| | --------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| | name: <unnamed> |
| | log: /Users/stefanogagliarducci/Dropbox/various/published/womenpart/EJ/3 replication package/Log/002_prepare_data_full.log |
| | log type: text |
| | opened on: 5 May 2021, 22:15:24 |
| |
|
| | . |
| | . |
| | . * Outline: |
| | . * (1) Use the clean data, get the data into shape for analysis |
| | . |
| | . * (1a) Use the Clean Cosponsor Data, add to it individual and district characteristics |
| | . use "$RawData/Cosponsors_Clean.dta", clear |
| |
|
| | . sort v2 state_abbrev district term_served |
| |
|
| | . merge v2 state_abbrev district term_served using "$RawData/IndividualCharacteristics_Clean.dta", |
| | keep(v2 state_abbrev state_icpsr district term_served name_clean v1_fix female party age tenure_run pus comc comr dwnom1 dwnom2 |
| | borninstate agestart privatesec anycoll namedcoll ivycoll statecoll anygrad jd mba phd military |
| | occ0 occ1 occ2 occ3 occ4 occ5 occ6 DSpndPct DDonaPct CQRating3 CQRating3_01 black native asian latino) |
| | (note: you are using old merge syntax; see [D] merge for new syntax) |
| | variables v2 state_abbrev district term_served do not uniquely identify observations in the master data |
| | (note: variable v2 was int, now long to accommodate using data's values) |
| | (note: variable district was byte, now double to accommodate using data's values) |
| | (note: variable term_served was byte, now float to accommodate using data's values) |
| |
|
| | . tab _merge |
| |
|
| | _merge | Freq. Percent Cum. |
| | ------------+----------------------------------- |
| | 1 | 22,493 2.13 2.13 |
| | 2 | 3 0.00 2.13 |
| | 3 | 1,035,492 97.87 100.00 |
| | ------------+----------------------------------- |
| | Total | 1,057,988 100.00 |
| |
|
| | . drop if _merge==2 |
| | (3 observations deleted) |
| |
|
| | . drop _merge |
| |
|
| | . |
| | . gen DSpndPct_miss=DSpndPct==. |
| |
|
| | . replace DSpndPct=50 if DSpndPct==. |
| | (208,766 real changes made) |
| |
|
| | . |
| | . sort v2 state_abbrev district term_served |
| |
|
| | . merge v2 state_abbrev district term_served using "$RawData/Committee_Clean.dta", |
| | keep(c_*) |
| | (note: you are using old merge syntax; see [D] merge for new syntax) |
| | variables v2 state_abbrev district term_served do not uniquely identify observations in the master data |
| |
|
| | . tab _merge |
| |
|
| | _merge | Freq. Percent Cum. |
| | ------------+----------------------------------- |
| | 1 | 15,803 1.49 1.49 |
| | 2 | 1 0.00 1.49 |
| | 3 | 1,042,182 98.51 100.00 |
| | ------------+----------------------------------- |
| | Total | 1,057,986 100.00 |
| |
|
| | . drop _merge |
| |
|
| | . |
| | . sort v2 state_abbrev district |
| |
|
| | . merge v2 state_abbrev district using "$RawData/DistrictCharacteristics_Clean.dta", |
| | keep(v2 state_abbrev district losing_candidate_clean_cqq losing_candidate_gender mixed_gender_election |
| | sample1 demshare1 repshare1 MV1_democrat tot_pop pct_age_over65 pct_black pct_for_born pct_urban med_inc_all lnpop lnarea lninc |
| | charisma_dem predicted_dem rep_incumbent_cqq dem_incumbent_cqq minor_incumbent_cqq lag_demshare1) |
| | (note: you are using old merge syntax; see [D] merge for new syntax) |
| | variables v2 state_abbrev district do not uniquely identify observations in the master data |
| |
|
| | . tab _merge |
| |
|
| | _merge | Freq. Percent Cum. |
| | ------------+----------------------------------- |
| | 1 | 21,611 2.04 2.04 |
| | 3 | 1,036,375 97.96 100.00 |
| | ------------+----------------------------------- |
| | Total | 1,057,986 100.00 |
| |
|
| | . drop _merge |
| |
|
| | . |
| | . foreach var of varlist state_abbrev state_icpsr district term_served name_clean v1_fix female party age tenure_run pus comc comr dwnom1 dwnom2 |
| | losing_candidate_clean_cqq losing_candidate_gender mixed_gender_election |
| | sample1 demshare1 repshare1 MV1_democrat charisma_dem predicted_dem |
