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qui:{
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import excel "Data\wordcount-eachspeech-all.xlsx", sheet("Sheet1") firstrow clear
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set obs 2655
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replace A="totnonstopwords" in 2655
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foreach v of varlist B-GI {
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egen totwordsX=total(`v')
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replace `v'=totwordsX in 2655
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drop totwordsX
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}
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foreach v of varlist B-GI {
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local x : variable label `v'
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rename `v' v`x'
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}
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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"
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keep A v*
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reshape long v, i(A) j(id)
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sort id
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by id: egen B = total(v) if A!="totnonstopwords"
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by id: egen C = max(B)
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keep if A=="totnonstopwords"
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keep id v C
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rename C A
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replace A=0 if A==.
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rename v totnonstopwords
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rename A word
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merge 1:1 id using "Data\speech_data.dta"
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drop if _merge==2
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replace totnonstopwords=-999 if totnonstopwords==0 | totnonstopwords==.
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replace totwords=-999 if totnonstopwords==-999
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g inspeechdata = (_merge==3)
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drop state A _merge id
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destring county_fips, replace
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reshape wide word event_day_Trump_ totnonstopwords totwords inspeechdata, i(county_fips) j(rally_number)
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drop if county_fips==.
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egen inspeechdata=rowmax(inspeechdata1 inspeechdata2 inspeechdata3 inspeechdata4 inspeechdata5 inspeechdata6 inspeechdata7 inspeechdata8 inspeechdata9)
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drop inspeechdata1 inspeechdata2 inspeechdata3 inspeechdata4 inspeechdata5 inspeechdata6 inspeechdata7 inspeechdata8 inspeechdata9 totwords*
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merge 1:m county_fips using "Data/full_data_tomergewithspeech.dta"
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keep if _merge!=1
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forval ee = 9(-1)1 {
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g abs_dist_event`ee' = abs(dist_event`ee')
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replace totnonstopwords`ee'=-999 if totnonstopwords`ee'==. & abs_dist_event`ee'!=.
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}
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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)
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g nwords = .
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forval ee = 9(-1)1 {
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replace nwords = word`ee' if abs_dist_event`ee'==closestevent & totnonstopwords`ee'!=-999
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}
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su nwords
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replace nwords = (nwords - r(mean)) / r(sd)
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su bias_off1
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replace bias_off1 = (bias_off1 - r(mean)) / r(sd)
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g TPXnwords = TRUMP_POST_1_30*nwords
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replace TPXnwords = 0 if NEVER_TREATED==1
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g TPXbiasXnwords=TRUMP_POST_1_30*bias_off1*nwords
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replace TPXbiasXnwords = 0 if NEVER_TREATED==1
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g TPXbias = TRUMP_POST_1_30 * bias_off1
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noisily: di "ALL REFERENCES: "
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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)
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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
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import excel "Data\wordcount-eachspeech-all.xlsx", sheet("Sheet1") firstrow clear
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set obs 2655
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replace A="totnonstopwords" in 2655
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foreach v of varlist B-GI {
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egen totwordsX=total(`v')
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replace `v'=totwordsX in 2655
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drop totwordsX
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}
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foreach v of varlist B-GI {
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local x : variable label `v'
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rename `v' v`x'
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}
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keep if A=="AFRICAN" | A=="BLACK" | A=="RACE" | A=="RACIAL" | A=="RACIST" | A=="totnonstopwords"
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keep A v*
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reshape long v, i(A) j(id)
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sort id
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by id: egen B = total(v) if A!="totnonstopwords"
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by id: egen C = max(B)
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keep if A=="totnonstopwords"
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keep id v C
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rename C A
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replace A=0 if A==.
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rename v totnonstopwords
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rename A word
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merge 1:1 id using "Data\speech_data.dta"
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drop if _merge==2
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replace totnonstopwords=-999 if totnonstopwords==0 | totnonstopwords==.
