|
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|
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|
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|
|
|
|
| qui:{
|
|
|
| import excel "Data\wordcount-eachspeech-all.xlsx", sheet("Sheet1") firstrow clear
|
| set obs 2655
|
| replace A="totnonstopwords" in 2655
|
| foreach v of varlist B-GI {
|
| egen totwordsX=total(`v')
|
| replace `v'=totwordsX in 2655
|
| drop totwordsX
|
| }
|
| foreach v of varlist B-GI {
|
| local x : variable label `v'
|
| rename `v' v`x'
|
| }
|
| keep if A=="DRUG" | A=="CRIME" | A=="RAPE" | A=="CRIMIN" | A=="GUN" | A=="PRISON" | A=="RIOT" | A=="THUG" | A=="URBAN" | A=="AFRICAN" | A=="BLACK" | A=="RACE" | A=="RACIAL" | A=="RACIST" | A=="totnonstopwords"
|
| keep A v*
|
|
|
| reshape long v, i(A) j(id)
|
| sort id
|
| by id: egen B = total(v) if A!="totnonstopwords"
|
| by id: egen C = max(B)
|
| keep if A=="totnonstopwords"
|
| keep id v C
|
| rename C A
|
| replace A=0 if A==.
|
| rename v totnonstopwords
|
| rename A word
|
| merge 1:1 id using "Data\speech_data.dta"
|
| drop if _merge==2
|
| replace totnonstopwords=-999 if totnonstopwords==0 | totnonstopwords==.
|
| replace totwords=-999 if totnonstopwords==-999
|
| g inspeechdata = (_merge==3)
|
| drop state A _merge id
|
| destring county_fips, replace
|
| reshape wide word event_day_Trump_ totnonstopwords totwords inspeechdata, i(county_fips) j(rally_number)
|
| drop if county_fips==.
|
| egen inspeechdata=rowmax(inspeechdata1 inspeechdata2 inspeechdata3 inspeechdata4 inspeechdata5 inspeechdata6 inspeechdata7 inspeechdata8 inspeechdata9)
|
| drop inspeechdata1 inspeechdata2 inspeechdata3 inspeechdata4 inspeechdata5 inspeechdata6 inspeechdata7 inspeechdata8 inspeechdata9 totwords*
|
|
|
| merge 1:m county_fips using "Data/full_data_tomergewithspeech.dta"
|
| keep if _merge!=1
|
|
|
|
|
| forval ee = 9(-1)1 {
|
| g abs_dist_event`ee' = abs(dist_event`ee')
|
| replace totnonstopwords`ee'=-999 if totnonstopwords`ee'==. & abs_dist_event`ee'!=.
|
| }
|
|
|
| egen closestevent=rowmin(abs_dist_event1 abs_dist_event2 abs_dist_event3 abs_dist_event4 abs_dist_event5 abs_dist_event6 abs_dist_event7 abs_dist_event8 abs_dist_event9)
|
| g nwords = .
|
| forval ee = 9(-1)1 {
|
| replace nwords = word`ee' if abs_dist_event`ee'==closestevent & totnonstopwords`ee'!=-999
|
| }
|
|
|
| su nwords
|
| replace nwords = (nwords - r(mean)) / r(sd)
|
|
|
| su bias_off1
|
| replace bias_off1 = (bias_off1 - r(mean)) / r(sd)
|
|
|
| g TPXnwords = TRUMP_POST_1_30*nwords
|
| replace TPXnwords = 0 if NEVER_TREATED==1
|
|
|
| g TPXbiasXnwords=TRUMP_POST_1_30*bias_off1*nwords
|
| replace TPXbiasXnwords = 0 if NEVER_TREATED==1
|
|
|
| g TPXbias = TRUMP_POST_1_30 * bias_off1
|
|
|
| noisily: di "ALL REFERENCES: "
|
| noisily: reghdfe black 1.TRUMP_PRE_M30 1.TRUMP_0 1.TRUMP_POST_1_30 TPXnwords bias_off1 TPXbias TPXbiasXnwords 1.TRUMP_POST_M30, a(i.county_id i.day_id i.county_id#c.day_id) cluster(county_id day_id)
|
| outreg2 using "Results/Table7A.txt", replace dec(3) keep(1.TRUMP_POST_1_30 TPXnwords bias_off1 TPXbias TPXbiasXnwords) addtext("Words","Explicit+Implicit") label nonotes nocons noni
|
|
|
|
|
|
|
| import excel "Data\wordcount-eachspeech-all.xlsx", sheet("Sheet1") firstrow clear
|
| set obs 2655
|
| replace A="totnonstopwords" in 2655
|
| foreach v of varlist B-GI {
|
| egen totwordsX=total(`v')
|
| replace `v'=totwordsX in 2655
|
| drop totwordsX
|
| }
|
| foreach v of varlist B-GI {
|
| local x : variable label `v'
|
| rename `v' v`x'
|
| }
|
| keep if A=="AFRICAN" | A=="BLACK" | A=="RACE" | A=="RACIAL" | A=="RACIST" | A=="totnonstopwords"
|
| keep A v*
|
|
|
|
|
| reshape long v, i(A) j(id)
|
| sort id
|
| by id: egen B = total(v) if A!="totnonstopwords"
|
| by id: egen C = max(B)
|
| keep if A=="totnonstopwords"
|
| keep id v C
|
| rename C A
|
| replace A=0 if A==.
|
| rename v totnonstopwords
|
| rename A word
|
| merge 1:1 id using "Data\speech_data.dta"
|
| drop if _merge==2
|
| replace totnonstopwords=-999 if totnonstopwords==0 | totnonstopwords==.
|
| replace totwords=-999 if totnonstopwords==-999
|
| g inspeechdata = (_merge==3)
|
| drop state A _merge id
|
| destring county_fips, replace
|
| reshape wide word event_day_Trump_ totnonstopwords totwords inspeechdata, i(county_fips) j(rally_number)
|
| drop if county_fips==.
|
| egen inspeechdata=rowmax(inspeechdata1 inspeechdata2 inspeechdata3 inspeechdata4 inspeechdata5 inspeechdata6 inspeechdata7 inspeechdata8 inspeechdata9)
|
| drop inspeechdata1 inspeechdata2 inspeechdata3 inspeechdata4 inspeechdata5 inspeechdata6 inspeechdata7 inspeechdata8 inspeechdata9 totwords*
|
|
|
| merge 1:m county_fips using "Data/full_data_tomergewithspeech.dta"
|
| keep if _merge!=1
|
|
|
|
|
| forval ee = 9(-1)1 {
|
| g abs_dist_event`ee' = abs(dist_event`ee')
|
| replace totnonstopwords`ee'=-999 if totnonstopwords`ee'==. & abs_dist_event`ee'!=.
|
| }
|
|
|
| egen closestevent=rowmin(abs_dist_event1 abs_dist_event2 abs_dist_event3 abs_dist_event4 abs_dist_event5 abs_dist_event6 abs_dist_event7 abs_dist_event8 abs_dist_event9)
|
| g nwords = .