| | tot_pop pct_age_over65 pct_black pct_for_born pct_urban med_inc_all lnpop lnarea lninc |
| | rep_incumbent_cqq dem_incumbent_cqq minor_incumbent_cqq lag_demshare1 |
| | borninstate agestart privatesec anycoll namedcoll ivycoll statecoll anygrad jd mba phd military |
| | occ0 occ1 occ2 occ3 occ4 occ5 occ6 DSpndPct DSpndPct_miss DDonaPct CQRating3 CQRating3_01 c_* black native asian latino { |
| | 2. ren `var' cosp_`var' |
| | 3. } |
| |
|
| | . |
| | . foreach name in "state_abbrev" "state_icpsr" "district" "term_served" "v1_fix" "age" "female" "tenure_run" "party" { |
| | 2. ren cosp_`name' cosponsor_`name' |
| | 3. } |
| |
|
| | . |
| | . egen cosponsor_v1_flex=group(cosponsor_v1_fix v2) |
| | (23105 missing values generated) |
| |
|
| | . |
| | . sort v2 HRnumber |
| |
|
| | . save "$IntermediateData/CosponsorsWithInfo_Clean_v2.dta", replace |
| | file /Users/stefanogagliarducci/Dropbox/various/published/womenpart/EJ/3 replication package/Data/IntermediateData/CosponsorsWithInfo_Clean_v2.dta saved |
| |
|
| | . |
| | . |
| | . |
| | . * (1b) Use the Clean Bill data, add to it individual and district characteristics |
| | . clear |
| |
|
| | . use "$RawData/BillCharacteristics_Clean.dta", clear |
| |
|
| | . sort v2 state_abbrev district term_served |
| |
|
| | . merge v2 state_abbrev district term_served using "$RawData/IndividualCharacteristics_Clean.dta", |
| | keep(v2 state_abbrev state_icpsr district term_served name_clean v1_fix female party age pus tenure_run comc comr dwnom1 dwnom2 |
| | borninstate agestart privatesec anycoll namedcoll ivycoll statecoll anygrad jd mba phd military |
| | occ0 occ1 occ2 occ3 occ4 occ5 occ6 DSpndPct DDonaPct CQRating3 CQRating3_01 black native asian latino) |
| | (note: you are using old merge syntax; see [D] merge for new syntax) |
| | variables v2 state_abbrev district term_served do not uniquely identify observations in the master data |
| | (note: variable v2 was int, now long to accommodate using data's values) |
| | (note: variable district was byte, now double to accommodate using data's values) |
| | (note: variable term_served was byte, now float to accommodate using data's values) |
| | (note: variable name_clean was str30, now str39 to accommodate using data's values) |
| |
|
| | . tab _merge |
| |
|
| | _merge | Freq. Percent Cum. |
| | ------------+----------------------------------- |
| | 1 | 1,031 1.61 1.61 |
| | 2 | 3 0.00 1.62 |
| | 3 | 62,990 98.38 100.00 |
| | ------------+----------------------------------- |
| | Total | 64,024 100.00 |
| |
|
| | . drop if _merge==2 |
| | (3 observations deleted) |
| |
|
| | . drop _merge |
| |
|
| | . |
| | . merge m:1 v2 state_abbrev district term_served using "$RawData/PrimaryElections.dta", keepusing(v2 state_abbrev district term_served mixed_gender_primary MVprim_fe |
| | > male) |
| |
|
| | Result # of obs. |
| | ----------------------------------------- |
| | not matched 1,034 |
| | from master 1,031 (_merge==1) |
| | from using 3 (_merge==2) |
| |
|
| | matched 62,990 (_merge==3) |
| | ----------------------------------------- |
| |
|
| | . compress |
| | variable v2 was long now int |
| | variable term_served was float now byte |
| | variable CQRating3_01 was float now byte |
| | variable black was float now byte |
| | variable native was float now byte |
| | variable asian was float now byte |
| | variable latino was float now byte |
| | variable district was double now byte |
| | variable CQRating3 was double now byte |
| | variable name_clean was str39 now str30 |
| | (2,753,032 bytes saved) |
| |
|
| | . |
| | . drop if _merge==2 |
| | (3 observations deleted) |
| |
|
| | . drop _merge |
| |
|
| | . |
| | . |
| | . gen DSpndPct_miss=DSpndPct==. |
| |
|
| | . replace DSpndPct=50 if DSpndPct==. |
| | (12,365 real changes made) |
| |
|
| | . |
| | . sort v2 state_abbrev district term_served |
| |
|
| | . merge v2 state_abbrev district term_served using "$RawData/Committee_Clean.dta", |
