Random graphs (90): Regression coefficients

version 14
use 7348_F1.dta, clear

// Prepare variables:
// Country variable
rename Y11_Country ctry
decode ctry, gen(country)
kountryadd "Macedonia (FYROM)" to "Macedonia" add
kountry country, from(other) stuck
rename _ISO3N_ geo
kountry geo, from(iso3n) to(iso2c)
rename _ISO2C_ cntry
replace cntry = "XK" if country == "Kosovo"
drop geo 

label define Y11_Country 30 "Macedonia", modify

// Wave identifier
rename Wave wave

// Gender
generate female = (Y11_HH2a == 2)

// Work-family conflict
*factor Y11_Q12a Y11_Q12b Y11_Q12c, pcf
*tab Y11_Q12a wave, mis
*tab Y11_Q12b wave, mis
*tab Y11_Q12c wave, mis
*alpha Y11_Q12a Y11_Q12b Y11_Q12c, item
scores wfb = mean(Y11_Q12a Y11_Q12b Y11_Q12c)
generate wfc = 5 - wfb
drop wfb

eststo clear

levelsof wave, local(wave)

foreach x of local wave {
eststo: mixed wfc female || ctry: female if wave == `x', cov(uns)

preserve
// Get no. of countries
matrix groups = e(N_g)
local n_g = groups[1,1]

// Predict residuals
predict u1 u0, reffects
predict u1se u0se, reses

// Calculate posterior slope
generate eb_female = u1 + _b[female]

// Plot posterior slope
egen pickone = tag(country)  // Keep one case per countr
keep if pickone
   
egen order_ = rank(-u1), unique
labmask order_, value(ctry) decode

gen high = u1 + _b[female] + (1.96 * u0se)
gen low  = u1 + _b[female] - (1.96 * u0se)
local avg =  _b[female]

twoway (rcap eb_female eb_female order_, horizontal) ///
       (rspike high low order_, horizontal) , ///
        xline(`avg') ylabel(1/`n_g', val ang(h)) ///
        ytitle("") ///
  xscale(alt) ///
        xlabel(-.2 (.1) .4) ///
        xtitle("Female WFC disadvantage") ///
        legend(off) ///
        title(`: label (wave) `x'') ///
        name(emp_bayes_`x', replace) xsize(3) nodraw
restore
}

graph combine emp_bayes_1 emp_bayes_2 emp_bayes_3, col(3) xsize(6) name(variation, replace) altshrink ///
      note("{it:Source:} European Quality of Life Surveys, 2003-11. {it:Notes:} Horizontal line shows average coefficient, country-specific" ///
        "estimates indicate deviation from this average. Error bars are 95% CI's based on random-effects models.")



coefplot est1, bylabel(EQLS 2003) || ///
         est2, bylabel(EQLS 2007) || ///
         est3, bylabel(EQLS 2011) || ///
       , xlabel(0 (.05) .2) drop(_cons) xscale(alt) baselevel coeflabel(female = "Female") ///
         xtitle("Female WFC disadvantage") xline(0) byopts(row(1)) ciopts(recast(rcap))



coefplot est1 est2 est3, xlabel(0 (.05) .2) drop(_cons) xscale(alt) baselevel coeflabel(female = "Female") ///
         xtitle("Female WFC disadvantage") xline(0) byopts(row(1)) ciopts(recast(rcap)) ///
  legend(order(2 "EQLS 2003" 4 "EQLS 2007" 6 "EQLS 2011"))