|
| forval ee = 9(-1)1 {
|
| replace nwords = word`ee' if abs_dist_event`ee'==closestevent & totnonstopwords`ee'!=-999
|
| }
|
|
|
| su nwords
|
| replace nwords = (nwords - r(mean)) / r(sd)
|
|
|
| su bias_off1
|
| replace bias_off1 = (bias_off1 - r(mean)) / r(sd)
|
|
|
| g TPXnwords = TRUMP_POST_1_30*nwords
|
| replace TPXnwords = 0 if NEVER_TREATED==1
|
|
|
| g TPXbiasXnwords=TRUMP_POST_1_30*bias_off1*nwords
|
| replace TPXbiasXnwords = 0 if NEVER_TREATED==1
|
|
|
| g TPXbias = TRUMP_POST_1_30 * bias_off1
|
|
|
|
|
| noisily: di "EXPLICIT REFERENCES"
|
| noisily: reghdfe black 1.TRUMP_PRE_M30 1.TRUMP_0 1.TRUMP_POST_1_30 TPXnwords bias_off1 TPXbias TPXbiasXnwords 1.TRUMP_POST_M30, a(i.county_id i.day_id i.county_id#c.day_id) cluster(county_id day_id)
|
| outreg2 using "Results/Table7A.txt", append dec(3) keep(1.TRUMP_POST_1_30 TPXnwords bias_off1 TPXbias TPXbiasXnwords) addtext("Words","Explicit") label nonotes nocons noni
|
|
|
|
|
|
|
| import excel "Data\wordcount-eachspeech-all.xlsx", sheet("Sheet1") firstrow clear
|
| set obs 2655
|
| replace A="totnonstopwords" in 2655
|
| foreach v of varlist B-GI {
|
| egen totwordsX=total(`v')
|
| replace `v'=totwordsX in 2655
|
| drop totwordsX
|
| }
|
| foreach v of varlist B-GI {
|
| local x : variable label `v'
|
| rename `v' v`x'
|
| }
|
| keep if A=="DRUG" | A=="CRIME" | A=="RAPE" | A=="CRIMIN" | A=="GUN" | A=="PRISON" | A=="RIOT" | A=="THUG" | A=="URBAN" | A=="totnonstopwords"
|
| keep A v*
|
|
|
| reshape long v, i(A) j(id)
|
| sort id
|
| by id: egen B = total(v) if A!="totnonstopwords"
|
| by id: egen C = max(B)
|
| keep if A=="totnonstopwords"
|
| keep id v C
|
| rename C A
|
| replace A=0 if A==.
|
| rename v totnonstopwords
|
| rename A word
|
| merge 1:1 id using "Data\speech_data.dta"
|
| drop if _merge==2
|
| replace totnonstopwords=-999 if totnonstopwords==0 | totnonstopwords==.
|
| replace totwords=-999 if totnonstopwords==-999
|
| g inspeechdata = (_merge==3)
|
| drop state A _merge id
|
| destring county_fips, replace
|
| reshape wide word event_day_Trump_ totnonstopwords totwords inspeechdata, i(county_fips) j(rally_number)
|
| drop if county_fips==.
|
| egen inspeechdata=rowmax(inspeechdata1 inspeechdata2 inspeechdata3 inspeechdata4 inspeechdata5 inspeechdata6 inspeechdata7 inspeechdata8 inspeechdata9)
|
| drop inspeechdata1 inspeechdata2 inspeechdata3 inspeechdata4 inspeechdata5 inspeechdata6 inspeechdata7 inspeechdata8 inspeechdata9 totwords*
|
|
|
| merge 1:m county_fips using "Data/full_data_tomergewithspeech.dta"
|
| keep if _merge!=1
|
|
|
|
|
| forval ee = 9(-1)1 {
|
| g abs_dist_event`ee' = abs(dist_event`ee')
|
| replace totnonstopwords`ee'=-999 if totnonstopwords`ee'==. & abs_dist_event`ee'!=.
|
| }
|
|
|
| egen closestevent=rowmin(abs_dist_event1 abs_dist_event2 abs_dist_event3 abs_dist_event4 abs_dist_event5 abs_dist_event6 abs_dist_event7 abs_dist_event8 abs_dist_event9)
|
| g nwords = .
|
| forval ee = 9(-1)1 {
|
| replace nwords = word`ee' if abs_dist_event`ee'==closestevent & totnonstopwords`ee'!=-999
|
| }
|
|
|
| su nwords
|
| replace nwords = (nwords - r(mean)) / r(sd)
|
|
|
| su bias_off1
|
| replace bias_off1 = (bias_off1 - r(mean)) / r(sd)
|
|
|
| g TPXnwords = TRUMP_POST_1_30*nwords
|
| replace TPXnwords = 0 if NEVER_TREATED==1
|
|
|
| g TPXbiasXnwords=TRUMP_POST_1_30*bias_off1*nwords
|
| replace TPXbiasXnwords = 0 if NEVER_TREATED==1
|
|
|
| g TPXbias = TRUMP_POST_1_30 * bias_off1
|
|
|
| noisily: di "IMPLICIT: "
|
| noisily: reghdfe black 1.TRUMP_PRE_M30 1.TRUMP_0 1.TRUMP_POST_1_30 TPXnwords bias_off1 TPXbias TPXbiasXnwords 1.TRUMP_POST_M30, a(i.county_id i.day_id i.county_id#c.day_id) cluster(county_id day_id)
|
| outreg2 using "Results/Table7A.txt", append dec(3) keep(1.TRUMP_POST_1_30 TPXnwords bias_off1 TPXbias TPXbiasXnwords) addtext("Words","Implicit") label nonotes nocons noni
|
|
|
|
|
| import excel "Data\wordcount-eachspeech-all.xlsx", sheet("Sheet1") firstrow clear
|
| set obs 2655
|
| replace A="totnonstopwords" in 2655
|
| foreach v of varlist B-GI {
|
| egen totwordsX=total(`v')
|
| replace `v'=totwordsX in 2655
|
| drop totwordsX
|
| }
|
| foreach v of varlist B-GI {
|
| local x : variable label `v'
|
| rename `v' v`x'
|
| }
|
| keep if A=="CHINA" | A=="TRADE" | A=="NAFTA" | A=="totnonstopwords"
|
| keep A v*
|
|
|
| reshape long v, i(A) j(id)
|
| sort id
|
| by id: egen B = total(v) if A!="totnonstopwords"
|
| by id: egen C = max(B)
|
| keep if A=="totnonstopwords"
|
| keep id v C
|
| rename C A
|
| replace A=0 if A==.
|
| rename v totnonstopwords
|
| rename A word
|
| merge 1:1 id using "Data\speech_data.dta"
|
| drop if _merge==2
|
| replace totnonstopwords=-999 if totnonstopwords==0 | totnonstopwords==.
|
| replace totwords=-999 if totnonstopwords==-999
|
| g inspeechdata = (_merge==3)
|
| drop state A _merge id
|
| destring county_fips, replace
|
| reshape wide word event_day_Trump_ totnonstopwords totwords inspeechdata, i(county_fips) j(rally_number)
|
| drop if county_fips==.
|
| egen inspeechdata=rowmax(inspeechdata1 inspeechdata2 inspeechdata3 inspeechdata4 inspeechdata5 inspeechdata6 inspeechdata7 inspeechdata8 inspeechdata9)
|
| drop inspeechdata1 inspeechdata2 inspeechdata3 inspeechdata4 inspeechdata5 inspeechdata6 inspeechdata7 inspeechdata8 inspeechdata9 totwords*
|
|
|
| merge 1:m county_fips using "Data/full_data_tomergewithspeech.dta"
|
| keep if _merge!=1
|
|
|
|
|
| forval ee = 9(-1)1 {
|
| g abs_dist_event`ee' = abs(dist_event`ee')
|
| replace totnonstopwords`ee'=-999 if totnonstopwords`ee'==. & abs_dist_event`ee'!=.
|
| }
|
|
|
| egen closestevent=rowmin(abs_dist_event1 abs_dist_event2 abs_dist_event3 abs_dist_event4 abs_dist_event5 abs_dist_event6 abs_dist_event7 abs_dist_event8 abs_dist_event9)
|
| g nwords = .
|
| forval ee = 9(-1)1 {
|
| replace nwords = word`ee' if abs_dist_event`ee'==closestevent & totnonstopwords`ee'!=-999
|
| }
|
|
|
| su nwords
|
| replace nwords = (nwords - r(mean)) / r(sd)
|
|
|
| su bias_off1
|
| replace bias_off1 = (bias_off1 - r(mean)) / r(sd)
|
|
|
| g TPXnwords = TRUMP_POST_1_30*nwords
|
| replace TPXnwords = 0 if NEVER_TREATED==1
|
|
|
| g TPXbiasXnwords=TRUMP_POST_1_30*bias_off1*nwords
|
| replace TPXbiasXnwords = 0 if NEVER_TREATED==1
|
|
|
| g TPXbias = TRUMP_POST_1_30 * bias_off1
|
|
|
| noisily: di "TRADE: "
|
| noisily: reghdfe black 1.TRUMP_PRE_M30 1.TRUMP_0 1.TRUMP_POST_1_30 TPXnwords bias_off1 TPXbias TPXbiasXnwords 1.TRUMP_POST_M30, a(i.county_id i.day_id i.county_id#c.day_id) cluster(county_id day_id)
|
| outreg2 using "Results/Table7A.txt", append dec(3) keep(1.TRUMP_POST_1_30 TPXnwords bias_off1 TPXbias TPXbiasXnwords) addtext("Words","Trade") label nonotes nocons noni
|
|
|
|
|
| import excel "Data\wordcount-eachspeech-all.xlsx", sheet("Sheet1") firstrow clear
|
| set obs 2655
|
| replace A="totnonstopwords" in 2655
|
| foreach v of varlist B-GI {
|
| egen totwordsX=total(`v')
|
| replace `v'=totwordsX in 2655
|
| drop totwordsX
|
| }
|
| foreach v of varlist B-GI {
|
| local x : variable label `v'
|
| rename `v' v`x'
|
| }
|
| keep if A=="HILARI" | A=="CLINTON" | A=="EMAIL" | A=="LOCK" | A=="totnonstopwords"
|
| keep A v*
|
|
|
| reshape long v, i(A) j(id)
|
| sort id
|
| by id: egen B = total(v) if A!="totnonstopwords"
|
| by id: egen C = max(B)
|
| keep if A=="totnonstopwords"
|
| keep id v C
|
| rename C A
|
| replace A=0 if A==.
