1,720,973 research outputs found
Heterogeneous economic returns to higher education: evidence from Italy
No full textThis 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 −22 % (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
Il tasso di rendimento dell'istruzione: l'approccio growth mixed model
No full textLa stima empirica del ritorno dell’istruzione sul reddito si pone come uno strumento utile alla valutazione dell’efficienza esterna dell’istruzione superiore. Il presente lavoro introduce un nuovo approccio metodologico alla stima dei tassi di ritorno dell’istruzione sul reddito. Si propone un modello di crescita ad effetti casuali (growth mixed model) per stimare in un’ottica sia di tipo cross-section che longitudinale il tasso di ritorno dell’istruzione sul reddito. Tale approccio integra sia il problema di autoselezione dovuto alla selezione non-casuale del campione di percettori di reddito sia il bias dovuto all’endogeneità dell’istruzione, attraverso i noti metodi del "Propensity Score" e dell’approccio "Two-Stage" di Heckman. L’applicazione empirica del modello proposto è rivolta alla stima dei differenziali di reddito tra differenti livelli educazionali per i laureati di una Università milanese nel periodo 2003-2005, attraverso l’utilizzo di una base dati di natura amministrativa, ricavata dall’integrazione degli archivi universitari, da quelli provinciali/nazionali inerenti il mercato lavorativo lombardo e i redditi dichiarati.Tassi di ritorno, growth mixed model, efficienza esterna, archivi amministrativi
Le priorità per il Sistema Universitario Lombardo : evidence from a Delphi research survey
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EFFICIENCY AND SCIENTIFIC PRODUCTIVITY IN ITALIAN UNIVERSITIES
Full text linkEfficiency in Higher Education Systems is an issue of crucial importance these days considering the strong dependence of this sector on public funds. Indeed in the context of the current economic crisis the evaluation of efficiency of education provision is a primary target for governments from a social viewpoint.
In this context, this thesis seeks to fill a significant gap in the literature on the Italian higher education system, by looking at issues of efficiency and quality. The thesis consists of three essays. The first paper is strictly related to the estimation of the overall efficiency of Italian Universities during the last decade using appropriate recently introduced (Tsionas, 2002; Greene, 2005) econometric techniques. Efficiency is measured by taking into account the multidimensional nature of academic institutions which -by their nature- involved teaching, research and administrative activities as their primary dimensions. Going deeply into the issue of academics’ efficiency, we should note that the main human capital stock of inputs for both the teaching and research dimensions consists of the academic body.
Quality, competences and professionalism of professors are leading “determinants” of teaching and research of our universities. Therefore the selection mechanisms of academics and their recruitment rules gather a great importance in this context. To this purpose we notice that a decentralization of academic selection procedures was introduced in Italy in 1998 with the “Berlinguer reform” act.
Second and the third paper of this thesis focus especially on the evaluation of the quality of those individuals who succeeded in competitive examinations to become associate, and full professors, and on the incentives to produce international research associated with different recruitment mechanisms (national versus local)
%CEM: a SAS macro to perform coarsened exact matching
No full textIn this paper we introduce %CEM, a macro package allowing researchers to automatically perform coarsened exact matching (CEM) in SAS environment. CEM is a non-parametric matching method widely used by researchers to avoid the confounding influence of pre-treatment control variables to improve causal inference in quasi-experimental studies. %CEM introduces a completely automated process which allows SAS users to efficiently perform CEM in fields in which large data sets are common and where SAS is the most popular statistical tool. In addition, such a macro may be used to test several coarsening combinations of numeric variables. This option also provides a visual representation of thematching frontier, thus enabling researchers to select the optimal setting which takes into account both the (Formula presented.) imbalance and the percentage of matched units. The paper concludes with an empirical application comparing computational performance and results obtained using alternative available software (SAS, R and STATA) using multiple administrative data sets from a large regional database
Estimation of educational returns using university and labour market administrative archives
No full textThis 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 ‘years of schooling completed’ and the ‘highest qualification obtained’ 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
The gravity of quality : research quality and the attractiveness of universities in Italy
Full text linkThis paper investigates whether or not research quality is significantly associated with a university’s ability to attract students from other provinces in Italy. First-university enrolments of students over the period 2003–11 are regressed on universities’ research-quality indicators computed from various bibliometric databases using fixed-effects gravity models. The estimates suggest that research performance is a significant predictor of student enrolment, with estimated elasticities between 0.013 and 0.059, depending on the indicator used
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