<_union_> + gen byte union=. + replace union=1 if E27==1 + replace union=0 if E27==2 + replace union=. if lstatus!=1 + label var union "Union membership at primary job 7 day recall" + la de lblunion 0 "Not union member" 1 "Union member" + label values union lblunion +* + + +*<_firmsize_l_> + gen byte firmsize_l=E13 + recode firmsize_l (1=1) (2=5) (3=10) (4=20) (5=50) (6=100) (7=.) + replace firmsize_l=. if lstatus!=1 + label var firmsize_l "Firm size (lower bracket) primary job 7 day recall" +* + + +*<_firmsize_u_> + gen byte firmsize_u=E13 + recode firmsize_u (1=5) (2=9) (3=19) (4=49) (5=99) (6=.) + replace firmsize_u=. if lstatus!=1 + label var firmsize_u "Firm size (upper bracket) primary job 7 day recall" +* + +} + + +*----------8.3: 7 day reference secondary job------------------------------* +* Since labels are the same as main job, values are labelled using main job labels + +{ +*<_empstat_2_> + gen byte empstat_2=F4 + recode empstat_2 (2=1) (5=2) + replace empstat_2=. if lstatus!=1|F1!=1 + label var empstat_2 "Employment status during past week secondary job 7 day recall" + la de lblempstat_2 1 "Paid employee" 2 "Non-paid employee" 3 "Employer" 4 "Self-employed" 5 "Other, workers not classifiable by status" + label values empstat_2 lblempstat +* + + +*<_ocusec_2_> + gen byte ocusec_2=F6 + recode ocusec_2 (3 4=2) + replace ocusec_2=. if lstatus!=1|F1!=1 + label var ocusec_2 "Sector of activity secondary job 7 day recall" + la de lblocusec_2 1 "Public Sector, Central Government, Army" 2 "Private, NGO" 3 "State owned" 4 "Public or State-owned, but cannot distinguish" + label values ocusec_2 lblocusec_2 +* + + +*<_industry_orig_2_> + gen industry_orig_2=F3_21group + replace industry_orig_2=. if lstatus!=1|F1!=1 + label var industry_orig_2 "Original survey industry code, secondary job 7 day recall" +* + + +*<_industrycat_isic_2_> + gen industrycat_isic_2="" +quietly +{ + replace industrycat_isic_2="A" if F3_21group==1 + replace industrycat_isic_2="B" if F3_21group==2 + replace industrycat_isic_2="C" if F3_21group==3 + replace industrycat_isic_2="D" if F3_21group==4 + replace industrycat_isic_2="E" if F3_21group==5 + replace industrycat_isic_2="F" if F3_21group==6 + replace industrycat_isic_2="G" if F3_21group==7 + replace industrycat_isic_2="H" if F3_21group==8 + replace industrycat_isic_2="I" if F3_21group==9 + replace industrycat_isic_2="J" if F3_21group==10 + replace industrycat_isic_2="K" if F3_21group==11 + replace industrycat_isic_2="L" if F3_21group==12 + replace industrycat_isic_2="M" if F3_21group==13 + replace industrycat_isic_2="N" if F3_21group==14 + replace industrycat_isic_2="O" if F3_21group==15 + replace industrycat_isic_2="P" if F3_21group==16 + replace industrycat_isic_2="Q" if F3_21group==17 + replace industrycat_isic_2="R" if F3_21group==18 + replace industrycat_isic_2="S" if F3_21group==19 + replace industrycat_isic_2="T" if F3_21group==20 + replace industrycat_isic_2="U" if F3_21group==21 +} + + replace industrycat_isic_2="" if industrycat_isic_2=="."|F1!=1 + label var industrycat_isic_2 "ISIC code of secondary job 7 day recall" +* + + +*<_industrycat10_2_> + gen industrycat10_2=F3_21group + recode industrycat10_2 (5=4) (6=5) (7 9=6) (8 10=7) (11/14=8) (15=9) (16/21=10) + replace industrycat10_2=. if lstatus!=1|F1!=1 + label var industrycat10_2 "1 digit industry classification, secondary job 7 day recall" + label values industrycat10_2 lblindustrycat10 +* + + +*<_industrycat4_2_> + gen byte industrycat4_2=industrycat10_2 + recode industrycat4_2 (3/5=2)(6/9=3)(10=4) + label var industrycat4_2 "1 digit industry classification (Broad Economic Activities), secondary job 7 day recall" + label values industrycat4_2 lblindustrycat4 +* + + +*<_occup_orig_2_> + gen occup_orig_2=F2_9group + replace occup_orig_2=. if lstatus!=1|F1!=1 + label var occup_orig_2 "Original occupation record secondary job 7 day recall" +* + + +*<_occup_isco_2_> + gen occup_isco_2="" + replace occup_isco_2="" if lstatus!=1 | occup_isco_2=="."|F1!=1 + label var occup_isco_2 "ISCO code of secondary job 7 day recall" +* + + +*<_occup_skill_2_> + gen occup_skill_2=F2_9group + replace occup_skill_2=1 if F2_9group==9 + replace occup_skill_2=2 if inrange(F2_9group,4,8) + replace occup_skill_2=3 if inrange(F2_9group,1,3) + replace occup_skill_2=. if F2_9group==0|lstatus!=1|F1!=1 + label var occup_skill_2 "Skill based on ISCO standard secondary job 7 day recall" +* + + +*<_occup_2_> + gen occup_2=F2_9group + replace occup_2=. if lstatus!=1|F1!=1 + label var occup_2 "1 digit occupational classification secondary job 7 day recall" + label values occup_2 lbloccup +* + + +*<_wage_no_compen_2_> + +/*<_wage_no_compen_2_note_> + +The questionnaire actually has questions about income of the second job, just as the +main job. However, the data set does not have the variables. + +*<_wage_no_compen_2_note_>*/ + gen wage_no_compen_2=. + replace wage_no_compen_2=. if F1!=1|empstat_2==2 + label var wage_no_compen_2 "Last wage payment secondary job 7 day recall" +* + + +*<_unitwage_2_> + gen byte unitwage_2=. + replace unitwage_2=. if lstatus!=1|F1!=1 + label var unitwage_2 "Last wages' time unit secondary job 7 day recall" + label values unitwage_2 lblunitwage +* + + +*<_whours_2_> + gen whours_2=G2_2 + replace whours_2=. if G2_2==0|F1!=1 + label var whours_2 "Hours of work in last week secondary job 7 day recall" +* + + +*<_wmonths_2_> + gen wmonths_2=. + label var wmonths_2 "Months of work in past 12 months secondary job 7 day recall" +* + + +*<_wage_total_2_> + gen wage_total_2=. + label var wage_total_2 "Annualized total wage secondary job 7 day recall" +* + + +*<_firmsize_l_2_> + gen byte firmsize_l_2=. + label var firmsize_l_2 "Firm size (lower bracket) secondary job 7 day recall" +* + + +*<_firmsize_u_2_> + gen byte firmsize_u_2=. + label var firmsize_u_2 "Firm size (upper bracket) secondary job 7 day recall" +* + +} + +*----------8.4: 7 day reference additional jobs------------------------------* + +*<_t_hours_others_> + gen t_hours_others=. + label var t_hours_others "Annualized hours worked in all but primary and secondary jobs 7 day recall" +* + + +*<_t_wage_nocompen_others_> + gen t_wage_nocompen_others=. + label var t_wage_nocompen_others "Annualized wage in all but primary & secondary jobs excl. bonuses, etc. 7 day recall" +* + + +*<_t_wage_others_> + gen t_wage_others=. + label var t_wage_others "Annualized wage in all but primary and secondary jobs (12-mon ref period)" +* + + +*----------8.5: 7 day reference total summary------------------------------* + + +*<_t_hours_total_> + gen t_hours_total=. + label var t_hours_total "Annualized hours worked in all jobs 7 day recall" +* + + +*<_t_wage_nocompen_total_> + gen t_wage_nocompen_total=. + label var t_wage_nocompen_total "Annualized wage in all jobs excl. bonuses, etc. 7 day recall" +* + + +*<_t_wage_total_> + gen t_wage_total=. + label var t_wage_total "Annualized total wage for all jobs 7 day recall" +* + + +*----------8.6: 12 month reference overall------------------------------* + +{ +*<_lstatus_year_> + gen byte lstatus_year=. + replace lstatus_year=. if age + + +*<_potential_lf_year_> + gen byte potential_lf_year=. + replace potential_lf_year=. if age + + +*<_underemployment_year_> + gen byte underemployment_year=. + replace underemployment_year=. if age + + +*<_nlfreason_year_> + gen byte nlfreason_year=. + label var nlfreason_year "Reason not in the labor force" + la de lblnlfreason_year 1 "Student" 2 "Housekeeper" 3 "Retired" 4 "Disable" 5 "Other" + label values nlfreason_year lblnlfreason_year +* + + +*<_unempldur_l_year_> + gen byte unempldur_l_year=. + label var unempldur_l_year "Unemployment duration (months) lower bracket" +* + + +*<_unempldur_u_year_> + gen byte unempldur_u_year=. + label var unempldur_u_year "Unemployment duration (months) upper bracket" +* + +} + +*----------8.7: 12 month reference main job------------------------------* + +{ +*<_empstat_year_> + gen byte empstat_year=. + label var empstat_year "Employment status during past week primary job 12 month recall" + la de lblempstat_year 1 "Paid employee" 2 "Non-paid employee" 3 "Employer" 4 "Self-employed" 5 "Other, workers not classifiable by status" + label values empstat_year lblempstat_year +* + + +*<_ocusec_year_> + gen byte ocusec_year=. + label var ocusec_year "Sector of activity primary job 12 day recall" + la de lblocusec_year 1 "Public Sector, Central Government, Army" 2 "Private, NGO" 3 "State owned" 4 "Public or State-owned, but cannot distinguish" + label values ocusec_year lblocusec_year +* + + +*<_industry_orig_year_> + gen industry_orig_year=. + label var industry_orig_year "Original industry record main job 12 month recall" +* + + +*<_industrycat_isic_year_> + gen industrycat_isic_year="" + replace industrycat_isic_year="" if industrycat_isic_year=="." + label var industrycat_isic_year "ISIC code of primary job 12 month recall" +* + + +*<_industrycat10_year_> + gen byte industrycat10_year=. + label var industrycat10_year "1 digit industry classification, primary job 12 month recall" + la de lblindustrycat10_year 1 "Agriculture" 2 "Mining" 3 "Manufacturing" 4 "Public utilities" 5 "Construction" 6 "Commerce" 7 "Transport and Comnunications" 8 "Financial and Business Services" 9 "Public Administration" 10 "Other Services, Unspecified" + label values industrycat10_year lblindustrycat10_year +* + + +*<_industrycat4_year_> + gen byte industrycat4_year=industrycat10_year + recode industrycat4_year (1=1)(2 3 4 5 =2)(6 7 8 9=3)(10=4) + label var industrycat4_year "1 digit industry classification (Broad Economic Activities), primary job 12 month recall" + la de lblindustrycat4_year 1 "Agriculture" 2 "Industry" 3 "Services" 4 "Other" + label values industrycat4_year lblindustrycat4_year +* + + +*<_occup_orig_year_> + gen occup_orig_year=. + label var occup_orig_year "Original occupation record primary job 12 month recall" +* + + +*<_occup_isco_year_> + gen str4 occup_isco_year="" + label var occup_isco_year "ISCO code of primary job 12 month recall" +* + + +*<_occup_skill_year_> + gen skill_level_year=substr(occup_isco_year,1,1) + destring skill_level_year, replace + gen occup_skill_year=. + replace occup_skill_year=1 if skill_level_year==9 + replace occup_skill_year=2 if inrange(skill_level_year,4,8) + replace occup_skill_year=3 if inrange(skill_level_year,1,3) + replace occup_skill_year=. if skill_level_year==0 + label var occup_skill_year "Skill based on ISCO standard primary job 12 month recall" +* + + +*<_occup_year_> + gen byte occup_year=. + label var occup_year "1 digit occupational classification, primary job 12 month recall" + la de lbloccup_year 1 "Managers" 2 "Professionals" 3 "Technicians" 4 "Clerks" 5 "Service and market sales workers" 6 "Skilled agricultural" 7 "Craft workers" 8 "Machine operators" 9 "Elementary occupations" 10 "Armed forces" 99 "Others" + label values occup_year lbloccup_year +* + + +*<_wage_no_compen_year_> + gen double wage_no_compen_year=. + label var wage_no_compen_year "Last wage payment primary job 12 month recall" +* + + +*<_unitwage_year_> + gen byte unitwage_year=. + label var unitwage_year "Last wages' time unit primary job 12 month recall" + la de lblunitwage_year 1 "Daily" 2 "Weekly" 3 "Every two weeks" 4 "Bimonthly" 5 "Monthly" 6 "Trimester" 7 "Biannual" 8 "Annually" 9 "Hourly" 10 "Other" + label values unitwage_year lblunitwage_year +* + + +*<_whours_year_> + gen whours_year=. + label var whours_year "Hours of work in last week primary job 12 month recall" +* + + +*<_wmonths_year_> + gen wmonths_year=. + label var wmonths_year "Months of work in past 12 months primary job 12 month recall" +* + + +*<_wage_total_year_> + gen wage_total_year=. + label var wage_total_year "Annualized total wage primary job 12 month recall" +* + + +*<_contract_year_> + gen byte contract_year=. + label var contract_year "Employment has contract primary job 12 month recall" + la de lblcontract_year 0 "Without contract" 1 "With contract" + label values contract_year lblcontract_year +* + + +*<_healthins_year_> + gen byte healthins_year=. + label var healthins_year "Employment has health insurance primary job 12 month recall" + la de lblhealthins_year 0 "Without health insurance" 1 "With health insurance" + label values healthins_year lblhealthins_year +* + + +*<_socialsec_year_> + gen byte socialsec_year=. + label var socialsec_year "Employment has social security insurance primary job 7 day recall" + la de lblsocialsec_year 1 "With social security" 0 "Without social secturity" + label values socialsec_year lblsocialsec_year +* + + +*<_union_year_> + gen byte union_year=. + label var union_year "Union membership at primary job 12 month recall" + la de lblunion_year 0 "Not union member" 1 "Union member" + label values union_year lblunion_year +* + + +*<_firmsize_l_year_> + gen byte firmsize_l_year=. + label var firmsize_l_year "Firm size (lower bracket) primary job 12 month recall" +* + + +*<_firmsize_u_year_> + gen byte firmsize_u_year=. + label var firmsize_u_year "Firm size (upper bracket) primary job 12 month recall" +* + +} + + +*----------8.8: 12 month reference secondary job------------------------------* + +{ + +*<_empstat_2_year_> + gen byte empstat_2_year=. + label var empstat_2_year "Employment status during past week secondary job 12 month recall" + label values empstat_2_year lblempstat_year +* + + +*<_ocusec_2_year_> + gen byte ocusec_2_year=. + label var ocusec_2_year "Sector of activity secondary job 12 day recall" + la de lblocusec_2_year 1 "Public Sector, Central Government, Army" 2 "Private, NGO" 3 "State owned" 4 "Public or State-owned, but cannot distinguish" + label values ocusec_2_year lblocusec_2_year +* + + + +*<_industry_orig_2_year_> + gen industry_orig_2_year=. + label var industry_orig_2_year "Original survey industry code, secondary job 12 month recall" +* + + + +*<_industrycat_isic_2_year_> + gen industrycat_isic_2_year=. + label var industrycat_isic_2_year "ISIC code of secondary job 12 month recall" +* + + +*<_industrycat10_2_year_> + gen byte industrycat10_2_year=. + label var industrycat10_2_year "1 digit industry classification, secondary job 12 month recall" + label values industrycat10_2_year lblindustrycat10_year +* + + +*<_industrycat4_2_year_> + gen byte industrycat4_2_year=industrycat10_2_year + recode industrycat4_2_year (1=1)(2 3 4 5 =2)(6 7 8 9=3)(10=4) + label var industrycat4_2_year "1 digit industry classification (Broad Economic Activities), secondary job 12 month recall" + label values industrycat4_2_year lblindustrycat4_year +* + + +*<_occup_orig_2_year_> + gen occup_orig_2_year=. + label var occup_orig_2_year "Original occupation record secondary job 12 month recall" +* + + +*<_occup_isco_2_year_> + gen occup_isco_2_year=. + label var occup_isco_2_year "ISCO code of secondary job 12 month recall" +* + + +*<_occup_skill_2_year_> + gen occup_skill_2_year=. + label var occup_skill_2_year "Skill based on ISCO standard secondary job 12 month recall" +* + + +*<_occup_2_year_> + gen byte occup_2_year=. + label var occup_2_year "1 digit occupational classification, secondary job 12 month recall" + label values occup_2_year lbloccup_year +* + + +*<_wage_no_compen_2_year_> + gen double wage_no_compen_2_year=. + label var wage_no_compen_2_year "Last wage payment secondary job 12 month recall" +* + + +*<_unitwage_2_year_> + gen byte unitwage_2_year=. + label var unitwage_2_year "Last wages' time unit secondary job 12 month recall" + label values unitwage_2_year lblunitwage_year +* + + +*<_whours_2_year_> + gen whours_2_year=. + label var whours_2_year "Hours of work in last week secondary job 12 month recall" +* + + +*<_wmonths_2_year_> + gen wmonths_2_year=. + label var wmonths_2_year "Months of work in past 12 months secondary job 12 month recall" +* + + +*<_wage_total_2_year_> + gen wage_total_2_year=. + label var wage_total_2_year "Annualized total wage secondary job 12 month recall" +* + + +*<_firmsize_l_2_year_> + gen byte firmsize_l_2_year=. + label var firmsize_l_2_year "Firm size (lower bracket) secondary job 12 month recall" +* + + +*<_firmsize_u_2_year_> + gen byte firmsize_u_2_year=. + label var firmsize_u_2_year "Firm size (upper bracket) secondary job 12 month recall" +* + +} + + +*----------8.9: 12 month reference additional jobs------------------------------* + + +*<_t_hours_others_year_> + gen t_hours_others_year=. + label var t_hours_others_year "Annualized hours worked in all but primary and secondary jobs 12 month recall" +* + + +*<_t_wage_nocompen_others_year_> + gen t_wage_nocompen_others_year=. + label var t_wage_nocompen_others_year "Annualized wage in all but primary & secondary jobs excl. bonuses, etc. 12 month recall)" +* + + +*<_t_wage_others_year_> + gen t_wage_others_year=. + label var t_wage_others_year "Annualized wage in all but primary and secondary jobs 12 month recall" +* + + +*----------8.10: 12 month total summary------------------------------* + + +*<_t_hours_total_year_> + gen t_hours_total_year=. + label var t_hours_total_year "Annualized hours worked in all jobs 12 month month recall" +* + + +*<_t_wage_nocompen_total_year_> + gen t_wage_nocompen_total_year=. + label var t_wage_nocompen_total_year "Annualized wage in all jobs excl. bonuses, etc. 12 month recall" +* + + +*<_t_wage_total_year_> + gen t_wage_total_year=. + label var t_wage_total_year "Annualized total wage for all jobs 12 month recall" +* + + +*----------8.11: Overall across reference periods------------------------------* + + +*<_njobs_> + gen njobs=. + replace njobs=1 if lstatus==1&F1!=1 + replace njobs=2 if lstatus==1&F1==1 + replace njobs=. if lstatus!=1 + label var njobs "Total number of jobs" +* + + +*<_t_hours_annual_> + gen t_hours_annual=. + label var t_hours_annual "Total hours worked in all jobs in the previous 12 months" +* + + +*<_linc_nc_> + gen linc_nc=. + label var linc_nc "Total annual wage income in all jobs, excl. bonuses, etc." +* + + +*<_laborincome_> + gen laborincome=. + label var laborincome "Total annual individual labor income in all jobs, incl. bonuses, etc." +* + + +*----------8.13: Labour cleanup------------------------------* + +{ +*<_% Correction min age_> + +** Drop info for cases under the age for which questions to be asked (do not need a variable for this) + local lab_var "minlaborage lstatus nlfreason unempldur_l unempldur_u empstat ocusec industry_orig industrycat_isic industrycat10 industrycat4 occup_orig occup_isco occup_skill occup wage_no_compen unitwage whours wmonths wage_total contract healthins socialsec union firmsize_l firmsize_u empstat_2 ocusec_2 industry_orig_2 industrycat_isic_2 industrycat10_2 industrycat4_2 occup_orig_2 occup_isco_2 occup_skill_2 occup_2 wage_no_compen_2 unitwage_2 whours_2 wmonths_2 wage_total_2 firmsize_l_2 firmsize_u_2 t_hours_others t_wage_nocompen_others t_wage_others t_hours_total t_wage_nocompen_total t_wage_total lstatus_year nlfreason_year unempldur_l_year unempldur_u_year empstat_year ocusec_year industry_orig_year industrycat_isic_year industrycat10_year industrycat4_year occup_orig_year occup_isco_year occup_skill_year occup_year unitwage_year whours_year wmonths_year wage_total_year contract_year healthins_year socialsec_year union_year firmsize_l_year firmsize_u_year empstat_2_year ocusec_2_year industry_orig_2_year industrycat_isic_2_year industrycat10_2_year industrycat4_2_year occup_orig_2_year occup_isco_2_year occup_skill_2_year occup_2_year wage_no_compen_2_year unitwage_2_year whours_2_year wmonths_2_year wage_total_2_year firmsize_l_2_year firmsize_u_2_year t_hours_others_year t_wage_nocompen_others_year t_wage_others_year t_hours_total_year t_wage_nocompen_total_year t_wage_total_year njobs t_hours_annual linc_nc laborincome" + + foreach v of local lab_var { + cap confirm numeric variable `v' + if _rc == 0 { // is indeed numeric + replace `v'=. if ( age < minlaborage & !missing(age) ) + } + else { // is not + replace `v'= "" if ( age < minlaborage & !missing(age) ) + } + + } + +* +} + + +/*%%============================================================================================= + 9: Final steps +==============================================================================================%%*/ + +quietly{ + +*<_% KEEP VARIABLES - ALL_> + + keep countrycode survname survey icls_v isced_version isco_version isic_version year vermast veralt harmonization int_year int_month hhid pid weight weight_m weight_q weight_old_series weight_m_old_series weight_q_old_series psu strata wave panel visit_no urban subnatid1 subnatid2 subnatid3 subnatidsurvey subnatid1_prev subnatid2_prev subnatid3_prev gaul_adm1_code gaul_adm2_code gaul_adm3_code hsize age male relationharm relationcs marital eye_dsablty hear_dsablty walk_dsablty conc_dsord slfcre_dsablty comm_dsablty migrated_mod_age migrated_ref_time migrated_binary migrated_years migrated_from_urban migrated_from_cat migrated_from_code migrated_from_country migrated_reason ed_mod_age school literacy educy educat7 educat5 educat4 educat_orig educat_isced vocational vocational_type vocational_length_l vocational_length_u vocational_field_orig vocational_financed minlaborage lstatus potential_lf underemployment nlfreason unempldur_l unempldur_u empstat ocusec industry_orig industrycat_isic industrycat10 industrycat4 occup_orig occup_isco occup_skill occup wage_no_compen unitwage whours wmonths wage_total contract healthins socialsec union firmsize_l firmsize_u empstat_2 ocusec_2 industry_orig_2 industrycat_isic_2 industrycat10_2 industrycat4_2 occup_orig_2 occup_isco_2 occup_skill_2 occup_2 wage_no_compen_2 unitwage_2 whours_2 wmonths_2 wage_total_2 firmsize_l_2 firmsize_u_2 t_hours_others t_wage_nocompen_others t_wage_others t_hours_total t_wage_nocompen_total t_wage_total lstatus_year potential_lf_year underemployment_year nlfreason_year unempldur_l_year unempldur_u_year empstat_year ocusec_year industry_orig_year industrycat_isic_year industrycat10_year industrycat4_year occup_orig_year occup_isco_year occup_skill_year occup_year wage_no_compen_year unitwage_year whours_year wmonths_year wage_total_year contract_year healthins_year socialsec_year union_year firmsize_l_year firmsize_u_year empstat_2_year ocusec_2_year industry_orig_2_year industrycat_isic_2_year industrycat10_2_year industrycat4_2_year occup_orig_2_year occup_isco_2_year occup_skill_2_year occup_2_year wage_no_compen_2_year unitwage_2_year whours_2_year wmonths_2_year wage_total_2_year firmsize_l_2_year firmsize_u_2_year t_hours_others_year t_wage_nocompen_others_year t_wage_others_year t_hours_total_year t_wage_nocompen_total_year t_wage_total_year njobs t_hours_annual linc_nc laborincome + +* + +*<_% ORDER VARIABLES_> + + order countrycode survname survey icls_v isced_version isco_version isic_version year vermast veralt harmonization int_year int_month hhid pid weight weight_m weight_q weight_old_series weight_m_old_series weight_q_old_series psu strata wave panel visit_no urban subnatid1 subnatid2 subnatid3 subnatidsurvey subnatid1_prev subnatid2_prev subnatid3_prev gaul_adm1_code gaul_adm2_code gaul_adm3_code hsize age male relationharm relationcs marital eye_dsablty hear_dsablty walk_dsablty conc_dsord slfcre_dsablty comm_dsablty migrated_mod_age migrated_ref_time migrated_binary migrated_years migrated_from_urban migrated_from_cat migrated_from_code migrated_from_country migrated_reason ed_mod_age school literacy educy educat7 educat5 educat4 educat_orig educat_isced vocational vocational_type vocational_length_l vocational_length_u vocational_field_orig vocational_financed minlaborage lstatus potential_lf underemployment nlfreason unempldur_l unempldur_u empstat ocusec industry_orig industrycat_isic industrycat10 industrycat4 occup_orig occup_isco occup_skill occup wage_no_compen unitwage whours wmonths wage_total contract healthins socialsec union firmsize_l firmsize_u empstat_2 ocusec_2 industry_orig_2 industrycat_isic_2 industrycat10_2 industrycat4_2 occup_orig_2 occup_isco_2 occup_skill_2 occup_2 wage_no_compen_2 unitwage_2 whours_2 wmonths_2 wage_total_2 firmsize_l_2 firmsize_u_2 t_hours_others t_wage_nocompen_others t_wage_others t_hours_total t_wage_nocompen_total t_wage_total lstatus_year potential_lf_year underemployment_year nlfreason_year unempldur_l_year unempldur_u_year empstat_year ocusec_year industry_orig_year industrycat_isic_year industrycat10_year industrycat4_year occup_orig_year occup_isco_year occup_skill_year occup_year wage_no_compen_year unitwage_year whours_year wmonths_year wage_total_year contract_year healthins_year socialsec_year union_year firmsize_l_year firmsize_u_year empstat_2_year ocusec_2_year industry_orig_2_year industrycat_isic_2_year industrycat10_2_year industrycat4_2_year occup_orig_2_year occup_isco_2_year occup_skill_2_year occup_2_year wage_no_compen_2_year unitwage_2_year whours_2_year wmonths_2_year wage_total_2_year firmsize_l_2_year firmsize_u_2_year t_hours_others_year t_wage_nocompen_others_year t_wage_others_year t_hours_total_year t_wage_nocompen_total_year t_wage_total_year njobs t_hours_annual linc_nc laborincome + +* + +*<_% DROP UNUSED LABELS_> + + * Store all labels in data + label dir + local all_lab `r(names)' + + * Store all variables with a label, extract value label names + local used_lab = "" + ds, has(vallabel) + + local labelled_vars `r(varlist)' + + foreach varName of local labelled_vars { + local y : value label `varName' + local used_lab `"`used_lab' `y'"' + } + + * Compare lists, `notused' is list of labels in directory but not used in final variables + local notused : list all_lab - used_lab // local `notused' defines value labs not in remaining vars + local notused_len : list sizeof notused // store size of local + + * drop labels if the length of the notused vector is 1 or greater, otherwise nothing to drop + if `notused_len' >= 1 { + label drop `notused' + } + else { + di "There are no unused labels to drop. No value labels dropped." + } + + +* + +} + +*<_% DELETE MISSING VARIABLES_> + +quietly: describe, varlist +local kept_vars `r(varlist)' + +foreach var of local kept_vars { + + capture assert missing(`var') + if !_rc drop `var' +} + +* + + +*<_% COMPRESS_> + +compress + +* + + +*<_% SAVE_> + +save "`path_output'/`level_2_harm'_ALL.dta", replace + +* diff --git a/GLD/ARM/ARM_2019_LFS/ARM_2019_LFS_V01_M_V03_A_GLD/Programs/ARM_2019_LFS_V01_M_V03_A_GLD_ALL.do b/GLD/ARM/ARM_2019_LFS/ARM_2019_LFS_V01_M_V03_A_GLD/Programs/ARM_2019_LFS_V01_M_V03_A_GLD_ALL.do new file mode 100644 index 000000000..baa9dfe55 --- /dev/null +++ b/GLD/ARM/ARM_2019_LFS/ARM_2019_LFS_V01_M_V03_A_GLD/Programs/ARM_2019_LFS_V01_M_V03_A_GLD_ALL.do @@ -0,0 +1,1807 @@ + +/*%%============================================================================================= + 0: GLD Harmonization Preamble +================================================================================================*/ + +/* ----------------------------------------------------------------------- +<_Program name_> ARM_2019_LFS_V01_M_V03_A_GLD_ALL.do +<_Application_> Stata SE 18 <_Application_> +<_Author(s)_> Wolrd Bank Job's Group +<_Date created_> 2024-1-05 +------------------------------------------------------------------------- +<_Country_> Armenia (ARM) +<_Survey Title_> National Labour Force Survey +<_Survey Year_> 2019 +<_Study ID_> ARM_2019_LFS_v01_M +<_Data collection from (M/Y)_> [01/2019] +<_Data collection to (M/Y)_> [12/2019] +<_Source of dataset_> The Armenian 2019 to 2021 data is downloaded from + the website of Statistical Committee of the + Republic of Armenia:https://armstat.am/en/?nid=212 + The data is publicly available. +<_Sample size (HH)_> 7,768 +<_Sample size (IND)_> 27,854 +<_Sampling method_> A stratified two-stage probability sample design + with 14 domains as the primary strata and 18,000 + households as the SSU. +<_Geographic coverage_> All 11 regions/marzes. +<_Currency_> Armenian Dram +----------------------------------------------------------------------- +<_ICLS Version_> ICLS 19 +<_ISCED Version_> ISCED-2011 +<_ISCO Version_> ISCO 08 +<_OCCUP National_> NSCO +<_ISIC Version_> ISIC Rev.4 +<_INDUS National_> ISIC Rev.4 +----------------------------------------------------------------------- + +<_Version Control_> + +* Date: 2024-09-24 - Update vars educy, educat7, educat_isced +* Date: 2024-10-10 - Include weight by quarter, old weight variable, correct contract variable, drop migration + + + +-------------------------------------------------------------------------*/ + + +/*%%============================================================================================= + 1: Setting up of program environment, dataset +================================================================================================*/ + +*----------1.1: Initial commands------------------------------* + +clear +set more off +set mem 800m + +*----------1.2: Set directories------------------------------* + +* Define path sections +local server "Y:/GLD" +local country "ARM" +local year "2019" +local survey "LFS" +local vermast "V01" +local veralt "V03" + +* From the definitions, set path chunks +local level_1 "`country'_`year'_`survey'" +local level_2_mast "`level_1'_`vermast'_M" +local level_2_harm "`level_1'_`vermast'_M_`veralt'_A_GLD" + +* From chunks, define path_in, path_output folder +local path_in_stata "`server'/`country'/`level_1'/`level_2_mast'/Data/Stata" +local path_in_other "`server'/`country'/`level_1'/`level_2_mast'/Data/Original" +local path_output "`server'/`country'/`level_1'/`level_2_harm'/Data/Harmonized" + +* Define Output file name +local out_file "`level_2_harm'_ALL.dta" + + +*----------1.3: Database assembly------------------------------* + +* All steps necessary to merge datasets (if several) to have all elements needed to produce +* harmonized output in a single file + +use "`path_in_stata'/ARM_LFS_2019_raw.dta", clear + +/*%%============================================================================================= + 2: Survey & ID +================================================================================================*/ + +{ + +*<_countrycode_> + gen str4 countrycode="`country'" + label var countrycode "Country code" +* + + +*<_survname_> + gen survname="LFS" + label var survname "Survey acronym" +* + + +*<_survey_> + gen survey="LFS" + label var survey "Survey type" +* + + +*<_icls_v_> + gen icls_v="ICLS-19" + label var icls_v "ICLS version underlying questionnaire questions" +* + + +*<_isced_version_> + gen isced_version="isced_2011" + label var isced_version "Version of ISCED used for educat_isced" +* + + +*<_isco_version_> + gen isco_version="" + label var isco_version "Version of ISCO used" +* + + +*<_isic_version_> + gen isic_version="" + label var isic_version "Version of ISIC used" +* + + +*<_year_> + gen int year=`year' + label var year "Year of survey" +* + + +*<_vermast_> + gen str3 vermast="`vermast'" + label var vermast "Version of master data" +* + + +*<_veralt_> + gen str3 veralt="`veralt'" + label var veralt "Version of the alt/harmonized data" +* + + +*<_harmonization_> + gen harmonization="GLD" + label var harmonization "Type of harmonization" +* + + +*<_int_year_> + gen int_year=`year' + label var int_year "Year of the interview" +* + + +*<_int_month_> + gen int_month=A6_Month + label de lblint_month 1 "January" 2 "February" 3 "March" 4 "April" 5 "May" 6 "June" 7 "July" 8 "August" 9 "September" 10 "October" 11 "November" 12 "December" + label value int_month lblint_month + label var int_month "Month of the interview" +* + + +*<_hhid_> + tostring A1, gen(hid) format(%03.0f) + tostring A6_Month, gen(month) format(%03.0f) + egen hhid=concat(month hid) + label var hhid "Household id" +* + + +*<_pid_> + sort hhid B4 + bys hhid: gen memberid=_n + tostring memberid, gen(id_str) format(%02.0f) + egen pid=concat(hhid id_str), punct("-") + label var pid "Individual ID" +* + + +*<_weight_> + gen weight = WeightsCalib_year + label var weight "Household sampling weight" +* + + +*<_weight_m_> + gen weight_m = . + label var weight_m "Survey sampling weight to obtain national estimates for each month" +* + + +*<_weight_q_> + egen weight_q = rowtotal(WeightsCalib_1 WeightsCalib_2 WeightsCalib_3 WeightsCalib_4) + label var weight_q "Survey sampling weight to obtain national estimates for each quarter" +* + + +*<_weight_old_series_> + gen weight_old_series = Weights_year + label var weight_old_series "Household sampling weight - Old 2014-2017 series weight" +* + + +*<_weight_m_old_series_> + gen weight_m_old_series = . + label var weight_m_old_series "Survey sampling weight to obtain national estimates for each month - Old 2014-2017 series weight" +* + + +*<_weight_q_old_series_> + egen weight_q_old_series = rowtotal(Weights_1 Weights_2 Weights_3 Weights_4) + label var weight_q_old_series "Survey sampling weight to obtain national estimates for each quarter - Old 2014-2017 series weight" +* + + +*<_psu_> + gen psu=. + label var psu "Primary sampling units" +* + + +*<_ssu_> + gen ssu=hhid + label var ssu "Secondary sampling units" +* + + +*<_strata_> + decode A3, gen(marzname) + decode A5, gen(urbanstat) + gen strata=marzname+" "+urbanstat + label var strata "Strata" +* + + +*<_wave_> + gen wave=. + replace wave=1 if inrange(int_month,1,3) + replace wave=2 if inrange(int_month,4,6) + replace wave=3 if inrange(int_month,7,9) + replace wave=4 if inrange(int_month,10,12) + label var wave "Survey wave" +* + + +*<_panel_> + gen panel="" + label var panel "Panel individual belongs to" +* + + +*<_visit_no_> + gen visit_no=. + label var visit_no "Visit number in panel" +* +} + +/*%%============================================================================================= + 3: Geography +================================================================================================*/ + +{ + +*<_urban_> + gen urban=A5 + recode urban (2=0) + la de lblurban 1 "Urban" 0 "Rural" + label values urban lblurban + label var urban "Location is urban" +* + + +*<_subnatid1_> + gen subnatid1=A3 + tostring subnatid1, replace + replace subnatid1=subnatid1+" - "+marzname + + * Unite names to entire series + replace subnatid1 = "7 - Kotayk" if subnatid1 == "7 - kotayk" + replace subnatid1 = "10 - Vayoc Dzor" if subnatid1 == "10 - Vayots dzor" + + label var subnatid1 "Subnational ID at First Administrative Level" +* + + +*<_subnatid2_> + gen subnatid2=. + label var subnatid2 "Subnational ID at Second Administrative Level" +* + + +*<_subnatid3_> + gen subnatid3=. + label var subnatid3 "Subnational ID at Third Administrative Level" +* + + +*<_subnatidsurvey_> + gen subnatidsurvey=subnatid1+" "+urbanstat + label var subnatidsurvey "Administrative level at which survey is representative" +* + + +*<_subnatid1_prev_> + +/* <_subnatid1_prev_note_> +subnatid1_prev is coded as missing unless the classification used for subnatid1 has changed since the previous survey. + */ + + gen subnatid1_prev=. + label var subnatid1_prev "Classification used for subnatid1 from previous survey" +* + + +*<_subnatid2_prev_> + gen subnatid2_prev=. + label var subnatid2_prev "Classification used for subnatid2 from previous survey" +* + + +*<_subnatid3_prev_> + gen subnatid3_prev=. + label var subnatid3_prev "Classification used for subnatid3 from previous survey" +* + + +*<_gaul_adm1_code_> + gen gaul_adm1_code=. + label var gaul_adm1_code "Global Administrative Unit Layers (GAUL) Admin 1 code" +* + + +*<_gaul_adm2_code_> + gen gaul_adm2_code=. + label var gaul_adm2_code "Global Administrative Unit Layers (GAUL) Admin 2 code" +* + + +*<_gaul_adm3_code_> + gen gaul_adm3_code=. + label var gaul_adm3_code "Global Administrative Unit Layers (GAUL) Admin 3 code" +* + +} + +/*%%============================================================================================= + 4: Demography +================================================================================================*/ + +{ + +*<_hsize_> + bys hhid: egen hsize=max(memberid) + label var hsize "Household size" +* + + +*<_age_> + gen age=Age + replace age=. if Age<0 + replace age=98 if age>98 & age!