| | keep(c_*) |
| | (note: you are using old merge syntax; see [D] merge for new syntax) |
| | variables v2 state_abbrev district term_served do not uniquely identify observations in the master data |
| |
|
| | . tab _merge |
| |
|
| | _merge | Freq. Percent Cum. |
| | ------------+----------------------------------- |
| | 1 | 426 0.67 0.67 |
| | 2 | 1 0.00 0.67 |
| | 3 | 63,595 99.33 100.00 |
| | ------------+----------------------------------- |
| | Total | 64,022 100.00 |
| |
|
| | . drop _merge |
| |
|
| | . |
| | . sort v2 state_abbrev district |
| |
|
| | . merge v2 state_abbrev district using "$RawData/DistrictCharacteristics_Clean.dta", |
| | keep(v2 state_abbrev district sample1 republican democratic minor1_vote |
| | demshare1 repshare1 MV1_democrat mixed_gender_election |
| | losing_candidate_clean_cqq losing_candidate_gender |
| | tot_pop pct_age_over65 pct_black pct_for_born pct_urban med_inc_all lnpop lnarea lninc |
| | charisma_dem predicted_dem rep_incumbent_cqq dem_incumbent_cqq minor_incumbent_cqq lag_demshare1) |
| | (note: you are using old merge syntax; see [D] merge for new syntax) |
| | variables v2 state_abbrev district do not uniquely identify observations in the master data |
| | (label _merge already defined) |
| |
|
| | . tab _merge |
| |
|
| | _merge | Freq. Percent Cum. |
| | ------------+----------------------------------- |
| | 1 | 1,032 1.61 1.61 |
| | 3 | 62,990 98.39 100.00 |
| | ------------+----------------------------------- |
| | Total | 64,022 100.00 |
| |
|
| | . drop _merge |
| |
|
| | . |
| | . ******************************************************************************* |
| | . * IMPORTANT ADDITION (DANIELE, 2013/06/04): Keep only non-private bills |
| | . count |
| | 64,022 |
| |
|
| | . keep if private==0 |
| | (1,626 observations deleted) |
| |
|
| | . count |
| | 62,396 |
| |
|
| | . ******************************************************************************* |
| | . |
| | . |
| | . keep v2 HRnumber state_abbrev state_icpsr district term_served name_clean sponsor v1_fix intro_date |
| | numb_cosponsors numb_committees_master plaw_master lma_date iter_length mult commem house_* |
| | major minor passh passs plaw_cbp plawdate female party age pus tenure_run |
| | comc comr dwnom1 dwnom2 republican democratic minor1_vote losing_candidate_clean_cqq |
| | losing_candidate_gender mixed_gender_election sample1 demshare1 repshare1 MV1_democrat |
| | tot_pop pct_age_over65 pct_black pct_urban pct_for_born med_inc_all lnpop lnarea lninc |
| | charisma_dem predicted_dem rep_incumbent_cqq dem_incumbent_cqq minor_incumbent_cqq lag_demshare1 private |
| | borninstate agestart privatesec anycoll namedcoll ivycoll statecoll anygrad jd mba phd military |
| | occ0 occ1 occ2 occ3 occ4 occ5 occ6 DSpndPct DSpndPct_miss DDonaPct CQRating3 CQRating3_01 c_* |
| | black native asian latino mixed_gender_primary MVprim_female |
| |
|
| | . |
| | . |
| | . |
| | . sort v2 HRnumber |
| |
|
| | . merge v2 HRnumber using "$IntermediateData/CosponsorsWithInfo_Clean_v2.dta" |
| | (note: you are using old merge syntax; see [D] merge for new syntax) |
| | (note: variable v2 was int, now long to accommodate using data's values) |
| | variables v2 HRnumber do not uniquely identify observations in /Users/stefanogagliarducci/Dropbox/various/published/womenpart/EJ/3 replication |
| | package/Data/IntermediateData/CosponsorsWithInfo_Clean_v2.dta |
| |
|
| | . tab _merge |
| |
|
| | _merge | Freq. Percent Cum. |
| | ------------+----------------------------------- |
| | 2 | 2,019 0.19 0.19 |
| | 3 | 1,055,967 99.81 100.00 |
| | ------------+----------------------------------- |
| | Total | 1,057,986 100.00 |
| |
|
| | . drop _merge |
| |
|
| | . |
| | . gen int sponsor_party = party |
| | (8,664 missing values generated) |
| |
|
| | . gen byte sponsor_female = female |
| | (8,537 missing values generated) |
| |
|
| | . gen byte sponsor_tenure_run = tenure_run |
