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* Set Directory
clear
set more off
set scheme s1mono
cd "$path"
global data_files "$path/Data"
global out_files "$path/output"
**==============================================================================
* Table A1
use "$data_files/Raw/allcity_info", clear
label variable pm25 "AOD"
label variable number "\# Monitors"
label variable area "Size of Built-up Area (km2)"
label variable pop "Urban Population (10,000)"
eststo clear
estpost tabstat pm25 number area pop, by(mainsample) statistics(mean sd) columns(statistics) listwise nototal
esttab using "$out_files/TableA1.tex", replace tex main(mean) aux(sd) nogaps nodepvar compress fragment nostar noobs unstack nonote nomtitle label
**==============================================================================
* Table C1
use "$data_files/firm_enf.dta", clear
keep if min_dist<50 & starty<=2010
drop if revenue == .
drop if key == .
label variable any_air "Any Air Pollution Enforcement"
label variable any_air_shutdown "\quad Suspension"
label variable any_air_fine "\quad Fine"
label variable any_air_renovate "\quad Upgrading"
label variable any_air_warning "\quad Warning"
label variable air "\# Air Pollution Enforcement"
label variable any_water "Any Water Pollu. Enforc."
label variable any_waste "Any Solid Waste Pollu. Enforc."
label variable any_proc "Any Procedure Pollu. Enforc."
label variable min_dist_10 "Monitor within 10 km"
label variable min_dist "Distance to Monitor (km)"
label variable starty "Year Started"
label variable employment "Employment"
label variable revenue "Revenue"
label variable up "Upwind Firms"
eststo clear
estpost summarize any_air* air any_water any_waste any_proc up
esttab using "$out_files/TableC1a1.tex", replace cells("mean(fmt(a2)) sd(fmt(a2)) count") noobs nolines nogaps nodepvar compress fragment nonumbers label mlabels(none) tex
display "Periods: "
display "Frequency: "
keep if year==2010 & quarter==1
gen state = (ownership==1 | ownership==2)
gen private = (ownership==3)
gen foreign = (ownership==9)
gen rest = (ownership==4|ownership==5)
label variable state "Owner: SOEs"
label variable private "Owner: Private"
label variable foreign "Owner: Foreign"
label variable rest "Owner: Other"
eststo clear
estpost summarize min_dist_10 min_dist starty state private foreign rest employment revenue
esttab using "$out_files/TableC1a2.tex", replace cells("mean(fmt(a2)) sd(fmt(a2)) count") noobs nolines nogaps nodepvar compress fragment nonumbers label mlabels(none) tex
display "Periods: "
display "Frequency: "
use "$data_files/city_pm.dta", clear
drop if pm25 == .
label variable number "\# Monitors"
label variable area "Size of Built-up Area (km2)"
label variable pop "Urban Population (10,000)"
label variable age_year "Age of the Mayor"
label variable pre "Precipitation (mm)"
label variable tem_mean "Mean Temperature"
label variable pm25 "Aerosol Optical Depth"
eststo clear
estpost summarize number area pop age_year pre tem_mean pm25
esttab using "$out_files/TableC1b1.tex", replace cells("mean(fmt(a2)) sd(fmt(a2)) count") noobs nolines nogaps nodepvar compress fragment nonumbers label mlabels(none) tex
display "Periods: "
display "Frequency: "
use "$data_files/city_pm.dta", clear
label variable post1 "Post"
label variable number "\# Mon"
label variable number_iv "Min \# Mon"
merge 1:1 city_cn year month using "$data_files/Raw/baidu.dta"
keep if _merge == 3
drop _merge
label variable sear_freq_w1 "Search Index: air pollution"
label variable sear_freq_w2 "Search Index: haze/smoke"
label variable sear_freq_w3 "Search Index: PM25"
label variable sear_freq_w4 "Search Index: air mask"
label variable sear_freq_w5 "Search Index: air purifier"
eststo clear
estpost summarize sear*
esttab using "$out_files/TableC1b3.tex", replace cells("mean(fmt(a2)) sd(fmt(a2)) count") noobs nolines nogaps nodepvar compress fragment nonumbers label mlabels(none) tex
display "Periods: "
display "Frequency: "
use "$data_files/city_enf.dta", clear
gen any_air_total = any_air+any_air_rest
label variable any_air_total "\# Firms Any Air Pollu. Enfor. (incl non-ASIF)"
label variable any_air "\# Firms Any Air Pollu. Enfor."
eststo clear
estpost summarize any_air any_air_total
esttab using "$out_files/TableC1b2.tex", replace cells("mean(fmt(a2)) sd(fmt(a2)) count") noobs nolines nogaps nodepvar compress fragment nonumbers label mlabels(none) tex
display "Periods: "
display "Frequency: "
use "$data_files/monitor_api.dta", clear
label variable pm25api "Particulate Matter 2.5 (PM$\_2.5$)"
label variable pm10api "Particulate Matter 10 (PM$\_10$))"
label variable AQI "Air Quality Index (AQI) "
eststo clear
estpost summarize pm25api pm10api AQI
esttab using "$out_files/TableC1c.tex", replace cells("mean(fmt(a2)) sd(fmt(a2)) count") noobs nolines nogaps nodepvar compress fragment nonumbers label mlabels(none) substitute(\_ _) tex
**==============================================================================
* Table C4
use "$data_files/monitor_api.dta", clear
gen log_pm25api = log(pm25api)
gen log_pm10api = log(pm10api)
gen log_aqi = log(AQI)
replace log_aqi = . if log_pm25api == .
rename pm25 AOD
label variable AOD "AOD"
eststo clear
reghdfe log_pm25api AOD pre tem_mean, a(monitor_id year#month) cl(city_id)
eststo A
estadd ysumm, mean
reghdfe log_pm10api AOD pre tem_mean, a(monitor_id year#month) cl(city_id)
eststo B
estadd ysumm, mean
reghdfe log_aqi AOD pre tem_mean, a(monitor_id year#month) cl(city_id)
eststo C
estadd ysumm, mean
esttab A B C using "$out_files/TableC4.tex", replace b(a2) noconstant se(a2) nolines nogaps compress fragment nonumbers label mlabels(none) collabels() keep(AOD) drop() stats(ymean N, labels("Mean Outcome" "Observations")) starlevels(* 0.10 ** 0.05 *** 0.01) substitute(\_ _) tex
**==============================================================================
* Table C5
use "$data_files/firm_enf.dta", clear
drop if revenue == .
drop if key == .
keep if min_dist<50 & starty<=2010 & time==1
gen twodigit = int(industry/100)
lab def twodigit_lb 6 "Mining and Washing of Coal & 6" ///
7 "Extraction of Petroleum and Natural Gas & 7" ///
8 "Mining and Processing of Ferrous Metal Ores & 8" ///
9 "Mining and Processing of Non-Ferrous Metal Ores & 9" ///
10 "Mining and Processing of Nonmetallic Mineral & 10" ///
11 "Mining Support & 11" ///
12 "Other Mining & 12" ///
13 "Agricultural and Sideline Food Processing & 13" ///
14 "Fermentation & 14" ///
15 "Beverage Manufacturing & 15" ///
16 "Tobacco Manufacturing & 16" ///
17 "Textile Mills & 17" ///
18 "Wearing Apparel and Clothing Accessories Manufacturing & 18" ///
19 "Leather, Fur and Related Products Manufacturing & 19" ///
20 "Wood and Bamboo Products Manufacturing & 20" ///
21 "Furniture Manufacturing & 21" ///
22 "Products Manufacturing & 22" ///
23 "Printing and Reproduction of Recorded Media & 23" ///
24 "Education and Entertainment Articles Manufacturing & 24" ///
25 "Petrochemicals Manufacturing & 25" ///
26 "Chemical Products Manufacturing& 26" ///
27 "Medicine Manufacturing & 27" ///
28 "Chemical Fibers Manufacturing & 28" ///
29 "Rubber Products Manufacturing & 29" ///
30 "Plastic Products Manufacturing & 30" ///
31 "Non-Metallic Mineral Products Manufacturing & 31" ///
32 "Iron and Steel Smelting & 32" ///
33 "Non-Ferrous Metal Smelting & 33" ///
34 "Fabricated Metal Products Manufacturing & 34" ///
35 "General Purpose Machinery Manufacturing & 35" ///
36 "Special Purpose Machinery Manufacturing & 36" ///
37 "Transport Equipment Manufacturing & 37" ///
38 "Electrical machinery and equipment Manufacturing & 38" ///
39 "Electrical Equipment Manufacturing & 39" ///
40 "Computers and Electronic Products Manufacturing & 40" ///
41 "General Instruments and Other Equipment Manufacturing & 41" ///
42 "Craft-works Manufacturing & 42" ///
43 "Renewable Materials Recovery & 43" ///
44 "Electricity and Heat Supply & 44" ///
45 "Gas Production and Supply & 45" ///
46 "Water Production and Supply & 46", add
label values twodigit twodigit_lb
eststo clear
estpost tabulate twodigit
esttab using "$out_files/TableC5.tex", replace tex cells("b(label(freq)) pct(fmt(2))") varlabels(`e(labels)', blist(Total)) nolines nogaps compress fragment label
**==============================================================================
* Table C6
use "$data_files/Raw/daily_monitor_api.dta", clear
* Construct daily indicators
gen above_100=0 & AQI!=.
replace above_100=1 if AQI>=100 & AQI!=.
gen above_200=0 & AQImax!=.
replace above_200=1 if AQImax>=200 & AQImax!=.
