{smcl}
{com}{sf}{ul off}{txt}
{com}. 
. **** REPLICATION OF TABLE C6 ****
. 
. 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. TABLE FOR PAPER
> */
. 
. **************************
. ***** 1. REGRESSIONS *****
. **************************
. 
. // Import casulaties data
. 
. use $data\EEREV-D-21-00004_Data_Municipalities.dta, clear
{txt}
{com}. 
. // Substract casualties
. 
. recode perc_d_1908_1913 (.=0) if dep==57
{txt}(5648 changes made to {bf:perc_d_1908_1913})

{com}. replace perc_i_full=perc_i_full-perc_d_1908_1913
{txt}(6,616 real changes made, 5,040 to missing)

{com}. 
. // Macros
. 
. global geogr_endow                      "water lelevation_mean lelevation_std ldist_de" 
{txt}
{com}. global pop                                      "perc_b_1928_1945 perc_b_1946_1964 perc_b_1965_1980 perc_b_1981_1996 perc_male_counter"
{txt}
{com}. global demog_chara                      "lpop_counter perc_fore $pop"
{txt}
{com}. global socec_aspec                      "perc_bacplus perc_bluecollar perc_chom lrev_median lrev_sd"
{txt}
{com}. 
. // Control vectors
. 
. global sigma                            "perc_prot_church pop_jew p_french_name lpop_1936 perc_fore_1936 perc_dial_1936 perc_disp_1946 $geogr_endow perc_droi_1936_ins"
{txt}
{com}. global w                                        "$demog_chara $socec_aspec"
{txt}
{com}. global dialect                          "dialect_lux dialect_mos dialect_rhe dialect_pal dialect_als dialect_hau dialect_lor dialect_fra"
{txt}
{com}. 
. // Controls vector
. 
. global rdd2                             "rdd_lat rdd_lon rdd_lat_2 rdd_lon_2 rdd_lat_lon"
{txt}
{com}. 
. // First stage
. 
. foreach year in 1965 1969 1974 1995 2002 2007 2012 2017{c -(}
{txt}  2{com}. 
.         ivreghdfe perc_i_full perc_e_1908_1927 ///
>                 perc_b_1903_1912 perc_b_1913_1922 perc_b_1923_1932 /// 
>                 $sigma $w $rdd2 /// 
>                 if annee==`year' & sample==1, cluster(ct_1936_enc) ///
>                 a(borderfe $dialect pop_jew water) partial($sigma $w)
{txt}  3{com}. 
.         estimates store P`year'T1_FS
{txt}  4{com}.         sum perc_i_full  if annee==`year' & sample==1
{txt}  5{com}.         scalar mean_y=r(mean)
{txt}  6{com}.         estadd scalar mean_y
{txt}  7{com}.         test perc_e_1908_1927
{txt}  8{com}.         estadd scalar F_fs=r(F)
{txt}  9{com}. 
. {c )-}
{res}{txt}(warning: absorbing 11 dimensions of fixed effects; check that you really want that)
{res}{txt}Warning - collinearities detected
Vars dropped:{col 21}perc_b_1981_1996
{res}{txt}note: {res}variable #12{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}variable #18{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 8 iterations)
{res}
{txt}OLS estimation
{hline 14}

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on ct_1936_enc

Number of clusters (ct_1936_enc) = {col 33}{res}    32{txt}{col 55}Number of obs = {res}     461
{txt}{col 55}F(  9,    31) = {res}    7.98
{txt}{col 55}Prob > F      = {res}  0.0000
{txt}Total (centered) SS     = {res} 5815.230934{txt}{col 55}Centered R2   = {res}  0.0489
{txt}Total (uncentered) SS   = {res} 5815.230934{txt}{col 55}Uncentered R2 = {res}  0.0489
{txt}Residual SS             = {res} 5530.860782{txt}{col 55}Root MSE      = {res}   3.651

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}     perc_i_full{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
perc_e_1908_1927 {c |}{col 18}{res}{space 2} .2069421{col 30}{space 2} .0533973{col 41}{space 1}    3.88{col 50}{space 3}0.001{col 58}{space 4} .0980376{col 71}{space 3} .3158466
{txt}perc_b_1903_1912 {c |}{col 18}{res}{space 2}-.0026919{col 30}{space 2} .0550213{col 41}{space 1}   -0.05{col 50}{space 3}0.961{col 58}{space 4}-.1149085{col 71}{space 3} .1095248
{txt}perc_b_1913_1922 {c |}{col 18}{res}{space 2}-.0995788{col 30}{space 2} .1610187{col 41}{space 1}   -0.62{col 50}{space 3}0.541{col 58}{space 4}-.4279786{col 71}{space 3} .2288209
{txt}perc_b_1923_1932 {c |}{col 18}{res}{space 2} -.080484{col 30}{space 2} .1356114{col 41}{space 1}   -0.59{col 50}{space 3}0.557{col 58}{space 4}-.3570652{col 71}{space 3} .1960973
{txt}{space 9}rdd_lat {c |}{col 18}{res}{space 2}-893.1876{col 30}{space 2} 1042.753{col 41}{space 1}   -0.86{col 50}{space 3}0.398{col 58}{space 4}-3019.897{col 71}{space 3} 1233.522
{txt}{space 9}rdd_lon {c |}{col 18}{res}{space 2} 307.6124{col 30}{space 2} 541.0899{col 41}{space 1}    0.57{col 50}{space 3}0.574{col 58}{space 4}-795.9478{col 71}{space 3} 1411.173
{txt}{space 7}rdd_lat_2 {c |}{col 18}{res}{space 2} 9.605479{col 30}{space 2} 10.28429{col 41}{space 1}    0.93{col 50}{space 3}0.358{col 58}{space 4}-11.36947{col 71}{space 3} 30.58043
{txt}{space 7}rdd_lon_2 {c |}{col 18}{res}{space 2}-1.898448{col 30}{space 2} 4.744908{col 41}{space 1}   -0.40{col 50}{space 3}0.692{col 58}{space 4}-11.57575{col 71}{space 3} 7.778855
{txt}{space 5}rdd_lat_lon {c |}{col 18}{res}{space 2}-5.626775{col 30}{space 2} 10.85427{col 41}{space 1}   -0.52{col 50}{space 3}0.608{col 58}{space 4} -27.7642{col 71}{space 3} 16.51065
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
Included instruments:{col 23}perc_e_1908_1927 perc_b_1903_1912 perc_b_1913_1922
{col 23}perc_b_1923_1932 rdd_lat rdd_lon rdd_lat_2 rdd_lon_2
{col 23}rdd_lat_lon
{help ivreg2##partial:Partialled-out}:{col 23}perc_prot_church pop_jew p_french_name lpop_1936
{col 23}perc_fore_1936 perc_dial_1936 perc_disp_1946 water
{col 23}lelevation_mean lelevation_std ldist_de perc_droi_1936_ins
{col 23}lpop_counter perc_fore perc_b_1928_1945 perc_b_1946_1964
{col 23}perc_b_1965_1980 perc_male_counter perc_bacplus
{col 23}perc_bluecollar perc_chom lrev_median lrev_sd _cons
{col 23}nb: total SS, model F and R2s are after partialling-out;
{col 23}    any {help ivreg2##s_small:small-sample adjustments} include partialled-out
{col 23}    variables in regressor count K
Dropped collinear:{col 23}perc_b_1981_1996
{hline 78}
{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}  borderfe25{col 14}{c |}{space 1}        8{col 27}{space 1}        0{col 39}{result}{space 1}        8{col 53}{text} {col 54}{c |}
{res}{col 1}{text} dialect_lux{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text} {col 54}{c |}
{res}{col 1}{text} dialect_mos{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_rhe{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_pal{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_als{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_hau{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_lor{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_fra{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text}?{col 54}{c |}
{res}{col 1}{text}     pop_jew{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text}       water{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{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
{res}
{txt}    Variable {c |}        Obs        Mean    Std. dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 1}perc_i_full {c |}{res}        461    7.551228    4.407727          0    39.3405

{txt}added scalar:
             e(mean_y) =  {res}7.5512275

{p 0 7}{space 1}{text:( 1)}{space 1} perc_e_1908_1927 = 0{p_end}

{txt}       F(  1,    31) ={res}   15.02
{txt}{col 13}Prob > F ={res}    0.0005

{txt}added scalar:
               e(F_fs) =  {res}15.019628
{txt}(warning: absorbing 11 dimensions of fixed effects; check that you really want that)
{res}{txt}Warning - collinearities detected
Vars dropped:{col 21}perc_b_1981_1996
{res}{txt}note: {res}variable #12{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}variable #18{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 8 iterations)
{res}
{txt}OLS estimation
{hline 14}

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on ct_1936_enc

Number of clusters (ct_1936_enc) = {col 33}{res}    32{txt}{col 55}Number of obs = {res}     461
{txt}{col 55}F(  9,    31) = {res}    9.46
{txt}{col 55}Prob > F      = {res}  0.0000
{txt}Total (centered) SS     = {res}  5871.22338{txt}{col 55}Centered R2   = {res}  0.0549
{txt}Total (uncentered) SS   = {res}  5871.22338{txt}{col 55}Uncentered R2 = {res}  0.0549
{txt}Residual SS             = {res} 5548.677438{txt}{col 55}Root MSE      = {res}   3.657

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}     perc_i_full{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
perc_e_1908_1927 {c |}{col 18}{res}{space 2} .2183392{col 30}{space 2} .0543352{col 41}{space 1}    4.02{col 50}{space 3}0.000{col 58}{space 4} .1075218{col 71}{space 3} .3291565
{txt}perc_b_1903_1912 {c |}{col 18}{res}{space 2}-.0050941{col 30}{space 2} .0547531{col 41}{space 1}   -0.09{col 50}{space 3}0.926{col 58}{space 4}-.1167639{col 71}{space 3} .1065756
{txt}perc_b_1913_1922 {c |}{col 18}{res}{space 2}-.1072731{col 30}{space 2} .1626284{col 41}{space 1}   -0.66{col 50}{space 3}0.514{col 58}{space 4} -.438956{col 71}{space 3} .2244098
{txt}perc_b_1923_1932 {c |}{col 18}{res}{space 2}-.0839366{col 30}{space 2} .1385243{col 41}{space 1}   -0.61{col 50}{space 3}0.549{col 58}{space 4}-.3664588{col 71}{space 3} .1985855
{txt}{space 9}rdd_lat {c |}{col 18}{res}{space 2}-763.5914{col 30}{space 2} 1049.829{col 41}{space 1}   -0.73{col 50}{space 3}0.472{col 58}{space 4}-2904.731{col 71}{space 3} 1377.548
{txt}{space 9}rdd_lon {c |}{col 18}{res}{space 2} 382.3731{col 30}{space 2} 566.0939{col 41}{space 1}    0.68{col 50}{space 3}0.504{col 58}{space 4} -772.183{col 71}{space 3} 1536.929
{txt}{space 7}rdd_lat_2 {c |}{col 18}{res}{space 2} 8.386107{col 30}{space 2} 10.34601{col 41}{space 1}    0.81{col 50}{space 3}0.424{col 58}{space 4}-12.71473{col 71}{space 3} 29.48694
{txt}{space 7}rdd_lon_2 {c |}{col 18}{res}{space 2}-1.899511{col 30}{space 2} 4.873111{col 41}{space 1}   -0.39{col 50}{space 3}0.699{col 58}{space 4}-11.83829{col 71}{space 3} 8.039265
{txt}{space 5}rdd_lat_lon {c |}{col 18}{res}{space 2}-7.146364{col 30}{space 2}  11.3133{col 41}{space 1}   -0.63{col 50}{space 3}0.532{col 58}{space 4}   -30.22{col 71}{space 3} 15.92727
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
Included instruments:{col 23}perc_e_1908_1927 perc_b_1903_1912 perc_b_1913_1922
{col 23}perc_b_1923_1932 rdd_lat rdd_lon rdd_lat_2 rdd_lon_2
{col 23}rdd_lat_lon
{help ivreg2##partial:Partialled-out}:{col 23}perc_prot_church pop_jew p_french_name lpop_1936
{col 23}perc_fore_1936 perc_dial_1936 perc_disp_1946 water
{col 23}lelevation_mean lelevation_std ldist_de perc_droi_1936_ins
{col 23}lpop_counter perc_fore perc_b_1928_1945 perc_b_1946_1964
{col 23}perc_b_1965_1980 perc_male_counter perc_bacplus
{col 23}perc_bluecollar perc_chom lrev_median lrev_sd _cons
{col 23}nb: total SS, model F and R2s are after partialling-out;
{col 23}    any {help ivreg2##s_small:small-sample adjustments} include partialled-out
{col 23}    variables in regressor count K
Dropped collinear:{col 23}perc_b_1981_1996
{hline 78}
{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}  borderfe25{col 14}{c |}{space 1}        8{col 27}{space 1}        0{col 39}{result}{space 1}        8{col 53}{text} {col 54}{c |}
{res}{col 1}{text} dialect_lux{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text} {col 54}{c |}
{res}{col 1}{text} dialect_mos{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_rhe{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_pal{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_als{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_hau{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_lor{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_fra{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text}?{col 54}{c |}
{res}{col 1}{text}     pop_jew{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text}       water{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{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
{res}
{txt}    Variable {c |}        Obs        Mean    Std. dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 1}perc_i_full {c |}{res}        461    7.551228    4.407727          0    39.3405

{txt}added scalar:
             e(mean_y) =  {res}7.5512275

{p 0 7}{space 1}{text:( 1)}{space 1} perc_e_1908_1927 = 0{p_end}

{txt}       F(  1,    31) ={res}   16.15
{txt}{col 13}Prob > F ={res}    0.0003

{txt}added scalar:
               e(F_fs) =  {res}16.147344
{txt}(warning: absorbing 11 dimensions of fixed effects; check that you really want that)
{res}{txt}Warning - collinearities detected
Vars dropped:{col 21}perc_b_1981_1996
{res}{txt}note: {res}variable #12{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}variable #18{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 8 iterations)
{res}
{txt}OLS estimation
{hline 14}

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on ct_1936_enc

Number of clusters (ct_1936_enc) = {col 33}{res}    32{txt}{col 55}Number of obs = {res}     461
{txt}{col 55}F(  9,    31) = {res}   11.25
{txt}{col 55}Prob > F      = {res}  0.0000
{txt}Total (centered) SS     = {res} 5713.731582{txt}{col 55}Centered R2   = {res}  0.0563
{txt}Total (uncentered) SS   = {res} 5713.731582{txt}{col 55}Uncentered R2 = {res}  0.0563
{txt}Residual SS             = {res}  5391.82672{txt}{col 55}Root MSE      = {res}   3.604

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}     perc_i_full{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
perc_e_1908_1927 {c |}{col 18}{res}{space 2} .2194824{col 30}{space 2}  .053245{col 41}{space 1}    4.12{col 50}{space 3}0.000{col 58}{space 4} .1108885{col 71}{space 3} .3280763
{txt}perc_b_1903_1912 {c |}{col 18}{res}{space 2}-.0145298{col 30}{space 2} .0554174{col 41}{space 1}   -0.26{col 50}{space 3}0.795{col 58}{space 4}-.1275544{col 71}{space 3} .0984947
{txt}perc_b_1913_1922 {c |}{col 18}{res}{space 2}-.0952393{col 30}{space 2} .1478432{col 41}{space 1}   -0.64{col 50}{space 3}0.524{col 58}{space 4}-.3967675{col 71}{space 3} .2062888
{txt}perc_b_1923_1932 {c |}{col 18}{res}{space 2}-.1128982{col 30}{space 2} .1257187{col 41}{space 1}   -0.90{col 50}{space 3}0.376{col 58}{space 4}-.3693031{col 71}{space 3} .1435067
{txt}{space 9}rdd_lat {c |}{col 18}{res}{space 2}-524.2094{col 30}{space 2} 775.9339{col 41}{space 1}   -0.68{col 50}{space 3}0.504{col 58}{space 4}-2106.737{col 71}{space 3} 1058.318
{txt}{space 9}rdd_lon {c |}{col 18}{res}{space 2} 360.5758{col 30}{space 2}  541.524{col 41}{space 1}    0.67{col 50}{space 3}0.510{col 58}{space 4}-743.8697{col 71}{space 3} 1465.021
{txt}{space 7}rdd_lat_2 {c |}{col 18}{res}{space 2} 5.918808{col 30}{space 2} 7.558147{col 41}{space 1}    0.78{col 50}{space 3}0.440{col 58}{space 4}-9.496135{col 71}{space 3} 21.33375
{txt}{space 7}rdd_lon_2 {c |}{col 18}{res}{space 2}-.9795795{col 30}{space 2} 4.551883{col 41}{space 1}   -0.22{col 50}{space 3}0.831{col 58}{space 4}-10.26321{col 71}{space 3} 8.304046
{txt}{space 5}rdd_lat_lon {c |}{col 18}{res}{space 2}-6.978226{col 30}{space 2} 10.83154{col 41}{space 1}   -0.64{col 50}{space 3}0.524{col 58}{space 4}-29.06929{col 71}{space 3} 15.11284
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
Included instruments:{col 23}perc_e_1908_1927 perc_b_1903_1912 perc_b_1913_1922
{col 23}perc_b_1923_1932 rdd_lat rdd_lon rdd_lat_2 rdd_lon_2
{col 23}rdd_lat_lon
{help ivreg2##partial:Partialled-out}:{col 23}perc_prot_church pop_jew p_french_name lpop_1936
{col 23}perc_fore_1936 perc_dial_1936 perc_disp_1946 water
{col 23}lelevation_mean lelevation_std ldist_de perc_droi_1936_ins
{col 23}lpop_counter perc_fore perc_b_1928_1945 perc_b_1946_1964
{col 23}perc_b_1965_1980 perc_male_counter perc_bacplus
{col 23}perc_bluecollar perc_chom lrev_median lrev_sd _cons
{col 23}nb: total SS, model F and R2s are after partialling-out;
{col 23}    any {help ivreg2##s_small:small-sample adjustments} include partialled-out
{col 23}    variables in regressor count K
Dropped collinear:{col 23}perc_b_1981_1996
{hline 78}
{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}  borderfe25{col 14}{c |}{space 1}        8{col 27}{space 1}        0{col 39}{result}{space 1}        8{col 53}{text} {col 54}{c |}
{res}{col 1}{text} dialect_lux{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text} {col 54}{c |}
{res}{col 1}{text} dialect_mos{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_rhe{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_pal{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_als{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_hau{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_lor{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_fra{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text}?{col 54}{c |}
{res}{col 1}{text}     pop_jew{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text}       water{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{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
{res}
{txt}    Variable {c |}        Obs        Mean    Std. dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 1}perc_i_full {c |}{res}        461    7.551228    4.407727          0    39.3405

{txt}added scalar:
             e(mean_y) =  {res}7.5512275

{p 0 7}{space 1}{text:( 1)}{space 1} perc_e_1908_1927 = 0{p_end}

{txt}       F(  1,    31) ={res}   16.99
{txt}{col 13}Prob > F ={res}    0.0003

{txt}added scalar:
               e(F_fs) =  {res}16.991883
{txt}(warning: absorbing 11 dimensions of fixed effects; check that you really want that)
{res}{txt}note: {res}variable #12{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}variable #18{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 8 iterations)
{res}
{txt}OLS estimation
{hline 14}

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on ct_1936_enc

Number of clusters (ct_1936_enc) = {col 33}{res}    32{txt}{col 55}Number of obs = {res}     461
{txt}{col 55}F(  9,    31) = {res}   11.08
{txt}{col 55}Prob > F      = {res}  0.0000
{txt}Total (centered) SS     = {res} 5574.224066{txt}{col 55}Centered R2   = {res}  0.0468
{txt}Total (uncentered) SS   = {res} 5574.224066{txt}{col 55}Uncentered R2 = {res}  0.0468
{txt}Residual SS             = {res} 5313.181838{txt}{col 55}Root MSE      = {res}   3.582

