minimum wage scneario

CHANGELOG.md

@@ -9,6 +9,9 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 ## [Unreleased]
 
 ### changed
+- **config** new switches `s36_minimum_wage`, `s36_scale_labor_costs`, and `s38_fix_capital_need`
+- **38_factor_costs** and **70_livestock** included labor cost scaling in case of minimum wage scenario
+- **36_employment** included calculations for of minimum wage scenario
 - **config** updated config to new module setup of MACCs
 - **51_nitrogen** moved maccs into emission modules. change of interface from vm_btm_reg to vm_emissions_reg
 - **58_peatland** moved maccs into emission modules. change of interface from vm_btm_reg to vm_emissions_reg
@@ -43,13 +46,15 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 - **57_maccs** added new Marginal Abatement Cost Curve (MACCs) data set from PBL (PBL2022)
 
 ### removed
+- **38_factor_costs** removed `mixed_reg_feb17` realization
 - **50_nr_soil_budget** old inconsistent module realizations
 - **53_methane** old inconsistent module realizations
 - **56_ghg_policy** old inconsistent module realizations
 - **57_maccs** old inconsistent module realizations
 - **15_food** removed read-in of non-needed input file "f15_calib_factor_FAOfsupply_iso"
 
 ### fixed
+- **38_factor_costs** fixed calibration of share parameter in `sticky_labor` realization
 - **59_som** corrected the som pool due to the carbon transfer from other and primary forest to secondary forest before optimization (presolve)  
 - **43_water_availability** added missing years after 2100 in "f43_wat_avail" to avoid infeasibilities in coupled runs with less_ts timesteps
 - **scripts** fixed some bugs related to background execution of start/output scripts

CITATION.cff

@@ -77,6 +77,11 @@ authors:
     affiliation: "Potsdam Institute for Climate Impact Research"
     email: crawford@pik-potsdam.de
 
+  - family-names: Leip
+    given-names: Debbora
+    affiliation: "Potsdam Institute for Climate Impact Research"
+    email: leip@pik-potsdam.de
+
   - family-names: Klein
     given-names: David
     affiliation: "Potsdam Institute for Climate Impact Research"

modules/36_employment/exo_may22/declarations.gms

@@ -15,13 +15,17 @@ positive variables
 ;
 
 parameters
- p36_hourly_costs_iso(t,iso)	   Hourly labor costs in agriculture on iso level (USDMER05 per hour)
- p36_hourly_costs(t,i)             Hourly labor costs in agriculture on regional level (USDMER05 per hour)
- p36_total_hours_worked(iso)       Total hours worked by all employed people (mio. hours per year)
- p36_calibration_hourly_costs(iso) Additive calibration term for hourly labor costs (USDMER05 per hour)
- p36_cost_share(t,i)               Capital share of factor costs (1)
- p36_share_calibration(i)          Additive calibration term for capital shares (1)
- p36_nonmagpie_labor_costs(t,i)    Labor costs from subsidies and VoP not covered by MAgPIE (mio. USDMER05)
+ p36_hourly_costs_iso_baseline(t,iso)   Hourly labor costs in agriculture on iso level (USDMER05 per hour)
+ p36_hourly_costs_increase(iso)         Difference between minimum hourly labor costs and actual hourly labor costs in 2050 (USDMER05 per hour)
+ p36_hourly_costs_iso(t,iso)            Hourly labor costs in agriculture on iso level after including minimum wage (USDMER05 per hour)
+ p36_hourly_costs_baseline(t,i)         Hourly labor costs in agriculture on regional level (USDMER05 per hour)
+ p36_hourly_costs(t,i)                  Hourly labor costs in agriculture on regional level after including minimum wage (USDMER05 per hour)
+ pm_labor_cost_scaling(t,i)             Multiplicative factor describing increase in hourly labor costs to match minimum wage (1)
+ p36_total_hours_worked(iso)            Total hours worked by all employed people (mio. hours per year)
+ p36_calibration_hourly_costs(iso)      Additive calibration term for hourly labor costs (USDMER05 per hour)
+ p36_cost_share(t,i)                    Capital share of factor costs (1)
+ p36_share_calibration(i)               Additive calibration term for capital shares (1)
+ p36_nonmagpie_labor_costs(t,i)         Labor costs from subsidies and VoP not covered by MAgPIE (mio. USDMER05)
 ;
 