|
| rename v totnonstopwords
|
| rename A word
|
| merge 1:1 id using "Data\speech_data.dta"
|
| drop if _merge==2
|
| replace totnonstopwords=-999 if totnonstopwords==0 | totnonstopwords==.
|
| replace totwords=-999 if totnonstopwords==-999
|
| g inspeechdata = (_merge==3)
|
| drop state A _merge id
|
| destring county_fips, replace
|
| reshape wide word event_day_Trump_ totnonstopwords totwords inspeechdata, i(county_fips) j(rally_number)
|
| drop if county_fips==.
|
| egen inspeechdata=rowmax(inspeechdata1 inspeechdata2 inspeechdata3 inspeechdata4 inspeechdata5 inspeechdata6 inspeechdata7 inspeechdata8 inspeechdata9)
|
| drop inspeechdata1 inspeechdata2 inspeechdata3 inspeechdata4 inspeechdata5 inspeechdata6 inspeechdata7 inspeechdata8 inspeechdata9 totwords*
|
|
|
| merge 1:m county_fips using "Data/full_data_tomergewithspeech.dta"
|
| keep if _merge!=1
|
|
|
|
|
| forval ee = 9(-1)1 {
|
| g abs_dist_event`ee' = abs(dist_event`ee')
|
| replace totnonstopwords`ee'=-999 if totnonstopwords`ee'==. & abs_dist_event`ee'!=.
|
| }
|
|
|
| egen closestevent=rowmin(abs_dist_event1 abs_dist_event2 abs_dist_event3 abs_dist_event4 abs_dist_event5 abs_dist_event6 abs_dist_event7 abs_dist_event8 abs_dist_event9)
|
| g nwords = .
|
| forval ee = 9(-1)1 {
|
| replace nwords = word`ee' if abs_dist_event`ee'==closestevent & totnonstopwords`ee'!=-999
|
| }
|
|
|
| su nwords
|
| replace nwords = (nwords - r(mean)) / r(sd)
|
|
|
| su bias_off1
|
| replace bias_off1 = (bias_off1 - r(mean)) / r(sd)
|
|
|
| g TPXnwords = TRUMP_POST_1_30*nwords
|
| replace TPXnwords = 0 if NEVER_TREATED==1
|
|
|
| g TPXbiasXnwords=TRUMP_POST_1_30*bias_off1*nwords
|
| replace TPXbiasXnwords = 0 if NEVER_TREATED==1
|
|
|
| g TPXbias = TRUMP_POST_1_30 * bias_off1
|
|
|
| noisily: di "CLINTON: "
|
| noisily: reghdfe black 1.TRUMP_PRE_M30 1.TRUMP_0 1.TRUMP_POST_1_30 TPXnwords bias_off1 TPXbias TPXbiasXnwords 1.TRUMP_POST_M30, a(i.county_id i.day_id i.county_id#c.day_id) cluster(county_id day_id)
|
| outreg2 using "Results/Table7A.txt", append dec(3) keep(1.TRUMP_POST_1_30 TPXnwords bias_off1 TPXbias TPXbiasXnwords) addtext("Words","Clinton") label nonotes nocons noni
|
|
|
|
|
| import excel "Data\wordcount-eachspeech-all.xlsx", sheet("Sheet1") firstrow clear
|
| set obs 2655
|
| replace A="totnonstopwords" in 2655
|
| foreach v of varlist B-GI {
|
| egen totwordsX=total(`v')
|
| replace `v'=totwordsX in 2655
|
| drop totwordsX
|
| }
|
| foreach v of varlist B-GI {
|
| local x : variable label `v'
|
| rename `v' v`x'
|
| }
|
| keep if A=="ISI" | A=="SYRIA" | A=="IRAQ" | A=="TERRORIST" | A=="AFGHANISTAN" | A=="ISLAM" | A=="totnonstopwords"
|
| keep A v*
|
|
|
| reshape long v, i(A) j(id)
|
| sort id
|
| by id: egen B = total(v) if A!="totnonstopwords"
|
| by id: egen C = max(B)
|
| keep if A=="totnonstopwords"
|
| keep id v C
|
| rename C A
|
| replace A=0 if A==.
|
| rename v totnonstopwords
|
| rename A word
|
| merge 1:1 id using "Data\speech_data.dta"
|
| drop if _merge==2
|
| replace totnonstopwords=-999 if totnonstopwords==0 | totnonstopwords==.
|
| replace totwords=-999 if totnonstopwords==-999
|
| g inspeechdata = (_merge==3)
|
| drop state A _merge id
|
| destring county_fips, replace
|
| reshape wide word event_day_Trump_ totnonstopwords totwords inspeechdata, i(county_fips) j(rally_number)
|
| drop if county_fips==.
|
| egen inspeechdata=rowmax(inspeechdata1 inspeechdata2 inspeechdata3 inspeechdata4 inspeechdata5 inspeechdata6 inspeechdata7 inspeechdata8 inspeechdata9)
|
| drop inspeechdata1 inspeechdata2 inspeechdata3 inspeechdata4 inspeechdata5 inspeechdata6 inspeechdata7 inspeechdata8 inspeechdata9 totwords*
|
|
|
| merge 1:m county_fips using "Data/full_data_tomergewithspeech.dta"
|
| keep if _merge!=1
|
|
|
|
|
| forval ee = 9(-1)1 {
|
| g abs_dist_event`ee' = abs(dist_event`ee')
|
| replace totnonstopwords`ee'=-999 if totnonstopwords`ee'==. & abs_dist_event`ee'!=.
|
| }
|
|
|
| egen closestevent=rowmin(abs_dist_event1 abs_dist_event2 abs_dist_event3 abs_dist_event4 abs_dist_event5 abs_dist_event6 abs_dist_event7 abs_dist_event8 abs_dist_event9)
|
| g nwords = .
|
| forval ee = 9(-1)1 {
|
| replace nwords = word`ee' if abs_dist_event`ee'==closestevent & totnonstopwords`ee'!=-999
|
| }
|
|
|
| su nwords
|
| replace nwords = (nwords - r(mean)) / r(sd)
|
|
|
| su bias_off1
|
| replace bias_off1 = (bias_off1 - r(mean)) / r(sd)
|
|
|
| g TPXnwords = TRUMP_POST_1_30*nwords
|
| replace TPXnwords = 0 if NEVER_TREATED==1
|
|
|
| g TPXbiasXnwords=TRUMP_POST_1_30*bias_off1*nwords
|
| replace TPXbiasXnwords = 0 if NEVER_TREATED==1
|
|
|
| g TPXbias = TRUMP_POST_1_30 * bias_off1
|
|
|
| noisily: di "TERROR: "
|
| noisily: reghdfe black 1.TRUMP_PRE_M30 1.TRUMP_0 1.TRUMP_POST_1_30 TPXnwords bias_off1 TPXbias TPXbiasXnwords 1.TRUMP_POST_M30, a(i.county_id i.day_id i.county_id#c.day_id) cluster(county_id day_id)
|
| outreg2 using "Results/Table7A.txt", append dec(3) keep(1.TRUMP_POST_1_30 TPXnwords bias_off1 TPXbias TPXbiasXnwords) addtext("Words","Terror") label nonotes nocons noni
|
|
|
|
|
| import excel "Data\wordcount-eachspeech-all.xlsx", sheet("Sheet1") firstrow clear
|
| set obs 2655
|
| replace A="totnonstopwords" in 2655
|
| foreach v of varlist B-GI {
|
| egen totwordsX=total(`v')
|
| replace `v'=totwordsX in 2655
|
| drop totwordsX
|
| }
|
| foreach v of varlist B-GI {
|
| local x : variable label `v'
|
| rename `v' v`x'
|
| }
|
| keep if A=="BUSI" | A=="JOB" | A=="MANUFACTUR" | A=="TAX" | A=="totnonstopwords"
|
| keep A v*
|
|
|
| reshape long v, i(A) j(id)
|
| sort id
|
| by id: egen B = total(v) if A!="totnonstopwords"
|
| by id: egen C = max(B)
|
| keep if A=="totnonstopwords"
|
| keep id v C
|
| rename C A
|
| replace A=0 if A==.