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}     perc_i_full{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
perc_e_1908_1927 {c |}{col 18}{res}{space 2} .2131556{col 30}{space 2}  .050844{col 41}{space 1}    4.19{col 50}{space 3}0.000{col 58}{space 4} .1094585{col 71}{space 3} .3168527
{txt}perc_b_1903_1912 {c |}{col 18}{res}{space 2}-.0025775{col 30}{space 2} .0556271{col 41}{space 1}   -0.05{col 50}{space 3}0.963{col 58}{space 4}-.1160298{col 71}{space 3} .1108748
{txt}perc_b_1913_1922 {c |}{col 18}{res}{space 2}-.1574566{col 30}{space 2} .1573056{col 41}{space 1}   -1.00{col 50}{space 3}0.325{col 58}{space 4}-.4782835{col 71}{space 3} .1633703
{txt}perc_b_1923_1932 {c |}{col 18}{res}{space 2}-.1180893{col 30}{space 2} .1077261{col 41}{space 1}   -1.10{col 50}{space 3}0.281{col 58}{space 4}-.3377981{col 71}{space 3} .1016195
{txt}{space 9}rdd_lat {c |}{col 18}{res}{space 2}-221.3008{col 30}{space 2} 989.2107{col 41}{space 1}   -0.22{col 50}{space 3}0.824{col 58}{space 4}-2238.809{col 71}{space 3} 1796.208
{txt}{space 9}rdd_lon {c |}{col 18}{res}{space 2} 450.0477{col 30}{space 2} 548.3365{col 41}{space 1}    0.82{col 50}{space 3}0.418{col 58}{space 4}-668.2919{col 71}{space 3} 1568.387
{txt}{space 7}rdd_lat_2 {c |}{col 18}{res}{space 2} 2.943152{col 30}{space 2} 9.784917{col 41}{space 1}    0.30{col 50}{space 3}0.766{col 58}{space 4}-17.01332{col 71}{space 3} 22.89962
{txt}{space 7}rdd_lon_2 {c |}{col 18}{res}{space 2} -.699489{col 30}{space 2} 4.877786{col 41}{space 1}   -0.14{col 50}{space 3}0.887{col 58}{space 4} -10.6478{col 71}{space 3} 9.248821
{txt}{space 5}rdd_lat_lon {c |}{col 18}{res}{space 2}-8.916881{col 30}{space 2} 10.97961{col 41}{space 1}   -0.81{col 50}{space 3}0.423{col 58}{space 4}-31.30995{col 71}{space 3} 13.47619
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
Included instruments:{col 23}perc_e_1908_1927 perc_b_1903_1912 perc_b_1913_1922
{col 23}perc_b_1923_1932 rdd_lat rdd_lon rdd_lat_2 rdd_lon_2
{col 23}rdd_lat_lon
{help ivreg2##partial:Partialled-out}:{col 23}perc_prot_church pop_jew p_french_name lpop_1936
{col 23}perc_fore_1936 perc_dial_1936 perc_disp_1946 water
{col 23}lelevation_mean lelevation_std ldist_de perc_droi_1936_ins
{col 23}lpop_counter perc_fore perc_b_1928_1945 perc_b_1946_1964
{col 23}perc_b_1965_1980 perc_b_1981_1996 perc_male_counter
{col 23}perc_bacplus perc_bluecollar perc_chom lrev_median lrev_sd
{col 23}_cons
{col 23}nb: total SS, model F and R2s are after partialling-out;
{col 23}    any {help ivreg2##s_small:small-sample adjustments} include partialled-out
{col 23}    variables in regressor count K
{hline 78}
{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}  borderfe25{col 14}{c |}{space 1}        8{col 27}{space 1}        0{col 39}{result}{space 1}        8{col 53}{text} {col 54}{c |}
{res}{col 1}{text} dialect_lux{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text} {col 54}{c |}
{res}{col 1}{text} dialect_mos{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_rhe{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_pal{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_als{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_hau{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_lor{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_fra{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text}?{col 54}{c |}
{res}{col 1}{text}     pop_jew{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text}       water{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{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
{res}
{txt}    Variable {c |}        Obs        Mean    Std. dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 1}perc_i_full {c |}{res}        461    7.551228    4.407727          0    39.3405

{txt}added scalar:
             e(mean_y) =  {res}7.5512275

{p 0 7}{space 1}{text:( 1)}{space 1} perc_e_1908_1927 = 0{p_end}

{txt}       F(  1,    31) ={res}   17.58
{txt}{col 13}Prob > F ={res}    0.0002

{txt}added scalar:
               e(F_fs) =  {res}17.575737
{txt}(warning: absorbing 11 dimensions of fixed effects; check that you really want that)
{res}{txt}note: {res}variable #12{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}variable #18{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 8 iterations)
{res}
{txt}OLS estimation
{hline 14}

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on ct_1936_enc

Number of clusters (ct_1936_enc) = {col 33}{res}    32{txt}{col 55}Number of obs = {res}     461
{txt}{col 55}F(  9,    31) = {res}    9.12
{txt}{col 55}Prob > F      = {res}  0.0000
{txt}Total (centered) SS     = {res} 5527.703523{txt}{col 55}Centered R2   = {res}  0.0494
{txt}Total (uncentered) SS   = {res} 5527.703523{txt}{col 55}Uncentered R2 = {res}  0.0494
{txt}Residual SS             = {res} 5254.430668{txt}{col 55}Root MSE      = {res}   3.563

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}     perc_i_full{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
perc_e_1908_1927 {c |}{col 18}{res}{space 2} .1998968{col 30}{space 2} .0507034{col 41}{space 1}    3.94{col 50}{space 3}0.000{col 58}{space 4} .0964866{col 71}{space 3}  .303307
{txt}perc_b_1903_1912 {c |}{col 18}{res}{space 2}-.0185728{col 30}{space 2} .0536692{col 41}{space 1}   -0.35{col 50}{space 3}0.732{col 58}{space 4}-.1280319{col 71}{space 3} .0908863
{txt}perc_b_1913_1922 {c |}{col 18}{res}{space 2} -.119767{col 30}{space 2} .1531293{col 41}{space 1}   -0.78{col 50}{space 3}0.440{col 58}{space 4}-.4320762{col 71}{space 3} .1925422
{txt}perc_b_1923_1932 {c |}{col 18}{res}{space 2}-.0720763{col 30}{space 2} .1156903{col 41}{space 1}   -0.62{col 50}{space 3}0.538{col 58}{space 4}-.3080281{col 71}{space 3} .1638755
{txt}{space 9}rdd_lat {c |}{col 18}{res}{space 2}-251.3486{col 30}{space 2} 1042.776{col 41}{space 1}   -0.24{col 50}{space 3}0.811{col 58}{space 4}-2378.104{col 71}{space 3} 1875.407
{txt}{space 9}rdd_lon {c |}{col 18}{res}{space 2} 643.1199{col 30}{space 2} 546.4715{col 41}{space 1}    1.18{col 50}{space 3}0.248{col 58}{space 4}-471.4161{col 71}{space 3} 1757.656
{txt}{space 7}rdd_lat_2 {c |}{col 18}{res}{space 2} 3.547467{col 30}{space 2} 10.21673{col 41}{space 1}    0.35{col 50}{space 3}0.731{col 58}{space 4}-17.28969{col 71}{space 3} 24.38463
{txt}{space 7}rdd_lon_2 {c |}{col 18}{res}{space 2}-.3210639{col 30}{space 2} 4.702554{col 41}{space 1}   -0.07{col 50}{space 3}0.946{col 58}{space 4}-9.911986{col 71}{space 3} 9.269858
{txt}{space 5}rdd_lat_lon {c |}{col 18}{res}{space 2}-12.97407{col 30}{space 2} 10.95005{col 41}{space 1}   -1.18{col 50}{space 3}0.245{col 58}{space 4}-35.30684{col 71}{space 3} 9.358706
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
Included instruments:{col 23}perc_e_1908_1927 perc_b_1903_1912 perc_b_1913_1922
{col 23}perc_b_1923_1932 rdd_lat rdd_lon rdd_lat_2 rdd_lon_2
{col 23}rdd_lat_lon
{help ivreg2##partial:Partialled-out}:{col 23}perc_prot_church pop_jew p_french_name lpop_1936
{col 23}perc_fore_1936 perc_dial_1936 perc_disp_1946 water
{col 23}lelevation_mean lelevation_std ldist_de perc_droi_1936_ins
{col 23}lpop_counter perc_fore perc_b_1928_1945 perc_b_1946_1964
{col 23}perc_b_1965_1980 perc_b_1981_1996 perc_male_counter
{col 23}perc_bacplus perc_bluecollar perc_chom lrev_median lrev_sd
{col 23}_cons
{col 23}nb: total SS, model F and R2s are after partialling-out;
{col 23}    any {help ivreg2##s_small:small-sample adjustments} include partialled-out
{col 23}    variables in regressor count K
{hline 78}
{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}  borderfe25{col 14}{c |}{space 1}        8{col 27}{space 1}        0{col 39}{result}{space 1}        8{col 53}{text} {col 54}{c |}
{res}{col 1}{text} dialect_lux{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text} {col 54}{c |}
{res}{col 1}{text} dialect_mos{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_rhe{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_pal{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_als{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_hau{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_lor{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_fra{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text}?{col 54}{c |}
{res}{col 1}{text}     pop_jew{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text}       water{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{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
{res}
{txt}    Variable {c |}        Obs        Mean    Std. dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 1}perc_i_full {c |}{res}        461    7.551228    4.407727          0    39.3405

{txt}added scalar:
             e(mean_y) =  {res}7.5512275

{p 0 7}{space 1}{text:( 1)}{space 1} perc_e_1908_1927 = 0{p_end}

{txt}       F(  1,    31) ={res}   15.54
{txt}{col 13}Prob > F ={res}    0.0004

{txt}added scalar:
               e(F_fs) =  {res}15.54311
{txt}(warning: absorbing 11 dimensions of fixed effects; check that you really want that)
{res}{txt}note: {res}variable #12{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}variable #18{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 8 iterations)
{res}
{txt}OLS estimation
{hline 14}

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on ct_1936_enc

Number of clusters (ct_1936_enc) = {col 33}{res}    32{txt}{col 55}Number of obs = {res}     461
{txt}{col 55}F(  9,    31) = {res}   14.42
{txt}{col 55}Prob > F      = {res}  0.0000
{txt}Total (centered) SS     = {res} 5863.422223{txt}{col 55}Centered R2   = {res}  0.0550
{txt}Total (uncentered) SS   = {res} 5863.422223{txt}{col 55}Uncentered R2 = {res}  0.0550
{txt}Residual SS             = {res} 5540.867385{txt}{col 55}Root MSE      = {res}   3.658

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}     perc_i_full{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
perc_e_1908_1927 {c |}{col 18}{res}{space 2} .2145197{col 30}{space 2} .0465508{col 41}{space 1}    4.61{col 50}{space 3}0.000{col 58}{space 4} .1195786{col 71}{space 3} .3094607
{txt}perc_b_1903_1912 {c |}{col 18}{res}{space 2}-.0064998{col 30}{space 2} .0531123{col 41}{space 1}   -0.12{col 50}{space 3}0.903{col 58}{space 4}-.1148231{col 71}{space 3} .1018235
{txt}perc_b_1913_1922 {c |}{col 18}{res}{space 2}-.1161925{col 30}{space 2} .1476109{col 41}{space 1}   -0.79{col 50}{space 3}0.437{col 58}{space 4}-.4172469{col 71}{space 3} .1848619
{txt}perc_b_1923_1932 {c |}{col 18}{res}{space 2}-.1015436{col 30}{space 2}  .116441{col 41}{space 1}   -0.87{col 50}{space 3}0.390{col 58}{space 4}-.3390267{col 71}{space 3} .1359395
{txt}{space 9}rdd_lat {c |}{col 18}{res}{space 2} -541.291{col 30}{space 2}  1081.18{col 41}{space 1}   -0.50{col 50}{space 3}0.620{col 58}{space 4}-2746.373{col 71}{space 3} 1663.791
{txt}{space 9}rdd_lon {c |}{col 18}{res}{space 2} 648.3075{col 30}{space 2} 553.1719{col 41}{space 1}    1.17{col 50}{space 3}0.250{col 58}{space 4} -479.894{col 71}{space 3} 1776.509
{txt}{space 7}rdd_lat_2 {c |}{col 18}{res}{space 2} 6.536369{col 30}{space 2} 10.56785{col 41}{space 1}    0.62{col 50}{space 3}0.541{col 58}{space 4} -15.0169{col 71}{space 3} 28.08964
{txt}{space 7}rdd_lon_2 {c |}{col 18}{res}{space 2}-1.419857{col 30}{space 2} 4.374414{col 41}{space 1}   -0.32{col 50}{space 3}0.748{col 58}{space 4}-10.34153{col 71}{space 3} 7.501819
{txt}{space 5}rdd_lat_lon {c |}{col 18}{res}{space 2}-12.74796{col 30}{space 2} 11.11533{col 41}{space 1}   -1.15{col 50}{space 3}0.260{col 58}{space 4}-35.41782{col 71}{space 3} 9.921896
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
Included instruments:{col 23}perc_e_1908_1927 perc_b_1903_1912 perc_b_1913_1922
{col 23}perc_b_1923_1932 rdd_lat rdd_lon rdd_lat_2 rdd_lon_2
{col 23}rdd_lat_lon
{help ivreg2##partial:Partialled-out}:{col 23}perc_prot_church pop_jew p_french_name lpop_1936
{col 23}perc_fore_1936 perc_dial_1936 perc_disp_1946 water
{col 23}lelevation_mean lelevation_std ldist_de perc_droi_1936_ins
{col 23}lpop_counter perc_fore perc_b_1928_1945 perc_b_1946_1964
{col 23}perc_b_1965_1980 perc_b_1981_1996 perc_male_counter
{col 23}perc_bacplus perc_bluecollar perc_chom lrev_median lrev_sd
{col 23}_cons
{col 23}nb: total SS, model F and R2s are after partialling-out;
{col 23}    any {help ivreg2##s_small:small-sample adjustments} include partialled-out
{col 23}    variables in regressor count K
{hline 78}
{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}  borderfe25{col 14}{c |}{space 1}        8{col 27}{space 1}        0{col 39}{result}{space 1}        8{col 53}{text} {col 54}{c |}
{res}{col 1}{text} dialect_lux{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text} {col 54}{c |}
{res}{col 1}{text} dialect_mos{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_rhe{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_pal{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_als{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_hau{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_lor{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_fra{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text}?{col 54}{c |}
{res}{col 1}{text}     pop_jew{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text}       water{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{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
{res}
{txt}    Variable {c |}        Obs        Mean    Std. dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 1}perc_i_full {c |}{res}        461    7.551228    4.407727          0    39.3405

{txt}added scalar:
             e(mean_y) =  {res}7.5512275

{p 0 7}{space 1}{text:( 1)}{space 1} perc_e_1908_1927 = 0{p_end}

{txt}       F(  1,    31) ={res}   21.24
{txt}{col 13}Prob > F ={res}    0.0001

{txt}added scalar:
               e(F_fs) =  {res}21.236336
{txt}(warning: absorbing 11 dimensions of fixed effects; check that you really want that)
{res}{txt}note: {res}variable #12{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}variable #18{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 8 iterations)
{res}
{txt}OLS estimation
{hline 14}

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on ct_1936_enc

Number of clusters (ct_1936_enc) = {col 33}{res}    32{txt}{col 55}Number of obs = {res}     461
{txt}{col 55}F(  9,    31) = {res}   15.31
{txt}{col 55}Prob > F      = {res}  0.0000
{txt}Total (centered) SS     = {res} 5776.589337{txt}{col 55}Centered R2   = {res}  0.0601
{txt}Total (uncentered) SS   = {res} 5776.589337{txt}{col 55}Uncentered R2 = {res}  0.0601
{txt}Residual SS             = {res} 5429.276468{txt}{col 55}Root MSE      = {res}   3.621

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}     perc_i_full{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
perc_e_1908_1927 {c |}{col 18}{res}{space 2} .2166132{col 30}{space 2} .0558227{col 41}{space 1}    3.88{col 50}{space 3}0.001{col 58}{space 4} .1027621{col 71}{space 3} .3304643
{txt}perc_b_1903_1912 {c |}{col 18}{res}{space 2} .0017695{col 30}{space 2}  .052509{col 41}{space 1}    0.03{col 50}{space 3}0.973{col 58}{space 4}-.1053233{col 71}{space 3} .1088623
{txt}perc_b_1913_1922 {c |}{col 18}{res}{space 2}-.1416121{col 30}{space 2} .1599204{col 41}{space 1}   -0.89{col 50}{space 3}0.383{col 58}{space 4} -.467772{col 71}{space 3} .1845477
{txt}perc_b_1923_1932 {c |}{col 18}{res}{space 2}-.0660861{col 30}{space 2} .1221169{col 41}{space 1}   -0.54{col 50}{space 3}0.592{col 58}{space 4}-.3151451{col 71}{space 3}  .182973
{txt}{space 9}rdd_lat {c |}{col 18}{res}{space 2}-623.4455{col 30}{space 2} 1076.316{col 41}{space 1}   -0.58{col 50}{space 3}0.567{col 58}{space 4}-2818.606{col 71}{space 3} 1571.715
{txt}{space 9}rdd_lon {c |}{col 18}{res}{space 2} 647.1013{col 30}{space 2} 636.9566{col 41}{space 1}    1.02{col 50}{space 3}0.318{col 58}{space 4}-651.9803{col 71}{space 3} 1946.183
{txt}{space 7}rdd_lat_2 {c |}{col 18}{res}{space 2} 7.313225{col 30}{space 2} 10.40101{col 41}{space 1}    0.70{col 50}{space 3}0.487{col 58}{space 4}-13.89977{col 71}{space 3} 28.52622
{txt}{space 7}rdd_lon_2 {c |}{col 18}{res}{space 2}-4.000945{col 30}{space 2} 5.035621{col 41}{space 1}   -0.79{col 50}{space 3}0.433{col 58}{space 4}-14.27116{col 71}{space 3} 6.269272
{txt}{space 5}rdd_lat_lon {c |}{col 18}{res}{space 2} -11.9348{col 30}{space 2}  12.8728{col 41}{space 1}   -0.93{col 50}{space 3}0.361{col 58}{space 4}-38.18905{col 71}{space 3} 14.31944
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
Included instruments:{col 23}perc_e_1908_1927 perc_b_1903_1912 perc_b_1913_1922
{col 23}perc_b_1923_1932 rdd_lat rdd_lon rdd_lat_2 rdd_lon_2
{col 23}rdd_lat_lon
{help ivreg2##partial:Partialled-out}:{col 23}perc_prot_church pop_jew p_french_name lpop_1936
{col 23}perc_fore_1936 perc_dial_1936 perc_disp_1946 water
{col 23}lelevation_mean lelevation_std ldist_de perc_droi_1936_ins
{col 23}lpop_counter perc_fore perc_b_1928_1945 perc_b_1946_1964
{col 23}perc_b_1965_1980 perc_b_1981_1996 perc_male_counter
{col 23}perc_bacplus perc_bluecollar perc_chom lrev_median lrev_sd
{col 23}_cons
{col 23}nb: total SS, model F and R2s are after partialling-out;
{col 23}    any {help ivreg2##s_small:small-sample adjustments} include partialled-out
{col 23}    variables in regressor count K
{hline 78}
{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}  borderfe25{col 14}{c |}{space 1}        8{col 27}{space 1}        0{col 39}{result}{space 1}        8{col 53}{text} {col 54}{c |}
{res}{col 1}{text} dialect_lux{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text} {col 54}{c |}
{res}{col 1}{text} dialect_mos{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_rhe{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_pal{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_als{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_hau{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_lor{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_fra{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text}?{col 54}{c |}
{res}{col 1}{text}     pop_jew{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text}       water{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{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
{res}
{txt}    Variable {c |}        Obs        Mean    Std. dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 1}perc_i_full {c |}{res}        461    7.551228    4.407727          0    39.3405