 *#################### R SECTION START (OUTPUT DECLARATIONS) ####################

modules/36_employment/exo_may22/equations.gms

@@ -8,16 +8,16 @@
 
 *' @equations
 
+*' Employment is calculated as total labor costs devided by hourly labor costs and 
+*' average hours worked per employed person per year. Total labor costs include
+*' labor costs from crop production (see [38_factor_costs]) and livestock production 
+*' (see [70_livestock]), and some labor costs for crop and livestock production 
+*' which are not covered by MAgPIE.
+
 * excluding labor costs for crop residues (as this is not include in the 
 * data on agricultural employment by the International Labour Organization)
 * and fish (as we cannot calibrate labor costs for fish to employment data)
-
 q36_employment(i2) .. v36_employment(i2)
                               =e= (vm_cost_prod_crop(i2,"labor") + vm_cost_prod_livst(i2,"labor") + sum(ct,p36_nonmagpie_labor_costs(ct,i2))) *
                                         (1 / sum(ct,f36_weekly_hours(ct,i2)*s36_weeks_in_year*p36_hourly_costs(ct,i2)));
 
-*' Employment is calculated as total labor costs devided by hourly labor costs and 
-*' average hours worked per employed person per year. Total labor costs include
-*' labor costs from crop production (see [38_factor_costs]) and livestock production 
-*' (see [70_livestock]), and some labor costs for crop and livestock production 
-*' which are not covered by MAgPIE.

modules/36_employment/exo_may22/input.gms

@@ -7,6 +7,8 @@
 
 scalars
 s36_weeks_in_year number of weeks in a year  / 52.1429 /
+s36_minimum_wage global minimum wage / 3 /
+s36_scale_labor_costs whether total labor costs should be scaled according to wage increase / 0 /
 ;
 
 table f36_weekly_hours(t_all,i) Historical values of average weekly hours worked per person in agriculture (h per week)
@@ -66,3 +68,5 @@ $ondelim
 $include "./modules/36_employment/exo_may22/input/f36_historical_share.csv"
 $offdelim
 ;
+
+

modules/36_employment/exo_may22/preloop.gms

@@ -7,5 +7,55 @@
 
 * get calibration factors and aggregation weight
 p36_calibration_hourly_costs(iso) = sum(t_past$(ord(t_past) eq card(t_past)), f36_hist_hourly_costs(t_past,iso)-(im_gdp_pc_mer_iso(t_past,iso)
-																				*f36_regr_hourly_costs("slope")+f36_regr_hourly_costs("intercept")));
-p36_total_hours_worked(iso) = sum(t_past$(ord(t_past) eq card(t_past)), f36_historic_ag_empl(t_past,iso)*f36_weekly_hours_iso(t_past,iso)*s36_weeks_in_year); 
+                                        *f36_regr_hourly_costs("slope")+f36_regr_hourly_costs("intercept")));
+p36_total_hours_worked(iso) = sum(t_past$(ord(t_past) eq card(t_past)), f36_historic_ag_empl(t_past,iso)*f36_weekly_hours_iso(t_past,iso)*s36_weeks_in_year); 
+
+*' @code
+
+*' Hourly labor costs are projected into the future by using a linear regression with
+*' GDPpcMER, which is calibrated such that historic values of agricultural employment 
+*' are met. A threshold is used in the regression to avoid too low or negative hourly
+*' labor costs.
+p36_hourly_costs_iso_baseline(t,iso) = max((im_gdp_pc_mer_iso(t,iso)*f36_regr_hourly_costs("slope") + f36_regr_hourly_costs("intercept") + p36_calibration_hourly_costs(iso)), f36_regr_hourly_costs("threshold"));
+
+*' @stop
+
+p36_hourly_costs_iso_baseline(t,iso)$(sum(sameas(t_past,t),1) = 1) = f36_hist_hourly_costs(t,iso);
+
+
+* necessary increase in hourly labor costs in target year (2050) to match minimum wage
+p36_hourly_costs_increase(iso) = s36_minimum_wage-p36_hourly_costs_iso_baseline("y2050",iso);
+
+p36_hourly_costs_iso(t,iso) = p36_hourly_costs_iso_baseline(t,iso); 
+
+*' @code
+*' In case of a scenario with an external global minimum wage we add a linear term to the baseline 
+*' hourly labor costs, starting from 0 zero in 2020 and increasing such that resulting hourly labor costs will match
+*' the minimum wage in 2050. After 2050 the additional term is decreased again, reaching 0 in 2100 (where baseline 
+*' hourly labor costs and new hourly labor costs will match again). 
+*' In case this means that hourly labor costs would decrease again below the minimum wage after 2050, we keep them 
+*' at minimum wage.
+*' If baseline hourly labor costs are already high enough to meet the minimum wage in 2050, they are not changed.
+*' @stop
+
+p36_hourly_costs_iso(t,iso)$((m_year(t) gt 2020) and (m_year(t) le 2050)) = p36_hourly_costs_iso_baseline(t,iso) + max(0, ((m_year(t)-2020)/(2050-2020))*p36_hourly_costs_increase(iso));
+
+p36_hourly_costs_iso(t,iso)$((m_year(t) gt 2050) and (m_year(t) le 2100)) = max(s36_minimum_wage, p36_hourly_costs_iso_baseline(t,iso) + max(0, p36_hourly_costs_increase(iso)-((m_year(t)-2050)/(2100-2050))*p36_hourly_costs_increase(iso)));
+
+* Hourly labor costs are then aggregated to regional level using the total hours worked in the last
+* year of `t_past` as weight.
+p36_hourly_costs_baseline(t,i) = sum(i_to_iso(i,iso), p36_hourly_costs_iso_baseline(t,iso)*p36_total_hours_worked(iso)) * (1/sum(i_to_iso(i,iso),p36_total_hours_worked(iso)));
+p36_hourly_costs(t,i) = sum(i_to_iso(i,iso), p36_hourly_costs_iso(t,iso)*p36_total_hours_worked(iso))*(1/sum(i_to_iso(i,iso),p36_total_hours_worked(iso)));
+
+*' @code
+*' If productivity is assumed to increase proportional to hourly labor costs also with external minimum wage,
+*' total labor costs should not be scaled. Otherwise, the scaling factor between baseline and increased hourly labor costs will
+*' be applied to labor costs for crop production ([38_factor_costs]), livestock production ([70_livestock]), and the
+*' non-MAgPIE labor costs.
+if (s36_scale_labor_costs eq 0,
+  pm_labor_cost_scaling(t,i) = 1;
+elseif (s36_scale_labor_costs eq 1),
+  pm_labor_cost_scaling(t,i) = p36_hourly_costs(t,i) / p36_hourly_costs_baseline(t,i);
+);
+*' @stop
+