|
| rename v totnonstopwords
|
| rename A word
|
| merge 1:1 id using "Data\speech_data.dta"
|
| drop if _merge==2
|
| replace totnonstopwords=-999 if totnonstopwords==0 | totnonstopwords==.
|
| replace totwords=-999 if totnonstopwords==-999
|
| g inspeechdata = (_merge==3)
|
| drop state A _merge id
|
| destring county_fips, replace
|
| reshape wide word event_day_Trump_ totnonstopwords totwords inspeechdata, i(county_fips) j(rally_number)
|
| drop if county_fips==.
|
| egen inspeechdata=rowmax(inspeechdata1 inspeechdata2 inspeechdata3 inspeechdata4 inspeechdata5 inspeechdata6 inspeechdata7 inspeechdata8 inspeechdata9)
|
| drop inspeechdata1 inspeechdata2 inspeechdata3 inspeechdata4 inspeechdata5 inspeechdata6 inspeechdata7 inspeechdata8 inspeechdata9 totwords*
|
|
|
| merge 1:m county_fips using "Data/full_data_tomergewithspeech.dta"
|
| keep if _merge!=1
|
|
|
|
|
| forval ee = 9(-1)1 {
|
| g abs_dist_event`ee' = abs(dist_event`ee')
|
| replace totnonstopwords`ee'=-999 if totnonstopwords`ee'==. & abs_dist_event`ee'!=.
|
| }
|
|
|
| egen closestevent=rowmin(abs_dist_event1 abs_dist_event2 abs_dist_event3 abs_dist_event4 abs_dist_event5 abs_dist_event6 abs_dist_event7 abs_dist_event8 abs_dist_event9)
|
| g nwords = .
|
| forval ee = 9(-1)1 {
|
| replace nwords = word`ee' if abs_dist_event`ee'==closestevent & totnonstopwords`ee'!=-999
|
| }
|
|
|
| su nwords
|
| replace nwords = (nwords - r(mean)) / r(sd)
|
|
|
| su bias_off1
|
| replace bias_off1 = (bias_off1 - r(mean)) / r(sd)
|
|
|
| g TPXnwords = TRUMP_POST_1_30*nwords
|
| replace TPXnwords = 0 if NEVER_TREATED==1
|
|
|
| g TPXbiasXnwords=TRUMP_POST_1_30*bias_off1*nwords
|
| replace TPXbiasXnwords = 0 if NEVER_TREATED==1
|
|
|
| g TPXbias = TRUMP_POST_1_30 * bias_off1
|
|
|
| noisily: di "JOB: "
|
| noisily: reghdfe black 1.TRUMP_PRE_M30 1.TRUMP_0 1.TRUMP_POST_1_30 TPXnwords bias_off1 TPXbias TPXbiasXnwords 1.TRUMP_POST_M30, a(i.county_id i.day_id i.county_id#c.day_id) cluster(county_id day_id)
|
| outreg2 using "Results/Table7A.txt", append dec(3) keep(1.TRUMP_POST_1_30 TPXnwords bias_off1 TPXbias TPXbiasXnwords) addtext("Words","Job") label nonotes nocons noni
|
|
|
|
|
| import excel "Data\wordcount-eachspeech-all.xlsx", sheet("Sheet1") firstrow clear
|
| set obs 2655
|
| replace A="totnonstopwords" in 2655
|
| foreach v of varlist B-GI {
|
| egen totwordsX=total(`v')
|
| replace `v'=totwordsX in 2655
|
| drop totwordsX
|
| }
|
| foreach v of varlist B-GI {
|
| local x : variable label `v'
|
| rename `v' v`x'
|
| }
|
| keep if A=="RIG" | A=="MEDIA" | A=="CNN" | A=="WASHINGTON" | A=="CORRUPT" | A=="SWAMP" | A=="totnonstopwords"
|
| keep A v*
|
|
|
| reshape long v, i(A) j(id)
|
| sort id
|
| by id: egen B = total(v) if A!="totnonstopwords"
|
| by id: egen C = max(B)
|
| keep if A=="totnonstopwords"
|
| keep id v C
|
| rename C A
|
| replace A=0 if A==.
|
| rename v totnonstopwords
|
| rename A word
|
| merge 1:1 id using "Data\speech_data.dta"
|
| drop if _merge==2
|
| replace totnonstopwords=-999 if totnonstopwords==0 | totnonstopwords==.
|
| replace totwords=-999 if totnonstopwords==-999
|
| g inspeechdata = (_merge==3)
|
| drop state A _merge id
|
| destring county_fips, replace
|
| reshape wide word event_day_Trump_ totnonstopwords totwords inspeechdata, i(county_fips) j(rally_number)
|
| drop if county_fips==.
|
| egen inspeechdata=rowmax(inspeechdata1 inspeechdata2 inspeechdata3 inspeechdata4 inspeechdata5 inspeechdata6 inspeechdata7 inspeechdata8 inspeechdata9)
|
| drop inspeechdata1 inspeechdata2 inspeechdata3 inspeechdata4 inspeechdata5 inspeechdata6 inspeechdata7 inspeechdata8 inspeechdata9 totwords*
|
|
|
| merge 1:m county_fips using "Data/full_data_tomergewithspeech.dta"
|
| keep if _merge!=1
|
|
|
|
|
| forval ee = 9(-1)1 {
|
| g abs_dist_event`ee' = abs(dist_event`ee')
|
| replace totnonstopwords`ee'=-999 if totnonstopwords`ee'==. & abs_dist_event`ee'!=.
|
| }
|
|
|
| egen closestevent=rowmin(abs_dist_event1 abs_dist_event2 abs_dist_event3 abs_dist_event4 abs_dist_event5 abs_dist_event6 abs_dist_event7 abs_dist_event8 abs_dist_event9)
|
| g nwords = .
|
| forval ee = 9(-1)1 {
|
| replace nwords = word`ee' if abs_dist_event`ee'==closestevent & totnonstopwords`ee'!=-999
|
| }
|
|
|
| su nwords
|
| replace nwords = (nwords - r(mean)) / r(sd)
|
|
|
| su bias_off1
|
| replace bias_off1 = (bias_off1 - r(mean)) / r(sd)
|
|
|
| g TPXnwords = TRUMP_POST_1_30*nwords
|
| replace TPXnwords = 0 if NEVER_TREATED==1
|
|
|
| g TPXbiasXnwords=TRUMP_POST_1_30*bias_off1*nwords
|
| replace TPXbiasXnwords = 0 if NEVER_TREATED==1
|
|
|
| g TPXbias = TRUMP_POST_1_30 * bias_off1
|
|
|
| noisily: di "CORRUPTION: "
|
| noisily: reghdfe black 1.TRUMP_PRE_M30 1.TRUMP_0 1.TRUMP_POST_1_30 TPXnwords bias_off1 TPXbias TPXbiasXnwords 1.TRUMP_POST_M30, a(i.county_id i.day_id i.county_id#c.day_id) cluster(county_id day_id)
|
| outreg2 using "Results/Table7A.txt", append dec(3) keep(1.TRUMP_POST_1_30 TPXnwords bias_off1 TPXbias TPXbiasXnwords) addtext("Words","Corruption") label nonotes nocons noni
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| qui:{
|
|
|
| import excel "Data\wordcount-eachspeech-all.xlsx", sheet("Sheet1") firstrow clear
|
| set obs 2655
|
| replace A="totnonstopwords" in 2655
|
| foreach v of varlist B-GI {
|
| egen totwordsX=total(`v')
|
| replace `v'=totwordsX in 2655
|
| drop totwordsX
|
| }
|
| foreach v of varlist B-GI {
|
| local x : variable label `v'
|
| rename `v' v`x'
|
| }
|
| keep if A=="DRUG" | A=="CRIME" | A=="RAPE" | A=="CRIMIN" | A=="GUN" | A=="PRISON" | A=="RIOT" | A=="THUG" | A=="URBAN" | A=="AFRICAN" | A=="BLACK" | A=="RACE" | A=="RACIAL" | A=="RACIST" | A=="totnonstopwords"
|
| keep A v*
|
|
|
| reshape long v, i(A) j(id)
|
| sort id
|
| by id: egen B = total(v) if A!="totnonstopwords"
|
| by id: egen C = max(B)
|
| keep if A=="totnonstopwords"
|
| keep id v C
|
| rename C A
|
| replace A=0 if A==.