* Collapse data to monthly level
collapse (mean) above_200 pm25api pm10api AQI, by(year month city_id)
* Merge with weather data
merge 1:1 city_id year month using "$data_files/weather_monthly.dta"
keep if _merge == 3
drop _merge
gen quarter = int((month-1)/3)+1
collapse (mean) above_200 pm25api pm10api AQI pre tem_mean, by(year quarter city_id)
* Construct monthly variables
egen time=group(year quarter)
replace pre=. if pre==-9999
bysort city_id: egen med_pre=median(pre)
gen high_pre=0 if pre!=.
replace high_pre=1 if pre>med_pre & pre!=.
label var high_pre "\$Rain_{>\tilde{x}}$"
gen log_pre=log(pre)
gen log_api25=log(pm25api)
gen log_aqi=log(AQI)
gen log_api10=log(pm10api)
gen tem_meand = int(tem_mean)
* Monthly pollution regressions
reghdfe log_api25 high_pre, absorb(time city_id tem_meand) cluster(city_id)
eststo A
estadd ysumm, mean
estadd scalar EN = e(N_full)
reghdfe log_api10 high_pre, absorb(time city_id tem_meand) cluster(city_id)
eststo B
estadd ysumm, mean
estadd scalar EN = e(N_full)
reghdfe log_aqi high_pre, absorb(time city_id tem_meand) cluster(city_id)
eststo C
estadd ysumm, mean
estadd scalar EN = e(N_full)
reghdfe above_200 high_pre if AQI!=., absorb(time city_id tem_meand) cluster(city_id)
eststo D
estadd ysumm, mean
estadd scalar EN = e(N_full)
esttab A B C D using "$out_files/TableC6.tex", replace b(a2) noconstant se(a2) nolines nogaps compress fragment nonumbers label mlabels(none) collabels() drop(_cons) stats(ymean EN, labels("Mean Outcome" "Observations")) starlevels(* 0.10 ** 0.05 *** 0.01) substitute(\_ _) tex
**==============================================================================
* Table C7
use "$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"
* Table
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 FirmFE = "Yes"
estadd local ITFE = "Yes"
estadd local PTFE = "Yes"
reghdfe any_water 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 FirmFE = "Yes"
estadd local ITFE = "Yes"
estadd local PTFE = "Yes"
reghdfe any_waste 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 FirmFE = "Yes"
estadd local ITFE = "Yes"
estadd local PTFE = "Yes"
reghdfe any_proc 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 FirmFE = "Yes"
estadd local ITFE = "Yes"
estadd local PTFE = "Yes"
esttab A B C D using "$out_files/TableC7a.tex", replace b(a2) noconstant se(a2) nolines nogaps compress fragment nonumbers label mlabels(none) collabels() keep(c.min_dist_10*) stats(ymean EN FirmFE ITFE PTFE, labels("Mean Outcome" "Observations" "Firm FE" "Industry-Time FE" "Province-Time FE")) starlevels(* 0.10 ** 0.05 *** 0.01) substitute(\_ _) tex
merge m:1 city_id using "$data_files/Raw/city_info.dta", keepusing(disttocoast)
keep if _merge == 3
drop _merge
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 FirmFE = "Yes"
estadd local ITFE = "Yes"
estadd local PTFE = "Yes"
estadd local DTFE = "No"
estadd local FCTFE = "No"
estadd local CTFE = "No"
reghdfe any_air c.min_dist_10#c.post1 if min_dist<50 & starty<=2010, absorb(time id industry#time prov_id#time c.disttocoast#time) cluster(city_id)
eststo B
estadd ysumm, mean
estadd scalar EN = e(N_full)
estadd local FirmFE = "Yes"
estadd local ITFE = "Yes"
estadd local PTFE = "Yes"
estadd local DTFE = "Yes"
estadd local FCTFE = "No"
estadd local CTFE = "No"
reghdfe any_air c.min_dist_10#c.post1 if min_dist<50 & starty<=2010, absorb(time id industry#time prov_id#time c.disttocoast#time c.employment#time) cluster(city_id)
eststo C
estadd ysumm, mean
estadd scalar EN = e(N_full)
estadd local FirmFE = "Yes"
estadd local ITFE = "Yes"
estadd local PTFE = "Yes"
estadd local DTFE = "Yes"
estadd local FCTFE = "Yes"
estadd local CTFE = "No"
reghdfe any_air c.min_dist_10#c.post1 if min_dist<50 & starty<=2010, absorb(time id industry#time prov_id#time city_id#time) cluster(city_id)
eststo D
estadd ysumm, mean
estadd scalar EN = e(N_full)
estadd local FirmFE = "Yes"
estadd local ITFE = "Yes"
estadd local PTFE = "No"
estadd local DTFE = "No"
estadd local FCTFE = "Yes"
estadd local CTFE = "Yes"
esttab A B C D using "$out_files/TableC7b.tex", replace b(a2) noconstant se(a2) nolines nogaps compress fragment nonumbers label mlabels(none) collabels() keep(c.min_dist_10*) stats(ymean EN DTFE FCTFE CTFE FirmFE ITFE PTFE, labels("Mean Outcome" "Observations" "Distance to coast-Time FE" "Firm characteristics-Time FE" "City-Time FE" "Firm FE" "Industry-Time FE" "Province-Time FE" )) starlevels(* 0.10 ** 0.05 *** 0.01) substitute(\_ _) tex
**==============================================================================
* Table C8
use "$data_files/Raw/city_info.dta", clear
merge 1:1 city_id using "$data_files/share.dta"
drop if _merge == 2
drop _merge
label variable number "\# Monitors"
label variable number_iv "Min \# Monitors"
regress share_rev_10 number, r
eststo A
estadd ysumm, mean
regress share_emp_10 number, r
eststo B
estadd ysumm, mean
regress share_rev_5 number, r
eststo C
estadd ysumm, mean
regress share_emp_5 number, r
eststo D
estadd ysumm, mean
esttab A B C D using "$out_files/TableC8a.tex", replace b(a2) noconstant se(a2) label nolines nogaps compress fragment nonumbers mlabels(none) collabels() drop(_cons) stats(ymean N, labels("Mean Outcome" "Observations")) starlevels(* 0.10 ** 0.05 *** 0.01) substitute(\_ _) tex
ivregress 2sls share_rev_10 (number = number_iv), r
eststo A
estadd ysumm, mean
ivregress 2sls share_emp_10 (number = number_iv), r
eststo B
estadd ysumm, mean
ivregress 2sls share_rev_5 (number = number_iv), r
eststo C
estadd ysumm, mean
ivregress 2sls share_emp_5 (number = number_iv), r
eststo D
estadd ysumm, mean
esttab A B C D using "$out_files/TableC8b.tex", replace b(a2) noconstant se(a2) label nolines nogaps compress fragment nonumbers mlabels(none) collabels() drop(_cons) stats(ymean N, labels("Mean Outcome" "Observations")) starlevels(* 0.10 ** 0.05 *** 0.01) substitute(\_ _) tex
**==============================================================================
* Table C9
* Robustness: additional controls
use "$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.post1#c.area c.post1#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.post1#c.area c.post1#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
reghdfe pm25 RD_Estimate i.time#c.area i.time#c.pop, a(city_id year#month pred tem_meand age_year incentive2#time) cluster(city_id)
estadd scalar EN = e(N_full)
eststo C
ivreghdfe pm25 i.time#c.area i.time#c.pop i.time#c.background (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 D
reghdfe pm25 RD_Estimate i.time#c.area i.time#c.pop i.time#c.background i.time#c.GDP, a(city_id year#month pred tem_meand age_year incentive2#time) cluster(city_id)
estadd scalar EN = e(N_full)
eststo E
ivreghdfe pm25 i.time#c.area i.time#c.pop i.time#c.background i.time#c.GDP (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 F
esttab A B C D E F using "$out_files/TableC9a.tex", tex keep(RD_Estimate) transform(@/1, pattern(0 0 0 0)) replace b(a2) se(a2) label noconstant nolines nogaps compress fragment nonumbers mlabels(none) coeflabels(RD_Estimate "\# Monitors") stats(EN, labels( "Observations")) starlevels(* 0.10 ** 0.05 *** 0.01)
use "$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.post1#c.area c.post1#c.pop, a(city_id year#quarter pred tem_meand age_year incentive2#time) cluster(city_id)
estadd scalar EN = e(N_full)
estadd local CFE = "Yes"
estadd local TTFE = "Yes"
estadd local CSPost = "Yes"
estadd local CSTFE = "No"
estadd local CCTFE = "No"
estadd local Weather = "Yes"
eststo A
ivreghdfe log_any_air c.post1#c.area c.post1#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)
estadd local CFE = "Yes"
estadd local TTFE = "Yes"
estadd local CSPost = "Yes"
estadd local CSTFE = "No"
estadd local CCTFE = "No"
estadd local Weather = "Yes"
eststo B
reghdfe log_any_air RD_Estimate i.time#c.area i.time#c.pop, a(city_id year#quarter pred tem_meand age_year incentive2#time) cluster(city_id)
estadd scalar EN = e(N_full)
estadd local CFE = "Yes"
estadd local TTFE = "Yes"
estadd local CSPost = "No"
estadd local CSTFE = "Yes"
estadd local CCTFE = "No"
estadd local Weather = "Yes"
eststo C
ivreghdfe log_any_air i.time#c.area i.time#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)
estadd local CFE = "Yes"
estadd local TTFE = "Yes"
estadd local CSPost = "No"
estadd local CSTFE = "Yes"
estadd local CCTFE = "No"
estadd local Weather = "Yes"
eststo D
reghdfe log_any_air RD_Estimate i.time#c.area i.time#c.pop i.time#c.background i.time#c.GDP, a(city_id year#quarter pred tem_meand age_year incentive2#time) cluster(city_id)
