{smcl}
{com}{sf}{ul off}{txt}
{com}. 
. **** REPLICATION OF FIGURE C2 ****
. 
. clear all
{res}{txt}
{com}. set mem 2g
{txt}{bf:set memory} ignored.
{p 4 4 2}
Memory no longer
needs to be set in modern Statas;
memory adjustments are performed on the fly
automatically.
{p_end}

{com}. set more off
{txt}
{com}. 
. /*      
>         OUTLINE
>         1. REGRESSIONS
>         2. GRAPH
> */
. 
. **************************
. ***** 1. REGRESSIONS *****
. **************************
. 
. // Import data
. 
. use $data\EEREV-D-21-00004_Data_Survey_Compo.dta, clear
{txt}
{com}. 
. drop if dep==57 | dep==67 | dep==68
{txt}(476 observations deleted)

{com}. 
. // Get empty sheet to export data
. 
. capture erase "$results\abst60.txt"
{txt}
{com}. capture erase "$results\abst70.txt"
{txt}
{com}. capture erase "$results\rrw70.txt"
{txt}
{com}. capture erase "$results\abst80.txt"
{txt}
{com}. capture erase "$results\rrw80.txt"
{txt}
{com}. 
. // Elections in the 60s
. 
. foreach var in vote_l1958 vote_r1958 vote_l1962r1 vote_l1962r2 vote_r1962{c -(}
{txt}  2{com}.         reghdfe `var' i.age i.sexe, a(revenu ppi_rec dep agglo) cluster(dep)
{txt}  3{com}.         estimates store v60`var'
{txt}  4{com}.         qui sum `var' if e(sample)
{txt}  5{com}.         scalar mean_y=r(mean)
{txt}  6{com}.         estadd scalar mean_y
{txt}  7{com}.         outreg2 using "$results\abst60", nocons dec(3) level(95)
{txt}  8{com}. {c )-}
{res}{txt}(dropped 1 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 11 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}     1,119
{txt}Absorbing 4 HDFE groups{col 51}F({res}   4{txt},{res}     64{txt}){col 67}= {res}     23.89
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.1628
{txt}{col 51}Adj R-squared{col 67}= {res}    0.0913
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0663
{txt}{col 1}Number of clusters ({res}dep{txt}) {col 30}= {res}        65{txt}{col 51}Root MSE{col 67}= {res}    0.3841

{txt}{ralign 96:(Std. err. adjusted for {res:65} clusters in dep)}
{hline 31}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 32}{c |}{col 44}    Robust
{col 1}                    vote_l1958{col 32}{c |} Coefficient{col 44}  std. err.{col 56}      t{col 64}   P>|t|{col 72}     [95% con{col 85}f. interval]
{hline 31}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 27}age {c |}
{space 3}\\ Aged 35 to 49 years old  {c |}{col 32}{res}{space 2}-.1523487{col 44}{space 2} .0358042{col 55}{space 1}   -4.26{col 64}{space 3}0.000{col 72}{space 4}-.2238759{col 85}{space 3}-.0808216
{txt}[0.3em] -- 50 to 64 years old  {c |}{col 32}{res}{space 2}-.1847171{col 44}{space 2} .0337394{col 55}{space 1}   -5.47{col 64}{space 3}0.000{col 72}{space 4}-.2521192{col 85}{space 3} -.117315
{txt}{space 6}[0.3em] -- 65 and above  {c |}{col 32}{res}{space 2} -.242808{col 44}{space 2} .0359929{col 55}{space 1}   -6.75{col 64}{space 3}0.000{col 72}{space 4}-.3147122{col 85}{space 3}-.1709038
{txt}{space 30} {c |}
{space 26}sexe {c |}
{space 15}[0.3em] Female  {c |}{col 32}{res}{space 2} .0870161{col 44}{space 2} .0294398{col 55}{space 1}    2.96{col 64}{space 3}0.004{col 72}{space 4} .0282033{col 85}{space 3} .1458288
{txt}{space 25}_cons {c |}{col 32}{res}{space 2} .2901493{col 44}{space 2} .0256582{col 55}{space 1}   11.31{col 64}{space 3}0.000{col 72}{space 4} .2388912{col 85}{space 3} .3414075
{txt}{hline 31}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{res}{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}      revenu{col 14}{c |}{space 1}       11{col 27}{space 1}        0{col 39}{result}{space 1}       11{col 53}{text} {col 54}{c |}
{res}{col 1}{text}     ppi_rec{col 14}{c |}{space 1}        6{col 27}{space 1}        1{col 39}{result}{space 1}        5{col 53}{text} {col 54}{c |}
{res}{col 1}{text}         dep{col 14}{c |}{space 1}       65{col 27}{space 1}       65{col 39}{result}{space 1}        0{col 53}{text}*{col 54}{c |}
{res}{col 1}{text}       agglo{col 14}{c |}{space 1}        5{col 27}{space 1}        1{col 39}{result}{space 1}        4{col 53}{text}?{col 54}{c |}
{res}{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
? = number of redundant parameters may be higher
* = FE nested within cluster; treated as redundant for DoF computation
{res}
{txt}added scalar:
             e(mean_y) =  {res}.20375335
{browse `"D:\Dropbox\SVLACHOS\Research\Malgre_nous\Replication_files\Results"' :dir}{com} : {txt}{stata `"seeout using "D:\Dropbox\SVLACHOS\Research\Malgre_nous\Replication_files\Results\abst60.txt""':seeout}
{res}{txt}(dropped 2 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 10 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}     1,038
{txt}Absorbing 4 HDFE groups{col 51}F({res}   4{txt},{res}     63{txt}){col 67}= {res}      0.95
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.4401
{txt}{col 51}R-squared{col 67}= {res}    0.0957
{txt}{col 51}Adj R-squared{col 67}= {res}    0.0129
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0067
{txt}{col 1}Number of clusters ({res}dep{txt}) {col 30}= {res}        64{txt}{col 51}Root MSE{col 67}= {res}    0.2589

{txt}{ralign 96:(Std. err. adjusted for {res:64} clusters in dep)}
{hline 31}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 32}{c |}{col 44}    Robust
{col 1}                    vote_r1958{col 32}{c |} Coefficient{col 44}  std. err.{col 56}      t{col 64}   P>|t|{col 72}     [95% con{col 85}f. interval]
{hline 31}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 27}age {c |}
{space 3}\\ Aged 35 to 49 years old  {c |}{col 32}{res}{space 2} .0004648{col 44}{space 2} .0201894{col 55}{space 1}    0.02{col 64}{space 3}0.982{col 72}{space 4}-.0398804{col 85}{space 3} .0408101
{txt}[0.3em] -- 50 to 64 years old  {c |}{col 32}{res}{space 2}-.0030095{col 44}{space 2} .0235312{col 55}{space 1}   -0.13{col 64}{space 3}0.899{col 72}{space 4} -.050033{col 85}{space 3} .0440139
{txt}{space 6}[0.3em] -- 65 and above  {c |}{col 32}{res}{space 2}-.0201524{col 44}{space 2} .0242788{col 55}{space 1}   -0.83{col 64}{space 3}0.410{col 72}{space 4}-.0686697{col 85}{space 3} .0283649
{txt}{space 30} {c |}
{space 26}sexe {c |}
{space 15}[0.3em] Female  {c |}{col 32}{res}{space 2} .0408243{col 44}{space 2}  .030761{col 55}{space 1}    1.33{col 64}{space 3}0.189{col 72}{space 4}-.0206467{col 85}{space 3} .1022953
{txt}{space 25}_cons {c |}{col 32}{res}{space 2} .0582459{col 44}{space 2} .0210141{col 55}{space 1}    2.77{col 64}{space 3}0.007{col 72}{space 4} .0162526{col 85}{space 3} .1002392
{txt}{hline 31}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{res}{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}      revenu{col 14}{c |}{space 1}       11{col 27}{space 1}        0{col 39}{result}{space 1}       11{col 53}{text} {col 54}{c |}
{res}{col 1}{text}     ppi_rec{col 14}{c |}{space 1}        6{col 27}{space 1}        1{col 39}{result}{space 1}        5{col 53}{text} {col 54}{c |}
{res}{col 1}{text}         dep{col 14}{c |}{space 1}       64{col 27}{space 1}       64{col 39}{result}{space 1}        0{col 53}{text}*{col 54}{c |}
{res}{col 1}{text}       agglo{col 14}{c |}{space 1}        5{col 27}{space 1}        1{col 39}{result}{space 1}        4{col 53}{text}?{col 54}{c |}
{res}{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
? = number of redundant parameters may be higher
* = FE nested within cluster; treated as redundant for DoF computation
{res}
{txt}added scalar:
             e(mean_y) =  {res}.07321773
{browse `"D:\Dropbox\SVLACHOS\Research\Malgre_nous\Replication_files\Results"' :dir}{com} : {txt}{stata `"seeout using "D:\Dropbox\SVLACHOS\Research\Malgre_nous\Replication_files\Results\abst60.txt""':seeout}
{res}{txt}(dropped 1 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 10 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}     1,261
{txt}Absorbing 4 HDFE groups{col 51}F({res}   4{txt},{res}     64{txt}){col 67}= {res}     13.64
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.1235
{txt}{col 51}Adj R-squared{col 67}= {res}    0.0577
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0302
{txt}{col 1}Number of clusters ({res}dep{txt}) {col 30}= {res}        65{txt}{col 51}Root MSE{col 67}= {res}    0.3800

{txt}{ralign 96:(Std. err. adjusted for {res:65} clusters in dep)}
{hline 31}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 32}{c |}{col 44}    Robust
{col 1}                  vote_l1962r1{col 32}{c |} Coefficient{col 44}  std. err.{col 56}      t{col 64}   P>|t|{col 72}     [95% con{col 85}f. interval]
{hline 31}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 27}age {c |}
{space 3}\\ Aged 35 to 49 years old  {c |}{col 32}{res}{space 2}-.0420396{col 44}{space 2} .0227697{col 55}{space 1}   -1.85{col 64}{space 3}0.069{col 72}{space 4}-.0875272{col 85}{space 3} .0034481
{txt}[0.3em] -- 50 to 64 years old  {c |}{col 32}{res}{space 2}-.0856277{col 44}{space 2} .0334417{col 55}{space 1}   -2.56{col 64}{space 3}0.013{col 72}{space 4}-.1524353{col 85}{space 3}-.0188202
{txt}{space 6}[0.3em] -- 65 and above  {c |}{col 32}{res}{space 2}-.0569442{col 44}{space 2}  .037878{col 55}{space 1}   -1.50{col 64}{space 3}0.138{col 72}{space 4}-.1326141{col 85}{space 3} .0187257
{txt}{space 30} {c |}
{space 26}sexe {c |}
{space 15}[0.3em] Female  {c |}{col 32}{res}{space 2} .1199734{col 44}{space 2} .0251936{col 55}{space 1}    4.76{col 64}{space 3}0.000{col 72}{space 4} .0696434{col 85}{space 3} .1703034
{txt}{space 25}_cons {c |}{col 32}{res}{space 2} .1717771{col 44}{space 2} .0236824{col 55}{space 1}    7.25{col 64}{space 3}0.000{col 72}{space 4} .1244662{col 85}{space 3}  .219088
{txt}{hline 31}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{res}{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}      revenu{col 14}{c |}{space 1}       11{col 27}{space 1}        0{col 39}{result}{space 1}       11{col 53}{text} {col 54}{c |}
{res}{col 1}{text}     ppi_rec{col 14}{c |}{space 1}        6{col 27}{space 1}        1{col 39}{result}{space 1}        5{col 53}{text} {col 54}{c |}
{res}{col 1}{text}         dep{col 14}{c |}{space 1}       65{col 27}{space 1}       65{col 39}{result}{space 1}        0{col 53}{text}*{col 54}{c |}
{res}{col 1}{text}       agglo{col 14}{c |}{space 1}        5{col 27}{space 1}        1{col 39}{result}{space 1}        4{col 53}{text}?{col 54}{c |}
{res}{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
? = number of redundant parameters may be higher
* = FE nested within cluster; treated as redundant for DoF computation
{res}
{txt}added scalar:
             e(mean_y) =  {res}.1887391
{browse `"D:\Dropbox\SVLACHOS\Research\Malgre_nous\Replication_files\Results"' :dir}{com} : {txt}{stata `"seeout using "D:\Dropbox\SVLACHOS\Research\Malgre_nous\Replication_files\Results\abst60.txt""':seeout}
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 11 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}     1,042
{txt}Absorbing 4 HDFE groups{col 51}F({res}   4{txt},{res}     57{txt}){col 67}= {res}      4.25
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0044
{txt}{col 51}R-squared{col 67}= {res}    0.1534
{txt}{col 51}Adj R-squared{col 67}= {res}    0.0819
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0151
{txt}{col 1}Number of clusters ({res}dep{txt}) {col 30}= {res}        58{txt}{col 51}Root MSE{col 67}= {res}    0.3976