|
| rename v totnonstopwords
|
| rename A word
|
| merge 1:1 id using "Data\speech_data.dta"
|
| drop if _merge==2
|
| replace totnonstopwords=-999 if totnonstopwords==0 | totnonstopwords==.
|
| replace totwords=-999 if totnonstopwords==-999
|
| g inspeechdata = (_merge==3)
|
| drop state A _merge id
|
| destring county_fips, replace
|
| reshape wide word event_day_Trump_ totnonstopwords totwords inspeechdata, i(county_fips) j(rally_number)
|
| drop if county_fips==.
|
| egen inspeechdata=rowmax(inspeechdata1 inspeechdata2 inspeechdata3 inspeechdata4 inspeechdata5 inspeechdata6 inspeechdata7 inspeechdata8 inspeechdata9)
|
| drop inspeechdata1 inspeechdata2 inspeechdata3 inspeechdata4 inspeechdata5 inspeechdata6 inspeechdata7 inspeechdata8 inspeechdata9 totwords*
|
|
|
| merge 1:m county_fips using "Data/full_data_tomergewithspeech.dta"
|
| keep if _merge!=1
|
|
|
|
|
| forval ee = 9(-1)1 {
|
| g abs_dist_event`ee' = abs(dist_event`ee')
|
| replace totnonstopwords`ee'=-999 if totnonstopwords`ee'==. & abs_dist_event`ee'!=.
|
| }
|
|
|
| egen closestevent=rowmin(abs_dist_event1 abs_dist_event2 abs_dist_event3 abs_dist_event4 abs_dist_event5 abs_dist_event6 abs_dist_event7 abs_dist_event8 abs_dist_event9)
|
| g nwords = .
|
| forval ee = 9(-1)1 {
|
| replace nwords = word`ee' if abs_dist_event`ee'==closestevent & totnonstopwords`ee'!=-999
|
| }
|
|
|
| su nwords
|
| replace nwords = (nwords - r(mean)) / r(sd)
|
|
|
| su bias_off2
|
| replace bias_off2 = (bias_off2 - r(mean)) / r(sd)
|
|
|
| g TPXnwords = TRUMP_POST_1_30*nwords
|
| replace TPXnwords = 0 if NEVER_TREATED==1
|
|
|
| g TPXbiasXnwords=TRUMP_POST_1_30*bias_off2*nwords
|
| replace TPXbiasXnwords = 0 if NEVER_TREATED==1
|
|
|
| g TPXbias = TRUMP_POST_1_30 * bias_off2
|
|
|
| noisily: di "ALL REFERENCES: "
|
| noisily: reghdfe black 1.TRUMP_PRE_M30 1.TRUMP_0 1.TRUMP_POST_1_30 TPXnwords bias_off2 TPXbias TPXbiasXnwords 1.TRUMP_POST_M30, a(i.county_id i.day_id i.county_id#c.day_id) cluster(county_id day_id)
|
| outreg2 using "Results/Table7B.txt", replace dec(3) keep(1.TRUMP_POST_1_30 TPXnwords bias_off2 TPXbias TPXbiasXnwords) addtext("Words","Explicit+Implicit") label nonotes nocons noni
|
|
|
|
|
|
|
| import excel "Data\wordcount-eachspeech-all.xlsx", sheet("Sheet1") firstrow clear
|
| set obs 2655
|
| replace A="totnonstopwords" in 2655
|
| foreach v of varlist B-GI {
|
| egen totwordsX=total(`v')
|
| replace `v'=totwordsX in 2655
|
| drop totwordsX
|
| }
|
| foreach v of varlist B-GI {
|
| local x : variable label `v'
|
| rename `v' v`x'
|
| }
|
| keep if A=="AFRICAN" | A=="BLACK" | A=="RACE" | A=="RACIAL" | A=="RACIST" | A=="totnonstopwords"
|
| keep A v*
|
|
|
|
|
| reshape long v, i(A) j(id)
|
| sort id
|
| by id: egen B = total(v) if A!="totnonstopwords"
|
| by id: egen C = max(B)
|
| keep if A=="totnonstopwords"
|
| keep id v C
|
| rename C A
|
| replace A=0 if A==.
|
| rename v totnonstopwords
|
| rename A word
|
| merge 1:1 id using "Data\speech_data.dta"
|
| drop if _merge==2
|
| replace totnonstopwords=-999 if totnonstopwords==0 | totnonstopwords==.
|
| replace totwords=-999 if totnonstopwords==-999
|
| g inspeechdata = (_merge==3)
|
| drop state A _merge id
|
| destring county_fips, replace
|
| reshape wide word event_day_Trump_ totnonstopwords totwords inspeechdata, i(county_fips) j(rally_number)
|
| drop if county_fips==.
|
| egen inspeechdata=rowmax(inspeechdata1 inspeechdata2 inspeechdata3 inspeechdata4 inspeechdata5 inspeechdata6 inspeechdata7 inspeechdata8 inspeechdata9)
|
| drop inspeechdata1 inspeechdata2 inspeechdata3 inspeechdata4 inspeechdata5 inspeechdata6 inspeechdata7 inspeechdata8 inspeechdata9 totwords*
|
|
|
| merge 1:m county_fips using "Data/full_data_tomergewithspeech.dta"
|
| keep if _merge!=1
|
|
|
|
|
| forval ee = 9(-1)1 {
|
| g abs_dist_event`ee' = abs(dist_event`ee')
|
| replace totnonstopwords`ee'=-999 if totnonstopwords`ee'==. & abs_dist_event`ee'!=.
|
| }
|
|
|
| egen closestevent=rowmin(abs_dist_event1 abs_dist_event2 abs_dist_event3 abs_dist_event4 abs_dist_event5 abs_dist_event6 abs_dist_event7 abs_dist_event8 abs_dist_event9)
|
| g nwords = .
|
| forval ee = 9(-1)1 {
|
| replace nwords = word`ee' if abs_dist_event`ee'==closestevent & totnonstopwords`ee'!=-999
|
| }
|
|
|
| su nwords
|
| replace nwords = (nwords - r(mean)) / r(sd)
|
|
|
| su bias_off2
|
| replace bias_off2 = (bias_off2 - r(mean)) / r(sd)
|
|
|
| g TPXnwords = TRUMP_POST_1_30*nwords
|
| replace TPXnwords = 0 if NEVER_TREATED==1
|
|
|
| g TPXbiasXnwords=TRUMP_POST_1_30*bias_off2*nwords
|
| replace TPXbiasXnwords = 0 if NEVER_TREATED==1
|
|
|
| g TPXbias = TRUMP_POST_1_30 * bias_off2
|
|
|
|
|
| noisily: di "EXPLICIT REFERENCES"
|
| noisily: reghdfe black 1.TRUMP_PRE_M30 1.TRUMP_0 1.TRUMP_POST_1_30 TPXnwords bias_off2 TPXbias TPXbiasXnwords 1.TRUMP_POST_M30, a(i.county_id i.day_id i.county_id#c.day_id) cluster(county_id day_id)
|
| outreg2 using "Results/Table7B.txt", append dec(3) keep(1.TRUMP_POST_1_30 TPXnwords bias_off2 TPXbias TPXbiasXnwords) addtext("Words","Explicit") label nonotes nocons noni
|
|
|
|
|
|
|
| import excel "Data\wordcount-eachspeech-all.xlsx", sheet("Sheet1") firstrow clear
|
| set obs 2655
|
| replace A="totnonstopwords" in 2655
|
| foreach v of varlist B-GI {
|
| egen totwordsX=total(`v')
|
| replace `v'=totwordsX in 2655
|
| drop totwordsX
|
| }
|
| foreach v of varlist B-GI {
|
| local x : variable label `v'
|
| rename `v' v`x'
|
| }
|
| keep if A=="DRUG" | A=="CRIME" | A=="RAPE" | A=="CRIMIN" | A=="GUN" | A=="PRISON" | A=="RIOT" | A=="THUG" | A=="URBAN" | A=="totnonstopwords"
|
| keep A v*
|
|
|
| reshape long v, i(A) j(id)
|
| sort id
|
| by id: egen B = total(v) if A!="totnonstopwords"
|
| by id: egen C = max(B)
|
| keep if A=="totnonstopwords"
|
| keep id v C
|
| rename C A
|
| replace A=0 if A==.