{txt}added scalar:
             e(mean_y) =  {res}7.5512275

{p 0 7}{space 1}{text:( 1)}{space 1} perc_e_1908_1927 = 0{p_end}

{txt}       F(  1,    31) ={res}   15.06
{txt}{col 13}Prob > F ={res}    0.0005

{txt}added scalar:
               e(F_fs) =  {res}15.057351
{txt}(warning: absorbing 11 dimensions of fixed effects; check that you really want that)
{res}{txt}note: {res}variable #12{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}variable #18{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 8 iterations)
{res}
{txt}OLS estimation
{hline 14}

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on ct_1936_enc

Number of clusters (ct_1936_enc) = {col 33}{res}    32{txt}{col 55}Number of obs = {res}     461
{txt}{col 55}F(  9,    31) = {res}   13.36
{txt}{col 55}Prob > F      = {res}  0.0000
{txt}Total (centered) SS     = {res} 5790.296555{txt}{col 55}Centered R2   = {res}  0.0616
{txt}Total (uncentered) SS   = {res} 5790.296555{txt}{col 55}Uncentered R2 = {res}  0.0616
{txt}Residual SS             = {res}  5433.88819{txt}{col 55}Root MSE      = {res}   3.623

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}     perc_i_full{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
perc_e_1908_1927 {c |}{col 18}{res}{space 2} .2135904{col 30}{space 2} .0544827{col 41}{space 1}    3.92{col 50}{space 3}0.000{col 58}{space 4} .1024721{col 71}{space 3} .3247086
{txt}perc_b_1903_1912 {c |}{col 18}{res}{space 2} .0193287{col 30}{space 2} .0576734{col 41}{space 1}    0.34{col 50}{space 3}0.740{col 58}{space 4}-.0982969{col 71}{space 3} .1369543
{txt}perc_b_1913_1922 {c |}{col 18}{res}{space 2}-.1418366{col 30}{space 2} .1704743{col 41}{space 1}   -0.83{col 50}{space 3}0.412{col 58}{space 4}-.4895213{col 71}{space 3} .2058481
{txt}perc_b_1923_1932 {c |}{col 18}{res}{space 2} -.072666{col 30}{space 2} .1149944{col 41}{space 1}   -0.63{col 50}{space 3}0.532{col 58}{space 4}-.3071987{col 71}{space 3} .1618667
{txt}{space 9}rdd_lat {c |}{col 18}{res}{space 2}-892.8128{col 30}{space 2} 1104.158{col 41}{space 1}   -0.81{col 50}{space 3}0.425{col 58}{space 4}-3144.758{col 71}{space 3} 1359.132
{txt}{space 9}rdd_lon {c |}{col 18}{res}{space 2} 637.6027{col 30}{space 2} 606.5287{col 41}{space 1}    1.05{col 50}{space 3}0.301{col 58}{space 4}-599.4207{col 71}{space 3} 1874.626
{txt}{space 7}rdd_lat_2 {c |}{col 18}{res}{space 2} 10.07373{col 30}{space 2}  10.7809{col 41}{space 1}    0.93{col 50}{space 3}0.357{col 58}{space 4}-11.91406{col 71}{space 3} 32.06151
{txt}{space 7}rdd_lon_2 {c |}{col 18}{res}{space 2}-3.521958{col 30}{space 2}   4.6543{col 41}{space 1}   -0.76{col 50}{space 3}0.455{col 58}{space 4}-13.01447{col 71}{space 3}  5.97055
{txt}{space 5}rdd_lat_lon {c |}{col 18}{res}{space 2}-11.87518{col 30}{space 2} 12.18028{col 41}{space 1}   -0.97{col 50}{space 3}0.337{col 58}{space 4}-36.71703{col 71}{space 3} 12.96667
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
Included instruments:{col 23}perc_e_1908_1927 perc_b_1903_1912 perc_b_1913_1922
{col 23}perc_b_1923_1932 rdd_lat rdd_lon rdd_lat_2 rdd_lon_2
{col 23}rdd_lat_lon
{help ivreg2##partial:Partialled-out}:{col 23}perc_prot_church pop_jew p_french_name lpop_1936
{col 23}perc_fore_1936 perc_dial_1936 perc_disp_1946 water
{col 23}lelevation_mean lelevation_std ldist_de perc_droi_1936_ins
{col 23}lpop_counter perc_fore perc_b_1928_1945 perc_b_1946_1964
{col 23}perc_b_1965_1980 perc_b_1981_1996 perc_male_counter
{col 23}perc_bacplus perc_bluecollar perc_chom lrev_median lrev_sd
{col 23}_cons
{col 23}nb: total SS, model F and R2s are after partialling-out;
{col 23}    any {help ivreg2##s_small:small-sample adjustments} include partialled-out
{col 23}    variables in regressor count K
{hline 78}
{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}  borderfe25{col 14}{c |}{space 1}        8{col 27}{space 1}        0{col 39}{result}{space 1}        8{col 53}{text} {col 54}{c |}
{res}{col 1}{text} dialect_lux{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text} {col 54}{c |}
{res}{col 1}{text} dialect_mos{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_rhe{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_pal{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_als{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_hau{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_lor{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_fra{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text}?{col 54}{c |}
{res}{col 1}{text}     pop_jew{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text}       water{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{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
{res}
{txt}    Variable {c |}        Obs        Mean    Std. dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 1}perc_i_full {c |}{res}        461    7.551228    4.407727          0    39.3405

{txt}added scalar:
             e(mean_y) =  {res}7.5512275

{p 0 7}{space 1}{text:( 1)}{space 1} perc_e_1908_1927 = 0{p_end}

{txt}       F(  1,    31) ={res}   15.37
{txt}{col 13}Prob > F ={res}    0.0005

{txt}added scalar:
               e(F_fs) =  {res}15.369007
{txt}
{com}. 
. // 1965-1969 FOR TABLE
. 
. foreach year in 1969{c -(}
{txt}  2{com}. 
.         reg perc_voixexd_ins perc_b_1903_1912 if annee==`year' & sample==1, cluster(ct_1936_enc)
{txt}  3{com}.         estimates store P`year'T1_VOTE
{txt}  4{com}.         qui sum perc_voixexd_ins if e(sample)
{txt}  5{com}.         scalar mean_y=r(mean)
{txt}  6{com}.         estadd scalar mean_y
{txt}  7{com}.         
. {c )-}

{txt}Linear regression                               Number of obs     = {res}       462
                                                {txt}{help j_robustsingular:F(0, 31) }         =  {res}        .
                                                {txt}Prob > F          = {res}         .
                                                {txt}R-squared         = {res}         .
                                                {txt}Root MSE          =    {res}      0

{txt}{ralign 82:(Std. err. adjusted for {res:32} clusters in ct_1936_enc)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}perc_voixexd_ins{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
perc_b_1903_1912 {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (omitted)
{space 11}_cons {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (omitted)
{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}added scalar:
             e(mean_y) =  {res}0
{txt}
{com}. 
. // Radical-Right
. 
. foreach year in 1965 1974 1995 2002 2007 2012 2017{c -(}
{txt}  2{com}.         
.         ivreghdfe perc_voixexd_ins (perc_i_full = perc_e_1908_1927) ///
>                 perc_b_1903_1912 perc_b_1913_1922 perc_b_1923_1932 /// 
>                 $sigma $w $rdd2 /// 
>                 if annee==`year' & sample==1, cluster(ct_1936_enc) ///
>                 a(borderfe $dialect pop_jew water) partial($sigma $w)
{txt}  3{com}.                 
.         estimates store P`year'T1_VOTE
{txt}  4{com}.         scalar f = e(rkf)
{txt}  5{com}.         estadd scalar F_fs=f
{txt}  6{com}.         qui sum perc_voixexd_ins if e(sample)
{txt}  7{com}.         scalar mean_y=r(mean)
{txt}  8{com}.         estadd scalar mean_y
{txt}  9{com}.         
. {c )-}
{res}{txt}(warning: absorbing 11 dimensions of fixed effects; check that you really want that)
{res}{txt}Warning - collinearities detected
Vars dropped:{col 21}perc_b_1981_1996
{res}{txt}note: {res}variable #13{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}variable #19{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 8 iterations)
{res}
{txt}IV (2SLS) estimation
{hline 20}

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on ct_1936_enc

Number of clusters (ct_1936_enc) = {col 33}{res}    32{txt}{col 55}Number of obs = {res}     461
{txt}{col 55}F(  9,    31) = {res}    1.12
{txt}{col 55}Prob > F      = {res}  0.3808
{txt}Total (centered) SS     = {res} 616.3397687{txt}{col 55}Centered R2   = {res} -0.0639
{txt}Total (uncentered) SS   = {res} 616.3397687{txt}{col 55}Uncentered R2 = {res} -0.0639
{txt}Residual SS             = {res} 655.7009037{txt}{col 55}Root MSE      = {res}   1.257

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}perc_voixexd_ins{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}perc_i_full {c |}{col 18}{res}{space 2} -.083208{col 30}{space 2}  .147876{col 41}{space 1}   -0.56{col 50}{space 3}0.578{col 58}{space 4}-.3848031{col 71}{space 3} .2183872
{txt}perc_b_1903_1912 {c |}{col 18}{res}{space 2} .0253577{col 30}{space 2} .0235006{col 41}{space 1}    1.08{col 50}{space 3}0.289{col 58}{space 4} -.022572{col 71}{space 3} .0732875
{txt}perc_b_1913_1922 {c |}{col 18}{res}{space 2} .0450425{col 30}{space 2} .0250386{col 41}{space 1}    1.80{col 50}{space 3}0.082{col 58}{space 4} -.006024{col 71}{space 3}  .096109
{txt}perc_b_1923_1932 {c |}{col 18}{res}{space 2}-.0856306{col 30}{space 2} .0382679{col 41}{space 1}   -2.24{col 50}{space 3}0.033{col 58}{space 4}-.1636785{col 71}{space 3}-.0075827
{txt}{space 9}rdd_lat {c |}{col 18}{res}{space 2}-763.5691{col 30}{space 2} 653.8063{col 41}{space 1}   -1.17{col 50}{space 3}0.252{col 58}{space 4}-2097.016{col 71}{space 3} 569.8776
{txt}{space 9}rdd_lon {c |}{col 18}{res}{space 2} 229.4608{col 30}{space 2} 162.2107{col 41}{space 1}    1.41{col 50}{space 3}0.167{col 58}{space 4}-101.3702{col 71}{space 3} 560.2918
{txt}{space 7}rdd_lat_2 {c |}{col 18}{res}{space 2} 8.193209{col 30}{space 2} 6.708618{col 41}{space 1}    1.22{col 50}{space 3}0.231{col 58}{space 4}-5.489107{col 71}{space 3} 21.87553
{txt}{space 7}rdd_lon_2 {c |}{col 18}{res}{space 2} .6156352{col 30}{space 2} 1.320382{col 41}{space 1}    0.47{col 50}{space 3}0.644{col 58}{space 4}-2.077302{col 71}{space 3} 3.308572
{txt}{space 5}rdd_lat_lon {c |}{col 18}{res}{space 2}-4.852363{col 30}{space 2} 3.243838{col 41}{space 1}   -1.50{col 50}{space 3}0.145{col 58}{space 4}-11.46821{col 71}{space 3} 1.763489
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{help ivreg2##idtest:Underidentification test} (Kleibergen-Paap rk LM statistic):{res}{col 71}   6.518
{txt}{col 52}Chi-sq({res}1{txt}) P-val =  {res}{col 73}0.0107
{txt}{hline 78}
{help ivreg2##widtest:Weak identification test} (Cragg-Donald Wald F statistic):{res}{col 71}   9.977
{txt}                         (Kleibergen-Paap rk Wald F statistic):{res}{col 71}  15.020
{txt}Stock-Yogo weak ID test critical values:{res}{txt}{col 42}10% maximal IV size{res}{col 73} 16.38
{txt}{col 42}15% maximal IV size{res}{col 73}  8.96
{txt}{col 42}20% maximal IV size{res}{col 73}  6.66
{txt}{col 42}25% maximal IV size{res}{col 73}  5.53
{txt}Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.
{hline 78}
{help ivreg2##overidtests:Hansen J statistic} (overidentification test of all instruments):{res}{col 71}   0.000
{txt}{col 50}(equation exactly identified)
{hline 78}
Instrumented:{col 23}perc_i_full
Included instruments:{col 23}perc_b_1903_1912 perc_b_1913_1922 perc_b_1923_1932
{col 23}rdd_lat rdd_lon rdd_lat_2 rdd_lon_2 rdd_lat_lon
Excluded instruments:{col 23}perc_e_1908_1927
{help ivreg2##partial:Partialled-out}:{col 23}perc_prot_church pop_jew p_french_name lpop_1936
{col 23}perc_fore_1936 perc_dial_1936 perc_disp_1946 water
{col 23}lelevation_mean lelevation_std ldist_de perc_droi_1936_ins
{col 23}lpop_counter perc_fore perc_b_1928_1945 perc_b_1946_1964
{col 23}perc_b_1965_1980 perc_male_counter perc_bacplus
{col 23}perc_bluecollar perc_chom lrev_median lrev_sd _cons
{col 23}nb: total SS, model F and R2s are after partialling-out;
{col 23}    any {help ivreg2##s_small:small-sample adjustments} include partialled-out
{col 23}    variables in regressor count K
Dropped collinear:{col 23}perc_b_1981_1996
{hline 78}
{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}  borderfe25{col 14}{c |}{space 1}        8{col 27}{space 1}        0{col 39}{result}{space 1}        8{col 53}{text} {col 54}{c |}
{res}{col 1}{text} dialect_lux{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text} {col 54}{c |}
{res}{col 1}{text} dialect_mos{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_rhe{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_pal{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_als{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_hau{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_lor{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_fra{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text}?{col 54}{c |}
{res}{col 1}{text}     pop_jew{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text}       water{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{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
{res}
{txt}added scalar:
               e(F_fs) =  {res}15.019628

{txt}added scalar:
             e(mean_y) =  {res}1.2032443
{txt}(warning: absorbing 11 dimensions of fixed effects; check that you really want that)
{res}{txt}Warning - collinearities detected
Vars dropped:{col 21}perc_b_1981_1996
{res}{txt}note: {res}variable #13{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}variable #19{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 8 iterations)
{res}
{txt}IV (2SLS) estimation
{hline 20}

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on ct_1936_enc

Number of clusters (ct_1936_enc) = {col 33}{res}    32{txt}{col 55}Number of obs = {res}     461
{txt}{col 55}F(  9,    31) = {res}    1.02
{txt}{col 55}Prob > F      = {res}  0.4439
{txt}Total (centered) SS     = {res} 73.57672047{txt}{col 55}Centered R2   = {res} -0.0013
{txt}Total (uncentered) SS   = {res} 73.57672047{txt}{col 55}Uncentered R2 = {res} -0.0013
{txt}Residual SS             = {res} 73.67101761{txt}{col 55}Root MSE      = {res}   .4213

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}perc_voixexd_ins{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}perc_i_full {c |}{col 18}{res}{space 2} .0139498{col 30}{space 2}  .020515{col 41}{space 1}    0.68{col 50}{space 3}0.502{col 58}{space 4}-.0278909{col 71}{space 3} .0557904
{txt}perc_b_1903_1912 {c |}{col 18}{res}{space 2} .0059649{col 30}{space 2} .0055428{col 41}{space 1}    1.08{col 50}{space 3}0.290{col 58}{space 4}-.0053398{col 71}{space 3} .0172696
{txt}perc_b_1913_1922 {c |}{col 18}{res}{space 2}-.0105094{col 30}{space 2} .0098216{col 41}{space 1}   -1.07{col 50}{space 3}0.293{col 58}{space 4}-.0305408{col 71}{space 3} .0095219
{txt}perc_b_1923_1932 {c |}{col 18}{res}{space 2}-.0110682{col 30}{space 2}   .00892{col 41}{space 1}   -1.24{col 50}{space 3}0.224{col 58}{space 4}-.0292605{col 71}{space 3} .0071242
{txt}{space 9}rdd_lat {c |}{col 18}{res}{space 2} 8.015942{col 30}{space 2} 100.5717{col 41}{space 1}    0.08{col 50}{space 3}0.937{col 58}{space 4}-197.1014{col 71}{space 3} 213.1333
{txt}{space 9}rdd_lon {c |}{col 18}{res}{space 2}-31.41696{col 30}{space 2} 80.15046{col 41}{space 1}   -0.39{col 50}{space 3}0.698{col 58}{space 4}-194.8849{col 71}{space 3}  132.051
{txt}{space 7}rdd_lat_2 {c |}{col 18}{res}{space 2}-.1223721{col 30}{space 2} 1.002447{col 41}{space 1}   -0.12{col 50}{space 3}0.904{col 58}{space 4}-2.166876{col 71}{space 3} 1.922132
{txt}{space 7}rdd_lon_2 {c |}{col 18}{res}{space 2} .6738608{col 30}{space 2} .5980342{col 41}{space 1}    1.13{col 50}{space 3}0.268{col 58}{space 4}-.5458379{col 71}{space 3}  1.89356
{txt}{space 5}rdd_lat_lon {c |}{col 18}{res}{space 2} .4396203{col 30}{space 2} 1.589182{col 41}{space 1}    0.28{col 50}{space 3}0.784{col 58}{space 4}-2.801538{col 71}{space 3} 3.680778
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{help ivreg2##idtest:Underidentification test} (Kleibergen-Paap rk LM statistic):{res}{col 71}   6.631
{txt}{col 52}Chi-sq({res}1{txt}) P-val =  {res}{col 73}0.0100
{txt}{hline 78}
{help ivreg2##widtest:Weak identification test} (Cragg-Donald Wald F statistic):{res}{col 71}  11.443
{txt}                         (Kleibergen-Paap rk Wald F statistic):{res}{col 71}  16.992
{txt}Stock-Yogo weak ID test critical values:{res}{txt}{col 42}10% maximal IV size{res}{col 73} 16.38
{txt}{col 42}15% maximal IV size{res}{col 73}  8.96
{txt}{col 42}20% maximal IV size{res}{col 73}  6.66
{txt}{col 42}25% maximal IV size{res}{col 73}  5.53
{txt}Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.
{hline 78}
{help ivreg2##overidtests:Hansen J statistic} (overidentification test of all instruments):{res}{col 71}   0.000
{txt}{col 50}(equation exactly identified)
{hline 78}
Instrumented:{col 23}perc_i_full
Included instruments:{col 23}perc_b_1903_1912 perc_b_1913_1922 perc_b_1923_1932
{col 23}rdd_lat rdd_lon rdd_lat_2 rdd_lon_2 rdd_lat_lon
Excluded instruments:{col 23}perc_e_1908_1927
{help ivreg2##partial:Partialled-out}:{col 23}perc_prot_church pop_jew p_french_name lpop_1936
{col 23}perc_fore_1936 perc_dial_1936 perc_disp_1946 water
{col 23}lelevation_mean lelevation_std ldist_de perc_droi_1936_ins
{col 23}lpop_counter perc_fore perc_b_1928_1945 perc_b_1946_1964
{col 23}perc_b_1965_1980 perc_male_counter perc_bacplus
{col 23}perc_bluecollar perc_chom lrev_median lrev_sd _cons
{col 23}nb: total SS, model F and R2s are after partialling-out;
{col 23}    any {help ivreg2##s_small:small-sample adjustments} include partialled-out
{col 23}    variables in regressor count K
Dropped collinear:{col 23}perc_b_1981_1996
{hline 78}
{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}  borderfe25{col 14}{c |}{space 1}        8{col 27}{space 1}        0{col 39}{result}{space 1}        8{col 53}{text} {col 54}{c |}
{res}{col 1}{text} dialect_lux{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text} {col 54}{c |}
{res}{col 1}{text} dialect_mos{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_rhe{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_pal{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_als{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_hau{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_lor{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_fra{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text}?{col 54}{c |}
{res}{col 1}{text}     pop_jew{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text}       water{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{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
{res}
{txt}added scalar:
               e(F_fs) =  {res}16.991883