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replace totwords=-999 if totnonstopwords==-999
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g inspeechdata = (_merge==3)
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|
drop state A _merge id
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|
destring county_fips, replace
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reshape wide word event_day_Trump_ totnonstopwords totwords inspeechdata, i(county_fips) j(rally_number)
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drop if county_fips==.
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egen inspeechdata=rowmax(inspeechdata1 inspeechdata2 inspeechdata3 inspeechdata4 inspeechdata5 inspeechdata6 inspeechdata7 inspeechdata8 inspeechdata9)
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drop inspeechdata1 inspeechdata2 inspeechdata3 inspeechdata4 inspeechdata5 inspeechdata6 inspeechdata7 inspeechdata8 inspeechdata9 totwords*
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|
|
merge 1:m county_fips using "Data/full_data_tomergewithspeech.dta"
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keep if _merge!=1
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forval ee = 9(-1)1 {
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|
g abs_dist_event`ee' = abs(dist_event`ee')
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|
replace totnonstopwords`ee'=-999 if totnonstopwords`ee'==. & abs_dist_event`ee'!=.
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|
}
|
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|
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|
|
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)
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g nwords = .
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|
|
forval ee = 9(-1)1 {
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|
|
replace nwords = word`ee' if abs_dist_event`ee'==closestevent & totnonstopwords`ee'!=-999
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|
|
}
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|
|
su nwords
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|
|
replace nwords = (nwords - r(mean)) / r(sd)
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|
su bias_off1
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|
|
replace bias_off1 = (bias_off1 - r(mean)) / r(sd)
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g TPXnwords = TRUMP_POST_1_30*nwords
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|
|
replace TPXnwords = 0 if NEVER_TREATED==1
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g TPXbiasXnwords=TRUMP_POST_1_30*bias_off1*nwords
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|
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replace TPXbiasXnwords = 0 if NEVER_TREATED==1
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|
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|
g TPXbias = TRUMP_POST_1_30 * bias_off1
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|
noisily: di "EXPLICIT REFERENCES"
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|
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)
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|
|
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
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|
|
|
|
|
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'
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|
|
}
|
|
|
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
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|
|
replace A=0 if A==.
|
|
|
rename v totnonstopwords
|
|
|
rename A word
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|
|
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)
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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
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import excel "Data\wordcount-eachspeech-all.xlsx", sheet("Sheet1") firstrow clear
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set obs 2655
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replace A="totnonstopwords" in 2655
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foreach v of varlist B-GI {
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egen totwordsX=total(`v')
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replace `v'=totwordsX in 2655
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drop totwordsX
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}
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foreach v of varlist B-GI {
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local x : variable label `v'
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rename `v' v`x'
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}
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keep if A=="BUSI" | A=="JOB" | A=="MANUFACTUR" | A=="TAX" | A=="totnonstopwords"
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keep A v*
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reshape long v, i(A) j(id)
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sort id
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by id: egen B = total(v) if A!="totnonstopwords"
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by id: egen C = max(B)
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keep if A=="totnonstopwords"
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keep id v C
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rename C A
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replace A=0 if A==.
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rename v totnonstopwords
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rename A word
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merge 1:1 id using "Data\speech_data.dta"
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drop if _merge==2
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replace totnonstopwords=-999 if totnonstopwords==0 | totnonstopwords==.
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replace totwords=-999 if totnonstopwords==-999
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g inspeechdata = (_merge==3)
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drop state A _merge id
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destring county_fips, replace
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reshape wide word event_day_Trump_ totnonstopwords totwords inspeechdata, i(county_fips) j(rally_number)
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drop if county_fips==.
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egen inspeechdata=rowmax(inspeechdata1 inspeechdata2 inspeechdata3 inspeechdata4 inspeechdata5 inspeechdata6 inspeechdata7 inspeechdata8 inspeechdata9)
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drop inspeechdata1 inspeechdata2 inspeechdata3 inspeechdata4 inspeechdata5 inspeechdata6 inspeechdata7 inspeechdata8 inspeechdata9 totwords*
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merge 1:m county_fips using "Data/full_data_tomergewithspeech.dta"
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keep if _merge!=1
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forval ee = 9(-1)1 {
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g abs_dist_event`ee' = abs(dist_event`ee')
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replace totnonstopwords`ee'=-999 if totnonstopwords`ee'==. & abs_dist_event`ee'!=.