{txt}{ralign 96:(Std. err. adjusted for {res:58} clusters in dep)}
{hline 31}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 32}{c |}{col 44}    Robust
{col 1}                  vote_l1962r2{col 32}{c |} Coefficient{col 44}  std. err.{col 56}      t{col 64}   P>|t|{col 72}     [95% con{col 85}f. interval]
{hline 31}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 27}age {c |}
{space 3}\\ Aged 35 to 49 years old  {c |}{col 32}{res}{space 2}-.0424157{col 44}{space 2} .0268947{col 55}{space 1}   -1.58{col 64}{space 3}0.120{col 72}{space 4}-.0962715{col 85}{space 3}   .01144
{txt}[0.3em] -- 50 to 64 years old  {c |}{col 32}{res}{space 2}-.0842504{col 44}{space 2} .0380763{col 55}{space 1}   -2.21{col 64}{space 3}0.031{col 72}{space 4}-.1604968{col 85}{space 3} -.008004
{txt}{space 6}[0.3em] -- 65 and above  {c |}{col 32}{res}{space 2}-.1048785{col 44}{space 2} .0366575{col 55}{space 1}   -2.86{col 64}{space 3}0.006{col 72}{space 4}-.1782838{col 85}{space 3}-.0314732
{txt}{space 30} {c |}
{space 26}sexe {c |}
{space 15}[0.3em] Female  {c |}{col 32}{res}{space 2} .0559135{col 44}{space 2} .0315321{col 55}{space 1}    1.77{col 64}{space 3}0.082{col 72}{space 4}-.0072285{col 85}{space 3} .1190554
{txt}{space 25}_cons {c |}{col 32}{res}{space 2}  .242494{col 44}{space 2} .0263925{col 55}{space 1}    9.19{col 64}{space 3}0.000{col 72}{space 4} .1896439{col 85}{space 3} .2953441
{txt}{hline 31}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{res}{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}      revenu{col 14}{c |}{space 1}       11{col 27}{space 1}        0{col 39}{result}{space 1}       11{col 53}{text} {col 54}{c |}
{res}{col 1}{text}     ppi_rec{col 14}{c |}{space 1}        6{col 27}{space 1}        1{col 39}{result}{space 1}        5{col 53}{text} {col 54}{c |}
{res}{col 1}{text}         dep{col 14}{c |}{space 1}       58{col 27}{space 1}       58{col 39}{result}{space 1}        0{col 53}{text}*{col 54}{c |}
{res}{col 1}{text}       agglo{col 14}{c |}{space 1}        5{col 27}{space 1}        1{col 39}{result}{space 1}        4{col 53}{text}?{col 54}{c |}
{res}{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
? = number of redundant parameters may be higher
* = FE nested within cluster; treated as redundant for DoF computation
{res}
{txt}added scalar:
             e(mean_y) =  {res}.22072937
{browse `"D:\Dropbox\SVLACHOS\Research\Malgre_nous\Replication_files\Results"' :dir}{com} : {txt}{stata `"seeout using "D:\Dropbox\SVLACHOS\Research\Malgre_nous\Replication_files\Results\abst60.txt""':seeout}
{res}{txt}(dropped 1 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 10 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}     1,199
{txt}Absorbing 4 HDFE groups{col 51}F({res}   4{txt},{res}     64{txt}){col 67}= {res}      9.32
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.1272
{txt}{col 51}Adj R-squared{col 67}= {res}    0.0580
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0325
{txt}{col 1}Number of clusters ({res}dep{txt}) {col 30}= {res}        65{txt}{col 51}Root MSE{col 67}= {res}    0.3568

{txt}{ralign 96:(Std. err. adjusted for {res:65} clusters in dep)}
{hline 31}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 32}{c |}{col 44}    Robust
{col 1}                    vote_r1962{col 32}{c |} Coefficient{col 44}  std. err.{col 56}      t{col 64}   P>|t|{col 72}     [95% con{col 85}f. interval]
{hline 31}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 27}age {c |}
{space 3}\\ Aged 35 to 49 years old  {c |}{col 32}{res}{space 2}-.0508875{col 44}{space 2} .0304562{col 55}{space 1}   -1.67{col 64}{space 3}0.100{col 72}{space 4}-.1117308{col 85}{space 3} .0099558
{txt}[0.3em] -- 50 to 64 years old  {c |}{col 32}{res}{space 2}-.1168819{col 44}{space 2} .0288275{col 55}{space 1}   -4.05{col 64}{space 3}0.000{col 72}{space 4}-.1744715{col 85}{space 3}-.0592924
{txt}{space 6}[0.3em] -- 65 and above  {c |}{col 32}{res}{space 2}-.1508999{col 44}{space 2} .0345679{col 55}{space 1}   -4.37{col 64}{space 3}0.000{col 72}{space 4}-.2199573{col 85}{space 3}-.0818425
{txt}{space 30} {c |}
{space 26}sexe {c |}
{space 15}[0.3em] Female  {c |}{col 32}{res}{space 2} .0619361{col 44}{space 2} .0200968{col 55}{space 1}    3.08{col 64}{space 3}0.003{col 72}{space 4} .0217881{col 85}{space 3}  .102084
{txt}{space 25}_cons {c |}{col 32}{res}{space 2} .1985737{col 44}{space 2} .0192241{col 55}{space 1}   10.33{col 64}{space 3}0.000{col 72}{space 4} .1601692{col 85}{space 3} .2369782
{txt}{hline 31}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{res}{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}      revenu{col 14}{c |}{space 1}       11{col 27}{space 1}        0{col 39}{result}{space 1}       11{col 53}{text} {col 54}{c |}
{res}{col 1}{text}     ppi_rec{col 14}{c |}{space 1}        6{col 27}{space 1}        1{col 39}{result}{space 1}        5{col 53}{text} {col 54}{c |}
{res}{col 1}{text}         dep{col 14}{c |}{space 1}       65{col 27}{space 1}       65{col 39}{result}{space 1}        0{col 53}{text}*{col 54}{c |}
{res}{col 1}{text}       agglo{col 14}{c |}{space 1}        5{col 27}{space 1}        1{col 39}{result}{space 1}        4{col 53}{text}?{col 54}{c |}
{res}{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
? = number of redundant parameters may be higher
* = FE nested within cluster; treated as redundant for DoF computation
{res}
{txt}added scalar:
             e(mean_y) =  {res}.16096747
{browse `"D:\Dropbox\SVLACHOS\Research\Malgre_nous\Replication_files\Results"' :dir}{com} : {txt}{stata `"seeout using "D:\Dropbox\SVLACHOS\Research\Malgre_nous\Replication_files\Results\abst60.txt""':seeout}

{com}. 
. // Elections in the 70s
. 
. foreach var in vote_l1973 vote_p1974r1 vote_p1974r2 vote_l1978r1 vote_l1978r2{c -(}
{txt}  2{com}.         reghdfe `var' i.age i.sexe, a(revenu profession dep agglo) cluster(dep)
{txt}  3{com}.         estimates store v70`var'
{txt}  4{com}.         qui sum `var' if e(sample)
{txt}  5{com}.         scalar mean_y=r(mean)
{txt}  6{com}.         estadd scalar mean_y
{txt}  7{com}.         outreg2 using "$results\abst70", nocons dec(3) level(95)
{txt}  8{com}. {c )-}
{res}{txt}(dropped 1 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 10 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}     2,809
{txt}Absorbing 4 HDFE groups{col 51}F({res}   4{txt},{res}     64{txt}){col 67}= {res}     35.64
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.1311
{txt}{col 51}Adj R-squared{col 67}= {res}    0.0937
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0627
{txt}{col 1}Number of clusters ({res}dep{txt}) {col 30}= {res}        65{txt}{col 51}Root MSE{col 67}= {res}    0.2897

{txt}{ralign 96:(Std. err. adjusted for {res:65} clusters in dep)}
{hline 31}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 32}{c |}{col 44}    Robust
{col 1}                    vote_l1973{col 32}{c |} Coefficient{col 44}  std. err.{col 56}      t{col 64}   P>|t|{col 72}     [95% con{col 85}f. interval]
{hline 31}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 27}age {c |}
{space 3}\\ Aged 35 to 49 years old  {c |}{col 32}{res}{space 2}-.1385759{col 44}{space 2} .0210267{col 55}{space 1}   -6.59{col 64}{space 3}0.000{col 72}{space 4}-.1805816{col 85}{space 3}-.0965703
{txt}[0.3em] -- 50 to 64 years old  {c |}{col 32}{res}{space 2}-.1890625{col 44}{space 2} .0182491{col 55}{space 1}  -10.36{col 64}{space 3}0.000{col 72}{space 4}-.2255192{col 85}{space 3}-.1526058
{txt}{space 6}[0.3em] -- 65 and above  {c |}{col 32}{res}{space 2}-.2037382{col 44}{space 2} .0179348{col 55}{space 1}  -11.36{col 64}{space 3}0.000{col 72}{space 4}-.2395671{col 85}{space 3}-.1679093
{txt}{space 30} {c |}
{space 26}sexe {c |}
{space 15}[0.3em] Female  {c |}{col 32}{res}{space 2} .0106104{col 44}{space 2} .0121059{col 55}{space 1}    0.88{col 64}{space 3}0.384{col 72}{space 4}-.0135739{col 85}{space 3} .0347947
{txt}{space 25}_cons {c |}{col 32}{res}{space 2} .2256886{col 44}{space 2} .0146339{col 55}{space 1}   15.42{col 64}{space 3}0.000{col 72}{space 4}  .196454{col 85}{space 3} .2549233
{txt}{hline 31}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{res}{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}      revenu{col 14}{c |}{space 1}       13{col 27}{space 1}        0{col 39}{result}{space 1}       13{col 53}{text} {col 54}{c |}
{res}{col 1}{text}  profession{col 14}{c |}{space 1}       32{col 27}{space 1}        1{col 39}{result}{space 1}       31{col 53}{text} {col 54}{c |}
{res}{col 1}{text}         dep{col 14}{c |}{space 1}       65{col 27}{space 1}       65{col 39}{result}{space 1}        0{col 53}{text}*{col 54}{c |}
{res}{col 1}{text}       agglo{col 14}{c |}{space 1}        5{col 27}{space 1}        1{col 39}{result}{space 1}        4{col 53}{text}?{col 54}{c |}
{res}{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
? = number of redundant parameters may be higher
* = FE nested within cluster; treated as redundant for DoF computation
{res}
{txt}added scalar:
             e(mean_y) =  {res}.10323959
{browse `"D:\Dropbox\SVLACHOS\Research\Malgre_nous\Replication_files\Results"' :dir}{com} : {txt}{stata `"seeout using "D:\Dropbox\SVLACHOS\Research\Malgre_nous\Replication_files\Results\abst70.txt""':seeout}
{res}{txt}(dropped 1 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 10 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}     3,272
{txt}Absorbing 4 HDFE groups{col 51}F({res}   4{txt},{res}     64{txt}){col 67}= {res}     52.78
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.1129
{txt}{col 51}Adj R-squared{col 67}= {res}    0.0803
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0626
{txt}{col 1}Number of clusters ({res}dep{txt}) {col 30}= {res}        65{txt}{col 51}Root MSE{col 67}= {res}    0.2696

{txt}{ralign 96:(Std. err. adjusted for {res:65} clusters in dep)}
{hline 31}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 32}{c |}{col 44}    Robust
{col 1}                  vote_p1974r1{col 32}{c |} Coefficient{col 44}  std. err.{col 56}      t{col 64}   P>|t|{col 72}     [95% con{col 85}f. interval]
{hline 31}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 27}age {c |}
{space 3}\\ Aged 35 to 49 years old  {c |}{col 32}{res}{space 2}-.1305142{col 44}{space 2} .0147134{col 55}{space 1}   -8.87{col 64}{space 3}0.000{col 72}{space 4}-.1599075{col 85}{space 3}-.1011208
{txt}[0.3em] -- 50 to 64 years old  {c |}{col 32}{res}{space 2} -.167254{col 44}{space 2} .0152455{col 55}{space 1}  -10.97{col 64}{space 3}0.000{col 72}{space 4}-.1977104{col 85}{space 3}-.1367975
{txt}{space 6}[0.3em] -- 65 and above  {c |}{col 32}{res}{space 2}-.1946853{col 44}{space 2} .0142239{col 55}{space 1}  -13.69{col 64}{space 3}0.000{col 72}{space 4}-.2231009{col 85}{space 3}-.1662697
{txt}{space 30} {c |}
{space 26}sexe {c |}
{space 15}[0.3em] Female  {c |}{col 32}{res}{space 2}-.0016802{col 44}{space 2}  .010872{col 55}{space 1}   -0.15{col 64}{space 3}0.878{col 72}{space 4}-.0233994{col 85}{space 3} .0200391
{txt}{space 25}_cons {c |}{col 32}{res}{space 2} .2032231{col 44}{space 2} .0097727{col 55}{space 1}   20.79{col 64}{space 3}0.000{col 72}{space 4} .1836999{col 85}{space 3} .2227463
{txt}{hline 31}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{res}{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}      revenu{col 14}{c |}{space 1}       13{col 27}{space 1}        0{col 39}{result}{space 1}       13{col 53}{text} {col 54}{c |}
{res}{col 1}{text}  profession{col 14}{c |}{space 1}       32{col 27}{space 1}        1{col 39}{result}{space 1}       31{col 53}{text} {col 54}{c |}
{res}{col 1}{text}         dep{col 14}{c |}{space 1}       65{col 27}{space 1}       65{col 39}{result}{space 1}        0{col 53}{text}*{col 54}{c |}
{res}{col 1}{text}       agglo{col 14}{c |}{space 1}        5{col 27}{space 1}        1{col 39}{result}{space 1}        4{col 53}{text}?{col 54}{c |}
{res}{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
? = number of redundant parameters may be higher
* = FE nested within cluster; treated as redundant for DoF computation
{res}
{txt}added scalar:
             e(mean_y) =  {res}.08649144
{browse `"D:\Dropbox\SVLACHOS\Research\Malgre_nous\Replication_files\Results"' :dir}{com} : {txt}{stata `"seeout using "D:\Dropbox\SVLACHOS\Research\Malgre_nous\Replication_files\Results\abst70.txt""':seeout}
{res}{txt}(dropped 1 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 10 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}     3,100
{txt}Absorbing 4 HDFE groups{col 51}F({res}   4{txt},{res}     64{txt}){col 67}= {res}     40.45
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.1149
{txt}{col 51}Adj R-squared{col 67}= {res}    0.0805
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0623
{txt}{col 1}Number of clusters ({res}dep{txt}) {col 30}= {res}        65{txt}{col 51}Root MSE{col 67}= {res}    0.2806