{txt}added scalar:
             e(mean_y) =  {res}.31363737
{txt}(warning: absorbing 11 dimensions of fixed effects; check that you really want that)
{res}{txt}note: {res}variable #13{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}variable #19{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 8 iterations)
{res}
{txt}IV (2SLS) estimation
{hline 20}

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on ct_1936_enc

Number of clusters (ct_1936_enc) = {col 33}{res}    32{txt}{col 55}Number of obs = {res}     461
{txt}{col 55}F(  9,    31) = {res}    1.96
{txt}{col 55}Prob > F      = {res}  0.0789
{txt}Total (centered) SS     = {res} 8862.452521{txt}{col 55}Centered R2   = {res} -0.6869
{txt}Total (uncentered) SS   = {res} 8862.452521{txt}{col 55}Uncentered R2 = {res} -0.6869
{txt}Residual SS             = {res} 14950.12933{txt}{col 55}Root MSE      = {res}   6.009

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}perc_voixexd_ins{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}perc_i_full {c |}{col 18}{res}{space 2} 1.258662{col 30}{space 2} .4445026{col 41}{space 1}    2.83{col 50}{space 3}0.008{col 58}{space 4} .3520925{col 71}{space 3} 2.165231
{txt}perc_b_1903_1912 {c |}{col 18}{res}{space 2} .0252248{col 30}{space 2} .0991869{col 41}{space 1}    0.25{col 50}{space 3}0.801{col 58}{space 4}-.1770682{col 71}{space 3} .2275178
{txt}perc_b_1913_1922 {c |}{col 18}{res}{space 2} -.100694{col 30}{space 2} .2170083{col 41}{space 1}   -0.46{col 50}{space 3}0.646{col 58}{space 4}-.5432854{col 71}{space 3} .3418974
{txt}perc_b_1923_1932 {c |}{col 18}{res}{space 2}-.0011807{col 30}{space 2} .1751256{col 41}{space 1}   -0.01{col 50}{space 3}0.995{col 58}{space 4}-.3583517{col 71}{space 3} .3559904
{txt}{space 9}rdd_lat {c |}{col 18}{res}{space 2} 1581.801{col 30}{space 2} 2451.802{col 41}{space 1}    0.65{col 50}{space 3}0.524{col 58}{space 4}-3418.682{col 71}{space 3} 6582.285
{txt}{space 9}rdd_lon {c |}{col 18}{res}{space 2}-1540.867{col 30}{space 2} 894.6733{col 41}{space 1}   -1.72{col 50}{space 3}0.095{col 58}{space 4}-3365.565{col 71}{space 3} 283.8312
{txt}{space 7}rdd_lat_2 {c |}{col 18}{res}{space 2}-18.70323{col 30}{space 2} 25.06914{col 41}{space 1}   -0.75{col 50}{space 3}0.461{col 58}{space 4}-69.83207{col 71}{space 3} 32.42562
{txt}{space 7}rdd_lon_2 {c |}{col 18}{res}{space 2}-5.109721{col 30}{space 2} 7.270583{col 41}{space 1}   -0.70{col 50}{space 3}0.487{col 58}{space 4}-19.93817{col 71}{space 3} 9.718732
{txt}{space 5}rdd_lat_lon {c |}{col 18}{res}{space 2} 32.59186{col 30}{space 2} 17.77398{col 41}{space 1}    1.83{col 50}{space 3}0.076{col 58}{space 4}-3.658403{col 71}{space 3} 68.84212
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{help ivreg2##idtest:Underidentification test} (Kleibergen-Paap rk LM statistic):{res}{col 71}   6.939
{txt}{col 52}Chi-sq({res}1{txt}) P-val =  {res}{col 73}0.0084
{txt}{hline 78}
{help ivreg2##widtest:Weak identification test} (Cragg-Donald Wald F statistic):{res}{col 71}  10.570
{txt}                         (Kleibergen-Paap rk Wald F statistic):{res}{col 71}  17.576
{txt}Stock-Yogo weak ID test critical values:{res}{txt}{col 42}10% maximal IV size{res}{col 73} 16.38
{txt}{col 42}15% maximal IV size{res}{col 73}  8.96
{txt}{col 42}20% maximal IV size{res}{col 73}  6.66
{txt}{col 42}25% maximal IV size{res}{col 73}  5.53
{txt}Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.
{hline 78}
{help ivreg2##overidtests:Hansen J statistic} (overidentification test of all instruments):{res}{col 71}   0.000
{txt}{col 50}(equation exactly identified)
{hline 78}
Instrumented:{col 23}perc_i_full
Included instruments:{col 23}perc_b_1903_1912 perc_b_1913_1922 perc_b_1923_1932
{col 23}rdd_lat rdd_lon rdd_lat_2 rdd_lon_2 rdd_lat_lon
Excluded instruments:{col 23}perc_e_1908_1927
{help ivreg2##partial:Partialled-out}:{col 23}perc_prot_church pop_jew p_french_name lpop_1936
{col 23}perc_fore_1936 perc_dial_1936 perc_disp_1946 water
{col 23}lelevation_mean lelevation_std ldist_de perc_droi_1936_ins
{col 23}lpop_counter perc_fore perc_b_1928_1945 perc_b_1946_1964
{col 23}perc_b_1965_1980 perc_b_1981_1996 perc_male_counter
{col 23}perc_bacplus perc_bluecollar perc_chom lrev_median lrev_sd
{col 23}_cons
{col 23}nb: total SS, model F and R2s are after partialling-out;
{col 23}    any {help ivreg2##s_small:small-sample adjustments} include partialled-out
{col 23}    variables in regressor count K
{hline 78}
{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}  borderfe25{col 14}{c |}{space 1}        8{col 27}{space 1}        0{col 39}{result}{space 1}        8{col 53}{text} {col 54}{c |}
{res}{col 1}{text} dialect_lux{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text} {col 54}{c |}
{res}{col 1}{text} dialect_mos{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_rhe{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_pal{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_als{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_hau{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_lor{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_fra{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text}?{col 54}{c |}
{res}{col 1}{text}     pop_jew{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text}       water{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{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
{res}
{txt}added scalar:
               e(F_fs) =  {res}17.575737

{txt}added scalar:
             e(mean_y) =  {res}22.176476
{txt}(warning: absorbing 11 dimensions of fixed effects; check that you really want that)
{res}{txt}note: {res}variable #13{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}variable #19{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 8 iterations)
{res}
{txt}IV (2SLS) estimation
{hline 20}

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on ct_1936_enc

Number of clusters (ct_1936_enc) = {col 33}{res}    32{txt}{col 55}Number of obs = {res}     461
{txt}{col 55}F(  9,    31) = {res}    2.10
{txt}{col 55}Prob > F      = {res}  0.0610
{txt}Total (centered) SS     = {res} 7920.454445{txt}{col 55}Centered R2   = {res} -0.3727
{txt}Total (uncentered) SS   = {res} 7920.454445{txt}{col 55}Uncentered R2 = {res} -0.3727
{txt}Residual SS             = {res} 10872.23623{txt}{col 55}Root MSE      = {res}   5.125

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}perc_voixexd_ins{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}perc_i_full {c |}{col 18}{res}{space 2} .8624033{col 30}{space 2} .3764896{col 41}{space 1}    2.29{col 50}{space 3}0.029{col 58}{space 4} .0945477{col 71}{space 3} 1.630259
{txt}perc_b_1903_1912 {c |}{col 18}{res}{space 2} .0212677{col 30}{space 2} .0879521{col 41}{space 1}    0.24{col 50}{space 3}0.811{col 58}{space 4}-.1581117{col 71}{space 3} .2006471
{txt}perc_b_1913_1922 {c |}{col 18}{res}{space 2}  .043992{col 30}{space 2} .1565307{col 41}{space 1}    0.28{col 50}{space 3}0.781{col 58}{space 4}-.2752545{col 71}{space 3} .3632386
{txt}perc_b_1923_1932 {c |}{col 18}{res}{space 2}-.1002396{col 30}{space 2} .1280557{col 41}{space 1}   -0.78{col 50}{space 3}0.440{col 58}{space 4} -.361411{col 71}{space 3} .1609317
{txt}{space 9}rdd_lat {c |}{col 18}{res}{space 2} -1389.22{col 30}{space 2} 1792.153{col 41}{space 1}   -0.78{col 50}{space 3}0.444{col 58}{space 4}-5044.341{col 71}{space 3} 2265.901
{txt}{space 9}rdd_lon {c |}{col 18}{res}{space 2}-1533.682{col 30}{space 2} 966.2648{col 41}{space 1}   -1.59{col 50}{space 3}0.123{col 58}{space 4}-3504.392{col 71}{space 3} 437.0278
{txt}{space 7}rdd_lat_2 {c |}{col 18}{res}{space 2} 11.96323{col 30}{space 2} 18.00637{col 41}{space 1}    0.66{col 50}{space 3}0.511{col 58}{space 4}-24.76101{col 71}{space 3} 48.68747
{txt}{space 7}rdd_lon_2 {c |}{col 18}{res}{space 2} 5.310307{col 30}{space 2} 6.916429{col 41}{space 1}    0.77{col 50}{space 3}0.448{col 58}{space 4}-8.795844{col 71}{space 3} 19.41646
{txt}{space 5}rdd_lat_lon {c |}{col 18}{res}{space 2} 29.55472{col 30}{space 2}  19.3184{col 41}{space 1}    1.53{col 50}{space 3}0.136{col 58}{space 4} -9.84542{col 71}{space 3} 68.95486
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{help ivreg2##idtest:Underidentification test} (Kleibergen-Paap rk LM statistic):{res}{col 71}   6.901
{txt}{col 52}Chi-sq({res}1{txt}) P-val =  {res}{col 73}0.0086
{txt}{hline 78}
{help ivreg2##widtest:Weak identification test} (Cragg-Donald Wald F statistic):{res}{col 71}   9.883
{txt}                         (Kleibergen-Paap rk Wald F statistic):{res}{col 71}  15.543
{txt}Stock-Yogo weak ID test critical values:{res}{txt}{col 42}10% maximal IV size{res}{col 73} 16.38
{txt}{col 42}15% maximal IV size{res}{col 73}  8.96
{txt}{col 42}20% maximal IV size{res}{col 73}  6.66
{txt}{col 42}25% maximal IV size{res}{col 73}  5.53
{txt}Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.
{hline 78}
{help ivreg2##overidtests:Hansen J statistic} (overidentification test of all instruments):{res}{col 71}   0.000
{txt}{col 50}(equation exactly identified)
{hline 78}
Instrumented:{col 23}perc_i_full
Included instruments:{col 23}perc_b_1903_1912 perc_b_1913_1922 perc_b_1923_1932
{col 23}rdd_lat rdd_lon rdd_lat_2 rdd_lon_2 rdd_lat_lon
Excluded instruments:{col 23}perc_e_1908_1927
{help ivreg2##partial:Partialled-out}:{col 23}perc_prot_church pop_jew p_french_name lpop_1936
{col 23}perc_fore_1936 perc_dial_1936 perc_disp_1946 water
{col 23}lelevation_mean lelevation_std ldist_de perc_droi_1936_ins
{col 23}lpop_counter perc_fore perc_b_1928_1945 perc_b_1946_1964
{col 23}perc_b_1965_1980 perc_b_1981_1996 perc_male_counter
{col 23}perc_bacplus perc_bluecollar perc_chom lrev_median lrev_sd
{col 23}_cons
{col 23}nb: total SS, model F and R2s are after partialling-out;
{col 23}    any {help ivreg2##s_small:small-sample adjustments} include partialled-out
{col 23}    variables in regressor count K
{hline 78}
{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}  borderfe25{col 14}{c |}{space 1}        8{col 27}{space 1}        0{col 39}{result}{space 1}        8{col 53}{text} {col 54}{c |}
{res}{col 1}{text} dialect_lux{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text} {col 54}{c |}
{res}{col 1}{text} dialect_mos{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_rhe{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_pal{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_als{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_hau{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_lor{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_fra{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text}?{col 54}{c |}
{res}{col 1}{text}     pop_jew{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text}       water{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{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
{res}
{txt}added scalar:
               e(F_fs) =  {res}15.54311

{txt}added scalar:
             e(mean_y) =  {res}22.244451
{txt}(warning: absorbing 11 dimensions of fixed effects; check that you really want that)
{res}{txt}note: {res}variable #13{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}variable #19{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 8 iterations)
{res}
{txt}IV (2SLS) estimation
{hline 20}

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on ct_1936_enc

Number of clusters (ct_1936_enc) = {col 33}{res}    32{txt}{col 55}Number of obs = {res}     461
{txt}{col 55}F(  9,    31) = {res}    2.78
{txt}{col 55}Prob > F      = {res}  0.0165
{txt}Total (centered) SS     = {res} 5464.077522{txt}{col 55}Centered R2   = {res}  0.0422
{txt}Total (uncentered) SS   = {res} 5464.077522{txt}{col 55}Uncentered R2 = {res}  0.0422
{txt}Residual SS             = {res} 5233.336842{txt}{col 55}Root MSE      = {res}   3.555

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}perc_voixexd_ins{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}perc_i_full {c |}{col 18}{res}{space 2} .0174222{col 30}{space 2} .2351787{col 41}{space 1}    0.07{col 50}{space 3}0.941{col 58}{space 4} -.462228{col 71}{space 3} .4970724
{txt}perc_b_1903_1912 {c |}{col 18}{res}{space 2} .0486347{col 30}{space 2} .0607979{col 41}{space 1}    0.80{col 50}{space 3}0.430{col 58}{space 4}-.0753635{col 71}{space 3} .1726328
{txt}perc_b_1913_1922 {c |}{col 18}{res}{space 2}-.0099578{col 30}{space 2} .0915771{col 41}{space 1}   -0.11{col 50}{space 3}0.914{col 58}{space 4}-.1967305{col 71}{space 3} .1768148
{txt}perc_b_1923_1932 {c |}{col 18}{res}{space 2}-.0317421{col 30}{space 2} .0658509{col 41}{space 1}   -0.48{col 50}{space 3}0.633{col 58}{space 4}-.1660459{col 71}{space 3} .1025618
{txt}{space 9}rdd_lat {c |}{col 18}{res}{space 2} -2323.42{col 30}{space 2} 1063.559{col 41}{space 1}   -2.18{col 50}{space 3}0.037{col 58}{space 4}-4492.562{col 71}{space 3}-154.2781
{txt}{space 9}rdd_lon {c |}{col 18}{res}{space 2}-1426.774{col 30}{space 2}  553.987{col 41}{space 1}   -2.58{col 50}{space 3}0.015{col 58}{space 4}-2556.638{col 71}{space 3}-296.9105
{txt}{space 7}rdd_lat_2 {c |}{col 18}{res}{space 2} 21.66398{col 30}{space 2} 10.66307{col 41}{space 1}    2.03{col 50}{space 3}0.051{col 58}{space 4}-.0835027{col 71}{space 3} 43.41146
{txt}{space 7}rdd_lon_2 {c |}{col 18}{res}{space 2}-.9777352{col 30}{space 2} 4.414635{col 41}{space 1}   -0.22{col 50}{space 3}0.826{col 58}{space 4}-9.981443{col 71}{space 3} 8.025973
{txt}{space 5}rdd_lat_lon {c |}{col 18}{res}{space 2} 29.34782{col 30}{space 2}  10.9207{col 41}{space 1}    2.69{col 50}{space 3}0.011{col 58}{space 4} 7.074914{col 71}{space 3} 51.62073
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{help ivreg2##idtest:Underidentification test} (Kleibergen-Paap rk LM statistic):{res}{col 71}   7.774
{txt}{col 52}Chi-sq({res}1{txt}) P-val =  {res}{col 73}0.0053
{txt}{hline 78}
{help ivreg2##widtest:Weak identification test} (Cragg-Donald Wald F statistic):{res}{col 71}  11.300
{txt}                         (Kleibergen-Paap rk Wald F statistic):{res}{col 71}  21.236
{txt}Stock-Yogo weak ID test critical values:{res}{txt}{col 42}10% maximal IV size{res}{col 73} 16.38
{txt}{col 42}15% maximal IV size{res}{col 73}  8.96
{txt}{col 42}20% maximal IV size{res}{col 73}  6.66
{txt}{col 42}25% maximal IV size{res}{col 73}  5.53
{txt}Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.
{hline 78}
{help ivreg2##overidtests:Hansen J statistic} (overidentification test of all instruments):{res}{col 71}   0.000
{txt}{col 50}(equation exactly identified)
{hline 78}
Instrumented:{col 23}perc_i_full
Included instruments:{col 23}perc_b_1903_1912 perc_b_1913_1922 perc_b_1923_1932
{col 23}rdd_lat rdd_lon rdd_lat_2 rdd_lon_2 rdd_lat_lon
Excluded instruments:{col 23}perc_e_1908_1927
{help ivreg2##partial:Partialled-out}:{col 23}perc_prot_church pop_jew p_french_name lpop_1936
{col 23}perc_fore_1936 perc_dial_1936 perc_disp_1946 water
{col 23}lelevation_mean lelevation_std ldist_de perc_droi_1936_ins
{col 23}lpop_counter perc_fore perc_b_1928_1945 perc_b_1946_1964
{col 23}perc_b_1965_1980 perc_b_1981_1996 perc_male_counter
{col 23}perc_bacplus perc_bluecollar perc_chom lrev_median lrev_sd
{col 23}_cons
{col 23}nb: total SS, model F and R2s are after partialling-out;
{col 23}    any {help ivreg2##s_small:small-sample adjustments} include partialled-out
{col 23}    variables in regressor count K
{hline 78}
{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}  borderfe25{col 14}{c |}{space 1}        8{col 27}{space 1}        0{col 39}{result}{space 1}        8{col 53}{text} {col 54}{c |}
{res}{col 1}{text} dialect_lux{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text} {col 54}{c |}
{res}{col 1}{text} dialect_mos{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_rhe{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_pal{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_als{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_hau{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_lor{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_fra{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text}?{col 54}{c |}
{res}{col 1}{text}     pop_jew{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text}       water{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{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
{res}
{txt}added scalar:
               e(F_fs) =  {res}21.236336

{txt}added scalar:
             e(mean_y) =  {res}14.86625
{txt}(warning: absorbing 11 dimensions of fixed effects; check that you really want that)
{res}{txt}note: {res}variable #13{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}variable #19{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 8 iterations)
{res}
{txt}IV (2SLS) estimation
{hline 20}

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on ct_1936_enc

Number of clusters (ct_1936_enc) = {col 33}{res}    32{txt}{col 55}Number of obs = {res}     461
{txt}{col 55}F(  9,    31) = {res}    3.31
{txt}{col 55}Prob > F      = {res}  0.0061
{txt}Total (centered) SS     = {res}  7584.34179{txt}{col 55}Centered R2   = {res}  0.0624
{txt}Total (uncentered) SS   = {res}  7584.34179{txt}{col 55}Uncentered R2 = {res}  0.0624
{txt}Residual SS             = {res} 7110.748483{txt}{col 55}Root MSE      = {res}   4.144