| | (8,537 missing values generated) |
| |
|
| | . gen byte sponsor_age = age |
| | (8,649 missing values generated) |
| |
|
| | . gen str2 sponsor_state_abbrev = state_abbrev |
| | (8,537 missing values generated) |
| |
|
| | . gen sponsor_state_icpsr = state_icpsr |
| | (8,537 missing values generated) |
| |
|
| | . gen int sponsor_district = district |
| | (8,537 missing values generated) |
| |
|
| | . gen byte sponsor_term_served = term_served |
| | (8,537 missing values generated) |
| |
|
| | . gen sponsor_v1_fix = v1_fix |
| | (8,702 missing values generated) |
| |
|
| | . |
| | . |
| | . |
| | . * Identify bills cosponsored by the opposite party |
| | . gen byte cosponsor_opposite_party = (cosponsor_party==100 & sponsor_party==200) | (cosponsor_party==200 & sponsor_party==100) if sponsor_party~=. & cosponsor_party |
| | > ~=. |
| | (29,028 missing values generated) |
| |
|
| | . egen numb_cosponsors_opposite = sum(cosponsor_opposite_party), by(v2 HRnumber) |
| |
|
| | . gen pct_cosponsors_opposite = numb_cosponsors_opposite/(numb_cosponsors) |
| | (28,056 missing values generated) |
| |
|
| | . |
| | . egen tag_bill = tag(v2 HRnumber) |
| |
|
| | . |
| | . * calculate number of bills cosponsored |
| | . egen nbills_cosponsored = count(HRnumber), by(v2 cosponsor_state_abbrev cosponsor_district cosponsor_term_served) |
| |
|
| | . |
| | . egen nbills_cosponsored_opposite = sum(cosponsor_opposite_party), by(v2 cosponsor_state_abbrev cosponsor_district cosponsor_term_served) |
| |
|
| | . gen pctbills_cosponsored_opposite = nbills_cosponsored_opposite/(nbills_cosponsored) |
| | (76 missing values generated) |
| |
|
| | . |
| | . |
| | . egen tag_cosponsor = tag(v2 cosponsor_state_abbrev cosponsor_district cosponsor_term_served) |
| |
|
| | . egen tag_sponsor = tag(v2 sponsor_state_abbrev sponsor_district sponsor_term_served) |
| |
|
| | . |
| | . |
| | . compress |
| | variable v2 was long now int |
| | variable DSpndPct_miss was float now byte |
| | variable cosponsor_term_served was float now byte |
| | variable cosp_CQRating3_01 was float now byte |
| | variable cosp_black was float now byte |
| | variable cosp_native was float now byte |
| | variable cosp_asian was float now byte |
| | variable cosp_latino was float now byte |
| | variable cosp_DSpndPct_miss was float now byte |
| | variable cosponsor_v1_flex was float now int |
| | variable sponsor_state_icpsr was float now byte |
| | variable sponsor_district was int now byte |
| | variable numb_cosponsors_opposite was float now int |
| | variable nbills_cosponsored was float now int |
| | variable nbills_cosponsored_opposite was float now int |
| | variable cosponsor_district was double now byte |
| | variable cosp_CQRating3 was double now byte |
| | variable cosp_name_clean was str39 now str30 |
| | (64,537,146 bytes saved) |
| |
|
| | . |
| | . |
| | . |
| | . ********************************************************************************************************* |
| | . |
| | . * (1) Create the RD forcing variable for sponsors and cosponsors |
| | . |
| | . |
| | . * (1a) Create RD forcing variables for sponsors... |
| | . gen MV1_female = MV1_democrat if sponsor_party==100 & sponsor_female==1 & mixed_gender_election==1 |
| | (976,107 missing values generated) |
| |
|
| | . replace MV1_female = -MV1_democrat if sponsor_party==200 & sponsor_female==1 & mixed_gender_election==1 |
| | (34,512 real changes made) |
| |
|
| | . replace MV1_female = MV1_democrat if sponsor_party==200 & sponsor_female==0 & mixed_gender_election==1 |
| | (61,535 real changes made) |
| |
|
| | . replace MV1_female = -MV1_democrat if sponsor_party==100 & sponsor_female==0 & mixed_gender_election==1 |
| | (35,070 real changes made) |
| |
|
| | . |
| | . |
| | . |
| | . |
| | . *****UPDATE, FEBRUARY 2014 |
| | . gen charisma_winner = charisma_dem if sponsor_party==100 |
| | (539,472 missing values generated) |
| |
|
