| | |
| | clear |
| | set more off |
| | set scheme s1mono |
| |
|
| | cd "$path" |
| | global data_files "$path/Data" |
| | global out_files "$path/output" |
| |
|
| | |
| | |
| | |
| | use "$data_files/firm_enf.dta", clear |
| | keep if min_dist<50 & starty<=2010 |
| | drop if revenue == . |
| | drop if key == . |
| |
|
| | label var min_dist_10 "Mon\$\_{<10km}\$" |
| | label var any_air "Any Enforcement (0/1)" |
| | label var post "Post" |
| | label var key "High Pollution" |
| |
|
| | gen min_dist_10_post1 = c.min_dist_10#c.post1 |
| | egen ind_time = group(industry prov_id time) |
| |
|
| | reg2hdfespatial any_air min_dist_10_post1, lat(lat) lon(lon) timevar(time) panelvar(id) altfetime(ind_time) distcutoff(100) lagcutoff(20) |
| | scalar Conley1 = _se[min_dist_10_post1] |
| |
|
| | reg2hdfespatial any_air_shutdown min_dist_10_post1, lat(lat) lon(lon) timevar(time) panelvar(id) altfetime(ind_time) distcutoff(100) lagcutoff(20) |
| | scalar Conley2 = _se[min_dist_10_post1] |
| |
|
| | reg2hdfespatial any_air_renovate min_dist_10_post1, lat(lat) lon(lon) timevar(time) panelvar(id) altfetime(ind_time) distcutoff(100) lagcutoff(20) |
| | scalar Conley3 = _se[min_dist_10_post1] |
| |
|
| | reg2hdfespatial any_air_fine min_dist_10_post1, lat(lat) lon(lon) timevar(time) panelvar(id) altfetime(ind_time) distcutoff(100) lagcutoff(20) |
| | scalar Conley4 = _se[min_dist_10_post1] |
| |
|
| | reg2hdfespatial any_air_warning min_dist_10_post1, lat(lat) lon(lon) timevar(time) panelvar(id) altfetime(ind_time) distcutoff(100) lagcutoff(20) |
| | scalar Conley5 = _se[min_dist_10_post1] |
| |
|
| | use "$data_files/firm_enf.dta", clear |
| | drop if revenue == . |
| | drop if key == . |
| |
|
| | label var min_dist_10 "Mon\$\_{<10km}\$" |
| | label var any_air "Any Enforcement (0/1)" |
| | label var post "Post" |
| | label var key "High Pollution" |
| |
|
| | eststo clear |
| | reghdfe any_air c.min_dist_10#c.post1 if min_dist<50 & starty<=2010, absorb(time id industry#time prov_id#time) cluster(city_id) |
| | eststo A |
| | estadd ysumm, mean |
| | estadd scalar EN = e(N_full) |
| | estadd local Conley = "[`: di %9.5f Conley1']" |
| | reghdfe any_air_shutdown c.min_dist_10#c.post1 if min_dist<50 & starty<=2010, absorb(time id industry#time prov_id#time) cluster(city_id) |
| | eststo B |
| | estadd ysumm, mean |
| | estadd scalar EN = e(N_full) |
| | estadd local Conley = "[`: di %9.5f Conley2']" |
| | reghdfe any_air_renovate c.min_dist_10#c.post1 if min_dist<50 & starty<=2010, absorb(time id industry#time prov_id#time) cluster(city_id) |
| | eststo C |
| | estadd ysumm, mean |
| | estadd scalar EN = e(N_full) |
| | estadd local Conley = "[`: di %9.5f Conley3']" |
| | reghdfe any_air_fine c.min_dist_10#c.post1 if min_dist<50 & starty<=2010, absorb(time id industry#time prov_id#time) cluster(city_id) |
| | eststo D |
| | estadd ysumm, mean |
| | estadd scalar EN = e(N_full) |
| | estadd local Conley = "[`:di %9.5f Conley4']" |
| | reghdfe any_air_warning c.min_dist_10#c.post1 if min_dist<50 & starty<=2010, absorb(time id industry#time prov_id#time) cluster(city_id) |
| | eststo E |
| | estadd ysumm, mean |
| | estadd scalar EN = e(N_full) |
| | estadd local Conley = "[`:di %9.5f Conley5']" |
| | esttab A B C D E using "$out_files/Table1a.tex", replace b(a2) noconstant se(a2) nolines nogaps compress fragment nonumbers label mlabels(none) collabels() keep(c.min_dist_10*) stats(ymean EN Conley, labels("Mean Outcome" "Observations" "Conley SE")) starlevels(* 0.10 ** 0.05 *** 0.01) substitute(\_ _) tex |
