Heterogeneous economic returns to higher education: evidence from Italy

This paper uses official Italian micro data and different methods to estimate, in the framework of potential outcomes, the marginal return to college education allowing for heterogeneous returns and for self-selection into higher education. Specifically, the paper is focused on the estimation of heterogeneity of average treatment effect (ATE) on a cohort of college and high school graduates using the 2008 survey on household, income and wealth of the Bank of Italy. Methodologically, this study was carried out by using both propensity-score-based (PS-based) methods and a new approach based on marginal treatment effects (MTE), recently proposed by Heckman and his associates as a useful strategy when the ignorability assumption may be violated. In the PS-based approach, heterogeneous treatment effects are estimated in three different manners: the traditional stratification approach (propensity score strata), the regression adjustment within propensity score strata and, finally, a non-parametric smoothing approach. In the MTE approach, the treatment effect heterogeneity across individuals is estimated in a parametric as well as a semi-parametric strategy. Our empirical analysis shows that the estimated heterogeneity is substantial: following MTE based results (quite representative of other methods) the return to college graduation for a randomly selected individual varies from as high as 20 % (for persons who would add one fifth of wage from graduating college) to as low as 1222 % (for persons who would lose from college graduation), suggesting that returns are higher for individuals more likely to attend college. Furthermore, the results of different methods show very low (point) estimates of ATE: average college returns vary from 3.5 % by the PS-smoothing method to 1.8 % by the parametric MTE method, which also leads a greater treatment effect on treated (5.5 %), a moderate, but significant sorting gain and a negligible selection bias

Estimation of educational returns using university and labour market administrative archives

This study estimates the rate of return to education for University of Milan (Italy) graduates who were active in the labour market during the period 2003-05, using official administrative data (University archives, Regional Labour market archive and Italian National Internal Revenue Service archive). The rate of return is measured in terms of differences in wage rates associated with differences in education. Both the \u2018years of schooling completed\u2019 and the \u2018highest qualification obtained\u2019 dimensions of education are considered. Methodologically, we propose a longitudinal extension of the Correlated Random Coefficient Model that, in contrast to alternative approaches for estimating educational returns, permits simultaneous evaluation of education effects on the earnings of graduates in both a cross-sectional (income differences between years or levels of education in 2005), and in a longitudinal framework (differences in income growth rates during the period 2003-05, between years or levels of education). Furthermore, the problem of self-selection (non-randomness of income earners), as well as education endogeneity bias, is taken into account. Empirical results, based on three institutional administrative archives, demonstrate that workers sort themselves into higher paying work experiences and income growth trajectories, while also providing strong evidence for a positive ability bias. Secondly, cross-section education returns confirm that graduates receive an income advantage in proportion to the educational level achieved, whereas longitudinal returns do not confirm this finding