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REPRO-Bench / 14 /replication_package /Replication /Code /ESLR_Analysis_IVCenso.do
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*****************************************************
*** ESLR: LR Ag Outcomes - RD Analysis - Censo IV ***
*****************************************************
capture log close
clear
set matsize 3000
set more off
set scheme s2color
** Set Workspace **
cd /Users/`c(username)'/Dropbox/Research_ElSalvador_LandReform/Replication
** ssc install rdrobust; winsor2; outreg2; lpoly; cmogram; dm88_1; grqreg; gr0002_3; pdslasso; lassopack; univar; ietoolkit
*********************
*** Load the Data ***
*********************
use "Data/censo_ag_wreform.dta", clear
label var Above500 "Above 500 Ha"
label var norm_dist "Normalized Distance to Reform Threshold (has)"
label var own_amt "Cumulative Landholdings of Former Owner (has)"
*********************
*** Set RD Params ***
*********************
** Baseline: Will use local linear rd with MSE optimal bandwidth
** with ses clustered at propietor level.
** Will use rdrobust package: net install rdrobust, from(https://sites.google.com/site/rdpackages/rdrobust/stata) replace
local polynomial_level 1
local bandwidth_choice "mserd"
local kernel_choice "tri"
local cluster_level "Expropretario_ISTA"
*********************************************
*** OUTCOME 1 - AGRICULTURAL PRODUCTIVITY ***
*********************************************
*Logs OF REVENUE:
rdrobust ln_agprod_pricew_crops norm_dist, c(0) p(`polynomial_level') bwselect(`bandwidth_choice') kernel(`kernel_choice') vce(cluster `cluster_level')
* outreg results
distinct `cluster_level' if norm_dist < `e(h_l)' & norm_dist > -1*`e(h_r)' & `e(outcomevar)'!=. & `e(runningvar)'!=.
local n_clust = `r(ndistinct)'
su `e(outcomevar)' if norm_dist < `e(h_l)' & norm_dist > -1*`e(h_r)'
outreg2 using "Output/Table4_LogProductivity_agg.tex", replace se tex noobs addstat(Observations, `e(N_h_l)' + `e(N_h_r)', Clusters, `n_clust', Mean Dep. Var., `r(mean)', Bandwidth, `e(h_l)') addtext(Fuzzy RD, N)
rdrobust ln_agprod_pricew_crops norm_dist, c(0) p(`polynomial_level') bwselect(`bandwidth_choice') kernel(`kernel_choice') vce(cluster `cluster_level') fuzzy(reform sharpbw)
* outreg results
distinct `cluster_level' if norm_dist < `e(h_l)' & norm_dist > -1*`e(h_r)' & `e(outcomevar)'!=. & `e(runningvar)'!=.
local n_clust = `r(ndistinct)'
su `e(outcomevar)' if norm_dist < `e(h_l)' & norm_dist > -1*`e(h_r)'
outreg2 using "Output/Table4_LogProductivity_agg.tex", append se tex noobs addstat(Observations, `e(N_h_l)' + `e(N_h_r)', Clusters, `n_clust', Mean Dep. Var., `r(mean)', Bandwidth, `e(h_l)') addtext(Fuzzy RD, Y)
* rdpower ln_agprod_pricew_crops norm_dist, c(0) tau(1) vce(cluster Expropretario_ISTA ) plot
**** NET OF COSTS w/o Labor costs:
rdrobust ln_agprod norm_dist, c(0) p(`polynomial_level') bwselect(`bandwidth_choice') kernel(`kernel_choice') vce(cluster `cluster_level')
* outreg results
distinct `cluster_level' if norm_dist < `e(h_l)' & norm_dist > -1*`e(h_r)' & `e(outcomevar)'!=. & `e(runningvar)'!=.
