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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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drop year TRUMP_*
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g FAKE_EFFECT = .
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forval iter = 1/1000 {
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di "ITERATION " `iter'
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qui: {
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g random_date = floor(runiform(20256,20765))
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g random_order = runiform()
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g random_county = floor(runiform(1,1479))
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sort random_order
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g FAKE_event_day_Trump_1 = .
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g FAKE_event_day_Trump_2 = .
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g FAKE_event_day_Trump_3 = .
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g FAKE_event_day_Trump_4 = .
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g FAKE_event_day_Trump_5 = .
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g FAKE_event_day_Trump_6 = .
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g FAKE_event_day_Trump_7 = .
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g FAKE_event_day_Trump_8 = .
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g FAKE_event_day_Trump_9 = .
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forval ii=1/196 {
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local completed = 0
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local counter = 1
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while `completed' == 0 {
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su FAKE_event_day_Trump_`counter' if county_id == random_county[`ii']
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if r(N) == 0 {
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replace FAKE_event_day_Trump_`counter' = random_date[`ii'] if county_id==random_county[`ii']
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local completed = 1
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}
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else {
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local counter = `counter' + 1
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}
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}
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}
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forval ii = 1/9 {
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g dist_event`ii' = day_id - FAKE_event_day_Trump_`ii'
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}
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g TRUMP_0 = 0
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forval ii = 1/9 {
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replace TRUMP_0 = 1 if dist_event`ii' == 0 & dist_event`ii'!=.
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}
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g TRUMP_POST_1_30 = 0
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forval ii = 1/9 {
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replace TRUMP_POST_1_30 = 1 if (dist_event`ii' > 0 & dist_event`ii'<=30 & dist_event`ii'!=.)
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}
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g TRUMP_POST_M30 = 0
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forval ii = 1/9 {
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replace TRUMP_POST_M30 = 1 if (dist_event`ii' >30 & dist_event`ii'!=.)
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}
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g TRUMP_PRE_M30 = 0
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forval ii = 1/9 {
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replace TRUMP_PRE_M30 = 1 if (dist_event`ii' <-30 & dist_event`ii'!=.)
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}
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reghdfe black_ps 1.TRUMP_* [w=n_stops], a(i.county_id i.day_id i.county_id#c.day_id) cluster(county_id day_id)
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replace FAKE_EFFECT = _b[1.TRUMP_POST_1_30] in `iter'
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drop FAKE_event_day_Trump_* random_* dist_event* TRUMP_*
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}
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}
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drop if FAKE_EFFECT == .
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hist FAKE_EFFECT if FAKE_EFFECT>-1.5 & FAKE_EFFECT<2, xline(1.07, lwidth(1)) percent xtitle("Coefficient on Fake Trump Rally") xlabel(-1.5(0.5)2) graphregion(color(white)) scheme(s1mono)
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graph export "Results\FigureA6.pdf", as(pdf) name("Graph") replace
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