=. + label var age "Individual age" +* + + +*<_male_> + gen male=B3 + recode male 2=0 + label var male "Sex - Ind is male" + la de lblmale 1 "Male" 0 "Female" + label values male lblmale +* + + +*<_relationharm_> + +/*<_relationharm_note_> + +21 households (70 observations) in the raw data set do not have household heads. +Their household IDs are: + +001125 001258 001645 002341 002371 +002389 002391 003182 003346 003368 +003476 004351 005046 005355 006637 +007039 007188 007295 007570 009403 +012496 + +During the harmonization, we did not assign household heads to these households. +But users can assign household heads based on their relationship to the head and +other characteristics such as gender and age. + +*<_relationharm_note_>*/ + + gen byte relationharm=B4 + recode relationharm (6 9=3) (7 8=4) (10=5) (11=6) + label var relationharm "Relationship to the head of household - Harmonized" + la de lblrelationharm 1 "Head of household" 2 "Spouse" 3 "Children" 4 "Parents" 5 "Other relatives" 6 "Other and non-relatives" + label values relationharm lblrelationharm +*<_relationharm_> + + +*<_relationcs_> + gen relationcs=B4 + label var relationcs "Relationship to the head of household - Country original" +* + + +*<_marital_> + gen marital=B11 + recode marital (1=2) (2=1) (3=5) + label var marital "Marital status" + la de lblmarital 1 "Married" 2 "Never Married" 3 "Living together" 4 "Divorced/Separated" 5 "Widowed" + label values marital lblmarital +* + + +*<_eye_dsablty_> + gen eye_dsablty=. + la de lbleye_dsablty 1 "No" 2 "Yes-some" 3 "Yes-a lot" 4 "Cannot at all" + label values eye_dsablty lbleye_dsablty + label var eye_dsablty "Disability related to eyesight" +* + + +*<_hear_dsablty_> + gen hear_dsablty=. + la de lblhear_dsablty 1 "No" 2 "Yes-some" 3 "Yes-a lot" 4 "Cannot at all" + label values hear_dsablty lblhear_dsablty + label var hear_dsablty "Disability related to hearing" +* + + +*<_walk_dsablty_> + gen walk_dsablty=. + la de lblwalk_dsablty 1 "No" 2 "Yes-some" 3 "Yes-a lot" 4 "Cannot at all" + label values walk_dsablty lblwalk_dsablty + label var walk_dsablty "Disability related to walking or climbing stairs" +* + + +*<_conc_dsord_> + gen conc_dsord=. + la de lblconc_dsord 1 "No" 2 "Yes-some" 3 "Yes-a lot" 4 "Cannot at all" + label values conc_dsord lblconc_dsord + label var conc_dsord "Disability related to concentration or remembering" +* + + +*<_slfcre_dsablty_> + gen slfcre_dsablty=. + la de lblslfcre_dsablty 1 "No" 2 "Yes-some" 3 "Yes-a lot" 4 "Cannot at all" + label values slfcre_dsablty lblslfcre_dsablty + label var eye_dsablty "Disability related to selfcare" +* + + +*<_comm_dsablty_> + gen comm_dsablty=. + la de lblcomm_dsablty 1 "No" 2 "Yes-some" 3 "Yes-a lot" 4 "Cannot at all" + label values comm_dsablty lblcomm_dsablty + label var eye_dsablty "Disability related to communicating" +* + +} + + +/*%%============================================================================================= + 5: Migration +==============================================================================================%%*/ + + +{ + +*<_migrated_mod_age_> + gen migrated_mod_age = . + label var migrated_mod_age "Migration module application age" +* + + +*<_migrated_ref_time_> + gen migrated_ref_time = . + label var migrated_ref_time "Reference time applied to migration questions (in years)" +* + + +*<_migrated_binary_> + gen migrated_binary = . + label de lblmigrated_binary 0 "No" 1 "Yes" + label values migrated_binary lblmigrated_binary + label var migrated_binary "Individual has migrated" +* + + +*<_migrated_years_> + gen migrated_years = . + label var migrated_years "Years since latest migration" +* + + +*<_migrated_from_urban_> + gen migrated_from_urban = . + label de lblmigrated_from_urban 0 "Rural" 1 "Urban" + label values migrated_from_urban lblmigrated_from_urban + label var migrated_from_urban "Migrated from area" +* + + +*<_migrated_from_cat_> + gen migrated_from_cat = . + label de lblmigrated_from_cat 1 "From same admin3 area" 2 "From same admin2 area" 3 "From same admin1 area" 4 "From other admin1 area" 5 "From other country" + label values migrated_from_cat lblmigrated_from_cat + label var migrated_from_cat "Category of migration area" +* + + +*<_migrated_from_code_> + gen migrated_from_code = . + *label de lblmigrated_from_code + *label values migrated_from_code lblmigrated_from_code + label var migrated_from_code "Code of migration area as subnatid level of migrated_from_cat" +* + + +*<_migrated_from_country_> + gen migrated_from_country = . + label var migrated_from_country "Code of migration country (ISO 3 Letter Code)" +* + + +*<_migrated_reason_> + gen migrated_reason = . + label de lblmigrated_reason 1 "Family reasons" 2 "Educational reasons" 3 "Employment" 4 "Forced (political reasons, natural disaster, …)" 5 "Other reasons" + label values migrated_reason lblmigrated_reason + label var migrated_reason "Reason for migrating" +* + + +} + + +/*%%============================================================================================= + 6: Education +================================================================================================*/ + + +{ +*<_ed_mod_age_> + gen byte ed_mod_age=6 + label var ed_mod_age "Education module application age" +* + + +*<_school_> + gen school=B9 + recode school (2=0) (3/5=.) + replace school=. if age + + +*<_literacy_> + gen byte literacy=. + replace literacy=0 if B7==1 + replace literacy=1 if inrange(B7,2,11) + replace literacy=. if age + + +*<_educy_> + gen byte educy=. + replace educy = 0 if B7 == 1 | B7 == 2 + replace educy = 4 if B7 == 3 + replace educy = 9 if B7 == 4 + replace educy = 12 if B7 == 5 + replace educy = 11 if B7 == 6 + replace educy = 15 if B7 == 7 + replace educy = 16 if B7 == 8 + replace educy = 18 if B7 == 9 | B7 == 10 + replace educy = 20 if B7 == 11 + replace educy=. if ageage & !mi(educy) & !mi(age) + label var educy "Years of education" +* + + +*<_educat7_> + gen byte educat7= B7 + recode educat7 (6=5) (7=6) (8/11=7) + replace educat7=. if age + + +*<_educat5_> + gen byte educat5=educat7 + recode educat5 (4=3) (5=4) (6 7=5) + replace educat5=. if age + + +*<_educat4_> + gen byte educat4=educat5 + replace educat4=. if age + + +*<_educat_orig_> + gen educat_orig=B7 + label var educat_orig "Original survey education code" +* + + +*<_educat_isced_> + gen educat_isced=. + label var educat_isced "ISCED standardised level of education" +* + + +*<_educat_isced_v_> + gen educat_isced_v="ISCED-2011" + label var educat_isced_v "Version of the ISCED used" +* + +*----------6.1: Education cleanup------------------------------* + +*<_% Correction min age_> + +** Drop info for cases under the age for which questions to be asked (do not need a variable for this) +local ed_var school literacy educy educat7 educat5 educat4 educat_isced +foreach v of local ed_var { + replace `v'=. if ( age < ed_mod_age & !missing(age) ) +} +replace educat_isced_v="." if ( age < ed_mod_age & !missing(age) ) +* + +} + +/*%%============================================================================================= + 7: Training +================================================================================================*/ + +{ + +*<_vocational_> + gen vocational=. + la de vocationallbl 1 "Yes" 0 "No" + la values vocational vocationallbl + label var vocational "Ever received vocational training" +* + + +*<_vocational_type_> + gen vocational_type=. + label de lblvocational_type 1 "Inside Enterprise" 2 "External" + label values vocational_type lblvocational_type + label var vocational_type "Type of vocational training" +* + + +*<_vocational_length_l_> + gen vocational_length_l=. + replace vocational_length_l=. if vocational!=1 + label var vocational_length_l "Length of training in months, lower limit" +* + + +*<_vocational_length_u_> + gen vocational_length_u=. + replace vocational_length_u=. if vocational!=1 + label var vocational_length_u "Length of training in months, upper limit" +* + + +*<_vocational_field_orig_> + gen vocational_field_orig=. + replace vocational_field_orig=. if vocational!=1 + label var vocational_field_orig "Original field of training information" +* + + +*<_vocational_financed_> + gen vocational_financed=. + label de lblvocational_financed 1 "Employer" 2 "Government" 3 "Mixed Employer/Government" 4 "Own funds" 5 "Other" + label var vocational_financed "How training was financed" +* + +} + +/*%%============================================================================================= + 8: Labour +================================================================================================*/ + +*<_minlaborage_> + +/*<_minlaborage_note_> + +The age range for the labor section is 15-75. + +*<_minlaborage_note_>*/ + + gen byte minlaborage=15 + label var minlaborage "Labor module application age" +* + + +*----------8.1: 7 day reference overall------------------------------* + +{ +*<_lstatus_> + +/*<_lstatus_note> + +The economically inavtive population also needs to be within the age range of +15 and 75. + +*<_lstatus_note>*/ + + gen byte lstatus=. + replace lstatus=1 if D1==1|inrange(D3,1,5)|D4==1|D5==1 + replace lstatus=2 if lstatus==.&inrange(J9,1,3) + replace lstatus=3 if !mi(J1_4group)&lstatus==. + replace lstatus=. if !inrange(age,15,75) + label var lstatus "Labor status" + la de lbllstatus 1 "Employed" 2 "Unemployed" 3 "Non-LF" + label values lstatus lbllstatus +* + + +*<_potential_lf_> + +/*<_potential_lf_note_> +Note: var "potential_lf" only takes value if the respondent is not in labor force. (lstatus==3) + +"potential_lf"=1 if the person is +1)available but not searching or (J16==1)&J9==4 +2)searching but not immediately available to work or inrange(J9,1,3)&J16==2 + +*/ + + gen potential_lf=. + replace potential_lf=1 if [(J16==1)&J9==4] | [inrange(J9,1,3)&J16==2] + replace potential_lf=0 if [(J16==1)&inrange(J9,1,3)] | [inrange(J9,1,3)&J16==1] + replace potential_lf=. if age75&!mi(age)] + replace potential_lf=. if lstatus!=3 + label var potential_lf "Potential labour force status" + la de lblpotential_lf 0 "No" 1 "Yes" + label values potential_lf lblpotential_lf +* + + +*<_underemployment_> + gen byte underemployment=G4 + replace underemployment=1 if inrange(G4,1,3) + replace underemployment=0 if G4==4 + replace underemployment=. if age75&!mi(age)] + replace underemployment=. if lstatus!=1 + label var underemployment "Underemployment status" + la de lblunderemployment 0 "No" 1 "Yes" + label values underemployment lblunderemployment +* + + +*<_nlfreason_> + gen byte nlfreason=J1_4group + recode nlfreason (4=5) + replace nlfreason=. if age75&!mi(age)] + replace nlfreason=. if lstatus!=3 + label var nlfreason "Reason not in the labor force" + la de lblnlfreason 1 "Student" 2 "Housekeeper" 3 "Retired" 4 "Disabled" 5 "Other" + label values nlfreason lblnlfreason +* + + +*<_unempldur_l_> + gen byte unempldur_l=J4 + recode unempldur_l (1=0) (2=3) (3=6) (4=9) (5=12) (6=24) (7=36) + replace unempldur_l=. if age75&!mi(age)] + replace unempldur_l=. if lstatus!=2 + label var unempldur_l "Unemployment duration (months) lower bracket" +* + + +*<_unempldur_u_> + gen byte unempldur_u=J4 + recode unempldur_u (1=3) (2=6) (3=9) (4=12) (5=24) (6=36) (7=.) + replace unempldur_u=. if age75&!mi(age)] + replace unempldur_u=. if lstatus!=2 + label var unempldur_u "Unemployment duration (months) upper bracket" +* +} + + +*----------8.2: 7 day reference main job------------------------------* + + +{ +*<_empstat_> + gen byte empstat=E7 + recode empstat (2=1) (5=2) (7=5) + replace empstat=. if lstatus!=1|age + + +*<_ocusec_> + gen byte ocusec=E10 + recode ocusec (3 4=2) + replace ocusec=. if lstatus!=1|age + + +*<_industry_orig_> + gen industry_orig=E4_21group + replace industry_orig=. if lstatus!=1 + label var industry_orig "Original survey industry code, main job 7 day recall" +* + + +*<_industrycat_isic_> + gen industrycat_isic="" +quietly +{ + replace industrycat_isic="A" if E4_21group==1 + replace industrycat_isic="B" if E4_21group==2 + replace industrycat_isic="C" if E4_21group==3 + replace industrycat_isic="D" if E4_21group==4 + replace industrycat_isic="E" if E4_21group==5 + replace industrycat_isic="F" if E4_21group==6 + replace industrycat_isic="G" if E4_21group==7 + replace industrycat_isic="H" if E4_21group==8 + replace industrycat_isic="I" if E4_21group==9 + replace industrycat_isic="J" if E4_21group==10 + replace industrycat_isic="K" if E4_21group==11 + replace industrycat_isic="L" if E4_21group==12 + replace industrycat_isic="M" if E4_21group==13 + replace industrycat_isic="N" if E4_21group==14 + replace industrycat_isic="O" if E4_21group==15 + replace industrycat_isic="P" if E4_21group==16 + replace industrycat_isic="Q" if E4_21group==17 + replace industrycat_isic="R" if E4_21group==18 + replace industrycat_isic="S" if E4_21group==19 + replace industrycat_isic="T" if E4_21group==20 + replace industrycat_isic="U" if E4_21group==21 +} + + replace industrycat_isic="" if industrycat_isic=="."|lstatus!=1 + label var industrycat_isic "ISIC code of primary job 7 day recall" +* + + +*<_industrycat10_> + gen industrycat10=E4_21group + recode industrycat10 (5=4) (6=5) (7 9=6) (8 10=7) (11/14=8) (15=9) (16/21=10) + replace industrycat10=. if lstatus!=1 + label var industrycat10 "1 digit industry classification, primary job 7 day recall" + la de lblindustrycat10 1 "Agriculture" 2 "Mining" 3 "Manufacturing" 4 "Public utilities" 5 "Construction" 6 "Commerce" 7 "Transport and Comnunications" 8 "Financial and Business Services" 9 "Public Administration" 10 "Other Services, Unspecified" + label values industrycat10 lblindustrycat10 +* + + +*<_industrycat4_> + gen byte industrycat4=industrycat10 + recode industrycat4 (3/5=2)(6/9=3)(10=4) + label var industrycat4 "1 digit industry classification (Broad Economic Activities), primary job 7 day recall" + la de lblindustrycat4 1 "Agriculture" 2 "Industry" 3 "Services" 4 "Other" + label values industrycat4 lblindustrycat4 +* + + +*<_occup_orig_> + gen occup_orig=E2_9group + replace occup_orig=. if lstatus!=1|[age>75&!mi(age)] + label var occup_orig "Original occupation record primary job 7 day recall" +* + + +*<_occup_isco_> + gen occup_isco="" + replace occup_isco="" if lstatus!=1 | occup_isco=="." + label var occup_isco "ISCO code of primary job 7 day recall" +* + + +*<_occup_skill_> + gen occup_skill=E2_9group + replace occup_skill=1 if E2_9group==9 + replace occup_skill=2 if inrange(E2_9group, 4, 8) + replace occup_skill=3 if inrange(E2_9group, 1, 3) + replace occup_skill=. if lstatus!=1 + la de lblskill 1 "Low skill" 2 "Medium skill" 3 "High skill" + label values occup_skill lblskill + label var occup_skill "Skill based on ISCO standard primary job 7 day recall" +* + + +*<_occup_> + gen occup=E2_9group + replace occup=. if lstatus!=1|[age>75&!mi(age)] + label var occup "1 digit occupational classification, primary job 7 day recall" + la de lbloccup 1 "Managers" 2 "Professionals" 3 "Technicians" 4 "Clerks" 5 "Service and market sales workers" 6 "Skilled agricultural" 7 "Craft workers" 8 "Machine operators" 9 "Elementary occupations" 10 "Armed forces" 99 "Others" + label values occup lbloccup +* + + +*<_wage_no_compen_> + +/*<_wage_no_compen_note_> + +The wage questions in the questionnare are organized into to parts: the first part +asks for the specific number of income if the given respondent could recall and was +willing to answer; the second part provides different categories of income range +if the given respondent could not recall or was not willing to answer the first part. + +The general logic here is to impute wage values for people who only answered an income +range. We used industry, occupation, income categories and gender to estimate their +specific income values. + +17.33% of total non-missing wage values were imputed using this method. +*<_wage_no_compen_note_>*/ + + * Overall --> wage info (here the variable, for us it should be wage_no_compen) + * to missing if value is 0. + gen wage14=E14_1+E14_2 + replace wage14=. if wage14==0 + + * First replace outliers by + winsor2 wage14, suffix(_w) cuts(1 99) + + * Create salary categories based on winsor values + gen salary_cat=. + replace salary_cat=1 if inrange(wage14_w, 1, 55000) + replace salary_cat=2 if wage14_w==55000 + replace salary_cat=3 if inrange(wage14_w, 55001, 110000) + replace salary_cat=4 if inrange(wage14_w, 110001, 220000) + replace salary_cat=5 if inrange(wage14_w, 220001, 440000) + replace salary_cat=6 if inrange(wage14_w, 440001, 600000) + replace salary_cat=7 if inrange(wage14_w, 600001, 700000) + + * Preserve to collapse, so we can merge the info in + preserve + + * Collpase by industry, sex, and salary categories + collapse (mean)wage14_w[iw=weight], by(industrycat10 occup male urban salary_cat) + + * Rename variable, otherwise when merging in, master version of an equally name one will be kept + rename wage14_w wage_group_estimate + + * Rename salary_cat to D15 since this is what we want the info to latch on to + rename salary_cat E15 + tempfile salary_helper + save "`salary_helper'" + + * Restore, merge in + restore + merge m:1 industrycat10 occup male urban E15 using "`salary_helper'", keep(matched master) nogen + + * Create wage variable + gen wage_no_compen=. + + * Fill it first with values that are accurate + replace wage_no_compen=wage14 if !mi(wage14)&mi(E15) + + * Now add the categorised means + replace wage_no_compen=wage_group_estimate if inrange(E15,1,8)&!mi(wage_group_estimate) + + * Keep only for employed employees, label + replace wage_no_compen=. if lstatus!=1|empstat==2 + label var wage_no_compen "Last wage payment primary job 7 day recall" +* + + +*<_unitwage_> + gen byte unitwage=E16 + recode unitwage (4=5) (5=7) (6=8) (7=10) + replace unitwage=. if lstatus!=1 | empstat==2 + label var unitwage "Last wages' time unit primary job 7 day recall" + la de lblunitwage 1 "Daily" 2 "Weekly" 3 "Every two weeks" 4 "Bimonthly" 5 "Monthly" 6 "Trimester" 7 "Biannual" 8 "Annually" 9 "Hourly" 10 "Other" + label values unitwage lblunitwage +* + + +*<_whours_> + gen whours=G2_1 + replace whours=. if lstatus!=1|G2_1==0 + label var whours "Hours of work in last week primary job 7 day recall" +* + + +*<_wmonths_> + gen wmonths=. + label var wmonths "Months of work in past 12 months primary job 7 day recall" +* + + +*<_wage_total_> + gen wage_total=. + label var wage_total "Annualized total wage primary job 7 day recall" +* + + +*<_contract_> + +/*<_contract_note_> + +There is no separate contract question in the questionnaire. +This contract variable was coded based on employment status question which asks +wether an employed respondent had a contract or not. + +*<_contract_note_>*/ + + gen byte contract = . + replace contract = (E7 == 1) + replace contract=. if lstatus!=1 + label var contract "Employment has contract primary job 7 day recall" + la de lblcontract 0 "Without contract" 1 "With contract" + label values contract lblcontract +* + + +*<_healthins_> + gen byte healthins=. + replace healthins=1 if E8_f==1 + replace healthins=0 if E8_f==2 + replace healthins=. if lstatus!=1 + label var healthins "Employment has health insurance primary job 7 day recall" + la de lblhealthins 0 "Without health insurance" 1 "With health insurance" + label values healthins lblhealthins +* + + +*<_socialsec_> + gen byte socialsec=. + replace socialsec=. if lstatus!=1 + label var socialsec "Employment has social security insurance primary job 7 day recall" + la de lblsocialsec 1 "With social security" 0 "Without social secturity" + label values socialsec lblsocialsec +* + + +*<_union_> + gen byte union=. + replace union=1 if E27==1 + replace union=0 if E27==2 + replace union=. if lstatus!=1 + label var union "Union membership at primary job 7 day recall" + la de lblunion 0 "Not union member" 1 "Union member" + label values union lblunion +* + + +*<_firmsize_l_> + gen byte firmsize_l=E13 + recode firmsize_l (1=1) (2=5) (3=10) (4=20) (5=50) (6=100) (7=.) + replace firmsize_l=. if lstatus!=1 + label var firmsize_l "Firm size (lower bracket) primary job 7 day recall" +* + + +*<_firmsize_u_> + gen byte firmsize_u=E13 + recode firmsize_u (1=5) (2=9) (3=19) (4=49) (5=99) (6=.) + replace firmsize_u=. if lstatus!=1 + label var firmsize_u "Firm size (upper bracket) primary job 7 day recall" +* + +} + + +*----------8.3: 7 day reference secondary job------------------------------* +* Since labels are the same as main job, values are labelled using main job labels + +{ +*<_empstat_2_> + gen byte empstat_2=F4 + recode empstat_2 (2=1) (5=2) + replace empstat_2=. if lstatus!=1|F1!=1 + label var empstat_2 "Employment status during past week secondary job 7 day recall" + la de lblempstat_2 1 "Paid employee" 2 "Non-paid employee" 3 "Employer" 4 "Self-employed" 5 "Other, workers not classifiable by status" + label values empstat_2 lblempstat +* + + +*<_ocusec_2_> + gen byte ocusec_2=F6 + recode ocusec_2 (3 4=2) + replace ocusec_2=. if lstatus!=1|F1!=1 + label var ocusec_2 "Sector of activity secondary job 7 day recall" + la de lblocusec_2 1 "Public Sector, Central Government, Army" 2 "Private, NGO" 3 "State owned" 4 "Public or State-owned, but cannot distinguish" + label values ocusec_2 lblocusec_2 +* + + +*<_industry_orig_2_> + gen industry_orig_2=F3_21group + replace industry_orig_2=. if lstatus!=1|F1!=1 + label var industry_orig_2 "Original survey industry code, secondary job 7 day recall" +* + + +*<_industrycat_isic_2_> + gen industrycat_isic_2="" +quietly +{ + replace industrycat_isic_2="A" if F3_21group==1 + replace industrycat_isic_2="B" if F3_21group==2 + replace industrycat_isic_2="C" if F3_21group==3 + replace industrycat_isic_2="D" if F3_21group==4 + replace industrycat_isic_2="E" if F3_21group==5 + replace industrycat_isic_2="F" if F3_21group==6 + replace industrycat_isic_2="G" if F3_21group==7 + replace industrycat_isic_2="H" if F3_21group==8 + replace industrycat_isic_2="I" if F3_21group==9 + replace industrycat_isic_2="J" if F3_21group==10 + replace industrycat_isic_2="K" if F3_21group==11 + replace industrycat_isic_2="L" if F3_21group==12 + replace industrycat_isic_2="M" if F3_21group==13 + replace industrycat_isic_2="N" if F3_21group==14 + replace industrycat_isic_2="O" if F3_21group==15 + replace industrycat_isic_2="P" if F3_21group==16 + replace industrycat_isic_2="Q" if F3_21group==17 + replace industrycat_isic_2="R" if F3_21group==18 + replace industrycat_isic_2="S" if F3_21group==19 + replace industrycat_isic_2="T" if F3_21group==20 + replace industrycat_isic_2="U" if F3_21group==21 +} + + replace industrycat_isic_2="" if industrycat_isic_2=="."|F1!=1 + label var industrycat_isic_2 "ISIC code of secondary job 7 day recall" +* + + +*<_industrycat10_2_> + gen industrycat10_2=F3_21group + recode industrycat10_2 (5=4) (6=5) (7 9=6) (8 10=7) (11/14=8) (15=9) (16/21=10) + replace industrycat10_2=. if lstatus!=1|F1!=1 + label var industrycat10_2 "1 digit industry classification, secondary job 7 day recall" + label values industrycat10_2 lblindustrycat10 +* + + +*<_industrycat4_2_> + gen byte industrycat4_2=industrycat10_2 + recode industrycat4_2 (3/5=2)(6/9=3)(10=4) + label var industrycat4_2 "1 digit industry classification (Broad Economic Activities), secondary job 7 day recall" + label values industrycat4_2 lblindustrycat4 +* + + +*<_occup_orig_2_> + gen occup_orig_2=F2_9group + replace occup_orig_2=. if lstatus!=1|F1!=1 + label var occup_orig_2 "Original occupation record secondary job 7 day recall" +* + + +*<_occup_isco_2_> + gen occup_isco_2="" + replace occup_isco_2="" if lstatus!=1 | occup_isco_2=="."|F1!=1 + label var occup_isco_2 "ISCO code of secondary job 7 day recall" +* + + +*<_occup_skill_2_> + gen occup_skill_2=F2_9group + replace occup_skill_2=1 if F2_9group==9 + replace occup_skill_2=2 if inrange(F2_9group,4,8) + replace occup_skill_2=3 if inrange(F2_9group,1,3) + replace occup_skill_2=. if F2_9group==0|lstatus!=1|F1!=1 + label var occup_skill_2 "Skill based on ISCO standard secondary job 7 day recall" +* + + +*<_occup_2_> + gen occup_2=F2_9group + replace occup_2=. if lstatus!=1|F1!=1 + label var occup_2 "1 digit occupational classification secondary job 7 day recall" + label values occup_2 lbloccup +* + + +*<_wage_no_compen_2_> + +/*<_wage_no_compen_2_note_> + +The questionnaire actually has questions about income of the second job, just as the +main job. However, the data set does not have the variables. + +*<_wage_no_compen_2_note_>*/ + gen wage_no_compen_2=. + replace wage_no_compen_2=. if F1!=1|empstat_2==2 + label var wage_no_compen_2 "Last wage payment secondary job 7 day recall" +* + + +*<_unitwage_2_> + gen byte unitwage_2=. + replace unitwage_2=. if lstatus!=1|F1!=1 + label var unitwage_2 "Last wages' time unit secondary job 7 day recall" + label values unitwage_2 lblunitwage +* + + +*<_whours_2_> + gen whours_2=G2_2 + replace whours_2=. if G2_2==0|F1!=1 + label var whours_2 "Hours of work in last week secondary job 7 day recall" +* + + +*<_wmonths_2_> + gen wmonths_2=. + label var wmonths_2 "Months of work in past 12 months secondary job 7 day recall" +* + + +*<_wage_total_2_> + gen wage_total_2=. + label var wage_total_2 "Annualized total wage secondary job 7 day recall" +* + + +*<_firmsize_l_2_> + gen byte firmsize_l_2=. + label var firmsize_l_2 "Firm size (lower bracket) secondary job 7 day recall" +* + + +*<_firmsize_u_2_> + gen byte firmsize_u_2=. + label var firmsize_u_2 "Firm size (upper bracket) secondary job 7 day recall" +* + +} + +*----------8.4: 7 day reference additional jobs------------------------------* + +*<_t_hours_others_> + gen t_hours_others=. + label var t_hours_others "Annualized hours worked in all but primary and secondary jobs 7 day recall" +* + + +*<_t_wage_nocompen_others_> + gen t_wage_nocompen_others=. + label var t_wage_nocompen_others "Annualized wage in all but primary & secondary jobs excl. bonuses, etc. 7 day recall" +* + + +*<_t_wage_others_> + gen t_wage_others=. + label var t_wage_others "Annualized wage in all but primary and secondary jobs (12-mon ref period)" +* + + +*----------8.5: 7 day reference total summary------------------------------* + + +*<_t_hours_total_> + gen t_hours_total=. + label var t_hours_total "Annualized hours worked in all jobs 7 day recall" +* + + +*<_t_wage_nocompen_total_> + gen t_wage_nocompen_total=. + label var t_wage_nocompen_total "Annualized wage in all jobs excl. bonuses, etc. 7 day recall" +* + + +*<_t_wage_total_> + gen t_wage_total=. + label var t_wage_total "Annualized total wage for all jobs 7 day recall" +* + + +*----------8.6: 12 month reference overall------------------------------* + +{ +*<_lstatus_year_> + gen byte lstatus_year=. + replace lstatus_year=. if age + + +*<_potential_lf_year_> + gen byte potential_lf_year=. + replace potential_lf_year=. if age + + +*<_underemployment_year_> + gen byte underemployment_year=. + replace underemployment_year=. if age + + +*<_nlfreason_year_> + gen byte nlfreason_year=. + label var nlfreason_year "Reason not in the labor force" + la de lblnlfreason_year 1 "Student" 2 "Housekeeper" 3 "Retired" 4 "Disable" 5 "Other" + label values nlfreason_year lblnlfreason_year +* + + +*<_unempldur_l_year_> + gen byte unempldur_l_year=. + label var unempldur_l_year "Unemployment duration (months) lower bracket" +* + + +*<_unempldur_u_year_> + gen byte unempldur_u_year=. + label var unempldur_u_year "Unemployment duration (months) upper bracket" +* + +} + +*----------8.7: 12 month reference main job------------------------------* + +{ +*<_empstat_year_> + gen byte empstat_year=. + label var empstat_year "Employment status during past week primary job 12 month recall" + la de lblempstat_year 1 "Paid employee" 2 "Non-paid employee" 3 "Employer" 4 "Self-employed" 5 "Other, workers not classifiable by status" + label values empstat_year lblempstat_year +* + + +*<_ocusec_year_> + gen byte ocusec_year=. + label var ocusec_year "Sector of activity primary job 12 day recall" + la de lblocusec_year 1 "Public Sector, Central Government, Army" 2 "Private, NGO" 3 "State owned" 4 "Public or State-owned, but cannot distinguish" + label values ocusec_year lblocusec_year +* + + +*<_industry_orig_year_> + gen industry_orig_year=. + label var industry_orig_year "Original industry record main job 12 month recall" +* + + +*<_industrycat_isic_year_> + gen industrycat_isic_year="" + replace industrycat_isic_year="" if industrycat_isic_year=="." + label var industrycat_isic_year "ISIC code of primary job 12 month recall" +* + + +*<_industrycat10_year_> + gen byte industrycat10_year=. + label var industrycat10_year "1 digit industry classification, primary job 12 month recall" + la de lblindustrycat10_year 1 "Agriculture" 2 "Mining" 3 "Manufacturing" 4 "Public utilities" 5 "Construction" 6 "Commerce" 7 "Transport and Comnunications" 8 "Financial and Business Services" 9 "Public Administration" 10 "Other Services, Unspecified" + label values industrycat10_year lblindustrycat10_year +* + + +*<_industrycat4_year_> + gen byte industrycat4_year=industrycat10_year + recode industrycat4_year (1=1)(2 3 4 5 =2)(6 7 8 9=3)(10=4) + label var industrycat4_year "1 digit industry classification (Broad Economic Activities), primary job 12 month recall" + la de lblindustrycat4_year 1 "Agriculture" 2 "Industry" 3 "Services" 4 "Other" + label values industrycat4_year lblindustrycat4_year +* + + +*<_occup_orig_year_> + gen occup_orig_year=. + label var occup_orig_year "Original occupation record primary job 12 month recall" +* + + +*<_occup_isco_year_> + gen str4 occup_isco_year="" + label var occup_isco_year "ISCO code of primary job 12 month recall" +* + + +*<_occup_skill_year_> + gen skill_level_year=substr(occup_isco_year,1,1) + destring skill_level_year, replace + gen occup_skill_year=. + replace occup_skill_year=1 if skill_level_year==9 + replace occup_skill_year=2 if