local n_clust = `r(ndistinct)'
su `e(outcomevar)' if norm_dist < `e(h_l)' & norm_dist > -1*`e(h_r)'
outreg2 using "Output/Table4_LogProductivity_agg.tex", append se tex noobs addstat(Observations, `e(N_h_l)' + `e(N_h_r)', Clusters, `n_clust', Mean Dep. Var., `r(mean)', Bandwidth, `e(h_l)') addtext(Fuzzy RD, N)
rdrobust ln_agprod norm_dist, c(0) p(`polynomial_level') bwselect(`bandwidth_choice') kernel(`kernel_choice') vce(cluster `cluster_level') fuzzy(reform sharpbw)
* outreg results
distinct `cluster_level' if norm_dist < `e(h_l)' & norm_dist > -1*`e(h_r)' & `e(outcomevar)'!=. & `e(runningvar)'!=.
local n_clust = `r(ndistinct)'
su `e(outcomevar)' if norm_dist < `e(h_l)' & norm_dist > -1*`e(h_r)'
outreg2 using "Output/Table4_LogProductivity_agg.tex", append se tex noobs addstat(Observations, `e(N_h_l)' + `e(N_h_r)', Clusters, `n_clust', Mean Dep. Var., `r(mean)', Bandwidth, `e(h_l)') addtext(Fuzzy RD, Y)
**** TFP PRODUCTIVITY:
rdrobust ln_tfp_geo norm_dist, c(0) p(`polynomial_level') bwselect(`bandwidth_choice') kernel(`kernel_choice') vce(cluster `cluster_level')
* outreg results
distinct `cluster_level' if norm_dist < `e(h_l)' & norm_dist > -1*`e(h_r)' & `e(outcomevar)'!=. & `e(runningvar)'!=.
local n_clust = `r(ndistinct)'
su `e(outcomevar)' if norm_dist < `e(h_l)' & norm_dist > -1*`e(h_r)'
outreg2 using "Output/Table4_LogProductivity_agg.tex", append se tex noobs addstat(Observations, `e(N_h_l)' + `e(N_h_r)', Clusters, `n_clust', Mean Dep. Var., `r(mean)', Bandwidth, `e(h_l)') addtext(Fuzzy RD, N)
rdrobust ln_tfp_geo norm_dist, c(0) p(`polynomial_level') bwselect(`bandwidth_choice') kernel(`kernel_choice') vce(cluster `cluster_level') fuzzy(reform sharpbw)
* outreg results
distinct `cluster_level' if norm_dist < `e(h_l)' & norm_dist > -1*`e(h_r)' & `e(outcomevar)'!=. & `e(runningvar)'!=.
local n_clust = `r(ndistinct)'
su `e(outcomevar)' if norm_dist < `e(h_l)' & norm_dist > -1*`e(h_r)'
outreg2 using "Output/Table4_LogProductivity_agg.tex", append se tex noobs addstat(Observations, `e(N_h_l)' + `e(N_h_r)', Clusters, `n_clust', Mean Dep. Var., `r(mean)', Bandwidth, `e(h_l)') addtext(Fuzzy RD, Y)
******************************
*** OUTCOME 2 - CASH CROPS ***
******************************
rdrobust CashCrop_Indicator norm_dist, c(0) p(`polynomial_level') bwselect(`bandwidth_choice') kernel(`kernel_choice') vce(cluster `cluster_level')
* outreg results
distinct `cluster_level' if norm_dist < `e(h_l)' & norm_dist > -1*`e(h_r)' & `e(outcomevar)'!=. & `e(runningvar)'!=.
local n_clust = `r(ndistinct)'
su `e(outcomevar)' if norm_dist < `e(h_l)' & norm_dist > -1*`e(h_r)'
*outreg2 using "Output/Table2_CashCrops_agg.tex", replace se tex noobs addstat(Observations, `e(N_h_l)' + `e(N_h_r)', Clusters, `n_clust', Mean Dep. Var., `r(mean)', Bandwidth, `e(h_l)')
rdrobust CashCrop_Share norm_dist, c(0) p(`polynomial_level') bwselect(`bandwidth_choice') kernel(`kernel_choice') vce(cluster `cluster_level')
* outreg results
distinct `cluster_level' if norm_dist < `e(h_l)' & norm_dist > -1*`e(h_r)' & `e(outcomevar)'!=. & `e(runningvar)'!=.