estadd scalar EN = e(N_full)
estadd local CFE = "Yes"
estadd local TTFE = "Yes"
estadd local CSPost = "No"
estadd local CSTFE = "Yes"
estadd local CCTFE = "Yes"
estadd local Weather = "Yes"
eststo E
ivreghdfe log_any_air i.time#c.area i.time#c.pop i.time#c.background i.time#c.GDP (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)
estadd local CFE = "Yes"
estadd local TTFE = "Yes"
estadd local CSPost = "No"
estadd local CSTFE = "Yes"
estadd local CCTFE = "Yes"
estadd local Weather = "Yes"
eststo F
esttab A B C D E F using "$out_files/TableC9b.tex", tex keep(RD_Estimate) transform(@/1, pattern(0 0 0 0)) replace b(a2) se(a2) label noconstant nolines nogaps compress fragment nonumbers mlabels(none) coeflabels(RD_Estimate "\# Monitors") stats(EN CFE TTFE CSPost CSTFE CCTFE Weather, labels("Observations" "City FE" "Target-Time FE" "City size $\times$ Post" "City size-Time FE" "City char.-Time FE" "Weather")) starlevels(* 0.10 ** 0.05 *** 0.01)
**==============================================================================
* Table C10
* Robustness: Sample Restriction
use "$data_files/city_pm.dta", clear
gen prov_id = int(city_id/100)
drop if prov_id == 54 | prov_id == 65
label variable post1 "Post"
label variable number "\# Mon"
label variable number_iv "Min \# Mon"
gen RD_Estimate = c.post1#c.number
reghdfe pm25 RD_Estimate c.post1#c.area c.post1#c.pop, a(city_id year#month pred tem_meand age_year incentive2#time) cluster(city_id)
estadd scalar EN = e(N_full)
eststo A
ivreghdfe pm25 c.post1#c.area c.post1#c.pop (RD_Estimate=c.post1#c.number_iv), a(city_id year#month pred tem_meand age_year incentive2#time) cluster(city_id)
estadd scalar EN = e(N_full)
eststo B
use "$data_files/city_pm_rd.dta", clear
gen prov_id = int(city_id/100)
drop if prov_id == 54 | prov_id == 65
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_full)
estadd scalar band = 11.3
eststo D
esttab A B C D using "$out_files/TableC10a.tex", tex keep(RD_Estimate) transform(@/1.21 1/1.21, pattern(0 0 0 1)) replace b(a2) se(a2) label noconstant nolines nogaps compress fragment nonumbers mlabels(none) coeflabels(RD_Estimate "\# Monitors") stats(EN, labels( "Observations")) starlevels(* 0.10 ** 0.05 *** 0.01)
use "$data_files/city_enf.dta", clear
gen prov_id = int(city_id/100)
drop if prov_id == 54 | prov_id == 65
label variable post1 "Post"
label variable number "\# Mon"
label variable number_iv "Min \# Mon"
gen RD_Estimate = c.post1#c.number
reghdfe log_any_air RD_Estimate c.post1#c.area c.post1#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.post1#c.area c.post1#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 "$data_files/city_enf_rd.dta", clear
gen prov_id = int(city_id/100)
drop if prov_id == 54 | prov_id == 65
gen dist1 = area - 20 if cutoff == 1
replace dist1 = area - 50 if cutoff == 2
gen bench = log_any_air if year < 2012
bys city_id cutoff: egen mean_bench = mean(bench)
gen above = dist1 > 0
gen RD_Estimate = c.post1#c.above
rdrobust log_any_air dist1 if year>=2015, fuzzy(number) p(1) h(11.3) covs(cutoff mean_bench) kernel(uni) vce(cluster city_id)
estadd scalar EN = e(N_h_l) + e(N_h_r)
estadd scalar band = e(h_l)
estadd local kern = "Uniform"
eststo C
reghdfe log_any_air RD_Estimate post1 above dist1 c.post1#c.dist1 c.above#c.dist1 c.post1#c.above#c.dist1 cutoff if abs(dist1) < 11.3, a(time) cl(city_id)
estadd scalar EN = e(N_full)
estadd scalar band = 11.3
estadd local kern = "Uniform"
eststo D
esttab A B C D using "$out_files/TableC10b.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 kern band, labels("Observations" "Kernel" "Bandwidth")) starlevels(* 0.10 ** 0.05 *** 0.01)
**==============================================================================
* Table C11
* asif vs all
use "$data_files/city_enf.dta", clear
gen log_any_air_total = log(any_air+any_air_rest+1)
label variable post1 "Post"
label variable number "\# Mon"
label variable number_iv "Min \# Mon"
gen RD_Estimate = c.post1#c.number
reghdfe log_any_air_total RD_Estimate c.post1#c.area c.post1#c.pop, a(city_id year#quarter pred tem_meand age_year incentive2#time) cluster(city_id)
estadd scalar EN = e(N_full)
eststo A
ivreghdfe log_any_air_total c.post1#c.area c.post1#c.pop (RD_Estimate=c.post1#c.number_iv), a(city_id year#quarter pred tem_meand age_year incentive2#time) cluster(city_id)
estadd scalar EN = e(N_full)
eststo B
use "$data_files/city_enf_rd.dta", clear
gen log_any_air_total = log(any_air+any_air_rest+1)
gen dist1 = area - 20 if cutoff == 1
replace dist1 = area - 50 if cutoff == 2
gen bench = log_any_air_total 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_total 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_total 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_full)
estadd scalar band = 11.3
eststo D
esttab A B C D using "$out_files/TableC11a.tex", tex keep(RD_Estimate) transform(@/1.21 1/1.21, pattern(0 0 0 1)) replace b(a2) se(a2) label noconstant nolines nogaps compress fragment nonumbers mlabels(none) coeflabels(RD_Estimate "\# Monitors") stats(EN, labels("Observations")) starlevels(* 0.10 ** 0.05 *** 0.01)
use "$data_files/city_enf.dta", clear
gen log_any_air_rest = log(any_air_rest+1)
label variable post1 "Post"
label variable number "\# Mon"
label variable number_iv "Min \# Mon"
gen RD_Estimate = c.post1#c.number
reghdfe log_any_air_rest RD_Estimate c.post1#c.area c.post1#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_rest c.post1#c.area c.post1#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 "$data_files/city_enf_rd.dta", clear
gen log_any_air_rest = log(any_air_rest+1)
gen dist1 = area - 20 if cutoff == 1
replace dist1 = area - 50 if cutoff == 2
gen bench = log_any_air_rest if year < 2012
bys city_id cutoff: egen mean_bench = mean(bench)
gen above = dist1 > 0
gen RD_Estimate = c.post1#c.above
rdrobust log_any_air_rest dist1 if year>=2015, fuzzy(number) p(1) h(11.3) covs(cutoff mean_bench year quarter) kernel(uni) vce(cluster city_id)
estadd scalar EN = e(N_h_l) + e(N_h_r)
estadd scalar band = e(h_l)
eststo C
reghdfe log_any_air_rest RD_Estimate post1 above dist1 c.post1#c.dist1 c.above#c.dist1 c.post1#c.above#c.dist1 cutoff if abs(dist1) < 11.3, a(time) cl(city_id)
estadd scalar EN = e(N_full)
estadd scalar band = 11.3
eststo D
esttab A B C D using "$out_files/TableC11b.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)
**==============================================================================
* Table C12
* kernel and covs
use "$data_files/city_pm_rd.dta", clear
gen dist1 = area - 20 if cutoff == 1
replace dist1 = area - 50 if cutoff == 2
gen bench = pm25 if year < 2012
bys city_id: egen mean_bench = mean(bench)
eststo clear
rdrobust pm25 dist1 if year>=2015, fuzzy(number) p(1) h(11.3) covs(cutoff mean_bench year month) kernel(uni) vce(cluster city_id)
estadd scalar EN = e(N_h_l) + e(N_h_r)
estadd scalar band = e(h_l)
eststo A
rdrobust pm25 dist1 if year>=2015, fuzzy(number) p(1) covs(cutoff mean_bench year month) kernel(tri) vce(cluster city_id)
estadd scalar EN = e(N_h_l) + e(N_h_r)
estadd scalar band = e(h_l)
eststo B
rdrobust pm25 dist1 if year>=2015, fuzzy(number) p(1) covs(cutoff mean_bench year month) kernel(epa) vce(cluster city_id)
estadd scalar EN = e(N_h_l) + e(N_h_r)
estadd scalar band = e(h_l)
eststo C
rdrobust pm25 dist1 if year>=2015, fuzzy(number) p(1) covs() kernel(uni) vce(cluster city_id)
estadd scalar EN = e(N_h_l) + e(N_h_r)
estadd scalar band = e(h_l)
eststo D
esttab A B C D using "$out_files/TableC12a1.tex", tex keep(RD_Estimate) replace b(a2) se(a2) label noconstant nolines nogaps compress fragment nonumbers mlabels(none) coeflabels(RD_Estimate "\# Monitors") stats(EN band, labels("Observations" "Bandwidth")) starlevels(* 0.10 ** 0.05 *** 0.01)
eststo clear
rdrobust number dist1 if year>=2015, p(1) h(11.3) covs(cutoff) kernel(uni) vce(cluster city_id)
eststo A
rdrobust number dist1 if year>=2015, p(1) h(12.3) covs(cutoff) kernel(tri) vce(cluster city_id)
eststo B
rdrobust number dist1 if year>=2015, p(1) h(12.5) covs(cutoff) kernel(epa) vce(cluster city_id)
eststo C
rdrobust number dist1 if year>=2015, p(1) h(13.8) covs() kernel(uni) vce(cluster city_id)
eststo D
esttab A B C D using "$out_files/TableC12a2.tex", tex replace b(a2) se(a2) label noconstant nolines nogaps compress fragment nonumbers noobs mlabels(none) keep(RD_Estimate) coeflabels(RD_Estimate "First stage") starlevels(* 0.10 ** 0.05 *** 0.01)
use "$data_files/city_enf_rd.dta", clear
gen dist1 = area - 20 if cutoff == 1
