Bayesian Treatment Effects Models with Variable Selection for Panel Outcomes with an Application to Earnings Effects of Maternity Leave
L Jacobi, H Wagner, S Fruehwirth-Schnatter
Journal of Econometrics | Elsevier | Published : 2016
We propose two alternative Bayesian treatment effect modeling and inferential frameworks for panel outcomes to estimate dynamic earnings effects of a long maternity leave on mothers’ subsequent earnings. Modeling of the endogeneity of the treatment and the panel structure of the earnings are based on the modeling tradition of the Roy switching regression model and the shared factor approach, respectively. We implement stochastic variable selection to test, for example, for the presence of different dynamics under the treatment. Exploiting a change in maternity leave policy and Austrian registry data we identify substantial negative but steadily decreasing earnings effects over a 5 years peri..View full abstract
Awarded by Austrian Science Fund (FWF)
Awarded by University of Melbourne
We thank the editor and three anonymous referees for very helpful comments. We are grateful to J.J. Heckman, Remi Piatek, Siddharta Chib and seminar participants at the University of Melbourne, Monash University, University of Innsbruck, University of Linz, as well as at the 2012 ISBA Meeting, the ESOBE 2012 meeting, the 5th Rimini Bayesian Workshop, the Melbourne Bayesian Econometrics Workshop 2013 and the IAAE 2014 Annual Conference for helpful comments and suggestions. We gratefully acknowledge funding from the Austrian Science Fund (FWF): S10309-G16 and University of Melbourne: FRG11FH10.