version 14
use ESS1e06_4.dta, clear
// Age variable
replace agea = . if agea == 999
qui centile(agea), centile(99.9)
replace agea = r(c_1) if age > r(c_1) & !missing(agea)
rename agea age
// Happiness variable
recode happy (77 88 99 = .)
// Education variable
recode eduyrs (77 88 99 = .)
qui centile eduyrs, centile(99.9)
replace eduyrs = r(c_1) if eduyrs > r(c_1) & !missing(eduyrs)
// Fit model
regress happy c.eduyrs##c.age##c.age, robust
// Caculate education slope as function of age
qui margins, dydx(eduyrs) over(age)
marginsplot, recastci(rarea) recast(line) ciopts(color(gs12)) ///
ytitle("Effect of education on happiness") ylabel(, format(%6.2f)) ///
xtitle("Age") xlabel(20(10)90) xmtick(14(1)93) ///
title("") name(slope, replace) xsize(4) nodraw
// Predict happiness for different values of age and education
qui margins, at(eduyrs=(9 12 15) age=(14 20 (5) 90 93))
marginsplot, xdimension(age) recastci(rarea) recast(connected) ciopts(color(gs12)) ///
ytitle("Predicted happiness") ylabel(, format(%6.1f)) ///
xtitle("Age") xlabel(20(10)90) xmtick(14(1)93) ///
legend(order(6 "15 yrs" 5 "12 yrs." 4 "9 yrs.") ///
title(Education, size(*.8)) pos(11) ring(0)) ///
title("") name(prediction, replace) xsize(4) nodraw
// Plot
graph combine slope prediction, xsize(8) row(1) note("{it:Source:} European Social Survey, round 1 (2002/2003).")