inrange(skill_level_year,4,8) + replace occup_skill_year=3 if inrange(skill_level_year,1,3) + replace occup_skill_year=. if skill_level_year==0 + label var occup_skill_year "Skill based on ISCO standard primary job 12 month recall" +* + + +*<_occup_year_> + gen byte occup_year=. + label var occup_year "1 digit occupational classification, primary job 12 month recall" + la de lbloccup_year 1 "Managers" 2 "Professionals" 3 "Technicians" 4 "Clerks" 5 "Service and market sales workers" 6 "Skilled agricultural" 7 "Craft workers" 8 "Machine operators" 9 "Elementary occupations" 10 "Armed forces" 99 "Others" + label values occup_year lbloccup_year +* + + +*<_wage_no_compen_year_> + gen double wage_no_compen_year=. + label var wage_no_compen_year "Last wage payment primary job 12 month recall" +* + + +*<_unitwage_year_> + gen byte unitwage_year=. + label var unitwage_year "Last wages' time unit primary job 12 month recall" + la de lblunitwage_year 1 "Daily" 2 "Weekly" 3 "Every two weeks" 4 "Bimonthly" 5 "Monthly" 6 "Trimester" 7 "Biannual" 8 "Annually" 9 "Hourly" 10 "Other" + label values unitwage_year lblunitwage_year +* + + +*<_whours_year_> + gen whours_year=. + label var whours_year "Hours of work in last week primary job 12 month recall" +* + + +*<_wmonths_year_> + gen wmonths_year=. + label var wmonths_year "Months of work in past 12 months primary job 12 month recall" +* + + +*<_wage_total_year_> + gen wage_total_year=. + label var wage_total_year "Annualized total wage primary job 12 month recall" +* + + +*<_contract_year_> + gen byte contract_year=. + label var contract_year "Employment has contract primary job 12 month recall" + la de lblcontract_year 0 "Without contract" 1 "With contract" + label values contract_year lblcontract_year +* + + +*<_healthins_year_> + gen byte healthins_year=. + label var healthins_year "Employment has health insurance primary job 12 month recall" + la de lblhealthins_year 0 "Without health insurance" 1 "With health insurance" + label values healthins_year lblhealthins_year +* + + +*<_socialsec_year_> + gen byte socialsec_year=. + label var socialsec_year "Employment has social security insurance primary job 7 day recall" + la de lblsocialsec_year 1 "With social security" 0 "Without social secturity" + label values socialsec_year lblsocialsec_year +* + + +*<_union_year_> + gen byte union_year=. + label var union_year "Union membership at primary job 12 month recall" + la de lblunion_year 0 "Not union member" 1 "Union member" + label values union_year lblunion_year +* + + +*<_firmsize_l_year_> + gen byte firmsize_l_year=. + label var firmsize_l_year "Firm size (lower bracket) primary job 12 month recall" +* + + +*<_firmsize_u_year_> + gen byte firmsize_u_year=. + label var firmsize_u_year "Firm size (upper bracket) primary job 12 month recall" +* + +} + + +*----------8.8: 12 month reference secondary job------------------------------* + +{ + +*<_empstat_2_year_> + gen byte empstat_2_year=. + label var empstat_2_year "Employment status during past week secondary job 12 month recall" + label values empstat_2_year lblempstat_year +* + + +*<_ocusec_2_year_> + gen byte ocusec_2_year=. + label var ocusec_2_year "Sector of activity secondary job 12 day recall" + la de lblocusec_2_year 1 "Public Sector, Central Government, Army" 2 "Private, NGO" 3 "State owned" 4 "Public or State-owned, but cannot distinguish" + label values ocusec_2_year lblocusec_2_year +* + + + +*<_industry_orig_2_year_> + gen industry_orig_2_year=. + label var industry_orig_2_year "Original survey industry code, secondary job 12 month recall" +* + + + +*<_industrycat_isic_2_year_> + gen industrycat_isic_2_year=. + label var industrycat_isic_2_year "ISIC code of secondary job 12 month recall" +* + + +*<_industrycat10_2_year_> + gen byte industrycat10_2_year=. + label var industrycat10_2_year "1 digit industry classification, secondary job 12 month recall" + label values industrycat10_2_year lblindustrycat10_year +* + + +*<_industrycat4_2_year_> + gen byte industrycat4_2_year=industrycat10_2_year + recode industrycat4_2_year (1=1)(2 3 4 5 =2)(6 7 8 9=3)(10=4) + label var industrycat4_2_year "1 digit industry classification (Broad Economic Activities), secondary job 12 month recall" + label values industrycat4_2_year lblindustrycat4_year +* + + +*<_occup_orig_2_year_> + gen occup_orig_2_year=. + label var occup_orig_2_year "Original occupation record secondary job 12 month recall" +* + + +*<_occup_isco_2_year_> + gen occup_isco_2_year=. + label var occup_isco_2_year "ISCO code of secondary job 12 month recall" +* + + +*<_occup_skill_2_year_> + gen occup_skill_2_year=. + label var occup_skill_2_year "Skill based on ISCO standard secondary job 12 month recall" +* + + +*<_occup_2_year_> + gen byte occup_2_year=. + label var occup_2_year "1 digit occupational classification, secondary job 12 month recall" + label values occup_2_year lbloccup_year +* + + +*<_wage_no_compen_2_year_> + gen double wage_no_compen_2_year=. + label var wage_no_compen_2_year "Last wage payment secondary job 12 month recall" +* + + +*<_unitwage_2_year_> + gen byte unitwage_2_year=. + label var unitwage_2_year "Last wages' time unit secondary job 12 month recall" + label values unitwage_2_year lblunitwage_year +* + + +*<_whours_2_year_> + gen whours_2_year=. + label var whours_2_year "Hours of work in last week secondary job 12 month recall" +* + + +*<_wmonths_2_year_> + gen wmonths_2_year=. + label var wmonths_2_year "Months of work in past 12 months secondary job 12 month recall" +* + + +*<_wage_total_2_year_> + gen wage_total_2_year=. + label var wage_total_2_year "Annualized total wage secondary job 12 month recall" +* + + +*<_firmsize_l_2_year_> + gen byte firmsize_l_2_year=. + label var firmsize_l_2_year "Firm size (lower bracket) secondary job 12 month recall" +* + + +*<_firmsize_u_2_year_> + gen byte firmsize_u_2_year=. + label var firmsize_u_2_year "Firm size (upper bracket) secondary job 12 month recall" +* + +} + + +*----------8.9: 12 month reference additional jobs------------------------------* + + +*<_t_hours_others_year_> + gen t_hours_others_year=. + label var t_hours_others_year "Annualized hours worked in all but primary and secondary jobs 12 month recall" +* + + +*<_t_wage_nocompen_others_year_> + gen t_wage_nocompen_others_year=. + label var t_wage_nocompen_others_year "Annualized wage in all but primary & secondary jobs excl. bonuses, etc. 12 month recall)" +* + + +*<_t_wage_others_year_> + gen t_wage_others_year=. + label var t_wage_others_year "Annualized wage in all but primary and secondary jobs 12 month recall" +* + + +*----------8.10: 12 month total summary------------------------------* + + +*<_t_hours_total_year_> + gen t_hours_total_year=. + label var t_hours_total_year "Annualized hours worked in all jobs 12 month month recall" +* + + +*<_t_wage_nocompen_total_year_> + gen t_wage_nocompen_total_year=. + label var t_wage_nocompen_total_year "Annualized wage in all jobs excl. bonuses, etc. 12 month recall" +* + + +*<_t_wage_total_year_> + gen t_wage_total_year=. + label var t_wage_total_year "Annualized total wage for all jobs 12 month recall" +* + + +*----------8.11: Overall across reference periods------------------------------* + + +*<_njobs_> + gen njobs=. + replace njobs=1 if lstatus==1&F1!=1 + replace njobs=2 if lstatus==1&F1==1 + replace njobs=. if lstatus!=1 + label var njobs "Total number of jobs" +* + + +*<_t_hours_annual_> + gen t_hours_annual=. + label var t_hours_annual "Total hours worked in all jobs in the previous 12 months" +* + + +*<_linc_nc_> + gen linc_nc=. + label var linc_nc "Total annual wage income in all jobs, excl. bonuses, etc." +* + + +*<_laborincome_> + gen laborincome=. + label var laborincome "Total annual individual labor income in all jobs, incl. bonuses, etc." +* + + +*----------8.13: Labour cleanup------------------------------* + +{ +*<_% Correction min age_> + +** Drop info for cases under the age for which questions to be asked (do not need a variable for this) + local lab_var "minlaborage lstatus nlfreason unempldur_l unempldur_u empstat ocusec industry_orig industrycat_isic industrycat10 industrycat4 occup_orig occup_isco occup_skill occup wage_no_compen unitwage whours wmonths wage_total contract healthins socialsec union firmsize_l firmsize_u empstat_2 ocusec_2 industry_orig_2 industrycat_isic_2 industrycat10_2 industrycat4_2 occup_orig_2 occup_isco_2 occup_skill_2 occup_2 wage_no_compen_2 unitwage_2 whours_2 wmonths_2 wage_total_2 firmsize_l_2 firmsize_u_2 t_hours_others t_wage_nocompen_others t_wage_others t_hours_total t_wage_nocompen_total t_wage_total lstatus_year nlfreason_year unempldur_l_year unempldur_u_year empstat_year ocusec_year industry_orig_year industrycat_isic_year industrycat10_year industrycat4_year occup_orig_year occup_isco_year occup_skill_year occup_year unitwage_year whours_year wmonths_year wage_total_year contract_year healthins_year socialsec_year union_year firmsize_l_year firmsize_u_year empstat_2_year ocusec_2_year industry_orig_2_year industrycat_isic_2_year industrycat10_2_year industrycat4_2_year occup_orig_2_year occup_isco_2_year occup_skill_2_year occup_2_year wage_no_compen_2_year unitwage_2_year whours_2_year wmonths_2_year wage_total_2_year firmsize_l_2_year firmsize_u_2_year t_hours_others_year t_wage_nocompen_others_year t_wage_others_year t_hours_total_year t_wage_nocompen_total_year t_wage_total_year njobs t_hours_annual linc_nc laborincome" + + foreach v of local lab_var { + cap confirm numeric variable `v' + if _rc == 0 { // is indeed numeric + replace `v'=. if ( age < minlaborage & !missing(age) ) + } + else { // is not + replace `v'= "" if ( age < minlaborage & !missing(age) ) + } + + } + +* +} + + +/*%%============================================================================================= + 9: Final steps +==============================================================================================%%*/ + +quietly{ + +*<_% KEEP VARIABLES - ALL_> + + keep countrycode survname survey icls_v isced_version isco_version isic_version year vermast veralt harmonization int_year int_month hhid pid weight weight_m weight_q weight_old_series weight_m_old_series weight_q_old_series psu strata wave panel visit_no urban subnatid1 subnatid2 subnatid3 subnatidsurvey subnatid1_prev subnatid2_prev subnatid3_prev gaul_adm1_code gaul_adm2_code gaul_adm3_code hsize age male relationharm relationcs marital eye_dsablty hear_dsablty walk_dsablty conc_dsord slfcre_dsablty comm_dsablty migrated_mod_age migrated_ref_time migrated_binary migrated_years migrated_from_urban migrated_from_cat migrated_from_code migrated_from_country migrated_reason ed_mod_age school literacy educy educat7 educat5 educat4 educat_orig educat_isced vocational vocational_type vocational_length_l vocational_length_u vocational_field_orig vocational_financed minlaborage lstatus potential_lf underemployment nlfreason unempldur_l unempldur_u empstat ocusec industry_orig industrycat_isic industrycat10 industrycat4 occup_orig occup_isco occup_skill occup wage_no_compen unitwage whours wmonths wage_total contract healthins socialsec union firmsize_l firmsize_u empstat_2 ocusec_2 industry_orig_2 industrycat_isic_2 industrycat10_2 industrycat4_2 occup_orig_2 occup_isco_2 occup_skill_2 occup_2 wage_no_compen_2 unitwage_2 whours_2 wmonths_2 wage_total_2 firmsize_l_2 firmsize_u_2 t_hours_others t_wage_nocompen_others t_wage_others t_hours_total t_wage_nocompen_total t_wage_total lstatus_year potential_lf_year underemployment_year nlfreason_year unempldur_l_year unempldur_u_year empstat_year ocusec_year industry_orig_year industrycat_isic_year industrycat10_year industrycat4_year occup_orig_year occup_isco_year occup_skill_year occup_year wage_no_compen_year unitwage_year whours_year wmonths_year wage_total_year contract_year healthins_year socialsec_year union_year firmsize_l_year firmsize_u_year empstat_2_year ocusec_2_year industry_orig_2_year industrycat_isic_2_year industrycat10_2_year industrycat4_2_year occup_orig_2_year occup_isco_2_year occup_skill_2_year occup_2_year wage_no_compen_2_year unitwage_2_year whours_2_year wmonths_2_year wage_total_2_year firmsize_l_2_year firmsize_u_2_year t_hours_others_year t_wage_nocompen_others_year t_wage_others_year t_hours_total_year t_wage_nocompen_total_year t_wage_total_year njobs t_hours_annual linc_nc laborincome + +* + +*<_% ORDER VARIABLES_> + + order countrycode survname survey icls_v isced_version isco_version isic_version year vermast veralt harmonization int_year int_month hhid pid weight weight_m weight_q weight_old_series weight_m_old_series weight_q_old_series psu strata wave panel visit_no urban subnatid1 subnatid2 subnatid3 subnatidsurvey subnatid1_prev subnatid2_prev subnatid3_prev gaul_adm1_code gaul_adm2_code gaul_adm3_code hsize age male relationharm relationcs marital eye_dsablty hear_dsablty walk_dsablty conc_dsord slfcre_dsablty comm_dsablty migrated_mod_age migrated_ref_time migrated_binary migrated_years migrated_from_urban migrated_from_cat migrated_from_code migrated_from_country migrated_reason ed_mod_age school literacy educy educat7 educat5 educat4 educat_orig educat_isced vocational vocational_type vocational_length_l vocational_length_u vocational_field_orig vocational_financed minlaborage lstatus potential_lf underemployment nlfreason unempldur_l unempldur_u empstat ocusec industry_orig industrycat_isic industrycat10 industrycat4 occup_orig occup_isco occup_skill occup wage_no_compen unitwage whours wmonths wage_total contract healthins socialsec union firmsize_l firmsize_u empstat_2 ocusec_2 industry_orig_2 industrycat_isic_2 industrycat10_2 industrycat4_2 occup_orig_2 occup_isco_2 occup_skill_2 occup_2 wage_no_compen_2 unitwage_2 whours_2 wmonths_2 wage_total_2 firmsize_l_2 firmsize_u_2 t_hours_others t_wage_nocompen_others t_wage_others t_hours_total t_wage_nocompen_total t_wage_total lstatus_year potential_lf_year underemployment_year nlfreason_year unempldur_l_year unempldur_u_year empstat_year ocusec_year industry_orig_year industrycat_isic_year industrycat10_year industrycat4_year occup_orig_year occup_isco_year occup_skill_year occup_year wage_no_compen_year unitwage_year whours_year wmonths_year wage_total_year contract_year healthins_year socialsec_year union_year firmsize_l_year firmsize_u_year empstat_2_year ocusec_2_year industry_orig_2_year industrycat_isic_2_year industrycat10_2_year industrycat4_2_year occup_orig_2_year occup_isco_2_year occup_skill_2_year occup_2_year wage_no_compen_2_year unitwage_2_year whours_2_year wmonths_2_year wage_total_2_year firmsize_l_2_year firmsize_u_2_year t_hours_others_year t_wage_nocompen_others_year t_wage_others_year t_hours_total_year t_wage_nocompen_total_year t_wage_total_year njobs t_hours_annual linc_nc laborincome + +* + +*<_% DROP UNUSED LABELS_> + + * Store all labels in data + label dir + local all_lab `r(names)' + + * Store all variables with a label, extract value label names + local used_lab = "" + ds, has(vallabel) + + local labelled_vars `r(varlist)' + + foreach varName of local labelled_vars { + local y : value label `varName' + local used_lab `"`used_lab' `y'"' + } + + * Compare lists, `notused' is list of labels in directory but not used in final variables + local notused : list all_lab - used_lab // local `notused' defines value labs not in remaining vars + local notused_len : list sizeof notused // store size of local + + * drop labels if the length of the notused vector is 1 or greater, otherwise nothing to drop + if `notused_len' >= 1 { + label drop `notused' + } + else { + di "There are no unused labels to drop. No value labels dropped." + } + + +* + +} + +*<_% DELETE MISSING VARIABLES_> + +quietly: describe, varlist +local kept_vars `r(varlist)' + +foreach var of local kept_vars { + + capture assert missing(`var') + if !_rc drop `var' +} + +* + + +*<_% COMPRESS_> + +compress + +* + + +*<_% SAVE_> + +save "`path_output'/`level_2_harm'_ALL.dta", replace + +* diff --git a/GLD/ARM/ARM_2020_LFS/ARM_2020_LFS_V01_M_V03_A_GLD/Programs/ARM_2020_LFS_V01_M_V03_A_GLD_ALL.do b/GLD/ARM/ARM_2020_LFS/ARM_2020_LFS_V01_M_V03_A_GLD/Programs/ARM_2020_LFS_V01_M_V03_A_GLD_ALL.do new file mode 100644 index 000000000..9c1b79975 --- /dev/null +++ b/GLD/ARM/ARM_2020_LFS/ARM_2020_LFS_V01_M_V03_A_GLD/Programs/ARM_2020_LFS_V01_M_V03_A_GLD_ALL.do @@ -0,0 +1,1785 @@ + +/*%%============================================================================================= + 0: GLD Harmonization Preamble +================================================================================================*/ + +/* ----------------------------------------------------------------------- +<_Program name_> ARM_2020_LFS_V01_M_V03_A_GLD_ALL.do +<_Application_> Stata SE 18 <_Application_> +<_Author(s)_> Wolrd Bank Job's Group +<_Date created_> 2024-1-10 +------------------------------------------------------------------------- +<_Country_> Armenia (ARM) +<_Survey Title_> National Labour Force Survey +<_Survey Year_> 2020 +<_Study ID_> ARM_2020_LFS_v01_M +<_Data collection from (M/Y)_> [01/2020] +<_Data collection to (M/Y)_> [12/2020] +<_Source of dataset_> The Armenian 2020 to 2021 data is downloaded from + the website of Statistical Committee of the + Republic of Armenia:https://armstat.am/en/?nid=212 + The data is publicly available. +<_Sample size (HH)_> 7,781 +<_Sample size (IND)_> 27,986 +<_Sampling method_> A stratified two-stage probability sample design + with 14 domains as the primary strata and 18,000 + households as the SSU. +<_Geographic coverage_> All 11 regions/marzes. +<_Currency_> Armenian Dram +----------------------------------------------------------------------- +<_ICLS Version_> ICLS 19 +<_ISCED Version_> ISCED-2011 +<_ISCO Version_> ISCO 08 +<_OCCUP National_> NSCO +<_ISIC Version_> ISIC Rev.4 +<_INDUS National_> ISIC Rev.4 +----------------------------------------------------------------------- + +<_Version Control_> + +* Date: 2024-09-24 - Update vars educy, educat7, educat_isced +* Date: 2024-10-10 - Include weight by quarter, old weight variable, correct contract variable, drop migration + + + +-------------------------------------------------------------------------*/ + + +/*%%============================================================================================= + 1: Setting up of program environment, dataset +================================================================================================*/ + +*----------1.1: Initial commands------------------------------* + +clear +set more off +set mem 800m + +*----------1.2: Set directories------------------------------* + +* Define path sections +local server "Y:/GLD" +local country "ARM" +local year "2020" +local survey "LFS" +local vermast "V01" +local veralt "V03" + +* From the definitions, set path chunks +local level_1 "`country'_`year'_`survey'" +local level_2_mast "`level_1'_`vermast'_M" +local level_2_harm "`level_1'_`vermast'_M_`veralt'_A_GLD" + +* From chunks, define path_in, path_output folder +local path_in_stata "`server'/`country'/`level_1'/`level_2_mast'/Data/Stata" +local path_in_other "`server'/`country'/`level_1'/`level_2_mast'/Data/Original" +local path_output "`server'/`country'/`level_1'/`level_2_harm'/Data/Harmonized" + +* Define Output file name +local out_file "`level_2_harm'_ALL.dta" + + +*----------1.3: Database assembly------------------------------* + +* All steps necessary to merge datasets (if several) to have all elements needed to produce +* harmonized output in a single file + +use "`path_in_stata'/ARM_LFS_2020_raw.dta", clear + +/*%%============================================================================================= + 2: Survey & ID +================================================================================================*/ + +{ + +*<_countrycode_> + gen str4 countrycode="`country'" + label var countrycode "Country code" +* + + +*<_survname_> + gen survname="LFS" + label var survname "Survey acronym" +* + + +*<_survey_> + gen survey="LFS" + label var survey "Survey type" +* + + +*<_icls_v_> + gen icls_v="ICLS-19" + label var icls_v "ICLS version underlying questionnaire questions" +* + + +*<_isced_version_> + gen isced_version="isced_2011" + label var isced_version "Version of ISCED used for educat_isced" +* + + +*<_isco_version_> + gen isco_version="" + label var isco_version "Version of ISCO used" +* + + +*<_isic_version_> + gen isic_version="" + label var isic_version "Version of ISIC used" +* + + +*<_year_> + gen int year=`year' + label var year "Year of survey" +* + + +*<_vermast_> + gen str3 vermast="`vermast'" + label var vermast "Version of master data" +* + + +*<_veralt_> + gen str3 veralt="`veralt'" + label var veralt "Version of the alt/harmonized data" +* + + +*<_harmonization_> + gen harmonization="GLD" + label var harmonization "Type of harmonization" +* + + +*<_int_year_> + gen int_year=`year' + label var int_year "Year of the interview" +* + + +*<_int_month_> + gen int_month=A6_Month + label de lblint_month 1 "January" 2 "February" 3 "March" 4 "April" 5 "May" 6 "June" 7 "July" 8 "August" 9 "September" 10 "October" 11 "November" 12 "December" + label value int_month lblint_month + label var int_month "Month of the interview" +* + + +*<_hhid_> + tostring A1, gen(hid) format(%03.0f) + tostring A6_Month, gen(month) format(%03.0f) + egen hhid=concat(month hid) + label var hhid "Household id" +* + + +*<_pid_> + sort hhid B4 + bys hhid: gen memberid=_n + tostring memberid, gen(id_str) format(%02.0f) + egen pid=concat(hhid id_str), punct("-") + label var pid "Individual ID" +* + + +*<_weight_> + gen weight = WeightsCalib_year + label var weight "Household sampling weight" +* + + +*<_weight_m_> + gen weight_m = . + label var weight_m "Survey sampling weight to obtain national estimates for each month" +* + + +*<_weight_q_> + egen weight_q = rowtotal(WeightsCalib_1 WeightsCalib_2 WeightsCalib_3 WeightsCalib_4) + label var weight_q "Survey sampling weight to obtain national estimates for each quarter" +* + + +*<_psu_> + gen psu=. + label var psu "Primary sampling units" +* + + +*<_ssu_> + gen ssu=hhid + label var ssu "Secondary sampling units" +* + + +*<_strata_> + decode A3, gen(marzname) + decode A5, gen(urbanstat) + gen strata=marzname+" "+urbanstat + label var strata "Strata" +* + + +*<_wave_> + gen wave=. + replace wave=1 if inrange(int_month,1,3) + replace wave=2 if inrange(int_month,4,6) + replace wave=3 if inrange(int_month,7,9) + replace wave=4 if inrange(int_month,10,12) + label var wave "Survey wave" +* + + +*<_panel_> + gen panel="" + label var panel "Panel individual belongs to" +* + + +*<_visit_no_> + gen visit_no=. + label var visit_no "Visit number in panel" +* +} + +/*%%============================================================================================= + 3: Geography +================================================================================================*/ + +{ + +*<_urban_> + gen urban=A5 + recode urban (2=0) + la de lblurban 1 "Urban" 0 "Rural" + label values urban lblurban + label var urban "Location is urban" +* + + +*<_subnatid1_> + gen subnatid1=A3 + tostring subnatid1, replace + replace subnatid1=subnatid1+" - "+marzname + label var subnatid1 "Subnational ID at First Administrative Level" +* + + +*<_subnatid2_> + gen subnatid2=. + label var subnatid2 "Subnational ID at Second Administrative Level" +* + + +*<_subnatid3_> + gen subnatid3=. + label var subnatid3 "Subnational ID at Third Administrative Level" +* + + +*<_subnatidsurvey_> + gen subnatidsurvey=subnatid1+" "+urbanstat + label var subnatidsurvey "Administrative level at which survey is representative" +* + + +*<_subnatid1_prev_> + +/* <_subnatid1_prev_note_> +subnatid1_prev is coded as missing unless the classification used for subnatid1 has changed since the previous survey. + */ + + gen subnatid1_prev=. + label var subnatid1_prev "Classification used for subnatid1 from previous survey" +* + + +*<_subnatid2_prev_> + gen subnatid2_prev=. + label var subnatid2_prev "Classification used for subnatid2 from previous survey" +* + + +*<_subnatid3_prev_> + gen subnatid3_prev=. + label var subnatid3_prev "Classification used for subnatid3 from previous survey" +* + + +*<_gaul_adm1_code_> + gen gaul_adm1_code=. + label var gaul_adm1_code "Global Administrative Unit Layers (GAUL) Admin 1 code" +* + + +*<_gaul_adm2_code_> + gen gaul_adm2_code=. + label var gaul_adm2_code "Global Administrative Unit Layers (GAUL) Admin 2 code" +* + + +*<_gaul_adm3_code_> + gen gaul_adm3_code=. + label var gaul_adm3_code "Global Administrative Unit Layers (GAUL) Admin 3 code" +* + +} + +/*%%============================================================================================= + 4: Demography +================================================================================================*/ + +{ + +*<_hsize_> + bys hhid: egen hsize=max(memberid) + label var hsize "Household size" +* + + +*<_age_> + gen age=Age + replace age=. if Age<0 + replace age=98 if age>98 & age!=. + label var age "Individual age" +* + + +*<_male_> + gen male=B3 + recode male 2=0 + label var male "Sex - Ind is male" + la de lblmale 1 "Male" 0 "Female" + label values male lblmale +* + + +*<_relationharm_> + +/*<_relationharm_note_> + +6 households (24 observations) in the raw data set do not have household heads. +Their household IDs are: + +003430 004285 005503 +006281 006305 012044 + +During the harmonization, we did not assign household heads to these households. +But users can assign household heads based on their relationship to the head and +other characteristics such as gender and age. + +*<_relationharm_note_>*/ + + gen byte relationharm=B4 + recode relationharm (6 9=3) (7 8=4) (10=5) (11=6) + label var relationharm "Relationship to the head of household - Harmonized" + la de lblrelationharm 1 "Head of household" 2 "Spouse" 3 "Children" 4 "Parents" 5 "Other relatives" 6 "Other and non-relatives" + label values relationharm lblrelationharm +*<_relationharm_> + + +*<_relationcs_> + gen relationcs=B4 + label var relationcs "Relationship to the head of household - Country original" +* + + +*<_marital_> + gen marital=B11 + recode marital (1=2) (2=1) (3=5) + label var marital "Marital status" + la de lblmarital 1 "Married" 2 "Never Married" 3 "Living together" 4 "Divorced/Separated" 5 "Widowed" + label values marital lblmarital +* + + +*<_eye_dsablty_> + gen eye_dsablty=. + la de lbleye_dsablty 1 "No" 2 "Yes-some" 3 "Yes-a lot" 4 "Cannot at all" + label values eye_dsablty lbleye_dsablty + label var eye_dsablty "Disability related to eyesight" +* + + +*<_hear_dsablty_> + gen hear_dsablty=. + la de lblhear_dsablty 1 "No" 2 "Yes-some" 3 "Yes-a lot" 4 "Cannot at all" + label values hear_dsablty lblhear_dsablty + label var hear_dsablty "Disability related to hearing" +* + + +*<_walk_dsablty_> + gen walk_dsablty=. + la de lblwalk_dsablty 1 "No" 2 "Yes-some" 3 "Yes-a lot" 4 "Cannot at all" + label values walk_dsablty lblwalk_dsablty + label var walk_dsablty "Disability related to walking or climbing stairs" +* + + +*<_conc_dsord_> + gen conc_dsord=. + la de lblconc_dsord 1 "No" 2 "Yes-some" 3 "Yes-a lot" 4 "Cannot at all" + label values conc_dsord lblconc_dsord + label var conc_dsord "Disability related to concentration or remembering" +* + + +*<_slfcre_dsablty_> + gen slfcre_dsablty=. + la de lblslfcre_dsablty 1 "No" 2 "Yes-some" 3 "Yes-a lot" 4 "Cannot at all" + label values slfcre_dsablty lblslfcre_dsablty + label var eye_dsablty "Disability related to selfcare" +* + + +*<_comm_dsablty_> + gen comm_dsablty=. + la de lblcomm_dsablty 1 "No" 2 "Yes-some" 3 "Yes-a lot" 4 "Cannot at all" + label values comm_dsablty lblcomm_dsablty + label var eye_dsablty "Disability related to communicating" +* + +} + + +/*%%============================================================================================= + 5: Migration +==============================================================================================%%*/ + + +{ + +*<_migrated_mod_age_> + gen migrated_mod_age = . + label var migrated_mod_age "Migration module application age" +* + + +*<_migrated_ref_time_> + gen migrated_ref_time = . + label var migrated_ref_time "Reference time applied to migration questions (in years)" +* + + +*<_migrated_binary_> + gen migrated_binary = . + label de lblmigrated_binary 0 "No" 1 "Yes" + label values migrated_binary lblmigrated_binary + label var migrated_binary "Individual has migrated" +* + + +*<_migrated_years_> + gen migrated_years = . + label var migrated_years "Years since latest migration" +* + + +*<_migrated_from_urban_> + gen migrated_from_urban = . + label de lblmigrated_from_urban 0 "Rural" 1 "Urban" + label values migrated_from_urban lblmigrated_from_urban + label var migrated_from_urban "Migrated from area" +* + + +*<_migrated_from_cat_> + gen migrated_from_cat = . + label de lblmigrated_from_cat 1 "From same admin3 area" 2 "From same admin2 area" 3 "From same admin1 area" 4 "From other admin1 area" 5 "From other country" + label values migrated_from_cat lblmigrated_from_cat + label var migrated_from_cat "Category of migration area" +* + + +*<_migrated_from_code_> + gen migrated_from_code = . + *label de lblmigrated_from_code + *label values migrated_from_code lblmigrated_from_code + label var migrated_from_code "Code of migration area as subnatid level of migrated_from_cat" +* + + +*<_migrated_from_country_> + gen migrated_from_country = . + label var migrated_from_country "Code of migration country (ISO 3 Letter Code)" +* + + +*<_migrated_reason_> + gen migrated_reason = . + label de lblmigrated_reason 1 "Family reasons" 2 "Educational reasons" 3 "Employment" 4 "Forced (political reasons, natural disaster, …)" 5 "Other reasons" + label values migrated_reason lblmigrated_reason + label var migrated_reason "Reason for migrating" +* + + +} + + +/*%%============================================================================================= + 6: Education +================================================================================================*/ + + +{ +*<_ed_mod_age_> + gen byte ed_mod_age=6 + label var ed_mod_age "Education module application age" +* + + +*<_school_> + gen school=B9 + recode school (2=0) (3/5=.) + replace school=. if age + + +*<_literacy_> + gen byte literacy=. + replace literacy=0 if B7==1 + replace literacy=1 if inrange(B7,2,11) + replace literacy=. if age + + +*<_educy_> + gen byte educy=. + replace educy = 0 if B7 == 1 | B7 == 2 + replace educy = 4 if B7 == 3 + replace educy = 9 if B7 == 4 + replace educy = 12 if B7 == 5 + replace educy = 11 if B7 == 6 + replace educy = 15 if B7 == 7 + replace educy = 16 if B7 == 8 + replace educy = 18 if B7 == 9 | B7 == 10 + replace educy = 20 if B7 == 11 + replace educy=. if ageage & !mi(educy) & !mi(age) + label var educy "Years of education" +* + + +*<_educat7_> + gen byte educat7= B7 + recode educat7 (6=5) (7=6) (8/11=7) + replace educat7=. if age + + +*<_educat5_> + gen byte educat5=educat7 + recode educat5 (4=3) (5=4) (6 7=5) + replace educat5=. if age + + +*<_educat4_> + gen byte educat4=educat5 + replace educat4=. if age + + +*<_educat_orig_> + gen educat_orig=B7 + label var educat_orig "Original survey education code" +* + + +*<_educat_isced_> + gen educat_isced=. + label var educat_isced "ISCED standardised level of education" +* + + +*<_educat_isced_v_> + gen educat_isced_v="ISCED-2011" + label var educat_isced_v "Version of the ISCED used" +* + +*----------6.1: Education cleanup------------------------------* + +*<_% Correction min age_> + +** Drop info for cases under the age for which questions to be asked (do not need a variable for this) +local ed_var school literacy educy educat7 educat5 educat4 educat_isced +foreach v of local ed_var { + replace `v'=. if ( age < ed_mod_age & !missing(age) ) +} +replace educat_isced_v="." if ( age < ed_mod_age & !missing(age) ) +* + +} + +/*%%============================================================================================= + 7: Training +================================================================================================*/ + +{ + +*<_vocational_> + gen vocational=. + la de vocationallbl 1 "Yes" 0 "No" + la values vocational vocationallbl + label var vocational "Ever received vocational training" +* + + +*<_vocational_type_> + gen vocational_type=. + label de lblvocational_type 1 "Inside Enterprise" 2 "External" + label values vocational_type lblvocational_type + label var vocational_type "Type of vocational training" +* + + +*<_vocational_length_l_> + gen vocational_length_l=. + replace vocational_length_l=. if vocational!=1 + label var vocational_length_l "Length of training in months, lower limit" +* + + +*<_vocational_length_u_> + gen vocational_length_u=. + replace vocational_length_u=. if vocational!=1 + label var vocational_length_u "Length of training in months, upper limit" +* + + +*<_vocational_field_orig_> + gen vocational_field_orig=. + replace vocational_field_orig=. if vocational!