clear
set mem 500m
set more off
set logtype text
set matsize 3000

cap log close
log using "$Log/TableD2.log", replace

use "$AnalysisData/bills_analysis_101-111_replication.dta"
keep if private==0

bysort v2 sponsor_state_abbrev sponsor_district sponsor_term_served: egen tot_bills=count(v2)

gen byte sponsor_democrat = sponsor_party==100 if sponsor_party~=.

gen byte NE = sponsor_state_icpsr>=1 & sponsor_state_icpsr<=14 if sponsor_state_icpsr~=.
gen byte MW = sponsor_state_icpsr>=21 & sponsor_state_icpsr<=37 if sponsor_state_icpsr~=.
gen byte SO = sponsor_state_icpsr>=40 & sponsor_state_icpsr<=56 if sponsor_state_icpsr~=.
gen byte WE = sponsor_state_icpsr>=61 & sponsor_state_icpsr<=82 if sponsor_state_icpsr~=.

replace sponsor_age=. if sponsor_age>100
gen sponsor_rookie=(sponsor_tenure_run==1) if sponsor_tenure_run!=.
gen byte leader = (comc==1) | (comr==1) if comc~=. & comr~=. 

gen lnpden=lnpop-lnarea
gen absMV=abs(MV1_democrat)

egen tag_congressmen=tag(v2 sponsor_state_abbrev sponsor_district sponsor_term_served)
egen group_congressmen = group(v2 sponsor_state_abbrev sponsor_district sponsor_term_served)
*egen tag_sponsor = tag(v2 sponsor_state_abbrev sponsor_district sponsor_term_served)
sort v2 sponsor_state_abbrev sponsor_district sponsor_term_served HRnumber
bysort v2 sponsor_state_abbrev sponsor_district sponsor_term_served: gen tag_sponsor=_n
egen group_sponsor = group(v2 sponsor_state_abbrev sponsor_district sponsor_term_served)

bysort v2 sponsor_state_abbrev sponsor_district sponsor_term_served: egen numb_cosponsors_m=mean(numb_cosponsors)

compress
 
*egen tag_bill = tag(v2 HRnumber)
sort v2 HRnumber
bysort v2 HRnumber: gen tag_bill=_n

gen int decade = 1980 if v2<=102
replace decade=1990 if v2>=103 & v2<=107
replace decade=2000 if v2>=108

egen district_id = group(decade sponsor_state_abbrev sponsor_district)

sort  district_id v2 HRnumber
bysort district_id v2: gen counter=_n
foreach var of varlist tot_bills sponsor_female MV1_female MV1_democrat mixed_gender_ele /*
*/                     sponsor_party sponsor_democrat sponsor_rookie sponsor_tenure_run sponsor_age /*
*/                     leader ivycoll black occ0 occ1 occ2 occ3 occ4 borninstate {
	sort counter district_id v2
	bysort counter district_id: gen X=`var'[_n+1] if counter==1 & `var'[_n+1]!=.
	bysort district_id v2: egen `var'_l1=max(X)
	drop X
} 
gen female_l1XMV1_female_l1=MV1_female_l1*sponsor_female_l1
gen absMV_l1=abs(MV1_democrat_l1)

local controls1 = "i.v2 "
local controls2 = "i.v2 MV1_female_l1 female_l1XMV1_female_l1 "
local controls3 = "i.v2 MV1_female_l1 female_l1XMV1_female_l1 "
local controls4 = "i.v2 "
local controls5 = "i.v2 "

local other_controls = "i.minor house_* sponsor_democrat_l1 sponsor_rookie_l1 sponsor_tenure_run_l1 sponsor_age_l1 leader_l1 ivycoll_l1 black_l1 occ0_l1 occ1_l1 occ2_l1 occ3_l1 occ4_l1 borninstate_l1 tot_bills NE MW WE pct_black pct_urban pct_for_born pct_age_over65 lninc lnpden"
local billchars = "i.minor house_*"
local indivchars = "sponsor_democrat_l1 sponsor_rookie_l1 sponsor_tenure_run_l1 sponsor_age_l1 leader_l1 ivycoll_l1 black_l1 occ0_l1 occ1_l1 occ2_l1 occ3_l1 occ4_l1 borninstate_l1 tot_bills"
local districtchars = "NE MW WE pct_black pct_urban pct_for_born pct_age_over65 lninc lnpden"

local if1 = "if tag_bill==1 & sponsor_female==0"
local if2 = "if sponsor_party_l1==100 & tag_bill==1 & sponsor_female==0"
local if3 = "if sponsor_party_l1==200 & tag_bill==1 & sponsor_female==0"