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}perc_voixexd_ins{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}perc_i_full {c |}{col 18}{res}{space 2} .2341308{col 30}{space 2} .3308742{col 41}{space 1}    0.71{col 50}{space 3}0.484{col 58}{space 4}-.4406915{col 71}{space 3} .9089531
{txt}perc_b_1903_1912 {c |}{col 18}{res}{space 2}  .036988{col 30}{space 2} .0519826{col 41}{space 1}    0.71{col 50}{space 3}0.482{col 58}{space 4}-.0690312{col 71}{space 3} .1430072
{txt}perc_b_1913_1922 {c |}{col 18}{res}{space 2} -.009642{col 30}{space 2} .1369037{col 41}{space 1}   -0.07{col 50}{space 3}0.944{col 58}{space 4}-.2888588{col 71}{space 3} .2695749
{txt}perc_b_1923_1932 {c |}{col 18}{res}{space 2} .0781076{col 30}{space 2} .1036222{col 41}{space 1}    0.75{col 50}{space 3}0.457{col 58}{space 4}-.1332314{col 71}{space 3} .2894465
{txt}{space 9}rdd_lat {c |}{col 18}{res}{space 2}-3092.145{col 30}{space 2} 1033.386{col 41}{space 1}   -2.99{col 50}{space 3}0.005{col 58}{space 4}-5199.751{col 71}{space 3}-984.5393
{txt}{space 9}rdd_lon {c |}{col 18}{res}{space 2}-1719.927{col 30}{space 2} 668.2458{col 41}{space 1}   -2.57{col 50}{space 3}0.015{col 58}{space 4}-3082.824{col 71}{space 3} -357.031
{txt}{space 7}rdd_lat_2 {c |}{col 18}{res}{space 2} 29.13831{col 30}{space 2} 10.85654{col 41}{space 1}    2.68{col 50}{space 3}0.012{col 58}{space 4} 6.996246{col 71}{space 3} 51.28038
{txt}{space 7}rdd_lon_2 {c |}{col 18}{res}{space 2}-.6319732{col 30}{space 2} 4.959656{col 41}{space 1}   -0.13{col 50}{space 3}0.899{col 58}{space 4}-10.74726{col 71}{space 3} 9.483312
{txt}{space 5}rdd_lat_lon {c |}{col 18}{res}{space 2} 35.25432{col 30}{space 2} 13.60825{col 41}{space 1}    2.59{col 50}{space 3}0.014{col 58}{space 4} 7.500117{col 71}{space 3} 63.00853
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{help ivreg2##idtest:Underidentification test} (Kleibergen-Paap rk LM statistic):{res}{col 71}   7.487
{txt}{col 52}Chi-sq({res}1{txt}) P-val =  {res}{col 73}0.0062
{txt}{hline 78}
{help ivreg2##widtest:Weak identification test} (Cragg-Donald Wald F statistic):{res}{col 71}  10.470
{txt}                         (Kleibergen-Paap rk Wald F statistic):{res}{col 71}  15.057
{txt}Stock-Yogo weak ID test critical values:{res}{txt}{col 42}10% maximal IV size{res}{col 73} 16.38
{txt}{col 42}15% maximal IV size{res}{col 73}  8.96
{txt}{col 42}20% maximal IV size{res}{col 73}  6.66
{txt}{col 42}25% maximal IV size{res}{col 73}  5.53
{txt}Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.
{hline 78}
{help ivreg2##overidtests:Hansen J statistic} (overidentification test of all instruments):{res}{col 71}   0.000
{txt}{col 50}(equation exactly identified)
{hline 78}
Instrumented:{col 23}perc_i_full
Included instruments:{col 23}perc_b_1903_1912 perc_b_1913_1922 perc_b_1923_1932
{col 23}rdd_lat rdd_lon rdd_lat_2 rdd_lon_2 rdd_lat_lon
Excluded instruments:{col 23}perc_e_1908_1927
{help ivreg2##partial:Partialled-out}:{col 23}perc_prot_church pop_jew p_french_name lpop_1936
{col 23}perc_fore_1936 perc_dial_1936 perc_disp_1946 water
{col 23}lelevation_mean lelevation_std ldist_de perc_droi_1936_ins
{col 23}lpop_counter perc_fore perc_b_1928_1945 perc_b_1946_1964
{col 23}perc_b_1965_1980 perc_b_1981_1996 perc_male_counter
{col 23}perc_bacplus perc_bluecollar perc_chom lrev_median lrev_sd
{col 23}_cons
{col 23}nb: total SS, model F and R2s are after partialling-out;
{col 23}    any {help ivreg2##s_small:small-sample adjustments} include partialled-out
{col 23}    variables in regressor count K
{hline 78}
{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}  borderfe25{col 14}{c |}{space 1}        8{col 27}{space 1}        0{col 39}{result}{space 1}        8{col 53}{text} {col 54}{c |}
{res}{col 1}{text} dialect_lux{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text} {col 54}{c |}
{res}{col 1}{text} dialect_mos{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_rhe{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_pal{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_als{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_hau{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_lor{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_fra{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text}?{col 54}{c |}
{res}{col 1}{text}     pop_jew{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text}       water{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{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
{res}
{txt}added scalar:
               e(F_fs) =  {res}15.057351

{txt}added scalar:
             e(mean_y) =  {res}23.231457
{txt}(warning: absorbing 11 dimensions of fixed effects; check that you really want that)
{res}{txt}note: {res}variable #13{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}variable #19{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 8 iterations)
{res}
{txt}IV (2SLS) estimation
{hline 20}

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on ct_1936_enc

Number of clusters (ct_1936_enc) = {col 33}{res}    32{txt}{col 55}Number of obs = {res}     461
{txt}{col 55}F(  9,    31) = {res}    2.99
{txt}{col 55}Prob > F      = {res}  0.0110
{txt}Total (centered) SS     = {res} 9062.548825{txt}{col 55}Centered R2   = {res}  0.0453
{txt}Total (uncentered) SS   = {res} 9062.548825{txt}{col 55}Uncentered R2 = {res}  0.0453
{txt}Residual SS             = {res} 8651.651047{txt}{col 55}Root MSE      = {res}   4.571

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}perc_voixexd_ins{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}perc_i_full {c |}{col 18}{res}{space 2} .0806427{col 30}{space 2} .4025551{col 41}{space 1}    0.20{col 50}{space 3}0.843{col 58}{space 4}-.7403738{col 71}{space 3} .9016592
{txt}perc_b_1903_1912 {c |}{col 18}{res}{space 2} .1116479{col 30}{space 2} .0658046{col 41}{space 1}    1.70{col 50}{space 3}0.100{col 58}{space 4}-.0225614{col 71}{space 3} .2458571
{txt}perc_b_1913_1922 {c |}{col 18}{res}{space 2}-.0216066{col 30}{space 2} .0991561{col 41}{space 1}   -0.22{col 50}{space 3}0.829{col 58}{space 4}-.2238369{col 71}{space 3} .1806237
{txt}perc_b_1923_1932 {c |}{col 18}{res}{space 2} .1263144{col 30}{space 2} .1074856{col 41}{space 1}    1.18{col 50}{space 3}0.249{col 58}{space 4}-.0929039{col 71}{space 3} .3455327
{txt}{space 9}rdd_lat {c |}{col 18}{res}{space 2}-392.6963{col 30}{space 2} 2109.221{col 41}{space 1}   -0.19{col 50}{space 3}0.854{col 58}{space 4}-4694.481{col 71}{space 3} 3909.088
{txt}{space 9}rdd_lon {c |}{col 18}{res}{space 2}-979.3367{col 30}{space 2} 998.7233{col 41}{space 1}   -0.98{col 50}{space 3}0.334{col 58}{space 4}-3016.246{col 71}{space 3} 1057.573
{txt}{space 7}rdd_lat_2 {c |}{col 18}{res}{space 2} 2.722046{col 30}{space 2} 21.47451{col 41}{space 1}    0.13{col 50}{space 3}0.900{col 58}{space 4} -41.0755{col 71}{space 3} 46.51959
{txt}{space 7}rdd_lon_2 {c |}{col 18}{res}{space 2} 1.544891{col 30}{space 2} 4.096998{col 41}{space 1}    0.38{col 50}{space 3}0.709{col 58}{space 4}-6.810991{col 71}{space 3} 9.900773
{txt}{space 5}rdd_lat_lon {c |}{col 18}{res}{space 2} 19.47202{col 30}{space 2} 20.31867{col 41}{space 1}    0.96{col 50}{space 3}0.345{col 58}{space 4}-21.96818{col 71}{space 3} 60.91222
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{help ivreg2##idtest:Underidentification test} (Kleibergen-Paap rk LM statistic):{res}{col 71}   7.189
{txt}{col 52}Chi-sq({res}1{txt}) P-val =  {res}{col 73}0.0073
{txt}{hline 78}
{help ivreg2##widtest:Weak identification test} (Cragg-Donald Wald F statistic):{res}{col 71}  10.236
{txt}                         (Kleibergen-Paap rk Wald F statistic):{res}{col 71}  15.369
{txt}Stock-Yogo weak ID test critical values:{res}{txt}{col 42}10% maximal IV size{res}{col 73} 16.38
{txt}{col 42}15% maximal IV size{res}{col 73}  8.96
{txt}{col 42}20% maximal IV size{res}{col 73}  6.66
{txt}{col 42}25% maximal IV size{res}{col 73}  5.53
{txt}Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.
{hline 78}
{help ivreg2##overidtests:Hansen J statistic} (overidentification test of all instruments):{res}{col 71}   0.000
{txt}{col 50}(equation exactly identified)
{hline 78}
Instrumented:{col 23}perc_i_full
Included instruments:{col 23}perc_b_1903_1912 perc_b_1913_1922 perc_b_1923_1932
{col 23}rdd_lat rdd_lon rdd_lat_2 rdd_lon_2 rdd_lat_lon
Excluded instruments:{col 23}perc_e_1908_1927
{help ivreg2##partial:Partialled-out}:{col 23}perc_prot_church pop_jew p_french_name lpop_1936
{col 23}perc_fore_1936 perc_dial_1936 perc_disp_1946 water
{col 23}lelevation_mean lelevation_std ldist_de perc_droi_1936_ins
{col 23}lpop_counter perc_fore perc_b_1928_1945 perc_b_1946_1964
{col 23}perc_b_1965_1980 perc_b_1981_1996 perc_male_counter
{col 23}perc_bacplus perc_bluecollar perc_chom lrev_median lrev_sd
{col 23}_cons
{col 23}nb: total SS, model F and R2s are after partialling-out;
{col 23}    any {help ivreg2##s_small:small-sample adjustments} include partialled-out
{col 23}    variables in regressor count K
{hline 78}
{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}  borderfe25{col 14}{c |}{space 1}        8{col 27}{space 1}        0{col 39}{result}{space 1}        8{col 53}{text} {col 54}{c |}
{res}{col 1}{text} dialect_lux{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text} {col 54}{c |}
{res}{col 1}{text} dialect_mos{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_rhe{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_pal{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_als{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_hau{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_lor{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_fra{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text}?{col 54}{c |}
{res}{col 1}{text}     pop_jew{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text}       water{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{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
{res}
{txt}added scalar:
               e(F_fs) =  {res}15.369007

{txt}added scalar:
             e(mean_y) =  {res}27.261345
{txt}
{com}. 
. // Abstention
. 
. foreach year in 1965 1969 1974 1995 2002 2007 2012 2017{c -(}
{txt}  2{com}.         
.         ivreghdfe perc_bna_ins (perc_i_full = perc_e_1908_1927) ///
>                 perc_b_1903_1912 perc_b_1913_1922 perc_b_1923_1932 /// 
>                 $sigma $w $rdd2 /// 
>                 if annee==`year' & sample==1, cluster(ct_1936_enc) ///
>                 a(borderfe $dialect pop_jew water) partial($sigma $w)
{txt}  3{com}.                 
.         estimates store P`year'T1_ABST
{txt}  4{com}.         scalar f = e(rkf)
{txt}  5{com}.         estadd scalar F_fs=f
{txt}  6{com}.         qui sum perc_bna_ins if e(sample)
{txt}  7{com}.         scalar mean_y=r(mean)
{txt}  8{com}.         estadd scalar mean_y
{txt}  9{com}. 
. {c )-}
{res}{txt}(warning: absorbing 11 dimensions of fixed effects; check that you really want that)
{res}{txt}Warning - collinearities detected
Vars dropped:{col 21}perc_b_1981_1996
{res}{txt}note: {res}variable #13{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}variable #19{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 8 iterations)
{res}
{txt}IV (2SLS) estimation
{hline 20}

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on ct_1936_enc

Number of clusters (ct_1936_enc) = {col 33}{res}    32{txt}{col 55}Number of obs = {res}     461
{txt}{col 55}F(  9,    31) = {res}    6.07
{txt}{col 55}Prob > F      = {res}  0.0001
{txt}Total (centered) SS     = {res} 11651.46153{txt}{col 55}Centered R2   = {res} -0.3288
{txt}Total (uncentered) SS   = {res} 11651.46153{txt}{col 55}Uncentered R2 = {res} -0.3288
{txt}Residual SS             = {res} 15481.92285{txt}{col 55}Root MSE      = {res}   6.108

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}    perc_bna_ins{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}perc_i_full {c |}{col 18}{res}{space 2} 1.144489{col 30}{space 2} .4953306{col 41}{space 1}    2.31{col 50}{space 3}0.028{col 58}{space 4}  .134256{col 71}{space 3} 2.154723
{txt}perc_b_1903_1912 {c |}{col 18}{res}{space 2}-.1886397{col 30}{space 2} .0896289{col 41}{space 1}   -2.10{col 50}{space 3}0.044{col 58}{space 4}-.3714391{col 71}{space 3}-.0058404
{txt}perc_b_1913_1922 {c |}{col 18}{res}{space 2} .0654376{col 30}{space 2} .2008857{col 41}{space 1}    0.33{col 50}{space 3}0.747{col 58}{space 4}-.3442714{col 71}{space 3} .4751466
{txt}perc_b_1923_1932 {c |}{col 18}{res}{space 2}-.5062117{col 30}{space 2} .1570918{col 41}{space 1}   -3.22{col 50}{space 3}0.003{col 58}{space 4}-.8266024{col 71}{space 3}-.1858209
{txt}{space 9}rdd_lat {c |}{col 18}{res}{space 2} 1140.321{col 30}{space 2} 3160.183{col 41}{space 1}    0.36{col 50}{space 3}0.721{col 58}{space 4}-5304.913{col 71}{space 3} 7585.556
{txt}{space 9}rdd_lon {c |}{col 18}{res}{space 2} 652.3542{col 30}{space 2} 1195.513{col 41}{space 1}    0.55{col 50}{space 3}0.589{col 58}{space 4} -1785.91{col 71}{space 3} 3090.618
{txt}{space 7}rdd_lat_2 {c |}{col 18}{res}{space 2}-10.69913{col 30}{space 2} 31.58854{col 41}{space 1}   -0.34{col 50}{space 3}0.737{col 58}{space 4}-75.12439{col 71}{space 3} 53.72612
{txt}{space 7}rdd_lon_2 {c |}{col 18}{res}{space 2}-.2969349{col 30}{space 2} 7.909899{col 41}{space 1}   -0.04{col 50}{space 3}0.970{col 58}{space 4}-16.42928{col 71}{space 3} 15.83541
{txt}{space 5}rdd_lat_lon {c |}{col 18}{res}{space 2}-13.45714{col 30}{space 2} 23.79087{col 41}{space 1}   -0.57{col 50}{space 3}0.576{col 58}{space 4}-61.97893{col 71}{space 3} 35.06465
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{help ivreg2##idtest:Underidentification test} (Kleibergen-Paap rk LM statistic):{res}{col 71}   6.518
{txt}{col 52}Chi-sq({res}1{txt}) P-val =  {res}{col 73}0.0107
{txt}{hline 78}
{help ivreg2##widtest:Weak identification test} (Cragg-Donald Wald F statistic):{res}{col 71}   9.977
{txt}                         (Kleibergen-Paap rk Wald F statistic):{res}{col 71}  15.020
{txt}Stock-Yogo weak ID test critical values:{res}{txt}{col 42}10% maximal IV size{res}{col 73} 16.38
{txt}{col 42}15% maximal IV size{res}{col 73}  8.96
{txt}{col 42}20% maximal IV size{res}{col 73}  6.66
{txt}{col 42}25% maximal IV size{res}{col 73}  5.53
{txt}Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.
{hline 78}
{help ivreg2##overidtests:Hansen J statistic} (overidentification test of all instruments):{res}{col 71}   0.000
{txt}{col 50}(equation exactly identified)
{hline 78}
Instrumented:{col 23}perc_i_full
Included instruments:{col 23}perc_b_1903_1912 perc_b_1913_1922 perc_b_1923_1932
{col 23}rdd_lat rdd_lon rdd_lat_2 rdd_lon_2 rdd_lat_lon
Excluded instruments:{col 23}perc_e_1908_1927
{help ivreg2##partial:Partialled-out}:{col 23}perc_prot_church pop_jew p_french_name lpop_1936
{col 23}perc_fore_1936 perc_dial_1936 perc_disp_1946 water
{col 23}lelevation_mean lelevation_std ldist_de perc_droi_1936_ins
{col 23}lpop_counter perc_fore perc_b_1928_1945 perc_b_1946_1964
{col 23}perc_b_1965_1980 perc_male_counter perc_bacplus
{col 23}perc_bluecollar perc_chom lrev_median lrev_sd _cons
{col 23}nb: total SS, model F and R2s are after partialling-out;
{col 23}    any {help ivreg2##s_small:small-sample adjustments} include partialled-out
{col 23}    variables in regressor count K
Dropped collinear:{col 23}perc_b_1981_1996
{hline 78}
{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}  borderfe25{col 14}{c |}{space 1}        8{col 27}{space 1}        0{col 39}{result}{space 1}        8{col 53}{text} {col 54}{c |}
{res}{col 1}{text} dialect_lux{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text} {col 54}{c |}
{res}{col 1}{text} dialect_mos{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_rhe{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_pal{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_als{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_hau{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_lor{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_fra{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text}?{col 54}{c |}
{res}{col 1}{text}     pop_jew{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text}       water{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{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
{res}
{txt}added scalar:
               e(F_fs) =  {res}15.019628

{txt}added scalar:
             e(mean_y) =  {res}15.249096
{txt}(warning: absorbing 11 dimensions of fixed effects; check that you really want that)
{res}{txt}Warning - collinearities detected
Vars dropped:{col 21}perc_b_1981_1996
{res}{txt}note: {res}variable #13{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}variable #19{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 8 iterations)
{res}
{txt}IV (2SLS) estimation
{hline 20}

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on ct_1936_enc

Number of clusters (ct_1936_enc) = {col 33}{res}    32{txt}{col 55}Number of obs = {res}     461
{txt}{col 55}F(  9,    31) = {res}    1.86
{txt}{col 55}Prob > F      = {res}  0.0969
{txt}Total (centered) SS     = {res} 18476.68829{txt}{col 55}Centered R2   = {res} -0.5527
{txt}Total (uncentered) SS   = {res} 18476.68829{txt}{col 55}Uncentered R2 = {res} -0.5527
{txt}Residual SS             = {res} 28689.42406{txt}{col 55}Root MSE      = {res}   8.315