modules/36_employment/exo_may22/presolve.gms

@@ -20,24 +20,6 @@ elseif (m_year(t)>=2010),
 *' categories not covered by MAgPIE (i.e. wool, beeswax, honey, silk-worms), which 
 *' are both kept constant for future years. 
 
-p36_nonmagpie_labor_costs(t,i) = (f36_unspecified_subsidies(t,i) + f36_nonmagpie_factor_costs(t,i)) * (1-p36_cost_share(t,i));
-
-
-*' Hourly labor costs are projected into the future by using a linear regression with
-*' GDPpcMER, which is calibrated such that historic values of agricultural employment 
-*' are met.
+p36_nonmagpie_labor_costs(t,i) = (f36_unspecified_subsidies(t,i) + f36_nonmagpie_factor_costs(t,i)) * (1-p36_cost_share(t,i)) * pm_labor_cost_scaling(t,i);
 
 *' @stop
-
-* historic hourly labor costs for t_past, calibrated regression values based on GDPpcMER for future years
-* A threshold of 0.1$/h is used in the regression to avoid too low or negative hourly labor costs.
-if (sum(sameas(t_past,t),1) = 1,
-	p36_hourly_costs_iso(t,iso) = f36_hist_hourly_costs(t,iso)
-else
-	p36_hourly_costs_iso(t,iso) = max((im_gdp_pc_mer_iso(t,iso)*f36_regr_hourly_costs("slope")+
-							 	 f36_regr_hourly_costs("intercept")+p36_calibration_hourly_costs(iso)), 
-								 f36_regr_hourly_costs("threshold"));
-);
-
-
-p36_hourly_costs(t,i) = sum(i_to_iso(i,iso),p36_hourly_costs_iso(t,iso)*p36_total_hours_worked(iso))*(1/sum(i_to_iso(i,iso),p36_total_hours_worked(iso)));

modules/36_employment/exo_may22/realization.gms

@@ -8,8 +8,9 @@
 *' @description This realization calculates agricultural employment based
 *' on it's relation to total labor costs. It therefore depends 
 *' on the labor costs calculated in the modules [38_factor_costs] and 
-*' [70_livestock], but does not affect resulting total costs or production 
-*' patterns.
+*' [70_livestock]. Resulting total costs and production patterns can be affected
+*' if an external minimum wage is set, which increases labor costs for
+*' crop and livestock production in [38_factor_costs] and [70_livestock].
 
 *' @limitations Labor availability is not seen as a limiting factor for
 *' agricultural production, as the number of people employed is directly linked

modules/36_employment/module.gms

@@ -10,9 +10,12 @@
 
 *' @description This module is used to calculate hourly labor costs in agriculutre
 *' and the number of people employed in crop and livestock production. 
-*' The calculation is based on labor costs in crop and livestock production
-*' coming from [38_factor_costs] and [70_livestock], as well as GDP pc from
-*' [09_drivers]. 
+*' Hourly labor costs are calculated based on a regression with GDP pc from [09_drivers].
+*' They can be increased by an externally set global minimum wage, and the module
+*' provides a scaling factor for labor costs to [38_factor_costs] and [70_livestock], 
+*' to increase total labor costs according to the increase in hourly labor costs.
+*' The calculation of employment then uses labor costs for crop and livestock production
+*' coming from [38_factor_costs] and [70_livestock].
 
 *' @authors Debbora Leip