local n_clust = `r(ndistinct)'
su `e(outcomevar)' if norm_dist < `e(h_l)' & norm_dist > -1*`e(h_r)'
outreg2 using "Output/Table2_CashCrops_agg.tex", replace se tex noobs addstat(Observations, `e(N_h_l)' + `e(N_h_r)', Clusters, `n_clust', Mean Dep. Var., `r(mean)', Bandwidth, `e(h_l)')
** Sugar Cane:
rdrobust SugarCane_Indicator norm_dist, c(0) p(`polynomial_level') bwselect(`bandwidth_choice') kernel(`kernel_choice') vce(cluster `cluster_level')
* outreg results
distinct `cluster_level' if norm_dist < `e(h_l)' & norm_dist > -1*`e(h_r)' & `e(outcomevar)'!=. & `e(runningvar)'!=.
local n_clust = `r(ndistinct)'
su `e(outcomevar)' if norm_dist < `e(h_l)' & norm_dist > -1*`e(h_r)'
outreg2 using "Output/Table2_CashCrops_agg.tex", append se tex noobs addstat(Observations, `e(N_h_l)' + `e(N_h_r)', Clusters, `n_clust', Mean Dep. Var., `r(mean)', Bandwidth, `e(h_l)')
rdrobust SugarCane_Share norm_dist, c(0) p(`polynomial_level') bwselect(`bandwidth_choice') kernel(`kernel_choice') vce(cluster `cluster_level')
* outreg results
distinct `cluster_level' if norm_dist < `e(h_l)' & norm_dist > -1*`e(h_r)' & `e(outcomevar)'!=. & `e(runningvar)'!=.
local n_clust = `r(ndistinct)'
su `e(outcomevar)' if norm_dist < `e(h_l)' & norm_dist > -1*`e(h_r)'
outreg2 using "Output/Table2_CashCrops_agg.tex", append se tex noobs addstat(Observations, `e(N_h_l)' + `e(N_h_r)', Clusters, `n_clust', Mean Dep. Var., `r(mean)', Bandwidth, `e(h_l)')
* Note: small sample means cannot compute optimal bw. Setting BW manually at level in previous regression:
rdrobust SugarCane_Yield norm_dist, c(0) p(`polynomial_level') h(`e(h_r)') b(`e(b_r)') kernel(`kernel_choice') vce(cluster `cluster_level')
* outreg results
distinct `cluster_level' if norm_dist < `e(h_l)' & norm_dist > -1*`e(h_r)' & `e(outcomevar)'!=. & `e(runningvar)'!=.
local n_clust = `r(ndistinct)'
su `e(outcomevar)' if norm_dist < `e(h_l)' & norm_dist > -1*`e(h_r)'
outreg2 using "Output/Table2_CashCrops_agg.tex", append se tex noobs addstat(Observations, `e(N_h_l)' + `e(N_h_r)', Clusters, `n_clust', Mean Dep. Var., `r(mean)', Bandwidth, `e(h_l)')
** Coffee:
rdrobust Coffee_Indicator norm_dist, c(0) p(`polynomial_level') bwselect(`bandwidth_choice') kernel(`kernel_choice') vce(cluster `cluster_level')
* outreg results
distinct `cluster_level' if norm_dist < `e(h_l)' & norm_dist > -1*`e(h_r)' & `e(outcomevar)'!=. & `e(runningvar)'!=.
local n_clust = `r(ndistinct)'
su `e(outcomevar)' if norm_dist < `e(h_l)' & norm_dist > -1*`e(h_r)' & `e(outcomevar)'!=. & `e(runningvar)'!=.
outreg2 using "Output/Table2_CashCrops_agg.tex", append se tex noobs addstat(Observations, `e(N_h_l)' + `e(N_h_r)', Clusters, `n_clust', Mean Dep. Var., `r(mean)', Bandwidth, `e(h_l)')
rdrobust Coffee_Share norm_dist, c(0) p(`polynomial_level') bwselect(`bandwidth_choice') kernel(`kernel_choice') vce(cluster `cluster_level')
* outreg results
distinct `cluster_level' if norm_dist < `e(h_l)' & norm_dist > -1*`e(h_r)' & `e(outcomevar)'!=. & `e(runningvar)'!=.