|
| rename v totnonstopwords
|
| rename A word
|
| merge 1:1 id using "Data\speech_data.dta"
|
| drop if _merge==2
|
| replace totnonstopwords=-999 if totnonstopwords==0 | totnonstopwords==.
|
| replace totwords=-999 if totnonstopwords==-999
|
| g inspeechdata = (_merge==3)
|
| drop state A _merge id
|
| destring county_fips, replace
|
| reshape wide word event_day_Trump_ totnonstopwords totwords inspeechdata, i(county_fips) j(rally_number)
|
| drop if county_fips==.
|
| egen inspeechdata=rowmax(inspeechdata1 inspeechdata2 inspeechdata3 inspeechdata4 inspeechdata5 inspeechdata6 inspeechdata7 inspeechdata8 inspeechdata9)
|
| drop inspeechdata1 inspeechdata2 inspeechdata3 inspeechdata4 inspeechdata5 inspeechdata6 inspeechdata7 inspeechdata8 inspeechdata9 totwords*
|
|
|
| merge 1:m county_fips using "Data/full_data_tomergewithspeech.dta"
|
| keep if _merge!=1
|
|
|
|
|
| forval ee = 9(-1)1 {
|
| g abs_dist_event`ee' = abs(dist_event`ee')
|
| replace totnonstopwords`ee'=-999 if totnonstopwords`ee'==. & abs_dist_event`ee'!=.
|
| }
|
|
|
| egen closestevent=rowmin(abs_dist_event1 abs_dist_event2 abs_dist_event3 abs_dist_event4 abs_dist_event5 abs_dist_event6 abs_dist_event7 abs_dist_event8 abs_dist_event9)
|
| g nwords = .
|
| forval ee = 9(-1)1 {
|
| replace nwords = word`ee' if abs_dist_event`ee'==closestevent & totnonstopwords`ee'!=-999
|
| }
|
|
|
| su nwords
|
| replace nwords = (nwords - r(mean)) / r(sd)
|
|
|
| su bias_off2
|
| replace bias_off2 = (bias_off2 - r(mean)) / r(sd)
|
|
|
| g TPXnwords = TRUMP_POST_1_30*nwords
|
| replace TPXnwords = 0 if NEVER_TREATED==1
|
|
|
| g TPXbiasXnwords=TRUMP_POST_1_30*bias_off2*nwords
|
| replace TPXbiasXnwords = 0 if NEVER_TREATED==1
|
|
|
| g TPXbias = TRUMP_POST_1_30 * bias_off2
|
|
|
| noisily: di "IMPLICIT: "
|
| noisily: reghdfe black 1.TRUMP_PRE_M30 1.TRUMP_0 1.TRUMP_POST_1_30 TPXnwords bias_off2 TPXbias TPXbiasXnwords 1.TRUMP_POST_M30, a(i.county_id i.day_id i.county_id#c.day_id) cluster(county_id day_id)
|
| outreg2 using "Results/Table7B.txt", append dec(3) keep(1.TRUMP_POST_1_30 TPXnwords bias_off2 TPXbias TPXbiasXnwords) addtext("Words","Implicit") label nonotes nocons noni
|
|
|
|
|
| import excel "Data\wordcount-eachspeech-all.xlsx", sheet("Sheet1") firstrow clear
|
| set obs 2655
|
| replace A="totnonstopwords" in 2655
|
| foreach v of varlist B-GI {
|
| egen totwordsX=total(`v')
|
| replace `v'=totwordsX in 2655
|
| drop totwordsX
|
| }
|
| foreach v of varlist B-GI {
|
| local x : variable label `v'
|
| rename `v' v`x'
|
| }
|
| keep if A=="CHINA" | A=="TRADE" | A=="NAFTA" | A=="totnonstopwords"
|
| keep A v*
|
|
|
| reshape long v, i(A) j(id)
|
| sort id
|
| by id: egen B = total(v) if A!="totnonstopwords"
|
| by id: egen C = max(B)
|
| keep if A=="totnonstopwords"
|
| keep id v C
|
| rename C A
|
| replace A=0 if A==.
|
| rename v totnonstopwords
|
| rename A word
|
| merge 1:1 id using "Data\speech_data.dta"
|
| drop if _merge==2
|
| replace totnonstopwords=-999 if totnonstopwords==0 | totnonstopwords==.
|
| replace totwords=-999 if totnonstopwords==-999
|
| g inspeechdata = (_merge==3)
|
| drop state A _merge id
|
| destring county_fips, replace
|
| reshape wide word event_day_Trump_ totnonstopwords totwords inspeechdata, i(county_fips) j(rally_number)
|
| drop if county_fips==.
|
| egen inspeechdata=rowmax(inspeechdata1 inspeechdata2 inspeechdata3 inspeechdata4 inspeechdata5 inspeechdata6 inspeechdata7 inspeechdata8 inspeechdata9)
|
| drop inspeechdata1 inspeechdata2 inspeechdata3 inspeechdata4 inspeechdata5 inspeechdata6 inspeechdata7 inspeechdata8 inspeechdata9 totwords*
|
|
|
| merge 1:m county_fips using "Data/full_data_tomergewithspeech.dta"
|
| keep if _merge!=1
|
|
|
|
|
| forval ee = 9(-1)1 {
|
| g abs_dist_event`ee' = abs(dist_event`ee')
|
| replace totnonstopwords`ee'=-999 if totnonstopwords`ee'==. & abs_dist_event`ee'!=.
|
| }
|
|
|
| egen closestevent=rowmin(abs_dist_event1 abs_dist_event2 abs_dist_event3 abs_dist_event4 abs_dist_event5 abs_dist_event6 abs_dist_event7 abs_dist_event8 abs_dist_event9)
|
| g nwords = .
|
| forval ee = 9(-1)1 {
|
| replace nwords = word`ee' if abs_dist_event`ee'==closestevent & totnonstopwords`ee'!=-999
|
| }
|
|
|
| su nwords
|
| replace nwords = (nwords - r(mean)) / r(sd)
|
|
|
| su bias_off2
|
| replace bias_off2 = (bias_off2 - r(mean)) / r(sd)
|
|
|
| g TPXnwords = TRUMP_POST_1_30*nwords
|
| replace TPXnwords = 0 if NEVER_TREATED==1
|
|
|
| g TPXbiasXnwords=TRUMP_POST_1_30*bias_off2*nwords
|
| replace TPXbiasXnwords = 0 if NEVER_TREATED==1
|
|
|
| g TPXbias = TRUMP_POST_1_30 * bias_off2
|
|
|
| noisily: di "TRADE: "
|
| noisily: reghdfe black 1.TRUMP_PRE_M30 1.TRUMP_0 1.TRUMP_POST_1_30 TPXnwords bias_off2 TPXbias TPXbiasXnwords 1.TRUMP_POST_M30, a(i.county_id i.day_id i.county_id#c.day_id) cluster(county_id day_id)
|
| outreg2 using "Results/Table7B.txt", append dec(3) keep(1.TRUMP_POST_1_30 TPXnwords bias_off2 TPXbias TPXbiasXnwords) addtext("Words","Trade") label nonotes nocons noni
|
|
|
|
|
| import excel "Data\wordcount-eachspeech-all.xlsx", sheet("Sheet1") firstrow clear
|
| set obs 2655
|
| replace A="totnonstopwords" in 2655
|
| foreach v of varlist B-GI {
|
| egen totwordsX=total(`v')
|
| replace `v'=totwordsX in 2655
|
| drop totwordsX
|
| }
|
| foreach v of varlist B-GI {
|
| local x : variable label `v'
|
| rename `v' v`x'
|
| }
|
| keep if A=="HILARI" | A=="CLINTON" | A=="EMAIL" | A=="LOCK" | A=="totnonstopwords"
|
| keep A v*
|
|
|
| reshape long v, i(A) j(id)
|
| sort id
|
| by id: egen B = total(v) if A!="totnonstopwords"
|
| by id: egen C = max(B)
|
| keep if A=="totnonstopwords"
|
| keep id v C
|
| rename C A
|
| replace A=0 if A==.