replace dist1 = area - 50 if cutoff == 2
gen dist2 = pop - 25 if cutoff == 1
replace dist2 = pop - 50 if cutoff == 2
gen bench = log_any_air if year < 2012
bys city_id: egen mean_bench = mean(bench)
gen above = dist1 > 0
gen RD_Estimate = c.post1#c.above
eststo clear
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 A
rdrobust log_any_air dist1 if year>=2015, fuzzy(number) p(1) covs(cutoff mean_bench year quarter) kernel(tri) vce(cluster city_id)
estadd scalar EN = e(N_h_l) + e(N_h_r)
estadd scalar band = e(h_l)
eststo B
rdrobust log_any_air dist1 if year>=2015, fuzzy(number) p(1) covs(cutoff mean_bench year quarter) kernel(epa) vce(cluster city_id)
estadd scalar EN = e(N_h_l) + e(N_h_r)
estadd scalar band = e(h_l)
eststo C
rdrobust log_any_air dist1 if year>=2015, fuzzy(number) p(1) covs() kernel(uni) vce(cluster city_id)
estadd scalar EN = e(N_h_l) + e(N_h_r)
estadd scalar band = e(h_l)
eststo D
esttab A B C D using "$out_files/TableC12b1.tex", tex keep(RD_Estimate) replace b(a2) se(a2) label noconstant nolines nogaps compress fragment nonumbers mlabels(none) coeflabels(RD_Estimate "\# Monitors") stats(EN band, labels("Observations" "Bandwidth")) starlevels(* 0.10 ** 0.05 *** 0.01)
eststo clear
rdrobust number dist1 if year>=2015, p(1) h(11.3) covs(cutoff) kernel(uni) vce(cluster city_id)
eststo A
estadd local kern = "Uniform"
estadd local cov = "Yes"
rdrobust number dist1 if year>=2015, p(1) h(13.1) covs(cutoff) kernel(tri) vce(cluster city_id)
eststo B
estadd local kern = "Epanechnikov"
estadd local cov = "Yes"
rdrobust number dist1 if year>=2015, p(1) h(12.5) covs(cutoff) kernel(epa) vce(cluster city_id)
eststo C
estadd local kern = "Triangle"
estadd local cov = "Yes"
rdrobust number dist1 if year>=2015, p(1) h(11.4) covs() kernel(uni) vce(cluster city_id)
eststo D
estadd local kern = "Uniform"
estadd local cov = "No"
esttab A B C D using "$out_files/TableC12b2.tex", tex replace b(a2) se(a2) label noconstant nolines nogaps compress fragment nonumbers noobs mlabels(none) keep(RD_Estimate) coeflabels(RD_Estimate "First stage") stats(kern cov, labels("Kernel" "Covariates")) starlevels(* 0.10 ** 0.05 *** 0.01)
**==============================================================================
* Table C13
* Cutoff 1
use "$data_files/city_pm.dta", clear
gen dist1 = area - 20
gen bench = pm25 if year < 2012
bys city_id: egen mean_bench = mean(bench)
gen above = dist1 > 0
gen RD_Estimate = c.post1#c.above
eststo clear
rdrobust pm25 dist1 if year>=2015, fuzzy(number) p(1) h(11.3) covs(mean_bench year quarter) kernel(uni) vce(cluster city_id)
estadd scalar EN = e(N_h_l) + e(N_h_r)
estadd scalar band = e(h_l)
eststo A
reghdfe pm25 RD_Estimate post1 above dist1 c.post1#c.dist1 c.above#c.dist1 c.post#c.above#c.dist1 if abs(dist1) < 11.3, a(year#month) cl(city_id)
estadd scalar EN = e(N_full)
estadd scalar band = 11.3
eststo B
use "$data_files/city_enf.dta", clear
gen dist1 = area - 20
gen bench = log_any_air if year < 2012
bys city_id: 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(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 if abs(dist1) < 11.3, a(time) cl(city_id)
estadd scalar EN = e(N_full)
estadd scalar band = 11.3
eststo D
esttab A B C D using "$out_files/TableC13a1.tex", tex keep(RD_Estimate) transform(@/0.79 1/0.79, pattern(0 1 0 1)) replace b(a2) se(a2) label noconstant nolines nogaps compress fragment nonumbers mlabels(none) coeflabels(RD_Estimate "\# Monitors") stats(EN band, labels("Observations" "Bandwidth")) starlevels(* 0.10 ** 0.05 *** 0.01)
eststo clear
rdrobust number dist1 if year>=2015, p(1) h(11.3) kernel(uni) vce(cluster city_id)
eststo A
rdrobust number dist1 if year>=2015, p(1) h(11.3) kernel(uni) vce(cluster city_id)
eststo B
rdrobust number dist1 if year>=2015, p(1) h(11.3) kernel(uni) vce(cluster city_id)
eststo C
rdrobust number dist1 if year>=2015, p(1) h(11.3) covs() kernel(uni) vce(cluster city_id)
eststo D
esttab A B C D using "$out_files/TableC13a2.tex", tex replace b(a2) se(a2) label noconstant nolines nogaps compress fragment nonumbers noobs mlabels(none) keep(RD_Estimate) coeflabels(RD_Estimate "First stage") starlevels(* 0.10 ** 0.05 *** 0.01)
* Cutoff 2
use "$data_files/city_pm.dta", clear
gen dist1 = area - 50
gen bench = pm25 if year < 2012
bys city_id: egen mean_bench = mean(bench)
gen above = dist1 > 0
gen RD_Estimate = c.post1#c.above
eststo clear
rdrobust pm25 dist1 if year>=2015, fuzzy(number) p(1) h(11.3) covs(mean_bench year month) kernel(uni) vce(cluster city_id)
estadd scalar EN = e(N_h_l) + e(N_h_r)
estadd scalar band = e(h_l)
eststo A
reghdfe pm25 RD_Estimate post1 above dist1 c.post1#c.dist1 c.above#c.dist1 c.post#c.above#c.dist1 if abs(dist1) < 11.3, a(time) cl(city_id)
estadd scalar EN = e(N_full)
estadd scalar band = 11.3
eststo B
use "$data_files/city_enf.dta", clear
gen dist1 = area - 50
gen bench = log_any_air if year < 2012
bys city_id: 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(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 if abs(dist1) < 11.3, a(time) cl(city_id)
estadd scalar EN = e(N_full)
estadd scalar band = 11.3
eststo D
esttab A B C D using "$out_files/TableC13b1.tex", tex keep(RD_Estimate) transform(@/1.76 1/1.76, pattern(0 1 0 1)) replace b(a2) se(a2) label noconstant nolines nogaps compress fragment nonumbers mlabels(none) coeflabels(RD_Estimate "\# Monitors") stats(EN band, labels("Observations" "Bandwidth")) starlevels(* 0.10 ** 0.05 *** 0.01)
eststo clear
rdrobust number dist1 if year>=2015, p(1) h(11.3) kernel(uni) vce(cluster city_id)
eststo A
estadd local kern = "Uniform"
estadd scalar band = 11.3
rdrobust number dist1 if year>=2015, p(1) h(11.3) kernel(uni) vce(cluster city_id)
eststo B
estadd local kern = "Uniform"
estadd scalar band = 11.3
rdrobust number dist1 if year>=2015, p(1) h(11.3) kernel(uni) vce(cluster city_id)
eststo C
estadd local kern = "Uniform"
estadd scalar band = 11.3
rdrobust number dist1 if year>=2015, p(1) h(11.3) covs() kernel(uni) vce(cluster city_id)
eststo D
estadd local kern = "Uniform"
estadd local band = 11.3
esttab A B C D using "$out_files/TableC13b2.tex", tex replace b(a2) se(a2) label noconstant nolines nogaps compress fragment nonumbers noobs mlabels(none) keep(RD_Estimate) coeflabels(RD_Estimate "First stage") stats(kern band, labels("Kernel" "Bandwidth")) starlevels(* 0.10 ** 0.05 *** 0.01)
**==============================================================================
* Table C14
* Spillover in aod
use "$data_files/city_pm_rd.dta", clear
rename pm pm_monitor
drop if pm_monitor == .
drop if pm_direct == .
drop if pm_indirect == .
gen dist1 = area - 20 if cutoff == 1
replace dist1 = area - 50 if cutoff == 2
gen bench_monitor = pm_monitor if year < 2012
bys city_id cutoff: egen mean_bench_monitor = mean(bench_monitor)
gen RD_Estimate = .
gen above = dist1 > 0
replace RD_Estimate = c.post1#c.number
eststo clear
reghdfe pm_monitor RD_Estimate c.post1#c.area c.post1#c.pop if cutoff == 1, a(city_id year#month pred tem_meand age_year incentive2#time) cluster(city_id)
eststo A
summ pm_monitor
estadd scalar ysumm = r(mean)
estadd scalar EN = e(N_full)
ivreghdfe pm_monitor c.post1#c.area c.post1#c.pop (RD_Estimate=c.post1#c.number_iv) if cutoff == 1, a(city_id year#month pred tem_meand age_year incentive2#time) cluster(city_id)
eststo B
summ pm_monitor
estadd scalar ysumm = r(mean)
estadd scalar EN = e(N_full)
rdrobust pm_monitor dist1 if year>=2015, fuzzy(number) p(1) h(11.3) covs(cutoff mean_bench_monitor year month) kernel(uni) vce(cluster city_id)
estadd scalar EN = e(N_h_l) + e(N_h_r)
summ pm_monitor if abs(dist1)<11.3
estadd scalar ysumm = r(mean)
eststo C
replace RD_Estimate = c.post1#c.above
reghdfe pm_monitor RD_Estimate post1 above dist1 c.post1#c.dist1 c.above#c.dist1 c.post#c.above#c.dist1 cutoff if abs(dist1) < 11.3, a(time) cl(city_id)
estadd scalar EN = e(N)
summ pm_monitor if abs(dist1)<11.3
estadd scalar ysumm = r(mean)
eststo D
esttab A B C D using "$out_files/TableC14a.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 ysumm, labels("Observations" "Mean Outcome")) starlevels(* 0.10 ** 0.05 *** 0.01) tex
use "$data_files/city_pm_rd.dta", clear
rename pm pm_monitor
drop if pm_monitor == .
drop if pm_direct == .
drop if pm_indirect == .
gen dist1 = area - 20 if cutoff == 1
replace dist1 = area - 50 if cutoff == 2
gen bench_dir = pm_direct if year < 2012
bys city_id cutoff: egen mean_bench_dir = mean(bench_dir)
gen bench_in = pm_indirect if year < 2012
bys city_id cutoff: egen mean_bench_in = mean(bench_in)
gen RD_Estimate = .