forvalues j=1/5 {
   forvalues k = 1/3 {
	  qui reg numb_cosponsors sponsor_female_l1 `controls2' `other_controls' `if`k'' & mixed_gender_election_l1==1, robust cluster(group_sponsor)
	  qui gen sample=e(sample)
	  
	  di ""
	  di ""
	  di "j = ", `j', "k = ", `k'
	  di ""
	  di ""

   	  di "rdbwselect_2014 numb_cosponsors MV1_female_l1 `if`k'', c(0) kernel(uniform)"
	  rdbwselect_2014 numb_cosponsors MV1_female_l1 `if`k'', c(0) kernel(uniform)
	  local band = e(h_CCT)

	  if `j'==1 {
	     di "reg numb_cosponsors sponsor_female_l1 `controls`j'' `other_controls' `if`k'', robust cluster(group_sponsor)"
	     reg numb_cosponsors sponsor_female_l1 `controls`j'' `other_controls' `if`k'', robust cluster(group_sponsor)   
	  }
	  else if `j'==2 {
	     di "reg numb_cosponsors sponsor_female_l1 `controls`j'' `if`k'' & sample==1 & abs(MV1_female_l1)<=`band', robust cluster(group_sponsor)"
	     reg numb_cosponsors sponsor_female_l1 `controls`j'' `if`k'' & sample==1 & abs(MV1_female_l1)<=`band', robust cluster(group_sponsor)   
      }
	  else if `j'==3 {
         qui probit sponsor_female_l1 i.v2 `districtchars' `if`k'' & tag_sponsor==1 & abs(MV1_female_l1)<=`band'
         predict pscore if sample==1
         gen wt = 1/pscore if sponsor_female_l1==1
         replace wt =1/(1-pscore) if sponsor_female_l1==0
	     di "reg numb_cosponsors sponsor_female_l1 `controls`j'' `billchars' [aw=wt] `if`k'' & sample==1 & abs(MV1_female_l1)<=`band', robust cluster(group_sponsor)"
         reg numb_cosponsors sponsor_female_l1 `controls`j'' `billchars' [aw=wt] `if`k'' & sample==1 & abs(MV1_female_l1 )<=`band', robust cluster(group_sponsor)
         drop pscore wt
      }
	  else if `j'==4 {
         qui probit sponsor_female_l1 i.v2 `districtchars' absMV_l1 `if`k'' & tag_sponsor==1 
         predict pscore
         gen wt = 1/pscore if sponsor_female_l1==1
         replace wt =1/(1-pscore) if sponsor_female_l1==0
	     di "reg numb_cosponsors sponsor_female_l1 `controls`j'' `billchars' [aw=wt] `if`k'', robust cluster(group_sponsor)"
         reg numb_cosponsors sponsor_female_l1 `controls`j'' `billchars' [aw=wt] `if`k'', robust cluster(group_sponsor)
         drop pscore wt
      }
	  else if `j'==5 {
         qui probit sponsor_female_l1 i.v2 `districtchars' `indivchars' absMV_l1 `if`k'' & tag_sponsor==1 
         predict pscore
         gen wt = 1/pscore if sponsor_female_l1==1
         replace wt =1/(1-pscore) if sponsor_female_l1==0
	     di "reg numb_cosponsors sponsor_female_l1 `controls`j'' `billchars' [aw=wt] `if`k'', robust cluster(group_sponsor)"
         reg numb_cosponsors sponsor_female_l1 `controls`j'' `billchars' [aw=wt] `if`k'', robust cluster(group_sponsor)
         drop pscore wt
      }
	  
	  if `j'~=2 & `j'~=3 {
         scalar b_col`j'_row`k' = _b[sponsor_female_l1]
         scalar se_col`j'_row`k' = _se[sponsor_female_l1]
         scalar n_col`j'_row`k' = e(N)
		 sum tag_congressmen if tag_congressmen==1 & e(sample)
		 scalar ni_col`j'_row`k' = e(N_clust)
         scalar ob_col`j'_row`k' = .
	  }
	  else if `j'==2 | `j'==3 {
         scalar b_col`j'_row`k' = _b[sponsor_female_l1]
         scalar se_col`j'_row`k' = _se[sponsor_female_l1]
         scalar n_col`j'_row`k' = e(N)
		 sum tag_congressmen if tag_congressmen==1 & e(sample)
		 scalar ni_col`j'_row`k' = e(N_clust)
         scalar ob_col`j'_row`k' = round(`band')
	  }

