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*** FIGURE A4
*** Distribution of the Difference-in-Differences Effects
**********************************************************************
use "Data\county_day_data.dta", clear
keep if year==2015 | year==2016 | year==2017
rename TRUMP_POST_1_30 TRUMP_POST30
rename TRUMP_PRE_M30 TRUMP_PREM30
rename TRUMP_POST_M30 TRUMP_POSTM30
***number of counties 1,478
qui: {
forval ii = 1/1478 {
su n_stops if county_id==`ii' & TRUMP_POST30==1
if r(N) != 0 {
total n_stops if county_id==`ii' & TRUMP_POST30==1
global stops`ii' = _b[n_stops]
g TREATED_COUNTY_`ii' = (county_id==`ii')
}
}
}
**I drop the first for collinearity
drop TREATED_COUNTY_9
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)
mat treat = 999* J(1478,2,1)
local numerator = 0
local denominator = 0
forval ii = 1/1478 {
qui: su n_stops if county_id==`ii' & TRUMP_POST30==1
if r(N) != 0 {
if `ii' == 9{
mat treat[`ii',1] = (_b[1.TRUMP_POST30])
mat treat[`ii',2] = (${stops`ii'})
local numerator = `numerator' + ((_b[1.TRUMP_POST30]) * ${stops`ii'})
local denominator = `denominator' + ${stops`ii'}
}
else {
mat treat[`ii',1] = (_b[1.TRUMP_POST30] + _b[1.TRUMP_POST30#1.TREATED_COUNTY_`ii'])
mat treat[`ii',2] = (${stops`ii'})
local numerator = `numerator' + ((_b[1.TRUMP_POST30] + _b[1.TRUMP_POST30#1.TREATED_COUNTY_`ii']) * ${stops`ii'})
local denominator = `denominator' + ${stops`ii'}
}
}
}
local effect = `numerator' / `denominator'
di `effect'
g yy = treat[_n,1] in 1/1478
g ww = treat[_n,2] in 1/1478
replace yy = . if yy==999
replace ww = . if ww==999
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)
graph export "Results\figureA4.pdf", as(pdf) name("Graph") replace
keep yy ww
drop if yy==.
save "Results\SA.dta", replace
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