gen above = dist1 > 0
replace RD_Estimate = c.post1#c.number
eststo clear
reghdfe pm_direct RD_Estimate c.post1#c.area c.post1#c.pop if cutoff == 1, a(city_id year#month pred tem_meand age_year incentive2#time) cluster(city_id)
eststo A
summ pm_direct
estadd scalar ysumm = r(mean)
estadd scalar EN = e(N_full)
ivreghdfe pm_direct c.post1#c.area c.post1#c.pop (RD_Estimate=c.post1#c.number_iv) if cutoff == 1, a(city_id year#month pred tem_meand age_year incentive2#time) cluster(city_id)
eststo B
summ pm_direct
estadd scalar ysumm = r(mean)
estadd scalar EN = e(N_full)
rdrobust pm_direct dist1 if year>=2015, fuzzy(number) p(1) h(11.3) covs(cutoff mean_bench_dir year month) kernel(uni) vce(cluster city_id)
estadd scalar EN = e(N_h_l) + e(N_h_r)
summ pm_direct if abs(dist1) < 11.3
estadd scalar ysumm = r(mean)
eststo C
replace RD_Estimate = c.post1#c.above
reghdfe pm_direct RD_Estimate post1 above dist1 c.post1#c.dist1 c.above#c.dist1 c.post#c.above#c.dist1 cutoff if abs(dist1) < 11.3, a(time) cl(city_id)
estadd scalar EN = e(N)
summ pm_direct if abs(dist1) < 11.3
estadd scalar ysumm = r(mean)
eststo D
esttab A B C D using "$out_files/TableC14b.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 ysumm, labels("Observations" "Mean Outcome")) starlevels(* 0.10 ** 0.05 *** 0.01) tex
replace RD_Estimate = c.post1#c.number
eststo clear
reghdfe pm_indirect RD_Estimate c.post1#c.area c.post1#c.pop if cutoff == 1, a(city_id year#month pred tem_meand age_year incentive2#time) cluster(city_id)
eststo A
summ pm_indirect
estadd scalar ysumm = r(mean)
estadd scalar EN = e(N_full)
ivreghdfe pm_indirect c.post1#c.area c.post1#c.pop pre tem_mean (RD_Estimate=c.post1#c.number_iv) if cutoff == 1, a(city_id year#month pred tem_meand age_year incentive2#time) cluster(city_id)
eststo B
summ pm_indirect
estadd scalar ysumm = r(mean)
estadd scalar EN = e(N_full)
rdrobust pm_indirect dist1 if year>=2015, fuzzy(number) p(1) h(11.3) covs(cutoff mean_bench_in year month) kernel(uni) vce(cluster city_id)
estadd scalar EN = e(N_h_l) + e(N_h_r)
summ pm_indirect if abs(dist1) < 11.3
estadd scalar ysumm = r(mean)
eststo C
replace RD_Estimate = c.post1#c.above
reghdfe pm_indirect 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)
summ pm_indirect if abs(dist1) < 11.3
estadd scalar ysumm = r(mean)
estadd scalar EN = e(N)
eststo D
esttab A B C D using "$out_files/TableC14c.tex", keep(RD_Estimate) transform(@/1.21 1/1.21, pattern(0 0 0 1)) replace b(a2) se(a2) label noconstant nolines nogaps compress fragment nonumbers mlabels(none) coeflabels(RD_Estimate "\# Monitors") stats(EN ysumm, labels("Observations" "Mean Outcome")) starlevels(* 0.10 ** 0.05 *** 0.01) tex
* Spillover in enf
use "$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_10 RD_Estimate c.post1#c.area c.post1#c.pop, a(city_id year#quarter pred tem_meand age_year incentive2#time) cluster(city_id)
summ log_any_air_10
estadd scalar ysumm = r(mean)
estadd scalar EN = e(N_full)
eststo A
ivreghdfe log_any_air_10 c.post1#c.area c.post1#c.pop (RD_Estimate=c.post1#c.number_iv), a(city_id year#quarter pred tem_meand age_year incentive2#time) cluster(city_id)
summ log_any_air_10
estadd scalar ysumm = r(mean)
estadd scalar EN = e(N_full)
eststo B
use "$data_files/city_enf_rd.dta", clear
gen dist1 = area - 20 if cutoff == 1
replace dist1 = area - 50 if cutoff == 2
gen bench_10 = log_any_air_10 if year < 2012
bys city_id cutoff: egen mean_bench_10 = mean(bench_10)
gen above = dist1 > 0
gen RD_Estimate = c.post1#c.above
rdrobust log_any_air_10 dist1 if year>=2015, fuzzy(number) p(1) h(11.3) covs(cutoff mean_bench_10 year quarter) kernel(uni) vce(cluster city_id)
summ log_any_air_10 if abs(dist1)<11.3
estadd scalar ysumm = r(mean)
estadd scalar EN = e(N_h_l) + e(N_h_r)
estadd scalar band = e(h_l)
eststo C
reghdfe log_any_air_10 RD_Estimate post1 above dist1 c.post1#c.dist1 c.above#c.dist1 c.post1#c.above#c.dist1 cutoff if abs(dist1) < 11.3, a(time) cl(city_id)
summ log_any_air_10 if abs(dist1)<11.3
estadd scalar ysumm = r(mean)
estadd scalar EN = e(N)
estadd scalar band = 11.3
eststo D
esttab A B C D using "$out_files/TableC14d.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 ysumm, labels("Observations" "Mean Outcome")) starlevels(* 0.10 ** 0.05 *** 0.01) tex
use "$data_files/city_enf.dta", clear
label variable post1 "Post"
label variable number "\# Mon"
label variable number_iv "Min \# Mon"
gen RD_Estimate = c.post1#c.number
eststo clear
reghdfe log_any_air_20 RD_Estimate c.post1#c.area c.post1#c.pop, a(city_id year#quarter pred tem_meand age_year incentive2#time) cluster(city_id)
summ log_any_air_20
estadd scalar ysumm = r(mean)
estadd scalar EN = e(N_full)
eststo A
ivreghdfe log_any_air_20 c.post1#c.area c.post1#c.pop (RD_Estimate=c.post1#c.number_iv), a(city_id year#quarter pred tem_meand age_year incentive2#time) cluster(city_id)
summ log_any_air_20
estadd scalar ysumm = r(mean)
estadd scalar EN = e(N_full)
eststo B
use "$data_files/city_enf_rd.dta", clear
gen dist1 = area - 20 if cutoff == 1
replace dist1 = area - 50 if cutoff == 2
gen bench_20 = log_any_air_20 if year < 2012
bys city_id cutoff: egen mean_bench_20 = mean(bench_20)
gen above = dist1 > 0
gen RD_Estimate = c.post1#c.above
rdrobust log_any_air_20 dist1 if year>=2015, fuzzy(number) p(1) h(11.3) covs(cutoff mean_bench_20 year quarter) kernel(uni) vce(cluster city_id)
summ log_any_air_20 if abs(dist1)<11.3
estadd scalar ysumm = r(mean)
estadd scalar EN = e(N_h_l) + e(N_h_r)
estadd scalar band = e(h_l)
eststo C
reghdfe log_any_air_20 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)
summ log_any_air_20 if abs(dist1)<11.3
estadd scalar ysumm = r(mean)
estadd scalar EN = e(N)
estadd scalar band = 11.3
eststo D
esttab A B C D using "$out_files/TableC14e.tex", keep(RD_Estimate) transform(@/1.21 1/1.21, pattern(0 0 0 1)) replace b(a2) se(a2) label noconstant nolines nogaps compress fragment nonumbers mlabels(none) coeflabels(RD_Estimate "\# Monitors") stats(EN ysumm, labels("Observations" "Mean Outcome")) starlevels(* 0.10 ** 0.05 *** 0.01) tex
use "$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_50 RD_Estimate c.post1#c.area c.post1#c.pop, a(city_id pred tem_meand age_year incentive2#time) cluster(city_id)
summ log_any_air_50
estadd scalar ysumm = r(mean)
estadd scalar EN = e(N_full)
eststo A
ivreghdfe log_any_air_50 c.post1#c.area c.post1#c.pop (RD_Estimate=c.post1#c.number_iv), a(city_id pred tem_meand age_year incentive2#time) cluster(city_id)
summ log_any_air_50
estadd scalar ysumm = r(mean)
estadd scalar EN = e(N_full)
eststo B
use "$data_files/city_enf_rd.dta", clear
gen dist1 = area - 20 if cutoff == 1
replace dist1 = area - 50 if cutoff == 2
gen bench_50 = log_any_air_50 if year < 2012
bys city_id cutoff: egen mean_bench_50 = mean(bench_50)
gen above = dist1 > 0
gen RD_Estimate = c.post1#c.above
rdrobust log_any_air_50 dist1 if year>=2015, fuzzy(number) p(1) h(11.3) covs(cutoff mean_bench_50 year quarter) kernel(uni) vce(cluster city_id)
summ log_any_air_50 if abs(dist1)<11.3
estadd scalar ysumm = r(mean)
estadd scalar EN = e(N_h_l) + e(N_h_r)
estadd local kern = "Uniform"
estadd scalar band = 11.3
eststo C
reghdfe log_any_air_50 RD_Estimate post1 above dist1 c.post1#c.dist1 c.above#c.dist1 c.post1#c.above#c.dist1 cutoff if abs(dist1) < 11.3, a(time) cl(city_id)
summ log_any_air_50 if abs(dist1)<11.3
estadd scalar ysumm = r(mean)
estadd scalar EN = e(N)
estadd local kern = "Uniform"
estadd scalar band = 11.3
eststo D
esttab A B C D using "$out_files/TableC14f.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 ysumm kern band, labels("Observations" "Mean Outcome" "Kernel" "Bandwidth")) starlevels(* 0.10 ** 0.05 *** 0.01) tex
**==============================================================================
* Table C15
* Promotion
use "$data_files/city_pm.dta", clear
label variable post1 "Post"
label variable number "\# Mon"
label variable number_iv "Min \# Mon"
gen above57 = age<=57
gen RD_Estimate = c.post1#c.number
label variable above57 "Below 58"
eststo clear
reghdfe pm25 RD_Estimate c.post1#c.area c.post1#c.pop c.RD_Estimate#c.above57, a(city_id year#month pred tem_meand age_year incentive2#time) cluster(city_id)
eststo A
estadd ysumm, mean
estadd scalar EN = e(N_full)
reghdfe pm25 RD_Estimate c.post1#c.area c.post1#c.pop c.RD_Estimate#c.above57 if age >= 51 & age <= 62, a(city_id year#month pred tem_meand age_year incentive2#time) cluster(city_id)
eststo B
estadd ysumm, mean
estadd scalar EN = e(N_full)
reghdfe pm25 RD_Estimate c.post1#c.area c.post1#c.pop c.RD_Estimate#c.above57 if age >= 53 & age <= 62, a(city_id year#month pred tem_meand age_year incentive2#time) cluster(city_id)
eststo C
estadd ysumm, mean
estadd scalar EN = e(N_full)
reghdfe pm25 RD_Estimate c.post1#c.area c.post1#c.pop c.RD_Estimate#c.above57 if age >= 55 & age <= 60, a(city_id year#month pred tem_meand age_year incentive2#time) cluster(city_id)
eststo D
estadd ysumm, mean
estadd scalar EN = e(N_full)