      drop sample
      
   }
}

preserve

* Display results

forvalues i = 1/5 {
   gen var`i' =.
}
gen str20 var6 = ""
		  
forvalues j=1/5 {
   forvalues k = 1/3 {
      replace var`j' = b_col`j'_row`k' if _n==6*(`k'-1)+1
      replace var`j' = se_col`j'_row`k' if _n==6*(`k'-1)+2
      replace var`j' = n_col`j'_row`k' if _n==6*(`k'-1)+3
      replace var`j' = ni_col`j'_row`k' if _n==6*(`k'-1)+4
      replace var`j' = ob_col`j'_row`k' if _n==6*(`k'-1)+5
   }
}   

keep var1-var6
keep if _n<=18

order var6 var1-var5

ren var6 sampletype
ren var1 OLS_all
ren var2 RD_bwidth
ren var3 RD_match_bw
ren var4 PS_match
ren var5 PS_match_indiv

foreach var of varlist OLS_all RD_bwidth RD_match_bw PS_match PS_match_indiv {
   gen str3 `var'_stars ="*" if abs(`var'/`var'[_n+1])>=1.645 & mod(_n,6)==1
   replace `var'_stars ="**" if abs(`var'/`var'[_n+1])>=1.96 & mod(_n,6)==1
   replace `var'_stars="***" if abs(`var'/`var'[_n+1])>=2.58 & mod(_n,6)==1
}

replace sampletype = "All" if _n>=1 & _n<=5
replace sampletype = "Democrats" if _n>=7 & _n<=11
replace sampletype = "Republicans" if _n>=13 & _n<=17

order sampletype OLS_all OLS_all_stars RD_bwidth RD_bwidth_stars RD_match_bw RD_match_bw_stars PS_match PS_match_stars PS_match_indiv PS_match_indiv_stars 
         export excel using "$Output/TableD2_Placebo_Cosponsors", firstrow(var) replace

restore


*********************************************************************************************************************************************


* use "$Data/bills_analysis_101-111_clean.dta", clear
use "$AnalysisData/bills_analysis_101-111_replication.dta", clear
keep if private==0

bysort v2 sponsor_state_abbrev sponsor_district sponsor_term_served: egen tot_bills=count(v2)

gen byte sponsor_democrat = sponsor_party==100 if sponsor_party~=.

gen byte NE = sponsor_state_icpsr>=1 & sponsor_state_icpsr<=14 if sponsor_state_icpsr~=.
gen byte MW = sponsor_state_icpsr>=21 & sponsor_state_icpsr<=37 if sponsor_state_icpsr~=.
gen byte SO = sponsor_state_icpsr>=40 & sponsor_state_icpsr<=56 if sponsor_state_icpsr~=.
gen byte WE = sponsor_state_icpsr>=61 & sponsor_state_icpsr<=82 if sponsor_state_icpsr~=.

replace sponsor_age=. if sponsor_age>100
gen sponsor_rookie=(sponsor_tenure_run==1) if sponsor_tenure_run!=.
gen byte leader = (comc==1) | (comr==1) if comc~=. & comr~=. 

gen lnpden=lnpop-lnarea
gen absMV=abs(MV1_democrat)

egen tag_congressmen=tag(v2 sponsor_state_abbrev sponsor_district sponsor_term_served)
egen group_congressmen = group(v2 sponsor_state_abbrev sponsor_district sponsor_term_served)
*egen tag_sponsor = tag(v2 sponsor_state_abbrev sponsor_district sponsor_term_served)
sort v2 sponsor_state_abbrev sponsor_district sponsor_term_served HRnumber
bysort v2 sponsor_state_abbrev sponsor_district sponsor_term_served: gen tag_sponsor=_n
egen group_sponsor = group(v2 sponsor_state_abbrev sponsor_district sponsor_term_served)

cap drop pct_cosponsors_opposite
gen pct_cosponsors_opposite=100*numb_cosponsors_opposite/(numb_cosponsors+1)
replace pct_cosponsors_opposite=. if pct_cosponsors_opposite>100

compress

*egen tag_bill = tag(v2 HRnumber)
sort v2 HRnumber
bysort v2 HRnumber: gen tag_bill=_n

gen int decade = 1980 if v2<=102
replace decade=1990 if v2>=103 & v2<=107
replace decade=2000 if v2>=108

egen district_id = group(decade sponsor_state_abbrev sponsor_district)