=1 + label var vocational_field_orig "Original field of training information" +* + + +*<_vocational_financed_> + gen vocational_financed=. + label de lblvocational_financed 1 "Employer" 2 "Government" 3 "Mixed Employer/Government" 4 "Own funds" 5 "Other" + label var vocational_financed "How training was financed" +* + +} + +/*%%============================================================================================= + 8: Labour +================================================================================================*/ + +*<_minlaborage_> + +/*<_minlaborage_note_> + +The age range for the labor section is 15-75. + +*<_minlaborage_note_>*/ + + gen byte minlaborage=15 + label var minlaborage "Labor module application age" +* + + +*----------8.1: 7 day reference overall------------------------------* + +{ +*<_lstatus_> + +/*<_lstatus_note> + +The economically inavtive population also needs to be within the age range of +15 and 75. + +*<_lstatus_note>*/ + + gen byte lstatus=. + replace lstatus=1 if D1==1|inrange(D3,1,5)|D4==1|D5==1 + replace lstatus=2 if lstatus==.&inrange(J9,1,3) + replace lstatus=3 if !mi(J1_6group)&lstatus==. + replace lstatus=. if !inrange(age,15,75) + label var lstatus "Labor status" + la de lbllstatus 1 "Employed" 2 "Unemployed" 3 "Non-LF" + label values lstatus lbllstatus +* + + +*<_potential_lf_> + +/*<_potential_lf_note_> +Note: var "potential_lf" only takes value if the respondent is not in labor force. (lstatus==3) + +"potential_lf"=1 if the person is +1)available but not searching or (J16==1)&J9==4 +2)searching but not immediately available to work or inrange(J9,1,3)&J16==2 + +*/ + + gen potential_lf=. + replace potential_lf=1 if [(J16==1)&J9==4] | [inrange(J9,1,3)&J16==2] + replace potential_lf=0 if [(J16==1)&inrange(J9,1,3)] | [inrange(J9,1,3)&J16==1] + replace potential_lf=. if age75&!mi(age)] + replace potential_lf=. if lstatus!=3 + label var potential_lf "Potential labour force status" + la de lblpotential_lf 0 "No" 1 "Yes" + label values potential_lf lblpotential_lf +* + + +*<_underemployment_> + gen byte underemployment=G4 + replace underemployment=1 if inrange(G4,1,3) + replace underemployment=0 if G4==4 + replace underemployment=. if age75&!mi(age)] + replace underemployment=. if lstatus!=1 + label var underemployment "Underemployment status" + la de lblunderemployment 0 "No" 1 "Yes" + label values underemployment lblunderemployment +* + + +*<_nlfreason_> + gen byte nlfreason=J1_6group + recode nlfreason (4/6=5) + replace nlfreason=. if age75&!mi(age)] + replace nlfreason=. if lstatus!=3 + label var nlfreason "Reason not in the labor force" + la de lblnlfreason 1 "Student" 2 "Housekeeper" 3 "Retired" 4 "Disabled" 5 "Other" + label values nlfreason lblnlfreason +* + + +*<_unempldur_l_> + gen byte unempldur_l=J4 + recode unempldur_l (1=0) (2=3) (3=6) (4=9) (5=12) (6=24) (7=36) + replace unempldur_l=. if age75&!mi(age)] + replace unempldur_l=. if lstatus!=2 + label var unempldur_l "Unemployment duration (months) lower bracket" +* + + +*<_unempldur_u_> + gen byte unempldur_u=J4 + recode unempldur_u (1=3) (2=6) (3=9) (4=12) (5=24) (6=36) (7 10=.) + replace unempldur_u=. if age75&!mi(age)] + replace unempldur_u=. if lstatus!=2 + label var unempldur_u "Unemployment duration (months) upper bracket" +* +} + + +*----------8.2: 7 day reference main job------------------------------* + + +{ +*<_empstat_> + gen byte empstat=E7 + recode empstat (2 6=1) (5=2) + replace empstat=. if lstatus!=1|age + + +*<_ocusec_> + gen byte ocusec=E10 + recode ocusec (3 4=2) + replace ocusec=. if lstatus!=1|age + + +*<_industry_orig_> + gen industry_orig=E4_21group + replace industry_orig=. if lstatus!=1 + label var industry_orig "Original survey industry code, main job 7 day recall" +* + + +*<_industrycat_isic_> + gen industrycat_isic="" +quietly +{ + replace industrycat_isic="A" if E4_21group==1 + replace industrycat_isic="B" if E4_21group==2 + replace industrycat_isic="C" if E4_21group==3 + replace industrycat_isic="D" if E4_21group==4 + replace industrycat_isic="E" if E4_21group==5 + replace industrycat_isic="F" if E4_21group==6 + replace industrycat_isic="G" if E4_21group==7 + replace industrycat_isic="H" if E4_21group==8 + replace industrycat_isic="I" if E4_21group==9 + replace industrycat_isic="J" if E4_21group==10 + replace industrycat_isic="K" if E4_21group==11 + replace industrycat_isic="L" if E4_21group==12 + replace industrycat_isic="M" if E4_21group==13 + replace industrycat_isic="N" if E4_21group==14 + replace industrycat_isic="O" if E4_21group==15 + replace industrycat_isic="P" if E4_21group==16 + replace industrycat_isic="Q" if E4_21group==17 + replace industrycat_isic="R" if E4_21group==18 + replace industrycat_isic="S" if E4_21group==19 + replace industrycat_isic="T" if E4_21group==20 + replace industrycat_isic="U" if E4_21group==21 +} + + replace industrycat_isic="" if industrycat_isic=="."|lstatus!=1 + label var industrycat_isic "ISIC code of primary job 7 day recall" +* + + +*<_industrycat10_> + gen industrycat10=E4_21group + recode industrycat10 (5=4) (6=5) (7 9=6) (8 10=7) (11/14=8) (15=9) (16/21=10) + replace industrycat10=. if lstatus!=1 + label var industrycat10 "1 digit industry classification, primary job 7 day recall" + la de lblindustrycat10 1 "Agriculture" 2 "Mining" 3 "Manufacturing" 4 "Public utilities" 5 "Construction" 6 "Commerce" 7 "Transport and Comnunications" 8 "Financial and Business Services" 9 "Public Administration" 10 "Other Services, Unspecified" + label values industrycat10 lblindustrycat10 +* + + +*<_industrycat4_> + gen byte industrycat4=industrycat10 + recode industrycat4 (3/5=2)(6/9=3)(10=4) + label var industrycat4 "1 digit industry classification (Broad Economic Activities), primary job 7 day recall" + la de lblindustrycat4 1 "Agriculture" 2 "Industry" 3 "Services" 4 "Other" + label values industrycat4 lblindustrycat4 +* + + +*<_occup_orig_> + gen occup_orig=E2_9group + replace occup_orig=. if lstatus!=1|[age>75&!mi(age)] + label var occup_orig "Original occupation record primary job 7 day recall" +* + + +*<_occup_isco_> + gen occup_isco="" + replace occup_isco="" if lstatus!=1 | occup_isco=="." + label var occup_isco "ISCO code of primary job 7 day recall" +* + + +*<_occup_skill_> + gen occup_skill=E2_9group + replace occup_skill=1 if E2_9group==9 + replace occup_skill=2 if inrange(E2_9group, 4, 8) + replace occup_skill=3 if inrange(E2_9group, 1, 3) + replace occup_skill=. if lstatus!=1 + la de lblskill 1 "Low skill" 2 "Medium skill" 3 "High skill" + label values occup_skill lblskill + label var occup_skill "Skill based on ISCO standard primary job 7 day recall" +* + + +*<_occup_> + gen occup=E2_9group + replace occup=. if lstatus!=1|[age>75&!mi(age)] + label var occup "1 digit occupational classification, primary job 7 day recall" + la de lbloccup 1 "Managers" 2 "Professionals" 3 "Technicians" 4 "Clerks" 5 "Service and market sales workers" 6 "Skilled agricultural" 7 "Craft workers" 8 "Machine operators" 9 "Elementary occupations" 10 "Armed forces" 99 "Others" + label values occup lbloccup +* + + +*<_wage_no_compen_> + +/*<_wage_no_compen_note_> + +The wage questions in the questionnare are organized into to parts: the first part +asks for the specific number of income if the given respondent could recall and was +willing to answer; the second part provides different categories of income range +if the given respondent could not recall or was not willing to answer the first part. + +The general logic here is to impute wage values for people who only answered an income +range. We used industry, occupation, income categories and gender to estimate their +specific income values. + +18.04% of total non-missing wage values were imputed using this method. +*<_wage_no_compen_note_>*/ + + * Overall --> wage info (here the variable, for us it should be wage_no_compen) + * to missing if value is 0. + gen wage14=E14_1+E14_2 + replace wage14=. if wage14==0 + + * First replace outliers by + winsor2 wage14, suffix(_w) cuts(1 99) + + * Create salary categories based on winsor values + gen salary_cat=. + replace salary_cat=1 if inrange(wage14_w, 1, 55000) + replace salary_cat=2 if wage14_w==55000 + replace salary_cat=3 if inrange(wage14_w, 55001, 110000) + replace salary_cat=4 if inrange(wage14_w, 110001, 220000) + replace salary_cat=5 if inrange(wage14_w, 220001, 440000) + replace salary_cat=6 if inrange(wage14_w, 440001, 600000) + replace salary_cat=7 if inrange(wage14_w, 600001, 700000) + + * Preserve to collapse, so we can merge the info in + preserve + + * Collpase by industry, sex, and salary categories + collapse (mean)wage14_w[iw=weight], by(industrycat10 occup male urban salary_cat) + + * Rename variable, otherwise when merging in, master version of an equally name one will be kept + rename wage14_w wage_group_estimate + + * Rename salary_cat to D15 since this is what we want the info to latch on to + rename salary_cat E15 + tempfile salary_helper + save "`salary_helper'" + + * Restore, merge in + restore + merge m:1 industrycat10 occup male urban E15 using "`salary_helper'", keep(matched master) nogen + + * Create wage variable + gen wage_no_compen=. + + * Fill it first with values that are accurate + replace wage_no_compen=wage14 if !mi(wage14)&mi(E15) + + * Now add the categorised means + replace wage_no_compen=wage_group_estimate if inrange(E15,1,8)&!mi(wage_group_estimate) + + * Keep only for employed employees, label + replace wage_no_compen=. if lstatus!=1|empstat==2 + label var wage_no_compen "Last wage payment primary job 7 day recall" +* + + +*<_unitwage_> + gen byte unitwage=E16 + recode unitwage (4=5) (5=7) (6=8) (7=10) + replace unitwage=. if lstatus!=1 | empstat==2 + label var unitwage "Last wages' time unit primary job 7 day recall" + la de lblunitwage 1 "Daily" 2 "Weekly" 3 "Every two weeks" 4 "Bimonthly" 5 "Monthly" 6 "Trimester" 7 "Biannual" 8 "Annually" 9 "Hourly" 10 "Other" + label values unitwage lblunitwage +* + + +*<_whours_> + gen whours=G2_1 + replace whours=. if lstatus!=1|G2_1==0 + label var whours "Hours of work in last week primary job 7 day recall" +* + + +*<_wmonths_> + gen wmonths=. + label var wmonths "Months of work in past 12 months primary job 7 day recall" +* + + +*<_wage_total_> + gen wage_total=. + label var wage_total "Annualized total wage primary job 7 day recall" +* + + +*<_contract_> + +/*<_contract_note_> + +There is no separate contract question in the questionnaire. +This contract variable was coded based on employment status question which asks +wether an employed respondent had a contract or not. + +*<_contract_note_>*/ + + gen byte contract = . + replace contract = (E7 == 1) + replace contract=. if lstatus!=1 + label var contract "Employment has contract primary job 7 day recall" + la de lblcontract 0 "Without contract" 1 "With contract" + label values contract lblcontract +* + + +*<_healthins_> + gen byte healthins=. + replace healthins=1 if E8_f==1 + replace healthins=0 if E8_f==2 + replace healthins=. if lstatus!=1 + label var healthins "Employment has health insurance primary job 7 day recall" + la de lblhealthins 0 "Without health insurance" 1 "With health insurance" + label values healthins lblhealthins +* + + +*<_socialsec_> + gen byte socialsec=. + replace socialsec=. if lstatus!=1 + label var socialsec "Employment has social security insurance primary job 7 day recall" + la de lblsocialsec 1 "With social security" 0 "Without social secturity" + label values socialsec lblsocialsec +* + + +*<_union_> + gen byte union=. + replace union=1 if E27==1 + replace union=0 if E27==2 + replace union=. if lstatus!=1 + label var union "Union membership at primary job 7 day recall" + la de lblunion 0 "Not union member" 1 "Union member" + label values union lblunion +* + + +*<_firmsize_l_> + gen byte firmsize_l=E13 + recode firmsize_l (1=1) (2=5) (3=10) (4=20) (5=50) (6=100) (7=.) + replace firmsize_l=. if lstatus!=1 + label var firmsize_l "Firm size (lower bracket) primary job 7 day recall" +* + + +*<_firmsize_u_> + gen byte firmsize_u=E13 + recode firmsize_u (1=5) (2=9) (3=19) (4=49) (5=99) (6=.) + replace firmsize_u=. if lstatus!=1 + label var firmsize_u "Firm size (upper bracket) primary job 7 day recall" +* + +} + + +*----------8.3: 7 day reference secondary job------------------------------* +* Since labels are the same as main job, values are labelled using main job labels + +{ +*<_empstat_2_> + gen byte empstat_2=F4 + recode empstat_2 (2=1) (5=2) + replace empstat_2=. if lstatus!=1|F1!=1 + label var empstat_2 "Employment status during past week secondary job 7 day recall" + la de lblempstat_2 1 "Paid employee" 2 "Non-paid employee" 3 "Employer" 4 "Self-employed" 5 "Other, workers not classifiable by status" + label values empstat_2 lblempstat +* + + +*<_ocusec_2_> + gen byte ocusec_2=F6 + recode ocusec_2 (3 4=2) + replace ocusec_2=. if lstatus!=1|F1!=1 + label var ocusec_2 "Sector of activity secondary job 7 day recall" + la de lblocusec_2 1 "Public Sector, Central Government, Army" 2 "Private, NGO" 3 "State owned" 4 "Public or State-owned, but cannot distinguish" + label values ocusec_2 lblocusec_2 +* + + +*<_industry_orig_2_> + gen industry_orig_2=F3_21group + replace industry_orig_2=. if lstatus!=1|F1!=1 + label var industry_orig_2 "Original survey industry code, secondary job 7 day recall" +* + + +*<_industrycat_isic_2_> + gen industrycat_isic_2="" +quietly +{ + replace industrycat_isic_2="A" if F3_21group==1 + replace industrycat_isic_2="B" if F3_21group==2 + replace industrycat_isic_2="C" if F3_21group==3 + replace industrycat_isic_2="D" if F3_21group==4 + replace industrycat_isic_2="E" if F3_21group==5 + replace industrycat_isic_2="F" if F3_21group==6 + replace industrycat_isic_2="G" if F3_21group==7 + replace industrycat_isic_2="H" if F3_21group==8 + replace industrycat_isic_2="I" if F3_21group==9 + replace industrycat_isic_2="J" if F3_21group==10 + replace industrycat_isic_2="K" if F3_21group==11 + replace industrycat_isic_2="L" if F3_21group==12 + replace industrycat_isic_2="M" if F3_21group==13 + replace industrycat_isic_2="N" if F3_21group==14 + replace industrycat_isic_2="O" if F3_21group==15 + replace industrycat_isic_2="P" if F3_21group==16 + replace industrycat_isic_2="Q" if F3_21group==17 + replace industrycat_isic_2="R" if F3_21group==18 + replace industrycat_isic_2="S" if F3_21group==19 + replace industrycat_isic_2="T" if F3_21group==20 + replace industrycat_isic_2="U" if F3_21group==21 +} + + replace industrycat_isic_2="" if industrycat_isic_2=="."|F1!=1 + label var industrycat_isic_2 "ISIC code of secondary job 7 day recall" +* + + +*<_industrycat10_2_> + gen industrycat10_2=F3_21group + recode industrycat10_2 (5=4) (6=5) (7 9=6) (8 10=7) (11/14=8) (15=9) (16/21=10) + replace industrycat10_2=. if lstatus!=1|F1!=1 + label var industrycat10_2 "1 digit industry classification, secondary job 7 day recall" + label values industrycat10_2 lblindustrycat10 +* + + +*<_industrycat4_2_> + gen byte industrycat4_2=industrycat10_2 + recode industrycat4_2 (3/5=2)(6/9=3)(10=4) + label var industrycat4_2 "1 digit industry classification (Broad Economic Activities), secondary job 7 day recall" + label values industrycat4_2 lblindustrycat4 +* + + +*<_occup_orig_2_> + gen occup_orig_2=F2_9group + replace occup_orig_2=. if lstatus!=1|F1!=1 + label var occup_orig_2 "Original occupation record secondary job 7 day recall" +* + + +*<_occup_isco_2_> + gen occup_isco_2="" + replace occup_isco_2="" if lstatus!=1 | occup_isco_2=="."|F1!=1 + label var occup_isco_2 "ISCO code of secondary job 7 day recall" +* + + +*<_occup_skill_2_> + gen occup_skill_2=F2_9group + replace occup_skill_2=1 if F2_9group==9 + replace occup_skill_2=2 if inrange(F2_9group,4,8) + replace occup_skill_2=3 if inrange(F2_9group,1,3) + replace occup_skill_2=. if F2_9group==0|lstatus!=1|F1!=1 + label var occup_skill_2 "Skill based on ISCO standard secondary job 7 day recall" +* + + +*<_occup_2_> + gen occup_2=F2_9group + replace occup_2=. if lstatus!=1|F1!=1 + label var occup_2 "1 digit occupational classification secondary job 7 day recall" + label values occup_2 lbloccup +* + + +*<_wage_no_compen_2_> + +/*<_wage_no_compen_2_note_> + +The questionnaire actually has questions about income of the second job, just as the +main job. However, the data set does not have the variables. + +*<_wage_no_compen_2_note_>*/ + gen wage_no_compen_2=. + replace wage_no_compen_2=. if F1!=1|empstat_2==2 + label var wage_no_compen_2 "Last wage payment secondary job 7 day recall" +* + + +*<_unitwage_2_> + gen byte unitwage_2=. + replace unitwage_2=. if lstatus!=1|F1!=1 + label var unitwage_2 "Last wages' time unit secondary job 7 day recall" + label values unitwage_2 lblunitwage +* + + +*<_whours_2_> + gen whours_2=G2_2 + replace whours_2=. if G2_2==0|F1!=1 + label var whours_2 "Hours of work in last week secondary job 7 day recall" +* + + +*<_wmonths_2_> + gen wmonths_2=. + label var wmonths_2 "Months of work in past 12 months secondary job 7 day recall" +* + + +*<_wage_total_2_> + gen wage_total_2=. + label var wage_total_2 "Annualized total wage secondary job 7 day recall" +* + + +*<_firmsize_l_2_> + gen byte firmsize_l_2=. + label var firmsize_l_2 "Firm size (lower bracket) secondary job 7 day recall" +* + + +*<_firmsize_u_2_> + gen byte firmsize_u_2=. + label var firmsize_u_2 "Firm size (upper bracket) secondary job 7 day recall" +* + +} + +*----------8.4: 7 day reference additional jobs------------------------------* + +*<_t_hours_others_> + gen t_hours_others=. + label var t_hours_others "Annualized hours worked in all but primary and secondary jobs 7 day recall" +* + + +*<_t_wage_nocompen_others_> + gen t_wage_nocompen_others=. + label var t_wage_nocompen_others "Annualized wage in all but primary & secondary jobs excl. bonuses, etc. 7 day recall" +* + + +*<_t_wage_others_> + gen t_wage_others=. + label var t_wage_others "Annualized wage in all but primary and secondary jobs (12-mon ref period)" +* + + +*----------8.5: 7 day reference total summary------------------------------* + + +*<_t_hours_total_> + gen t_hours_total=. + label var t_hours_total "Annualized hours worked in all jobs 7 day recall" +* + + +*<_t_wage_nocompen_total_> + gen t_wage_nocompen_total=. + label var t_wage_nocompen_total "Annualized wage in all jobs excl. bonuses, etc. 7 day recall" +* + + +*<_t_wage_total_> + gen t_wage_total=. + label var t_wage_total "Annualized total wage for all jobs 7 day recall" +* + + +*----------8.6: 12 month reference overall------------------------------* + +{ +*<_lstatus_year_> + gen byte lstatus_year=. + replace lstatus_year=. if age + + +*<_potential_lf_year_> + gen byte potential_lf_year=. + replace potential_lf_year=. if age + + +*<_underemployment_year_> + gen byte underemployment_year=. + replace underemployment_year=. if age + + +*<_nlfreason_year_> + gen byte nlfreason_year=. + label var nlfreason_year "Reason not in the labor force" + la de lblnlfreason_year 1 "Student" 2 "Housekeeper" 3 "Retired" 4 "Disable" 5 "Other" + label values nlfreason_year lblnlfreason_year +* + + +*<_unempldur_l_year_> + gen byte unempldur_l_year=. + label var unempldur_l_year "Unemployment duration (months) lower bracket" +* + + +*<_unempldur_u_year_> + gen byte unempldur_u_year=. + label var unempldur_u_year "Unemployment duration (months) upper bracket" +* + +} + +*----------8.7: 12 month reference main job------------------------------* + +{ +*<_empstat_year_> + gen byte empstat_year=. + label var empstat_year "Employment status during past week primary job 12 month recall" + la de lblempstat_year 1 "Paid employee" 2 "Non-paid employee" 3 "Employer" 4 "Self-employed" 5 "Other, workers not classifiable by status" + label values empstat_year lblempstat_year +* + + +*<_ocusec_year_> + gen byte ocusec_year=. + label var ocusec_year "Sector of activity primary job 12 day recall" + la de lblocusec_year 1 "Public Sector, Central Government, Army" 2 "Private, NGO" 3 "State owned" 4 "Public or State-owned, but cannot distinguish" + label values ocusec_year lblocusec_year +* + + +*<_industry_orig_year_> + gen industry_orig_year=. + label var industry_orig_year "Original industry record main job 12 month recall" +* + + +*<_industrycat_isic_year_> + gen industrycat_isic_year="" + replace industrycat_isic_year="" if industrycat_isic_year=="." + label var industrycat_isic_year "ISIC code of primary job 12 month recall" +* + + +*<_industrycat10_year_> + gen byte industrycat10_year=. + label var industrycat10_year "1 digit industry classification, primary job 12 month recall" + la de lblindustrycat10_year 1 "Agriculture" 2 "Mining" 3 "Manufacturing" 4 "Public utilities" 5 "Construction" 6 "Commerce" 7 "Transport and Comnunications" 8 "Financial and Business Services" 9 "Public Administration" 10 "Other Services, Unspecified" + label values industrycat10_year lblindustrycat10_year +* + + +*<_industrycat4_year_> + gen byte industrycat4_year=industrycat10_year + recode industrycat4_year (1=1)(2 3 4 5 =2)(6 7 8 9=3)(10=4) + label var industrycat4_year "1 digit industry classification (Broad Economic Activities), primary job 12 month recall" + la de lblindustrycat4_year 1 "Agriculture" 2 "Industry" 3 "Services" 4 "Other" + label values industrycat4_year lblindustrycat4_year +* + + +*<_occup_orig_year_> + gen occup_orig_year=. + label var occup_orig_year "Original occupation record primary job 12 month recall" +* + + +*<_occup_isco_year_> + gen str4 occup_isco_year="" + label var occup_isco_year "ISCO code of primary job 12 month recall" +* + + +*<_occup_skill_year_> + gen skill_level_year=substr(occup_isco_year,1,1) + destring skill_level_year, replace + gen occup_skill_year=. + replace occup_skill_year=1 if skill_level_year==9 + replace occup_skill_year=2 if inrange(skill_level_year,4,8) + replace occup_skill_year=3 if inrange(skill_level_year,1,3) + replace occup_skill_year=. if skill_level_year==0 + label var occup_skill_year "Skill based on ISCO standard primary job 12 month recall" +* + + +*<_occup_year_> + gen byte occup_year=. + label var occup_year "1 digit occupational classification, primary job 12 month recall" + la de lbloccup_year 1 "Managers" 2 "Professionals" 3 "Technicians" 4 "Clerks" 5 "Service and market sales workers" 6 "Skilled agricultural" 7 "Craft workers" 8 "Machine operators" 9 "Elementary occupations" 10 "Armed forces" 99 "Others" + label values occup_year lbloccup_year +* + + +*<_wage_no_compen_year_> + gen double wage_no_compen_year=. + label var wage_no_compen_year "Last wage payment primary job 12 month recall" +* + + +*<_unitwage_year_> + gen byte unitwage_year=. + label var unitwage_year "Last wages' time unit primary job 12 month recall" + la de lblunitwage_year 1 "Daily" 2 "Weekly" 3 "Every two weeks" 4 "Bimonthly" 5 "Monthly" 6 "Trimester" 7 "Biannual" 8 "Annually" 9 "Hourly" 10 "Other" + label values unitwage_year lblunitwage_year +* + + +*<_whours_year_> + gen whours_year=. + label var whours_year "Hours of work in last week primary job 12 month recall" +* + + +*<_wmonths_year_> + gen wmonths_year=. + label var wmonths_year "Months of work in past 12 months primary job 12 month recall" +* + + +*<_wage_total_year_> + gen wage_total_year=. + label var wage_total_year "Annualized total wage primary job 12 month recall" +* + + +*<_contract_year_> + gen byte contract_year=. + label var contract_year "Employment has contract primary job 12 month recall" + la de lblcontract_year 0 "Without contract" 1 "With contract" + label values contract_year lblcontract_year +* + + +*<_healthins_year_> + gen byte healthins_year=. + label var healthins_year "Employment has health insurance primary job 12 month recall" + la de lblhealthins_year 0 "Without health insurance" 1 "With health insurance" + label values healthins_year lblhealthins_year +* + + +*<_socialsec_year_> + gen byte socialsec_year=. + label var socialsec_year "Employment has social security insurance primary job 7 day recall" + la de lblsocialsec_year 1 "With social security" 0 "Without social secturity" + label values socialsec_year lblsocialsec_year +* + + +*<_union_year_> + gen byte union_year=. + label var union_year "Union membership at primary job 12 month recall" + la de lblunion_year 0 "Not union member" 1 "Union member" + label values union_year lblunion_year +* + + +*<_firmsize_l_year_> + gen byte firmsize_l_year=. + label var firmsize_l_year "Firm size (lower bracket) primary job 12 month recall" +* + + +*<_firmsize_u_year_> + gen byte firmsize_u_year=. + label var firmsize_u_year "Firm size (upper bracket) primary job 12 month recall" +* + +} + + +*----------8.8: 12 month reference secondary job------------------------------* + +{ + +*<_empstat_2_year_> + gen byte empstat_2_year=. + label var empstat_2_year "Employment status during past week secondary job 12 month recall" + label values empstat_2_year lblempstat_year +* + + +*<_ocusec_2_year_> + gen byte ocusec_2_year=. + label var ocusec_2_year "Sector of activity secondary job 12 day recall" + la de lblocusec_2_year 1 "Public Sector, Central Government, Army" 2 "Private, NGO" 3 "State owned" 4 "Public or State-owned, but cannot distinguish" + label values ocusec_2_year lblocusec_2_year +* + + + +*<_industry_orig_2_year_> + gen industry_orig_2_year=. + label var industry_orig_2_year "Original survey industry code, secondary job 12 month recall" +* + + + +*<_industrycat_isic_2_year_> + gen industrycat_isic_2_year=. + label var industrycat_isic_2_year "ISIC code of secondary job 12 month recall" +* + + +*<_industrycat10_2_year_> + gen byte industrycat10_2_year=. + label var industrycat10_2_year "1 digit industry classification, secondary job 12 month recall" + label values industrycat10_2_year lblindustrycat10_year +* + + +*<_industrycat4_2_year_> + gen byte industrycat4_2_year=industrycat10_2_year + recode industrycat4_2_year (1=1)(2 3 4 5 =2)(6 7 8 9=3)(10=4) + label var industrycat4_2_year "1 digit industry classification (Broad Economic Activities), secondary job 12 month recall" + label values industrycat4_2_year lblindustrycat4_year +* + + +*<_occup_orig_2_year_> + gen occup_orig_2_year=. + label var occup_orig_2_year "Original occupation record secondary job 12 month recall" +* + + +*<_occup_isco_2_year_> + gen occup_isco_2_year=. + label var occup_isco_2_year "ISCO code of secondary job 12 month recall" +* + + +*<_occup_skill_2_year_> + gen occup_skill_2_year=. + label var occup_skill_2_year "Skill based on ISCO standard secondary job 12 month recall" +* + + +*<_occup_2_year_> + gen byte occup_2_year=. + label var occup_2_year "1 digit occupational classification, secondary job 12 month recall" + label values occup_2_year lbloccup_year +* + + +*<_wage_no_compen_2_year_> + gen double wage_no_compen_2_year=. + label var wage_no_compen_2_year "Last wage payment secondary job 12 month recall" +* + + +*<_unitwage_2_year_> + gen byte unitwage_2_year=. + label var unitwage_2_year "Last wages' time unit secondary job 12 month recall" + label values unitwage_2_year lblunitwage_year +* + + +*<_whours_2_year_> + gen whours_2_year=. + label var whours_2_year "Hours of work in last week secondary job 12 month recall" +* + + +*<_wmonths_2_year_> + gen wmonths_2_year=. + label var wmonths_2_year "Months of work in past 12 months secondary job 12 month recall" +* + + +*<_wage_total_2_year_> + gen wage_total_2_year=. + label var wage_total_2_year "Annualized total wage secondary job 12 month recall" +* + + +*<_firmsize_l_2_year_> + gen byte firmsize_l_2_year=. + label var firmsize_l_2_year "Firm size (lower bracket) secondary job 12 month recall" +* + + +*<_firmsize_u_2_year_> + gen byte firmsize_u_2_year=. + label var firmsize_u_2_year "Firm size (upper bracket) secondary job 12 month recall" +* + +} + + +*----------8.9: 12 month reference additional jobs------------------------------* + + +*<_t_hours_others_year_> + gen t_hours_others_year=. + label var t_hours_others_year "Annualized hours worked in all but primary and secondary jobs 12 month recall" +* + + +*<_t_wage_nocompen_others_year_> + gen t_wage_nocompen_others_year=. + label var t_wage_nocompen_others_year "Annualized wage in all but primary & secondary jobs excl. bonuses, etc. 12 month recall)" +* + + +*<_t_wage_others_year_> + gen t_wage_others_year=. + label var t_wage_others_year "Annualized wage in all but primary and secondary jobs 12 month recall" +* + + +*----------8.10: 12 month total summary------------------------------* + + +*<_t_hours_total_year_> + gen t_hours_total_year=. + label var t_hours_total_year "Annualized hours worked in all jobs 12 month month recall" +* + + +*<_t_wage_nocompen_total_year_> + gen t_wage_nocompen_total_year=. + label var t_wage_nocompen_total_year "Annualized wage in all jobs excl. bonuses, etc. 12 month recall" +* + + +*<_t_wage_total_year_> + gen t_wage_total_year=. + label var t_wage_total_year "Annualized total wage for all jobs 12 month recall" +* + + +*----------8.11: Overall across reference periods------------------------------* + + +*<_njobs_> + gen njobs=. + replace njobs=1 if lstatus==1&F1!=1 + replace njobs=2 if lstatus==1&F1==1 + replace njobs=. if lstatus!