{txt}{ralign 96:(Std. err. adjusted for {res:65} clusters in dep)}
{hline 31}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 32}{c |}{col 44}    Robust
{col 1}                  vote_p1974r2{col 32}{c |} Coefficient{col 44}  std. err.{col 56}      t{col 64}   P>|t|{col 72}     [95% con{col 85}f. interval]
{hline 31}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 27}age {c |}
{space 3}\\ Aged 35 to 49 years old  {c |}{col 32}{res}{space 2} -.130835{col 44}{space 2} .0161333{col 55}{space 1}   -8.11{col 64}{space 3}0.000{col 72}{space 4}-.1630651{col 85}{space 3} -.098605
{txt}[0.3em] -- 50 to 64 years old  {c |}{col 32}{res}{space 2}-.1756574{col 44}{space 2} .0173607{col 55}{space 1}  -10.12{col 64}{space 3}0.000{col 72}{space 4}-.2103395{col 85}{space 3}-.1409754
{txt}{space 6}[0.3em] -- 65 and above  {c |}{col 32}{res}{space 2}-.2002213{col 44}{space 2} .0161706{col 55}{space 1}  -12.38{col 64}{space 3}0.000{col 72}{space 4}-.2325259{col 85}{space 3}-.1679168
{txt}{space 30} {c |}
{space 26}sexe {c |}
{space 15}[0.3em] Female  {c |}{col 32}{res}{space 2}-.0052142{col 44}{space 2}  .010327{col 55}{space 1}   -0.50{col 64}{space 3}0.615{col 72}{space 4}-.0258448{col 85}{space 3} .0154164
{txt}{space 25}_cons {c |}{col 32}{res}{space 2} .2154783{col 44}{space 2} .0119858{col 55}{space 1}   17.98{col 64}{space 3}0.000{col 72}{space 4} .1915339{col 85}{space 3} .2394228
{txt}{hline 31}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{res}{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}      revenu{col 14}{c |}{space 1}       13{col 27}{space 1}        0{col 39}{result}{space 1}       13{col 53}{text} {col 54}{c |}
{res}{col 1}{text}  profession{col 14}{c |}{space 1}       32{col 27}{space 1}        1{col 39}{result}{space 1}       31{col 53}{text} {col 54}{c |}
{res}{col 1}{text}         dep{col 14}{c |}{space 1}       65{col 27}{space 1}       65{col 39}{result}{space 1}        0{col 53}{text}*{col 54}{c |}
{res}{col 1}{text}       agglo{col 14}{c |}{space 1}        5{col 27}{space 1}        1{col 39}{result}{space 1}        4{col 53}{text}?{col 54}{c |}
{res}{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
? = number of redundant parameters may be higher
* = FE nested within cluster; treated as redundant for DoF computation
{res}
{txt}added scalar:
             e(mean_y) =  {res}.09451613
{browse `"D:\Dropbox\SVLACHOS\Research\Malgre_nous\Replication_files\Results"' :dir}{com} : {txt}{stata `"seeout using "D:\Dropbox\SVLACHOS\Research\Malgre_nous\Replication_files\Results\abst70.txt""':seeout}
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 10 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}     3,583
{txt}Absorbing 4 HDFE groups{col 51}F({res}   4{txt},{res}     64{txt}){col 67}= {res}      6.43
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0002
{txt}{col 51}R-squared{col 67}= {res}    0.0443
{txt}{col 51}Adj R-squared{col 67}= {res}    0.0120
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0083
{txt}{col 1}Number of clusters ({res}dep{txt}) {col 30}= {res}        65{txt}{col 51}Root MSE{col 67}= {res}    0.2851

{txt}{ralign 96:(Std. err. adjusted for {res:65} clusters in dep)}
{hline 31}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 32}{c |}{col 44}    Robust
{col 1}                  vote_l1978r1{col 32}{c |} Coefficient{col 44}  std. err.{col 56}      t{col 64}   P>|t|{col 72}     [95% con{col 85}f. interval]
{hline 31}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 27}age {c |}
{space 3}\\ Aged 35 to 49 years old  {c |}{col 32}{res}{space 2}-.0392134{col 44}{space 2} .0142984{col 55}{space 1}   -2.74{col 64}{space 3}0.008{col 72}{space 4}-.0677777{col 85}{space 3}-.0106491
{txt}[0.3em] -- 50 to 64 years old  {c |}{col 32}{res}{space 2}-.0647799{col 44}{space 2} .0135175{col 55}{space 1}   -4.79{col 64}{space 3}0.000{col 72}{space 4}-.0917843{col 85}{space 3}-.0377756
{txt}{space 6}[0.3em] -- 65 and above  {c |}{col 32}{res}{space 2}-.0613075{col 44}{space 2} .0169221{col 55}{space 1}   -3.62{col 64}{space 3}0.001{col 72}{space 4}-.0951133{col 85}{space 3}-.0275017
{txt}{space 30} {c |}
{space 26}sexe {c |}
{space 15}[0.3em] Female  {c |}{col 32}{res}{space 2} .0131533{col 44}{space 2} .0119927{col 55}{space 1}    1.10{col 64}{space 3}0.277{col 72}{space 4}-.0108049{col 85}{space 3} .0371115
{txt}{space 25}_cons {c |}{col 32}{res}{space 2} .1174186{col 44}{space 2}  .009406{col 55}{space 1}   12.48{col 64}{space 3}0.000{col 72}{space 4}  .098628{col 85}{space 3} .1362092
{txt}{hline 31}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{res}{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}      revenu{col 14}{c |}{space 1}       13{col 27}{space 1}        0{col 39}{result}{space 1}       13{col 53}{text} {col 54}{c |}
{res}{col 1}{text}  profession{col 14}{c |}{space 1}       33{col 27}{space 1}        1{col 39}{result}{space 1}       32{col 53}{text} {col 54}{c |}
{res}{col 1}{text}         dep{col 14}{c |}{space 1}       65{col 27}{space 1}       65{col 39}{result}{space 1}        0{col 53}{text}*{col 54}{c |}
{res}{col 1}{text}       agglo{col 14}{c |}{space 1}        5{col 27}{space 1}        1{col 39}{result}{space 1}        4{col 53}{text}?{col 54}{c |}
{res}{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
? = number of redundant parameters may be higher
* = FE nested within cluster; treated as redundant for DoF computation
{res}
{txt}added scalar:
             e(mean_y) =  {res}.09042702
{browse `"D:\Dropbox\SVLACHOS\Research\Malgre_nous\Replication_files\Results"' :dir}{com} : {txt}{stata `"seeout using "D:\Dropbox\SVLACHOS\Research\Malgre_nous\Replication_files\Results\abst70.txt""':seeout}
{res}{txt}(dropped 1 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 10 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}     3,126
{txt}Absorbing 4 HDFE groups{col 51}F({res}   4{txt},{res}     58{txt}){col 67}= {res}      8.26
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.0574
{txt}{col 51}Adj R-squared{col 67}= {res}    0.0230
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0126
{txt}{col 1}Number of clusters ({res}dep{txt}) {col 30}= {res}        59{txt}{col 51}Root MSE{col 67}= {res}    0.2959

{txt}{ralign 96:(Std. err. adjusted for {res:59} clusters in dep)}
{hline 31}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 32}{c |}{col 44}    Robust
{col 1}                  vote_l1978r2{col 32}{c |} Coefficient{col 44}  std. err.{col 56}      t{col 64}   P>|t|{col 72}     [95% con{col 85}f. interval]
{hline 31}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 27}age {c |}
{space 3}\\ Aged 35 to 49 years old  {c |}{col 32}{res}{space 2}-.0430925{col 44}{space 2} .0158446{col 55}{space 1}   -2.72{col 64}{space 3}0.009{col 72}{space 4} -.074809{col 85}{space 3} -.011376
{txt}[0.3em] -- 50 to 64 years old  {c |}{col 32}{res}{space 2}-.0736187{col 44}{space 2} .0139729{col 55}{space 1}   -5.27{col 64}{space 3}0.000{col 72}{space 4}-.1015886{col 85}{space 3}-.0456489
{txt}{space 6}[0.3em] -- 65 and above  {c |}{col 32}{res}{space 2}-.0960936{col 44}{space 2}  .020984{col 55}{space 1}   -4.58{col 64}{space 3}0.000{col 72}{space 4}-.1380977{col 85}{space 3}-.0540896
{txt}{space 30} {c |}
{space 26}sexe {c |}
{space 15}[0.3em] Female  {c |}{col 32}{res}{space 2}-.0146274{col 44}{space 2} .0148193{col 55}{space 1}   -0.99{col 64}{space 3}0.328{col 72}{space 4}-.0442914{col 85}{space 3} .0150367
{txt}{space 25}_cons {c |}{col 32}{res}{space 2} .1498337{col 44}{space 2} .0121825{col 55}{space 1}   12.30{col 64}{space 3}0.000{col 72}{space 4} .1254477{col 85}{space 3} .1742197
{txt}{hline 31}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{res}{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}      revenu{col 14}{c |}{space 1}       13{col 27}{space 1}        0{col 39}{result}{space 1}       13{col 53}{text} {col 54}{c |}
{res}{col 1}{text}  profession{col 14}{c |}{space 1}       32{col 27}{space 1}        1{col 39}{result}{space 1}       31{col 53}{text} {col 54}{c |}
{res}{col 1}{text}         dep{col 14}{c |}{space 1}       59{col 27}{space 1}       59{col 39}{result}{space 1}        0{col 53}{text}*{col 54}{c |}
{res}{col 1}{text}       agglo{col 14}{c |}{space 1}        5{col 27}{space 1}        1{col 39}{result}{space 1}        4{col 53}{text}?{col 54}{c |}
{res}{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
? = number of redundant parameters may be higher
* = FE nested within cluster; treated as redundant for DoF computation
{res}
{txt}added scalar:
             e(mean_y) =  {res}.09948816
{browse `"D:\Dropbox\SVLACHOS\Research\Malgre_nous\Replication_files\Results"' :dir}{com} : {txt}{stata `"seeout using "D:\Dropbox\SVLACHOS\Research\Malgre_nous\Replication_files\Results\abst70.txt""':seeout}

{com}. 
. foreach var in rrw_p1974r1 rrw_l1978r1{c -(}
{txt}  2{com}.         reghdfe `var' i.age i.sexe, a(revenu profession dep agglo) cluster(dep)
{txt}  3{com}.         estimates store v70`var'
{txt}  4{com}.         qui sum `var' if e(sample)
{txt}  5{com}.         scalar mean_y=r(mean)
{txt}  6{com}.         estadd scalar mean_y
{txt}  7{com}.         outreg2 using "$results\rrw70", nocons dec(3) level(95)
{txt}  8{com}. {c )-}
{res}{txt}(dropped 1 {browse "http://scorreia.com/research/singletons.pdf":singleton observations})
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 10 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}     3,272
{txt}Absorbing 4 HDFE groups{col 51}F({res}   4{txt},{res}     64{txt}){col 67}= {res}      2.09
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0922
{txt}{col 51}R-squared{col 67}= {res}    0.0465
{txt}{col 51}Adj R-squared{col 67}= {res}    0.0115
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0016
{txt}{col 1}Number of clusters ({res}dep{txt}) {col 30}= {res}        65{txt}{col 51}Root MSE{col 67}= {res}    0.0626