esttab A B C D using "$out_files/TableC15a.tex", replace b(a2) noconstant se(a2) nolines nogaps compress fragment nonumbers label mlabels(none) collabels() keep(RD_Estimate c.RD_Estimate#c.above57) coeflabels(RD_Estimate "\# Monitors" c.RD_Estimate#c.above57 "\# Monitors $\times$ Below 58") stats(ymean EN, labels("Mean Outcome" "Observations")) starlevels(* 0.10 ** 0.05 *** 0.01) substitute(\_ _) tex
use "$data_files/city_enf.dta", clear
label variable post1 "Post"
label variable number "\# Mon"
label variable number_iv "Min \# Mon"
gen above57 = age <= 57
gen RD_Estimate = c.post1#c.number
label variable above57 "Below 58"
eststo clear
reghdfe log_any_air RD_Estimate c.post1#c.area c.post1#c.pop c.RD_Estimate#c.above57, a(city_id year#quarter pred tem_meand age_year incentive2#time) cluster(city_id)
eststo A
estadd ysumm, mean
estadd scalar EN = e(N_full)
reghdfe log_any_air RD_Estimate c.post1#c.area c.post1#c.pop c.RD_Estimate#c.above57 if age >= 51 & age <= 62, a(city_id year#quarter pred tem_meand age_year incentive2#time) cluster(city_id)
eststo B
estadd ysumm, mean
estadd scalar EN = e(N_full)
reghdfe log_any_air RD_Estimate c.post1#c.area c.post1#c.pop c.RD_Estimate#c.above57 if age >= 53 & age <= 62, a(city_id year#quarter pred tem_meand age_year incentive2#time) cluster(city_id)
eststo C
estadd ysumm, mean
estadd scalar EN = e(N_full)
reghdfe log_any_air RD_Estimate c.post1#c.area c.post1#c.pop c.RD_Estimate#c.above57 if age >= 55 & age <= 60, a(city_id year#quarter pred tem_meand age_year incentive2#time) cluster(city_id)
eststo D
estadd ysumm, mean
estadd scalar EN = e(N_full)
esttab A B C D using "$out_files/TableC15b.tex", replace b(a2) noconstant se(a2) nolines nogaps compress fragment nonumbers label mlabels(none) collabels() keep(RD_Estimate c.RD_Estimate#c.above57) coeflabels(RD_Estimate "\# Monitors" c.RD_Estimate#c.above57 "\# Monitors $\times$ Below 58") stats(ymean EN, labels("Mean Outcome" "Observations")) starlevels(* 0.10 ** 0.05 *** 0.01) substitute(\_ _) tex
**==============================================================================
* Table C16
* Balance
use "$data_files/city_pm.dta", clear
keep if year < 2015
replace light = log(light)
gen log_any_air = log(any_air+1)
collapse (mean) pm25 light log_any_air number area pop age city_id, by(city_cn)
gen above57 = age > 57
label variable number "\# Monitors"
label variable area "Size of buildup area"
label variable pop "Urban population"
label variable pm25 "AOD before 2015"
label variable light "Night light before 2015"
label variable log_any_air "log(\# Firms) before 2015"
regress above57 number area pop pm25 light log_any_air
test number area pop pm25 light log_any_air
regress above57 number area pop pm25 light log_any_air if age >= 51 & age <= 62
test number area pop pm25 light log_any_air
regress above57 number area pop pm25 light log_any_air if age >= 53 & age <= 62
test number area pop pm25 light log_any_air
regress above57 number area pop pm25 light log_any_air if age >= 55 & age <= 60
test number area pop pm25 light log_any_air
eststo clear
eststo tot: estpost summarize number area pop pm25 light log_any_air
eststo treat1: estpost summarize number area pop pm25 light log_any_air if above57==1
eststo control1: estpost summarize number area pop pm25 light log_any_air if above57==0
eststo diff1: estpost ttest number area pop pm25 light log_any_air, by(above57)
eststo diff1: estadd scalar pvalue = 0.19
eststo diff2: estpost ttest number area pop pm25 light log_any_air if age >= 51 & age <= 62, by(above57)
eststo diff2: estadd scalar pvalue = 0.15
eststo diff3: estpost ttest number area pop pm25 light log_any_air if age >= 53 & age <= 62, by(above57)
eststo diff3: estadd scalar pvalue = 0.29
eststo diff4: estpost ttest number area pop pm25 light log_any_air if age >= 55 & age <= 60, by(above57)
eststo diff4: estadd scalar pvalue = 0.37
esttab tot treat1 control1 diff1 diff2 diff3 diff4 using "$out_files/TableC16.tex", tex label noconstant nolines nogaps compress fragment nonumbers mlabels(,none) collabels(,none) cells(mean(pattern(1 1 1 0 0 0 0) fmt(a2)) & b(star pattern(0 0 0 1 1 1 1) fmt(a2)) sd(pattern(1 1 1 0 0 0 0) fmt(a2) par) & se(pattern(0 0 0 1 1 1 1) fmt(a2) par)) stats(N pvalue, labels("Observations" "Joint Test (p-value)")) starlevels(* 0.10 ** 0.05 *** 0.01) replace
**==============================================================================
* Table C17
use "$data_files/city_pm.dta", clear
label variable post1 "Post"
label variable number "\# Mon"
label variable number_iv "Min \# Mon"
merge 1:1 city_cn year month using "$data_files/Raw/baidu.dta"
keep if _merge == 3
drop _merge
replace sear_freq_w1 = sear_freq_w1/pop
replace sear_freq_w2 = sear_freq_w2/pop
replace sear_freq_w3 = sear_freq_w3/pop
replace sear_freq_w4 = sear_freq_w4/pop
replace sear_freq_w5 = sear_freq_w5/pop
foreach x of varlist sear_freq_w* {
egen m_`x' = mean(`x')
egen sd_`x' = sd(`x')
gen std_`x' = (`x'- m_`x')/sd_`x'
}
forvalues i=1/5 {
replace sear_freq_w`i'=0 if sear_freq_w`i'==.
gen log_w`i'=log(sear_freq_w`i'+1)
gen any_w`i'=0
replace any_w`i'=1 if sear_freq_w`i'>0 & sear_freq_w`i'!=.
}
eststo clear
ivreghdfe log_w1 i.time#c.area i.time#c.pop (c.post1#c.number=c.post1#c.number_iv), a(city_id year#month pred tem_meand age_year incentive2#time) cluster(city_id)
eststo A
summ log_w1
estadd scalar ymean = r(mean)
ivreghdfe log_w2 i.time#c.area i.time#c.pop (c.post1#c.number=c.post1#c.number_iv), a(city_id year#month pred tem_meand age_year incentive2#time) cluster(city_id)
eststo B
summ log_w2
estadd scalar ymean = r(mean)
ivreghdfe log_w3 i.time#c.area i.time#c.pop (c.post1#c.number=c.post1#c.number_iv), a(city_id year#month pred tem_meand age_year incentive2#time) cluster(city_id)
eststo C
summ log_w3
estadd scalar ymean = r(mean)
ivreghdfe log_w4 i.time#c.area i.time#c.pop (c.post1#c.number=c.post1#c.number_iv), a(city_id year#month pred tem_meand age_year incentive2#time) cluster(city_id)
eststo D
summ log_w4
estadd scalar ymean = r(mean)
ivreghdfe log_w5 i.time#c.area i.time#c.pop (c.post1#c.number=c.post1#c.number_iv), a(city_id year#month pred tem_meand age_year incentive2#time) cluster(city_id)
eststo E
summ log_w5
estadd scalar ymean = r(mean)
estfe A B C D E, labels(city_id "City FE" time "Time FE")
return list
esttab A B C D E using "$out_files/TableC17.tex", replace b(a2) se(a2) keep(c.post1#c.number) coeflabels(c.post1#c.number "\# Monitors") label noconstant nolines nogaps compress fragment nonumbers mlabels(none) collabels() stats(ymean N, labels( "Mean Outcome" "Observations")) starlevels(* 0.10 ** 0.05 *** 0.01)
**==============================================================================
** Figures
**==============================================================================
* Figure D3
use "$data_files/firm_enf.dta", clear
fvset base 4 min_d_d4
reghdfe any_air i.post##i.min_d_d4 if min_dist<50 & starty<=2010, absorb(id time industry#time prov_id#time) cluster(city_id) poolsize(1) compact
coefplot, baselevels omitted vert yline(0, lc(cranberry)) keep(1.post1#*) coeflabels(1.post1#0.min_d_d4 = "0-5km" 1.post1#1.min_d_d4 = "5-10km" 1.post1#2.min_d_d4 = "10-15km" 1.post1#3.min_d_d4 = "15-20km" 1.post1#4.min_d_d4 = "20-50km") drop() graphregion(color(white) fcolor(white)) plotregion(color(white)) ytitle(Parameter Estimate) xtitle() le(95)
graph export "$out_files/any_air_gradient_50_ci.pdf", replace
**==============================================================================
* Figure D5
use "$data_files/firm_enf.dta", clear
merge m:1 city_id using "$data_files/Raw/city_info.dta", keepusing(env_lat env_lon centroid_lat centroid_lon)
keep if _merge == 3
drop _merge
geodist env_lat env_lon lat lon, gen(env_dist)
gen min_env_d4 = int(env_dist/5)
replace min_env_d4 = 4 if min_env_d4 > 4
* set base level
fvset base 20 time
fvset base 4 min_env_d4
geodist centroid_lat centroid_lon lat lon, gen(cen_dist)
gen min_cen_d4 = int(cen_dist/5)
replace min_cen_d4 = 4 if min_cen_d4 > 4
* set base level
fvset base 20 time
fvset base 4 min_cen_d4
reghdfe any_air i.time##i.min_env_d4 i.post##i.min_d_d4 i.post##i.min_cen_d4 if env_dist<50 & starty<=2010, absorb(time id industry#time prov_id#time) cluster(city_id) poolsize(1) compact
qui coefplot, baselevels omitted vert yline(0, lc(black)) xline(20.5, lc(cranberry) lp(dash)) keep(*.time#0.min_env_d4) drop() graphregion(color(white) fcolor(white)) plotregion(color(white)) ytitle(Parameter Estimate) xtitle(Year) le(95) mc(black) ciopts(recast(rcap) lwidth(0.3) lpattern(dash)) gen(enf_5_) replace
twoway (rarea enf_5_ul1 enf_5_ll1 enf_5_at, color(gs6%20)) (scatter enf_5_b enf_5_at, msymbol(p) mc(black%60)) (line enf_5_b enf_5_at, lp(dash) lc(blackblack%60)), yline(0, lc(black)) xline(20.5, lp(dash) lc(cranberry)) graphregion(fcolor(white) lcolor(none) ifcolor(white) ilcolor(white) ilpattern(blank)) plotregion(fcolor(white) lcolor(none) ifcolor(white) ilcolor(white)) legend(off) ytitle("") xtitle("") xtick(1(1)32) xlabel(1 "2010" 5 "2011" 9 "2012" 13 "2013" 17 "2014" 21 "2015" 25 "2016" 29 "2017") ysc(r(-0.01 0.01)) ylab(-0.01(0.005)0.01)