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}    perc_bna_ins{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}perc_i_full {c |}{col 18}{res}{space 2}  1.64528{col 30}{space 2} .7518721{col 41}{space 1}    2.19{col 50}{space 3}0.036{col 58}{space 4} .1118268{col 71}{space 3} 3.178733
{txt}perc_b_1903_1912 {c |}{col 18}{res}{space 2}-.1411236{col 30}{space 2} .1313375{col 41}{space 1}   -1.07{col 50}{space 3}0.291{col 58}{space 4}-.4089882{col 71}{space 3}  .126741
{txt}perc_b_1913_1922 {c |}{col 18}{res}{space 2} .0243438{col 30}{space 2} .2478696{col 41}{space 1}    0.10{col 50}{space 3}0.922{col 58}{space 4}-.4811896{col 71}{space 3} .5298772
{txt}perc_b_1923_1932 {c |}{col 18}{res}{space 2}-.5175639{col 30}{space 2} .2085799{col 41}{space 1}   -2.48{col 50}{space 3}0.019{col 58}{space 4}-.9429654{col 71}{space 3}-.0921625
{txt}{space 9}rdd_lat {c |}{col 18}{res}{space 2} 2215.133{col 30}{space 2} 3472.533{col 41}{space 1}    0.64{col 50}{space 3}0.528{col 58}{space 4}-4867.144{col 71}{space 3} 9297.411
{txt}{space 9}rdd_lon {c |}{col 18}{res}{space 2}-121.6048{col 30}{space 2} 1439.112{col 41}{space 1}   -0.08{col 50}{space 3}0.933{col 58}{space 4}-3056.693{col 71}{space 3} 2813.483
{txt}{space 7}rdd_lat_2 {c |}{col 18}{res}{space 2}-22.92584{col 30}{space 2} 35.52546{col 41}{space 1}   -0.65{col 50}{space 3}0.523{col 58}{space 4}-95.38049{col 71}{space 3} 49.52881
{txt}{space 7}rdd_lon_2 {c |}{col 18}{res}{space 2}-5.351427{col 30}{space 2} 9.883153{col 41}{space 1}   -0.54{col 50}{space 3}0.592{col 58}{space 4}-25.50825{col 71}{space 3}  14.8054
{txt}{space 5}rdd_lat_lon {c |}{col 18}{res}{space 2} 3.657642{col 30}{space 2} 28.16664{col 41}{space 1}    0.13{col 50}{space 3}0.898{col 58}{space 4} -53.7886{col 71}{space 3} 61.10388
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{help ivreg2##idtest:Underidentification test} (Kleibergen-Paap rk LM statistic):{res}{col 71}   6.689
{txt}{col 52}Chi-sq({res}1{txt}) P-val =  {res}{col 73}0.0097
{txt}{hline 78}
{help ivreg2##widtest:Weak identification test} (Cragg-Donald Wald F statistic):{res}{col 71}  10.989
{txt}                         (Kleibergen-Paap rk Wald F statistic):{res}{col 71}  16.147
{txt}Stock-Yogo weak ID test critical values:{res}{txt}{col 42}10% maximal IV size{res}{col 73} 16.38
{txt}{col 42}15% maximal IV size{res}{col 73}  8.96
{txt}{col 42}20% maximal IV size{res}{col 73}  6.66
{txt}{col 42}25% maximal IV size{res}{col 73}  5.53
{txt}Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.
{hline 78}
{help ivreg2##overidtests:Hansen J statistic} (overidentification test of all instruments):{res}{col 71}   0.000
{txt}{col 50}(equation exactly identified)
{hline 78}
Instrumented:{col 23}perc_i_full
Included instruments:{col 23}perc_b_1903_1912 perc_b_1913_1922 perc_b_1923_1932
{col 23}rdd_lat rdd_lon rdd_lat_2 rdd_lon_2 rdd_lat_lon
Excluded instruments:{col 23}perc_e_1908_1927
{help ivreg2##partial:Partialled-out}:{col 23}perc_prot_church pop_jew p_french_name lpop_1936
{col 23}perc_fore_1936 perc_dial_1936 perc_disp_1946 water
{col 23}lelevation_mean lelevation_std ldist_de perc_droi_1936_ins
{col 23}lpop_counter perc_fore perc_b_1928_1945 perc_b_1946_1964
{col 23}perc_b_1965_1980 perc_male_counter perc_bacplus
{col 23}perc_bluecollar perc_chom lrev_median lrev_sd _cons
{col 23}nb: total SS, model F and R2s are after partialling-out;
{col 23}    any {help ivreg2##s_small:small-sample adjustments} include partialled-out
{col 23}    variables in regressor count K
Dropped collinear:{col 23}perc_b_1981_1996
{hline 78}
{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}  borderfe25{col 14}{c |}{space 1}        8{col 27}{space 1}        0{col 39}{result}{space 1}        8{col 53}{text} {col 54}{c |}
{res}{col 1}{text} dialect_lux{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text} {col 54}{c |}
{res}{col 1}{text} dialect_mos{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_rhe{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_pal{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_als{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_hau{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_lor{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_fra{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text}?{col 54}{c |}
{res}{col 1}{text}     pop_jew{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text}       water{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{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
{res}
{txt}added scalar:
               e(F_fs) =  {res}16.147344

{txt}added scalar:
             e(mean_y) =  {res}23.581786
{txt}(warning: absorbing 11 dimensions of fixed effects; check that you really want that)
{res}{txt}Warning - collinearities detected
Vars dropped:{col 21}perc_b_1981_1996
{res}{txt}note: {res}variable #13{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}variable #19{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 8 iterations)
{res}
{txt}IV (2SLS) estimation
{hline 20}

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on ct_1936_enc

Number of clusters (ct_1936_enc) = {col 33}{res}    32{txt}{col 55}Number of obs = {res}     461
{txt}{col 55}F(  9,    31) = {res}    2.04
{txt}{col 55}Prob > F      = {res}  0.0675
{txt}Total (centered) SS     = {res} 8856.052586{txt}{col 55}Centered R2   = {res} -0.2343
{txt}Total (uncentered) SS   = {res} 8856.052586{txt}{col 55}Uncentered R2 = {res} -0.2343
{txt}Residual SS             = {res} 10931.29238{txt}{col 55}Root MSE      = {res}   5.132

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}    perc_bna_ins{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}perc_i_full {c |}{col 18}{res}{space 2} .8807469{col 30}{space 2}  .385914{col 41}{space 1}    2.28{col 50}{space 3}0.029{col 58}{space 4} .0936701{col 71}{space 3} 1.667824
{txt}perc_b_1903_1912 {c |}{col 18}{res}{space 2}-.0413195{col 30}{space 2} .0919786{col 41}{space 1}   -0.45{col 50}{space 3}0.656{col 58}{space 4}-.2289112{col 71}{space 3} .1462721
{txt}perc_b_1913_1922 {c |}{col 18}{res}{space 2}-.1006792{col 30}{space 2} .1612604{col 41}{space 1}   -0.62{col 50}{space 3}0.537{col 58}{space 4} -.429572{col 71}{space 3} .2282135
{txt}perc_b_1923_1932 {c |}{col 18}{res}{space 2}-.1150245{col 30}{space 2} .1476119{col 41}{space 1}   -0.78{col 50}{space 3}0.442{col 58}{space 4} -.416081{col 71}{space 3}  .186032
{txt}{space 9}rdd_lat {c |}{col 18}{res}{space 2} 92.13586{col 30}{space 2} 1449.859{col 41}{space 1}    0.06{col 50}{space 3}0.950{col 58}{space 4} -2864.87{col 71}{space 3} 3049.142
{txt}{space 9}rdd_lon {c |}{col 18}{res}{space 2}-1475.598{col 30}{space 2} 612.0802{col 41}{space 1}   -2.41{col 50}{space 3}0.022{col 58}{space 4}-2723.944{col 71}{space 3}-227.2523
{txt}{space 7}rdd_lat_2 {c |}{col 18}{res}{space 2}-3.223335{col 30}{space 2}  14.7328{col 41}{space 1}   -0.22{col 50}{space 3}0.828{col 58}{space 4}-33.27107{col 71}{space 3}  26.8244
{txt}{space 7}rdd_lon_2 {c |}{col 18}{res}{space 2}-4.780939{col 30}{space 2} 4.233056{col 41}{space 1}   -1.13{col 50}{space 3}0.267{col 58}{space 4}-13.41431{col 71}{space 3} 3.852435
{txt}{space 5}rdd_lat_lon {c |}{col 18}{res}{space 2} 31.44183{col 30}{space 2} 11.99604{col 41}{space 1}    2.62{col 50}{space 3}0.013{col 58}{space 4} 6.975739{col 71}{space 3} 55.90791
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{help ivreg2##idtest:Underidentification test} (Kleibergen-Paap rk LM statistic):{res}{col 71}   6.631
{txt}{col 52}Chi-sq({res}1{txt}) P-val =  {res}{col 73}0.0100
{txt}{hline 78}
{help ivreg2##widtest:Weak identification test} (Cragg-Donald Wald F statistic):{res}{col 71}  11.443
{txt}                         (Kleibergen-Paap rk Wald F statistic):{res}{col 71}  16.992
{txt}Stock-Yogo weak ID test critical values:{res}{txt}{col 42}10% maximal IV size{res}{col 73} 16.38
{txt}{col 42}15% maximal IV size{res}{col 73}  8.96
{txt}{col 42}20% maximal IV size{res}{col 73}  6.66
{txt}{col 42}25% maximal IV size{res}{col 73}  5.53
{txt}Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.
{hline 78}
{help ivreg2##overidtests:Hansen J statistic} (overidentification test of all instruments):{res}{col 71}   0.000
{txt}{col 50}(equation exactly identified)
{hline 78}
Instrumented:{col 23}perc_i_full
Included instruments:{col 23}perc_b_1903_1912 perc_b_1913_1922 perc_b_1923_1932
{col 23}rdd_lat rdd_lon rdd_lat_2 rdd_lon_2 rdd_lat_lon
Excluded instruments:{col 23}perc_e_1908_1927
{help ivreg2##partial:Partialled-out}:{col 23}perc_prot_church pop_jew p_french_name lpop_1936
{col 23}perc_fore_1936 perc_dial_1936 perc_disp_1946 water
{col 23}lelevation_mean lelevation_std ldist_de perc_droi_1936_ins
{col 23}lpop_counter perc_fore perc_b_1928_1945 perc_b_1946_1964
{col 23}perc_b_1965_1980 perc_male_counter perc_bacplus
{col 23}perc_bluecollar perc_chom lrev_median lrev_sd _cons
{col 23}nb: total SS, model F and R2s are after partialling-out;
{col 23}    any {help ivreg2##s_small:small-sample adjustments} include partialled-out
{col 23}    variables in regressor count K
Dropped collinear:{col 23}perc_b_1981_1996
{hline 78}
{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}  borderfe25{col 14}{c |}{space 1}        8{col 27}{space 1}        0{col 39}{result}{space 1}        8{col 53}{text} {col 54}{c |}
{res}{col 1}{text} dialect_lux{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text} {col 54}{c |}
{res}{col 1}{text} dialect_mos{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_rhe{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_pal{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_als{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_hau{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_lor{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_fra{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text}?{col 54}{c |}
{res}{col 1}{text}     pop_jew{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text}       water{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{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
{res}
{txt}added scalar:
               e(F_fs) =  {res}16.991883

{txt}added scalar:
             e(mean_y) =  {res}17.035087
{txt}(warning: absorbing 11 dimensions of fixed effects; check that you really want that)
{res}{txt}note: {res}variable #13{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}variable #19{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 8 iterations)
{res}
{txt}IV (2SLS) estimation
{hline 20}

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on ct_1936_enc

Number of clusters (ct_1936_enc) = {col 33}{res}    32{txt}{col 55}Number of obs = {res}     461
{txt}{col 55}F(  9,    31) = {res}    1.10
{txt}{col 55}Prob > F      = {res}  0.3892
{txt}Total (centered) SS     = {res} 5963.638638{txt}{col 55}Centered R2   = {res} -0.0392
{txt}Total (uncentered) SS   = {res} 5963.638638{txt}{col 55}Uncentered R2 = {res} -0.0392
{txt}Residual SS             = {res} 6197.271231{txt}{col 55}Root MSE      = {res}   3.869

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}    perc_bna_ins{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}perc_i_full {c |}{col 18}{res}{space 2}-.2022867{col 30}{space 2} .2427279{col 41}{space 1}   -0.83{col 50}{space 3}0.411{col 58}{space 4}-.6973335{col 71}{space 3}   .29276
{txt}perc_b_1903_1912 {c |}{col 18}{res}{space 2}  .073154{col 30}{space 2} .0618943{col 41}{space 1}    1.18{col 50}{space 3}0.246{col 58}{space 4}-.0530802{col 71}{space 3} .1993882
{txt}perc_b_1913_1922 {c |}{col 18}{res}{space 2} .0099482{col 30}{space 2}  .112736{col 41}{space 1}    0.09{col 50}{space 3}0.930{col 58}{space 4}-.2199783{col 71}{space 3} .2398747
{txt}perc_b_1923_1932 {c |}{col 18}{res}{space 2}-.1064724{col 30}{space 2} .0663689{col 41}{space 1}   -1.60{col 50}{space 3}0.119{col 58}{space 4}-.2418327{col 71}{space 3} .0288879
{txt}{space 9}rdd_lat {c |}{col 18}{res}{space 2}-2470.388{col 30}{space 2} 2145.691{col 41}{space 1}   -1.15{col 50}{space 3}0.258{col 58}{space 4}-6846.554{col 71}{space 3} 1905.777
{txt}{space 9}rdd_lon {c |}{col 18}{res}{space 2}-284.5312{col 30}{space 2} 627.7266{col 41}{space 1}   -0.45{col 50}{space 3}0.654{col 58}{space 4}-1564.788{col 71}{space 3} 995.7257
{txt}{space 7}rdd_lat_2 {c |}{col 18}{res}{space 2} 24.97718{col 30}{space 2} 21.50079{col 41}{space 1}    1.16{col 50}{space 3}0.254{col 58}{space 4}-18.87397{col 71}{space 3} 68.82833
{txt}{space 7}rdd_lon_2 {c |}{col 18}{res}{space 2} 2.280888{col 30}{space 2} 3.945531{col 41}{space 1}    0.58{col 50}{space 3}0.567{col 58}{space 4}-5.766076{col 71}{space 3} 10.32785
{txt}{space 5}rdd_lat_lon {c |}{col 18}{res}{space 2} 5.218877{col 30}{space 2}  12.7442{col 41}{space 1}    0.41{col 50}{space 3}0.685{col 58}{space 4} -20.7731{col 71}{space 3} 31.21085
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{help ivreg2##idtest:Underidentification test} (Kleibergen-Paap rk LM statistic):{res}{col 71}   6.939
{txt}{col 52}Chi-sq({res}1{txt}) P-val =  {res}{col 73}0.0084
{txt}{hline 78}
{help ivreg2##widtest:Weak identification test} (Cragg-Donald Wald F statistic):{res}{col 71}  10.570
{txt}                         (Kleibergen-Paap rk Wald F statistic):{res}{col 71}  17.576
{txt}Stock-Yogo weak ID test critical values:{res}{txt}{col 42}10% maximal IV size{res}{col 73} 16.38
{txt}{col 42}15% maximal IV size{res}{col 73}  8.96
{txt}{col 42}20% maximal IV size{res}{col 73}  6.66
{txt}{col 42}25% maximal IV size{res}{col 73}  5.53
{txt}Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.
{hline 78}
{help ivreg2##overidtests:Hansen J statistic} (overidentification test of all instruments):{res}{col 71}   0.000
{txt}{col 50}(equation exactly identified)
{hline 78}
Instrumented:{col 23}perc_i_full
Included instruments:{col 23}perc_b_1903_1912 perc_b_1913_1922 perc_b_1923_1932
{col 23}rdd_lat rdd_lon rdd_lat_2 rdd_lon_2 rdd_lat_lon
Excluded instruments:{col 23}perc_e_1908_1927
{help ivreg2##partial:Partialled-out}:{col 23}perc_prot_church pop_jew p_french_name lpop_1936
{col 23}perc_fore_1936 perc_dial_1936 perc_disp_1946 water
{col 23}lelevation_mean lelevation_std ldist_de perc_droi_1936_ins
{col 23}lpop_counter perc_fore perc_b_1928_1945 perc_b_1946_1964
{col 23}perc_b_1965_1980 perc_b_1981_1996 perc_male_counter
{col 23}perc_bacplus perc_bluecollar perc_chom lrev_median lrev_sd
{col 23}_cons
{col 23}nb: total SS, model F and R2s are after partialling-out;
{col 23}    any {help ivreg2##s_small:small-sample adjustments} include partialled-out
{col 23}    variables in regressor count K
{hline 78}
{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}  borderfe25{col 14}{c |}{space 1}        8{col 27}{space 1}        0{col 39}{result}{space 1}        8{col 53}{text} {col 54}{c |}
{res}{col 1}{text} dialect_lux{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text} {col 54}{c |}
{res}{col 1}{text} dialect_mos{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_rhe{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_pal{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_als{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_hau{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_lor{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_fra{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text}?{col 54}{c |}
{res}{col 1}{text}     pop_jew{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text}       water{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{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
{res}
{txt}added scalar:
               e(F_fs) =  {res}17.575737

{txt}added scalar:
             e(mean_y) =  {res}19.770708
{txt}(warning: absorbing 11 dimensions of fixed effects; check that you really want that)
{res}{txt}note: {res}variable #13{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}variable #19{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 8 iterations)
{res}
{txt}IV (2SLS) estimation
{hline 20}

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on ct_1936_enc

Number of clusters (ct_1936_enc) = {col 33}{res}    32{txt}{col 55}Number of obs = {res}     461
{txt}{col 55}F(  9,    31) = {res}    2.76
{txt}{col 55}Prob > F      = {res}  0.0170
{txt}Total (centered) SS     = {res} 8927.807775{txt}{col 55}Centered R2   = {res} -0.5780
{txt}Total (uncentered) SS   = {res} 8927.807775{txt}{col 55}Uncentered R2 = {res} -0.5780
{txt}Residual SS             = {res} 14088.43427{txt}{col 55}Root MSE      = {res}   5.834