/* Deletion, Daniele 2021-03-12
gen MVprim_female2=MVprim_female^2
gen MVprim_female3=MVprim_female^3
gen femaleXMVprim_female=sponsor_female*MVprim_female
gen femaleXMVprim_female2=sponsor_female*MVprim_female2
gen femaleXMVprim_female3=sponsor_female*MVprim_female3
gen safe=MV1_democrat>=0.2 & sponsor_party==100 | MV1_democrat<=-0.2 & sponsor_party==200 if MV1_democrat!=.
*/

sort  district_id v2 HRnumber
bysort district_id v2: gen counter=_n
foreach var of varlist tot_bills sponsor_female MV1_female MV1_democrat mixed_gender_ele /*
*/                     sponsor_party sponsor_democrat sponsor_rookie sponsor_tenure_run sponsor_age /*
*/                     leader ivycoll black occ0 occ1 occ2 occ3 occ4 borninstate {
	sort counter district_id v2
	bysort counter district_id: gen X=`var'[_n+1] if counter==1 & `var'[_n+1]!=.
	bysort district_id v2: egen `var'_l1=max(X)
	drop X
}
 
gen female_l1XMV1_female_l1=MV1_female_l1*sponsor_female_l1
gen absMV_l1=abs(MV1_democrat_l1)

local controls1 = "i.v2 "
local controls2 = "i.v2 MV1_female_l1 female_l1XMV1_female_l1 "
local controls3 = "i.v2 MV1_female_l1 female_l1XMV1_female_l1 "
local controls4 = "i.v2 "
local controls5 = "i.v2 "

local other_controls = "i.minor house_* sponsor_democrat_l1 sponsor_rookie_l1 sponsor_tenure_run_l1 sponsor_age_l1 leader_l1 ivycoll_l1 black_l1 occ0_l1 occ1_l1 occ2_l1 occ3_l1 occ4_l1 borninstate_l1 tot_bills NE MW WE pct_black pct_urban pct_for_born pct_age_over65 lninc lnpden"
local billchars = "i.minor house_*"
local indivchars = "sponsor_democrat_l1 sponsor_rookie_l1 sponsor_tenure_run_l1 sponsor_age_l1 leader_l1 ivycoll_l1 black_l1 occ0_l1 occ1_l1 occ2_l1 occ3_l1 occ4_l1 borninstate_l1 tot_bills"
local districtchars = "NE MW WE pct_black pct_urban pct_for_born pct_age_over65 lninc lnpden"

local if1 = "if tag_bill==1 & sponsor_female==0"
local if2 = "if sponsor_party_l1==100 & tag_bill==1 & sponsor_female==0"
local if3 = "if sponsor_party_l1==200 & tag_bill==1 & sponsor_female==0"

forvalues j=1/5 {
   forvalues k = 1/3 {
	  qui reg pct_cosponsors_opposite sponsor_female_l1 `controls2' `other_controls' `if`k'' & mixed_gender_election_l1==1, robust cluster(group_sponsor)
	  qui gen sample=e(sample)
	  
      di ""
	  di ""
	  di "j = ", `j', "k = ", `k'
	  di ""
	  di ""

   	  di "rdbwselect_2014 pct_cosponsors_opposite MV1_female_l1 `if`k'', c(0) kernel(uniform)"
	  rdbwselect_2014 pct_cosponsors_opposite MV1_female_l1 `if`k'', c(0) kernel(uniform)
	  local band = e(h_CCT)
	  	  