=1 + label var njobs "Total number of jobs" +* + + +*<_t_hours_annual_> + gen t_hours_annual=. + label var t_hours_annual "Total hours worked in all jobs in the previous 12 months" +* + + +*<_linc_nc_> + gen linc_nc=. + label var linc_nc "Total annual wage income in all jobs, excl. bonuses, etc." +* + + +*<_laborincome_> + gen laborincome=. + label var laborincome "Total annual individual labor income in all jobs, incl. bonuses, etc." +* + + +*----------8.13: Labour cleanup------------------------------* + +{ +*<_% Correction min age_> + +** Drop info for cases under the age for which questions to be asked (do not need a variable for this) + local lab_var "minlaborage lstatus nlfreason unempldur_l unempldur_u empstat ocusec industry_orig industrycat_isic industrycat10 industrycat4 occup_orig occup_isco occup_skill occup wage_no_compen unitwage whours wmonths wage_total contract healthins socialsec union firmsize_l firmsize_u empstat_2 ocusec_2 industry_orig_2 industrycat_isic_2 industrycat10_2 industrycat4_2 occup_orig_2 occup_isco_2 occup_skill_2 occup_2 wage_no_compen_2 unitwage_2 whours_2 wmonths_2 wage_total_2 firmsize_l_2 firmsize_u_2 t_hours_others t_wage_nocompen_others t_wage_others t_hours_total t_wage_nocompen_total t_wage_total lstatus_year nlfreason_year unempldur_l_year unempldur_u_year empstat_year ocusec_year industry_orig_year industrycat_isic_year industrycat10_year industrycat4_year occup_orig_year occup_isco_year occup_skill_year occup_year unitwage_year whours_year wmonths_year wage_total_year contract_year healthins_year socialsec_year union_year firmsize_l_year firmsize_u_year empstat_2_year ocusec_2_year industry_orig_2_year industrycat_isic_2_year industrycat10_2_year industrycat4_2_year occup_orig_2_year occup_isco_2_year occup_skill_2_year occup_2_year wage_no_compen_2_year unitwage_2_year whours_2_year wmonths_2_year wage_total_2_year firmsize_l_2_year firmsize_u_2_year t_hours_others_year t_wage_nocompen_others_year t_wage_others_year t_hours_total_year t_wage_nocompen_total_year t_wage_total_year njobs t_hours_annual linc_nc laborincome" + + foreach v of local lab_var { + cap confirm numeric variable `v' + if _rc == 0 { // is indeed numeric + replace `v'=. if ( age < minlaborage & !missing(age) ) + } + else { // is not + replace `v'= "" if ( age < minlaborage & !missing(age) ) + } + + } + +* +} + + +/*%%============================================================================================= + 9: Final steps +==============================================================================================%%*/ + +quietly{ + +*<_% KEEP VARIABLES - ALL_> + + keep countrycode survname survey icls_v isced_version isco_version isic_version year vermast veralt harmonization int_year int_month hhid pid weight weight_m weight_q psu strata wave panel visit_no urban subnatid1 subnatid2 subnatid3 subnatidsurvey subnatid1_prev subnatid2_prev subnatid3_prev gaul_adm1_code gaul_adm2_code gaul_adm3_code hsize age male relationharm relationcs marital eye_dsablty hear_dsablty walk_dsablty conc_dsord slfcre_dsablty comm_dsablty migrated_mod_age migrated_ref_time migrated_binary migrated_years migrated_from_urban migrated_from_cat migrated_from_code migrated_from_country migrated_reason ed_mod_age school literacy educy educat7 educat5 educat4 educat_orig educat_isced vocational vocational_type vocational_length_l vocational_length_u vocational_field_orig vocational_financed minlaborage lstatus potential_lf underemployment nlfreason unempldur_l unempldur_u empstat ocusec industry_orig industrycat_isic industrycat10 industrycat4 occup_orig occup_isco occup_skill occup wage_no_compen unitwage whours wmonths wage_total contract healthins socialsec union firmsize_l firmsize_u empstat_2 ocusec_2 industry_orig_2 industrycat_isic_2 industrycat10_2 industrycat4_2 occup_orig_2 occup_isco_2 occup_skill_2 occup_2 wage_no_compen_2 unitwage_2 whours_2 wmonths_2 wage_total_2 firmsize_l_2 firmsize_u_2 t_hours_others t_wage_nocompen_others t_wage_others t_hours_total t_wage_nocompen_total t_wage_total lstatus_year potential_lf_year underemployment_year nlfreason_year unempldur_l_year unempldur_u_year empstat_year ocusec_year industry_orig_year industrycat_isic_year industrycat10_year industrycat4_year occup_orig_year occup_isco_year occup_skill_year occup_year wage_no_compen_year unitwage_year whours_year wmonths_year wage_total_year contract_year healthins_year socialsec_year union_year firmsize_l_year firmsize_u_year empstat_2_year ocusec_2_year industry_orig_2_year industrycat_isic_2_year industrycat10_2_year industrycat4_2_year occup_orig_2_year occup_isco_2_year occup_skill_2_year occup_2_year wage_no_compen_2_year unitwage_2_year whours_2_year wmonths_2_year wage_total_2_year firmsize_l_2_year firmsize_u_2_year t_hours_others_year t_wage_nocompen_others_year t_wage_others_year t_hours_total_year t_wage_nocompen_total_year t_wage_total_year njobs t_hours_annual linc_nc laborincome + +* + + +*<_% ORDER VARIABLES_> + + order countrycode survname survey icls_v isced_version isco_version isic_version year vermast veralt harmonization int_year int_month hhid pid weight weight_m weight_q psu strata wave panel visit_no urban subnatid1 subnatid2 subnatid3 subnatidsurvey subnatid1_prev subnatid2_prev subnatid3_prev gaul_adm1_code gaul_adm2_code gaul_adm3_code hsize age male relationharm relationcs marital eye_dsablty hear_dsablty walk_dsablty conc_dsord slfcre_dsablty comm_dsablty migrated_mod_age migrated_ref_time migrated_binary migrated_years migrated_from_urban migrated_from_cat migrated_from_code migrated_from_country migrated_reason ed_mod_age school literacy educy educat7 educat5 educat4 educat_orig educat_isced vocational vocational_type vocational_length_l vocational_length_u vocational_field_orig vocational_financed minlaborage lstatus potential_lf underemployment nlfreason unempldur_l unempldur_u empstat ocusec industry_orig industrycat_isic industrycat10 industrycat4 occup_orig occup_isco occup_skill occup wage_no_compen unitwage whours wmonths wage_total contract healthins socialsec union firmsize_l firmsize_u empstat_2 ocusec_2 industry_orig_2 industrycat_isic_2 industrycat10_2 industrycat4_2 occup_orig_2 occup_isco_2 occup_skill_2 occup_2 wage_no_compen_2 unitwage_2 whours_2 wmonths_2 wage_total_2 firmsize_l_2 firmsize_u_2 t_hours_others t_wage_nocompen_others t_wage_others t_hours_total t_wage_nocompen_total t_wage_total lstatus_year potential_lf_year underemployment_year nlfreason_year unempldur_l_year unempldur_u_year empstat_year ocusec_year industry_orig_year industrycat_isic_year industrycat10_year industrycat4_year occup_orig_year occup_isco_year occup_skill_year occup_year wage_no_compen_year unitwage_year whours_year wmonths_year wage_total_year contract_year healthins_year socialsec_year union_year firmsize_l_year firmsize_u_year empstat_2_year ocusec_2_year industry_orig_2_year industrycat_isic_2_year industrycat10_2_year industrycat4_2_year occup_orig_2_year occup_isco_2_year occup_skill_2_year occup_2_year wage_no_compen_2_year unitwage_2_year whours_2_year wmonths_2_year wage_total_2_year firmsize_l_2_year firmsize_u_2_year t_hours_others_year t_wage_nocompen_others_year t_wage_others_year t_hours_total_year t_wage_nocompen_total_year t_wage_total_year njobs t_hours_annual linc_nc laborincome + +* + + +*<_% DROP UNUSED LABELS_> + + * Store all labels in data + label dir + local all_lab `r(names)' + + * Store all variables with a label, extract value label names + local used_lab = "" + ds, has(vallabel) + + local labelled_vars `r(varlist)' + + foreach varName of local labelled_vars { + local y : value label `varName' + local used_lab `"`used_lab' `y'"' + } + + * Compare lists, `notused' is list of labels in directory but not used in final variables + local notused : list all_lab - used_lab // local `notused' defines value labs not in remaining vars + local notused_len : list sizeof notused // store size of local + + * drop labels if the length of the notused vector is 1 or greater, otherwise nothing to drop + if `notused_len' >= 1 { + label drop `notused' + } + else { + di "There are no unused labels to drop. No value labels dropped." + } + + +* + +} + +*<_% DELETE MISSING VARIABLES_> + +quietly: describe, varlist +local kept_vars `r(varlist)' + +foreach var of local kept_vars { + + capture assert missing(`var') + if !_rc drop `var' +} + +* + + +*<_% COMPRESS_> + +compress + +* + + +*<_% SAVE_> + +save "`path_output'/`level_2_harm'_ALL.dta", replace + +* diff --git a/GLD/ARM/ARM_2021_LFS/ARM_2021_LFS_V01_M_V03_A_GLD/Programs/ARM_2021_LFS_V01_M_V03_A_GLD_ALL.do b/GLD/ARM/ARM_2021_LFS/ARM_2021_LFS_V01_M_V03_A_GLD/Programs/ARM_2021_LFS_V01_M_V03_A_GLD_ALL.do new file mode 100644 index 000000000..59a968b26 --- /dev/null +++ b/GLD/ARM/ARM_2021_LFS/ARM_2021_LFS_V01_M_V03_A_GLD/Programs/ARM_2021_LFS_V01_M_V03_A_GLD_ALL.do @@ -0,0 +1,1795 @@ + +/*%%============================================================================================= + 0: GLD Harmonization Preamble +================================================================================================*/ + +/* ----------------------------------------------------------------------- +<_Program name_> ARM_2021_LFS_V01_M_V03_A_GLD_ALL.do +<_Application_> Stata SE 18 <_Application_> +<_Author(s)_> Wolrd Bank Job's Group +<_Date created_> 2024-1-10 +------------------------------------------------------------------------- +<_Country_> Armenia (ARM) +<_Survey Title_> National Labour Force Survey +<_Survey Year_> 2021 +<_Study ID_> ARM_2021_LFS_v01_M +<_Data collection from (M/Y)_> [01/2021] +<_Data collection to (M/Y)_> [12/2021] +<_Source of dataset_> The Armenian 2021 to 2021 data is downloaded from + the website of Statistical Committee of the + Republic of Armenia:https://armstat.am/en/?nid=212 + The data is publicly available. +<_Sample size (HH)_> 7,776 +<_Sample size (IND)_> 26,923 +<_Sampling method_> A stratified two-stage probability sample design + with 14 domains as the primary strata and 18,000 + households as the SSU. +<_Geographic coverage_> All 11 regions/marzes. +<_Currency_> Armenian Dram +----------------------------------------------------------------------- +<_ICLS Version_> ICLS 19 +<_ISCED Version_> ISCED-2011 +<_ISCO Version_> ISCO 08 +<_OCCUP National_> NSCO +<_ISIC Version_> ISIC Rev.4 +<_INDUS National_> ISIC Rev.4 +----------------------------------------------------------------------- + +<_Version Control_> + +* Date: 2024-09-24 - Update vars educy, educat7, educat_isced +* Date: 2024-10-10 - Include weight by quarter, old weight variable, correct contract variable, drop migration + + + +-------------------------------------------------------------------------*/ + + +/*%%============================================================================================= + 1: Setting up of program environment, dataset +================================================================================================*/ + +*----------1.1: Initial commands------------------------------* + +clear +set more off +set mem 800m + +*----------1.2: Set directories------------------------------* + +* Define path sections +local server "Y:/GLD" +local country "ARM" +local year "2021" +local survey "LFS" +local vermast "V01" +local veralt "V03" + +* From the definitions, set path chunks +local level_1 "`country'_`year'_`survey'" +local level_2_mast "`level_1'_`vermast'_M" +local level_2_harm "`level_1'_`vermast'_M_`veralt'_A_GLD" + +* From chunks, define path_in, path_output folder +local path_in_stata "`server'/`country'/`level_1'/`level_2_mast'/Data/Stata" +local path_in_other "`server'/`country'/`level_1'/`level_2_mast'/Data/Original" +local path_output "`server'/`country'/`level_1'/`level_2_harm'/Data/Harmonized" + +* Define Output file name +local out_file "`level_2_harm'_ALL.dta" + + +*----------1.3: Database assembly------------------------------* + +* All steps necessary to merge datasets (if several) to have all elements needed to produce +* harmonized output in a single file + +use "`path_in_stata'/ARM_LFS_2021_raw.dta", clear +rename (E2_9groups_ISCO_88 _v1 F2_9groups_ISCO_88 _v2) (E2_9group E4_21group F2_9group F3_21group) + +/*%%============================================================================================= + 2: Survey & ID +================================================================================================*/ + +{ + +*<_countrycode_> + gen str4 countrycode="`country'" + label var countrycode "Country code" +* + + +*<_survname_> + gen survname="LFS" + label var survname "Survey acronym" +* + + +*<_survey_> + gen survey="LFS" + label var survey "Survey type" +* + + +*<_icls_v_> + gen icls_v="ICLS-19" + label var icls_v "ICLS version underlying questionnaire questions" +* + + +*<_isced_version_> + gen isced_version="isced_2011" + label var isced_version "Version of ISCED used for educat_isced" +* + + +*<_isco_version_> + gen isco_version="" + label var isco_version "Version of ISCO used" +* + + +*<_isic_version_> + gen isic_version="" + label var isic_version "Version of ISIC used" +* + + +*<_year_> + gen int year=`year' + label var year "Year of survey" +* + + +*<_vermast_> + gen str3 vermast="`vermast'" + label var vermast "Version of master data" +* + + +*<_veralt_> + gen str3 veralt="`veralt'" + label var veralt "Version of the alt/harmonized data" +* + + +*<_harmonization_> + gen harmonization="GLD" + label var harmonization "Type of harmonization" +* + + +*<_int_year_> + gen int_year=`year' + label var int_year "Year of the interview" +* + + +*<_int_month_> + gen int_month=A6_Month + label de lblint_month 1 "January" 2 "February" 3 "March" 4 "April" 5 "May" 6 "June" 7 "July" 8 "August" 9 "September" 10 "October" 11 "November" 12 "December" + label value int_month lblint_month + label var int_month "Month of the interview" +* + + +*<_hhid_> + tostring A1, gen(hid) format(%03.0f) + tostring A6_Month, gen(month) format(%03.0f) + egen hhid=concat(month hid) + label var hhid "Household id" +* + + +*<_pid_> + sort hhid B4 + bys hhid: gen memberid=_n + tostring memberid, gen(id_str) format(%02.0f) + egen pid=concat(hhid id_str), punct("-") + label var pid "Individual ID" +* + + +*<_weight_> + gen weight = WeightsCalib_year + label var weight "Household sampling weight" +* + + +*<_weight_m_> + gen weight_m = . + label var weight_m "Survey sampling weight to obtain national estimates for each month" +* + + +*<_weight_q_> + egen weight_q = rowtotal(WeightsCalib_1 WeightsCalib_2 WeightsCalib_3 WeightsCalib_4) + label var weight_q "Survey sampling weight to obtain national estimates for each quarter" +* + + +*<_psu_> + gen psu=. + label var psu "Primary sampling units" +* + + +*<_ssu_> + gen ssu=hhid + label var ssu "Secondary sampling units" +* + + +*<_strata_> + decode A3, gen(marzname) + decode A5, gen(urbanstat) + gen strata=marzname + " " + urbanstat + label var strata "Strata" +* + + +*<_wave_> + gen wave=. + replace wave=1 if inrange(int_month,1,3) + replace wave=2 if inrange(int_month,4,6) + replace wave=3 if inrange(int_month,7,9) + replace wave=4 if inrange(int_month,10,12) + label var wave "Survey wave" +* + + +*<_panel_> + gen panel="" + label var panel "Panel individual belongs to" +* + + +*<_visit_no_> + gen visit_no=. + label var visit_no "Visit number in panel" +* +} + +/*%%============================================================================================= + 3: Geography +================================================================================================*/ + +{ + +*<_urban_> + gen urban=A5 + recode urban (2=0) + la de lblurban 1 "Urban" 0 "Rural" + label values urban lblurban + label var urban "Location is urban" +* + + +*<_subnatid1_> + gen subnatid1=A3 + tostring subnatid1, replace + replace subnatid1=subnatid1+" - "+marzname + label var subnatid1 "Subnational ID at First Administrative Level" +* + + +*<_subnatid2_> + gen subnatid2=. + label var subnatid2 "Subnational ID at Second Administrative Level" +* + + +*<_subnatid3_> + gen subnatid3=. + label var subnatid3 "Subnational ID at Third Administrative Level" +* + + +*<_subnatidsurvey_> + gen subnatidsurvey=subnatid1+" "+urbanstat + label var subnatidsurvey "Administrative level at which survey is representative" +* + + +*<_subnatid1_prev_> + +/* <_subnatid1_prev_note_> +subnatid1_prev is coded as missing unless the classification used for subnatid1 has changed since the previous survey. + */ + + gen subnatid1_prev=. + label var subnatid1_prev "Classification used for subnatid1 from previous survey" +* + + +*<_subnatid2_prev_> + gen subnatid2_prev=. + label var subnatid2_prev "Classification used for subnatid2 from previous survey" +* + + +*<_subnatid3_prev_> + gen subnatid3_prev=. + label var subnatid3_prev "Classification used for subnatid3 from previous survey" +* + + +*<_gaul_adm1_code_> + gen gaul_adm1_code=. + label var gaul_adm1_code "Global Administrative Unit Layers (GAUL) Admin 1 code" +* + + +*<_gaul_adm2_code_> + gen gaul_adm2_code=. + label var gaul_adm2_code "Global Administrative Unit Layers (GAUL) Admin 2 code" +* + + +*<_gaul_adm3_code_> + gen gaul_adm3_code=. + label var gaul_adm3_code "Global Administrative Unit Layers (GAUL) Admin 3 code" +* + +} + +/*%%============================================================================================= + 4: Demography +================================================================================================*/ + +{ + +*<_hsize_> + bys hhid: egen hsize=max(memberid) + label var hsize "Household size" +* + + +*<_age_> + +/*<_age_note_> + +Because the raw data in 2021 and 2022 do not have each observation's actual age, +and instead, they only have age in age groups. Here we coded age using the mean of +each age group to proceed with other variables and our quality checks. Therefore, +the age variable only represents the age group the observation is in. + +*<_age_note_>*/ + + gen age=. + replace age=(Age_16groups-1)*5+2 + replace age=98 if age>98 & age!=. + label var age "Individual age" +* + + +*<_male_> + gen male=B3 + recode male 2=0 + label var male "Sex - Ind is male" + la de lblmale 1 "Male" 0 "Female" + label values male lblmale +* + + +*<_relationharm_> + +/*<_relationharm_note_> + +7 households (27 observations) in the raw data set do not have household heads. +Their household IDs are: + +003331 004606 007502 +009139 009481 012302 +012648 + +During the harmonization, we did not assign household heads to these households. +But users can assign household heads based on their relationship to the head and +other characteristics such as gender and age. + +*<_relationharm_note_>*/ + + gen byte relationharm=B4 + recode relationharm (6 9=3) (7 8=4) (10=5) (11=6) + replace relationharm=5 if pid=="009002-02" + label var relationharm "Relationship to the head of household - Harmonized" + la de lblrelationharm 1 "Head of household" 2 "Spouse" 3 "Children" 4 "Parents" 5 "Other relatives" 6 "Other and non-relatives" + label values relationharm lblrelationharm +*<_relationharm_> + + +*<_relationcs_> + gen relationcs=B4 + label var relationcs "Relationship to the head of household - Country original" +* + + +*<_marital_> + gen marital=B11 + recode marital (1=2) (2=1) (3=5) + label var marital "Marital status" + la de lblmarital 1 "Married" 2 "Never Married" 3 "Living together" 4 "Divorced/Separated" 5 "Widowed" + label values marital lblmarital +* + + +*<_eye_dsablty_> + gen eye_dsablty=. + la de lbleye_dsablty 1 "No" 2 "Yes-some" 3 "Yes-a lot" 4 "Cannot at all" + label values eye_dsablty lbleye_dsablty + label var eye_dsablty "Disability related to eyesight" +* + + +*<_hear_dsablty_> + gen hear_dsablty=. + la de lblhear_dsablty 1 "No" 2 "Yes-some" 3 "Yes-a lot" 4 "Cannot at all" + label values hear_dsablty lblhear_dsablty + label var hear_dsablty "Disability related to hearing" +* + + +*<_walk_dsablty_> + gen walk_dsablty=. + la de lblwalk_dsablty 1 "No" 2 "Yes-some" 3 "Yes-a lot" 4 "Cannot at all" + label values walk_dsablty lblwalk_dsablty + label var walk_dsablty "Disability related to walking or climbing stairs" +* + + +*<_conc_dsord_> + gen conc_dsord=. + la de lblconc_dsord 1 "No" 2 "Yes-some" 3 "Yes-a lot" 4 "Cannot at all" + label values conc_dsord lblconc_dsord + label var conc_dsord "Disability related to concentration or remembering" +* + + +*<_slfcre_dsablty_> + gen slfcre_dsablty=. + la de lblslfcre_dsablty 1 "No" 2 "Yes-some" 3 "Yes-a lot" 4 "Cannot at all" + label values slfcre_dsablty lblslfcre_dsablty + label var eye_dsablty "Disability related to selfcare" +* + + +*<_comm_dsablty_> + gen comm_dsablty=. + la de lblcomm_dsablty 1 "No" 2 "Yes-some" 3 "Yes-a lot" 4 "Cannot at all" + label values comm_dsablty lblcomm_dsablty + label var eye_dsablty "Disability related to communicating" +* + +} + + +/*%%============================================================================================= + 5: Migration +==============================================================================================%%*/ + + +{ + +*<_migrated_mod_age_> + gen migrated_mod_age = . + label var migrated_mod_age "Migration module application age" +* + + +*<_migrated_ref_time_> + gen migrated_ref_time = . + label var migrated_ref_time "Reference time applied to migration questions (in years)" +* + + +*<_migrated_binary_> + gen migrated_binary = . + label de lblmigrated_binary 0 "No" 1 "Yes" + label values migrated_binary lblmigrated_binary + label var migrated_binary "Individual has migrated" +* + + +*<_migrated_years_> + gen migrated_years = . + label var migrated_years "Years since latest migration" +* + + +*<_migrated_from_urban_> + gen migrated_from_urban = . + label de lblmigrated_from_urban 0 "Rural" 1 "Urban" + label values migrated_from_urban lblmigrated_from_urban + label var migrated_from_urban "Migrated from area" +* + + +*<_migrated_from_cat_> + gen migrated_from_cat = . + label de lblmigrated_from_cat 1 "From same admin3 area" 2 "From same admin2 area" 3 "From same admin1 area" 4 "From other admin1 area" 5 "From other country" + label values migrated_from_cat lblmigrated_from_cat + label var migrated_from_cat "Category of migration area" +* + + +*<_migrated_from_code_> + gen migrated_from_code = . + *label de lblmigrated_from_code + *label values migrated_from_code lblmigrated_from_code + label var migrated_from_code "Code of migration area as subnatid level of migrated_from_cat" +* + + +*<_migrated_from_country_> + gen migrated_from_country = . + label var migrated_from_country "Code of migration country (ISO 3 Letter Code)" +* + + +*<_migrated_reason_> + gen migrated_reason = . + label de lblmigrated_reason 1 "Family reasons" 2 "Educational reasons" 3 "Employment" 4 "Forced (political reasons, natural disaster, …)" 5 "Other reasons" + label values migrated_reason lblmigrated_reason + label var migrated_reason "Reason for migrating" +* + +} + + +/*%%============================================================================================= + 6: Education +================================================================================================*/ + + +{ +*<_ed_mod_age_> + gen byte ed_mod_age=6 + label var ed_mod_age "Education module application age" +* + + +*<_school_> + gen school=B9 + recode school (2=0) (3/5=.) + replace school=. if !inrange(Age_16groups,2,16) + label var school "Attending school" + la de lblschool 0 "No" 1 "Yes" + label values school lblschool +* + + +*<_literacy_> + gen byte literacy=. + replace literacy=0 if B7==1 + replace literacy=1 if inrange(B7,2,11) + replace literacy=. if !inrange(Age_16groups,2,16) + label var literacy "Individual can read & write" + la de lblliteracy 0 "No" 1 "Yes" + label values literacy lblliteracy +* + + +*<_educy_> + gen byte educy=. + replace educy = 0 if B7 == 1 | B7 == 2 + replace educy = 4 if B7 == 3 + replace educy = 9 if B7 == 4 + replace educy = 12 if B7 == 5 + replace educy = 11 if B7 == 6 + replace educy = 15 if B7 == 7 + replace educy = 16 if B7 == 8 + replace educy = 18 if B7 == 9 | B7 == 10 + replace educy = 20 if B7 == 11 + replace educy=. if ageage & !mi(educy) & !mi(age) + label var educy "Years of education" +* + + +*<_educat7_> + gen byte educat7= B7 + recode educat7 (6=5) (7=6) (8/11=7) + replace educat7=. if age + + +*<_educat5_> + gen byte educat5=educat7 + recode educat5 (4=3) (5=4) (6 7=5) + replace educat5=. if !inrange(Age_16groups,2,16) + label var educat5 "Level of education 2" + la de lbleducat5 1 "No education" 2 "Primary incomplete" 3 "Primary complete but secondary incomplete" 4 "Secondary complete" 5 "Some tertiary/post-secondary" + label values educat5 lbleducat5 +* + + +*<_educat4_> + gen byte educat4=educat5 + replace educat4=. if !inrange(Age_16groups,2,16) + recode educat4 (3=2) (4=3) (5=4) + label var educat4 "Level of education 3" + la de lbleducat4 1 "No education" 2 "Primary" 3 "Secondary" 4 "Post-secondary" + label values educat4 lbleducat4 +* + + +*<_educat_orig_> + gen educat_orig=B7 + label var educat_orig "Original survey education code" +* + + +*<_educat_isced_> + gen educat_isced=. + label var educat_isced "ISCED standardised level of education" +* + + +*<_educat_isced_v_> + gen educat_isced_v="ISCED-2011" + label var educat_isced_v "Version of the ISCED used" +* + +*----------6.1: Education cleanup------------------------------* + +*<_% Correction min age_> + +** Drop info for cases under the age for which questions to be asked (do not need a variable for this) +local ed_var school literacy educy educat7 educat5 educat4 educat_isced +foreach v of local ed_var { + replace `v'=. if ( age < ed_mod_age & !missing(age) ) +} +replace educat_isced_v="." if ( age < ed_mod_age & !missing(age) ) +* + +} + +/*%%============================================================================================= + 7: Training +================================================================================================*/ + +{ + +*<_vocational_> + gen vocational=. + la de vocationallbl 1 "Yes" 0 "No" + la values vocational vocationallbl + label var vocational "Ever received vocational training" +* + + +*<_vocational_type_> + gen vocational_type=. + label de lblvocational_type 1 "Inside Enterprise" 2 "External" + label values vocational_type lblvocational_type + label var vocational_type "Type of vocational training" +* + + +*<_vocational_length_l_> + gen vocational_length_l=. + replace vocational_length_l=. if vocational!=1 + label var vocational_length_l "Length of training in months, lower limit" +* + + +*<_vocational_length_u_> + gen vocational_length_u=. + replace vocational_length_u=. if vocational!=1 + label var vocational_length_u "Length of training in months, upper limit" +* + + +*<_vocational_field_orig_> + gen vocational_field_orig=. + replace vocational_field_orig=. if vocational!=1 + label var vocational_field_orig "Original field of training information" +* + + +*<_vocational_financed_> + gen vocational_financed=. + label de lblvocational_financed 1 "Employer" 2 "Government" 3 "Mixed Employer/Government" 4 "Own funds" 5 "Other" + label var vocational_financed "How training was financed" +* + +} + +/*%%============================================================================================= + 8: Labour +================================================================================================*/ + +*<_minlaborage_> + +/*<_minlaborage_note_> + +The age range for the labor section is 15-75. + +*<_minlaborage_note_>*/ + + gen byte minlaborage=15 + label var minlaborage "Labor module application age" +* + + +*----------8.1: 7 day reference overall------------------------------* + +{ +*<_lstatus_> + +/*<_lstatus_note> + +The economically inavtive population also needs to be within the age range of +15 and 75. + +*<_lstatus_note>*/ + + gen byte lstatus=. + replace lstatus=1 if D1==1|inrange(D3,1,5)|D4==1|D5==1 + replace lstatus=2 if lstatus==.&inrange(J9,1,3) + replace lstatus=3 if !mi(J1_4groups)&lstatus==. + replace lstatus=. if !inrange(Age_16groups,4,16) + label var lstatus "Labor status" + la de lbllstatus 1 "Employed" 2 "Unemployed" 3 "Non-LF" + label values lstatus lbllstatus +* + + +*<_potential_lf_> + +/*<_potential_lf_note_> +Note: var "potential_lf" only takes value if the respondent is not in labor force. (lstatus==3) + +"potential_lf"=1 if the person is +1)available but not searching or (J16==1)&J9==4 +2)searching but not immediately available to work or inrange(J9,1,3)&J16==2 + +*/ + + gen potential_lf=. + replace potential_lf=1 if [(J16==1)&J9==4] | [inrange(J9,1,3)&J16==2] + replace potential_lf=0 if [(J16==1)&inrange(J9,1,3)] | [inrange(J9,1,3)&J16==1] + replace potential_lf=. if !inrange(Age_16groups,4,16) + replace potential_lf=. if lstatus!=3 + label var potential_lf "Potential labour force status" + la de lblpotential_lf 0 "No" 1 "Yes" + label values potential_lf lblpotential_lf +* + + +*<_underemployment_> + gen byte underemployment=G4 + replace underemployment=1 if inrange(G4,1,3) + replace underemployment=0 if G4==4 + replace underemployment=. if !inrange(Age_16groups,4,16) + replace underemployment=. if lstatus!=1 + label var underemployment "Underemployment status" + la de lblunderemployment 0 "No" 1 "Yes" + label values underemployment lblunderemployment +* + + +*<_nlfreason_> + gen byte nlfreason=J1_4group + recode nlfreason (4=5) + replace nlfreason=. if !inrange(Age_16groups,4,16) + replace nlfreason=. if lstatus!=3 + label var nlfreason "Reason not in the labor force" + la de lblnlfreason 1 "Student" 2 "Housekeeper" 3 "Retired" 4 "Disabled" 5 "Other" + label values nlfreason lblnlfreason +* + + +*<_unempldur_l_> + gen byte unempldur_l=J4 + recode unempldur_l (1=0) (2=3) (3=6) (4=9) (5=12) (6=24) (7=36) + replace unempldur_l=. if !inrange(Age_16groups,4,16) + replace unempldur_l=. if lstatus!=2 + label var unempldur_l "Unemployment duration (months) lower bracket" +* + + +*<_unempldur_u_> + gen byte unempldur_u=J4 + recode unempldur_u (1=3) (2=6) (3=9) (4=12) (5=24) (6=36) (7 10=.) + replace unempldur_u=. if !inrange(Age_16groups,4,16) + replace unempldur_u=. if lstatus!=2 + label var unempldur_u "Unemployment duration (months) upper bracket" +* +} + + +*----------8.2: 7 day reference main job------------------------------* + + +{ +*<_empstat_> + gen byte empstat=E7 + recode empstat (2 6=1) (5=2) + replace empstat=. if lstatus!=1|!inrange(Age_16groups,4,16) + label var empstat "Employment status during past week primary job 7 day recall" + la de lblempstat 1 "Paid employee" 2 "Non-paid employee" 3 "Employer" 4 "Self-employed" 5 "Other, workers not classifiable by status" + label values empstat lblempstat +* + + +*<_ocusec_> + gen byte ocusec=E10 + recode ocusec (3 4=2) + replace ocusec=. if lstatus!=1|!inrange(Age_16groups,4,16) + label var ocusec "Sector of activity primary job 7 day recall" + la de lblocusec 1 "Public Sector, Central Government, Army" 2 "Private, NGO" 3 "State owned" 4 "Public or State-owned, but cannot distinguish" + label values ocusec lblocusec +* + + +*<_industry_orig_> + gen industry_orig=E4_21group + replace industry_orig=. if lstatus!=1 + label var industry_orig "Original survey industry code, main job 7 day recall" +* + + +*<_industrycat_isic_> + gen industrycat_isic="" +quietly +{ + replace industrycat_isic="A" if E4_21group==1 + replace industrycat_isic="B" if E4_21group==2 + replace industrycat_isic="C" if E4_21group==3 + replace industrycat_isic="D" if E4_21group==4 + replace industrycat_isic="E" if E4_21group==5 + replace industrycat_isic="F" if E4_21group==6 + replace industrycat_isic="G" if E4_21group==7 + replace industrycat_isic="H" if E4_21group==8 + replace industrycat_isic="I" if E4_21group==9 + replace industrycat_isic="J" if E4_21group==10 + replace industrycat_isic="K" if E4_21group==11 + replace industrycat_isic="L" if E4_21group==12 + replace industrycat_isic="M" if E4_21group==13 + replace industrycat_isic="N" if E4_21group==14 + replace industrycat_isic="O" if E4_21group==15 + replace industrycat_isic="P" if E4_21group==16 + replace industrycat_isic="Q" if E4_21group==17 + replace industrycat_isic="R" if E4_21group==18 + replace industrycat_isic="S" if E4_21group==19 + replace industrycat_isic="T" if E4_21group==20 + replace industrycat_isic="U" if E4_21group==21 +} + + replace industrycat_isic="" if industrycat_isic=="."|lstatus!=1 + label var industrycat_isic "ISIC code of primary job 7 day recall" +* + + +*<_industrycat10_> + gen industrycat10=E4_21group + recode industrycat10 (5=4) (6=5) (7 9=6) (8 10=7) (11/14=8) (15=9) (16/21=10) + replace industrycat10=. if lstatus!=1 + label var industrycat10 "1 digit industry classification, primary job 7 day recall" + la de lblindustrycat10 1 "Agriculture" 2 "Mining" 3 "Manufacturing" 4 "Public utilities" 5 "Construction" 6 "Commerce" 7 "Transport and Comnunications" 8 "Financial and Business Services" 9 "Public Administration" 10 "Other Services, Unspecified" + label values industrycat10 lblindustrycat10 +* + + +*<_industrycat4_> + gen byte industrycat4=industrycat10 + recode industrycat4 (3/5=2)(6/9=3)(10=4) + label var industrycat4 "1 digit industry classification (Broad Economic Activities), primary job 7 day recall" + la de lblindustrycat4 1 "Agriculture" 2 "Industry" 3 "Services" 4 "Other" + label values industrycat4 lblindustrycat4 +* + + +*<_occup_orig_> + gen occup_orig=E2_9group + replace occup_orig=. if lstatus!=1|!inrange(Age_16groups,4,16) + label var occup_orig "Original occupation record primary job 7 day recall" +* + + +*<_occup_isco_> + gen occup_isco="" + replace occup_isco="" if lstatus!=1 | occup_isco=="." + label var occup_isco "ISCO code of primary job 7 day recall" +* + + +*<_occup_skill_> + gen occup_skill=E2_9group + replace occup_skill=1 if E2_9group==9 + replace occup_skill=2 if inrange(E2_9group, 4, 8) + replace occup_skill=3 if inrange(E2_9group, 1, 3) + replace occup_skill=. if lstatus!=1 + la de lblskill 1 "Low skill" 2 "Medium skill" 3 "High skill" + label values occup_skill lblskill + label var occup_skill "Skill based on ISCO standard primary job 7 day recall" +* + + +*<_occup_> + gen occup=E2_9group + replace occup=. if lstatus!=1|!inrange(Age_16groups,4,16) + label var occup "1 digit occupational classification, primary job 7 day recall" + la de lbloccup 1 "Managers" 2 "Professionals" 3 "Technicians" 4 "Clerks" 5 "Service and market sales workers" 6 "Skilled agricultural" 7 "Craft workers" 8 "Machine operators" 9 "Elementary occupations" 10 "Armed forces" 99 "Others" + label values occup lbloccup +* + + +*<_wage_no_compen_> + +/*<_wage_no_compen_note_> + +The wage questions in the questionnare are organized into to parts: the first part +asks for the specific number of income if the given respondent could recall and was +willing to answer; the second part provides different categories of income range +if the given respondent could not recall or was not willing to answer the first part. + +The general logic here is to impute wage values for people who only answered an income +range. We used industry, occupation, income categories and gender to estimate their +specific income values. + +21.86% of total non-missing wage values were imputed using this method. +*<_wage_no_compen_note_>*/ + + * Overall --> wage info (here the variable, for us it should be wage_no_compen) + * to missing if value is 0. + gen wage14=E14_1+E14_2 + replace wage14=. if wage14==0 + + * First replace outliers by + winsor2 wage14, suffix(_w) cuts(1 99) + + * Create salary categories based on winsor values + gen salary_cat=. + replace salary_cat=1 if inrange(wage14_w, 1, 55000) + replace salary_cat=2 if wage14_w==55000 + replace salary_cat=3 if inrange(wage14_w, 55001, 110000) + replace salary_cat=4 if inrange(wage14_w, 110001, 220000) + replace salary_cat=5 if inrange(wage14_w, 220001, 440000) + replace salary_cat=6 if inrange(wage14_w, 440001, 600000) + replace salary_cat=7 if inrange(wage14_w, 600001, 700000) + + * Preserve to collapse, so we can merge the info in + preserve + + * Collpase by industry, sex, and salary categories + collapse (mean)wage14_w[iw=weight], by(industrycat10 occup male urban salary_cat) + + * Rename variable, otherwise when merging in, master version of an equally name one will be kept + rename wage14_w wage_group_estimate + + * Rename salary_cat to D15 since this is what we want the info to latch on to + rename salary_cat E15 + tempfile salary_helper + save "`salary_helper'" + + * Restore, merge in + restore + merge m:1 industrycat10 occup male urban E15 using "`salary_helper'", keep(matched master) nogen + + * Create wage variable + gen wage_no_compen=. + + * Fill it first with values that are accurate + replace wage_no_compen=wage14 if !mi(wage14)&mi(E15) + + * Now add the categorised means + replace wage_no_compen=wage_group_estimate if inrange(E15,1,8)&!mi(wage_group_estimate) + + * Keep only for employed employees, label + replace wage_no_compen=. if lstatus!