{txt}{ralign 96:(Std. err. adjusted for {res:65} clusters in dep)}
{hline 31}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 32}{c |}{col 44}    Robust
{col 1}                   rrw_p1974r1{col 32}{c |} Coefficient{col 44}  std. err.{col 56}      t{col 64}   P>|t|{col 72}     [95% con{col 85}f. interval]
{hline 31}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 27}age {c |}
{space 3}\\ Aged 35 to 49 years old  {c |}{col 32}{res}{space 2} .0043553{col 44}{space 2} .0033594{col 55}{space 1}    1.30{col 64}{space 3}0.199{col 72}{space 4}-.0023559{col 85}{space 3} .0110665
{txt}[0.3em] -- 50 to 64 years old  {c |}{col 32}{res}{space 2} .0026737{col 44}{space 2} .0030501{col 55}{space 1}    0.88{col 64}{space 3}0.384{col 72}{space 4}-.0034196{col 85}{space 3} .0087669
{txt}{space 6}[0.3em] -- 65 and above  {c |}{col 32}{res}{space 2}-.0020296{col 44}{space 2} .0019383{col 55}{space 1}   -1.05{col 64}{space 3}0.299{col 72}{space 4}-.0059019{col 85}{space 3} .0018426
{txt}{space 30} {c |}
{space 26}sexe {c |}
{space 15}[0.3em] Female  {c |}{col 32}{res}{space 2}-.0023532{col 44}{space 2}  .002642{col 55}{space 1}   -0.89{col 64}{space 3}0.376{col 72}{space 4}-.0076311{col 85}{space 3} .0029248
{txt}{space 25}_cons {c |}{col 32}{res}{space 2}  .003663{col 44}{space 2} .0020015{col 55}{space 1}    1.83{col 64}{space 3}0.072{col 72}{space 4}-.0003355{col 85}{space 3} .0076614
{txt}{hline 31}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{res}{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}      revenu{col 14}{c |}{space 1}       13{col 27}{space 1}        0{col 39}{result}{space 1}       13{col 53}{text} {col 54}{c |}
{res}{col 1}{text}  profession{col 14}{c |}{space 1}       32{col 27}{space 1}        1{col 39}{result}{space 1}       31{col 53}{text} {col 54}{c |}
{res}{col 1}{text}         dep{col 14}{c |}{space 1}       65{col 27}{space 1}       65{col 39}{result}{space 1}        0{col 53}{text}*{col 54}{c |}
{res}{col 1}{text}       agglo{col 14}{c |}{space 1}        5{col 27}{space 1}        1{col 39}{result}{space 1}        4{col 53}{text}?{col 54}{c |}
{res}{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
? = number of redundant parameters may be higher
* = FE nested within cluster; treated as redundant for DoF computation
{res}
{txt}added scalar:
             e(mean_y) =  {res}.00397311
{browse `"D:\Dropbox\SVLACHOS\Research\Malgre_nous\Replication_files\Results"' :dir}{com} : {txt}{stata `"seeout using "D:\Dropbox\SVLACHOS\Research\Malgre_nous\Replication_files\Results\rrw70.txt""':seeout}
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 10 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}     3,583
{txt}Absorbing 4 HDFE groups{col 51}F({res}   4{txt},{res}     64{txt}){col 67}= {res}      1.44
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.2323
{txt}{col 51}R-squared{col 67}= {res}    0.0507
{txt}{col 51}Adj R-squared{col 67}= {res}    0.0186
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0014
{txt}{col 1}Number of clusters ({res}dep{txt}) {col 30}= {res}        65{txt}{col 51}Root MSE{col 67}= {res}    0.0756

{txt}{ralign 96:(Std. err. adjusted for {res:65} clusters in dep)}
{hline 31}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 32}{c |}{col 44}    Robust
{col 1}                   rrw_l1978r1{col 32}{c |} Coefficient{col 44}  std. err.{col 56}      t{col 64}   P>|t|{col 72}     [95% con{col 85}f. interval]
{hline 31}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 27}age {c |}
{space 3}\\ Aged 35 to 49 years old  {c |}{col 32}{res}{space 2} .0049235{col 44}{space 2} .0027371{col 55}{space 1}    1.80{col 64}{space 3}0.077{col 72}{space 4}-.0005445{col 85}{space 3} .0103916
{txt}[0.3em] -- 50 to 64 years old  {c |}{col 32}{res}{space 2} .0067472{col 44}{space 2} .0039333{col 55}{space 1}    1.72{col 64}{space 3}0.091{col 72}{space 4}-.0011106{col 85}{space 3} .0146049
{txt}{space 6}[0.3em] -- 65 and above  {c |}{col 32}{res}{space 2} .0052915{col 44}{space 2} .0051583{col 55}{space 1}    1.03{col 64}{space 3}0.309{col 72}{space 4}-.0050134{col 85}{space 3} .0155963
{txt}{space 30} {c |}
{space 26}sexe {c |}
{space 15}[0.3em] Female  {c |}{col 32}{res}{space 2} .0027891{col 44}{space 2} .0025862{col 55}{space 1}    1.08{col 64}{space 3}0.285{col 72}{space 4}-.0023775{col 85}{space 3} .0079556
{txt}{space 25}_cons {c |}{col 32}{res}{space 2} .0008991{col 44}{space 2} .0025864{col 55}{space 1}    0.35{col 64}{space 3}0.729{col 72}{space 4}-.0042678{col 85}{space 3} .0060661
{txt}{hline 31}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{res}{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}      revenu{col 14}{c |}{space 1}       13{col 27}{space 1}        0{col 39}{result}{space 1}       13{col 53}{text} {col 54}{c |}
{res}{col 1}{text}  profession{col 14}{c |}{space 1}       33{col 27}{space 1}        1{col 39}{result}{space 1}       32{col 53}{text} {col 54}{c |}
{res}{col 1}{text}         dep{col 14}{c |}{space 1}       65{col 27}{space 1}       65{col 39}{result}{space 1}        0{col 53}{text}*{col 54}{c |}
{res}{col 1}{text}       agglo{col 14}{c |}{space 1}        5{col 27}{space 1}        1{col 39}{result}{space 1}        4{col 53}{text}?{col 54}{c |}
{res}{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
? = number of redundant parameters may be higher
* = FE nested within cluster; treated as redundant for DoF computation
{res}
{txt}added scalar:
             e(mean_y) =  {res}.00586101
{browse `"D:\Dropbox\SVLACHOS\Research\Malgre_nous\Replication_files\Results"' :dir}{com} : {txt}{stata `"seeout using "D:\Dropbox\SVLACHOS\Research\Malgre_nous\Replication_files\Results\rrw70.txt""':seeout}

{com}. 
. // Elections in the 80s
. 
. foreach var in vote_l1986 vote_p1988r1 vote_l1993 vote_e1994 vote_p1995r1{c -(}
{txt}  2{com}.         reghdfe `var' i.age i.sexe, a(revenu profession dep) cluster(dep)
{txt}  3{com}.         estimates store v80`var'
{txt}  4{com}.         qui sum `var' if e(sample)
{txt}  5{com}.         scalar mean_y=r(mean)
{txt}  6{com}.         estadd scalar mean_y
{txt}  7{com}.         outreg2 using "$results\abst80", nocons dec(3) level(95)
{txt}  8{com}. {c )-}
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 7 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}     2,789
{txt}Absorbing 3 HDFE groups{col 51}F({res}   4{txt},{res}     72{txt}){col 67}= {res}     37.40
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.1333
{txt}{col 51}Adj R-squared{col 67}= {res}    0.1017
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0697
{txt}{col 1}Number of clusters ({res}dep{txt}) {col 30}= {res}        73{txt}{col 51}Root MSE{col 67}= {res}    0.3423

{txt}{ralign 96:(Std. err. adjusted for {res:73} clusters in dep)}
{hline 31}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 32}{c |}{col 44}    Robust
{col 1}                    vote_l1986{col 32}{c |} Coefficient{col 44}  std. err.{col 56}      t{col 64}   P>|t|{col 72}     [95% con{col 85}f. interval]
{hline 31}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 27}age {c |}
{space 3}\\ Aged 35 to 49 years old  {c |}{col 32}{res}{space 2}-.1655192{col 44}{space 2} .0190345{col 55}{space 1}   -8.70{col 64}{space 3}0.000{col 72}{space 4}-.2034639{col 85}{space 3}-.1275746
{txt}[0.3em] -- 50 to 64 years old  {c |}{col 32}{res}{space 2}-.2076022{col 44}{space 2} .0188295{col 55}{space 1}  -11.03{col 64}{space 3}0.000{col 72}{space 4}-.2451381{col 85}{space 3}-.1700664
{txt}{space 6}[0.3em] -- 65 and above  {c |}{col 32}{res}{space 2}-.2302246{col 44}{space 2} .0214799{col 55}{space 1}  -10.72{col 64}{space 3}0.000{col 72}{space 4}-.2730441{col 85}{space 3}-.1874051
{txt}{space 30} {c |}
{space 26}sexe {c |}
{space 15}[0.3em] Female  {c |}{col 32}{res}{space 2} .0255212{col 44}{space 2} .0170088{col 55}{space 1}    1.50{col 64}{space 3}0.138{col 72}{space 4}-.0083853{col 85}{space 3} .0594277
{txt}{space 25}_cons {c |}{col 32}{res}{space 2} .2728232{col 44}{space 2}  .014745{col 55}{space 1}   18.50{col 64}{space 3}0.000{col 72}{space 4} .2434296{col 85}{space 3} .3022167
{txt}{hline 31}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{res}{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}      revenu{col 14}{c |}{space 1}       10{col 27}{space 1}        0{col 39}{result}{space 1}       10{col 53}{text} {col 54}{c |}
{res}{col 1}{text}  profession{col 14}{c |}{space 1}       13{col 27}{space 1}        1{col 39}{result}{space 1}       12{col 53}{text} {col 54}{c |}
{res}{col 1}{text}         dep{col 14}{c |}{space 1}       73{col 27}{space 1}       73{col 39}{result}{space 1}        0{col 53}{text}*{col 54}{c |}
{res}{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}
{txt}added scalar:
             e(mean_y) =  {res}.15417712
{browse `"D:\Dropbox\SVLACHOS\Research\Malgre_nous\Replication_files\Results"' :dir}{com} : {txt}{stata `"seeout using "D:\Dropbox\SVLACHOS\Research\Malgre_nous\Replication_files\Results\abst80.txt""':seeout}
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 7 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}     2,641
{txt}Absorbing 3 HDFE groups{col 51}F({res}   4{txt},{res}     72{txt}){col 67}= {res}      0.42
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.7973
{txt}{col 51}R-squared{col 67}= {res}    0.0452
{txt}{col 51}Adj R-squared{col 67}= {res}    0.0084
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0003
{txt}{col 1}Number of clusters ({res}dep{txt}) {col 30}= {res}        73{txt}{col 51}Root MSE{col 67}= {res}    0.1397

{txt}{ralign 96:(Std. err. adjusted for {res:73} clusters in dep)}
{hline 31}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 32}{c |}{col 44}    Robust
{col 1}                  vote_p1988r1{col 32}{c |} Coefficient{col 44}  std. err.{col 56}      t{col 64}   P>|t|{col 72}     [95% con{col 85}f. interval]
{hline 31}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 27}age {c |}
{space 3}\\ Aged 35 to 49 years old  {c |}{col 32}{res}{space 2} .0012905{col 44}{space 2} .0065981{col 55}{space 1}    0.20{col 64}{space 3}0.845{col 72}{space 4}-.0118626{col 85}{space 3} .0144436
{txt}[0.3em] -- 50 to 64 years old  {c |}{col 32}{res}{space 2}-.0050491{col 44}{space 2} .0067568{col 55}{space 1}   -0.75{col 64}{space 3}0.457{col 72}{space 4}-.0185185{col 85}{space 3} .0084203
{txt}{space 6}[0.3em] -- 65 and above  {c |}{col 32}{res}{space 2} -.003538{col 44}{space 2} .0071059{col 55}{space 1}   -0.50{col 64}{space 3}0.620{col 72}{space 4}-.0177034{col 85}{space 3} .0106274
{txt}{space 30} {c |}
{space 26}sexe {c |}
{space 15}[0.3em] Female  {c |}{col 32}{res}{space 2}-.0016709{col 44}{space 2} .0063265{col 55}{space 1}   -0.26{col 64}{space 3}0.792{col 72}{space 4}-.0142826{col 85}{space 3} .0109407
{txt}{space 25}_cons {c |}{col 32}{res}{space 2} .0222996{col 44}{space 2}  .005551{col 55}{space 1}    4.02{col 64}{space 3}0.000{col 72}{space 4} .0112337{col 85}{space 3} .0333654
{txt}{hline 31}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{res}{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}      revenu{col 14}{c |}{space 1}       10{col 27}{space 1}        0{col 39}{result}{space 1}       10{col 53}{text} {col 54}{c |}
{res}{col 1}{text}  profession{col 14}{c |}{space 1}       13{col 27}{space 1}        1{col 39}{result}{space 1}       12{col 53}{text} {col 54}{c |}
{res}{col 1}{text}         dep{col 14}{c |}{space 1}       73{col 27}{space 1}       73{col 39}{result}{space 1}        0{col 53}{text}*{col 54}{c |}
{res}{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}
{txt}added scalar:
             e(mean_y) =  {res}.02006816
{browse `"D:\Dropbox\SVLACHOS\Research\Malgre_nous\Replication_files\Results"' :dir}{com} : {txt}{stata `"seeout using "D:\Dropbox\SVLACHOS\Research\Malgre_nous\Replication_files\Results\abst80.txt""':seeout}
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 8 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}     2,619
{txt}Absorbing 3 HDFE groups{col 51}F({res}   4{txt},{res}     74{txt}){col 67}= {res}     35.51
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.1369
{txt}{col 51}Adj R-squared{col 67}= {res}    0.0998
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0661
{txt}{col 1}Number of clusters ({res}dep{txt}) {col 30}= {res}        75{txt}{col 51}Root MSE{col 67}= {res}    0.3692