| | . replace charisma_winner = -charisma_dem if sponsor_party==200 |
| | (429,341 real changes made) |
| |
|
| | . |
| | . gen predicted_winner = predicted_dem if sponsor_party==100 |
| | (539,472 missing values generated) |
| |
|
| | . replace predicted_winner = 1-predicted_dem if sponsor_party==200 |
| | (429,341 real changes made) |
| |
|
| | . |
| | . *************************************************** |
| | . |
| | . |
| | . |
| | . |
| | . drop if sponsor=="Rep Herseth, Stephanie" | cosponsor=="Rep Herseth, Stephanie" |
| | (1,060 observations deleted) |
| |
|
| | . |
| | . replace MV1_female = 100*MV1_female |
| | (212,265 real changes made) |
| |
|
| | . label var MV1_female "Margin victory female sponsor" |
| |
|
| | . |
| | . * interactions between gender dummy and RD forcing variable |
| | . gen femaleXMV1_female=sponsor_female*MV1_female |
| | (844,661 missing values generated) |
| |
|
| | . forvalues j = 2/4{ |
| | 2. gen MV1_female__`j' = MV1_female^`j' |
| | 3. gen femaleXMV1_female__`j' = sponsor_female*MV1_female__`j' |
| | 4. } |
| | (844,661 missing values generated) |
| | (844,661 missing values generated) |
| | (844,661 missing values generated) |
| | (844,661 missing values generated) |
| | (844,661 missing values generated) |
| | (844,661 missing values generated) |
| |
|
| | . |
| | . |
| | . * (1b) Create RD forcing variables for cosponsors... |
| | . gen cosp_MV1_female = cosp_MV1_democrat if cosponsor_party==100 & cosponsor_female==1 & cosp_mixed_gender_election==1 |
| | (977,135 missing values generated) |
| |
|
| | . replace cosp_MV1_female = -cosp_MV1_democrat if cosponsor_party==200 & cosponsor_female==1 & cosp_mixed_gender_election==1 |
| | (26,772 real changes made) |
| |
|
| | . replace cosp_MV1_female = cosp_MV1_democrat if cosponsor_party==200 & cosponsor_female==0 & cosp_mixed_gender_election==1 |
| | (60,172 real changes made) |
| |
|
| | . replace cosp_MV1_female = -cosp_MV1_democrat if cosponsor_party==100 & cosponsor_female==0 & cosp_mixed_gender_election==1 |
| | (43,701 real changes made) |
| |
|
| | . |
| | . replace cosp_MV1_female = 100*cosp_MV1_female |
| | (210,436 real changes made) |
| |
|
| | . label var cosp_MV1_female "Margin victory female cosponsor" |
| |
|
| | . |
| | . *****UPDATE, FEBRUARY 2014 |
| | . gen cosp_charisma_winner = cosp_charisma_dem if cosponsor_party==100 |
| | (495,602 missing values generated) |
| |
|
| | . replace cosp_charisma_winner = -cosp_charisma_dem if cosponsor_party==200 |
| | (375,333 real changes made) |
| |
|
| | . |
| | . gen cosp_predicted_winner = cosp_predicted_dem if cosponsor_party==100 |
| | (495,602 missing values generated) |
| |
|
| | . replace cosp_predicted_winner = 1-cosp_predicted_dem if cosponsor_party==200 |
| | (375,333 real changes made) |
| |
|
| | . |
| | . *************************************************** |
| | . |
| | . |
| | . |
| | . |
| | . * interactions between gender dummy and RD forcing variable |
| | . gen femaleXcosp_MV1_female=cosponsor_female*cosp_MV1_female |
| | (846,490 missing values generated) |
| |
|
| | . forvalues j = 2/4 { |
| | 2. gen cosp_MV1_female__`j' = cosp_MV1_female^`j' |
| | 3. gen femaleXcosp_MV1_female__`j' = cosponsor_female*cosp_MV1_female__`j' |
| | 4. } |
| | (846,490 missing values generated) |
| | (846,490 missing values generated) |
| | (846,490 missing values generated) |
| | (846,490 missing values generated) |
| | (846,490 missing values generated) |
| | (846,490 missing values generated) |
| |
|
| | . |
| | . * discretize running variable |
| | . gen MV1_female_bins = int(MV1_female)+0.5 if MV1_female>0 & MV1_female~=. |
| | (941,200 missing values generated) |
| |
|
| | . replace MV1_female_bins = int(MV1_female)-0.5 if MV1_female<0 & MV1_female~=. |
| | (96,539 real changes made) |
| |
|
| | . |
| | . gen MV1_female_bins2 = 2*int(MV1_female/2)+1 if MV1_female>0 & MV1_female~=. |
| | (941,200 missing values generated) |
| |
|