=1|empstat==2 + label var wage_no_compen "Last wage payment primary job 7 day recall" +* + + +*<_unitwage_> + gen byte unitwage=E16 + recode unitwage (4=5) (5=7) (6=8) (7=10) + replace unitwage=. if lstatus!=1 | empstat==2 + label var unitwage "Last wages' time unit primary job 7 day recall" + la de lblunitwage 1 "Daily" 2 "Weekly" 3 "Every two weeks" 4 "Bimonthly" 5 "Monthly" 6 "Trimester" 7 "Biannual" 8 "Annually" 9 "Hourly" 10 "Other" + label values unitwage lblunitwage +* + + +*<_whours_> + gen whours=G2_1 + replace whours=. if lstatus!=1|G2_1==0 + label var whours "Hours of work in last week primary job 7 day recall" +* + + +*<_wmonths_> + gen wmonths=. + label var wmonths "Months of work in past 12 months primary job 7 day recall" +* + + +*<_wage_total_> + gen wage_total=. + label var wage_total "Annualized total wage primary job 7 day recall" +* + + +*<_contract_> + +/*<_contract_note_> + +There is no separate contract question in the questionnaire. +This contract variable was coded based on employment status question which asks +wether an employed respondent had a contract or not. + +*<_contract_note_>*/ + + gen byte contract = . + replace contract = (E7 == 1) + replace contract=. if lstatus!=1 + label var contract "Employment has contract primary job 7 day recall" + la de lblcontract 0 "Without contract" 1 "With contract" + label values contract lblcontract +* + + +*<_healthins_> + gen byte healthins=. + replace healthins=1 if E8_f==1 + replace healthins=0 if E8_f==2 + replace healthins=. if lstatus!=1 + label var healthins "Employment has health insurance primary job 7 day recall" + la de lblhealthins 0 "Without health insurance" 1 "With health insurance" + label values healthins lblhealthins +* + + +*<_socialsec_> + gen byte socialsec=. + replace socialsec=. if lstatus!=1 + label var socialsec "Employment has social security insurance primary job 7 day recall" + la de lblsocialsec 1 "With social security" 0 "Without social secturity" + label values socialsec lblsocialsec +* + + +*<_union_> + gen byte union=. + replace union=1 if E27==1 + replace union=0 if E27==2 + replace union=. if lstatus!=1 + label var union "Union membership at primary job 7 day recall" + la de lblunion 0 "Not union member" 1 "Union member" + label values union lblunion +* + + +*<_firmsize_l_> + gen byte firmsize_l=E13 + recode firmsize_l (1=1) (2=5) (3=10) (4=20) (5=50) (6=100) (7=.) + replace firmsize_l=. if lstatus!=1 + label var firmsize_l "Firm size (lower bracket) primary job 7 day recall" +* + + +*<_firmsize_u_> + gen byte firmsize_u=E13 + recode firmsize_u (1=5) (2=9) (3=19) (4=49) (5=99) (6=.) + replace firmsize_u=. if lstatus!=1 + label var firmsize_u "Firm size (upper bracket) primary job 7 day recall" +* + +} + + +*----------8.3: 7 day reference secondary job------------------------------* +* Since labels are the same as main job, values are labelled using main job labels + +{ +*<_empstat_2_> + gen byte empstat_2=F4 + recode empstat_2 (2=1) (5=2) + replace empstat_2=. if lstatus!=1|F1!=1 + label var empstat_2 "Employment status during past week secondary job 7 day recall" + la de lblempstat_2 1 "Paid employee" 2 "Non-paid employee" 3 "Employer" 4 "Self-employed" 5 "Other, workers not classifiable by status" + label values empstat_2 lblempstat +* + + +*<_ocusec_2_> + gen byte ocusec_2=F6 + recode ocusec_2 (3 4=2) + replace ocusec_2=. if lstatus!=1|F1!=1 + label var ocusec_2 "Sector of activity secondary job 7 day recall" + la de lblocusec_2 1 "Public Sector, Central Government, Army" 2 "Private, NGO" 3 "State owned" 4 "Public or State-owned, but cannot distinguish" + label values ocusec_2 lblocusec_2 +* + + +*<_industry_orig_2_> + gen industry_orig_2=F3_21group + replace industry_orig_2=. if lstatus!=1|F1!=1 + label var industry_orig_2 "Original survey industry code, secondary job 7 day recall" +* + + +*<_industrycat_isic_2_> + gen industrycat_isic_2="" +quietly +{ + replace industrycat_isic_2="A" if F3_21group==1 + replace industrycat_isic_2="B" if F3_21group==2 + replace industrycat_isic_2="C" if F3_21group==3 + replace industrycat_isic_2="D" if F3_21group==4 + replace industrycat_isic_2="E" if F3_21group==5 + replace industrycat_isic_2="F" if F3_21group==6 + replace industrycat_isic_2="G" if F3_21group==7 + replace industrycat_isic_2="H" if F3_21group==8 + replace industrycat_isic_2="I" if F3_21group==9 + replace industrycat_isic_2="J" if F3_21group==10 + replace industrycat_isic_2="K" if F3_21group==11 + replace industrycat_isic_2="L" if F3_21group==12 + replace industrycat_isic_2="M" if F3_21group==13 + replace industrycat_isic_2="N" if F3_21group==14 + replace industrycat_isic_2="O" if F3_21group==15 + replace industrycat_isic_2="P" if F3_21group==16 + replace industrycat_isic_2="Q" if F3_21group==17 + replace industrycat_isic_2="R" if F3_21group==18 + replace industrycat_isic_2="S" if F3_21group==19 + replace industrycat_isic_2="T" if F3_21group==20 + replace industrycat_isic_2="U" if F3_21group==21 +} + + replace industrycat_isic_2="" if industrycat_isic_2=="."|F1!=1 + label var industrycat_isic_2 "ISIC code of secondary job 7 day recall" +* + + +*<_industrycat10_2_> + gen industrycat10_2=F3_21group + recode industrycat10_2 (5=4) (6=5) (7 9=6) (8 10=7) (11/14=8) (15=9) (16/21=10) + replace industrycat10_2=. if lstatus!=1|F1!=1 + label var industrycat10_2 "1 digit industry classification, secondary job 7 day recall" + label values industrycat10_2 lblindustrycat10 +* + + +*<_industrycat4_2_> + gen byte industrycat4_2=industrycat10_2 + recode industrycat4_2 (3/5=2)(6/9=3)(10=4) + label var industrycat4_2 "1 digit industry classification (Broad Economic Activities), secondary job 7 day recall" + label values industrycat4_2 lblindustrycat4 +* + + +*<_occup_orig_2_> + gen occup_orig_2=F2_9group + replace occup_orig_2=. if lstatus!=1|F1!=1 + label var occup_orig_2 "Original occupation record secondary job 7 day recall" +* + + +*<_occup_isco_2_> + gen occup_isco_2="" + replace occup_isco_2="" if lstatus!=1 | occup_isco_2=="."|F1!=1 + label var occup_isco_2 "ISCO code of secondary job 7 day recall" +* + + +*<_occup_skill_2_> + gen occup_skill_2=F2_9group + replace occup_skill_2=1 if F2_9group==9 + replace occup_skill_2=2 if inrange(F2_9group,4,8) + replace occup_skill_2=3 if inrange(F2_9group,1,3) + replace occup_skill_2=. if F2_9group==0|lstatus!=1|F1!=1 + label var occup_skill_2 "Skill based on ISCO standard secondary job 7 day recall" +* + + +*<_occup_2_> + gen occup_2=F2_9group + replace occup_2=. if lstatus!=1|F1!=1 + label var occup_2 "1 digit occupational classification secondary job 7 day recall" + label values occup_2 lbloccup +* + + +*<_wage_no_compen_2_> + +/*<_wage_no_compen_2_note_> + +The questionnaire actually has questions about income of the second job, just as the +main job. However, the data set does not have the variables. + +*<_wage_no_compen_2_note_>*/ + gen wage_no_compen_2=. + replace wage_no_compen_2=. if F1!=1|empstat_2==2 + label var wage_no_compen_2 "Last wage payment secondary job 7 day recall" +* + + +*<_unitwage_2_> + gen byte unitwage_2=. + replace unitwage_2=. if lstatus!=1|F1!=1 + label var unitwage_2 "Last wages' time unit secondary job 7 day recall" + label values unitwage_2 lblunitwage +* + + +*<_whours_2_> + gen whours_2=G2_2 + replace whours_2=. if G2_2==0|F1!=1 + label var whours_2 "Hours of work in last week secondary job 7 day recall" +* + + +*<_wmonths_2_> + gen wmonths_2=. + label var wmonths_2 "Months of work in past 12 months secondary job 7 day recall" +* + + +*<_wage_total_2_> + gen wage_total_2=. + label var wage_total_2 "Annualized total wage secondary job 7 day recall" +* + + +*<_firmsize_l_2_> + gen byte firmsize_l_2=. + label var firmsize_l_2 "Firm size (lower bracket) secondary job 7 day recall" +* + + +*<_firmsize_u_2_> + gen byte firmsize_u_2=. + label var firmsize_u_2 "Firm size (upper bracket) secondary job 7 day recall" +* + +} + +*----------8.4: 7 day reference additional jobs------------------------------* + +*<_t_hours_others_> + gen t_hours_others=. + label var t_hours_others "Annualized hours worked in all but primary and secondary jobs 7 day recall" +* + + +*<_t_wage_nocompen_others_> + gen t_wage_nocompen_others=. + label var t_wage_nocompen_others "Annualized wage in all but primary & secondary jobs excl. bonuses, etc. 7 day recall" +* + + +*<_t_wage_others_> + gen t_wage_others=. + label var t_wage_others "Annualized wage in all but primary and secondary jobs (12-mon ref period)" +* + + +*----------8.5: 7 day reference total summary------------------------------* + + +*<_t_hours_total_> + gen t_hours_total=. + label var t_hours_total "Annualized hours worked in all jobs 7 day recall" +* + + +*<_t_wage_nocompen_total_> + gen t_wage_nocompen_total=. + label var t_wage_nocompen_total "Annualized wage in all jobs excl. bonuses, etc. 7 day recall" +* + + +*<_t_wage_total_> + gen t_wage_total=. + label var t_wage_total "Annualized total wage for all jobs 7 day recall" +* + + +*----------8.6: 12 month reference overall------------------------------* + +{ +*<_lstatus_year_> + gen byte lstatus_year=. + replace lstatus_year=. if !inrange(Age_16groups,4,16) + label var lstatus_year "Labor status during last year" + la de lbllstatus_year 1 "Employed" 2 "Unemployed" 3 "Non-LF" + label values lstatus_year lbllstatus_year +* + + +*<_potential_lf_year_> + gen byte potential_lf_year=. + replace potential_lf_year=. if !inrange(Age_16groups,4,16) + replace potential_lf_year=. if lstatus_year!=3 + label var potential_lf_year "Potential labour force status" + la de lblpotential_lf_year 0 "No" 1 "Yes" + label values potential_lf_year lblpotential_lf_year +* + + +*<_underemployment_year_> + gen byte underemployment_year=. + replace underemployment_year=. if !inrange(Age_16groups,4,16)&age!=. + replace underemployment_year=. if lstatus_year==1 + label var underemployment_year "Underemployment status" + la de lblunderemployment_year 0 "No" 1 "Yes" + label values underemployment_year lblunderemployment_year +* + + +*<_nlfreason_year_> + gen byte nlfreason_year=. + label var nlfreason_year "Reason not in the labor force" + la de lblnlfreason_year 1 "Student" 2 "Housekeeper" 3 "Retired" 4 "Disable" 5 "Other" + label values nlfreason_year lblnlfreason_year +* + + +*<_unempldur_l_year_> + gen byte unempldur_l_year=. + label var unempldur_l_year "Unemployment duration (months) lower bracket" +* + + +*<_unempldur_u_year_> + gen byte unempldur_u_year=. + label var unempldur_u_year "Unemployment duration (months) upper bracket" +* + +} + +*----------8.7: 12 month reference main job------------------------------* + +{ +*<_empstat_year_> + gen byte empstat_year=. + label var empstat_year "Employment status during past week primary job 12 month recall" + la de lblempstat_year 1 "Paid employee" 2 "Non-paid employee" 3 "Employer" 4 "Self-employed" 5 "Other, workers not classifiable by status" + label values empstat_year lblempstat_year +* + + +*<_ocusec_year_> + gen byte ocusec_year=. + label var ocusec_year "Sector of activity primary job 12 day recall" + la de lblocusec_year 1 "Public Sector, Central Government, Army" 2 "Private, NGO" 3 "State owned" 4 "Public or State-owned, but cannot distinguish" + label values ocusec_year lblocusec_year +* + + +*<_industry_orig_year_> + gen industry_orig_year=. + label var industry_orig_year "Original industry record main job 12 month recall" +* + + +*<_industrycat_isic_year_> + gen industrycat_isic_year="" + replace industrycat_isic_year="" if industrycat_isic_year=="." + label var industrycat_isic_year "ISIC code of primary job 12 month recall" +* + + +*<_industrycat10_year_> + gen byte industrycat10_year=. + label var industrycat10_year "1 digit industry classification, primary job 12 month recall" + la de lblindustrycat10_year 1 "Agriculture" 2 "Mining" 3 "Manufacturing" 4 "Public utilities" 5 "Construction" 6 "Commerce" 7 "Transport and Comnunications" 8 "Financial and Business Services" 9 "Public Administration" 10 "Other Services, Unspecified" + label values industrycat10_year lblindustrycat10_year +* + + +*<_industrycat4_year_> + gen byte industrycat4_year=industrycat10_year + recode industrycat4_year (1=1)(2 3 4 5 =2)(6 7 8 9=3)(10=4) + label var industrycat4_year "1 digit industry classification (Broad Economic Activities), primary job 12 month recall" + la de lblindustrycat4_year 1 "Agriculture" 2 "Industry" 3 "Services" 4 "Other" + label values industrycat4_year lblindustrycat4_year +* + + +*<_occup_orig_year_> + gen occup_orig_year=. + label var occup_orig_year "Original occupation record primary job 12 month recall" +* + + +*<_occup_isco_year_> + gen str4 occup_isco_year="" + label var occup_isco_year "ISCO code of primary job 12 month recall" +* + + +*<_occup_skill_year_> + gen skill_level_year=substr(occup_isco_year,1,1) + destring skill_level_year, replace + gen occup_skill_year=. + replace occup_skill_year=1 if skill_level_year==9 + replace occup_skill_year=2 if inrange(skill_level_year,4,8) + replace occup_skill_year=3 if inrange(skill_level_year,1,3) + replace occup_skill_year=. if skill_level_year==0 + label var occup_skill_year "Skill based on ISCO standard primary job 12 month recall" +* + + +*<_occup_year_> + gen byte occup_year=. + label var occup_year "1 digit occupational classification, primary job 12 month recall" + la de lbloccup_year 1 "Managers" 2 "Professionals" 3 "Technicians" 4 "Clerks" 5 "Service and market sales workers" 6 "Skilled agricultural" 7 "Craft workers" 8 "Machine operators" 9 "Elementary occupations" 10 "Armed forces" 99 "Others" + label values occup_year lbloccup_year +* + + +*<_wage_no_compen_year_> + gen double wage_no_compen_year=. + label var wage_no_compen_year "Last wage payment primary job 12 month recall" +* + + +*<_unitwage_year_> + gen byte unitwage_year=. + label var unitwage_year "Last wages' time unit primary job 12 month recall" + la de lblunitwage_year 1 "Daily" 2 "Weekly" 3 "Every two weeks" 4 "Bimonthly" 5 "Monthly" 6 "Trimester" 7 "Biannual" 8 "Annually" 9 "Hourly" 10 "Other" + label values unitwage_year lblunitwage_year +* + + +*<_whours_year_> + gen whours_year=. + label var whours_year "Hours of work in last week primary job 12 month recall" +* + + +*<_wmonths_year_> + gen wmonths_year=. + label var wmonths_year "Months of work in past 12 months primary job 12 month recall" +* + + +*<_wage_total_year_> + gen wage_total_year=. + label var wage_total_year "Annualized total wage primary job 12 month recall" +* + + +*<_contract_year_> + gen byte contract_year=. + label var contract_year "Employment has contract primary job 12 month recall" + la de lblcontract_year 0 "Without contract" 1 "With contract" + label values contract_year lblcontract_year +* + + +*<_healthins_year_> + gen byte healthins_year=. + label var healthins_year "Employment has health insurance primary job 12 month recall" + la de lblhealthins_year 0 "Without health insurance" 1 "With health insurance" + label values healthins_year lblhealthins_year +* + + +*<_socialsec_year_> + gen byte socialsec_year=. + label var socialsec_year "Employment has social security insurance primary job 7 day recall" + la de lblsocialsec_year 1 "With social security" 0 "Without social secturity" + label values socialsec_year lblsocialsec_year +* + + +*<_union_year_> + gen byte union_year=. + label var union_year "Union membership at primary job 12 month recall" + la de lblunion_year 0 "Not union member" 1 "Union member" + label values union_year lblunion_year +* + + +*<_firmsize_l_year_> + gen byte firmsize_l_year=. + label var firmsize_l_year "Firm size (lower bracket) primary job 12 month recall" +* + + +*<_firmsize_u_year_> + gen byte firmsize_u_year=. + label var firmsize_u_year "Firm size (upper bracket) primary job 12 month recall" +* + +} + + +*----------8.8: 12 month reference secondary job------------------------------* + +{ + +*<_empstat_2_year_> + gen byte empstat_2_year=. + label var empstat_2_year "Employment status during past week secondary job 12 month recall" + label values empstat_2_year lblempstat_year +* + + +*<_ocusec_2_year_> + gen byte ocusec_2_year=. + label var ocusec_2_year "Sector of activity secondary job 12 day recall" + la de lblocusec_2_year 1 "Public Sector, Central Government, Army" 2 "Private, NGO" 3 "State owned" 4 "Public or State-owned, but cannot distinguish" + label values ocusec_2_year lblocusec_2_year +* + + + +*<_industry_orig_2_year_> + gen industry_orig_2_year=. + label var industry_orig_2_year "Original survey industry code, secondary job 12 month recall" +* + + + +*<_industrycat_isic_2_year_> + gen industrycat_isic_2_year=. + label var industrycat_isic_2_year "ISIC code of secondary job 12 month recall" +* + + +*<_industrycat10_2_year_> + gen byte industrycat10_2_year=. + label var industrycat10_2_year "1 digit industry classification, secondary job 12 month recall" + label values industrycat10_2_year lblindustrycat10_year +* + + +*<_industrycat4_2_year_> + gen byte industrycat4_2_year=industrycat10_2_year + recode industrycat4_2_year (1=1)(2 3 4 5 =2)(6 7 8 9=3)(10=4) + label var industrycat4_2_year "1 digit industry classification (Broad Economic Activities), secondary job 12 month recall" + label values industrycat4_2_year lblindustrycat4_year +* + + +*<_occup_orig_2_year_> + gen occup_orig_2_year=. + label var occup_orig_2_year "Original occupation record secondary job 12 month recall" +* + + +*<_occup_isco_2_year_> + gen occup_isco_2_year=. + label var occup_isco_2_year "ISCO code of secondary job 12 month recall" +* + + +*<_occup_skill_2_year_> + gen occup_skill_2_year=. + label var occup_skill_2_year "Skill based on ISCO standard secondary job 12 month recall" +* + + +*<_occup_2_year_> + gen byte occup_2_year=. + label var occup_2_year "1 digit occupational classification, secondary job 12 month recall" + label values occup_2_year lbloccup_year +* + + +*<_wage_no_compen_2_year_> + gen double wage_no_compen_2_year=. + label var wage_no_compen_2_year "Last wage payment secondary job 12 month recall" +* + + +*<_unitwage_2_year_> + gen byte unitwage_2_year=. + label var unitwage_2_year "Last wages' time unit secondary job 12 month recall" + label values unitwage_2_year lblunitwage_year +* + + +*<_whours_2_year_> + gen whours_2_year=. + label var whours_2_year "Hours of work in last week secondary job 12 month recall" +* + + +*<_wmonths_2_year_> + gen wmonths_2_year=. + label var wmonths_2_year "Months of work in past 12 months secondary job 12 month recall" +* + + +*<_wage_total_2_year_> + gen wage_total_2_year=. + label var wage_total_2_year "Annualized total wage secondary job 12 month recall" +* + + +*<_firmsize_l_2_year_> + gen byte firmsize_l_2_year=. + label var firmsize_l_2_year "Firm size (lower bracket) secondary job 12 month recall" +* + + +*<_firmsize_u_2_year_> + gen byte firmsize_u_2_year=. + label var firmsize_u_2_year "Firm size (upper bracket) secondary job 12 month recall" +* + +} + + +*----------8.9: 12 month reference additional jobs------------------------------* + + +*<_t_hours_others_year_> + gen t_hours_others_year=. + label var t_hours_others_year "Annualized hours worked in all but primary and secondary jobs 12 month recall" +* + + +*<_t_wage_nocompen_others_year_> + gen t_wage_nocompen_others_year=. + label var t_wage_nocompen_others_year "Annualized wage in all but primary & secondary jobs excl. bonuses, etc. 12 month recall)" +* + + +*<_t_wage_others_year_> + gen t_wage_others_year=. + label var t_wage_others_year "Annualized wage in all but primary and secondary jobs 12 month recall" +* + + +*----------8.10: 12 month total summary------------------------------* + + +*<_t_hours_total_year_> + gen t_hours_total_year=. + label var t_hours_total_year "Annualized hours worked in all jobs 12 month month recall" +* + + +*<_t_wage_nocompen_total_year_> + gen t_wage_nocompen_total_year=. + label var t_wage_nocompen_total_year "Annualized wage in all jobs excl. bonuses, etc. 12 month recall" +* + + +*<_t_wage_total_year_> + gen t_wage_total_year=. + label var t_wage_total_year "Annualized total wage for all jobs 12 month recall" +* + + +*----------8.11: Overall across reference periods------------------------------* + + +*<_njobs_> + gen njobs=. + replace njobs=1 if lstatus==1&F1!=1 + replace njobs=2 if lstatus==1&F1==1 + replace njobs=. if lstatus!=1 + label var njobs "Total number of jobs" +* + + +*<_t_hours_annual_> + gen t_hours_annual=. + label var t_hours_annual "Total hours worked in all jobs in the previous 12 months" +* + + +*<_linc_nc_> + gen linc_nc=. + label var linc_nc "Total annual wage income in all jobs, excl. bonuses, etc." +* + + +*<_laborincome_> + gen laborincome=. + label var laborincome "Total annual individual labor income in all jobs, incl. bonuses, etc." +* + + +*----------8.13: Labour cleanup------------------------------* + +{ +*<_% Correction min age_> + +** Drop info for cases under the age for which questions to be asked (do not need a variable for this) + local lab_var "minlaborage lstatus nlfreason unempldur_l unempldur_u empstat ocusec industry_orig industrycat_isic industrycat10 industrycat4 occup_orig occup_isco occup_skill occup wage_no_compen unitwage whours wmonths wage_total contract healthins socialsec union firmsize_l firmsize_u empstat_2 ocusec_2 industry_orig_2 industrycat_isic_2 industrycat10_2 industrycat4_2 occup_orig_2 occup_isco_2 occup_skill_2 occup_2 wage_no_compen_2 unitwage_2 whours_2 wmonths_2 wage_total_2 firmsize_l_2 firmsize_u_2 t_hours_others t_wage_nocompen_others t_wage_others t_hours_total t_wage_nocompen_total t_wage_total lstatus_year nlfreason_year unempldur_l_year unempldur_u_year empstat_year ocusec_year industry_orig_year industrycat_isic_year industrycat10_year industrycat4_year occup_orig_year occup_isco_year occup_skill_year occup_year unitwage_year whours_year wmonths_year wage_total_year contract_year healthins_year socialsec_year union_year firmsize_l_year firmsize_u_year empstat_2_year ocusec_2_year industry_orig_2_year industrycat_isic_2_year industrycat10_2_year industrycat4_2_year occup_orig_2_year occup_isco_2_year occup_skill_2_year occup_2_year wage_no_compen_2_year unitwage_2_year whours_2_year wmonths_2_year wage_total_2_year firmsize_l_2_year firmsize_u_2_year t_hours_others_year t_wage_nocompen_others_year t_wage_others_year t_hours_total_year t_wage_nocompen_total_year t_wage_total_year njobs t_hours_annual linc_nc laborincome" + + foreach v of local lab_var { + cap confirm numeric variable `v' + if _rc == 0 { // is indeed numeric + replace `v'=. if ( age < minlaborage & !missing(age) ) + } + else { // is not + replace `v'= "" if ( age < minlaborage & !missing(age) ) + } + + } + +* +} + + +/*%%============================================================================================= + 9: Final steps +==============================================================================================%%*/ + +quietly{ + +*<_% KEEP VARIABLES - ALL_> + + keep countrycode survname survey icls_v isced_version isco_version isic_version year vermast veralt harmonization int_year int_month hhid pid weight weight_m weight_q psu strata wave panel visit_no urban subnatid1 subnatid2 subnatid3 subnatidsurvey subnatid1_prev subnatid2_prev subnatid3_prev gaul_adm1_code gaul_adm2_code gaul_adm3_code hsize age male relationharm relationcs marital eye_dsablty hear_dsablty walk_dsablty conc_dsord slfcre_dsablty comm_dsablty migrated_mod_age migrated_ref_time migrated_binary migrated_years migrated_from_urban migrated_from_cat migrated_from_code migrated_from_country migrated_reason ed_mod_age school literacy educy educat7 educat5 educat4 educat_orig educat_isced vocational vocational_type vocational_length_l vocational_length_u vocational_field_orig vocational_financed minlaborage lstatus potential_lf underemployment nlfreason unempldur_l unempldur_u empstat ocusec industry_orig industrycat_isic industrycat10 industrycat4 occup_orig occup_isco occup_skill occup wage_no_compen unitwage whours wmonths wage_total contract healthins socialsec union firmsize_l firmsize_u empstat_2 ocusec_2 industry_orig_2 industrycat_isic_2 industrycat10_2 industrycat4_2 occup_orig_2 occup_isco_2 occup_skill_2 occup_2 wage_no_compen_2 unitwage_2 whours_2 wmonths_2 wage_total_2 firmsize_l_2 firmsize_u_2 t_hours_others t_wage_nocompen_others t_wage_others t_hours_total t_wage_nocompen_total t_wage_total lstatus_year potential_lf_year underemployment_year nlfreason_year unempldur_l_year unempldur_u_year empstat_year ocusec_year industry_orig_year industrycat_isic_year industrycat10_year industrycat4_year occup_orig_year occup_isco_year occup_skill_year occup_year wage_no_compen_year unitwage_year whours_year wmonths_year wage_total_year contract_year healthins_year socialsec_year union_year firmsize_l_year firmsize_u_year empstat_2_year ocusec_2_year industry_orig_2_year industrycat_isic_2_year industrycat10_2_year industrycat4_2_year occup_orig_2_year occup_isco_2_year occup_skill_2_year occup_2_year wage_no_compen_2_year unitwage_2_year whours_2_year wmonths_2_year wage_total_2_year firmsize_l_2_year firmsize_u_2_year t_hours_others_year t_wage_nocompen_others_year t_wage_others_year t_hours_total_year t_wage_nocompen_total_year t_wage_total_year njobs t_hours_annual linc_nc laborincome + +* + +*<_% ORDER VARIABLES_> + + order countrycode survname survey icls_v isced_version isco_version isic_version year vermast veralt harmonization int_year int_month hhid pid weight weight_m weight_q psu strata wave panel visit_no urban subnatid1 subnatid2 subnatid3 subnatidsurvey subnatid1_prev subnatid2_prev subnatid3_prev gaul_adm1_code gaul_adm2_code gaul_adm3_code hsize age male relationharm relationcs marital eye_dsablty hear_dsablty walk_dsablty conc_dsord slfcre_dsablty comm_dsablty migrated_mod_age migrated_ref_time migrated_binary migrated_years migrated_from_urban migrated_from_cat migrated_from_code migrated_from_country migrated_reason ed_mod_age school literacy educy educat7 educat5 educat4 educat_orig educat_isced vocational vocational_type vocational_length_l vocational_length_u vocational_field_orig vocational_financed minlaborage lstatus potential_lf underemployment nlfreason unempldur_l unempldur_u empstat ocusec industry_orig industrycat_isic industrycat10 industrycat4 occup_orig occup_isco occup_skill occup wage_no_compen unitwage whours wmonths wage_total contract healthins socialsec union firmsize_l firmsize_u empstat_2 ocusec_2 industry_orig_2 industrycat_isic_2 industrycat10_2 industrycat4_2 occup_orig_2 occup_isco_2 occup_skill_2 occup_2 wage_no_compen_2 unitwage_2 whours_2 wmonths_2 wage_total_2 firmsize_l_2 firmsize_u_2 t_hours_others t_wage_nocompen_others t_wage_others t_hours_total t_wage_nocompen_total t_wage_total lstatus_year potential_lf_year underemployment_year nlfreason_year unempldur_l_year unempldur_u_year empstat_year ocusec_year industry_orig_year industrycat_isic_year industrycat10_year industrycat4_year occup_orig_year occup_isco_year occup_skill_year occup_year wage_no_compen_year unitwage_year whours_year wmonths_year wage_total_year contract_year healthins_year socialsec_year union_year firmsize_l_year firmsize_u_year empstat_2_year ocusec_2_year industry_orig_2_year industrycat_isic_2_year industrycat10_2_year industrycat4_2_year occup_orig_2_year occup_isco_2_year occup_skill_2_year occup_2_year wage_no_compen_2_year unitwage_2_year whours_2_year wmonths_2_year wage_total_2_year firmsize_l_2_year firmsize_u_2_year t_hours_others_year t_wage_nocompen_others_year t_wage_others_year t_hours_total_year t_wage_nocompen_total_year t_wage_total_year njobs t_hours_annual linc_nc laborincome + +* + +*<_% DROP UNUSED LABELS_> + + * Store all labels in data + label dir + local all_lab `r(names)' + + * Store all variables with a label, extract value label names + local used_lab = "" + ds, has(vallabel) + + local labelled_vars `r(varlist)' + + foreach varName of local labelled_vars { + local y : value label `varName' + local used_lab `"`used_lab' `y'"' + } + + * Compare lists, `notused' is list of labels in directory but not used in final variables + local notused : list all_lab - used_lab // local `notused' defines value labs not in remaining vars + local notused_len : list sizeof notused // store size of local + + * drop labels if the length of the notused vector is 1 or greater, otherwise nothing to drop + if `notused_len' >= 1 { + label drop `notused' + } + else { + di "There are no unused labels to drop. No value labels dropped." + } + + +* + +} + +*<_% DELETE MISSING VARIABLES_> + +quietly: describe, varlist +local kept_vars `r(varlist)' + +foreach var of local kept_vars { + + capture assert missing(`var') + if !