|
| rename v totnonstopwords
|
| rename A word
|
| merge 1:1 id using "Data\speech_data.dta"
|
| drop if _merge==2
|
| replace totnonstopwords=-999 if totnonstopwords==0 | totnonstopwords==.
|
| replace totwords=-999 if totnonstopwords==-999
|
| g inspeechdata = (_merge==3)
|
| drop state A _merge id
|
| destring county_fips, replace
|
| reshape wide word event_day_Trump_ totnonstopwords totwords inspeechdata, i(county_fips) j(rally_number)
|
| drop if county_fips==.
|
| egen inspeechdata=rowmax(inspeechdata1 inspeechdata2 inspeechdata3 inspeechdata4 inspeechdata5 inspeechdata6 inspeechdata7 inspeechdata8 inspeechdata9)
|
| drop inspeechdata1 inspeechdata2 inspeechdata3 inspeechdata4 inspeechdata5 inspeechdata6 inspeechdata7 inspeechdata8 inspeechdata9 totwords*
|
|
|
| merge 1:m county_fips using "Data/full_data_tomergewithspeech.dta"
|
| keep if _merge!=1
|
|
|
|
|
| forval ee = 9(-1)1 {
|
| g abs_dist_event`ee' = abs(dist_event`ee')
|
| replace totnonstopwords`ee'=-999 if totnonstopwords`ee'==. & abs_dist_event`ee'!=.
|
| }
|
|
|
| egen closestevent=rowmin(abs_dist_event1 abs_dist_event2 abs_dist_event3 abs_dist_event4 abs_dist_event5 abs_dist_event6 abs_dist_event7 abs_dist_event8 abs_dist_event9)
|
| g nwords = .
|
| forval ee = 9(-1)1 {
|
| replace nwords = word`ee' if abs_dist_event`ee'==closestevent & totnonstopwords`ee'!=-999
|
| }
|
|
|
| su nwords
|
| replace nwords = (nwords - r(mean)) / r(sd)
|
|
|
| su bias_off2
|
| replace bias_off2 = (bias_off2 - r(mean)) / r(sd)
|
|
|
| g TPXnwords = TRUMP_POST_1_30*nwords
|
| replace TPXnwords = 0 if NEVER_TREATED==1
|
|
|
| g TPXbiasXnwords=TRUMP_POST_1_30*bias_off2*nwords
|
| replace TPXbiasXnwords = 0 if NEVER_TREATED==1
|
|
|
| g TPXbias = TRUMP_POST_1_30 * bias_off2
|
|
|
| noisily: di "CLINTON: "
|
| noisily: reghdfe black 1.TRUMP_PRE_M30 1.TRUMP_0 1.TRUMP_POST_1_30 TPXnwords bias_off2 TPXbias TPXbiasXnwords 1.TRUMP_POST_M30, a(i.county_id i.day_id i.county_id#c.day_id) cluster(county_id day_id)
|
| outreg2 using "Results/Table7B.txt", append dec(3) keep(1.TRUMP_POST_1_30 TPXnwords bias_off2 TPXbias TPXbiasXnwords) addtext("Words","Clinton") label nonotes nocons noni
|
|
|
|
|
| import excel "Data\wordcount-eachspeech-all.xlsx", sheet("Sheet1") firstrow clear
|
| set obs 2655
|
| replace A="totnonstopwords" in 2655
|
| foreach v of varlist B-GI {
|
| egen totwordsX=total(`v')
|
| replace `v'=totwordsX in 2655
|
| drop totwordsX
|
| }
|
| foreach v of varlist B-GI {
|
| local x : variable label `v'
|
| rename `v' v`x'
|
| }
|
| keep if A=="ISI" | A=="SYRIA" | A=="IRAQ" | A=="TERRORIST" | A=="AFGHANISTAN" | A=="ISLAM" | A=="totnonstopwords"
|
| keep A v*
|
|
|
| reshape long v, i(A) j(id)
|
| sort id
|
| by id: egen B = total(v) if A!="totnonstopwords"
|
| by id: egen C = max(B)
|
| keep if A=="totnonstopwords"
|
| keep id v C
|
| rename C A
|
| replace A=0 if A==.
|
| rename v totnonstopwords
|
| rename A word
|
| merge 1:1 id using "Data\speech_data.dta"
|
| drop if _merge==2
|
| replace totnonstopwords=-999 if totnonstopwords==0 | totnonstopwords==.
|
| replace totwords=-999 if totnonstopwords==-999
|
| g inspeechdata = (_merge==3)
|
| drop state A _merge id
|
| destring county_fips, replace
|
| reshape wide word event_day_Trump_ totnonstopwords totwords inspeechdata, i(county_fips) j(rally_number)
|
| drop if county_fips==.
|
| egen inspeechdata=rowmax(inspeechdata1 inspeechdata2 inspeechdata3 inspeechdata4 inspeechdata5 inspeechdata6 inspeechdata7 inspeechdata8 inspeechdata9)
|
| drop inspeechdata1 inspeechdata2 inspeechdata3 inspeechdata4 inspeechdata5 inspeechdata6 inspeechdata7 inspeechdata8 inspeechdata9 totwords*
|
|
|
| merge 1:m county_fips using "Data/full_data_tomergewithspeech.dta"
|
| keep if _merge!=1
|
|
|
|
|
| forval ee = 9(-1)1 {
|
| g abs_dist_event`ee' = abs(dist_event`ee')
|
| replace totnonstopwords`ee'=-999 if totnonstopwords`ee'==. & abs_dist_event`ee'!=.
|
| }
|
|
|
| egen closestevent=rowmin(abs_dist_event1 abs_dist_event2 abs_dist_event3 abs_dist_event4 abs_dist_event5 abs_dist_event6 abs_dist_event7 abs_dist_event8 abs_dist_event9)
|
| g nwords = .
|
| forval ee = 9(-1)1 {
|
| replace nwords = word`ee' if abs_dist_event`ee'==closestevent & totnonstopwords`ee'!=-999
|
| }
|
|
|
| su nwords
|
| replace nwords = (nwords - r(mean)) / r(sd)
|
|
|
| su bias_off2
|
| replace bias_off2 = (bias_off2 - r(mean)) / r(sd)
|
|
|
| g TPXnwords = TRUMP_POST_1_30*nwords
|
| replace TPXnwords = 0 if NEVER_TREATED==1
|
|
|
| g TPXbiasXnwords=TRUMP_POST_1_30*bias_off2*nwords
|
| replace TPXbiasXnwords = 0 if NEVER_TREATED==1
|
|
|
| g TPXbias = TRUMP_POST_1_30 * bias_off2
|
|
|
| noisily: di "TERROR: "
|
| noisily: reghdfe black 1.TRUMP_PRE_M30 1.TRUMP_0 1.TRUMP_POST_1_30 TPXnwords bias_off2 TPXbias TPXbiasXnwords 1.TRUMP_POST_M30, a(i.county_id i.day_id i.county_id#c.day_id) cluster(county_id day_id)
|
| outreg2 using "Results/Table7B.txt", append dec(3) keep(1.TRUMP_POST_1_30 TPXnwords bias_off2 TPXbias TPXbiasXnwords) addtext("Words","Terror") label nonotes nocons noni
|
|
|
|
|
| import excel "Data\wordcount-eachspeech-all.xlsx", sheet("Sheet1") firstrow clear
|
| set obs 2655
|
| replace A="totnonstopwords" in 2655
|
| foreach v of varlist B-GI {
|
| egen totwordsX=total(`v')
|
| replace `v'=totwordsX in 2655
|
| drop totwordsX
|
| }
|
| foreach v of varlist B-GI {
|
| local x : variable label `v'
|
| rename `v' v`x'
|
| }
|
| keep if A=="BUSI" | A=="JOB" | A=="MANUFACTUR" | A=="TAX" | A=="totnonstopwords"
|
| keep A v*
|
|
|
| reshape long v, i(A) j(id)
|
| sort id
|
| by id: egen B = total(v) if A!="totnonstopwords"
|
| by id: egen C = max(B)
|
| keep if A=="totnonstopwords"
|
| keep id v C
|
| rename C A
|
| replace A=0 if A==.