graph export "$out_files/any_air_env_event_5.pdf", replace
qui coefplot, baselevels omitted vert yline(0, lc(black)) xline(20.5, lc(cranberry) lp(dash)) keep(*.time#1.min_env_d4) drop() graphregion(color(white) fcolor(white)) plotregion(color(white)) ytitle(Parameter Estimate) xtitle(Year) le(95) mc(black) ciopts(recast(rcap) lwidth(0.3) lpattern(dash)) gen(enf_10_) replace
twoway (rarea enf_10_ul1 enf_10_ll1 enf_10_at, color(gs6%20)) (scatter enf_10_b enf_10_at, msymbol(p) mc(black%60)) (line enf_10_b enf_10_at, lp(dash) lc(blackblack%60)), yline(0, lc(black)) xline(20.5, lp(dash) lc(cranberry)) graphregion(fcolor(white) lcolor(none) ifcolor(white) ilcolor(white) ilpattern(blank)) plotregion(fcolor(white) lcolor(none) ifcolor(white) ilcolor(white)) legend(off) ytitle("") xtitle("") xtick(1(1)32) xlabel(1 "2010" 5 "2011" 9 "2012" 13 "2013" 17 "2014" 21 "2015" 25 "2016" 29 "2017") ysc(r(-0.01 0.01)) ylab(-0.01(0.005)0.01)
graph export "$out_files/any_air_env_event_10.pdf", replace
qui coefplot, baselevels omitted vert yline(0, lc(black)) xline(20.5, lc(cranberry) lp(dash)) keep(*.time#2.min_env_d4) drop() graphregion(color(white) fcolor(white)) plotregion(color(white)) ytitle(Parameter Estimate) xtitle(Year) le(95) mc(black) ciopts(recast(rcap) lwidth(0.3) lpattern(dash)) gen(enf_15_) replace
twoway (rarea enf_15_ul1 enf_15_ll1 enf_15_at, color(gs6%20)) (scatter enf_15_b enf_10_at, msymbol(p) mc(black%60)) (line enf_15_b enf_15_at, lp(dash) lc(blackblack%60)), yline(0, lc(black)) xline(20.5, lp(dash) lc(cranberry)) graphregion(fcolor(white) lcolor(none) ifcolor(white) ilcolor(white) ilpattern(blank)) plotregion(fcolor(white) lcolor(none) ifcolor(white) ilcolor(white)) legend(off) ytitle("") xtitle("") xtick(1(1)32) xlabel(1 "2010" 5 "2011" 9 "2012" 13 "2013" 17 "2014" 21 "2015" 25 "2016" 29 "2017") ysc(r(-0.01 0.01)) ylab(-0.01(0.005)0.01)
graph export "$out_files/any_air_env_event_15.pdf", replace
qui coefplot, baselevels omitted vert yline(0, lc(black)) xline(20.5, lc(cranberry) lp(dash)) keep(*.time#3.min_env_d4) drop() graphregion(color(white) fcolor(white)) plotregion(color(white)) ytitle(Parameter Estimate) xtitle(Year) le(95) mc(black) ciopts(recast(rcap) lwidth(0.3) lpattern(dash)) gen(enf_20_) replace
twoway (rarea enf_20_ul1 enf_20_ll1 enf_20_at, color(gs6%20)) (scatter enf_20_b enf_20_at, msymbol(p) mc(black%60)) (line enf_20_b enf_20_at, lp(dash) lc(blackblack%60)), yline(0, lc(black)) xline(20.5, lp(dash) lc(cranberry)) graphregion(fcolor(white) lcolor(none) ifcolor(white) ilcolor(white) ilpattern(blank)) plotregion(fcolor(white) lcolor(none) ifcolor(white) ilcolor(white)) legend(off) ytitle("") xtitle("") xtick(1(1)32) xlabel(1 "2010" 5 "2011" 9 "2012" 13 "2013" 17 "2014" 21 "2015" 25 "2016" 29 "2017") ysc(r(-0.01 0.01)) ylab(-0.01(0.005)0.01)
graph export "$out_files/any_air_env_event_20.pdf", replace
reghdfe any_air i.time##i.min_cen_d4 i.post##i.min_d_d4 i.post##i.min_env_d4 if cen_dist<50 & starty<=2010, absorb(time id industry#time prov_id#time) cluster(city_id) poolsize(1) compact
qui coefplot, baselevels omitted vert yline(0, lc(black)) xline(20.5, lc(cranberry) lp(dash)) keep(*.time#0.min_cen_d4) drop() graphregion(color(white) fcolor(white)) plotregion(color(white)) ytitle(Parameter Estimate) xtitle(Year) le(95) mc(black) ciopts(recast(rcap) lwidth(0.3) lpattern(dash)) gen(enf_5_) replace
twoway (rarea enf_5_ul1 enf_5_ll1 enf_5_at, color(gs6%20)) (scatter enf_5_b enf_5_at, msymbol(p) mc(black%60)) (line enf_5_b enf_5_at, lp(dash) lc(blackblack%60)), yline(0, lc(black)) xline(20.5, lp(dash) lc(cranberry)) graphregion(fcolor(white) lcolor(none) ifcolor(white) ilcolor(white) ilpattern(blank)) plotregion(fcolor(white) lcolor(none) ifcolor(white) ilcolor(white)) legend(off) ytitle("") xtitle("") xtick(1(1)32) xlabel(1 "2010" 5 "2011" 9 "2012" 13 "2013" 17 "2014" 21 "2015" 25 "2016" 29 "2017") ysc(r(-0.01 0.01)) ylab(-0.01(0.005)0.01)
graph export "$out_files/any_air_cen_event_5.pdf", replace
qui coefplot, baselevels omitted vert yline(0, lc(black)) xline(20.5, lc(cranberry) lp(dash)) keep(*.time#1.min_cen_d4) drop() graphregion(color(white) fcolor(white)) plotregion(color(white)) ytitle(Parameter Estimate) xtitle(Year) le(95) mc(black) ciopts(recast(rcap) lwidth(0.3) lpattern(dash)) gen(enf_10_) replace
twoway (rarea enf_10_ul1 enf_10_ll1 enf_10_at, color(gs6%20)) (scatter enf_10_b enf_10_at, msymbol(p) mc(black%60)) (line enf_10_b enf_10_at, lp(dash) lc(blackblack%60)), yline(0, lc(black)) xline(20.5, lp(dash) lc(cranberry)) graphregion(fcolor(white) lcolor(none) ifcolor(white) ilcolor(white) ilpattern(blank)) plotregion(fcolor(white) lcolor(none) ifcolor(white) ilcolor(white)) legend(off) ytitle("") xtitle("") xtick(1(1)32) xlabel(1 "2010" 5 "2011" 9 "2012" 13 "2013" 17 "2014" 21 "2015" 25 "2016" 29 "2017") ysc(r(-0.01 0.01)) ylab(-0.01(0.005)0.01)
graph export "$out_files/any_air_cen_event_10.pdf", replace
qui coefplot, baselevels omitted vert yline(0, lc(black)) xline(20.5, lc(cranberry) lp(dash)) keep(*.time#2.min_cen_d4) drop() graphregion(color(white) fcolor(white)) plotregion(color(white)) ytitle(Parameter Estimate) xtitle(Year) le(95) mc(black) ciopts(recast(rcap) lwidth(0.3) lpattern(dash)) gen(enf_15_) replace
twoway (rarea enf_15_ul1 enf_15_ll1 enf_15_at, color(gs6%20)) (scatter enf_15_b enf_10_at, msymbol(p) mc(black%60)) (line enf_15_b enf_15_at, lp(dash) lc(blackblack%60)), yline(0, lc(black)) xline(20.5, lp(dash) lc(cranberry)) graphregion(fcolor(white) lcolor(none) ifcolor(white) ilcolor(white) ilpattern(blank)) plotregion(fcolor(white) lcolor(none) ifcolor(white) ilcolor(white)) legend(off) ytitle("") xtitle("") xtick(1(1)32) xlabel(1 "2010" 5 "2011" 9 "2012" 13 "2013" 17 "2014" 21 "2015" 25 "2016" 29 "2017") ysc(r(-0.01 0.01)) ylab(-0.01(0.005)0.01)
graph export "$out_files/any_air_cen_event_15.pdf", replace
qui coefplot, baselevels omitted vert yline(0, lc(black)) xline(20.5, lc(cranberry) lp(dash)) keep(*.time#3.min_cen_d4) drop() graphregion(color(white) fcolor(white)) plotregion(color(white)) ytitle(Parameter Estimate) xtitle(Year) le(95) mc(black) ciopts(recast(rcap) lwidth(0.3) lpattern(dash)) gen(enf_20_) replace
twoway (rarea enf_20_ul1 enf_20_ll1 enf_20_at, color(gs6%20)) (scatter enf_20_b enf_20_at, msymbol(p) mc(black%60)) (line enf_20_b enf_20_at, lp(dash) lc(blackblack%60)), yline(0, lc(black)) xline(20.5, lp(dash) lc(cranberry)) graphregion(fcolor(white) lcolor(none) ifcolor(white) ilcolor(white) ilpattern(blank)) plotregion(fcolor(white) lcolor(none) ifcolor(white) ilcolor(white)) legend(off) ytitle("") xtitle("") xtick(1(1)32) xlabel(1 "2010" 5 "2011" 9 "2012" 13 "2013" 17 "2014" 21 "2015" 25 "2016" 29 "2017") ysc(r(-0.01 0.01)) ylab(-0.01(0.005)0.01)
graph export "$out_files/any_air_cen_event_20.pdf", replace
**==============================================================================
* Figure D5
use "$data_files/city_enf.dta", clear
set scheme s1mono
fvset base 2014 year
fvset base 20 time
reghdfe log_any_air i.time##c.number i.post1##c.area i.post1##c.pop, a(city_id year#quarter pred tem_meand age_year incentive2#time) cluster(city_id) poolsize(1) compact
coefplot, baselevels omitted vert yline(-0, lc(black)) xline(20.5, lp(dash) lc(cranberry)) keep(*me#c.number) coeflabels() drop() graphregion(color(white) fcolor(white)) plotregion(color(white)) ytitle(Parameter Estimate) le(95) mc(black) gen(pm1_) replace
regress number number_iv
predict num_hat
reghdfe log_any_air i.time##c.num_hat i.post1##c.area i.post1##c.pop, a(city_id year#quarter pred tem_meand age_year incentive2#time) cluster(city_id) poolsize(1) compact
coefplot, baselevels omitted vert yline(-0, lc(black)) xline(20.5, lp(dash) lc(cranberry)) keep(*me#c.num_hat) coeflabels() drop() graphregion(color(white) fcolor(white)) plotregion(color(white)) ytitle(Parameter Estimate) le(95) mc(black) gen(pm2_) replace
twoway (rarea pm1_ul1 pm1_ll1 pm1_at, color(gs6%20)) (line pm1_b pm1_at, lwidth(medthick) lp(dash) lc(blackblack%70)) (rarea pm2_ul1 pm2_ll1 pm2_at, color(gs6%20)) (line pm2_b pm2_at, lp(dash) lc(blackblack%40)), yline(-0, lc(black)) xline(20.5, lp(dash) lc(cranberry)) graphregion(fcolor(white) lcolor(none) ifcolor(white) ilcolor(white) ilpattern(blank)) plotregion(fcolor(white) lcolor(none) ifcolor(white) ilcolor(white)) ytitle("") xtitle("") xtick(1(1)32) xlabel(1 "2010" 5 "2011" 9 "2012" 13 "2013" 17 "2014" 21 "2015" 25 "2016" 29 "2017") ysc(r(-0.2 0.6)) ylabel(-0.2(0.2)0.6) legend(order(2 "DiD" 4 "DiD+IV") pos(2) ring(0) rows(2))
graph export "$out_files/eventenf.pdf", replace
**==============================================================================
* Figure D11
* balance
use "$data_files/city_pm.dta", clear
keep if year < 2015
replace light = log(light)