{txt}{ralign 96:(Std. err. adjusted for {res:75} clusters in dep)}
{hline 31}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 32}{c |}{col 44}    Robust
{col 1}                    vote_l1993{col 32}{c |} Coefficient{col 44}  std. err.{col 56}      t{col 64}   P>|t|{col 72}     [95% con{col 85}f. interval]
{hline 31}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 27}age {c |}
{space 3}\\ Aged 35 to 49 years old  {c |}{col 32}{res}{space 2}-.1663047{col 44}{space 2} .0235754{col 55}{space 1}   -7.05{col 64}{space 3}0.000{col 72}{space 4}-.2132797{col 85}{space 3}-.1193298
{txt}[0.3em] -- 50 to 64 years old  {c |}{col 32}{res}{space 2}-.2424772{col 44}{space 2} .0233561{col 55}{space 1}  -10.38{col 64}{space 3}0.000{col 72}{space 4}-.2890152{col 85}{space 3}-.1959392
{txt}{space 6}[0.3em] -- 65 and above  {c |}{col 32}{res}{space 2}-.2607235{col 44}{space 2} .0243718{col 55}{space 1}  -10.70{col 64}{space 3}0.000{col 72}{space 4}-.3092853{col 85}{space 3}-.2121616
{txt}{space 30} {c |}
{space 26}sexe {c |}
{space 15}[0.3em] Female  {c |}{col 32}{res}{space 2} .0255694{col 44}{space 2} .0165618{col 55}{space 1}    1.54{col 64}{space 3}0.127{col 72}{space 4}-.0074308{col 85}{space 3} .0585696
{txt}{space 25}_cons {c |}{col 32}{res}{space 2} .3339877{col 44}{space 2} .0160118{col 55}{space 1}   20.86{col 64}{space 3}0.000{col 72}{space 4} .3020835{col 85}{space 3}  .365892
{txt}{hline 31}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{res}{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}      revenu{col 14}{c |}{space 1}       10{col 27}{space 1}        0{col 39}{result}{space 1}       10{col 53}{text} {col 54}{c |}
{res}{col 1}{text}  profession{col 14}{c |}{space 1}       21{col 27}{space 1}        1{col 39}{result}{space 1}       20{col 53}{text} {col 54}{c |}
{res}{col 1}{text}         dep{col 14}{c |}{space 1}       75{col 27}{space 1}       75{col 39}{result}{space 1}        0{col 53}{text}*{col 54}{c |}
{res}{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}
{txt}added scalar:
             e(mean_y) =  {res}.18594884
{browse `"D:\Dropbox\SVLACHOS\Research\Malgre_nous\Replication_files\Results"' :dir}{com} : {txt}{stata `"seeout using "D:\Dropbox\SVLACHOS\Research\Malgre_nous\Replication_files\Results\abst80.txt""':seeout}
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 8 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}     2,515
{txt}Absorbing 3 HDFE groups{col 51}F({res}   4{txt},{res}     74{txt}){col 67}= {res}     32.60
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0000
{txt}{col 51}R-squared{col 67}= {res}    0.1340
{txt}{col 51}Adj R-squared{col 67}= {res}    0.0951
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0572
{txt}{col 1}Number of clusters ({res}dep{txt}) {col 30}= {res}        75{txt}{col 51}Root MSE{col 67}= {res}    0.4190

{txt}{ralign 96:(Std. err. adjusted for {res:75} clusters in dep)}
{hline 31}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 32}{c |}{col 44}    Robust
{col 1}                    vote_e1994{col 32}{c |} Coefficient{col 44}  std. err.{col 56}      t{col 64}   P>|t|{col 72}     [95% con{col 85}f. interval]
{hline 31}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 27}age {c |}
{space 3}\\ Aged 35 to 49 years old  {c |}{col 32}{res}{space 2}-.1550976{col 44}{space 2} .0218126{col 55}{space 1}   -7.11{col 64}{space 3}0.000{col 72}{space 4}  -.19856{col 85}{space 3}-.1116351
{txt}[0.3em] -- 50 to 64 years old  {c |}{col 32}{res}{space 2}-.2434935{col 44}{space 2} .0246029{col 55}{space 1}   -9.90{col 64}{space 3}0.000{col 72}{space 4}-.2925158{col 85}{space 3}-.1944711
{txt}{space 6}[0.3em] -- 65 and above  {c |}{col 32}{res}{space 2}-.2675496{col 44}{space 2} .0269474{col 55}{space 1}   -9.93{col 64}{space 3}0.000{col 72}{space 4}-.3212435{col 85}{space 3}-.2138558
{txt}{space 30} {c |}
{space 26}sexe {c |}
{space 15}[0.3em] Female  {c |}{col 32}{res}{space 2} .0672197{col 44}{space 2} .0199418{col 55}{space 1}    3.37{col 64}{space 3}0.001{col 72}{space 4} .0274848{col 85}{space 3} .1069546
{txt}{space 25}_cons {c |}{col 32}{res}{space 2} .3867722{col 44}{space 2} .0168064{col 55}{space 1}   23.01{col 64}{space 3}0.000{col 72}{space 4} .3532848{col 85}{space 3} .4202597
{txt}{hline 31}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{res}{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}      revenu{col 14}{c |}{space 1}       10{col 27}{space 1}        0{col 39}{result}{space 1}       10{col 53}{text} {col 54}{c |}
{res}{col 1}{text}  profession{col 14}{c |}{space 1}       21{col 27}{space 1}        1{col 39}{result}{space 1}       20{col 53}{text} {col 54}{c |}
{res}{col 1}{text}         dep{col 14}{c |}{space 1}       75{col 27}{space 1}       75{col 39}{result}{space 1}        0{col 53}{text}*{col 54}{c |}
{res}{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}
{txt}added scalar:
             e(mean_y) =  {res}.26322068
{browse `"D:\Dropbox\SVLACHOS\Research\Malgre_nous\Replication_files\Results"' :dir}{com} : {txt}{stata `"seeout using "D:\Dropbox\SVLACHOS\Research\Malgre_nous\Replication_files\Results\abst80.txt""':seeout}
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 8 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}     2,499
{txt}Absorbing 3 HDFE groups{col 51}F({res}   4{txt},{res}     74{txt}){col 67}= {res}      1.35
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.2607
{txt}{col 51}R-squared{col 67}= {res}    0.0540
{txt}{col 51}Adj R-squared{col 67}= {res}    0.0113
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0018
{txt}{col 1}Number of clusters ({res}dep{txt}) {col 30}= {res}        75{txt}{col 51}Root MSE{col 67}= {res}    0.2143

{txt}{ralign 96:(Std. err. adjusted for {res:75} clusters in dep)}
{hline 31}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 32}{c |}{col 44}    Robust
{col 1}                  vote_p1995r1{col 32}{c |} Coefficient{col 44}  std. err.{col 56}      t{col 64}   P>|t|{col 72}     [95% con{col 85}f. interval]
{hline 31}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 27}age {c |}
{space 3}\\ Aged 35 to 49 years old  {c |}{col 32}{res}{space 2}-.0068462{col 44}{space 2} .0129271{col 55}{space 1}   -0.53{col 64}{space 3}0.598{col 72}{space 4}-.0326039{col 85}{space 3} .0189116
{txt}[0.3em] -- 50 to 64 years old  {c |}{col 32}{res}{space 2} .0171799{col 44}{space 2} .0134215{col 55}{space 1}    1.28{col 64}{space 3}0.205{col 72}{space 4} -.009563{col 85}{space 3} .0439228
{txt}{space 6}[0.3em] -- 65 and above  {c |}{col 32}{res}{space 2} .0033001{col 44}{space 2} .0137667{col 55}{space 1}    0.24{col 64}{space 3}0.811{col 72}{space 4}-.0241307{col 85}{space 3} .0307309
{txt}{space 30} {c |}
{space 26}sexe {c |}
{space 15}[0.3em] Female  {c |}{col 32}{res}{space 2}-.0069606{col 44}{space 2} .0108217{col 55}{space 1}   -0.64{col 64}{space 3}0.522{col 72}{space 4}-.0285233{col 85}{space 3} .0146022
{txt}{space 25}_cons {c |}{col 32}{res}{space 2} .0498893{col 44}{space 2} .0087137{col 55}{space 1}    5.73{col 64}{space 3}0.000{col 72}{space 4} .0325269{col 85}{space 3} .0672516
{txt}{hline 31}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{res}{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}      revenu{col 14}{c |}{space 1}       10{col 27}{space 1}        0{col 39}{result}{space 1}       10{col 53}{text} {col 54}{c |}
{res}{col 1}{text}  profession{col 14}{c |}{space 1}       21{col 27}{space 1}        1{col 39}{result}{space 1}       20{col 53}{text} {col 54}{c |}
{res}{col 1}{text}         dep{col 14}{c |}{space 1}       75{col 27}{space 1}       75{col 39}{result}{space 1}        0{col 53}{text}*{col 54}{c |}
{res}{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}
{txt}added scalar:
             e(mean_y) =  {res}.04881953
{browse `"D:\Dropbox\SVLACHOS\Research\Malgre_nous\Replication_files\Results"' :dir}{com} : {txt}{stata `"seeout using "D:\Dropbox\SVLACHOS\Research\Malgre_nous\Replication_files\Results\abst80.txt""':seeout}

{com}. 
. foreach var in rrw_l1986 rrw_p1988r1 rrw_l1993 rrw_e1994 rrw_p1995r1{c -(}
{txt}  2{com}.         reghdfe `var' i.age i.sexe, a(revenu profession dep) cluster(dep)
{txt}  3{com}.         estimates store v80`var'
{txt}  4{com}.         qui sum `var' if e(sample)
{txt}  5{com}.         scalar mean_y=r(mean)
{txt}  6{com}.         estadd scalar mean_y
{txt}  7{com}.         outreg2 using "$results\rrw80", nocons dec(3) level(95)
{txt}  8{com}. {c )-}
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 7 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}     2,789
{txt}Absorbing 3 HDFE groups{col 51}F({res}   4{txt},{res}     72{txt}){col 67}= {res}      1.69
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.1609
{txt}{col 51}R-squared{col 67}= {res}    0.0567
{txt}{col 51}Adj R-squared{col 67}= {res}    0.0223
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0031
{txt}{col 1}Number of clusters ({res}dep{txt}) {col 30}= {res}        73{txt}{col 51}Root MSE{col 67}= {res}    0.1812