| | . replace MV1_female_bins2 = 2*int(MV1_female/2)-1 if MV1_female<0 & MV1_female~=. |
| | (96,539 real changes made) |
| |
|
| | . |
| | . gen cosp_MV1_female_bins = int(cosp_MV1_female)+.5 if cosp_MV1_female>0 & cosp_MV1_female~=. |
| | (950,363 missing values generated) |
| |
|
| | . replace cosp_MV1_female_bins = int(cosp_MV1_female)-0.5 if cosp_MV1_female<0 & cosp_MV1_female~=. |
| | (103,873 real changes made) |
| |
|
| | . |
| | . gen cosp_MV1_female_bins2 = 2*int(cosp_MV1_female/2)+1 if cosp_MV1_female>0 & cosp_MV1_female~=. |
| | (950,363 missing values generated) |
| |
|
| | . replace cosp_MV1_female_bins2 = 2*int(cosp_MV1_female/2)-1 if cosp_MV1_female<0 & cosp_MV1_female~=. |
| | (103,873 real changes made) |
| |
|
| | . |
| | . * these two variables may come in handy later |
| | . gen byte sponsor_democrat = sponsor_party==100 |
| |
|
| | . gen MV1_democratXsponsor_democrat = MV1_democrat*sponsor_democrat |
| | (108,617 missing values generated) |
| |
|
| | . |
| | . |
| | . * NEW OUTCOMES * |
| | . |
| | . * identify bills cosponsored by women, and by women of the opposite party |
| | . gen byte cosponsor_fem = (cosponsor_female==1) if cosponsor_female~=. |
| | (22,496 missing values generated) |
| |
|
| | . egen numb_cosponsors_fem = sum(cosponsor_fem), by(v2 HRnumber) |
| |
|
| | . gen pct_cosponsors_fem = numb_cosponsors_fem/(numb_cosponsors) |
| | (28,037 missing values generated) |
| |
|
| | . |
| | . gen byte cosponsor_fem_opposite = (cosponsor_party==100 & sponsor_party==200 & cosponsor_female==1) | (cosponsor_party==200 & sponsor_party==100 & cosponsor_female |
| | > ==1) if sponsor_party~=. & cosponsor_party~=. & cosponsor_female~=. |
| | (29,009 missing values generated) |
| |
|
| | . egen numb_cosponsors_fem_opposite = sum(cosponsor_fem_opposite), by(v2 HRnumber) |
| |
|
| | . gen pct_cosponsors_fem_opposite = numb_cosponsors_fem_opposite/(numb_cosponsors) |
| | (28,037 missing values generated) |
| |
|
| | . |
| | . gen byte cosponsor_male_sp = (cosponsor_party==100 & sponsor_party==100 & cosponsor_female==0) | (cosponsor_party==200 & sponsor_party==200 & cosponsor_female==0) |
| | > if sponsor_party~=. & cosponsor_party~=. & cosponsor_female~=. |
| | (29,009 missing values generated) |
| |
|
| | . egen numb_cosponsors_male_sp = sum(cosponsor_male_sp), by(v2 HRnumber) |
| |
|
| | . gen pct_cosponsors_male_sp = numb_cosponsors_male_sp/(numb_cosponsors) |
| | (28,037 missing values generated) |
| |
|
| | . |
| | . * identify cosponsored bills by women, and women of opposite party |
| | . egen nbills_cosponsored_fem = sum(sponsor_female), by(v2 cosponsor_state_abbrev cosponsor_district cosponsor_term_served) |
| |
|
| | . gen pctbills_cosponsored_fem = nbills_cosponsored_fem/(nbills_cosponsored) |
| | (76 missing values generated) |
| |
|
| | . |
| | . gen byte sponsor_female_opposite = (cosponsor_party==100 & sponsor_party==200 & sponsor_female==1) | (cosponsor_party==200 & sponsor_party==100 & sponsor_female== |
| | > 1) if sponsor_party~=. & cosponsor_party~=. & sponsor_female~=. |
| | (29,009 missing values generated) |
| |
|
| | . egen nbills_cosponsored_fem_opp = sum(sponsor_female_opposite), by(v2 cosponsor_state_abbrev cosponsor_district cosponsor_term_served) |
| |
|
| | . gen pctbills_cosponsored_fem_opp = nbills_cosponsored_fem_opp/(nbills_cosponsored) |
| | (76 missing values generated) |
| |
|
| | . |
| | . * identify variance/sd/distance in DW among cosponsors |
| | . egen sd_cosp_dwnom1_nospons = sd(cosp_dwnom1), by(v2 HRnumber) |
| | (27939 missing values generated) |
| |
|
| | . replace sd_cosp_dwnom1_nospons = . if numb_cosponsors==0 |
| | (166 real changes made, 166 to missing) |
| |
|
| | . gen var_cosp_dwnom1_nospons = sd_cosp_dwnom1_nospons^2 |
| | (28,105 missing values generated) |
| |
|
| | . replace var_cosp_dwnom1_nospons = . if numb_cosponsors==0 |
| | (0 real changes made) |
| |
|
| | . egen m_cosp_dwnom1_nospons=mean(cosp_dwnom1), by(v2 HRnumber) |