	  if `j'==1 {
	     di "reg pct_cosponsors_opposite sponsor_female_l1 `controls`j'' `other_controls' `if`k'', robust cluster(group_sponsor)"
	     reg pct_cosponsors_opposite sponsor_female_l1 `controls`j'' `other_controls' `if`k'', robust cluster(group_sponsor)   
	  }
	  else if `j'==2 {
	     di "reg pct_cosponsors_opposite sponsor_female_l1 `controls`j'' `if`k'' & sample==1 & abs(MV1_female_l1)<=`band', robust cluster(group_sponsor)"
	     reg pct_cosponsors_opposite sponsor_female_l1 `controls`j'' `if`k'' & sample==1 & abs(MV1_female_l1)<=`band', robust cluster(group_sponsor)   
	  }
	  else if `j'==3 {
         qui probit sponsor_female_l1 i.v2 `districtchars' `if`k'' & tag_sponsor==1 & abs(MV1_female_l1)<=`band'
         predict pscore if sample==1 
         gen wt = 1/pscore if sponsor_female_l1==1
         replace wt =1/(1-pscore) if sponsor_female_l1==0
	     di "reg pct_cosponsors_opposite sponsor_female_l1 `controls`j'' `billchars' [aw=wt] `if`k'' & sample==1 & abs(MV1_female_l1)<=`band', robust cluster(group_sponsor)"
         reg pct_cosponsors_opposite sponsor_female_l1 `controls`j'' `billchars' [aw=wt] `if`k'' & sample==1 & abs(MV1_female_l1)<=`band', robust cluster(group_sponsor)
         drop pscore wt
      }
	  else if `j'==4 {
         qui probit sponsor_female_l1 i.v2 `districtchars' absMV_l1 `if`k'' & tag_sponsor==1 
         predict pscore
         gen wt = 1/pscore if sponsor_female_l1==1
         replace wt =1/(1-pscore) if sponsor_female_l1==0
	     di "reg pct_cosponsors_opposite sponsor_female_l1 `controls`j'' `billchars' [aw=wt] `if`k'', robust cluster(group_sponsor)"
         reg pct_cosponsors_opposite sponsor_female_l1 `controls`j'' `billchars' [aw=wt] `if`k'', robust cluster(group_sponsor)
         drop pscore wt
      }
	  else if `j'==5 {
         qui probit sponsor_female_l1 i.v2 `districtchars' `indivchars'  absMV_l1 `if`k'' & tag_sponsor==1 
         predict pscore
         gen wt = 1/pscore if sponsor_female_l1==1
         replace wt =1/(1-pscore) if sponsor_female_l1==0
	     di "reg pct_cosponsors_opposite sponsor_female_l1 `controls`j'' `billchars' [aw=wt] `if`k'', robust cluster(group_sponsor)"
         reg pct_cosponsors_opposite sponsor_female_l1 `controls`j'' `billchars' [aw=wt] `if`k'', robust cluster(group_sponsor)
         drop pscore wt
      }

	  if `j'~=2 & `j'~=3 {
         scalar b_col`j'_row`k' = _b[sponsor_female_l1]
         scalar se_col`j'_row`k' = _se[sponsor_female_l1]
         scalar n_col`j'_row`k' = e(N)
		 sum tag_congressmen if tag_congressmen==1 & e(sample)
		 scalar ni_col`j'_row`k' = e(N_clust)
         scalar ob_col`j'_row`k' = .
	  }
	  else if `j'==2 | `j'==3 {
         scalar b_col`j'_row`k' = _b[sponsor_female_l1]
         scalar se_col`j'_row`k' = _se[sponsor_female_l1]
         scalar n_col`j'_row`k' = e(N)
		 sum tag_congressmen if tag_congressmen==1 & e(sample)
		 scalar ni_col`j'_row`k' = e(N_clust)
         scalar ob_col`j'_row`k' = round(`band')
	  }

      drop sample 
      
   }
}

preserve

* Display results

forvalues i = 1/5 {
   gen var`i' =.
}
gen str20 var6 = ""
		  
forvalues j=1/5 {
   forvalues k = 1/3 {
      replace var`j' = b_col`j'_row`k' if _n==6*(`k'-1)+1
      replace var`j' = se_col`j'_row`k' if _n==6*(`k'-1)+2
      replace var`j' = n_col`j'_row`k' if _n==6*(`k'-1)+3
      replace var`j' = ni_col`j'_row`k' if _n==6*(`k'-1)+4
      replace var`j' = ob_col`j'_row`k' if _n==6*(`k'-1)+5
   }
}   

keep var1-var6
keep if _n<=18

order var6 var1-var5

ren var6 sampletype
ren var1 OLS_all
ren var2 RD_bwidth
ren var3 RD_match_bw
ren var4 PS_match
ren var5 PS_match_indiv

foreach var of varlist OLS_all RD_bwidth RD_match_bw PS_match PS_match_indiv {
   gen str3 `var'_stars ="*" if abs(`var'/`var'[_n+1])>=1.645 & mod(_n,6)==1
   replace `var'_stars ="**" if abs(`var'/`var'[_n+1])>=1.96 & mod(_n,6)==1
   replace `var'_stars="***" if abs(`var'/`var'[_n+1])>=2.58 & mod(_n,6)==1
}

replace sampletype = "All" if _n>=1 & _n<=5
replace sampletype = "Democrats" if _n>=7 & _n<=11
replace sampletype = "Republicans" if _n>=13 & _n<=17

order sampletype OLS_all OLS_all_stars RD_bwidth RD_bwidth_stars RD_match_bw RD_match_bw_stars PS_match PS_match_stars PS_match_indiv PS_match_indiv_stars 
         export excel using "$Output/TableD2_Placebo_CosponsorsOpposite", firstrow(var) replace

restore

log close