{txt}{ralign 96:(Std. err. adjusted for {res:73} clusters in dep)}
{hline 31}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 32}{c |}{col 44}    Robust
{col 1}                     rrw_l1986{col 32}{c |} Coefficient{col 44}  std. err.{col 56}      t{col 64}   P>|t|{col 72}     [95% con{col 85}f. interval]
{hline 31}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 27}age {c |}
{space 3}\\ Aged 35 to 49 years old  {c |}{col 32}{res}{space 2} -.002142{col 44}{space 2} .0098208{col 55}{space 1}   -0.22{col 64}{space 3}0.828{col 72}{space 4}-.0217194{col 85}{space 3} .0174354
{txt}[0.3em] -- 50 to 64 years old  {c |}{col 32}{res}{space 2}-.0011661{col 44}{space 2} .0085918{col 55}{space 1}   -0.14{col 64}{space 3}0.892{col 72}{space 4}-.0182935{col 85}{space 3} .0159612
{txt}{space 6}[0.3em] -- 65 and above  {c |}{col 32}{res}{space 2} .0087333{col 44}{space 2}  .010852{col 55}{space 1}    0.80{col 64}{space 3}0.424{col 72}{space 4}-.0128998{col 85}{space 3} .0303665
{txt}{space 30} {c |}
{space 26}sexe {c |}
{space 15}[0.3em] Female  {c |}{col 32}{res}{space 2}-.0199328{col 44}{space 2} .0094196{col 55}{space 1}   -2.12{col 64}{space 3}0.038{col 72}{space 4}-.0387105{col 85}{space 3}-.0011551
{txt}{space 25}_cons {c |}{col 32}{res}{space 2} .0438866{col 44}{space 2} .0063423{col 55}{space 1}    6.92{col 64}{space 3}0.000{col 72}{space 4} .0312435{col 85}{space 3} .0565297
{txt}{hline 31}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{res}{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}      revenu{col 14}{c |}{space 1}       10{col 27}{space 1}        0{col 39}{result}{space 1}       10{col 53}{text} {col 54}{c |}
{res}{col 1}{text}  profession{col 14}{c |}{space 1}       13{col 27}{space 1}        1{col 39}{result}{space 1}       12{col 53}{text} {col 54}{c |}
{res}{col 1}{text}         dep{col 14}{c |}{space 1}       73{col 27}{space 1}       73{col 39}{result}{space 1}        0{col 53}{text}*{col 54}{c |}
{res}{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}
{txt}added scalar:
             e(mean_y) =  {res}.03477949
{browse `"D:\Dropbox\SVLACHOS\Research\Malgre_nous\Replication_files\Results"' :dir}{com} : {txt}{stata `"seeout using "D:\Dropbox\SVLACHOS\Research\Malgre_nous\Replication_files\Results\rrw80.txt""':seeout}
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 7 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}     2,641
{txt}Absorbing 3 HDFE groups{col 51}F({res}   4{txt},{res}     72{txt}){col 67}= {res}      3.40
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0133
{txt}{col 51}R-squared{col 67}= {res}    0.0582
{txt}{col 51}Adj R-squared{col 67}= {res}    0.0219
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0056
{txt}{col 1}Number of clusters ({res}dep{txt}) {col 30}= {res}        73{txt}{col 51}Root MSE{col 67}= {res}    0.3016

{txt}{ralign 96:(Std. err. adjusted for {res:73} clusters in dep)}
{hline 31}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 32}{c |}{col 44}    Robust
{col 1}                   rrw_p1988r1{col 32}{c |} Coefficient{col 44}  std. err.{col 56}      t{col 64}   P>|t|{col 72}     [95% con{col 85}f. interval]
{hline 31}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 27}age {c |}
{space 3}\\ Aged 35 to 49 years old  {c |}{col 32}{res}{space 2}-.0095773{col 44}{space 2} .0175459{col 55}{space 1}   -0.55{col 64}{space 3}0.587{col 72}{space 4}-.0445543{col 85}{space 3} .0253997
{txt}[0.3em] -- 50 to 64 years old  {c |}{col 32}{res}{space 2}-.0110204{col 44}{space 2} .0162797{col 55}{space 1}   -0.68{col 64}{space 3}0.501{col 72}{space 4}-.0434735{col 85}{space 3} .0214327
{txt}{space 6}[0.3em] -- 65 and above  {c |}{col 32}{res}{space 2} .0026093{col 44}{space 2} .0179372{col 55}{space 1}    0.15{col 64}{space 3}0.885{col 72}{space 4}-.0331479{col 85}{space 3} .0383665
{txt}{space 30} {c |}
{space 26}sexe {c |}
{space 15}[0.3em] Female  {c |}{col 32}{res}{space 2}-.0481291{col 44}{space 2} .0146547{col 55}{space 1}   -3.28{col 64}{space 3}0.002{col 72}{space 4}-.0773427{col 85}{space 3}-.0189154
{txt}{space 25}_cons {c |}{col 32}{res}{space 2} .1325443{col 44}{space 2} .0111427{col 55}{space 1}   11.90{col 64}{space 3}0.000{col 72}{space 4} .1103319{col 85}{space 3} .1547568
{txt}{hline 31}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{res}{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}      revenu{col 14}{c |}{space 1}       10{col 27}{space 1}        0{col 39}{result}{space 1}       10{col 53}{text} {col 54}{c |}
{res}{col 1}{text}  profession{col 14}{c |}{space 1}       13{col 27}{space 1}        1{col 39}{result}{space 1}       12{col 53}{text} {col 54}{c |}
{res}{col 1}{text}         dep{col 14}{c |}{space 1}       73{col 27}{space 1}       73{col 39}{result}{space 1}        0{col 53}{text}*{col 54}{c |}
{res}{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}
{txt}added scalar:
             e(mean_y) =  {res}.10374858
{browse `"D:\Dropbox\SVLACHOS\Research\Malgre_nous\Replication_files\Results"' :dir}{com} : {txt}{stata `"seeout using "D:\Dropbox\SVLACHOS\Research\Malgre_nous\Replication_files\Results\rrw80.txt""':seeout}
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 8 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}     2,619
{txt}Absorbing 3 HDFE groups{col 51}F({res}   4{txt},{res}     74{txt}){col 67}= {res}      1.37
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.2525
{txt}{col 51}R-squared{col 67}= {res}    0.0678
{txt}{col 51}Adj R-squared{col 67}= {res}    0.0277
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0023
{txt}{col 1}Number of clusters ({res}dep{txt}) {col 30}= {res}        75{txt}{col 51}Root MSE{col 67}= {res}    0.1926

{txt}{ralign 96:(Std. err. adjusted for {res:75} clusters in dep)}
{hline 31}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 32}{c |}{col 44}    Robust
{col 1}                     rrw_l1993{col 32}{c |} Coefficient{col 44}  std. err.{col 56}      t{col 64}   P>|t|{col 72}     [95% con{col 85}f. interval]
{hline 31}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 27}age {c |}
{space 3}\\ Aged 35 to 49 years old  {c |}{col 32}{res}{space 2} -.000627{col 44}{space 2} .0091346{col 55}{space 1}   -0.07{col 64}{space 3}0.945{col 72}{space 4}-.0188281{col 85}{space 3} .0175742
{txt}[0.3em] -- 50 to 64 years old  {c |}{col 32}{res}{space 2} .0095849{col 44}{space 2} .0136476{col 55}{space 1}    0.70{col 64}{space 3}0.485{col 72}{space 4}-.0176086{col 85}{space 3} .0367783
{txt}{space 6}[0.3em] -- 65 and above  {c |}{col 32}{res}{space 2}-.0036888{col 44}{space 2} .0145456{col 55}{space 1}   -0.25{col 64}{space 3}0.801{col 72}{space 4}-.0326716{col 85}{space 3} .0252939
{txt}{space 30} {c |}
{space 26}sexe {c |}
{space 15}[0.3em] Female  {c |}{col 32}{res}{space 2}-.0185203{col 44}{space 2} .0081933{col 55}{space 1}   -2.26{col 64}{space 3}0.027{col 72}{space 4}-.0348457{col 85}{space 3}-.0021948
{txt}{space 25}_cons {c |}{col 32}{res}{space 2} .0476237{col 44}{space 2} .0073689{col 55}{space 1}    6.46{col 64}{space 3}0.000{col 72}{space 4} .0329408{col 85}{space 3} .0623066
{txt}{hline 31}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{res}{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}      revenu{col 14}{c |}{space 1}       10{col 27}{space 1}        0{col 39}{result}{space 1}       10{col 53}{text} {col 54}{c |}
{res}{col 1}{text}  profession{col 14}{c |}{space 1}       21{col 27}{space 1}        1{col 39}{result}{space 1}       20{col 53}{text} {col 54}{c |}
{res}{col 1}{text}         dep{col 14}{c |}{space 1}       75{col 27}{space 1}       75{col 39}{result}{space 1}        0{col 53}{text}*{col 54}{c |}
{res}{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}
{txt}added scalar:
             e(mean_y) =  {res}.03970981
{browse `"D:\Dropbox\SVLACHOS\Research\Malgre_nous\Replication_files\Results"' :dir}{com} : {txt}{stata `"seeout using "D:\Dropbox\SVLACHOS\Research\Malgre_nous\Replication_files\Results\rrw80.txt""':seeout}
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 8 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}     2,515
{txt}Absorbing 3 HDFE groups{col 51}F({res}   4{txt},{res}     74{txt}){col 67}= {res}      3.10
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0206
{txt}{col 51}R-squared{col 67}= {res}    0.0632
{txt}{col 51}Adj R-squared{col 67}= {res}    0.0211
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0038
{txt}{col 1}Number of clusters ({res}dep{txt}) {col 30}= {res}        75{txt}{col 51}Root MSE{col 67}= {res}    0.2261

{txt}{ralign 96:(Std. err. adjusted for {res:75} clusters in dep)}
{hline 31}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 32}{c |}{col 44}    Robust
{col 1}                     rrw_e1994{col 32}{c |} Coefficient{col 44}  std. err.{col 56}      t{col 64}   P>|t|{col 72}     [95% con{col 85}f. interval]
{hline 31}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 27}age {c |}
{space 3}\\ Aged 35 to 49 years old  {c |}{col 32}{res}{space 2}-.0105001{col 44}{space 2} .0101371{col 55}{space 1}   -1.04{col 64}{space 3}0.304{col 72}{space 4}-.0306987{col 85}{space 3} .0096986
{txt}[0.3em] -- 50 to 64 years old  {c |}{col 32}{res}{space 2}-.0014357{col 44}{space 2} .0113796{col 55}{space 1}   -0.13{col 64}{space 3}0.900{col 72}{space 4}-.0241102{col 85}{space 3} .0212387
{txt}{space 6}[0.3em] -- 65 and above  {c |}{col 32}{res}{space 2} -.006074{col 44}{space 2} .0133002{col 55}{space 1}   -0.46{col 64}{space 3}0.649{col 72}{space 4}-.0325751{col 85}{space 3} .0204272
{txt}{space 30} {c |}
{space 26}sexe {c |}
{space 15}[0.3em] Female  {c |}{col 32}{res}{space 2}-.0306279{col 44}{space 2} .0100865{col 55}{space 1}   -3.04{col 64}{space 3}0.003{col 72}{space 4}-.0507257{col 85}{space 3}  -.01053
{txt}{space 25}_cons {c |}{col 32}{res}{space 2} .0745899{col 44}{space 2} .0068998{col 55}{space 1}   10.81{col 64}{space 3}0.000{col 72}{space 4} .0608418{col 85}{space 3} .0883381
{txt}{hline 31}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{res}{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}      revenu{col 14}{c |}{space 1}       10{col 27}{space 1}        0{col 39}{result}{space 1}       10{col 53}{text} {col 54}{c |}
{res}{col 1}{text}  profession{col 14}{c |}{space 1}       21{col 27}{space 1}        1{col 39}{result}{space 1}       20{col 53}{text} {col 54}{c |}
{res}{col 1}{text}         dep{col 14}{c |}{space 1}       75{col 27}{space 1}       75{col 39}{result}{space 1}        0{col 53}{text}*{col 54}{c |}
{res}{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}
{txt}added scalar:
             e(mean_y) =  {res}.05526839
{browse `"D:\Dropbox\SVLACHOS\Research\Malgre_nous\Replication_files\Results"' :dir}{com} : {txt}{stata `"seeout using "D:\Dropbox\SVLACHOS\Research\Malgre_nous\Replication_files\Results\rrw80.txt""':seeout}
{res}{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 8 iterations)
{res}
{txt}HDFE Linear regression{col 51}Number of obs{col 67}= {res}     2,499
{txt}Absorbing 3 HDFE groups{col 51}F({res}   4{txt},{res}     74{txt}){col 67}= {res}      4.28
{txt}Statistics robust to heteroskedasticity{col 51}Prob > F{col 67}= {res}    0.0036
{txt}{col 51}R-squared{col 67}= {res}    0.0972
{txt}{col 51}Adj R-squared{col 67}= {res}    0.0564
{txt}{col 51}Within R-sq.{col 67}= {res}    0.0118
{txt}{col 1}Number of clusters ({res}dep{txt}) {col 30}= {res}        75{txt}{col 51}Root MSE{col 67}= {res}    0.3130