|
| rename v totnonstopwords
|
| rename A word
|
| merge 1:1 id using "Data\speech_data.dta"
|
| drop if _merge==2
|
| replace totnonstopwords=-999 if totnonstopwords==0 | totnonstopwords==.
|
| replace totwords=-999 if totnonstopwords==-999
|
| g inspeechdata = (_merge==3)
|
| drop state A _merge id
|
| destring county_fips, replace
|
| reshape wide word event_day_Trump_ totnonstopwords totwords inspeechdata, i(county_fips) j(rally_number)
|
| drop if county_fips==.
|
| egen inspeechdata=rowmax(inspeechdata1 inspeechdata2 inspeechdata3 inspeechdata4 inspeechdata5 inspeechdata6 inspeechdata7 inspeechdata8 inspeechdata9)
|
| drop inspeechdata1 inspeechdata2 inspeechdata3 inspeechdata4 inspeechdata5 inspeechdata6 inspeechdata7 inspeechdata8 inspeechdata9 totwords*
|
|
|
| merge 1:m county_fips using "Data/full_data_tomergewithspeech.dta"
|
| keep if _merge!=1
|
|
|
|
|
| forval ee = 9(-1)1 {
|
| g abs_dist_event`ee' = abs(dist_event`ee')
|
| replace totnonstopwords`ee'=-999 if totnonstopwords`ee'==. & abs_dist_event`ee'!=.
|
| }
|
|
|
| egen closestevent=rowmin(abs_dist_event1 abs_dist_event2 abs_dist_event3 abs_dist_event4 abs_dist_event5 abs_dist_event6 abs_dist_event7 abs_dist_event8 abs_dist_event9)
|
| g nwords = .
|
| forval ee = 9(-1)1 {
|
| replace nwords = word`ee' if abs_dist_event`ee'==closestevent & totnonstopwords`ee'!=-999
|
| }
|
|
|
| su nwords
|
| replace nwords = (nwords - r(mean)) / r(sd)
|
|
|
| su bias_off2
|
| replace bias_off2 = (bias_off2 - r(mean)) / r(sd)
|
|
|
| g TPXnwords = TRUMP_POST_1_30*nwords
|
| replace TPXnwords = 0 if NEVER_TREATED==1
|
|
|
| g TPXbiasXnwords=TRUMP_POST_1_30*bias_off2*nwords
|
| replace TPXbiasXnwords = 0 if NEVER_TREATED==1
|
|
|
| g TPXbias = TRUMP_POST_1_30 * bias_off2
|
|
|
| noisily: di "JOB: "
|
| noisily: reghdfe black 1.TRUMP_PRE_M30 1.TRUMP_0 1.TRUMP_POST_1_30 TPXnwords bias_off2 TPXbias TPXbiasXnwords 1.TRUMP_POST_M30, a(i.county_id i.day_id i.county_id#c.day_id) cluster(county_id day_id)
|
| outreg2 using "Results/Table7B.txt", append dec(3) keep(1.TRUMP_POST_1_30 TPXnwords bias_off2 TPXbias TPXbiasXnwords) addtext("Words","Job") label nonotes nocons noni
|
|
|
|
|
| import excel "Data\wordcount-eachspeech-all.xlsx", sheet("Sheet1") firstrow clear
|
| set obs 2655
|
| replace A="totnonstopwords" in 2655
|
| foreach v of varlist B-GI {
|
| egen totwordsX=total(`v')
|
| replace `v'=totwordsX in 2655
|
| drop totwordsX
|
| }
|
| foreach v of varlist B-GI {
|
| local x : variable label `v'
|
| rename `v' v`x'
|
| }
|
| keep if A=="RIG" | A=="MEDIA" | A=="CNN" | A=="WASHINGTON" | A=="CORRUPT" | A=="SWAMP" | A=="totnonstopwords"
|
| keep A v*
|
|
|
| reshape long v, i(A) j(id)
|
| sort id
|
| by id: egen B = total(v) if A!="totnonstopwords"
|
| by id: egen C = max(B)
|
| keep if A=="totnonstopwords"
|
| keep id v C
|
| rename C A
|
| replace A=0 if A==.
|
| rename v totnonstopwords
|
| rename A word
|
| merge 1:1 id using "Data\speech_data.dta"
|
| drop if _merge==2
|
| replace totnonstopwords=-999 if totnonstopwords==0 | totnonstopwords==.
|
| replace totwords=-999 if totnonstopwords==-999
|
| g inspeechdata = (_merge==3)
|
| drop state A _merge id
|
| destring county_fips, replace
|
| reshape wide word event_day_Trump_ totnonstopwords totwords inspeechdata, i(county_fips) j(rally_number)
|
| drop if county_fips==.
|
| egen inspeechdata=rowmax(inspeechdata1 inspeechdata2 inspeechdata3 inspeechdata4 inspeechdata5 inspeechdata6 inspeechdata7 inspeechdata8 inspeechdata9)
|
| drop inspeechdata1 inspeechdata2 inspeechdata3 inspeechdata4 inspeechdata5 inspeechdata6 inspeechdata7 inspeechdata8 inspeechdata9 totwords*
|
|
|
| merge 1:m county_fips using "Data/full_data_tomergewithspeech.dta"
|
| keep if _merge!=1
|
|
|
|
|
| forval ee = 9(-1)1 {
|
| g abs_dist_event`ee' = abs(dist_event`ee')
|
| replace totnonstopwords`ee'=-999 if totnonstopwords`ee'==. & abs_dist_event`ee'!=.
|
| }
|
|
|
| egen closestevent=rowmin(abs_dist_event1 abs_dist_event2 abs_dist_event3 abs_dist_event4 abs_dist_event5 abs_dist_event6 abs_dist_event7 abs_dist_event8 abs_dist_event9)
|
| g nwords = .
|
| forval ee = 9(-1)1 {
|
| replace nwords = word`ee' if abs_dist_event`ee'==closestevent & totnonstopwords`ee'!=-999
|
| }
|
|
|
| su nwords
|
| replace nwords = (nwords - r(mean)) / r(sd)
|
|
|
| su bias_off2
|
| replace bias_off2 = (bias_off2 - r(mean)) / r(sd)
|
|
|
| g TPXnwords = TRUMP_POST_1_30*nwords
|
| replace TPXnwords = 0 if NEVER_TREATED==1
|
|
|
| g TPXbiasXnwords=TRUMP_POST_1_30*bias_off2*nwords
|
| replace TPXbiasXnwords = 0 if NEVER_TREATED==1
|
|
|
| g TPXbias = TRUMP_POST_1_30 * bias_off2
|
|
|
| noisily: di "CORRUPTION: "
|
| noisily: reghdfe black 1.TRUMP_PRE_M30 1.TRUMP_0 1.TRUMP_POST_1_30 TPXnwords bias_off2 TPXbias TPXbiasXnwords 1.TRUMP_POST_M30, a(i.county_id i.day_id i.county_id#c.day_id) cluster(county_id day_id)
|
| outreg2 using "Results/Table7B.txt", append dec(3) keep(1.TRUMP_POST_1_30 TPXnwords bias_off2 TPXbias TPXbiasXnwords) addtext("Words","Corruption") label nonotes nocons noni
|
|
|
| }
|
|
|
| } |