_rc drop `var' +} + +* + + +*<_% COMPRESS_> + +compress + +* + + +*<_% SAVE_> + +save "`path_output'/`level_2_harm'_ALL.dta", replace + +* diff --git a/GLD/ARM/ARM_2022_LFS/ARM_2022_LFS_V01_M_V03_A_GLD/Programs/ARM_2022_LFS_V01_M_V03_A_GLD_ALL.do b/GLD/ARM/ARM_2022_LFS/ARM_2022_LFS_V01_M_V03_A_GLD/Programs/ARM_2022_LFS_V01_M_V03_A_GLD_ALL.do new file mode 100644 index 000000000..07afae473 --- /dev/null +++ b/GLD/ARM/ARM_2022_LFS/ARM_2022_LFS_V01_M_V03_A_GLD/Programs/ARM_2022_LFS_V01_M_V03_A_GLD_ALL.do @@ -0,0 +1,1794 @@ + +/*%%============================================================================================= + 0: GLD Harmonization Preamble +================================================================================================*/ + +/* ----------------------------------------------------------------------- +<_Program name_> ARM_2022_LFS_V01_M_V03_A_GLD_ALL.do +<_Application_> Stata SE 18 <_Application_> +<_Author(s)_> Wolrd Bank Job's Group +<_Date created_> 2024-1-16 +------------------------------------------------------------------------- +<_Country_> Armenia (ARM) +<_Survey Title_> National Labour Force Survey +<_Survey Year_> 2022 +<_Study ID_> ARM_2022_LFS_v01_M +<_Data collection from (M/Y)_> [01/2022] +<_Data collection to (M/Y)_> [12/2022] +<_Source of dataset_> The Armenian 2022 to 2022 data is downloaded from + the website of Statistical Committee of the + Republic of Armenia:https://armstat.am/en/?nid=212 + The data is publicly available. +<_Sample size (HH)_> 7,760 +<_Sample size (IND)_> 27,218 +<_Sampling method_> A stratified two-stage probability sample design + with 14 domains as the primary strata and 18,000 + households as the SSU. +<_Geographic coverage_> All 11 regions/marzes. +<_Currency_> Armenian Dram +----------------------------------------------------------------------- +<_ICLS Version_> ICLS 19 +<_ISCED Version_> ISCED-2011 +<_ISCO Version_> ISCO 08 +<_OCCUP National_> NSCO +<_ISIC Version_> ISIC Rev.4 +<_INDUS National_> ISIC Rev.4 +----------------------------------------------------------------------- + +<_Version Control_> + +* Date: 2024-09-24 - Update vars educy, educat7, educat_isced +* Date: 2024-10-10 - Include weight by quarter, old weight variable, correct contract variable, drop migration + + + +-------------------------------------------------------------------------*/ + + +/*%%============================================================================================= + 1: Setting up of program environment, dataset +================================================================================================*/ + +*----------1.1: Initial commands------------------------------* + +clear +set more off +set mem 800m + +*----------1.2: Set directories------------------------------* + +* Define path sections +local server "Y:/GLD" +local country "ARM" +local year "2022" +local survey "LFS" +local vermast "V01" +local veralt "V03" + +* From the definitions, set path chunks +local level_1 "`country'_`year'_`survey'" +local level_2_mast "`level_1'_`vermast'_M" +local level_2_harm "`level_1'_`vermast'_M_`veralt'_A_GLD" + +* From chunks, define path_in, path_output folder +local path_in_stata "`server'/`country'/`level_1'/`level_2_mast'/Data/Stata" +local path_in_other "`server'/`country'/`level_1'/`level_2_mast'/Data/Original" +local path_output "`server'/`country'/`level_1'/`level_2_harm'/Data/Harmonized" + +* Define Output file name +local out_file "`level_2_harm'_ALL.dta" + + +*----------1.3: Database assembly------------------------------* + +* All steps necessary to merge datasets (if several) to have all elements needed to produce +* harmonized output in a single file + +use "`path_in_stata'/ARM_LFS_2022_raw.dta", clear +rename (_v1 _v2) (E4_21group F3_21group) + +/*%%============================================================================================= + 2: Survey & ID +================================================================================================*/ + +{ + +*<_countrycode_> + gen str4 countrycode="`country'" + label var countrycode "Country code" +* + + +*<_survname_> + gen survname="LFS" + label var survname "Survey acronym" +* + + +*<_survey_> + gen survey="LFS" + label var survey "Survey type" +* + + +*<_icls_v_> + gen icls_v="ICLS-19" + label var icls_v "ICLS version underlying questionnaire questions" +* + + +*<_isced_version_> + gen isced_version="isced_2011" + label var isced_version "Version of ISCED used for educat_isced" +* + + +*<_isco_version_> + gen isco_version="" + label var isco_version "Version of ISCO used" +* + + +*<_isic_version_> + gen isic_version="" + label var isic_version "Version of ISIC used" +* + + +*<_year_> + gen int year=`year' + label var year "Year of survey" +* + + +*<_vermast_> + gen str3 vermast="`vermast'" + label var vermast "Version of master data" +* + + +*<_veralt_> + gen str3 veralt="`veralt'" + label var veralt "Version of the alt/harmonized data" +* + + +*<_harmonization_> + gen harmonization="GLD" + label var harmonization "Type of harmonization" +* + + +*<_int_year_> + gen int_year=`year' + label var int_year "Year of the interview" +* + + +*<_int_month_> + gen int_month=A6_Month + label de lblint_month 1 "January" 2 "February" 3 "March" 4 "April" 5 "May" 6 "June" 7 "July" 8 "August" 9 "September" 10 "October" 11 "November" 12 "December" + label value int_month lblint_month + label var int_month "Month of the interview" +* + + +*<_hhid_> + tostring A1, gen(hid) format(%03.0f) + tostring A6_Month, gen(month) format(%03.0f) + egen hhid=concat(month hid) + label var hhid "Household id" +* + + +*<_pid_> + sort hhid B4 + bys hhid: gen memberid=_n + tostring memberid, gen(id_str) format(%02.0f) + egen pid=concat(hhid id_str), punct("-") + label var pid "Individual ID" +* + + +*<_weight_> + gen weight = WeightsCalib_year + label var weight "Household sampling weight" +* + + +*<_weight_m_> + gen weight_m = . + label var weight_m "Survey sampling weight to obtain national estimates for each month" +* + + +*<_weight_q_> + egen weight_q = rowtotal(WeightsCalib_1 WeightsCalib_2 WeightsCalib_3 WeightsCalib_4) + label var weight_q "Survey sampling weight to obtain national estimates for each quarter" +* + + +*<_psu_> + gen psu=. + label var psu "Primary sampling units" +* + + +*<_ssu_> + gen ssu=hhid + label var ssu "Secondary sampling units" +* + + +*<_strata_> + decode A3, gen(marzname) + decode A5, gen(urbanstat) + gen strata=marzname+" "+urbanstat + label var strata "Strata" +* + + +*<_wave_> + gen wave=. + replace wave=1 if inrange(int_month,1,3) + replace wave=2 if inrange(int_month,4,6) + replace wave=3 if inrange(int_month,7,9) + replace wave=4 if inrange(int_month,10,12) + label var wave "Survey wave" +* + + +*<_panel_> + gen panel="" + label var panel "Panel individual belongs to" +* + + +*<_visit_no_> + gen visit_no=. + label var visit_no "Visit number in panel" +* +} + +/*%%============================================================================================= + 3: Geography +================================================================================================*/ + +{ + +*<_urban_> + gen urban=A5 + recode urban (2=0) + la de lblurban 1 "Urban" 0 "Rural" + label values urban lblurban + label var urban "Location is urban" +* + + +*<_subnatid1_> + gen subnatid1=A3 + tostring subnatid1, replace + replace subnatid1=subnatid1+" - "+marzname + label var subnatid1 "Subnational ID at First Administrative Level" +* + + +*<_subnatid2_> + gen subnatid2=. + label var subnatid2 "Subnational ID at Second Administrative Level" +* + + +*<_subnatid3_> + gen subnatid3=. + label var subnatid3 "Subnational ID at Third Administrative Level" +* + + +*<_subnatidsurvey_> + gen subnatidsurvey=subnatid1+" "+urbanstat + label var subnatidsurvey "Administrative level at which survey is representative" +* + + +*<_subnatid1_prev_> + +/* <_subnatid1_prev_note_> +subnatid1_prev is coded as missing unless the classification used for subnatid1 has changed since the previous survey. + */ + + gen subnatid1_prev=. + label var subnatid1_prev "Classification used for subnatid1 from previous survey" +* + + +*<_subnatid2_prev_> + gen subnatid2_prev=. + label var subnatid2_prev "Classification used for subnatid2 from previous survey" +* + + +*<_subnatid3_prev_> + gen subnatid3_prev=. + label var subnatid3_prev "Classification used for subnatid3 from previous survey" +* + + +*<_gaul_adm1_code_> + gen gaul_adm1_code=. + label var gaul_adm1_code "Global Administrative Unit Layers (GAUL) Admin 1 code" +* + + +*<_gaul_adm2_code_> + gen gaul_adm2_code=. + label var gaul_adm2_code "Global Administrative Unit Layers (GAUL) Admin 2 code" +* + + +*<_gaul_adm3_code_> + gen gaul_adm3_code=. + label var gaul_adm3_code "Global Administrative Unit Layers (GAUL) Admin 3 code" +* + +} + +/*%%============================================================================================= + 4: Demography +================================================================================================*/ + +{ + +*<_hsize_> + bys hhid: egen hsize=max(memberid) + label var hsize "Household size" +* + + +*<_age_> + +/*<_age_note_> + +Because the raw data in 2021 and 2022 do not have each observation's actual age, +and instead, they only have age in age groups. Here we coded age using the mean of +each age group to proceed with other variables and our quality checks. Therefore, +the age variable only represents the age group the observation is in. + +*<_age_note_>*/ + + gen age=. + replace age=(Age_16groups-1)*5+2 + replace age=98 if age>98 & age!=. + label var age "Individual age" +* + + +*<_male_> + gen male=B3 + recode male 2=0 + label var male "Sex - Ind is male" + la de lblmale 1 "Male" 0 "Female" + label values male lblmale +* + + +*<_relationharm_> + +/*<_relationharm_note_> + +11 households (27 observations) in the raw data set do not have household heads. +Their household IDs are: + +002302 003209 004284 004374 005174 +006051 006649 011184 011479 011481 +012402 + +During the harmonization, we did not assign household heads to these households. +But users can assign household heads based on their relationship to the head and +other characteristics such as gender and age. + +*<_relationharm_note_>*/ + + gen byte relationharm=B4 + recode relationharm (6 9=3) (7 8=4) (10=5) (11=6) + label var relationharm "Relationship to the head of household - Harmonized" + la de lblrelationharm 1 "Head of household" 2 "Spouse" 3 "Children" 4 "Parents" 5 "Other relatives" 6 "Other and non-relatives" + label values relationharm lblrelationharm +*<_relationharm_> + + +*<_relationcs_> + gen relationcs=B4 + label var relationcs "Relationship to the head of household - Country original" +* + + +*<_marital_> + gen marital=B11 + recode marital (1=2) (2=1) (3=5) + label var marital "Marital status" + la de lblmarital 1 "Married" 2 "Never Married" 3 "Living together" 4 "Divorced/Separated" 5 "Widowed" + label values marital lblmarital +* + + +*<_eye_dsablty_> + gen eye_dsablty=. + la de lbleye_dsablty 1 "No" 2 "Yes-some" 3 "Yes-a lot" 4 "Cannot at all" + label values eye_dsablty lbleye_dsablty + label var eye_dsablty "Disability related to eyesight" +* + + +*<_hear_dsablty_> + gen hear_dsablty=. + la de lblhear_dsablty 1 "No" 2 "Yes-some" 3 "Yes-a lot" 4 "Cannot at all" + label values hear_dsablty lblhear_dsablty + label var hear_dsablty "Disability related to hearing" +* + + +*<_walk_dsablty_> + gen walk_dsablty=. + la de lblwalk_dsablty 1 "No" 2 "Yes-some" 3 "Yes-a lot" 4 "Cannot at all" + label values walk_dsablty lblwalk_dsablty + label var walk_dsablty "Disability related to walking or climbing stairs" +* + + +*<_conc_dsord_> + gen conc_dsord=. + la de lblconc_dsord 1 "No" 2 "Yes-some" 3 "Yes-a lot" 4 "Cannot at all" + label values conc_dsord lblconc_dsord + label var conc_dsord "Disability related to concentration or remembering" +* + + +*<_slfcre_dsablty_> + gen slfcre_dsablty=. + la de lblslfcre_dsablty 1 "No" 2 "Yes-some" 3 "Yes-a lot" 4 "Cannot at all" + label values slfcre_dsablty lblslfcre_dsablty + label var eye_dsablty "Disability related to selfcare" +* + + +*<_comm_dsablty_> + gen comm_dsablty=. + la de lblcomm_dsablty 1 "No" 2 "Yes-some" 3 "Yes-a lot" 4 "Cannot at all" + label values comm_dsablty lblcomm_dsablty + label var eye_dsablty "Disability related to communicating" +* + +} + + +/*%%============================================================================================= + 5: Migration +==============================================================================================%%*/ + + +{ + +*<_migrated_mod_age_> + gen migrated_mod_age = . + label var migrated_mod_age "Migration module application age" +* + + +*<_migrated_ref_time_> + gen migrated_ref_time = . + label var migrated_ref_time "Reference time applied to migration questions (in years)" +* + + +*<_migrated_binary_> + gen migrated_binary = . + label de lblmigrated_binary 0 "No" 1 "Yes" + label values migrated_binary lblmigrated_binary + label var migrated_binary "Individual has migrated" +* + + +*<_migrated_years_> + gen migrated_years = . + label var migrated_years "Years since latest migration" +* + + +*<_migrated_from_urban_> + gen migrated_from_urban = . + label de lblmigrated_from_urban 0 "Rural" 1 "Urban" + label values migrated_from_urban lblmigrated_from_urban + label var migrated_from_urban "Migrated from area" +* + + +*<_migrated_from_cat_> + gen migrated_from_cat = . + label de lblmigrated_from_cat 1 "From same admin3 area" 2 "From same admin2 area" 3 "From same admin1 area" 4 "From other admin1 area" 5 "From other country" + label values migrated_from_cat lblmigrated_from_cat + label var migrated_from_cat "Category of migration area" +* + + +*<_migrated_from_code_> + gen migrated_from_code = . + *label de lblmigrated_from_code + *label values migrated_from_code lblmigrated_from_code + label var migrated_from_code "Code of migration area as subnatid level of migrated_from_cat" +* + + +*<_migrated_from_country_> + gen migrated_from_country = . + label var migrated_from_country "Code of migration country (ISO 3 Letter Code)" +* + + +*<_migrated_reason_> + gen migrated_reason = . + label de lblmigrated_reason 1 "Family reasons" 2 "Educational reasons" 3 "Employment" 4 "Forced (political reasons, natural disaster, …)" 5 "Other reasons" + label values migrated_reason lblmigrated_reason + label var migrated_reason "Reason for migrating" +* + +} + + +/*%%============================================================================================= + 6: Education +================================================================================================*/ + + +{ +*<_ed_mod_age_> + gen byte ed_mod_age=6 + label var ed_mod_age "Education module application age" +* + + +*<_school_> + gen school=B9 + recode school (2=0) (3/5=.) + replace school=. if !inrange(Age_16groups,2,16) + label var school "Attending school" + la de lblschool 0 "No" 1 "Yes" + label values school lblschool +* + + +*<_literacy_> + gen byte literacy=. + replace literacy=0 if B7==1 + replace literacy=1 if inrange(B7,2,11) + replace literacy=. if !inrange(Age_16groups,2,16) + label var literacy "Individual can read & write" + la de lblliteracy 0 "No" 1 "Yes" + label values literacy lblliteracy +* + + +*<_educy_> + gen byte educy=. + replace educy = 0 if B7 == 1 | B7 == 2 + replace educy = 4 if B7 == 3 + replace educy = 9 if B7 == 4 + replace educy = 12 if B7 == 5 + replace educy = 11 if B7 == 6 + replace educy = 15 if B7 == 7 + replace educy = 16 if B7 == 8 + replace educy = 18 if B7 == 9 | B7 == 10 + replace educy = 20 if B7 == 11 + replace educy=. if ageage & !mi(educy) & !mi(age) + label var educy "Years of education" +* + + +*<_educat7_> + gen byte educat7= B7 + recode educat7 (6=5) (7=6) (8/11=7) + replace educat7=. if age + + +*<_educat5_> + gen byte educat5=educat7 + recode educat5 (4=3) (5=4) (6 7=5) + replace educat5=. if !inrange(Age_16groups,2,16) + label var educat5 "Level of education 2" + la de lbleducat5 1 "No education" 2 "Primary incomplete" 3 "Primary complete but secondary incomplete" 4 "Secondary complete" 5 "Some tertiary/post-secondary" + label values educat5 lbleducat5 +* + + +*<_educat4_> + gen byte educat4=educat5 + replace educat4=. if !inrange(Age_16groups,2,16) + recode educat4 (3=2) (4=3) (5=4) + label var educat4 "Level of education 3" + la de lbleducat4 1 "No education" 2 "Primary" 3 "Secondary" 4 "Post-secondary" + label values educat4 lbleducat4 +* + + +*<_educat_orig_> + gen educat_orig=B7 + label var educat_orig "Original survey education code" +* + + +*<_educat_isced_> + gen educat_isced=. + label var educat_isced "ISCED standardised level of education" +* + + +*<_educat_isced_v_> + gen educat_isced_v="ISCED-2011" + label var educat_isced_v "Version of the ISCED used" +* + +*----------6.1: Education cleanup------------------------------* + +*<_% Correction min age_> + +** Drop info for cases under the age for which questions to be asked (do not need a variable for this) +local ed_var school literacy educy educat7 educat5 educat4 educat_isced +foreach v of local ed_var { + replace `v'=. if ( age < ed_mod_age & !missing(age) ) +} +replace educat_isced_v="." if ( age < ed_mod_age & !missing(age) ) +* + +} + +/*%%============================================================================================= + 7: Training +================================================================================================*/ + +{ + +*<_vocational_> + gen vocational=. + la de vocationallbl 1 "Yes" 0 "No" + la values vocational vocationallbl + label var vocational "Ever received vocational training" +* + + +*<_vocational_type_> + gen vocational_type=. + label de lblvocational_type 1 "Inside Enterprise" 2 "External" + label values vocational_type lblvocational_type + label var vocational_type "Type of vocational training" +* + + +*<_vocational_length_l_> + gen vocational_length_l=. + replace vocational_length_l=. if vocational!=1 + label var vocational_length_l "Length of training in months, lower limit" +* + + +*<_vocational_length_u_> + gen vocational_length_u=. + replace vocational_length_u=. if vocational!=1 + label var vocational_length_u "Length of training in months, upper limit" +* + + +*<_vocational_field_orig_> + gen vocational_field_orig=. + replace vocational_field_orig=. if vocational!=1 + label var vocational_field_orig "Original field of training information" +* + + +*<_vocational_financed_> + gen vocational_financed=. + label de lblvocational_financed 1 "Employer" 2 "Government" 3 "Mixed Employer/Government" 4 "Own funds" 5 "Other" + label var vocational_financed "How training was financed" +* + +} + +/*%%============================================================================================= + 8: Labour +================================================================================================*/ + +*<_minlaborage_> + +/*<_minlaborage_note_> + +The age range for the labor section is 15-75. + +*<_minlaborage_note_>*/ + + gen byte minlaborage=15 + label var minlaborage "Labor module application age" +* + + +*----------8.1: 7 day reference overall------------------------------* + +{ +*<_lstatus_> + +/*<_lstatus_note> + +The economically inavtive population also needs to be within the age range of +15 and 75. + +*<_lstatus_note>*/ + + gen byte lstatus=. + replace lstatus=1 if D1==1|inrange(D3,1,5)|D4==1|D5==1 + replace lstatus=2 if lstatus==.&inrange(J9,1,3) + replace lstatus=3 if !mi(J1_4group)&lstatus==. + replace lstatus=. if !inrange(Age_16groups,4,16) + label var lstatus "Labor status" + la de lbllstatus 1 "Employed" 2 "Unemployed" 3 "Non-LF" + label values lstatus lbllstatus +* + + +*<_potential_lf_> + +/*<_potential_lf_note_> +Note: var "potential_lf" only takes value if the respondent is not in labor force. (lstatus==3) + +"potential_lf"=1 if the person is +1)available but not searching or (J16==1)&J9==4 +2)searching but not immediately available to work or inrange(J9,1,3)&J16==2 + +*/ + + gen potential_lf=. + replace potential_lf=1 if [(J16==1)&J9==4] | [inrange(J9,1,3)&J16==2] + replace potential_lf=0 if [(J16==1)&inrange(J9,1,3)] | [inrange(J9,1,3)&J16==1] + replace potential_lf=. if !inrange(Age_16groups,4,16) + replace potential_lf=. if lstatus!=3 + label var potential_lf "Potential labour force status" + la de lblpotential_lf 0 "No" 1 "Yes" + label values potential_lf lblpotential_lf +* + + +*<_underemployment_> + gen byte underemployment=G4 + replace underemployment=1 if inrange(G4,1,3) + replace underemployment=0 if G4==4 + replace underemployment=. if !inrange(Age_16groups,4,16) + replace underemployment=. if lstatus!=1 + label var underemployment "Underemployment status" + la de lblunderemployment 0 "No" 1 "Yes" + label values underemployment lblunderemployment +* + + +*<_nlfreason_> + gen byte nlfreason=J1_4group + recode nlfreason (4=5) + replace nlfreason=. if !inrange(Age_16groups,4,16) + replace nlfreason=. if lstatus!=3 + label var nlfreason "Reason not in the labor force" + la de lblnlfreason 1 "Student" 2 "Housekeeper" 3 "Retired" 4 "Disabled" 5 "Other" + label values nlfreason lblnlfreason +* + + +*<_unempldur_l_> + gen byte unempldur_l=J4 + recode unempldur_l (1=0) (2=3) (3=6) (4=9) (5=12) (6=24) (7=36) + replace unempldur_l=. if !inrange(Age_16groups,4,16) + replace unempldur_l=. if lstatus!=2 + label var unempldur_l "Unemployment duration (months) lower bracket" +* + + +*<_unempldur_u_> + gen byte unempldur_u=J4 + recode unempldur_u (1=3) (2=6) (3=9) (4=12) (5=24) (6=36) (7=.) + replace unempldur_u=. if !inrange(Age_16groups,4,16) + replace unempldur_u=. if lstatus!=2 + label var unempldur_u "Unemployment duration (months) upper bracket" +* +} + + +*----------8.2: 7 day reference main job------------------------------* + + +{ +*<_empstat_> + gen byte empstat=E7 + recode empstat (2 6=1) (5=2) + replace empstat=. if lstatus!=1|!inrange(Age_16groups,4,16) + label var empstat "Employment status during past week primary job 7 day recall" + la de lblempstat 1 "Paid employee" 2 "Non-paid employee" 3 "Employer" 4 "Self-employed" 5 "Other, workers not classifiable by status" + label values empstat lblempstat +* + + +*<_ocusec_> + gen byte ocusec=E10 + recode ocusec (3 4=2) + replace ocusec=. if lstatus!=1|!inrange(Age_16groups,4,16) + label var ocusec "Sector of activity primary job 7 day recall" + la de lblocusec 1 "Public Sector, Central Government, Army" 2 "Private, NGO" 3 "State owned" 4 "Public or State-owned, but cannot distinguish" + label values ocusec lblocusec +* + + +*<_industry_orig_> + gen industry_orig=E4_21group + replace industry_orig=. if lstatus!=1 + label var industry_orig "Original survey industry code, main job 7 day recall" +* + + +*<_industrycat_isic_> + gen industrycat_isic="" +quietly +{ + replace industrycat_isic="A" if E4_21group==1 + replace industrycat_isic="B" if E4_21group==2 + replace industrycat_isic="C" if E4_21group==3 + replace industrycat_isic="D" if E4_21group==4 + replace industrycat_isic="E" if E4_21group==5 + replace industrycat_isic="F" if E4_21group==6 + replace industrycat_isic="G" if E4_21group==7 + replace industrycat_isic="H" if E4_21group==8 + replace industrycat_isic="I" if E4_21group==9 + replace industrycat_isic="J" if E4_21group==10 + replace industrycat_isic="K" if E4_21group==11 + replace industrycat_isic="L" if E4_21group==12 + replace industrycat_isic="M" if E4_21group==13 + replace industrycat_isic="N" if E4_21group==14 + replace industrycat_isic="O" if E4_21group==15 + replace industrycat_isic="P" if E4_21group==16 + replace industrycat_isic="Q" if E4_21group==17 + replace industrycat_isic="R" if E4_21group==18 + replace industrycat_isic="S" if E4_21group==19 + replace industrycat_isic="T" if E4_21group==20 + replace industrycat_isic="U" if E4_21group==21 +} + + replace industrycat_isic="" if industrycat_isic=="."|lstatus!=1 + label var industrycat_isic "ISIC code of primary job 7 day recall" +* + + +*<_industrycat10_> + gen industrycat10=E4_21group + recode industrycat10 (5=4) (6=5) (7 9=6) (8 10=7) (11/14=8) (15=9) (16/21=10) + replace industrycat10=. if lstatus!=1 + label var industrycat10 "1 digit industry classification, primary job 7 day recall" + la de lblindustrycat10 1 "Agriculture" 2 "Mining" 3 "Manufacturing" 4 "Public utilities" 5 "Construction" 6 "Commerce" 7 "Transport and Comnunications" 8 "Financial and Business Services" 9 "Public Administration" 10 "Other Services, Unspecified" + label values industrycat10 lblindustrycat10 +* + + +*<_industrycat4_> + gen byte industrycat4=industrycat10 + recode industrycat4 (3/5=2)(6/9=3)(10=4) + label var industrycat4 "1 digit industry classification (Broad Economic Activities), primary job 7 day recall" + la de lblindustrycat4 1 "Agriculture" 2 "Industry" 3 "Services" 4 "Other" + label values industrycat4 lblindustrycat4 +* + + +*<_occup_orig_> + gen occup_orig=E2_9group + replace occup_orig=. if lstatus!=1|!inrange(Age_16groups,4,16) + label var occup_orig "Original occupation record primary job 7 day recall" +* + + +*<_occup_isco_> + gen occup_isco="" + replace occup_isco="" if lstatus!=1 | occup_isco=="." + label var occup_isco "ISCO code of primary job 7 day recall" +* + + +*<_occup_skill_> + gen occup_skill=E2_9group + replace occup_skill=1 if E2_9group==9 + replace occup_skill=2 if inrange(E2_9group, 4, 8) + replace occup_skill=3 if inrange(E2_9group, 1, 3) + replace occup_skill=. if lstatus!=1 + la de lblskill 1 "Low skill" 2 "Medium skill" 3 "High skill" + label values occup_skill lblskill + label var occup_skill "Skill based on ISCO standard primary job 7 day recall" +* + + +*<_occup_> + gen occup=E2_9group + replace occup=. if lstatus!=1|!inrange(Age_16groups,4,16) + label var occup "1 digit occupational classification, primary job 7 day recall" + la de lbloccup 1 "Managers" 2 "Professionals" 3 "Technicians" 4 "Clerks" 5 "Service and market sales workers" 6 "Skilled agricultural" 7 "Craft workers" 8 "Machine operators" 9 "Elementary occupations" 10 "Armed forces" 99 "Others" + label values occup lbloccup +* + + +*<_wage_no_compen_> + +/*<_wage_no_compen_note_> + +The wage questions in the questionnare are organized into to parts: the first part +asks for the specific number of income if the given respondent could recall and was +willing to answer; the second part provides different categories of income range +if the given respondent could not recall or was not willing to answer the first part. + +The general logic here is to impute wage values for people who only answered an income +range. We used industry, occupation, income categories and gender to estimate their +specific income values. + +26.35% of total non-missing wage values were imputed using this method. +*<_wage_no_compen_note_>*/ + + * Overall --> wage info (here the variable, for us it should be wage_no_compen) + * to missing if value is 0. + gen wage14=E14_1+E14_2 + replace wage14=. if wage14==0 + + * First replace outliers by + winsor2 wage14, suffix(_w) cuts(1 99) + + * Create salary categories based on winsor values + gen salary_cat=. + replace salary_cat=1 if inrange(wage14_w, 1, 55000) + replace salary_cat=2 if wage14_w==55000 + replace salary_cat=3 if inrange(wage14_w, 55001, 110000) + replace salary_cat=4 if inrange(wage14_w, 110001, 220000) + replace salary_cat=5 if inrange(wage14_w, 220001, 440000) + replace salary_cat=6 if inrange(wage14_w, 440001, 600000) + replace salary_cat=7 if inrange(wage14_w, 600001, 700000) + + * Preserve to collapse, so we can merge the info in + preserve + + * Collpase by industry, sex, and salary categories + collapse (mean)wage14_w[iw=weight], by(industrycat10 occup male urban salary_cat) + + * Rename variable, otherwise when merging in, master version of an equally name one will be kept + rename wage14_w wage_group_estimate + + * Rename salary_cat to D15 since this is what we want the info to latch on to + rename salary_cat E15 + tempfile salary_helper + save "`salary_helper'" + + * Restore, merge in + restore + merge m:1 industrycat10 occup male urban E15 using "`salary_helper'", keep(matched master) nogen + + * Create wage variable + gen wage_no_compen=. + + * Fill it first with values that are accurate + replace wage_no_compen=wage14 if !mi(wage14)&mi(E15) + + * Now add the categorised means + replace wage_no_compen=wage_group_estimate if inrange(E15,1,8)&!mi(wage_group_estimate) + + * Keep only for employed employees, label + replace wage_no_compen=. if lstatus!=1|empstat==2 + label var wage_no_compen "Last wage payment primary job 7 day recall" +* + + +*<_unitwage_> + gen byte unitwage=E16 + recode unitwage (4=5) (5=7) (6=8) (7=10) + replace unitwage=. if lstatus!=1 | empstat==2 + label var unitwage "Last wages' time unit primary job 7 day recall" + la de lblunitwage 1 "Daily" 2 "Weekly" 3 "Every two weeks" 4 "Bimonthly" 5 "Monthly" 6 "Trimester" 7 "Biannual" 8 "Annually" 9 "Hourly" 10 "Other" + label values unitwage lblunitwage +* + + +*<_whours_> + gen whours=G2_1 + replace whours=. if lstatus!=1|G2_1==0 + label var whours "Hours of work in last week primary job 7 day recall" +* + + +*<_wmonths_> + gen wmonths=. + label var wmonths "Months of work in past 12 months primary job 7 day recall" +* + + +*<_wage_total_> + gen wage_total=. + label var wage_total "Annualized total wage primary job 7 day recall" +* + + +*<_contract_> + +/*<_contract_note_> + +There is no separate contract question in the questionnaire. +This contract variable was coded based on employment status question which asks +wether an employed respondent had a contract or not. + +*<_contract_note_>*/ + + gen byte contract = . + replace contract = (E7 == 1) + replace contract=. if lstatus!=1 + label var contract "Employment has contract primary job 7 day recall" + la de lblcontract 0 "Without contract" 1 "With contract" + label values contract lblcontract +* + + +*<_healthins_> + gen byte healthins=. + replace healthins=1 if E8_f==1 + replace healthins=0 if E8_f==2 + replace healthins=. if lstatus!=1 + label var healthins "Employment has health insurance primary job 7 day recall" + la de lblhealthins 0 "Without health insurance" 1 "With health insurance" + label values healthins lblhealthins +* + + +*<_socialsec_> + gen byte socialsec=. + replace socialsec=. if lstatus!=1 + label var socialsec "Employment has social security insurance primary job 7 day recall" + la de lblsocialsec 1 "With social security" 0 "Without social secturity" + label values socialsec lblsocialsec +* + + +*<_union_> + gen byte union=. + replace union=1 if E27==1 + replace union=0 if E27==2 + replace union=. if lstatus!=1 + label var union "Union membership at primary job 7 day recall" + la de lblunion 0 "Not union member" 1 "Union member" + label values union lblunion +* + + +*<_firmsize_l_> + gen byte firmsize_l=E13 + recode firmsize_l (1=1) (2=5) (3=10) (4=20) (5=50) (6=100) (7=.) + replace firmsize_l=. if lstatus!=1 + label var firmsize_l "Firm size (lower bracket) primary job 7 day recall" +* + + +*<_firmsize_u_> + gen byte firmsize_u=E13 + recode firmsize_u (1=5) (2=9) (3=19) (4=49) (5=99) (6=.) + replace firmsize_u=. if lstatus!=1 + label var firmsize_u "Firm size (upper bracket) primary job 7 day recall" +* + +} + + +*----------8.3: 7 day reference secondary job------------------------------* +* Since labels are the same as main job, values are labelled using main job labels + +{ +*<_empstat_2_> + gen byte empstat_2=F4 + recode empstat_2 (2=1) (5=2) + replace empstat_2=. if lstatus!=1|F1!=1 + label var empstat_2 "Employment status during past week secondary job 7 day recall" + la de lblempstat_2 1 "Paid employee" 2 "Non-paid employee" 3 "Employer" 4 "Self-employed" 5 "Other, workers not classifiable by status" + label values empstat_2 lblempstat +* + + +*<_ocusec_2_> + gen byte ocusec_2=F6 + recode ocusec_2 (3 4=2) + replace ocusec_2=. if lstatus!=1|F1!=1 + label var ocusec_2 "Sector of activity secondary job 7 day recall" + la de lblocusec_2 1 "Public Sector, Central Government, Army" 2 "Private, NGO" 3 "State owned" 4 "Public or State-owned, but cannot distinguish" + label values ocusec_2 lblocusec_2 +* + + +*<_industry_orig_2_> + gen industry_orig_2=F3_21group + replace industry_orig_2=. if lstatus!=1|F1!=1 + label var industry_orig_2 "Original survey industry code, secondary job 7 day recall" +* + + +*<_industrycat_isic_2_> + gen industrycat_isic_2="" +quietly +{ + replace industrycat_isic_2="A" if F3_21group==1 + replace industrycat_isic_2="B" if F3_21group==2 + replace industrycat_isic_2="C" if F3_21group==3 + replace industrycat_isic_2="D" if F3_21group==4 + replace industrycat_isic_2="E" if F3_21group==5 + replace industrycat_isic_2="F" if F3_21group==6 + replace industrycat_isic_2="G" if F3_21group==7 + replace industrycat_isic_2="H" if F3_21group==8 + replace industrycat_isic_2="I" if F3_21group==9 + replace industrycat_isic_2="J" if F3_21group==10 + replace industrycat_isic_2="K" if F3_21group==11 + replace industrycat_isic_2="L" if F3_21group==12 + replace industrycat_isic_2="M" if F3_21group==13 + replace industrycat_isic_2="N" if F3_21group==14 + replace industrycat_isic_2="O" if F3_21group==15 + replace industrycat_isic_2="P" if F3_21group==16 + replace industrycat_isic_2="Q" if F3_21group==17 + replace industrycat_isic_2="R" if F3_21group==18 + replace industrycat_isic_2="S" if F3_21group==19 + replace industrycat_isic_2="T" if F3_21group==20 + replace industrycat_isic_2="U" if F3_21group==21 +} + + replace industrycat_isic_2="" if industrycat_isic_2=="."|F1!=1 + label var industrycat_isic_2 "ISIC code of secondary job 7 day recall" +* + + +*<_industrycat10_2_> + gen industrycat10_2=F3_21group + recode industrycat10_2 (5=4) (6=5) (7 9=6) (8 10=7) (11/14=8) (15=9) (16/21=10) + replace industrycat10_2=. if lstatus!=1|F1!=1 + label var industrycat10_2 "1 digit industry classification, secondary job 7 day recall" + label values industrycat10_2 lblindustrycat10 +* + + +*<_industrycat4_2_> + gen byte industrycat4_2=industrycat10_2 + recode industrycat4_2 (3/5=2)(6/9=3)(10=4) + label var industrycat4_2 "1 digit industry classification (Broad Economic Activities), secondary job 7 day recall" + label values industrycat4_2 lblindustrycat4 +* + + +*<_occup_orig_2_> + gen occup_orig_2=F2_9group + replace occup_orig_2=. if lstatus!=1|F1!=1 + label var occup_orig_2 "Original occupation record secondary job 7 day recall" +* + + +*<_occup_isco_2_> + gen occup_isco_2="" + replace occup_isco_2="" if lstatus!=1 | occup_isco_2=="."|F1!=1 + label var occup_isco_2 "ISCO code of secondary job 7 day recall" +* + + +*<_occup_skill_2_> + gen occup_skill_2=F2_9group + replace occup_skill_2=1 if F2_9group==9 + replace occup_skill_2=2 if inrange(F2_9group,4,8) + replace occup_skill_2=3 if inrange(F2_9group,1,3) + replace occup_skill_2=. if F2_9group==0|lstatus!=1|F1!=1 + label var occup_skill_2 "Skill based on ISCO standard secondary job 7 day recall" +* + + +*<_occup_2_> + gen occup_2=F2_9group + replace occup_2=. if lstatus!=1|F1!=1 + label var occup_2 "1 digit occupational classification secondary job 7 day recall" + label values occup_2 lbloccup +* + + +*<_wage_no_compen_2_> + +/*<_wage_no_compen_2_note_> + +The questionnaire actually has questions about income of the second job, just as the +main job. However, the data set does not have the variables. + +*<_wage_no_compen_2_note_>*/ + gen wage_no_compen_2=. + replace wage_no_compen_2=. if F1!=1|empstat_2==2 + label var wage_no_compen_2 "Last wage payment secondary job 7 day recall" +* + + +*<_unitwage_2_> + gen byte unitwage_2=. + replace unitwage_2=. if lstatus!=1|F1!=1 + label var unitwage_2 "Last wages' time unit secondary job 7 day recall" + label values unitwage_2 lblunitwage +* + + +*<_whours_2_> + gen whours_2=G2_2 + replace whours_2=. if G2_2==0|F1!=1 + label var whours_2 "Hours of work in last week secondary job 7 day recall" +* + + +*<_wmonths_2_> + gen wmonths_2=. + label var wmonths_2 "Months of work in past 12 months secondary job 7 day recall" +* + + +*<_wage_total_2_> + gen wage_total_2=. + label var wage_total_2 "Annualized total wage secondary job 7 day recall" +* + + +*<_firmsize_l_2_> + gen byte firmsize_l_2=. + label var firmsize_l_2 "Firm size (lower bracket) secondary job 7 day recall" +* + + +*<_firmsize_u_2_> + gen byte firmsize_u_2=. + label var firmsize_u_2 "Firm size (upper bracket) secondary job 7 day recall" +* + +} + +*----------8.4: 7 day reference additional jobs------------------------------* + +*<_t_hours_others_> + gen t_hours_others=. + label var t_hours_others "Annualized hours worked in all but primary and secondary jobs 7 day recall" +* + + +*<_t_wage_nocompen_others_> + gen t_wage_nocompen_others=. + label var t_wage_nocompen_others "Annualized wage in all but primary & secondary jobs excl. bonuses, etc. 7 day recall" +* + + +*<_t_wage_others_> + gen t_wage_others=. + label var t_wage_others "Annualized wage in all but primary and secondary jobs (12-mon ref period)" +* + + +*----------8.5: 7 day reference total summary------------------------------* + + +*<_t_hours_total_> + gen t_hours_total=. + label var t_hours_total "Annualized hours worked in all jobs 7 day recall" +* + + +*<_t_wage_nocompen_total_> + gen t_wage_nocompen_total=. + label var t_wage_nocompen_total "Annualized wage in all jobs excl. bonuses, etc. 7 day recall" +* + + +*<_t_wage_total_> + gen t_wage_total=. + label var t_wage_total "Annualized total wage for all jobs 7 day recall" +* + + +*----------8.6: 12 month reference overall------------------------------* + +{ +*<_lstatus_year_> + gen byte lstatus_year=. + replace lstatus_year=. if !inrange(Age_16groups,4,16) + label var lstatus_year "Labor status during last year" + la de lbllstatus_year 1 "Employed" 2 "Unemployed" 3 "Non-LF" + label values lstatus_year lbllstatus_year +* + + +*<_potential_lf_year_> + gen byte potential_lf_year=. + replace potential_lf_year=. if !inrange(Age_16groups,4,16) + replace potential_lf_year=. if lstatus_year!