| |
|
| | |
| | use "$data_files/firm_enf.dta", clear |
| | drop if revenue == . |
| | drop if key == . |
| |
|
| | label var min_dist_10 "Mon\$\_{<10km}\$" |
| | label var any_air "Any Enforcement (0/1)" |
| | label var post "Post" |
| | label var key "High Pollution" |
| |
|
| | eststo clear |
| | reghdfe air c.min_dist_10#c.post1##c.key if min_dist<50 & starty<=2010, absorb(time id industry#time prov_id#time) cluster(city_id) |
| | eststo A |
| | estadd ysumm, mean |
| | estadd scalar EN = e(N_full) |
| | reghdfe air_1 c.min_dist_10#c.post1##c.key if min_dist<50 & starty<=2010, absorb(time id industry#time prov_id#time) cluster(city_id) |
| | eststo B |
| | estadd ysumm, mean |
| | estadd scalar EN = e(N_full) |
| | reghdfe air_2 c.min_dist_10#c.post1##c.key if min_dist<50 & starty<=2010, absorb(time id industry#time prov_id#time) cluster(city_id) |
| | eststo C |
| | estadd ysumm, mean |
| | estadd scalar EN = e(N_full) |
| | reghdfe leni c.min_dist_10#c.post1##c.key if min_dist<50 & starty<=2010, absorb(time id industry#time prov_id#time) cluster(city_id) |
| | eststo D |
| | estadd ysumm, mean |
| | estadd scalar EN = e(N_full) |
| | reghdfe stri c.min_dist_10#c.post1##c.key if min_dist<50 & starty<=2010, absorb(time id industry#time prov_id#time) cluster(city_id) |
| | eststo E |
| | estadd ysumm, mean |
| | estadd scalar EN = e(N_full) |
| | esttab A B C D E using "$out_files/Table1b.tex", replace b(a2) noconstant se(a2) nolines nogaps compress fragment nonumbers label mlabels(none) collabels() keep(c.min_dist_10*) stats(ymean EN, labels("Mean Outcome" "Observations")) starlevels(* 0.10 ** 0.05 *** 0.01) substitute(\_ _) tex |
| |
|
| | |
| | gen Shock = high_pre |
| | eststo clear |
| | reghdfe any_air c.min_dist_10#c.post1##c.Shock tem_mean if min_dist<50 & starty<=2010, absorb(time id industry#time prov_id#time) cluster(city_id) |
| | eststo A |
| | estadd ysumm, mean |
| | estadd scalar EN = e(N_full) |
| | reghdfe any_air c.min_dist_10##c.post1##c.Shock tem_mean if min_dist<50 & starty<=2010, absorb(time id industry#time prov_id#time) cluster(city_id) |
| | eststo B |
| | estadd ysumm, mean |
| | estadd scalar EN = e(N_full) |
| | replace Shock = upwd |
| | reghdfe any_air c.min_dist_10#c.post1##c.Shock tem_mean if min_dist<50 & starty<=2010, absorb(time id industry#time prov_id#time) cluster(city_id) |
| | eststo C |
| | estadd ysumm, mean |
| | estadd scalar EN = e(N_full) |
| | reghdfe any_air c.min_dist_10##c.post1##c.Shock tem_mean if min_dist<50 & starty<=2010, absorb(time id industry#time prov_id#time) cluster(city_id) |
| | eststo D |
| | estadd ysumm, mean |
| | estadd scalar EN = e(N_full) |
| | esttab A B C D using "$out_files/Table2.tex", replace b(a2) noconstant se(a2) nolines nogaps compress fragment nonumbers label mlabels(none) collabels() keep() drop(_cons tem_mean post1 min_dist_10) order(Shock c.min_dist_10#c.post1 c.min_dist_10#c.Shock c.min_dist_10#c.post1#c.Shock) stats(ymean EN, labels("Mean Outcome" "Observations")) starlevels(* 0.10 ** 0.05 *** 0.01) substitute(\_ _) tex |
| |
|
| | |
| | |
| | use "$data_files/city_pm.dta", clear |
| | label variable post1 "Post" |
| | label variable number "\# Mon" |
| | label variable number_iv "Min \# Mon" |
| |
|
| | gen RD_Estimate = c.post1#c.number |
