*******Verdienststrukturerhebung 2010********* ********************************************** ********************************************** ************ Syntax X: Plots *************** ********************************************** clear clear matrix set more off, perm set scrollbufsize 50000 set matsize 11000, perm numlabel _all, add cap log close log using "$log/plots", text replace set rmsg on use "${orig}\vse_work.dta", clear cd "$tex" ****Full sample preserve pctile eval1=ln_wage if female==1, nq(100) pctile eval2=ln_wage if female==0, nq(100) *Dichtefunktion für Männer mit gaussian Kernel kdensity ln_wage if female==0, at(eval2) gen(evalm densm) width(0.10) kernel(gau) kdensity ln_wage if female==1, at(eval1) gen(evalf densf) width(0.10) kernel(gau) *Lohnunterschiede grafisch š¢„² die Verteilung, OLS-Unterschied als Linie definieren gen qtau=_n/100 if _n<100 gen qdiff=evalm-evalf if _n<100 reg ln_wage female //obtain mean gap and CIs graph twoway (line qdiff qtau if qtau>0.0 & qtau<1.0, connect(l) /// m(i) lw(medium) lc(black) ) , yline(.215, lpattern(dash) lcolor(grey)) /// xlabel(0.0 0.2 0.4 0.6 0.8 1.0) ylabel(0.0 0.1 0.2 0.3 0.4 0.5) /// xtitle("Quantile") ytitle("Log Wage Differential") graphr(fcolor(white) lc(white)) title("Germany") scheme(sj) graph save gap_full.gph, replace *yline(.217 .213, lpattern(dash) lcolor(grey) ) restore ****East preserve keep if ost==1 pctile eval1=ln_wage if female==1, nq(100) pctile eval2=ln_wage if female==0, nq(100) *Dichtefunktion für Männer mit gaussian Kernel kdensity ln_wage if female==0, at(eval2) gen(evalm densm) width(0.10) kernel(gau) kdensity ln_wage if female==1, at(eval1) gen(evalf densf) width(0.10) kernel(gau) *Lohnunterschiede grafisch š¢„² die Verteilung, OLS-Unterschied als Linie definieren gen qtau=_n/100 if _n<100 gen qdiff=evalm-evalf if _n<100 reg ln_wage female //obtain mean gap and CIs graph twoway (line qdiff qtau if qtau>0.0 & qtau<1.0, connect(l) /// m(i) lw(medium) lc(black) ) , yline(.107, lpattern(dash) lcolor(grey)) /// xlabel(0.0 0.2 0.4 0.6 0.8 1.0) ylabel(0.0 0.1 0.2 0.3 0.4 0.5) /// xtitle("Quantile") ytitle("Log Wage Differential") graphr(fcolor(white) lc(white)) title("East Germany") scheme(sj) graph save gap_east.gph, replace *yline(.109 .105, lpattern(dash) lcolor(grey) ) restore ****West preserve keep if ost==0 pctile eval1=ln_wage if female==1, nq(100) pctile eval2=ln_wage if female==0, nq(100) *Dichtefunktion für Männer mit gaussian Kernel kdensity ln_wage if female==0, at(eval2) gen(evalm densm) width(0.10) kernel(gau) kdensity ln_wage if female==1, at(eval1) gen(evalf densf) width(0.10) kernel(gau) *Lohnunterschiede grafisch š¢„² die Verteilung, OLS-Unterschied als Linie definieren gen qtau=_n/100 if _n<100 gen qdiff=evalm-evalf if _n<100 reg ln_wage female //obtain mean gap and CIs graph twoway (line qdiff qtau if qtau>0.0 & qtau<1.0, connect(l) /// m(i) lw(medium) lc(black) ) , yline(.230, lpattern(dash) lcolor(grey)) /// xlabel(0.0 0.2 0.4 0.6 0.8 1.0) ylabel(0.0 0.1 0.2 0.3 0.4 0.5) /// xtitle("Quantile") ytitle("Log Wage Differential") graphr(fcolor(white) lc(white)) title("West Germany") scheme(sj) graph save gap_west.gph, replace *yline(.228 .232, lpattern(dash) lcolor(grey) ) restore ****Public preserve keep if public==1 pctile eval1=ln_wage if female==1, nq(100) pctile eval2=ln_wage if female==0, nq(100) *Dichtefunktion für Männer mit gaussian Kernel kdensity ln_wage if female==0, at(eval2) gen(evalm densm) width(0.10) kernel(gau) kdensity ln_wage if female==1, at(eval1) gen(evalf densf) width(0.10) kernel(gau) *Lohnunterschiede grafisch š¢„² die Verteilung, OLS-Unterschied als Linie definieren gen qtau=_n/100 if _n<100 gen qdiff=evalm-evalf if _n<100 reg ln_wage female //obtain mean gap and CIs graph twoway (line qdiff qtau if qtau>0.0 & qtau<1.0, connect(l) /// m(i) lw(medium) lc(black) ) , yline(.156, lpattern(dash) lcolor(grey)) /// xlabel(0.0 0.2 0.4 0.6 0.8 1.0) ylabel(0.0 0.1 0.2 0.3 0.4 0.5) /// xtitle("Quantile") ytitle("Log Wage Differential") graphr(fcolor(white) lc(white)) title("Public sector") scheme(sj) graph save gap_public.gph, replace *yline(.152 .160, lpattern(dash) lcolor(grey) ) restore graph combine gap_full.gph gap_west.gph gap_east.gph gap_public.gph, c(2) xsize(6) ysize(5) /// graphr(fcolor(white) lc(white)) scheme(sj) note("Source: RDC of the Federal Statistical Office and Statistical Offices of the LƤnder, Verdienststrukturerhebung, 2010," "own calculations.", size(vsmall)) graph export gaps.eps, replace cap log close