//Only include wave with participants
use "${inter}/Psycorona_long_sft2",clear
cap drop miss
egen miss=rmiss(w_c19perBeh01_Harmonized w_c19perBeh02_Harmonized w_c19perBeh03_Harmonized age gender unemployment edu w_PFS01)
drop if miss>0
cap drop m33
merge n:1 CountryName edate using "${inter}/vaccination",gen(m33) update
keep if m33==3
sort CountryName edate
keep CountryName people_vaccinated_per_hundred edate
duplicates drop  CountryName edate,force
keep if edate==22383|edate==22474
codebook CountryName 
export excel using "${inter}/vaccination_07",firstrow(variables) 

import excel "${inter}/vaccination_07.xls", sheet("Sheet1") firstrow clear
save "${inter}/vaccination_07_final_used",replace

////2021 population data (source: https://www.cia.gov/the-world-factbook/about/archives/2021/field/population/country-comparison)
import delimited "${input}/pop_data 2021", varnames(1) clear
rename name CountryName
cap drop pop
destring value, ignore(",") gen(pop)
replace pop=pop/1000
keep CountryName pop
replace CountryName="Czech Republic" if CountryName=="Czechia" 
replace CountryName="Republic of Serbia" if CountryName=="Serbia" 
replace CountryName="South Korea" if CountryName=="Korea, South"
replace CountryName="United Republic of Tanzania" if CountryName=="Tanzania"
replace CountryName="United States of America" if CountryName=="United States"
save "${inter}/2021pop", replace

//all countries in final regression & two dates
use "${inter}/Psycorona_long_sft2",clear
cap drop miss
egen miss=rmiss(w_c19perBeh01_Harmonized w_c19perBeh02_Harmonized w_c19perBeh03_Harmonized age gender unemployment edu w_PFS01 )
drop if miss>0
duplicates drop CountryName,force
keep CountryName sft_pca COUNTRYTot_Population（thousand）
cap drop date1
gen date1="2021-04-13"
cap drop date2
gen date2="2021-07-13"
tolong date*,i(CountryName)
gen date2=date(date,"YMD") 
format date2 %dM_d,_CY
rename date2 edate
cap drop m44
merge 1:1 CountryName edate using "${inter}/vaccination",gen(m44) update
keep if m44==3
sort CountryName edate
keep CountryName people_vaccinated_per_hundred edate sft_pca
drop if CountryName=="Hong Kong S.A.R."|CountryName=="Taiwan"
save "${inter}/vaccination_07_all",replace


use "${inter}/vaccination_07_final_used",clear
cap drop date_num
bysort CountryName: egen date_num=count(edate)
cap drop a1
merge 1:1 CountryName edate using "${inter}/vaccination_07_all",gen(a1)
cap drop num
bysort CountryName: egen num=sum(date_num)
cap drop CountryName1
gen CountryName1=CountryName
replace CountryName1=CountryName+"*" if num==0
cap drop country
encode CountryName, gen(country)
drop a1 num date_num
rename people_vaccinated_per_hundred people_vaccinated
reshape wide people_vaccinated, j(edate) i(country)
sort CountryName 
cap drop increase_vacc
gen increase_vacc=people_vaccinated22474-people_vaccinated22383 

//figure S1
graph hbar people_vaccinated22383 increase_vacc  if people_vaccinated22474<=29,  bar(1, color("0 108 162")) bar(2, color("172 205 220"))  over(CountryName1, sort(people_vaccinated22474)lab(angle(0) labsize(vsmall) ))  graphregion(color(white))  ytitle("")  legend(label(1 "April 13, 2021") label(2 "Increase between April 13 and July 13, 2021") col(1) size(vsmall)) graphregion(fcolor(white)) ysize(13)  xsize(6.5) stack 
graph save "${output}/vaccination1",replace

graph hbar people_vaccinated22383 increase_vacc  if people_vaccinated22474>29, bar(1, color("0 108 162")) bar(2, color("172 205 220"))  over(CountryName1, sort(people_vaccinated22474)lab(angle(0) labsize(vsmall) ))  graphregion(color(white))  ytitle("")  legend(label(1 "April 13, 2021") label(2 "Increase between April 13 and July 13, 2021") col(1) size(vsmall)) graphregion(fcolor(white)) ysize(13)xsize(6.5) stack 
graph save "${output}/vaccination2",replace

graph combine "${output}/vaccination1.gph" "${output}/vaccination2.gph" , col(2)  scheme(s1mono) scale(0.7)  ysize(9) xsize(8.2)
graph save "${output}/vaccination_combined",replace


use "${inter}/vaccination_07_all",clear
cap drop m55
merge n:1 CountryName using  "${inter}/2021pop",gen(m55)
replace pop=53798.084 if CountryName=="Myanmar"
replace pop=5133.392  if CountryName=="Palestine"
drop if m55==2
cap drop country
encode CountryName, gen(country)
rename people_vaccinated_per_hundred people_vaccinated
reshape wide people_vaccinated, j(edate) i(country)

//X: country-level family ties, Y: increase in vaccination coverage between April 13 and July 13 2021 as a percentage of vaccination coverage on April 13 2021 (%)
tab CountryName if people_vaccinated22383==0
//for Bosnia and Herzegovina & Libya, use data nearest to April 13
replace people_vaccinated22383=0.79 if CountryName=="Bosnia and Herzegovina" //April 14
replace people_vaccinated22383=0.01 if CountryName=="Libya" //April 17
cap drop increase_vacc_per
gen increase_vacc_per=(people_vaccinated22474-people_vaccinated22383)/people_vaccinated22383
sum increase_vacc_per,d
sort increase_vacc_per
drop if increase_vacc_per==623 | increase_vacc_per==138.5|CountryName=="Albania" //outlier 

//Figure S2
twoway (scatter increase_vacc_per sft_pca [w=pop],mlcolor("46 134 178") mfcolor("222 236 243") )(lfit increase_vacc_per sft_pca, color("155 58 74")), ///
xtitle("Country-level strength of family ties",size(small)) ytitle(`"Precentage increase of country-level vaccination coverage"' `"between April 13 and July 13, 2021"' , size(small)) legend(off) scheme(s1mono) xlab(,labsize(small)) ylab(,labsize(small))
reg increase_vacc_per sft_pca
graph save "${output}/vaccination5",replace