local n_clust = `r(ndistinct)'
su `e(outcomevar)' if norm_dist < `e(h_l)' & norm_dist > -1*`e(h_r)' & `e(outcomevar)'!=. & `e(runningvar)'!=.
outreg2 using "Output/Table2_CashCrops_agg.tex", append se tex noobs addstat(Observations, `e(N_h_l)' + `e(N_h_r)', Clusters, `n_clust', Mean Dep. Var., `r(mean)', Bandwidth, `e(h_l)')
rdrobust Coffee_Yield norm_dist, c(0) p(`polynomial_level') bwselect(`bandwidth_choice') kernel(`kernel_choice') vce(cluster `cluster_level')
* outreg results
distinct `cluster_level' if norm_dist < `e(h_l)' & norm_dist > -1*`e(h_r)' & `e(outcomevar)'!=. & `e(runningvar)'!=.
local n_clust = `r(ndistinct)'
su `e(outcomevar)' if norm_dist < `e(h_l)' & norm_dist > -1*`e(h_r)' & `e(outcomevar)'!=. & `e(runningvar)'!=.
outreg2 using "Output/Table2_CashCrops_agg.tex", append se tex noobs addstat(Observations, `e(N_h_l)' + `e(N_h_r)', Clusters, `n_clust', Mean Dep. Var., `r(mean)', Bandwidth, `e(h_l)')
********************************
*** OUTCOME 3 - STAPLE CROPS ***
********************************
rdrobust ConsCrop_Indicator norm_dist, c(0) p(`polynomial_level') bwselect(`bandwidth_choice') kernel(`kernel_choice') vce(cluster `cluster_level')
* outreg results
distinct `cluster_level' if norm_dist < `e(h_l)' & norm_dist > -1*`e(h_r)' & `e(outcomevar)'!=. & `e(runningvar)'!=.
local n_clust = `r(ndistinct)'
su `e(outcomevar)' if norm_dist < `e(h_l)' & norm_dist > -1*`e(h_r)'
*outreg2 using "Output/Table3_ConsCrops_agg.tex", replace se tex noobs addstat(Observations, `e(N_h_l)' + `e(N_h_r)', Clusters, `n_clust', Mean Dep. Var., `r(mean)', Bandwidth, `e(h_l)')
rdrobust StapleCrop_Share norm_dist, c(0) p(`polynomial_level') bwselect(`bandwidth_choice') kernel(`kernel_choice') vce(cluster `cluster_level')
* outreg results
distinct `cluster_level' if norm_dist < `e(h_l)' & norm_dist > -1*`e(h_r)' & `e(outcomevar)'!=. & `e(runningvar)'!=.
local n_clust = `r(ndistinct)'
su `e(outcomevar)' if norm_dist < `e(h_l)' & norm_dist > -1*`e(h_r)'
outreg2 using "Output/Table3_ConsCrops_agg.tex", replace se tex noobs addstat(Observations, `e(N_h_l)' + `e(N_h_r)', Clusters, `n_clust', Mean Dep. Var., `r(mean)', Bandwidth, `e(h_l)')
** Maize:
rdrobust Maize_Indicator norm_dist, c(0) p(`polynomial_level') bwselect(`bandwidth_choice') kernel(`kernel_choice') vce(cluster `cluster_level')
* Check this. Strange since rd plot is so strong.
* outreg results
distinct `cluster_level' if norm_dist < `e(h_l)' & norm_dist > -1*`e(h_r)' & `e(outcomevar)'!=. & `e(runningvar)'!=.
local n_clust = `r(ndistinct)'
su `e(outcomevar)' if norm_dist < `e(h_l)' & norm_dist > -1*`e(h_r)'
outreg2 using "Output/Table3_ConsCrops_agg.tex", append se tex noobs addstat(Observations, `e(N_h_l)' + `e(N_h_r)', Clusters, `n_clust', Mean Dep. Var., `r(mean)', Bandwidth, `e(h_l)')
rdrobust Maize_Share norm_dist, c(0) p(`polynomial_level') bwselect(`bandwidth_choice') kernel(`kernel_choice') vce(cluster `cluster_level')
distinct `cluster_level' if norm_dist < `e(h_l)' & norm_dist > -1*`e(h_r)' & `e(outcomevar)'!=. & `e(runningvar)'!=.
