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use "Data\county_day_data.dta", clear
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keep if year==2015 | year==2016 | year==2017
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rename TRUMP_POST_1_30 TRUMP_POST30
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rename TRUMP_PRE_M30 TRUMP_PREM30
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rename TRUMP_POST_M30 TRUMP_POSTM30
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qui: {
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forval ii = 1/1478 {
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su n_stops if county_id==`ii' & TRUMP_POST30==1
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if r(N) != 0 {
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total n_stops if county_id==`ii' & TRUMP_POST30==1
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global stops`ii' = _b[n_stops]
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g TREATED_COUNTY_`ii' = (county_id==`ii')
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}
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}
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}
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drop TREATED_COUNTY_9
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reghdfe black_ps 1.TRUMP_POST30 1.TRUMP_POST30#1.TREATED_COUNTY_* [w=n_stops], a(county_id day_id i.county_id#c.day_id TRUMP_PREM30 TRUMP_0 TRUMP_POSTM30) cluster(county_id day_id)
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mat treat = 999* J(1478,2,1)
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local numerator = 0
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local denominator = 0
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forval ii = 1/1478 {
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qui: su n_stops if county_id==`ii' & TRUMP_POST30==1
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if r(N) != 0 {
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if `ii' == 9{
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mat treat[`ii',1] = (_b[1.TRUMP_POST30])
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mat treat[`ii',2] = (${stops`ii'})
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local numerator = `numerator' + ((_b[1.TRUMP_POST30]) * ${stops`ii'})
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local denominator = `denominator' + ${stops`ii'}
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}
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else {
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mat treat[`ii',1] = (_b[1.TRUMP_POST30] + _b[1.TRUMP_POST30#1.TREATED_COUNTY_`ii'])
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mat treat[`ii',2] = (${stops`ii'})
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local numerator = `numerator' + ((_b[1.TRUMP_POST30] + _b[1.TRUMP_POST30#1.TREATED_COUNTY_`ii']) * ${stops`ii'})
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local denominator = `denominator' + ${stops`ii'}
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}
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}
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}
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local effect = `numerator' / `denominator'
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di `effect'
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g yy = treat[_n,1] in 1/1478
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g ww = treat[_n,2] in 1/1478
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replace yy = . if yy==999
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replace ww = . if ww==999
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graph twoway (hist yy [fweight=ww] if yy>-10 & yy<10, frac xtitle("Treatment Effects")) (scatteri 0 1.053357 0.2 1.053357, recast(line) lw(0.5)), legend(label(1 "Distribution Effects") label(2 "Average Effect")) graphregion(color(white)) scheme(s1mono)
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graph export "Results\figureA4.pdf", as(pdf) name("Graph") replace
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keep yy ww
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drop if yy==.
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save "Results\SA.dta", replace
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