| | (21685 missing values generated) |
| |
|
| | . replace m_cosp_dwnom1_nospons = . if numb_cosponsors==0 |
| | (166 real changes made, 166 to missing) |
| |
|
| | . gen a_cosp_dwnom1=abs(cosp_dwnom1) |
| | (36,648 missing values generated) |
| |
|
| | . egen ma_cosp_dwnom1_nospons=mean(a_cosp_dwnom1), by(v2 HRnumber) |
| | (21685 missing values generated) |
| |
|
| | . replace ma_cosp_dwnom1_nospons = . if numb_cosponsors==0 |
| | (166 real changes made, 166 to missing) |
| |
|
| | . gen d_cosp_dwnom1=cosp_dwnom1-dwnom1 |
| | (53,124 missing values generated) |
| |
|
| | . egen md_cosp_dwnom1_nospons=mean(d_cosp_dwnom1), by(v2 HRnumber) |
| | (38498 missing values generated) |
| |
|
| | . replace md_cosp_dwnom1_nospons = . if numb_cosponsors==0 |
| | (166 real changes made, 166 to missing) |
| |
|
| | . gen ad_cosp_dwnom1=abs(cosp_dwnom1-dwnom1) |
| | (53,124 missing values generated) |
| |
|
| | . egen mad_cosp_dwnom1_nospons=mean(d_cosp_dwnom1), by(v2 HRnumber) |
| | (38498 missing values generated) |
| |
|
| | . replace mad_cosp_dwnom1_nospons = . if numb_cosponsors==0 |
| | (166 real changes made, 166 to missing) |
| |
|
| | . drop a_cosp_dwnom1 d_cosp_dwnom1 ad_cosp_dwnom1 |
| |
|
| | . |
| | . expand 2, gen(new) |
| | (1,056,926 observations created) |
| |
|
| | . bysort v2 HRnumber new: gen counter=_n |
| |
|
| | . drop if new==1 & counter!=1 |
| | (993,020 observations deleted) |
| |
|
| | . replace cosp_dwnom1=dwnom1 if new==1 |
| | (61,460 real changes made, 789 to missing) |
| |
|
| | . egen sd_cosp_dwnom1_spons = sd(cosp_dwnom1), by(v2 HRnumber) |
| | (43640 missing values generated) |
| |
|
| | . replace sd_cosp_dwnom1_spons = 0 if numb_cosponsors==0 |
| | (38,840 real changes made) |
| |
|
| | . gen var_cosp_dwnom1_spons = sd_cosp_dwnom1_spons^2 |
| | (4,970 missing values generated) |
| |
|
| | . replace var_cosp_dwnom1_spons = 0 if numb_cosponsors==0 |
| | (0 real changes made) |
| |
|
| | . egen m_cosp_dwnom1_spons=mean(cosp_dwnom1), by(v2 HRnumber) |
| | (4752 missing values generated) |
| |
|
| | . *replace m_cosp_dwnom1_spons = . if numb_cosponsors==0 |
| | . gen a_cosp_dwnom1=abs(cosp_dwnom1) |
| | (39,821 missing values generated) |
| |
|
| | . egen ma_cosp_dwnom1_spons=mean(a_cosp_dwnom1), by(v2 HRnumber) |
| | (4752 missing values generated) |
| |
|
| | . *replace ma_cosp_dwnom1_spons = . if numb_cosponsors==0 |
| | . gen d_cosp_dwnom1=cosp_dwnom1-dwnom1 |
| | (56,297 missing values generated) |
| |
|
| | . egen md_cosp_dwnom1_spons=mean(d_cosp_dwnom1), by(v2 HRnumber) |
| | (22370 missing values generated) |
| |
|
| | . replace md_cosp_dwnom1_spons = 0 if numb_cosponsors==0 |
| | (598 real changes made) |
| |
|
| | . gen ad_cosp_dwnom1=abs(cosp_dwnom1-dwnom1) |
| | (56,297 missing values generated) |
| |
|
| | . egen mad_cosp_dwnom1_spons=mean(d_cosp_dwnom1), by(v2 HRnumber) |
| | (22370 missing values generated) |
| |
|
| | . replace mad_cosp_dwnom1_spons = 0 if numb_cosponsors==0 |
| | (598 real changes made) |
| |
|
| | . drop a_cosp_dwnom1 d_cosp_dwnom1 ad_cosp_dwnom1 |
| |
|
| | . |
| | . drop if new==1 |
| | (63,906 observations deleted) |
| |
|
| | . drop new counter |
| |
|
| | . |
| | . * add network measures |
| | . merge m:1 v2 cosponsor_state_abbrev cosponsor_district cosponsor_term_served using "$RawData/CentralityMeasures_all.dta", keep(master matched) keepusing(degree clo |
| | > seness betweenness eigenvector closeness_w betweenness_w eigenvector_w) |
| |
|
| | Result # of obs. |
| | ----------------------------------------- |
| | not matched 21,592 |
| | from master 21,592 (_merge==1) |
| | from using 0 (_merge==2) |
| |
|
| | matched 1,035,334 (_merge==3) |
| | ----------------------------------------- |
| |
|
| | . drop _m |
| |
|
| | . foreach var of varlist degree closeness betweenness eigenvector closeness_w betweenness_w eigenvector_w { |
| | 2. rename `var' cosponsor_`var' |
| | 3. egen m_`var'_nospons = mean(cosponsor_`var'), by(v2 HRnumber) |