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}
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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)
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g nwords = .
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forval ee = 9(-1)1 {
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replace nwords = word`ee' if abs_dist_event`ee'==closestevent & totnonstopwords`ee'!=-999
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}
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su nwords
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replace nwords = (nwords - r(mean)) / r(sd)
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su bias_off2
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replace bias_off2 = (bias_off2 - r(mean)) / r(sd)
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g TPXnwords = TRUMP_POST_1_30*nwords
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replace TPXnwords = 0 if NEVER_TREATED==1
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g TPXbiasXnwords=TRUMP_POST_1_30*bias_off2*nwords
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replace TPXbiasXnwords = 0 if NEVER_TREATED==1
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g TPXbias = TRUMP_POST_1_30 * bias_off2
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noisily: di "JOB: "
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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)
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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
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import excel "Data\wordcount-eachspeech-all.xlsx", sheet("Sheet1") firstrow clear
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set obs 2655
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replace A="totnonstopwords" in 2655
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foreach v of varlist B-GI {
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egen totwordsX=total(`v')
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replace `v'=totwordsX in 2655
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drop totwordsX
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}
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foreach v of varlist B-GI {
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local x : variable label `v'
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rename `v' v`x'
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}
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keep if A=="RIG" | A=="MEDIA" | A=="CNN" | A=="WASHINGTON" | A=="CORRUPT" | A=="SWAMP" | A=="totnonstopwords"
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keep A v*
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reshape long v, i(A) j(id)
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sort id
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by id: egen B = total(v) if A!="totnonstopwords"
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by id: egen C = max(B)
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keep if A=="totnonstopwords"
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keep id v C
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rename C A
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replace A=0 if A==.
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rename v totnonstopwords
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rename A word
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merge 1:1 id using "Data\speech_data.dta"
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drop if _merge==2
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replace totnonstopwords=-999 if totnonstopwords==0 | totnonstopwords==.
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replace totwords=-999 if totnonstopwords==-999
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g inspeechdata = (_merge==3)
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drop state A _merge id
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destring county_fips, replace
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reshape wide word event_day_Trump_ totnonstopwords totwords inspeechdata, i(county_fips) j(rally_number)
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drop if county_fips==.
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egen inspeechdata=rowmax(inspeechdata1 inspeechdata2 inspeechdata3 inspeechdata4 inspeechdata5 inspeechdata6 inspeechdata7 inspeechdata8 inspeechdata9)
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drop inspeechdata1 inspeechdata2 inspeechdata3 inspeechdata4 inspeechdata5 inspeechdata6 inspeechdata7 inspeechdata8 inspeechdata9 totwords*
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merge 1:m county_fips using "Data/full_data_tomergewithspeech.dta"
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keep if _merge!=1
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forval ee = 9(-1)1 {
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g abs_dist_event`ee' = abs(dist_event`ee')
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replace totnonstopwords`ee'=-999 if totnonstopwords`ee'==. & abs_dist_event`ee'!=.
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}
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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)
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g nwords = .
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forval ee = 9(-1)1 {
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replace nwords = word`ee' if abs_dist_event`ee'==closestevent & totnonstopwords`ee'!=-999
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}
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su nwords
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replace nwords = (nwords - r(mean)) / r(sd)
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su bias_off2
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replace bias_off2 = (bias_off2 - r(mean)) / r(sd)
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g TPXnwords = TRUMP_POST_1_30*nwords
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replace TPXnwords = 0 if NEVER_TREATED==1
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g TPXbiasXnwords=TRUMP_POST_1_30*bias_off2*nwords
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replace TPXbiasXnwords = 0 if NEVER_TREATED==1
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g TPXbias = TRUMP_POST_1_30 * bias_off2
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noisily: di "CORRUPTION: "
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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)
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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
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}
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} |