{txt}{ralign 96:(Std. err. adjusted for {res:75} clusters in dep)}
{hline 31}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 32}{c |}{col 44}    Robust
{col 1}                   rrw_p1995r1{col 32}{c |} Coefficient{col 44}  std. err.{col 56}      t{col 64}   P>|t|{col 72}     [95% con{col 85}f. interval]
{hline 31}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 27}age {c |}
{space 3}\\ Aged 35 to 49 years old  {c |}{col 32}{res}{space 2}-.0315668{col 44}{space 2} .0214135{col 55}{space 1}   -1.47{col 64}{space 3}0.145{col 72}{space 4}-.0742341{col 85}{space 3} .0111006
{txt}[0.3em] -- 50 to 64 years old  {c |}{col 32}{res}{space 2}-.0477797{col 44}{space 2} .0211414{col 55}{space 1}   -2.26{col 64}{space 3}0.027{col 72}{space 4}-.0899048{col 85}{space 3}-.0056546
{txt}{space 6}[0.3em] -- 65 and above  {c |}{col 32}{res}{space 2}-.0764467{col 44}{space 2} .0248197{col 55}{space 1}   -3.08{col 64}{space 3}0.003{col 72}{space 4}-.1259011{col 85}{space 3}-.0269924
{txt}{space 30} {c |}
{space 26}sexe {c |}
{space 15}[0.3em] Female  {c |}{col 32}{res}{space 2}-.0500266{col 44}{space 2} .0166191{col 55}{space 1}   -3.01{col 64}{space 3}0.004{col 72}{space 4}-.0831408{col 85}{space 3}-.0169124
{txt}{space 25}_cons {c |}{col 32}{res}{space 2}  .179701{col 44}{space 2} .0169376{col 55}{space 1}   10.61{col 64}{space 3}0.000{col 72}{space 4} .1459522{col 85}{space 3} .2134498
{txt}{hline 31}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Absorbed degrees of freedom:
{res}{col 1}{text}{hline 13}{c TT}{hline 12}{hline 12}{hline 14}{hline 1}{c TRC}
{col 1}{text} Absorbed FE{col 14}{c |} Categories{col 27} - Redundant{col 39}  = Num. Coefs{col 54}{c |}
{res}{col 1}{text}{hline 13}{c +}{hline 12}{hline 12}{hline 14}{hline 1}{c RT}
{col 1}{text}      revenu{col 14}{c |}{space 1}       10{col 27}{space 1}        0{col 39}{result}{space 1}       10{col 53}{text} {col 54}{c |}
{res}{col 1}{text}  profession{col 14}{c |}{space 1}       21{col 27}{space 1}        1{col 39}{result}{space 1}       20{col 53}{text} {col 54}{c |}
{res}{col 1}{text}         dep{col 14}{c |}{space 1}       75{col 27}{space 1}       75{col 39}{result}{space 1}        0{col 53}{text}*{col 54}{c |}
{res}{col 1}{text}{hline 13}{c BT}{hline 12}{hline 12}{hline 14}{hline 1}{c BRC}
* = FE nested within cluster; treated as redundant for DoF computation
{res}
{txt}added scalar:
             e(mean_y) =  {res}.11764706
{browse `"D:\Dropbox\SVLACHOS\Research\Malgre_nous\Replication_files\Results"' :dir}{com} : {txt}{stata `"seeout using "D:\Dropbox\SVLACHOS\Research\Malgre_nous\Replication_files\Results\rrw80.txt""':seeout}

{com}. 
. ********************
. ***** 2. GRAPH *****
. ********************
. 
. // Abstention graph
. 
. insheet using "$results\abst60.txt", clear
{txt}(6 vars, 16 obs)

{com}. drop if _n==1
{txt}(1 observation deleted)

{com}. g id=_n
{txt}
{com}. forvalues i=2(1)6{c -(}
{txt}  2{com}.         rename v`i' `= strtoname(v`i'[1])'_str
{txt}  3{com}. {c )-}
{res}{txt}
{com}. save $results\tmp, replace
{txt}{p 0 4 2}
(file {bf}
D:\Dropbox\SVLACHOS\Research\Malgre_nous\Replication_files\Results\tmp.dta{rm}
not found)
{p_end}
{p 0 4 2}
file {bf}
D:\Dropbox\SVLACHOS\Research\Malgre_nous\Replication_files\Results\tmp.dta{rm}
saved
{p_end}

{com}. 
. insheet using "$results\abst70.txt", clear
{txt}(6 vars, 16 obs)

{com}. drop if _n==1
{txt}(1 observation deleted)

{com}. g id=_n
{txt}
{com}. forvalues i=2(1)6{c -(}
{txt}  2{com}.         rename v`i' `= strtoname(v`i'[1])'_str
{txt}  3{com}. {c )-}
{res}{txt}
{com}. merge 1:1 id v1 using $results\tmp
{res}
{txt}{col 5}Result{col 33}Number of obs
{col 5}{hline 41}
{col 5}Not matched{col 30}{res}               0
{txt}{col 5}Matched{col 30}{res}              15{txt}  (_merge==3)
{col 5}{hline 41}

{com}. drop _merge
{txt}
{com}. save $results\tmp, replace
{txt}{p 0 4 2}
file {bf}
D:\Dropbox\SVLACHOS\Research\Malgre_nous\Replication_files\Results\tmp.dta{rm}
saved
{p_end}

{com}. 
. insheet using "$results\abst80.txt", clear
{txt}(6 vars, 16 obs)

{com}. drop if _n==1
{txt}(1 observation deleted)

{com}. g id=_n
{txt}
{com}. forvalues i=2(1)6{c -(}
{txt}  2{com}.         rename v`i' `= strtoname(v`i'[1])'_str
{txt}  3{com}. {c )-}
{res}{txt}
{com}. merge 1:1 id v1 using $results\tmp
{res}
{txt}{col 5}Result{col 33}Number of obs
{col 5}{hline 41}
{col 5}Not matched{col 30}{res}               0
{txt}{col 5}Matched{col 30}{res}              15{txt}  (_merge==3)
{col 5}{hline 41}

{com}. drop _merge
{txt}
{com}. save $results\tmp, replace
{txt}{p 0 4 2}
file {bf}
D:\Dropbox\SVLACHOS\Research\Malgre_nous\Replication_files\Results\tmp.dta{rm}
saved
{p_end}

{com}. save $results\tmp2, replace
{txt}{p 0 4 2}
(file {bf}
D:\Dropbox\SVLACHOS\Research\Malgre_nous\Replication_files\Results\tmp2.dta{rm}
not found)
{p_end}
{p 0 4 2}
file {bf}
D:\Dropbox\SVLACHOS\Research\Malgre_nous\Replication_files\Results\tmp2.dta{rm}
saved
{p_end}

{com}. 
. drop if vote_l1958=="vote_l1958"
{txt}(1 observation deleted)

{com}. rename v1 margins
{res}{txt}
{com}. drop if margins=="VARIABLES"
{txt}(0 observations deleted)

{com}. drop if margins==""
{txt}(6 observations deleted)

{com}. drop if _n>4
{txt}(4 observations deleted)

{com}. 
. rename *_str *
{res}{txt}
{com}. reshape long vote_, i(margins) j(annee) string
{txt}(j = e1994 l1958 l1962r1 l1962r2 l1973 l1978r1 l1978r2 l1986 l1993 p1974r1 p1974r2 p1988r1 p1995r1 r1958 r1962)

Data{col 36}Wide{col 43}->{col 48}Long
{hline 77}
Number of observations     {res}           4   {txt}->   {res}60          
{txt}Number of variables        {res}          17   {txt}->   {res}4           
{txt}j variable (15 values)                    ->   {res}annee
{txt}xij variables:
   {res}vote_e1994 vote_l1958 ... vote_r1962   {txt}->   {res}vote_
{txt}{hline 77}

{com}. 
. rename vote_ beta
{res}{txt}
{com}. replace beta = subinstr(beta, "*", "", .) 
{txt}(39 real changes made)

{com}. destring beta, replace
{txt}beta: all characters numeric; {res}replaced {txt}as {res}double
{txt}
{com}. 
. save $results\tmp, replace
{txt}{p 0 4 2}
file {bf}
D:\Dropbox\SVLACHOS\Research\Malgre_nous\Replication_files\Results\tmp.dta{rm}
saved
{p_end}

{com}. 
. use $results\tmp2, clear
{txt}
{com}. 
. drop if vote_l1958=="vote_l1958"
{txt}(1 observation deleted)

{com}. rename v1 margins
{res}{txt}
{com}. drop if margins=="VARIABLES"
{txt}(0 observations deleted)

{com}. replace margins=margins[_n-1] if margins==""
{txt}(5 real changes made)

{com}. drop if margins==""
{txt}(1 observation deleted)

{com}. drop if _n==1 | _n==3 | _n==5 | _n==7 | _n==9 | _n==11 | _n==13
{txt}(7 observations deleted)

{com}. drop if _n>4
{txt}(2 observations deleted)

{com}. 
. rename *_str *
{res}{txt}
{com}. reshape long vote_, i(margins) j(annee) string
{txt}(j = e1994 l1958 l1962r1 l1962r2 l1973 l1978r1 l1978r2 l1986 l1993 p1974r1 p1974r2 p1988r1 p1995r1 r1958 r1962)

Data{col 36}Wide{col 43}->{col 48}Long
{hline 77}
Number of observations     {res}           4   {txt}->   {res}60          
{txt}Number of variables        {res}          17   {txt}->   {res}4           
{txt}j variable (15 values)                    ->   {res}annee
{txt}xij variables:
   {res}vote_e1994 vote_l1958 ... vote_r1962   {txt}->   {res}vote_
{txt}{hline 77}

{com}. 
. rename vote_ se
{res}{txt}
{com}. replace se = subinstr(se, "(", "", .) 
{txt}(60 real changes made)

{com}. replace se = subinstr(se, ")", "", .) 
{txt}(60 real changes made)

{com}. destring se, replace
{txt}se: all characters numeric; {res}replaced {txt}as {res}double
{txt}
{com}. 
. merge 1:1 annee margins using $results\tmp
{res}
{txt}{col 5}Result{col 33}Number of obs
{col 5}{hline 41}
{col 5}Not matched{col 30}{res}               0
{txt}{col 5}Matched{col 30}{res}              60{txt}  (_merge==3)
{col 5}{hline 41}

{com}. drop _merge id
{txt}
{com}. save $results\tmp, replace
{txt}{p 0 4 2}
file {bf}
D:\Dropbox\SVLACHOS\Research\Malgre_nous\Replication_files\Results\tmp.dta{rm}
saved
{p_end}

{com}. 
. use $results\tmp, clear
{txt}
{com}. 
. g year=substr(annee, 2, 4)
{txt}
{com}. g election=substr(annee, 1, 1)
{txt}
{com}. g round=substr(annee, strlen(annee)-1, 2)
{txt}
{com}. g strlen=strlen(annee)
{txt}
{com}. 
. replace election="Ref." if election=="r"
{txt}variable {bf}{res}election{sf}{txt} was {bf}{res}str1{sf}{txt} now {bf}{res}str4{sf}
{txt}(8 real changes made)

{com}. replace election="Parl." if election=="l"
{txt}variable {bf}{res}election{sf}{txt} was {bf}{res}str4{sf}{txt} now {bf}{res}str5{sf}
{txt}(32 real changes made)

{com}. replace election="Pres." if election=="p"
{txt}(16 real changes made)

{com}. replace election="Euro." if election=="e"
{txt}(4 real changes made)

{com}. 
. replace round=" ("+upper(round)+")"
{txt}variable {bf}{res}round{sf}{txt} was {bf}{res}str2{sf}{txt} now {bf}{res}str5{sf}
{txt}(60 real changes made)

{com}. replace round="" if strlen==5
{txt}(28 real changes made)

{com}. 
. g y=year+" "+election+round
{txt}
{com}. replace year=election+round+" "+year
{txt}variable {bf}{res}year{sf}{txt} was {bf}{res}str4{sf}{txt} now {bf}{res}str15{sf}
{txt}(60 real changes made)

{com}. 
. drop election round year strlen
{txt}
{com}. 
. gen up95 = beta + invnormal(0.975)*se // 
{txt}
{com}. gen lo95 = beta - invnormal(0.975)*se
{txt}
{com}. 
. encode y, g(year_enc)
{txt}
{com}. 
. replace margins="Aged 35 to 49" if margins=="2bn.age"
{txt}(0 real changes made)

{com}. replace margins="Aged 50 to 64" if margins=="3.age"
{txt}(15 real changes made)

{com}. replace margins="Aged 65 and above" if margins=="4.age"
{txt}(15 real changes made)

{com}. replace margins="Female" if margins=="2.sexe"
{txt}(15 real changes made)

{com}. encode margins, g(var_enc)
{txt}
{com}. 
. xtset var_enc year_enc
{res}
{col 1}{txt:Panel variable: }{res:var_enc}{txt: (strongly balanced)}
{p 1 16 2}{txt:Time variable: }{res:year_enc}{txt:, }{res:{bind:1}}{txt: to }{res:{bind:15}}{p_end}
{txt}{col 10}Delta: {res}1 unit
{txt}
{com}. 
. tab var_enc