gen log_any_air = log(any_air+1)
collapse (mean) pm25 light log_any_air number area pop age city_id GDP, by(city_cn)
gen above57 = age > 57
label variable number "\# Monitors"
label variable area "Size of buildup area"
label variable pop "Urban population"
label variable pm25 "AOD before 2015"
label variable light "Night light before 2015"
label variable log_any_air "log(\# Firms) before 2015"
fvset base 58 age
regress number i.age if age>=50 & age<=60
coefplot, baselevels omitted vert drop(_cons) keep(*.age) yline(0, lc(cranberry)) graphregion(fcolor(white) lcolor(none) ifcolor(white) ilcolor(white) ilpattern(blank)) plotregion(fcolor(white) lcolor(none) ifcolor(white) ilcolor(white)) legend(off) ytitle("") xtitle("Age of Mayor")coeflabels(50.age = "50" 51.age = "51" 52.age = "52" 53.age = "53" 54.age = "54" 55.age = "55" 56.age = "56" 57.age = "57" 58.age = "58" 59.age = "59" 60.age = "60") le(95)
graph export "$out_files/number_age.pdf", replace
regress area i.age if age>=50 & age<=60
coefplot, baselevels omitted vert drop(_cons) keep(*.age) yline(0, lc(cranberry)) graphregion(fcolor(white) lcolor(none) ifcolor(white) ilcolor(white) ilpattern(blank)) plotregion(fcolor(white) lcolor(none) ifcolor(white) ilcolor(white)) legend(off) ytitle("") xtitle("Age of Mayor")coeflabels(50.age = "50" 51.age = "51" 52.age = "52" 53.age = "53" 54.age = "54" 55.age = "55" 56.age = "56" 57.age = "57" 58.age = "58" 59.age = "59" 60.age = "60") le(95)
graph export "$out_files/area_age.pdf", replace
regress pop i.age if age>=50 & age<=60
coefplot, baselevels omitted vert drop(_cons) keep(*.age) yline(0, lc(cranberry)) graphregion(fcolor(white) lcolor(none) ifcolor(white) ilcolor(white) ilpattern(blank)) plotregion(fcolor(white) lcolor(none) ifcolor(white) ilcolor(white)) legend(off) ytitle("") xtitle("Age of Mayor")coeflabels(50.age = "50" 51.age = "51" 52.age = "52" 53.age = "53" 54.age = "54" 55.age = "55" 56.age = "56" 57.age = "57" 58.age = "58" 59.age = "59" 60.age = "60") le(95)
graph export "$out_files/pop_age.pdf", replace
regress pm25 i.age if age>=50 & age<=60
coefplot, baselevels omitted vert drop(_cons) keep(*.age) yline(0, lc(cranberry)) graphregion(fcolor(white) lcolor(none) ifcolor(white) ilcolor(white) ilpattern(blank)) plotregion(fcolor(white) lcolor(none) ifcolor(white) ilcolor(white)) legend(off) ytitle("") xtitle("Age of Mayor")coeflabels(50.age = "50" 51.age = "51" 52.age = "52" 53.age = "53" 54.age = "54" 55.age = "55" 56.age = "56" 57.age = "57" 58.age = "58" 59.age = "59" 60.age = "60") le(95)
graph export "$out_files/pm_age.pdf", replace
regress light i.age if age>=50 & age<=60
coefplot, baselevels omitted vert drop(_cons) keep(*.age) yline(0, lc(cranberry)) graphregion(fcolor(white) lcolor(none) ifcolor(white) ilcolor(white) ilpattern(blank)) plotregion(fcolor(white) lcolor(none) ifcolor(white) ilcolor(white)) legend(off) ytitle("") xtitle("Age of Mayor")coeflabels(50.age = "50" 51.age = "51" 52.age = "52" 53.age = "53" 54.age = "54" 55.age = "55" 56.age = "56" 57.age = "57" 58.age = "58" 59.age = "59" 60.age = "60") le(95)
graph export "$out_files/light_age.pdf", replace
regress log_any_air i.age if age>=50 & age<=60
coefplot, baselevels omitted vert drop(_cons) keep(*.age) yline(0, lc(cranberry)) graphregion(fcolor(white) lcolor(none) ifcolor(white) ilcolor(white) ilpattern(blank)) plotregion(fcolor(white) lcolor(none) ifcolor(white) ilcolor(white)) legend(off) ytitle("") xtitle("Age of Mayor")coeflabels(50.age = "50" 51.age = "51" 52.age = "52" 53.age = "53" 54.age = "54" 55.age = "55" 56.age = "56" 57.age = "57" 58.age = "58" 59.age = "59" 60.age = "60") le(95)
graph export "$out_files/enf_age.pdf", replace
**==============================================================================
* Figure D7
* Bandwidths
use "$data_files/city_pm_rd.dta", clear
gen dist1 = area - 20 if cutoff == 1
replace dist1 = area - 50 if cutoff == 2
frame create fs fs_b fs_var
quietly{
forvalues x = 4(2)20 {
qui rdrobust number dist1, p(1) h(`x') kernel(uni) covs(cutoff) vce(cluster city_id)
frame post fs (e(tau_cl)) (e(se_tau_cl))
}
}
frame fs: gen fs_ul = fs_b + 1.96*fs_var
frame fs: gen fs_ll = fs_b - 1.96*fs_var
frame fs: gen fs_at = 2 + 2*_n
frame fs: twoway (connected fs_b fs_at, sort msymbol(S) color(black)) (line fs_ul fs_at, sort lpattern(dash) lcolor(gs9)) /*
*/ (line fs_ll fs_at, sort lpattern(dash) lcolor(gs9)), ytitle(Number of monitors) yline(0, lc(cranberry)) /*
*/ xtitle(Bandwidth) xline(11.3, lcolor(blue) lpattern(dash) lwidth(thin)) /*
*/ graphregion(fcolor(white) lcolor(none) ifcolor(white) ilcolor(white) ilpattern(blank)) plotregion(fcolor(white) lcolor(none) ifcolor(white) ilcolor(white)) legend(off) ysc(r(0 2)) ylabel(0(0.5)2) xlabel(4(2)20)
graph export "$out_files/band_fs.pdf", replace
gen bench = pm25 if year < 2012
bys city_id cutoff: egen mean_bench = mean(bench)
frame create rd rd_b rd_var
quietly{
forvalues x = 4(2)20 {
qui rdrobust pm25 dist1 if year >= 2015, fuzzy(number) covs(cutoff mean_bench year) p(1) h(`x') vce(cluster city_id) kernel(uni)
frame post rd (e(tau_cl)) (e(se_tau_cl))
}
}
frame rd: gen rd_ul = rd_b + 1.96*rd_var
frame rd: gen rd_ll = rd_b - 1.96*rd_var
frame rd: gen rd_at = 2 + 2*_n
frame rd: twoway (connected rd_b rd_at, sort msymbol(S) color(black)) (line rd_ul rd_at, sort lpattern(dash) lcolor(gs9)) /*
*/ (line rd_ll rd_at, sort lpattern(dash) lcolor(gs9)), ytitle(Number of monitors) yline(0, lc(cranberry)) /*
*/ xtitle(Bandwidth) xline(11.3, lcolor(blue) lpattern(dash) lwidth(thin)) /*
*/ graphregion(fcolor(white) lcolor(none) ifcolor(white) ilcolor(white) ilpattern(blank)) plotregion(fcolor(white) lcolor(none) ifcolor(white) ilcolor(white)) legend(off) ysc(r(-0.075 0.05)) ylabel(-0.075(0.025)0.05) xlabel(4(2)20)
graph export "$out_files/band_rd.pdf", replace
use "$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)
frame drop rd
frame create rd rd_b rd_var
quietly{
forvalues x = 4(2)20 {
qui rdrobust log_any_air dist1 if year >= 2015, fuzzy(number) covs(cutoff mean_bench year) p(1) h(`x') vce(cluster city_id) kernel(uni)
frame post rd (e(tau_cl)) (e(se_tau_cl))
}
}
frame rd: gen rd_ul = rd_b + 1.96*rd_var
frame rd: gen rd_ll = rd_b - 1.96*rd_var
frame rd: gen rd_at = 2 + 2*_n
frame rd: twoway (connected rd_b rd_at, sort msymbol(S) color(black)) (line rd_ul rd_at, sort lpattern(dash) lcolor(gs9)) /*
*/ (line rd_ll rd_at, sort lpattern(dash) lcolor(gs9)), ytitle(Number of monitors) yline(0, lc(cranberry)) /*
*/ xtitle(Bandwidth) xline(11.3, lcolor(blue) lpattern(dash) lwidth(thin)) /*
*/ graphregion(fcolor(white) lcolor(none) ifcolor(white) ilcolor(white) ilpattern(blank)) plotregion(fcolor(white) lcolor(none) ifcolor(white) ilcolor(white)) legend(off) ysc(r(-0.2 0.6)) ylabel(-0.2(0.2)0.6) xlabel(4(2)20)
graph export "$out_files/band_rd_enf.pdf", replace
**==============================================================================
* Figure D7
use "$data_files/city_pm_rd.dta", clear
gen dist1 = area - 20 if cutoff == 1
replace dist1 = area - 50 if cutoff == 2
hist dist1 if cutoff == 1 & year == 2015 & month == 1, /*
*/ start(-24) width(12) xline(0, lc(cranberry)) ysc(r(0 0.025)) /*
*/ ylabel(0(0.005)0.025) xtitle("Size of the Build-up Area") /*
*/ graphregion(fcolor(white) lcolor(none) ifcolor(white) ilcolor(white) ilpattern(blank)) /*
*/ plotregion(fcolor(white) lcolor(none) ifcolor(white) ilcolor(white)) /*
*/ legend(nobox region(fcolor(white) margin(zero) lcolor(white)))
graph export "$out_files/Cutoff1Score1.pdf", replace
hist dist1 if cutoff == 2 & year == 2015 & month == 1, /*
*/ start(-60) width(12) xline(0, lc(cranberry)) ysc(r(0 0.025)) /*
*/ ylabel(0(0.005)0.025) xtitle("Size of the Build-up Area") /*
*/ graphregion(fcolor(white) lcolor(none) ifcolor(white) ilcolor(white) ilpattern(blank)) /*
*/ plotregion(fcolor(white) lcolor(none) ifcolor(white) ilcolor(white)) /*
*/ legend(nobox region(fcolor(white) margin(zero) lcolor(white)))
graph export "$out_files/Cutoff2Score1.pdf", replace
rddensity dist1 if year==2015 & month==1 & dist1<40 & dist1>-40, all plot plot_range(-20 20) nohist graph_opt(legend(off) xtitle("Size of the Buildup Area") ytitle("Density") graphregion(fcolor(white) lcolor(none) ifcolor(white) ilcolor(white) ilpattern(blank)) plotregion(fcolor(white) lcolor(none) ifcolor(white) ilcolor(white)))
graph export "$out_files/DensityTest1.pdf", as(pdf) replace
**==============================================================================
* Figure D9
* hist
use "$data_files/Raw/firm_info.dta", clear
hist min_dist if min_dist < 50, xtitle("Distance to the closest monitor (km)") /*
*/ graphregion(fcolor(white) lcolor(none) ifcolor(white) ilcolor(white) ilpattern(blank)) /*
*/ plotregion(fcolor(white) lcolor(none) ifcolor(white) ilcolor(white)) /*
*/ legend(nobox region(fcolor(white) margin(zero) lcolor(white)))
graph export "$out_files/hist_min_dist.pdf", as(pdf) replace
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