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}    perc_bna_ins{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}perc_i_full {c |}{col 18}{res}{space 2}-.9163402{col 30}{space 2} .3611299{col 41}{space 1}   -2.54{col 50}{space 3}0.016{col 58}{space 4} -1.65287{col 71}{space 3}-.1798108
{txt}perc_b_1903_1912 {c |}{col 18}{res}{space 2} .0370633{col 30}{space 2} .1211799{col 41}{space 1}    0.31{col 50}{space 3}0.762{col 58}{space 4}-.2100847{col 71}{space 3} .2842112
{txt}perc_b_1913_1922 {c |}{col 18}{res}{space 2} .0234324{col 30}{space 2} .1440405{col 41}{space 1}    0.16{col 50}{space 3}0.872{col 58}{space 4}-.2703401{col 71}{space 3}  .317205
{txt}perc_b_1923_1932 {c |}{col 18}{res}{space 2} .0463855{col 30}{space 2}   .15744{col 41}{space 1}    0.29{col 50}{space 3}0.770{col 58}{space 4}-.2747154{col 71}{space 3} .3674865
{txt}{space 9}rdd_lat {c |}{col 18}{res}{space 2}-902.9596{col 30}{space 2} 2062.866{col 41}{space 1}   -0.44{col 50}{space 3}0.665{col 58}{space 4}-5110.203{col 71}{space 3} 3304.284
{txt}{space 9}rdd_lon {c |}{col 18}{res}{space 2}-886.2706{col 30}{space 2}   971.07{col 41}{space 1}   -0.91{col 50}{space 3}0.368{col 58}{space 4}-2866.781{col 71}{space 3}  1094.24
{txt}{space 7}rdd_lat_2 {c |}{col 18}{res}{space 2} 7.966612{col 30}{space 2} 20.79789{col 41}{space 1}    0.38{col 50}{space 3}0.704{col 58}{space 4}-34.45096{col 71}{space 3} 50.38418
{txt}{space 7}rdd_lon_2 {c |}{col 18}{res}{space 2}-1.556142{col 30}{space 2}  6.50106{col 41}{space 1}   -0.24{col 50}{space 3}0.812{col 58}{space 4}-14.81514{col 71}{space 3} 11.70286
{txt}{space 5}rdd_lat_lon {c |}{col 18}{res}{space 2} 18.69927{col 30}{space 2} 19.42778{col 41}{space 1}    0.96{col 50}{space 3}0.343{col 58}{space 4}-20.92395{col 71}{space 3} 58.32249
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{help ivreg2##idtest:Underidentification test} (Kleibergen-Paap rk LM statistic):{res}{col 71}   6.901
{txt}{col 52}Chi-sq({res}1{txt}) P-val =  {res}{col 73}0.0086
{txt}{hline 78}
{help ivreg2##widtest:Weak identification test} (Cragg-Donald Wald F statistic):{res}{col 71}   9.883
{txt}                         (Kleibergen-Paap rk Wald F statistic):{res}{col 71}  15.543
{txt}Stock-Yogo weak ID test critical values:{res}{txt}{col 42}10% maximal IV size{res}{col 73} 16.38
{txt}{col 42}15% maximal IV size{res}{col 73}  8.96
{txt}{col 42}20% maximal IV size{res}{col 73}  6.66
{txt}{col 42}25% maximal IV size{res}{col 73}  5.53
{txt}Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.
{hline 78}
{help ivreg2##overidtests:Hansen J statistic} (overidentification test of all instruments):{res}{col 71}   0.000
{txt}{col 50}(equation exactly identified)
{hline 78}
Instrumented:{col 23}perc_i_full
Included instruments:{col 23}perc_b_1903_1912 perc_b_1913_1922 perc_b_1923_1932
{col 23}rdd_lat rdd_lon rdd_lat_2 rdd_lon_2 rdd_lat_lon
Excluded instruments:{col 23}perc_e_1908_1927
{help ivreg2##partial:Partialled-out}:{col 23}perc_prot_church pop_jew p_french_name lpop_1936
{col 23}perc_fore_1936 perc_dial_1936 perc_disp_1946 water
{col 23}lelevation_mean lelevation_std ldist_de perc_droi_1936_ins
{col 23}lpop_counter perc_fore perc_b_1928_1945 perc_b_1946_1964
{col 23}perc_b_1965_1980 perc_b_1981_1996 perc_male_counter
{col 23}perc_bacplus perc_bluecollar perc_chom lrev_median lrev_sd
{col 23}_cons
{col 23}nb: total SS, model F and R2s are after partialling-out;
{col 23}    any {help ivreg2##s_small:small-sample adjustments} include partialled-out
{col 23}    variables in regressor count K
{hline 78}
{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}  borderfe25{col 14}{c |}{space 1}        8{col 27}{space 1}        0{col 39}{result}{space 1}        8{col 53}{text} {col 54}{c |}
{res}{col 1}{text} dialect_lux{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text} {col 54}{c |}
{res}{col 1}{text} dialect_mos{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_rhe{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_pal{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_als{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_hau{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_lor{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_fra{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text}?{col 54}{c |}
{res}{col 1}{text}     pop_jew{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text}       water{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{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
{res}
{txt}added scalar:
               e(F_fs) =  {res}15.54311

{txt}added scalar:
             e(mean_y) =  {res}28.377338
{txt}(warning: absorbing 11 dimensions of fixed effects; check that you really want that)
{res}{txt}note: {res}variable #13{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}variable #19{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 8 iterations)
{res}
{txt}IV (2SLS) estimation
{hline 20}

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on ct_1936_enc

Number of clusters (ct_1936_enc) = {col 33}{res}    32{txt}{col 55}Number of obs = {res}     461
{txt}{col 55}F(  9,    31) = {res}    1.50
{txt}{col 55}Prob > F      = {res}  0.1911
{txt}Total (centered) SS     = {res} 4168.077339{txt}{col 55}Centered R2   = {res} -0.2911
{txt}Total (uncentered) SS   = {res} 4168.077339{txt}{col 55}Uncentered R2 = {res} -0.2911
{txt}Residual SS             = {res} 5381.466398{txt}{col 55}Root MSE      = {res}   3.605

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}    perc_bna_ins{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}perc_i_full {c |}{col 18}{res}{space 2}  .465128{col 30}{space 2} .2283772{col 41}{space 1}    2.04{col 50}{space 3}0.050{col 58}{space 4}-.0006504{col 71}{space 3} .9309064
{txt}perc_b_1903_1912 {c |}{col 18}{res}{space 2} -.003173{col 30}{space 2}  .060622{col 41}{space 1}   -0.05{col 50}{space 3}0.959{col 58}{space 4}-.1268123{col 71}{space 3} .1204663
{txt}perc_b_1913_1922 {c |}{col 18}{res}{space 2}-.0451928{col 30}{space 2} .1063369{col 41}{space 1}   -0.42{col 50}{space 3}0.674{col 58}{space 4}-.2620683{col 71}{space 3} .1716828
{txt}perc_b_1923_1932 {c |}{col 18}{res}{space 2}-.0459747{col 30}{space 2} .0917184{col 41}{space 1}   -0.50{col 50}{space 3}0.620{col 58}{space 4}-.2330355{col 71}{space 3} .1410862
{txt}{space 9}rdd_lat {c |}{col 18}{res}{space 2}-712.6445{col 30}{space 2} 1475.185{col 41}{space 1}   -0.48{col 50}{space 3}0.632{col 58}{space 4}-3721.305{col 71}{space 3} 2296.016
{txt}{space 9}rdd_lon {c |}{col 18}{res}{space 2}-1009.793{col 30}{space 2} 593.1301{col 41}{space 1}   -1.70{col 50}{space 3}0.099{col 58}{space 4} -2219.49{col 71}{space 3} 199.9038
{txt}{space 7}rdd_lat_2 {c |}{col 18}{res}{space 2} 5.987867{col 30}{space 2} 14.92077{col 41}{space 1}    0.40{col 50}{space 3}0.691{col 58}{space 4}-24.44324{col 71}{space 3} 36.41897
{txt}{space 7}rdd_lon_2 {c |}{col 18}{res}{space 2} 8.995635{col 30}{space 2}   3.8686{col 41}{space 1}    2.33{col 50}{space 3}0.027{col 58}{space 4} 1.105574{col 71}{space 3}  16.8857
{txt}{space 5}rdd_lat_lon {c |}{col 18}{res}{space 2} 17.94582{col 30}{space 2} 11.64382{col 41}{space 1}    1.54{col 50}{space 3}0.133{col 58}{space 4}-5.801917{col 71}{space 3} 41.69355
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{help ivreg2##idtest:Underidentification test} (Kleibergen-Paap rk LM statistic):{res}{col 71}   7.774
{txt}{col 52}Chi-sq({res}1{txt}) P-val =  {res}{col 73}0.0053
{txt}{hline 78}
{help ivreg2##widtest:Weak identification test} (Cragg-Donald Wald F statistic):{res}{col 71}  11.300
{txt}                         (Kleibergen-Paap rk Wald F statistic):{res}{col 71}  21.236
{txt}Stock-Yogo weak ID test critical values:{res}{txt}{col 42}10% maximal IV size{res}{col 73} 16.38
{txt}{col 42}15% maximal IV size{res}{col 73}  8.96
{txt}{col 42}20% maximal IV size{res}{col 73}  6.66
{txt}{col 42}25% maximal IV size{res}{col 73}  5.53
{txt}Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.
{hline 78}
{help ivreg2##overidtests:Hansen J statistic} (overidentification test of all instruments):{res}{col 71}   0.000
{txt}{col 50}(equation exactly identified)
{hline 78}
Instrumented:{col 23}perc_i_full
Included instruments:{col 23}perc_b_1903_1912 perc_b_1913_1922 perc_b_1923_1932
{col 23}rdd_lat rdd_lon rdd_lat_2 rdd_lon_2 rdd_lat_lon
Excluded instruments:{col 23}perc_e_1908_1927
{help ivreg2##partial:Partialled-out}:{col 23}perc_prot_church pop_jew p_french_name lpop_1936
{col 23}perc_fore_1936 perc_dial_1936 perc_disp_1946 water
{col 23}lelevation_mean lelevation_std ldist_de perc_droi_1936_ins
{col 23}lpop_counter perc_fore perc_b_1928_1945 perc_b_1946_1964
{col 23}perc_b_1965_1980 perc_b_1981_1996 perc_male_counter
{col 23}perc_bacplus perc_bluecollar perc_chom lrev_median lrev_sd
{col 23}_cons
{col 23}nb: total SS, model F and R2s are after partialling-out;
{col 23}    any {help ivreg2##s_small:small-sample adjustments} include partialled-out
{col 23}    variables in regressor count K
{hline 78}
{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}  borderfe25{col 14}{c |}{space 1}        8{col 27}{space 1}        0{col 39}{result}{space 1}        8{col 53}{text} {col 54}{c |}
{res}{col 1}{text} dialect_lux{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text} {col 54}{c |}
{res}{col 1}{text} dialect_mos{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_rhe{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_pal{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_als{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_hau{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_lor{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_fra{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text}?{col 54}{c |}
{res}{col 1}{text}     pop_jew{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text}       water{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{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
{res}
{txt}added scalar:
               e(F_fs) =  {res}21.236336

{txt}added scalar:
             e(mean_y) =  {res}16.723038
{txt}(warning: absorbing 11 dimensions of fixed effects; check that you really want that)
{res}{txt}note: {res}variable #13{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}variable #19{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 8 iterations)
{res}
{txt}IV (2SLS) estimation
{hline 20}

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on ct_1936_enc

Number of clusters (ct_1936_enc) = {col 33}{res}    32{txt}{col 55}Number of obs = {res}     461
{txt}{col 55}F(  9,    31) = {res}    2.46
{txt}{col 55}Prob > F      = {res}  0.0300
{txt}Total (centered) SS     = {res}  5072.10631{txt}{col 55}Centered R2   = {res}  0.0083
{txt}Total (uncentered) SS   = {res}  5072.10631{txt}{col 55}Uncentered R2 = {res}  0.0083
{txt}Residual SS             = {res} 5029.880834{txt}{col 55}Root MSE      = {res}   3.486

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}    perc_bna_ins{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}perc_i_full {c |}{col 18}{res}{space 2} .1841015{col 30}{space 2} .3011778{col 41}{space 1}    0.61{col 50}{space 3}0.545{col 58}{space 4}-.4301547{col 71}{space 3} .7983576
{txt}perc_b_1903_1912 {c |}{col 18}{res}{space 2}-.0028853{col 30}{space 2} .0845775{col 41}{space 1}   -0.03{col 50}{space 3}0.973{col 58}{space 4}-.1753822{col 71}{space 3} .1696115
{txt}perc_b_1913_1922 {c |}{col 18}{res}{space 2}-.0580417{col 30}{space 2} .1054261{col 41}{space 1}   -0.55{col 50}{space 3}0.586{col 58}{space 4}-.2730597{col 71}{space 3} .1569762
{txt}perc_b_1923_1932 {c |}{col 18}{res}{space 2}-.0511339{col 30}{space 2} .1011335{col 41}{space 1}   -0.51{col 50}{space 3}0.617{col 58}{space 4} -.257397{col 71}{space 3} .1551291
{txt}{space 9}rdd_lat {c |}{col 18}{res}{space 2} 37.27498{col 30}{space 2} 967.3492{col 41}{space 1}    0.04{col 50}{space 3}0.970{col 58}{space 4}-1935.647{col 71}{space 3} 2010.197
{txt}{space 9}rdd_lon {c |}{col 18}{res}{space 2}-1189.463{col 30}{space 2} 477.3399{col 41}{space 1}   -2.49{col 50}{space 3}0.018{col 58}{space 4}-2163.005{col 71}{space 3}-215.9222
{txt}{space 7}rdd_lat_2 {c |}{col 18}{res}{space 2}-2.069627{col 30}{space 2} 9.823573{col 41}{space 1}   -0.21{col 50}{space 3}0.835{col 58}{space 4}-22.10494{col 71}{space 3} 17.96568
{txt}{space 7}rdd_lon_2 {c |}{col 18}{res}{space 2} 4.633612{col 30}{space 2} 4.013401{col 41}{space 1}    1.15{col 50}{space 3}0.257{col 58}{space 4}-3.551774{col 71}{space 3}   12.819
{txt}{space 5}rdd_lat_lon {c |}{col 18}{res}{space 2} 22.87028{col 30}{space 2} 9.405975{col 41}{space 1}    2.43{col 50}{space 3}0.021{col 58}{space 4} 3.686667{col 71}{space 3} 42.05389
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{help ivreg2##idtest:Underidentification test} (Kleibergen-Paap rk LM statistic):{res}{col 71}   7.487
{txt}{col 52}Chi-sq({res}1{txt}) P-val =  {res}{col 73}0.0062
{txt}{hline 78}
{help ivreg2##widtest:Weak identification test} (Cragg-Donald Wald F statistic):{res}{col 71}  10.470
{txt}                         (Kleibergen-Paap rk Wald F statistic):{res}{col 71}  15.057
{txt}Stock-Yogo weak ID test critical values:{res}{txt}{col 42}10% maximal IV size{res}{col 73} 16.38
{txt}{col 42}15% maximal IV size{res}{col 73}  8.96
{txt}{col 42}20% maximal IV size{res}{col 73}  6.66
{txt}{col 42}25% maximal IV size{res}{col 73}  5.53
{txt}Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.
{hline 78}
{help ivreg2##overidtests:Hansen J statistic} (overidentification test of all instruments):{res}{col 71}   0.000
{txt}{col 50}(equation exactly identified)
{hline 78}
Instrumented:{col 23}perc_i_full
Included instruments:{col 23}perc_b_1903_1912 perc_b_1913_1922 perc_b_1923_1932
{col 23}rdd_lat rdd_lon rdd_lat_2 rdd_lon_2 rdd_lat_lon
Excluded instruments:{col 23}perc_e_1908_1927
{help ivreg2##partial:Partialled-out}:{col 23}perc_prot_church pop_jew p_french_name lpop_1936
{col 23}perc_fore_1936 perc_dial_1936 perc_disp_1946 water
{col 23}lelevation_mean lelevation_std ldist_de perc_droi_1936_ins
{col 23}lpop_counter perc_fore perc_b_1928_1945 perc_b_1946_1964
{col 23}perc_b_1965_1980 perc_b_1981_1996 perc_male_counter
{col 23}perc_bacplus perc_bluecollar perc_chom lrev_median lrev_sd
{col 23}_cons
{col 23}nb: total SS, model F and R2s are after partialling-out;
{col 23}    any {help ivreg2##s_small:small-sample adjustments} include partialled-out
{col 23}    variables in regressor count K
{hline 78}
{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}  borderfe25{col 14}{c |}{space 1}        8{col 27}{space 1}        0{col 39}{result}{space 1}        8{col 53}{text} {col 54}{c |}
{res}{col 1}{text} dialect_lux{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text} {col 54}{c |}
{res}{col 1}{text} dialect_mos{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_rhe{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_pal{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_als{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_hau{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_lor{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_fra{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text}?{col 54}{c |}
{res}{col 1}{text}     pop_jew{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text}       water{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{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
{res}
{txt}added scalar:
               e(F_fs) =  {res}15.057351

{txt}added scalar:
             e(mean_y) =  {res}19.403315
{txt}(warning: absorbing 11 dimensions of fixed effects; check that you really want that)
{res}{txt}note: {res}variable #13{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}note: {res}variable #19{txt} is probably collinear with the fixed effects (all partialled-out values are close to zero; tol = 1.0e-09)
{txt}({browse "http://scorreia.com/research/hdfe.pdf":MWFE estimator} converged in 8 iterations)
{res}
{txt}IV (2SLS) estimation
{hline 20}

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity and clustering on ct_1936_enc

Number of clusters (ct_1936_enc) = {col 33}{res}    32{txt}{col 55}Number of obs = {res}     461
{txt}{col 55}F(  9,    31) = {res}    1.88
{txt}{col 55}Prob > F      = {res}  0.0936
{txt}Total (centered) SS     = {res} 6125.307571{txt}{col 55}Centered R2   = {res} -0.1232
{txt}Total (uncentered) SS   = {res} 6125.307571{txt}{col 55}Uncentered R2 = {res} -0.1232
{txt}Residual SS             = {res} 6880.087365{txt}{col 55}Root MSE      = {res}   4.077

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}    perc_bna_ins{col 18}{c |} Coefficient{col 30}  std. err.{col 42}      t{col 50}   P>|t|{col 58}     [95% con{col 71}f. interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}perc_i_full {c |}{col 18}{res}{space 2} .3691224{col 30}{space 2} .2637931{col 41}{space 1}    1.40{col 50}{space 3}0.172{col 58}{space 4}-.1688872{col 71}{space 3}  .907132
{txt}perc_b_1903_1912 {c |}{col 18}{res}{space 2}-.1189215{col 30}{space 2} .0648172{col 41}{space 1}   -1.83{col 50}{space 3}0.076{col 58}{space 4}-.2511171{col 71}{space 3}  .013274
{txt}perc_b_1913_1922 {c |}{col 18}{res}{space 2} .0551218{col 30}{space 2} .1042705{col 41}{space 1}    0.53{col 50}{space 3}0.601{col 58}{space 4}-.1575392{col 71}{space 3} .2677829
{txt}perc_b_1923_1932 {c |}{col 18}{res}{space 2}-.1383141{col 30}{space 2} .1236946{col 41}{space 1}   -1.12{col 50}{space 3}0.272{col 58}{space 4}-.3905909{col 71}{space 3} .1139626
{txt}{space 9}rdd_lat {c |}{col 18}{res}{space 2}-1579.464{col 30}{space 2}  1684.74{col 41}{space 1}   -0.94{col 50}{space 3}0.356{col 58}{space 4}-5015.513{col 71}{space 3} 1856.585
{txt}{space 9}rdd_lon {c |}{col 18}{res}{space 2}-1021.645{col 30}{space 2} 644.5566{col 41}{space 1}   -1.59{col 50}{space 3}0.123{col 58}{space 4}-2336.227{col 71}{space 3} 292.9369
{txt}{space 7}rdd_lat_2 {c |}{col 18}{res}{space 2} 14.83066{col 30}{space 2} 17.13927{col 41}{space 1}    0.87{col 50}{space 3}0.394{col 58}{space 4}-20.12511{col 71}{space 3} 49.78644
{txt}{space 7}rdd_lon_2 {c |}{col 18}{res}{space 2} 7.402964{col 30}{space 2} 4.242421{col 41}{space 1}    1.74{col 50}{space 3}0.091{col 58}{space 4}-1.249512{col 71}{space 3} 16.05544
{txt}{space 5}rdd_lat_lon {c |}{col 18}{res}{space 2} 18.52318{col 30}{space 2} 12.70162{col 41}{space 1}    1.46{col 50}{space 3}0.155{col 58}{space 4}-7.381951{col 71}{space 3} 44.42831
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{help ivreg2##idtest:Underidentification test} (Kleibergen-Paap rk LM statistic):{res}{col 71}   7.189
{txt}{col 52}Chi-sq({res}1{txt}) P-val =  {res}{col 73}0.0073
{txt}{hline 78}
{help ivreg2##widtest:Weak identification test} (Cragg-Donald Wald F statistic):{res}{col 71}  10.236
{txt}                         (Kleibergen-Paap rk Wald F statistic):{res}{col 71}  15.369
{txt}Stock-Yogo weak ID test critical values:{res}{txt}{col 42}10% maximal IV size{res}{col 73} 16.38
{txt}{col 42}15% maximal IV size{res}{col 73}  8.96
{txt}{col 42}20% maximal IV size{res}{col 73}  6.66
{txt}{col 42}25% maximal IV size{res}{col 73}  5.53
{txt}Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.
{hline 78}
{help ivreg2##overidtests:Hansen J statistic} (overidentification test of all instruments):{res}{col 71}   0.000
{txt}{col 50}(equation exactly identified)
{hline 78}
Instrumented:{col 23}perc_i_full
Included instruments:{col 23}perc_b_1903_1912 perc_b_1913_1922 perc_b_1923_1932
{col 23}rdd_lat rdd_lon rdd_lat_2 rdd_lon_2 rdd_lat_lon
Excluded instruments:{col 23}perc_e_1908_1927
{help ivreg2##partial:Partialled-out}:{col 23}perc_prot_church pop_jew p_french_name lpop_1936
{col 23}perc_fore_1936 perc_dial_1936 perc_disp_1946 water
{col 23}lelevation_mean lelevation_std ldist_de perc_droi_1936_ins
{col 23}lpop_counter perc_fore perc_b_1928_1945 perc_b_1946_1964
{col 23}perc_b_1965_1980 perc_b_1981_1996 perc_male_counter
{col 23}perc_bacplus perc_bluecollar perc_chom lrev_median lrev_sd
{col 23}_cons
{col 23}nb: total SS, model F and R2s are after partialling-out;
{col 23}    any {help ivreg2##s_small:small-sample adjustments} include partialled-out
{col 23}    variables in regressor count K
{hline 78}
{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}  borderfe25{col 14}{c |}{space 1}        8{col 27}{space 1}        0{col 39}{result}{space 1}        8{col 53}{text} {col 54}{c |}
{res}{col 1}{text} dialect_lux{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text} {col 54}{c |}
{res}{col 1}{text} dialect_mos{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_rhe{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_pal{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_als{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_hau{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_lor{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text} dialect_fra{col 14}{c |}{space 1}        1{col 27}{space 1}        1{col 39}{result}{space 1}        0{col 53}{text}?{col 54}{c |}
{res}{col 1}{text}     pop_jew{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{col 53}{text}?{col 54}{c |}
{res}{col 1}{text}       water{col 14}{c |}{space 1}        2{col 27}{space 1}        1{col 39}{result}{space 1}        1{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
{res}
{txt}added scalar:
               e(F_fs) =  {res}15.369007

{txt}added scalar:
             e(mean_y) =  {res}20.641729
{txt}
{com}. 
. estfe . P*, labels(dialect_lux "Historical dialects")
{res}{txt}
{com}. return list

{txt}macros:
        r(indicate_fe) : "{res} "Historical dialects=0.dialect_lux"  "borderfe25=0.borderfe25" "dialect_mos=0.dialect_mos" "dialect_rhe=0.dialect_rhe" "diale{txt}.."