local n_clust = `r(ndistinct)'
su `e(outcomevar)' if norm_dist < `e(h_l)' & norm_dist > -1*`e(h_r)'
outreg2 using "Output/Table3_ConsCrops_agg.tex", append se tex noobs addstat(Observations, `e(N_h_l)' + `e(N_h_r)', Clusters, `n_clust', Mean Dep. Var., `r(mean)', Bandwidth, `e(h_l)')
rdrobust Maize_Yield norm_dist, c(0) p(`polynomial_level') bwselect(`bandwidth_choice') kernel(`kernel_choice') vce(cluster `cluster_level')
distinct `cluster_level' if norm_dist < `e(h_l)' & norm_dist > -1*`e(h_r)' & `e(outcomevar)'!=. & `e(runningvar)'!=.
local n_clust = `r(ndistinct)'
su `e(outcomevar)' if norm_dist < `e(h_l)' & norm_dist > -1*`e(h_r)'
outreg2 using "Output/Table3_ConsCrops_agg.tex", append se tex noobs addstat(Observations, `e(N_h_l)' + `e(N_h_r)', Clusters, `n_clust', Mean Dep. Var., `r(mean)', Bandwidth, `e(h_l)')
** Beans:
rdrobust Beans_Indicator norm_dist, c(0) p(`polynomial_level') bwselect(`bandwidth_choice') kernel(`kernel_choice') vce(cluster `cluster_level') // fuzzy(reform)
* outreg results
distinct `cluster_level' if norm_dist < `e(h_l)' & norm_dist > -1*`e(h_r)' & `e(outcomevar)'!=. & `e(runningvar)'!=.
local n_clust = `r(ndistinct)'
su `e(outcomevar)' if norm_dist < `e(h_l)' & norm_dist > -1*`e(h_r)'
outreg2 using "Output/Table3_ConsCrops_agg.tex", append se tex noobs addstat(Observations, `e(N_h_l)' + `e(N_h_r)', Clusters, `n_clust', Mean Dep. Var., `r(mean)', Bandwidth, `e(h_l)')
rdrobust Beans_Share norm_dist, c(0) p(`polynomial_level') bwselect(`bandwidth_choice') kernel(`kernel_choice') vce(cluster `cluster_level') // fuzzy(reform)
* outreg results
distinct `cluster_level' if norm_dist < `e(h_l)' & norm_dist > -1*`e(h_r)' & `e(outcomevar)'!=. & `e(runningvar)'!=.
local n_clust = `r(ndistinct)'
su `e(outcomevar)' if norm_dist < `e(h_l)' & norm_dist > -1*`e(h_r)'
outreg2 using "Output/Table3_ConsCrops_agg.tex", append se tex noobs addstat(Observations, `e(N_h_l)' + `e(N_h_r)', Clusters, `n_clust', Mean Dep. Var., `r(mean)', Bandwidth, `e(h_l)')
* Note: Following Cannot Compute Optimal BW Above: rdrobust Beans_Yield norm_dist, c(0) p(`polynomial_level') bwselect(`bandwidth_choice') kernel(`kernel_choice') vce(cluster `cluster_level')
* Setting BW manually at level in previous regression:
rdrobust Beans_Yield norm_dist, c(0) p(`polynomial_level') b(`e(h_r)') h(`e(b_r)') kernel(`kernel_choice') vce(cluster `cluster_level')
* outreg results
distinct `cluster_level' if norm_dist < `e(h_l)' & norm_dist > -1*`e(h_r)' & `e(outcomevar)'!=. & `e(runningvar)'!=.
local n_clust = `r(ndistinct)'
su `e(outcomevar)' if norm_dist < `e(h_l)' & norm_dist > -1*`e(h_r)'
outreg2 using "Output/Table3_ConsCrops_agg.tex", append se tex noobs addstat(Observations, `e(N_h_l)' + `e(N_h_r)', Clusters, `n_clust', Mean Dep. Var., `r(mean)', Bandwidth, `e(h_l)')