=3 + label var potential_lf_year "Potential labour force status" + la de lblpotential_lf_year 0 "No" 1 "Yes" + label values potential_lf_year lblpotential_lf_year +* + + +*<_underemployment_year_> + gen byte underemployment_year=. + replace underemployment_year=. if !inrange(Age_16groups,4,16) + replace underemployment_year=. if lstatus_year==1 + label var underemployment_year "Underemployment status" + la de lblunderemployment_year 0 "No" 1 "Yes" + label values underemployment_year lblunderemployment_year +* + + +*<_nlfreason_year_> + gen byte nlfreason_year=. + label var nlfreason_year "Reason not in the labor force" + la de lblnlfreason_year 1 "Student" 2 "Housekeeper" 3 "Retired" 4 "Disable" 5 "Other" + label values nlfreason_year lblnlfreason_year +* + + +*<_unempldur_l_year_> + gen byte unempldur_l_year=. + label var unempldur_l_year "Unemployment duration (months) lower bracket" +* + + +*<_unempldur_u_year_> + gen byte unempldur_u_year=. + label var unempldur_u_year "Unemployment duration (months) upper bracket" +* + +} + +*----------8.7: 12 month reference main job------------------------------* + +{ +*<_empstat_year_> + gen byte empstat_year=. + label var empstat_year "Employment status during past week primary job 12 month recall" + la de lblempstat_year 1 "Paid employee" 2 "Non-paid employee" 3 "Employer" 4 "Self-employed" 5 "Other, workers not classifiable by status" + label values empstat_year lblempstat_year +* + + +*<_ocusec_year_> + gen byte ocusec_year=. + label var ocusec_year "Sector of activity primary job 12 day recall" + la de lblocusec_year 1 "Public Sector, Central Government, Army" 2 "Private, NGO" 3 "State owned" 4 "Public or State-owned, but cannot distinguish" + label values ocusec_year lblocusec_year +* + + +*<_industry_orig_year_> + gen industry_orig_year=. + label var industry_orig_year "Original industry record main job 12 month recall" +* + + +*<_industrycat_isic_year_> + gen industrycat_isic_year="" + replace industrycat_isic_year="" if industrycat_isic_year=="." + label var industrycat_isic_year "ISIC code of primary job 12 month recall" +* + + +*<_industrycat10_year_> + gen byte industrycat10_year=. + label var industrycat10_year "1 digit industry classification, primary job 12 month recall" + la de lblindustrycat10_year 1 "Agriculture" 2 "Mining" 3 "Manufacturing" 4 "Public utilities" 5 "Construction" 6 "Commerce" 7 "Transport and Comnunications" 8 "Financial and Business Services" 9 "Public Administration" 10 "Other Services, Unspecified" + label values industrycat10_year lblindustrycat10_year +* + + +*<_industrycat4_year_> + gen byte industrycat4_year=industrycat10_year + recode industrycat4_year (1=1)(2 3 4 5 =2)(6 7 8 9=3)(10=4) + label var industrycat4_year "1 digit industry classification (Broad Economic Activities), primary job 12 month recall" + la de lblindustrycat4_year 1 "Agriculture" 2 "Industry" 3 "Services" 4 "Other" + label values industrycat4_year lblindustrycat4_year +* + + +*<_occup_orig_year_> + gen occup_orig_year=. + label var occup_orig_year "Original occupation record primary job 12 month recall" +* + + +*<_occup_isco_year_> + gen str4 occup_isco_year="" + label var occup_isco_year "ISCO code of primary job 12 month recall" +* + + +*<_occup_skill_year_> + gen skill_level_year=substr(occup_isco_year,1,1) + destring skill_level_year, replace + gen occup_skill_year=. + replace occup_skill_year=1 if skill_level_year==9 + replace occup_skill_year=2 if inrange(skill_level_year,4,8) + replace occup_skill_year=3 if inrange(skill_level_year,1,3) + replace occup_skill_year=. if skill_level_year==0 + label var occup_skill_year "Skill based on ISCO standard primary job 12 month recall" +* + + +*<_occup_year_> + gen byte occup_year=. + label var occup_year "1 digit occupational classification, primary job 12 month recall" + la de lbloccup_year 1 "Managers" 2 "Professionals" 3 "Technicians" 4 "Clerks" 5 "Service and market sales workers" 6 "Skilled agricultural" 7 "Craft workers" 8 "Machine operators" 9 "Elementary occupations" 10 "Armed forces" 99 "Others" + label values occup_year lbloccup_year +* + + +*<_wage_no_compen_year_> + gen double wage_no_compen_year=. + label var wage_no_compen_year "Last wage payment primary job 12 month recall" +* + + +*<_unitwage_year_> + gen byte unitwage_year=. + label var unitwage_year "Last wages' time unit primary job 12 month recall" + la de lblunitwage_year 1 "Daily" 2 "Weekly" 3 "Every two weeks" 4 "Bimonthly" 5 "Monthly" 6 "Trimester" 7 "Biannual" 8 "Annually" 9 "Hourly" 10 "Other" + label values unitwage_year lblunitwage_year +* + + +*<_whours_year_> + gen whours_year=. + label var whours_year "Hours of work in last week primary job 12 month recall" +* + + +*<_wmonths_year_> + gen wmonths_year=. + label var wmonths_year "Months of work in past 12 months primary job 12 month recall" +* + + +*<_wage_total_year_> + gen wage_total_year=. + label var wage_total_year "Annualized total wage primary job 12 month recall" +* + + +*<_contract_year_> + gen byte contract_year=. + label var contract_year "Employment has contract primary job 12 month recall" + la de lblcontract_year 0 "Without contract" 1 "With contract" + label values contract_year lblcontract_year +* + + +*<_healthins_year_> + gen byte healthins_year=. + label var healthins_year "Employment has health insurance primary job 12 month recall" + la de lblhealthins_year 0 "Without health insurance" 1 "With health insurance" + label values healthins_year lblhealthins_year +* + + +*<_socialsec_year_> + gen byte socialsec_year=. + label var socialsec_year "Employment has social security insurance primary job 7 day recall" + la de lblsocialsec_year 1 "With social security" 0 "Without social secturity" + label values socialsec_year lblsocialsec_year +* + + +*<_union_year_> + gen byte union_year=. + label var union_year "Union membership at primary job 12 month recall" + la de lblunion_year 0 "Not union member" 1 "Union member" + label values union_year lblunion_year +* + + +*<_firmsize_l_year_> + gen byte firmsize_l_year=. + label var firmsize_l_year "Firm size (lower bracket) primary job 12 month recall" +* + + +*<_firmsize_u_year_> + gen byte firmsize_u_year=. + label var firmsize_u_year "Firm size (upper bracket) primary job 12 month recall" +* + +} + + +*----------8.8: 12 month reference secondary job------------------------------* + +{ + +*<_empstat_2_year_> + gen byte empstat_2_year=. + label var empstat_2_year "Employment status during past week secondary job 12 month recall" + label values empstat_2_year lblempstat_year +* + + +*<_ocusec_2_year_> + gen byte ocusec_2_year=. + label var ocusec_2_year "Sector of activity secondary job 12 day recall" + la de lblocusec_2_year 1 "Public Sector, Central Government, Army" 2 "Private, NGO" 3 "State owned" 4 "Public or State-owned, but cannot distinguish" + label values ocusec_2_year lblocusec_2_year +* + + + +*<_industry_orig_2_year_> + gen industry_orig_2_year=. + label var industry_orig_2_year "Original survey industry code, secondary job 12 month recall" +* + + + +*<_industrycat_isic_2_year_> + gen industrycat_isic_2_year=. + label var industrycat_isic_2_year "ISIC code of secondary job 12 month recall" +* + + +*<_industrycat10_2_year_> + gen byte industrycat10_2_year=. + label var industrycat10_2_year "1 digit industry classification, secondary job 12 month recall" + label values industrycat10_2_year lblindustrycat10_year +* + + +*<_industrycat4_2_year_> + gen byte industrycat4_2_year=industrycat10_2_year + recode industrycat4_2_year (1=1)(2 3 4 5 =2)(6 7 8 9=3)(10=4) + label var industrycat4_2_year "1 digit industry classification (Broad Economic Activities), secondary job 12 month recall" + label values industrycat4_2_year lblindustrycat4_year +* + + +*<_occup_orig_2_year_> + gen occup_orig_2_year=. + label var occup_orig_2_year "Original occupation record secondary job 12 month recall" +* + + +*<_occup_isco_2_year_> + gen occup_isco_2_year=. + label var occup_isco_2_year "ISCO code of secondary job 12 month recall" +* + + +*<_occup_skill_2_year_> + gen occup_skill_2_year=. + label var occup_skill_2_year "Skill based on ISCO standard secondary job 12 month recall" +* + + +*<_occup_2_year_> + gen byte occup_2_year=. + label var occup_2_year "1 digit occupational classification, secondary job 12 month recall" + label values occup_2_year lbloccup_year +* + + +*<_wage_no_compen_2_year_> + gen double wage_no_compen_2_year=. + label var wage_no_compen_2_year "Last wage payment secondary job 12 month recall" +* + + +*<_unitwage_2_year_> + gen byte unitwage_2_year=. + label var unitwage_2_year "Last wages' time unit secondary job 12 month recall" + label values unitwage_2_year lblunitwage_year +* + + +*<_whours_2_year_> + gen whours_2_year=. + label var whours_2_year "Hours of work in last week secondary job 12 month recall" +* + + +*<_wmonths_2_year_> + gen wmonths_2_year=. + label var wmonths_2_year "Months of work in past 12 months secondary job 12 month recall" +* + + +*<_wage_total_2_year_> + gen wage_total_2_year=. + label var wage_total_2_year "Annualized total wage secondary job 12 month recall" +* + + +*<_firmsize_l_2_year_> + gen byte firmsize_l_2_year=. + label var firmsize_l_2_year "Firm size (lower bracket) secondary job 12 month recall" +* + + +*<_firmsize_u_2_year_> + gen byte firmsize_u_2_year=. + label var firmsize_u_2_year "Firm size (upper bracket) secondary job 12 month recall" +* + +} + + +*----------8.9: 12 month reference additional jobs------------------------------* + + +*<_t_hours_others_year_> + gen t_hours_others_year=. + label var t_hours_others_year "Annualized hours worked in all but primary and secondary jobs 12 month recall" +* + + +*<_t_wage_nocompen_others_year_> + gen t_wage_nocompen_others_year=. + label var t_wage_nocompen_others_year "Annualized wage in all but primary & secondary jobs excl. bonuses, etc. 12 month recall)" +* + + +*<_t_wage_others_year_> + gen t_wage_others_year=. + label var t_wage_others_year "Annualized wage in all but primary and secondary jobs 12 month recall" +* + + +*----------8.10: 12 month total summary------------------------------* + + +*<_t_hours_total_year_> + gen t_hours_total_year=. + label var t_hours_total_year "Annualized hours worked in all jobs 12 month month recall" +* + + +*<_t_wage_nocompen_total_year_> + gen t_wage_nocompen_total_year=. + label var t_wage_nocompen_total_year "Annualized wage in all jobs excl. bonuses, etc. 12 month recall" +* + + +*<_t_wage_total_year_> + gen t_wage_total_year=. + label var t_wage_total_year "Annualized total wage for all jobs 12 month recall" +* + + +*----------8.11: Overall across reference periods------------------------------* + + +*<_njobs_> + gen njobs=. + replace njobs=1 if lstatus==1&F1!=1 + replace njobs=2 if lstatus==1&F1==1 + replace njobs=. if lstatus!=1 + label var njobs "Total number of jobs" +* + + +*<_t_hours_annual_> + gen t_hours_annual=. + label var t_hours_annual "Total hours worked in all jobs in the previous 12 months" +* + + +*<_linc_nc_> + gen linc_nc=. + label var linc_nc "Total annual wage income in all jobs, excl. bonuses, etc." +* + + +*<_laborincome_> + gen laborincome=. + label var laborincome "Total annual individual labor income in all jobs, incl. bonuses, etc." +* + + +*----------8.13: Labour cleanup------------------------------* + +{ +*<_% Correction min age_> + +** Drop info for cases under the age for which questions to be asked (do not need a variable for this) + local lab_var "minlaborage lstatus nlfreason unempldur_l unempldur_u empstat ocusec industry_orig industrycat_isic industrycat10 industrycat4 occup_orig occup_isco occup_skill occup wage_no_compen unitwage whours wmonths wage_total contract healthins socialsec union firmsize_l firmsize_u empstat_2 ocusec_2 industry_orig_2 industrycat_isic_2 industrycat10_2 industrycat4_2 occup_orig_2 occup_isco_2 occup_skill_2 occup_2 wage_no_compen_2 unitwage_2 whours_2 wmonths_2 wage_total_2 firmsize_l_2 firmsize_u_2 t_hours_others t_wage_nocompen_others t_wage_others t_hours_total t_wage_nocompen_total t_wage_total lstatus_year nlfreason_year unempldur_l_year unempldur_u_year empstat_year ocusec_year industry_orig_year industrycat_isic_year industrycat10_year industrycat4_year occup_orig_year occup_isco_year occup_skill_year occup_year unitwage_year whours_year wmonths_year wage_total_year contract_year healthins_year socialsec_year union_year firmsize_l_year firmsize_u_year empstat_2_year ocusec_2_year industry_orig_2_year industrycat_isic_2_year industrycat10_2_year industrycat4_2_year occup_orig_2_year occup_isco_2_year occup_skill_2_year occup_2_year wage_no_compen_2_year unitwage_2_year whours_2_year wmonths_2_year wage_total_2_year firmsize_l_2_year firmsize_u_2_year t_hours_others_year t_wage_nocompen_others_year t_wage_others_year t_hours_total_year t_wage_nocompen_total_year t_wage_total_year njobs t_hours_annual linc_nc laborincome" + + foreach v of local lab_var { + cap confirm numeric variable `v' + if _rc == 0 { // is indeed numeric + replace `v'=. if ( age < minlaborage & !missing(age) ) + } + else { // is not + replace `v'= "" if ( age < minlaborage & !missing(age) ) + } + + } + +* +} + + +/*%%============================================================================================= + 9: Final steps +==============================================================================================%%*/ + +quietly{ + +*<_% KEEP VARIABLES - ALL_> + + keep countrycode survname survey icls_v isced_version isco_version isic_version year vermast veralt harmonization int_year int_month hhid pid weight weight_m weight_q psu strata wave panel visit_no urban subnatid1 subnatid2 subnatid3 subnatidsurvey subnatid1_prev subnatid2_prev subnatid3_prev gaul_adm1_code gaul_adm2_code gaul_adm3_code hsize age male relationharm relationcs marital eye_dsablty hear_dsablty walk_dsablty conc_dsord slfcre_dsablty comm_dsablty migrated_mod_age migrated_ref_time migrated_binary migrated_years migrated_from_urban migrated_from_cat migrated_from_code migrated_from_country migrated_reason ed_mod_age school literacy educy educat7 educat5 educat4 educat_orig educat_isced vocational vocational_type vocational_length_l vocational_length_u vocational_field_orig vocational_financed minlaborage lstatus potential_lf underemployment nlfreason unempldur_l unempldur_u empstat ocusec industry_orig industrycat_isic industrycat10 industrycat4 occup_orig occup_isco occup_skill occup wage_no_compen unitwage whours wmonths wage_total contract healthins socialsec union firmsize_l firmsize_u empstat_2 ocusec_2 industry_orig_2 industrycat_isic_2 industrycat10_2 industrycat4_2 occup_orig_2 occup_isco_2 occup_skill_2 occup_2 wage_no_compen_2 unitwage_2 whours_2 wmonths_2 wage_total_2 firmsize_l_2 firmsize_u_2 t_hours_others t_wage_nocompen_others t_wage_others t_hours_total t_wage_nocompen_total t_wage_total lstatus_year potential_lf_year underemployment_year nlfreason_year unempldur_l_year unempldur_u_year empstat_year ocusec_year industry_orig_year industrycat_isic_year industrycat10_year industrycat4_year occup_orig_year occup_isco_year occup_skill_year occup_year wage_no_compen_year unitwage_year whours_year wmonths_year wage_total_year contract_year healthins_year socialsec_year union_year firmsize_l_year firmsize_u_year empstat_2_year ocusec_2_year industry_orig_2_year industrycat_isic_2_year industrycat10_2_year industrycat4_2_year occup_orig_2_year occup_isco_2_year occup_skill_2_year occup_2_year wage_no_compen_2_year unitwage_2_year whours_2_year wmonths_2_year wage_total_2_year firmsize_l_2_year firmsize_u_2_year t_hours_others_year t_wage_nocompen_others_year t_wage_others_year t_hours_total_year t_wage_nocompen_total_year t_wage_total_year njobs t_hours_annual linc_nc laborincome + +* + +*<_% ORDER VARIABLES_> + + order countrycode survname survey icls_v isced_version isco_version isic_version year vermast veralt harmonization int_year int_month hhid pid weight weight_m weight_q psu strata wave panel visit_no urban subnatid1 subnatid2 subnatid3 subnatidsurvey subnatid1_prev subnatid2_prev subnatid3_prev gaul_adm1_code gaul_adm2_code gaul_adm3_code hsize age male relationharm relationcs marital eye_dsablty hear_dsablty walk_dsablty conc_dsord slfcre_dsablty comm_dsablty migrated_mod_age migrated_ref_time migrated_binary migrated_years migrated_from_urban migrated_from_cat migrated_from_code migrated_from_country migrated_reason ed_mod_age school literacy educy educat7 educat5 educat4 educat_orig educat_isced vocational vocational_type vocational_length_l vocational_length_u vocational_field_orig vocational_financed minlaborage lstatus potential_lf underemployment nlfreason unempldur_l unempldur_u empstat ocusec industry_orig industrycat_isic industrycat10 industrycat4 occup_orig occup_isco occup_skill occup wage_no_compen unitwage whours wmonths wage_total contract healthins socialsec union firmsize_l firmsize_u empstat_2 ocusec_2 industry_orig_2 industrycat_isic_2 industrycat10_2 industrycat4_2 occup_orig_2 occup_isco_2 occup_skill_2 occup_2 wage_no_compen_2 unitwage_2 whours_2 wmonths_2 wage_total_2 firmsize_l_2 firmsize_u_2 t_hours_others t_wage_nocompen_others t_wage_others t_hours_total t_wage_nocompen_total t_wage_total lstatus_year potential_lf_year underemployment_year nlfreason_year unempldur_l_year unempldur_u_year empstat_year ocusec_year industry_orig_year industrycat_isic_year industrycat10_year industrycat4_year occup_orig_year occup_isco_year occup_skill_year occup_year wage_no_compen_year unitwage_year whours_year wmonths_year wage_total_year contract_year healthins_year socialsec_year union_year firmsize_l_year firmsize_u_year empstat_2_year ocusec_2_year industry_orig_2_year industrycat_isic_2_year industrycat10_2_year industrycat4_2_year occup_orig_2_year occup_isco_2_year occup_skill_2_year occup_2_year wage_no_compen_2_year unitwage_2_year whours_2_year wmonths_2_year wage_total_2_year firmsize_l_2_year firmsize_u_2_year t_hours_others_year t_wage_nocompen_others_year t_wage_others_year t_hours_total_year t_wage_nocompen_total_year t_wage_total_year njobs t_hours_annual linc_nc laborincome + +* + +*<_% DROP UNUSED LABELS_> + + * Store all labels in data + label dir + local all_lab `r(names)' + + * Store all variables with a label, extract value label names + local used_lab = "" + ds, has(vallabel) + + local labelled_vars `r(varlist)' + + foreach varName of local labelled_vars { + local y : value label `varName' + local used_lab `"`used_lab' `y'"' + } + + * Compare lists, `notused' is list of labels in directory but not used in final variables + local notused : list all_lab - used_lab // local `notused' defines value labs not in remaining vars + local notused_len : list sizeof notused // store size of local + + * drop labels if the length of the notused vector is 1 or greater, otherwise nothing to drop + if `notused_len' >= 1 { + label drop `notused' + } + else { + di "There are no unused labels to drop. No value labels dropped." + } + + +* + +} + +*<_% DELETE MISSING VARIABLES_> + +quietly: describe, varlist +local kept_vars `r(varlist)' + +foreach var of local kept_vars { + + capture assert missing(`var') + if !_rc drop `var' +} + +* + + +*<_% COMPRESS_> + +compress + +* + + +*<_% SAVE_> + +save "`path_output'/`level_2_harm'_ALL.dta", replace + +* From f3580d33bdda644bba09f66e2b9ff77d445d1123 Mon Sep 17 00:00:00 2001 From: Mario G <63501500+gronert-m@users.noreply.github.com> Date: Thu, 10 Oct 2024 17:18:38 -0400 Subject: [PATCH 2/3] Update ARM LFS CSD Update documentation to take into account changes made in the code --- .../ARM/LFS/1. Introduction to Armenia LFS.md | 35 ++++++++- .../ARM/LFS/utilities/Comparison_weights.do | 70 ++++++++++++++++++ .../LFS/utilities/Error_pop_move_2018_eng.png | Bin 0 -> 73793 bytes .../LFS/utilities/in-exclusion_from_2018.png | Bin 0 -> 313962 bytes .../LFS/utilities/in-exclusion_til_2017.png | Bin 0 -> 45615 bytes .../ARM/LFS/utilities/weight_timelines.png | Bin 0 -> 90391 bytes 6 files changed, 101 insertions(+), 4 deletions(-) create mode 100644 Support/B - Country Survey Details/ARM/LFS/utilities/Comparison_weights.do create mode 100644 Support/B - Country Survey Details/ARM/LFS/utilities/Error_pop_move_2018_eng.png create mode 100644 Support/B - Country Survey Details/ARM/LFS/utilities/in-exclusion_from_2018.png create mode 100644 Support/B - Country Survey Details/ARM/LFS/utilities/in-exclusion_til_2017.png create mode 100644 Support/B - Country Survey Details/ARM/LFS/utilities/weight_timelines.png diff --git a/Support/B - Country Survey Details/ARM/LFS/1. Introduction to Armenia LFS.md b/Support/B - Country Survey Details/ARM/LFS/1. Introduction to Armenia LFS.md index fbe773764..5631233b0 100644 --- a/Support/B - Country Survey Details/ARM/LFS/1. Introduction to Armenia LFS.md +++ b/Support/B - Country Survey Details/ARM/LFS/1. Introduction to Armenia LFS.md @@ -75,6 +75,18 @@ This change leads to an apparent decrease in non-paid employees after 2017. In addition, kindly be advised that it is not feasible to convert between different ICLS versions in ARM LFS. Although the questionnaire screenshots above show that the employment status is composed by several sub-questions in terms of "for-sale" and "for-own-consumption" work, the raw datasets only present the final decision about whether a given observation is employed or not based on their answers to the sub-questions which we couldn't see. Therefore, we were not able to convert between ICLS-13 and ICLS-19 by "switching on and off" the "for-own-consumption jobs". +### Changes to the weight variable + +At the same time as the change of employment definition was implemented, a change in the weight calculation was also introduced. From 2018 onwards a new weight (referred in the raw data as "_calibrated_") is used. This value results in a higher extended population. during 2018 and 2019 both the old weights (used in 2014 to 2017) and the calibrated weights (used since 2018) are available in the raw data. + +The GLD harmonization includes by default the calibrated weights as the standard weights (variables `weight` and `weight_q`). For the years 2018 and 2019 the old weights are kept in special variables (i.e., not part of the common GLD dictionary) called `weight_old_series` and `weight_q_old_series`. + +The graph below plots the labor force participation using the old series (blue line) and the new weights (red line). Additionally, the green line denotes the data as reported by the Armenian NSO. The change in employment definition should decrease LFP as own consumption workers are no longer employed. This is only visible with the old weights, as the new weights increase the population that indicates a positive jump in the labor force participation (LFP) + +![LFP plot by weights](utilities/weight_timelines.png) + +Users are advised to take these changes into account when trying to create a series over all LFS years. The code to produce the above graph [can be found here](utilities/Comparison_weights.do). + ### Coding of industry and occupation codes In terms of classifications of industry and occupation, ARM LFS used ISIC-4 and ISCO-08 respectively for all years. No national classifications applied. @@ -83,10 +95,13 @@ However, regarding the level of classification, both industry and occupation onl ### Coding PSU and strata -Based on the description of sampling methodology in the annual report of 2018 (refer to the screenshot below), the sampling is based on the 2011 census. The PSUs are census enumeration areas to which we currently do not have access. In this case, we didn't code `psu` in GLD. We may update this variable in the future if information concerned becomes availabel. +Based on the description of sampling methodology in the annual report of 2018 (refer to the screenshot below), the sampling is based on the 2011 census. The PSUs are census enumeration areas to which we currently do not have access. In this case, we didn't code `psu` in GLD. We may update this variable in the future if information concerned becomes available. ![PSU](utilities/PSU.png) +### Age restriction of the questionnaire labor market module + +While most surveys limit the market module to all people aged above lower age threshold (commonly 15 years of age), the Armenian ILCS is limited also by an upper age threshold. Only people aged 15 to 75 respond to the labor market module and thus have labor variables. Given the low labor force participation of people aged 76 and older, it can be assumed that the labor force participation of the population 15+ is lower than the one that can be calculated. ### Coding of education @@ -137,10 +152,22 @@ Different from previous years, the last two years, 2021 and 2022 do not have the In this case, we harmonized our `age` variable using the mean of each sub-group of the original `Age_16groups` so as to proceed with our quality checks which require numeric values (i.e., all people between 0 and 4 are coded as 2 year olds, all 65 to 69 are coded as 67). Hence, for 2021 and 2022, `age` in GLD harmonization of ARM LFS does not represent the actual age of a given observation. Yet instead, it indicates the age group a given observation belongs to. -### Migration from other countries +### Absent household members + +Armenia's LFS includes in the general information about the household all members the household deems to be part of it. However, many of the people the household emotionally may list as its members are absent (e.g., a child who has left for work in another country) and thus are not to be included. + +The logic in the questionnaires from 2014 to 2017 is to have the enumerator skip any members who have been absent for 3 or more months (except for military service), as shown below. + +![Skipping absent HH members until 2017](utilities/in-exclusion_til_2017.png) + +From 2018, a special section (section **C**) is introduced to collect more information on absent household members and determine their exclusion. Their general status is determined in questions C3 and C4 (green box in the screenshot below), their eligibility is determined in question C12 (red box) following the parameters outlined below (yellow box). + +![Skipping absent HH members from 2018](utilities/in-exclusion_from_2018.png) + +The above screenshot is from the 2019 questionnaire and questions as well as instructions change slightly over the years. In 2022, all people aged 2022 are coded as eligible, even though 253 individuals claim that they have not usually resided in the household in the previous year (C3 == 2) and have been absent for at least 3 months (C10 == 4 or 5). -Since 2018, ARM LFS includes a migration section. From 2019 to 2022, one of the "last settlement" options is *Artsakh* (also known as Nagorno-Karabakh), an enclave of mostly ethnic Armenian contested between Armenia and Azerbaijan. The international community’s position as of December 2023 is that the area is official part of Azerbaijan. Consequently, and as there is no ISO three-letter country code for Artsakh, respondents with this answer are coded as "AZE", the ISO code of Azerbaijan. This is purely to keep answers within the alpha-3 ISO codes and in no way an endorsement of any political position. +Users are advised to review the logic and take into account how it may impact any calculation of the working age calculation (as absentees are present in the data even though they lack labor module answers). Finally, users are also advised to review the translations as there may be errors in the English translation. The only error in this section we have found is shown below, where the English translation has a different skip pattern to the Armenian version.

-![migration_country](utilities/migration.png) +![Difference in skip pattern between English and Armenian version in 2018](utilities/Error_pop_move_2018_eng.png) diff --git a/Support/B - Country Survey Details/ARM/LFS/utilities/Comparison_weights.do b/Support/B - Country Survey Details/ARM/LFS/utilities/Comparison_weights.do new file mode 100644 index 000000000..58bcba2b4 --- /dev/null +++ b/Support/B - Country Survey Details/ARM/LFS/utilities/Comparison_weights.do @@ -0,0 +1,70 @@ +clear + +*---- Append 2014 to 2022 data +foreach year of numlist 2014/2022 { + + append using "Y:/GLD/ARM/ARM_`year'_LFS\ARM_`year'_LFS_V01_M_V03_A_GLD/Data/Harmonized/ARM_`year'_LFS_V01_M_V03_A_GLD_ALL.dta" + + +} + +*---- Create variables for comparison +gen lfp_old_series = . +replace lfp_old_series = weight if inlist(lstatus,1,2) & inrange(year,2014,2017) +replace lfp_old_series = weight_old_series if inlist(lstatus,1,2) & inrange(year,2018,2019) + +gen wap_old_series = . +replace wap_old_series = weight if inlist(lstatus,1,2,3) & inrange(year,2014,2017) +replace wap_old_series = weight_old_series if inlist(lstatus,1,2,3) & inrange(year,2018,2019) + +gen lfp_new_series = . +replace lfp_new_series = weight if inlist(lstatus,1,2) & inrange(year,2018,2022) + +gen wap_new_series = . +replace wap_new_series = weight if inlist(lstatus,1,2,3) & inrange(year,2018,2022) + +gen lfp_cmb_series = . +replace lfp_cmb_series = weight if inlist(lstatus,1,2) + +gen wap_cmb_series = . +replace wap_cmb_series = weight if inlist(lstatus,1,2,3) + + +*---- Collapse data to get by year +collapse (sum) lfp_* wap_*, by(year) + +// Loop through all variables in the dataset +foreach var of varlist * { + // Replace 0 with missing value (.) + replace `var' = . if `var' == 0 +} +*list + +*---- Add in official data + +gen lfp_off = . +replace lfp_off = 1375700 if year == 2014 +replace lfp_off = 1316400 if year == 2015 +replace lfp_off = 1226300 if year == 2016 +replace lfp_off = 1230700 if year == 2017 +replace lfp_off = 1293800 if year == 2018 +replace lfp_off = 1318100 if year == 2019 +replace lfp_off = 1286700 if year == 2020 +replace lfp_off = 1287300 if year == 2021 +replace lfp_off = 1311300 if year == 2022 + + +*---- Plot + +// Determine the range of years +summarize year +local min_year = r(min) +local max_year = r(max) + +twoway (line lfp_old_series year) (line lfp_new_series year) (line lfp_off year), /// + title("Plot of ARM LFP over years by weight variable") /// + xlabel(`min_year'(1)`max_year', grid) ylabel(, grid) /// + legend(order(1 "LFP with weight 204-17, old weigth 2018-19" 2 "LFP with weight 2018-2022" 3 "LFP ARMSTAT Data") /// + position(6) row(3)) + +gr export "Y:/GLD/ARM/ARM_2022_LFS/ARM_2022_LFS_V01_M_V03_A_GLD/Work/weight_timelines.png", replace diff --git a/Support/B - Country Survey Details/ARM/LFS/utilities/Error_pop_move_2018_eng.png b/Support/B - Country Survey Details/ARM/LFS/utilities/Error_pop_move_2018_eng.png new file mode 100644 index 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17:21:34 -0400 Subject: [PATCH 3/3] Update 1. Introduction to Armenia LFS.md Drop comparison to reported data as this is already included in the weight section. --- .../ARM/LFS/1. Introduction to Armenia LFS.md | 7 ------- 1 file changed, 7 deletions(-) diff --git a/Support/B - Country Survey Details/ARM/LFS/1. Introduction to Armenia LFS.md b/Support/B - Country Survey Details/ARM/LFS/1. Introduction to Armenia LFS.md index 5631233b0..6aa739a3e 100644 --- a/Support/B - Country Survey Details/ARM/LFS/1. Introduction to Armenia LFS.md +++ b/Support/B - Country Survey Details/ARM/LFS/1. Introduction to Armenia LFS.md @@ -134,13 +134,6 @@ With this information, the coding choice is shown below. The key distinction is | | | | 10. Certified specialist | 7 University incomplete or complete | | | | | 11. Post-graduate (Ph.D, doctorate, internship, residency) | 7 University incomplete or complete | -### Employment rate comparison - -As part of our harmonization quality checks, we conducted a cross examination of employment rate with official annual reports. The figure below shows the comparison which indicates that our `lstatus` was correctly harmonized and the results align with official results. - -

- -![employment_rate](utilities/employment_comparison.png) ### Age variables in 2021 and 2022