| |
|
| | eststo clear |
| | reghdfe pm25 RD_Estimate c.post#c.area c.post#c.pop, a(city_id year#month pred tem_meand age_year incentive2#time) cluster(city_id) |
| | estadd scalar EN = e(N_full) |
| | eststo A |
| | ivreghdfe pm25 c.post#c.area c.post#c.pop (RD_Estimate=c.post1#c.number_iv), a(city_id year#month pred tem_meand age_year incentive2#time) cluster(city_id) |
| | estadd scalar EN = e(N_full) |
| | eststo B |
| |
|
| | use "$data_files/city_pm_rd.dta", clear |
| |
|
| | gen dist1 = area - 20 if cutoff == 1 |
| | replace dist1 = area - 50 if cutoff == 2 |
| |
|
| | gen bench = pm25 if year < 2012 |
| | bys city_id cutoff: egen mean_bench = mean(bench) |
| |
|
| | gen above = dist1 > 0 |
| | gen RD_Estimate = c.post1#c.above |
| |
|
| | rdrobust pm25 dist1 if year>=2015, fuzzy(number) p(1) h(11.3) covs(cutoff mean_bench year month) kernel(uni) vce(cluster city_id) |
| | estadd scalar EN = e(N_h_l) + e(N_h_r) |
| | estadd scalar band = e(h_l) |
| | eststo C |
| | reghdfe pm25 RD_Estimate post1 above dist1 c.post1#c.dist1 c.above#c.dist1 c.post#c.above#c.dist1 cutoff if abs(dist1) < 11.3, a(time) cl(city_id) |
| | estadd scalar EN = e(N) |
| | estadd scalar band = 11.3 |
| | eststo D |
| | esttab A B C D using "$out_files/Table3a.tex", keep(RD_Estimate) transform(@/1.21 1/1.21, pattern(0 0 0 1)) replace b(a2) se(a2) label noconstant nolines nogaps compress fragment nonumbers mlabels(none) coeflabels(RD_Estimate "\# Monitors") stats(EN, labels( "Observations")) starlevels(* 0.10 ** 0.05 *** 0.01) tex |
| |
|
| | use "$data_files/city_enf.dta", clear |
| |
|
| | label variable post1 "Post" |
| | label variable number "\# Mon" |
| | label variable number_iv "Min \# Mon" |
| |
|
| | gen RD_Estimate = c.post1#c.number |
| |
|
| | eststo clear |
| | reghdfe log_any_air RD_Estimate c.post#c.area c.post#c.pop, a(city_id year#quarter pred tem_meand age_year incentive2#time) cluster(city_id) |
| | estadd scalar EN = e(N_full) |
| | eststo A |
| | ivreghdfe log_any_air c.post#c.area c.post#c.pop (RD_Estimate=c.post1#c.number_iv), a(city_id year#quarter pred tem_meand age_year incentive2#time) cluster(city_id) |
| | estadd scalar EN = e(N_full) |
| | eststo B |
| |
|
| | use "$data_files/city_enf_rd.dta", clear |
| |
|
| | gen dist1 = area - 20 if cutoff == 1 |
| | replace dist1 = area - 50 if cutoff == 2 |
| |
|
| | gen bench = log_any_air if year < 2012 |
| | bys city_id cutoff: egen mean_bench = mean(bench) |
| |
|
| | gen above = dist1 > 0 |
| | gen RD_Estimate = c.post1#c.above |
| |
|
| | rdrobust log_any_air dist1 if year>=2015, fuzzy(number) p(1) h(11.3) covs(cutoff mean_bench year quarter) kernel(uni) vce(cluster city_id) |
| | estadd scalar EN = e(N_h_l) + e(N_h_r) |
| | estadd scalar band = e(h_l) |
| | eststo C |
| | reghdfe log_any_air RD_Estimate post1 above dist1 c.post1#c.dist1 c.above#c.dist1 c.post1#c.above#c.dist1 cutoff if abs(dist1) < 11.3, a(time) cl(city_id) |
| | estadd scalar EN = e(N) |
| | estadd scalar band = 11.3 |
| | eststo D |
| | esttab A B C D using "$out_files/Table3b.tex", tex keep(RD_Estimate) transform(@/1.21 1/1.21, pattern(0 0 0 1)) replace b(a2) se(a2) label noconstant nolines nogaps compress fragment nonumbers mlabels(none) coeflabels(RD_Estimate "\# Monitors") stats(EN, labels("Observations")) starlevels(* 0.10 ** 0.05 *** 0.01) |
| |
|
| | replace RD_Estimate = number_iv |
| |
|
| | eststo clear |
