Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
This article uses household survey data to estimate the determinants of earnings in Indonesia, a country where nonsalaried work is widespread and earnings data are available for salaried employees only. We deal with the selection bias by estimating a Full-Information Maximum Likelihood (FIML) system of equations, where selection into the labour market is modelled in a multinomial setting. We find that some estimated parameters of the earnings equation differ from a binomial selection procedure by Heckman (1979), in particular for those variables with the strongest impact on the selection into the different labour-market statuses. However, the estimated returns to education are unaffected, even when we deal with the endogeneity of educational attainment following Duflo (2001). Overall, our findings show that the choice of the selection rule affects the estimates of the earnings determinants in the Indonesian labour market.