Info

(photo credit to Nigel Jones)
Ph.D. Candidate in Economics
University of California-Berkeley
530 Evans Hall #3880, Berkeley, CA 94720, USA

Email: raffaele.saggio@econ.berkeley.edu


Working Papers


By restricting the support of the unobserved heterogeneity and allowing cross-sectional units to be classified into a finite number of classes, we provide a non-linear panel data estimator that leaves the relationship between unobservables and observables unrestricted and it is able to use the whole sample in estimating the effects of interest. The latter represents an important improvement over typical maximum likelihood fixed effects models where the parameters are identified only through the sample of movers. Using results from Hahn and Moon (2010), we show that this non-linear group fixed effects estimator is consistent as both N and T goes to infinity under correct specification.  It is also higher-order unbiased compared to standard non-linear panel data estimators. We apply this new estimator to different empirical applications. The results suggest that the non-linear group fixed effects estimator can be considered as a reliable solution to deal with the problem of unobserved heterogeneity in a flexible but yet parsimonious way.    

Time to completion and labour market outcomes: Does the early bird really get the worm?

(joint with Davide Malacrino) 

This paper investigates how time to college completion affects subsequent labor market outcomes. We use a recent reform in which the Italian government consolidated the teaching offer in all universities in an attempt to decrease time to graduation. The reform was successful in reducing the proportion of students graduating late from a second level degree, but worsened a variety of post-graduation outcomes including earnings. Using this policy change as an instrumental variable, we find that late graduation is associated with better after graduation labor market outcomes. To disentangle the human capital effect of late graduation from working experience accumulated while still in college, we use a student choice model combined with revealed preferences restrictions. We believe that our findings have implications for the current policy debate as national governments are increasingly investing in public programs explicitly aimed at reducing time to graduation.