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RBC_Matlab.m
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RBC_Matlab.m
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%% Basic RBC model with full depreciation
%
% Jesus Fernandez-Villaverde
% Haverford, July 3, 2013
%% 0. Housekeeping
clear all
close all
clc
tic
%% 1. Calibration
aalpha = 1/3; % Elasticity of output w.r.t. capital
bbeta = 0.95; % Discount factor
% Productivity values
vProductivity = [0.9792; 0.9896; 1.0000; 1.0106; 1.0212]';
% Transition matrix
mTransition = [0.9727, 0.0273, 0.0000, 0.0000, 0.0000;
0.0041, 0.9806, 0.0153, 0.0000, 0.0000;
0.0000, 0.0082, 0.9837, 0.0082, 0.0000;
0.0000, 0.0000, 0.0153, 0.9806, 0.0041;
0.0000, 0.0000, 0.0000, 0.0273, 0.9727];
%% 2. Steady State
capitalSteadyState = (aalpha*bbeta)^(1/(1-aalpha));
outputSteadyState = capitalSteadyState^aalpha;
consumptionSteadyState = outputSteadyState-capitalSteadyState;
fprintf(' Output = %2.6f, Capital = %2.6f, Consumption = %2.6f\n', outputSteadyState, capitalSteadyState, consumptionSteadyState);
fprintf('\n')
% We generate the grid of capital
vGridCapital = 0.5*capitalSteadyState:0.00001:1.5*capitalSteadyState;
nGridCapital = length(vGridCapital);
nGridProductivity = length(vProductivity);
%% 3. Required matrices and vectors
mOutput = zeros(nGridCapital,nGridProductivity);
mValueFunction = zeros(nGridCapital,nGridProductivity);
mValueFunctionNew = zeros(nGridCapital,nGridProductivity);
mPolicyFunction = zeros(nGridCapital,nGridProductivity);
expectedValueFunction = zeros(nGridCapital,nGridProductivity);
%% 4. We pre-build output for each point in the grid
mOutput = (vGridCapital'.^aalpha)*vProductivity;
%% 5. Main iteration
maxDifference = 10.0;
tolerance = 0.0000001;
iteration = 0;
while (maxDifference>tolerance)
expectedValueFunction = mValueFunction*mTransition';
for nProductivity = 1:nGridProductivity
% We start from previous choice (monotonicity of policy function)
gridCapitalNextPeriod = 1;
for nCapital = 1:nGridCapital
valueHighSoFar = -1000.0;
capitalChoice = vGridCapital(1);
for nCapitalNextPeriod = gridCapitalNextPeriod:nGridCapital
consumption = mOutput(nCapital,nProductivity)-vGridCapital(nCapitalNextPeriod);
valueProvisional = (1-bbeta)*log(consumption)+bbeta*expectedValueFunction(nCapitalNextPeriod,nProductivity);
if (valueProvisional>valueHighSoFar)
valueHighSoFar = valueProvisional;
capitalChoice = vGridCapital(nCapitalNextPeriod);
gridCapitalNextPeriod = nCapitalNextPeriod;
else
break; % We break when we have achieved the max
end
end
mValueFunctionNew(nCapital,nProductivity) = valueHighSoFar;
mPolicyFunction(nCapital,nProductivity) = capitalChoice;
end
end
maxDifference = max(max(abs(mValueFunctionNew-mValueFunction)));
mValueFunction = mValueFunctionNew;
iteration = iteration+1;
if (mod(iteration,10)==0 || iteration ==1)
fprintf(' Iteration = %d, Sup Diff = %2.8f\n', iteration, maxDifference);
end
end
fprintf(' Iteration = %d, Sup Diff = %2.8f\n', iteration, maxDifference);
fprintf('\n')
fprintf(' My check = %2.6f\n', mPolicyFunction(1000,3));
fprintf('\n')
toc
%% 6. Plotting results
figure(1)
subplot(3,1,1)
plot(vGridCapital,mValueFunction)
xlim([vGridCapital(1) vGridCapital(nGridCapital)])
title('Value Function')
subplot(3,1,2)
plot(vGridCapital,mPolicyFunction)
xlim([vGridCapital(1) vGridCapital(nGridCapital)])
title('Policy Function')
vExactPolicyFunction = aalpha*bbeta.*(vGridCapital.^aalpha);
subplot(3,1,3)
plot((100.*(vExactPolicyFunction'-mPolicyFunction(:,3))./mPolicyFunction(:,3)))
title('Comparison of Exact and Approximated Policy Function')
%set(gcf,'PaperOrientation','landscape','PaperPosition',[-0.9 -0.5 12.75 9])
%print('-dpdf','Figure1.pdf')