          {txt}var_enc {c |}      Freq.     Percent        Cum.
{hline 18}{c +}{hline 35}
            2.age {c |}{res}         15       25.00       25.00
{txt}    Aged 50 to 64 {c |}{res}         15       25.00       50.00
{txt}Aged 65 and above {c |}{res}         15       25.00       75.00
{txt}           Female {c |}{res}         15       25.00      100.00
{txt}{hline 18}{c +}{hline 35}
            Total {c |}{res}         60      100.00
{txt}
{com}. 
. format beta %9.2f
{txt}
{com}. 
. twoway (scatter beta year_enc if var_enc==1, mcolor(navy) connect(line) lcolor(navy)) ///
>         (line up95 year_enc if var_enc==1, lcolor(navy) lpattern("......-")) ///
>         (line lo95 year_enc if var_enc==1, lcolor(navy) lpattern("......-")) ///
>         (scatter beta year_enc if var_enc==2, mcolor(maroon) msymbol(S) connect(line) lcolor(maroon)) ///
>         (line up95 year_enc if var_enc==2, lcolor(maroon) lpattern("......-")) ///
>         (line lo95 year_enc if var_enc==2, lcolor(maroon) lpattern("......-")) ///
>         (scatter beta year_enc if var_enc==3, mcolor(green) msymbol(T) connect(line) lcolor(green)) ///
>         (line up95 year_enc if var_enc==3, lcolor(green) lpattern("......-")) ///
>         (line lo95 year_enc if var_enc==3, lcolor(green) lpattern("......-")) ///
>         (scatter beta year_enc if var_enc==4, mcolor(purple) msymbol(D) connect(line) lcolor(purple)) ///
>         (line up95 year_enc if var_enc==4, lcolor(purple) lpattern("......-")) ///
>         (line lo95 year_enc if var_enc==4, lcolor(purple) lpattern("......-"))  ///
>         , ylabel(-.3(.15).15, labsize(vsmall) format(%3.2f) angle(0)) yline(0, lpattern(dash)) yscale(r(-.39 .195)) /// 
>         xlabel(1(1)15, labsize(vsmall) angle(30) valuelabel) ///
>         ytitle("OLS Coefficient (95% C.I.)", size(small)) xtitle("") ///
>         leg(lab(1 "Aged 35 to 49") lab(4 "Aged 50 to 64") lab(7 "Aged 65 and above") lab(10 "Female") r(2) pos(7) ring(0) order(10 1 4 7) region(col(white)) symx(*0.5) size(vsmall)) ///
>         graphregion(color(white)) subtitle("Abstention", ring(0))
{res}{txt}
{com}. graph export "$results\EEREV-D-21-00004_FigureC2_abst.png", replace width(3600) height(3600)
{txt}{p 0 4 2}
file {bf}
D:\Dropbox\SVLACHOS\Research\Malgre_nous\Replication_files\Results\EEREV-D-21-00004_FigureC2_abst.png{rm}
saved as
PNG
format
{p_end}

{com}. 
. // Rad right graph
. 
. insheet using "$results\rrw70.txt", clear
{txt}(3 vars, 16 obs)

{com}. drop if _n==1
{txt}(1 observation deleted)

{com}. g id=_n
{txt}
{com}. forvalues i=2(1)3{c -(}
{txt}  2{com}.         rename v`i' `= strtoname(v`i'[1])'_str
{txt}  3{com}. {c )-}
{res}{txt}
{com}. save $results\tmp, replace
{txt}{p 0 4 2}
file {bf}
D:\Dropbox\SVLACHOS\Research\Malgre_nous\Replication_files\Results\tmp.dta{rm}
saved
{p_end}

{com}. 
. insheet using "$results\rrw80.txt", clear
{txt}(6 vars, 16 obs)

{com}. drop if _n==1
{txt}(1 observation deleted)

{com}. g id=_n
{txt}
{com}. forvalues i=2(1)6{c -(}
{txt}  2{com}.         rename v`i' `= strtoname(v`i'[1])'_str
{txt}  3{com}. {c )-}
{res}{txt}
{com}. merge 1:1 id v1 using $results\tmp
{res}
{txt}{col 5}Result{col 33}Number of obs
{col 5}{hline 41}
{col 5}Not matched{col 30}{res}               0
{txt}{col 5}Matched{col 30}{res}              15{txt}  (_merge==3)
{col 5}{hline 41}

{com}. drop _merge
{txt}
{com}. save $results\tmp, replace
{txt}{p 0 4 2}
file {bf}
D:\Dropbox\SVLACHOS\Research\Malgre_nous\Replication_files\Results\tmp.dta{rm}
saved
{p_end}

{com}. save $results\tmp2, replace
{txt}{p 0 4 2}
file {bf}
D:\Dropbox\SVLACHOS\Research\Malgre_nous\Replication_files\Results\tmp2.dta{rm}
saved
{p_end}

{com}. 
. drop if rrw_l1986_str=="rrw_l1986"
{txt}(1 observation deleted)

{com}. rename v1 margins
{res}{txt}
{com}. drop if margins=="VARIABLES"
{txt}(0 observations deleted)

{com}. drop if margins==""
{txt}(6 observations deleted)

{com}. drop if _n>4
{txt}(4 observations deleted)

{com}. 
. rename *_str *
{res}{txt}
{com}. reshape long rrw_, i(margins) j(annee) string
{txt}(j = e1994 l1978r1 l1986 l1993 p1974r1 p1988r1 p1995r1)

Data{col 36}Wide{col 43}->{col 48}Long
{hline 77}
Number of observations     {res}           4   {txt}->   {res}28          
{txt}Number of variables        {res}           9   {txt}->   {res}4           
{txt}j variable (7 values)                     ->   {res}annee
{txt}xij variables:
  {res}rrw_e1994 rrw_l1978r1 ... rrw_p1995r1   {txt}->   {res}rrw_
{txt}{hline 77}

{com}. 
. rename rrw_ beta
{res}{txt}
{com}. replace beta = subinstr(beta, "*", "", .) 
{txt}(9 real changes made)

{com}. destring beta, replace
{txt}beta: all characters numeric; {res}replaced {txt}as {res}double
{txt}
{com}. 
. save $results\tmp, replace
{txt}{p 0 4 2}
file {bf}
D:\Dropbox\SVLACHOS\Research\Malgre_nous\Replication_files\Results\tmp.dta{rm}
saved
{p_end}

{com}. 
. use $results\tmp2, clear
{txt}
{com}. 
. drop if rrw_l1986_str=="rrw_l1986"
{txt}(1 observation deleted)

{com}. rename v1 margins
{res}{txt}
{com}. drop if margins=="VARIABLES"
{txt}(0 observations deleted)

{com}. replace margins=margins[_n-1] if margins==""
{txt}(5 real changes made)

{com}. drop if margins==""
{txt}(1 observation deleted)

{com}. drop if _n==1 | _n==3 | _n==5 | _n==7 | _n==9 | _n==11 | _n==13
{txt}(7 observations deleted)

{com}. drop if _n>4
{txt}(2 observations deleted)

{com}. 
. rename *_str *
{res}{txt}
{com}. reshape long rrw_, i(margins) j(annee) string
{txt}(j = e1994 l1978r1 l1986 l1993 p1974r1 p1988r1 p1995r1)

Data{col 36}Wide{col 43}->{col 48}Long
{hline 77}
Number of observations     {res}           4   {txt}->   {res}28          
{txt}Number of variables        {res}           9   {txt}->   {res}4           
{txt}j variable (7 values)                     ->   {res}annee
{txt}xij variables:
  {res}rrw_e1994 rrw_l1978r1 ... rrw_p1995r1   {txt}->   {res}rrw_
{txt}{hline 77}

{com}. 
. rename rrw_ se
{res}{txt}
{com}. replace se = subinstr(se, "(", "", .) 
{txt}(28 real changes made)

{com}. replace se = subinstr(se, ")", "", .) 
{txt}(28 real changes made)

{com}. destring se, replace
{txt}se: all characters numeric; {res}replaced {txt}as {res}double
{txt}
{com}. 
. merge 1:1 annee margins using $results\tmp
{res}
{txt}{col 5}Result{col 33}Number of obs
{col 5}{hline 41}
{col 5}Not matched{col 30}{res}               0
{txt}{col 5}Matched{col 30}{res}              28{txt}  (_merge==3)
{col 5}{hline 41}

{com}. drop _merge id
{txt}
{com}. save $results\tmp, replace
{txt}{p 0 4 2}
file {bf}
D:\Dropbox\SVLACHOS\Research\Malgre_nous\Replication_files\Results\tmp.dta{rm}
saved
{p_end}

{com}. 
. use $results\tmp, clear
{txt}
{com}. 
. g year=substr(annee, 2, 4)
{txt}
{com}. g election=substr(annee, 1, 1)
{txt}
{com}. g round=substr(annee, strlen(annee)-1, 2)
{txt}
{com}. g strlen=strlen(annee)
{txt}
{com}. 
. replace election="Ref." if election=="r"
{txt}(0 real changes made)

{com}. replace election="Parl." if election=="l"
{txt}variable {bf}{res}election{sf}{txt} was {bf}{res}str1{sf}{txt} now {bf}{res}str5{sf}
{txt}(12 real changes made)

{com}. replace election="Pres." if election=="p"
{txt}(12 real changes made)

{com}. replace election="Euro." if election=="e"
{txt}(4 real changes made)

{com}. 
. replace round=" ("+upper(round)+")"
{txt}variable {bf}{res}round{sf}{txt} was {bf}{res}str2{sf}{txt} now {bf}{res}str5{sf}
{txt}(28 real changes made)

{com}. replace round="" if strlen==5
{txt}(12 real changes made)

{com}. 
. g y=year+" "+election+round
{txt}
{com}. replace year=election+round+" "+year
{txt}variable {bf}{res}year{sf}{txt} was {bf}{res}str4{sf}{txt} now {bf}{res}str15{sf}
{txt}(28 real changes made)

{com}. 
. drop election round year strlen
{txt}
{com}. 
. gen up95 = beta + invnormal(0.975)*se // 
{txt}
{com}. gen lo95 = beta - invnormal(0.975)*se
{txt}
{com}. 
. encode y, g(year_enc)
{txt}
{com}. 
. replace margins="Aged 35 to 49" if margins=="2bn.age"
{txt}(0 real changes made)

{com}. replace margins="Aged 50 to 64" if margins=="3.age"
{txt}(7 real changes made)

{com}. replace margins="Aged 65 and above" if margins=="4.age"
{txt}(7 real changes made)

{com}. replace margins="Female" if margins=="2.sexe"
{txt}(7 real changes made)

{com}. encode margins, g(var_enc)
{txt}
{com}. 
. xtset var_enc year_enc
{res}
{col 1}{txt:Panel variable: }{res:var_enc}{txt: (strongly balanced)}
{p 1 16 2}{txt:Time variable: }{res:year_enc}{txt:, }{res:{bind:1}}{txt: to }{res:{bind:7}}{p_end}
{txt}{col 10}Delta: {res}1 unit
{txt}
{com}. 
. tab var_enc

          {txt}var_enc {c |}      Freq.     Percent        Cum.
{hline 18}{c +}{hline 35}
            2.age {c |}{res}          7       25.00       25.00
{txt}    Aged 50 to 64 {c |}{res}          7       25.00       50.00
{txt}Aged 65 and above {c |}{res}          7       25.00       75.00
{txt}           Female {c |}{res}          7       25.00      100.00
{txt}{hline 18}{c +}{hline 35}
            Total {c |}{res}         28      100.00
{txt}
{com}. 
. format beta %9.2f
{txt}
{com}. 
. twoway (scatter beta year_enc if var_enc==1, mcolor(navy) connect(line) lcolor(navy)) ///
>         (line up95 year_enc if var_enc==1, lcolor(navy) lpattern("......-")) ///
>         (line lo95 year_enc if var_enc==1, lcolor(navy) lpattern("......-")) ///
>         (scatter beta year_enc if var_enc==2, mcolor(maroon) msymbol(S) connect(line) lcolor(maroon)) ///
>         (line up95 year_enc if var_enc==2, lcolor(maroon) lpattern("......-")) ///
>         (line lo95 year_enc if var_enc==2, lcolor(maroon) lpattern("......-")) ///
>         (scatter beta year_enc if var_enc==3, mcolor(green) msymbol(T) connect(line) lcolor(green)) ///
>         (line up95 year_enc if var_enc==3, lcolor(green) lpattern("......-")) ///
>         (line lo95 year_enc if var_enc==3, lcolor(green) lpattern("......-")) ///
>         (scatter beta year_enc if var_enc==4, mcolor(purple) msymbol(D) connect(line) lcolor(purple)) ///
>         (line up95 year_enc if var_enc==4, lcolor(purple) lpattern("......-")) ///
>         (line lo95 year_enc if var_enc==4, lcolor(purple) lpattern("......-"))  ///
>         , ylabel(-.1(.05).05, labsize(vsmall) format(%3.2f) angle(0)) yline(0, lpattern(dash)) yscale(r(-.13 .065)) /// 
>         xlabel(1(1)7, labsize(vsmall) angle(30) valuelabel) ///
>         ytitle("OLS Coefficient (95% C.I.)", size(small)) xtitle("") ///
>         leg(lab(1 "Aged 35 to 49") lab(4 "Aged 50 to 64") lab(7 "Aged 65 and above") lab(10 "Female") r(2) pos(7) ring(0) order(10 1 4 7) region(col(white)) symx(*0.5) size(vsmall)) ///
>         graphregion(color(white)) subtitle("Radical right-wing vote", ring(0))
{res}{txt}
{com}. graph export "$results\EEREV-D-21-00004_FigureC2_vote.png", replace width(3600) height(3600)
{txt}{p 0 4 2}
file {bf}
D:\Dropbox\SVLACHOS\Research\Malgre_nous\Replication_files\Results\EEREV-D-21-00004_FigureC2_vote.png{rm}
saved as
PNG
format
{p_end}

{com}. 
. cap log close
{smcl}
{com}{sf}{ul off}