| | regress number number_iv if year>=2015, vce(cluster city_id) |
| | eststo A |
| | regress number RD_Estimate pop area if year>=2015, vce(cluster city_id) |
| | eststo B |
| | rdrobust number dist1 if year>=2015, p(1) h(11.3) covs(cutoff) kernel(uni) vce(cluster city_id) |
| | eststo C |
| | estadd local kern = "Uniform" |
| | estadd scalar band = 11.3 |
| | rdrobust number dist1 if year>=2015, p(1) h(11.3) covs(cutoff) kernel(uni) vce(cluster city_id) |
| | eststo D |
| | estadd local kern = "Uniform" |
| | estadd scalar band = 11.3 |
| | esttab A B C D using "$out_files/Table3c.tex", tex replace b(a2) se(a2) label noconstant nolines nogaps compress fragment nonumbers noobs mlabels(none) keep(RD_Estimate) coeflabels(RD_Estimate "Estimate") stats(kern band, labels("Kernel" "Bandwidth")) starlevels(* 0.10 ** 0.05 *** 0.01) |
| |
|
| |
|
| | |
| | |
| | use "$data_files/monitor_api.dta", clear |
| |
|
| | gen log_pm25api = log(pm25api) |
| | gen log_pm10api = log(pm10api) |
| |
|
| | gen reassign = (year == 2017) |
| | replace reassign = 1 if year == 2016 & month >= 11 |
| |
|
| | rename pm25 AOD |
| | label variable AOD "AOD" |
| | label variable reassign "Reassigned" |
| |
|
| | eststo clear |
| | reghdfe log_pm25api AOD pre tem_mean, a(monitor_id year#month) cl(city_id) |
| | eststo A |
| | estadd ysumm, mean |
| | reghdfe log_pm25api AOD pre tem_mean if ~compare, a(monitor_id year#month) cl(city_id) |
| | eststo B |
| | estadd ysumm, mean |
| | reghdfe log_pm25api AOD c.AOD#c.reassign pre tem_mean if ~compare, a(monitor_id year#month) cl(city_id) |
| | eststo C |
| | estadd ysumm, mean |
| | reghdfe log_pm25api AOD pre tem_mean if compare, a(monitor_id year#month) cl(city_id) |
| | eststo D |
| | estadd ysumm, mean |
| | reghdfe log_pm25api AOD c.AOD#c.reassign pre tem_mean if compare, a(monitor_id year#month) cl(city_id) |
| | eststo E |
| | estadd ysumm, mean |
| |
|
| | use "$data_files/city_pm.dta", clear |
| |
|
| | label variable post1 "Post" |
| | label variable number "\# Mon" |
| |
|
| | gen reassign = (year == 2017) |
| | replace reassign = 1 if year == 2016 & month >= 10 |
| | label variable reassign "Reassigned" |
| |
|
| | reghdfe pm25 c.post1#c.number c.post1#c.number#c.reassign c.post1#c.area c.post1#c.pop, a(city_id year#month pred tem_meand age_year incentive2#time) cluster(city_id) |
| | eststo F |
| | estadd ysumm, mean |
| |
|
| | use "$data_files/city_enf.dta", clear |
| |
|
| | label variable post1 "Post" |
| | label variable number "\# Mon" |
| |
|
| | gen reassign = (year == 2017) |
| | replace reassign = 1 if year == 2016 & quarter == 4 |
| | label variable reassign "Reassigned" |
| |
|
| | reghdfe log_any_air c.post1#c.number c.post1#c.number#c.reassign c.post1#c.area c.post1#c.pop, a(city_id year#quarter pred tem_meand age_year incentive2#time) cluster(city_id) |
| | eststo G |
| | estadd ysumm, mean |
| | esttab A B C D E F G using "$out_files/Table4.tex", replace b(a2) noconstant se(a2) nolines nogaps compress fragment nonumbers label mlabels(none) collabels() keep(AOD c.AOD#c.reassign c.post1#c.number c.post1#c.number#c.reassign) drop() coeflabels(c.AOD#c.reassign "AOD $\times$ Reassigned" c.post1#c.number "\# Monitors" c.post1#c.number#c.reassign "\# Monitors $\times$ Reassigned") stats(ymean N, labels("Mean Outcome" "Observations")) starlevels(* 0.10 ** 0.05 *** 0.01) substitute(\_ _) tex |
| |
|
| |
|
| |
|