{com}. 
. ******************************
. ***** 2. TABLE FOR PAPER *****
. ******************************
. 
. // Labels
. 
. la var perc_e_1908_1927         "\\ Eligible births (\%)"
{txt}
{com}. la var perc_i_full                      "\\ Conscription proxy (\%)"
{txt}
{com}. 
. // First-Stage
. 
. estout P1965T1_FS P1969T1_FS P1974T1_FS P1995T1_FS P2002T1_FS P2007T1_FS P2012T1_FS P2017T1_FS ///
>         using "$results\\$program.tex", replace style(tex) type label ///
>         cells(b(star fmt(%9.3f)) se(par fmt(%9.3f)))  ///
>         stats(mean_y, lab("\\ Mean dep. variable") fmt(2)) ///
>         collabels(none) ///
>         mlabels(, span none prefix(\multicolumn{c -(}@span{c )-}{c -(}c{c )-}{c -(}) suffix({c )-})) ///
>         msign(--) starlevels(* .1 ** .05 *** .01) ///
>         keep(perc_e_1908_1927) ///
>         order(perc_e_1908_1927) ///
>         title(Abstention and the radical right-wing vote: Excluding casualties) ///
>         prehead( ///
>         "\begin{c -(}table{c )-}[t!]" ///
>         "\begin{c -(}center{c )-}" ///
>         "\begin{c -(}threeparttable{c )-}" ///
>         "\begin{c -(}scriptsize{c )-}" ///
>         "\caption{c -(}@title\label{c -(}$program{c )-}{c )-}" ///
>         "\begin{c -(}tabular*{c )-}{c -(}\columnwidth{c )-}{c -(}@{c -(}\extracolsep{c -(}\stretch{c -(}1{c )-}{c )-}{c )-}l*{c -(}@M{c )-}{c -(}c{c )-}@{c -(}{c )-}{c )-}" ///
>         "\hline" "\hline" ///
>         "&\multicolumn{c -(}1{c )-}{c -(}c{c )-}{c -(}(1){c )-} &\multicolumn{c -(}1{c )-}{c -(}c{c )-}{c -(}(2){c )-}  &\multicolumn{c -(}1{c )-}{c -(}c{c )-}{c -(}(3){c )-} &\multicolumn{c -(}1{c )-}{c -(}c{c )-}{c -(}(4){c )-} &\multicolumn{c -(}1{c )-}{c -(}c{c )-}{c -(}(5){c )-}  &\multicolumn{c -(}1{c )-}{c -(}c{c )-}{c -(}(6){c )-}  &\multicolumn{c -(}1{c )-}{c -(}c{c )-}{c -(}(7){c )-} &\multicolumn{c -(}1{c )-}{c -(}c{c )-}{c -(}(8){c )-}\\" ///   
>         "       &\multicolumn{c -(}3{c )-}{c -(}c{c )-}{c -(}Earlier elections{c )-} &\multicolumn{c -(}5{c )-}{c -(}c{c )-}{c -(}Later elections{c )-}\\" ///
>         "\cmidrule(lr){c -(}2-4{c )-} \cmidrule(lr){c -(}5-9{c )-}" ///
>         "\multicolumn{c -(}1{c )-}{c -(}l{c )-}{c -(}\textit{c -(}Election year{c )-}{c )-}&\multicolumn{c -(}1{c )-}{c -(}c{c )-}{c -(}1965{c )-} &\multicolumn{c -(}1{c )-}{c -(}c{c )-}{c -(}1969{c )-} &\multicolumn{c -(}1{c )-}{c -(}c{c )-}{c -(}1974{c )-} &\multicolumn{c -(}1{c )-}{c -(}c{c )-}{c -(}1995{c )-}  &\multicolumn{c -(}1{c )-}{c -(}c{c )-}{c -(}2002{c )-} &\multicolumn{c -(}1{c )-}{c -(}c{c )-}{c -(}2007{c )-} &\multicolumn{c -(}1{c )-}{c -(}c{c )-}{c -(}2012{c )-} &\multicolumn{c -(}1{c )-}{c -(}c{c )-}{c -(}2017{c )-}\\" ///
>         "%\hline" ///
>         "\cmidrule(lr){c -(}2-9{c )-}" ///
>         "& \multicolumn{c -(}8{c )-}{c -(}c{c )-}{c -(}Panel A: First-Stage Estimates. Dep. Variable: Conscription proxy (\%){c )-}\\") ///
>         posthead("\hline") ///
>         prefoot("") ///
>         postfoot("\\")
{res}
\begin{c -(}table{c )-}[t!]
\begin{c -(}center{c )-}
\begin{c -(}threeparttable{c )-}
\begin{c -(}scriptsize{c )-}
\caption{c -(}Abstention and the radical right-wing vote: Excluding casualties\label{c -(}EEREV-D-21-00004_TableC6{c )-}{c )-}
\begin{c -(}tabular*{c )-}{c -(}\columnwidth{c )-}{c -(}@{c -(}\extracolsep{c -(}\stretch{c -(}1{c )-}{c )-}{c )-}l*{c -(}8{c )-}{c -(}c{c )-}@{c -(}{c )-}{c )-}
\hline
\hline
&\multicolumn{c -(}1{c )-}{c -(}c{c )-}{c -(}(1){c )-} &\multicolumn{c -(}1{c )-}{c -(}c{c )-}{c -(}(2){c )-}  &\multicolumn{c -(}1{c )-}{c -(}c{c )-}{c -(}(3){c )-} &\multicolumn{c -(}1{c )-}{c -(}c{c )-}{c -(}(4){c )-} &\multicolumn{c -(}1{c )-}{c -(}c{c )-}{c -(}(5){c )-}  &\multicolumn{c -(}1{c )-}{c -(}c{c )-}{c -(}(6){c )-}  &\multicolumn{c -(}1{c )-}{c -(}c{c )-}{c -(}(7){c )-} &\multicolumn{c -(}1{c )-}{c -(}c{c )-}{c -(}(8){c )-}\\
       &\multicolumn{c -(}3{c )-}{c -(}c{c )-}{c -(}Earlier elections{c )-} &\multicolumn{c -(}5{c )-}{c -(}c{c )-}{c -(}Later elections{c )-}\\
\cmidrule(lr){c -(}2-4{c )-} \cmidrule(lr){c -(}5-9{c )-}
\multicolumn{c -(}1{c )-}{c -(}l{c )-}{c -(}\textit{c -(}Election year{c )-}{c )-}&\multicolumn{c -(}1{c )-}{c -(}c{c )-}{c -(}1965{c )-} &\multicolumn{c -(}1{c )-}{c -(}c{c )-}{c -(}1969{c )-} &\multicolumn{c -(}1{c )-}{c -(}c{c )-}{c -(}1974{c )-} &\multicolumn{c -(}1{c )-}{c -(}c{c )-}{c -(}1995{c )-}  &\multicolumn{c -(}1{c )-}{c -(}c{c )-}{c -(}2002{c )-} &\multicolumn{c -(}1{c )-}{c -(}c{c )-}{c -(}2007{c )-} &\multicolumn{c -(}1{c )-}{c -(}c{c )-}{c -(}2012{c )-} &\multicolumn{c -(}1{c )-}{c -(}c{c )-}{c -(}2017{c )-}\\
%\hline
\cmidrule(lr){c -(}2-9{c )-}
& \multicolumn{c -(}8{c )-}{c -(}c{c )-}{c -(}Panel A: First-Stage Estimates. Dep. Variable: Conscription proxy (\%){c )-}\\
\hline
\\ Eligible births (\%)&       0.207***&       0.218***&       0.219***&       0.213***&       0.200***&       0.215***&       0.217***&       0.214***\\
                    &     (0.053)   &     (0.054)   &     (0.053)   &     (0.051)   &     (0.051)   &     (0.047)   &     (0.056)   &     (0.054)   \\

\\ Mean dep. variable&        7.55   &        7.55   &        7.55   &        7.55   &        7.55   &        7.55   &        7.55   &        7.55   \\
\\
{txt}(output written to {browse  `"D:\Dropbox\SVLACHOS\Research\Malgre_nous\Replication_files\Results\EEREV-D-21-00004_TableC6.tex"'})

{com}. 
. // Radical-Right
. 
. estout P1965T1_VOTE P1969T1_VOTE P1974T1_VOTE P1995T1_VOTE P2002T1_VOTE P2007T1_VOTE P2012T1_VOTE P2017T1_VOTE ///
>         using "$results\\$program.tex", append style(tex) type label ///
>         cells(b(star fmt(%9.3f)) se(par fmt(%9.3f)))  ///
>         stats(mean_y, lab("\\ Mean dep. variable") fmt(2)) ///
>         collabels(none) ///
>         mlabels(, span none prefix(\multicolumn{c -(}@span{c )-}{c -(}c{c )-}{c -(}) suffix({c )-})) ///
>         msign(--) starlevels(* .1 ** .05 *** .01) ///
>         keep(perc_i_full) ///
>         order(perc_i_full) ///
>         prehead("%\hline" ///
>         "\cmidrule(lr){c -(}2-9{c )-}" ///
>         "& \multicolumn{c -(}8{c )-}{c -(}c{c )-}{c -(}Panel B: 2SLS Estimates. Dep. Variable: Radical right-wing vote (\% of registered){c )-}\\") ///
>         posthead("\hline") ///
>         prefoot("") ///
>         postfoot("\\")
{res}
%\hline
\cmidrule(lr){c -(}2-9{c )-}
& \multicolumn{c -(}8{c )-}{c -(}c{c )-}{c -(}Panel B: 2SLS Estimates. Dep. Variable: Radical right-wing vote (\% of registered){c )-}\\
\hline
\\ Conscription proxy (\%)&     --0.083   &               &       0.014   &       1.259***&       0.862** &       0.017   &       0.234   &       0.081   \\
                    &     (0.148)   &               &     (0.021)   &     (0.445)   &     (0.376)   &     (0.235)   &     (0.331)   &     (0.403)   \\

\\ Mean dep. variable&        1.20   &        0.00   &        0.31   &       22.18   &       22.24   &       14.87   &       23.23   &       27.26   \\
\\
{txt}(output written to {browse  `"D:\Dropbox\SVLACHOS\Research\Malgre_nous\Replication_files\Results\EEREV-D-21-00004_TableC6.tex"'})

{com}. 
. // Abstention
. 
. estout P1965T1_ABST P1969T1_ABST P1974T1_ABST P1995T1_ABST P2002T1_ABST P2007T1_ABST P2012T1_ABST P2017T1_ABST ///
>         using "$results\\$program.tex", append style(tex) type label ///
>         cells(b(star fmt(%9.3f)) se(par fmt(%9.3f)))  ///
>         stats(mean_y, lab("\\ Mean dep. variable") fmt(2)) ///
>         collabels(none) ///
>         mlabels(, span none prefix(\multicolumn{c -(}@span{c )-}{c -(}c{c )-}{c -(}) suffix({c )-})) ///
>         msign(--) starlevels(* .1 ** .05 *** .01) ///
>         keep(perc_i_full) ///
>         order(perc_i_full) ///
>         prehead("%\hline" ///
>         "\cmidrule(lr){c -(}2-9{c )-}" ///
>         "& \multicolumn{c -(}8{c )-}{c -(}c{c )-}{c -(}Panel C: 2SLS Estimates. Dep. Variable: Abstention (\% of registered){c )-}\\") /// 
>         posthead("\hline") ///
>         prefoot("") ///
>         postfoot("")
{res}
%\hline
\cmidrule(lr){c -(}2-9{c )-}
& \multicolumn{c -(}8{c )-}{c -(}c{c )-}{c -(}Panel C: 2SLS Estimates. Dep. Variable: Abstention (\% of registered){c )-}\\
\hline
\\ Conscription proxy (\%)&       1.144** &       1.645** &       0.881** &     --0.202   &     --0.916** &       0.465*  &       0.184   &       0.369   \\
                    &     (0.495)   &     (0.752)   &     (0.386)   &     (0.243)   &     (0.361)   &     (0.228)   &     (0.301)   &     (0.264)   \\

\\ Mean dep. variable&       15.25   &       23.58   &       17.04   &       19.77   &       28.38   &       16.72   &       19.40   &       20.64   \\

{txt}(output written to {browse  `"D:\Dropbox\SVLACHOS\Research\Malgre_nous\Replication_files\Results\EEREV-D-21-00004_TableC6.tex"'})

{com}. 
. // Closure
. 
. estout P1965T1_ABST P1969T1_ABST P1974T1_ABST P1995T1_ABST P2002T1_ABST P2007T1_ABST P2012T1_ABST P2017T1_ABST ///
>         using "$results\\$program.tex", append style(tex) type label ///
>         cells(b(star fmt(%9.3f)) se(par fmt(%9.3f)))  ///
>         stats(F_fs N N_clust, lab("First-stage $ F $-statistic" "Observations" "Clusters") fmt(2 0 0)) ///
>         collabels(none) ///
>         mlabels(, span none prefix(\multicolumn{c -(}@span{c )-}{c -(}c{c )-}{c -(}) suffix({c )-})) ///
>         msign(--) starlevels(* .1 ** .05 *** .01) ///
>         drop(*) ///     
>         indicate( ///   
>         "Border segment FE = 0.borderfe25" ///
>         "Historical dialect FE = 0.dialect_lux" ///
>         "Full set of controls = perc_b_1903_1912" ///   "Historical dialects = 0.dialect_lux" ///
>         , labels(Yes )) ///
>         prehead("\\ Lat-lon polynomial & 2nd & 2nd & 2nd & 2nd & 2nd & 2nd & 2nd & 2nd \\ ") ///
>         posthead("") ///
>         prefoot("\hline") ///
>         postfoot("\hline" "\hline" ///
>         "\end{c -(}tabular*{c )-}" /// 
>         "\end{c -(}scriptsize{c )-}" ///
>         "\begin{c -(}tablenotes{c )-}[normal,flushleft]" ///
>         "\begin{c -(}scriptsize{c )-}" ///
>         "\item \emph{c -(}Notes{c )-}:" /// 
>         "2SLS estimates of the effect of conscription into the Wehrmacht net of 1908-1913 casualties on support for radical right-wing candidates and on abstention. " ///
>         "The unit of observation is a municipality. " ///
>         "Standard errors clustered at the canton level in parentheses. " ///
>         "Panel A: 2SLS estimates with radical right-wing vote as the outcome; " ///
>         "Panel B: 2SLS estimates abstention as the outcome. " ///
>         "Each column presents the estimation for a different election. " ///
>         "All specifications include a quadratic polynomial in latitude and longitude ($ x+y+x^2+y^2+xy $). " ///
>         "First-stage F-statistic is the Kleibergen-Paap rk Wald F-statistic of the first-stage estimation. " ///
>         "* significant at 10\%; ** at 5\%; *** at 1\%. " ///    
>         "\end{c -(}scriptsize{c )-}" ///
>         "\end{c -(}tablenotes{c )-}" ///
>         "\end{c -(}threeparttable{c )-}" ///
>         "\end{c -(}center{c )-}" ///
>         "\end{c -(}table{c )-}")
{res}
\\ Lat-lon polynomial & 2nd & 2nd & 2nd & 2nd & 2nd & 2nd & 2nd & 2nd \\ 

Border segment FE   &         Yes   &         Yes   &         Yes   &         Yes   &         Yes   &         Yes   &         Yes   &         Yes   \\
Historical dialect FE &         Yes   &         Yes   &         Yes   &         Yes   &         Yes   &         Yes   &         Yes   &         Yes   \\
Full set of controls &         Yes   &         Yes   &         Yes   &         Yes   &         Yes   &         Yes   &         Yes   &         Yes   \\
\hline
First-stage $ F $-statistic&       15.02   &       16.15   &       16.99   &       17.58   &       15.54   &       21.24   &       15.06   &       15.37   \\
Observations        &         461   &         461   &         461   &         461   &         461   &         461   &         461   &         461   \\
Clusters            &          32   &          32   &          32   &          32   &          32   &          32   &          32   &          32   \\
\hline
\hline
\end{c -(}tabular*{c )-}
\end{c -(}scriptsize{c )-}
\begin{c -(}tablenotes{c )-}[normal,flushleft]
\begin{c -(}scriptsize{c )-}
\item \emph{c -(}Notes{c )-}:
2SLS estimates of the effect of conscription into the Wehrmacht net of 1908-1913 casualties on support for radical right-wing candidates and on abstention. 
The unit of observation is a municipality. 
Standard errors clustered at the canton level in parentheses. 
Panel A: 2SLS estimates with radical right-wing vote as the outcome; 
Panel B: 2SLS estimates abstention as the outcome. 
Each column presents the estimation for a different election. 
All specifications include a quadratic polynomial in latitude and longitude ($ x+y+x^2+y^2+xy $). 
First-stage F-statistic is the Kleibergen-Paap rk Wald F-statistic of the first-stage estimation. 
* significant at 10\%; ** at 5\%; *** at 1\%. 
\end{c -(}scriptsize{c )-}
\end{c -(}tablenotes{c )-}
\end{c -(}threeparttable{c )-}
\end{c -(}center{c )-}
\end{c -(}table{c )-}
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