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Supply of Food, Feed, and Forestry |
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v5.4 |
- Inputs to the Module
- Description
- Equations
- Insights and intuition
- Policy options
- IAMC Reference Card
- References
Table 1: Inputs required by the supply module 1
Name | Resolution | Unit | Source |
---|---|---|---|
Land use and land cover | By GLU, land type, and year | thousand |
Land Allocator |
Historical harvested area (used to calculate historical yield) | By GLU, crop, management practice, and year | thousand |
Exogenous |
Historical production (used to calculate historical yield) | By GLU, crop, management practice, and year | thousand |
Exogenous |
Agriculture productivity growth (used to calculate future yield) | By GLU, crop, management practice, year | % per year | Exogenous |
Non-fertilizer, non-water, non-land variable cost of production | By GLU, crop, management practice, and year | 1975$/kg | Exogenous |
Fertilizer coefficients | By GLU, crop, management practice, and year | 1975$/kg | Exogenous |
Water coefficients | By GLU, crop, management practice, and year | 1975$/kg | Exogenous |
Commodity prices | By region, commodity, and year | 1975$/kg | Marketplace |
Fertilizer prices | By region, commodity, and year | 1975$/kg | Marketplace |
Water prices | By basin and year | 1975$/m3 | Marketplace |
1: Note that this table differs from the one provided on the Supply Inputs Page in that it lists all inputs to the land supply module, including information passed from other modules. Additionally, the units listed are the units GCAM requires, rather than the units the raw input data uses.
Variable costs are defined here as the non-land costs of crop production, per-unit of crop. We model the cost of fertilizer and water explicitly, including input-output coefficients and prices of each. Other components of variable cost are derived from USDA cost data.
Variable costs set hard price floors in the model: production goes to zero when price is less than or equal to the variable costs. As a result, these costs should be interpreted as pure minimum or shut-down costs. They should be just the cost of materials and hired labor for producing a crop or product with a given technology in a subregion.
Value-added categories are not included in the variable costs. In addition, variable costs do not include land costs, as the model is based on allocating land on per unit profits. They should also not include cost categories that represent return to capital or profits. We can assume these costs are captured in the distribution of profit rates behind the logit. Otherwise, consider that if these costs are put into our variable costs, ultimately all marginal profit rates (from economic theory) would be zero and provide no value to our modeling. In addition, accounting costs such as depreciation should not be part of variable costs.
Data on labor costs can be difficult to use, since some farm wage categories are income that the farmer either earns or expects to be paid and thus, some labor costs are really profit to the land-owner (i.e., farmer). Therefore, we have restricted our variable cost data to include what is labeled as “hired labor”.
Note that introducing variable costs that differ by region can result in unintended consequences. Different variable costs create different price floors, which can result in a region ceasing production of a particular product if technical change lowers the global product price significantly (i.e., to a point where the variable cost is less than the price received).
The main points can be summarized as:
- Variable costs create price floors
- Variable costs should be based on technology data. They should not be used as calibration parameters to adjust profits.
- Variable costs should not include land costs, value-added categories of land, return to capital, and owner-wages.
Profit rate for all agricultural production technologies is calculated as:
where
See calcProfitRate
in ag_production_technology.cpp.
Agricultural supply is calculated as:
where
See calcSupply
in ag_production_technology.cpp.
For technologies that have production in the historical period, yield for the historical period is calculated as:
For all technologies, future yield is calculated as:
where
See initCalc
in ag_production_technology.cpp.
GCAM uses one of two different logit formulations to calculate the shares for each technology or subsector. For livestock, subsectors represent different production systems, where technologies represent different feed sources.
The first option, also known as the relative-cost-logit
, is:
where
The second option, also known as the absolute-cost-logit
, is:
where
See relative cost logit and absolute cost logit.
To be completed...
To be completed...
Agricultural commodities
- Wheat
- Rice
- Other coarse grains
- Oilseeds
- Sugar crops
- Ruminant meat
- Non-ruminant meat and eggs
- Dairy products