// Open Allbus 2008
use V154 V151 V156 V760 V754 V755 V5 V767 using ZA4602_v1-0-0.dta, clear
// Age
generate age = V154 if V154 != 999
// Sex
generate female = (V151 == 2)
// Migrant
generate migrant = (V156 == 2)
// Interviewer ID
rename V760 id
// Interviewer sex
generate femaleinterviewer = (V754 == 2)
// Interviewer age
generate interviewerage = V755
// Attractiveness rating by interviewer before and after interview
qui factor V5 V767, pcf
predict attractiveness
// Calculate Spearman-Brown for two-item scales according
// to Eisinga et al. (https://doi.org/10.1007/s00038-012-0416-3):
spearman V5 V767
// Fit model with respondents clustered in interviewers
mixed attractiveness c.age##i.female i.migrant i.femaleinterviewer##c.interviewerage || id:
// Calculate margins and plot
qui margins, at(age = (18 (10) 98) female = (0 1))
marginsplot, recast(line) recastci(rarea) ciopt(color(gs14)) ///
plot1opts(lpattern(dash)) ///
legend(ring(0) pos(2)) ///
title("Female beauty premium disappears with age", span) ///
ytitle("Predicted attractiveness", axis(1)) ///
xtitle("Age") ///
xlabel(20 (10) 100) ///
addplot(histogram age, discrete yaxis(2) ///
lcolor(white) ///
ylabel(0 0.01 0.02, format(%6.2f) axis(2)) ///
yscale(alt range(0 0.1) axis(2)) ///
ytitle("Age density", axis(2)) ///
legend(order(3 "Men" 4 "Women"))) ///
note(" " "{it:Source:} German General Social Survey Allbus 2008, doi:10.4232/1.12345", span) ///
name(figure1, replace)