| | 4. replace m_`var'_nospons=. if numb_cosponsors==0 |
| | 5. } |
| | (21664 missing values generated) |
| | (166 real changes made, 166 to missing) |
| | (21664 missing values generated) |
| | (166 real changes made, 166 to missing) |
| | (21664 missing values generated) |
| | (166 real changes made, 166 to missing) |
| | (21664 missing values generated) |
| | (166 real changes made, 166 to missing) |
| | (21664 missing values generated) |
| | (166 real changes made, 166 to missing) |
| | (21664 missing values generated) |
| | (166 real changes made, 166 to missing) |
| | (21664 missing values generated) |
| | (166 real changes made, 166 to missing) |
| |
|
| | . |
| | . expand 2, gen(new) |
| | (1,056,926 observations created) |
| |
|
| | . bysort v2 HRnumber new: gen counter=_n |
| |
|
| | . drop if new==1 & counter!=1 |
| | (993,020 observations deleted) |
| |
|
| | . merge m:1 v2 sponsor_state_abbrev sponsor_district sponsor_term_served using "$RawData/CentralityMeasures_all.dta", keep(master matched) keepusing(degree closeness |
| | > betweenness eigenvector closeness_w betweenness_w eigenvector_w) |
| |
|
| | Result # of obs. |
| | ----------------------------------------- |
| | not matched 11,108 |
| | from master 11,108 (_merge==1) |
| | from using 0 (_merge==2) |
| |
|
| | matched 1,109,724 (_merge==3) |
| | ----------------------------------------- |
| |
|
| | . drop _m |
| |
|
| | . foreach var of varlist degree closeness betweenness eigenvector closeness_w betweenness_w eigenvector_w { |
| | 2. replace cosponsor_`var'=`var' if new==1 |
| | 3. egen m_`var'_spons = mean(cosponsor_`var'), by(v2 HRnumber) |
| | 4. * replace m_`var'_spons=. if numb_cosponsors==0 |
| | . drop `var' cosponsor_`var' |
| | 5. } |
| | (61,589 real changes made, 414 to missing) |
| | (4382 missing values generated) |
| | (61,597 real changes made, 414 to missing) |
| | (4382 missing values generated) |
| | (61,747 real changes made, 414 to missing) |
| | (4382 missing values generated) |
| | (61,747 real changes made, 414 to missing) |
| | (4382 missing values generated) |
| | (61,247 real changes made, 414 to missing) |
| | (4382 missing values generated) |
| | (61,747 real changes made, 414 to missing) |
| | (4382 missing values generated) |
| | (61,747 real changes made, 414 to missing) |
| | (4382 missing values generated) |
| |
|
| | . |
| | . drop if new==1 |
| | (63,906 observations deleted) |
| |
|
| | . drop new counter |
| |
|
| | . |
| | . |
| | . |
| | . **************************************************************************************** |
| | . ***** UPDATE, FEBRUARY 2014: Create some additional variables measuring the characteristics of cosponsors |
| | . |
| | . * identify whether cosponsor is committee chair or committee ranking members |
| | . gen byte cosponsor_leader = (cosp_comc==1) | (cosp_comr==1) if cosp_comc~=. & cosp_comr~=. |
| | (29,033 missing values generated) |
| |
|
| | . egen numb_cosponsors_leader = sum(cosponsor_leader), by(v2 HRnumber) |
| |
|
| | . gen pct_cosponsors_leader = numb_cosponsors_leader/(numb_cosponsors) |
| | (28,037 missing values generated) |
| |
|
| | . |
| | . * Calculate average tenure and age of cosponsors, pct of cosponsors that are rookies |
| | . egen avgtenure_cosponsors = mean(cosponsor_tenure_run), by(v2 HRnumber) |
| | --Break-- |
| | r(1); |
| |
|
| | end of do-file |
| | --Break-- |
| | r(1); |
| |
|
| | end of do-file |
| |
|
| | --Break-- |
| | r(1); |
| |
|
| | . do "/Users/stefanogagliarducci/Dropbox/various/published/womenpart/EJ/3 replication package/Dofiles/Table6.do" |
| |
|
| | . clear |
| |
|
| | . set mem 500m |
| | set memory ignored. |
| | Memory no longer needs to be set in modern Statas; memory adjustments are performed on the fly automatically. |
| |
|
| | . set more off |
| |
|
| | . set logtype text |
| |
|
| | . set matsize 3000 |
| |
|
| | . |
| | . cap log close |
| |
|
