This papers contains a survey of the recent literature devoted to returns to schooling within a dynamic structural framework. I present a historical perspective on the evolution of the literature, from early static models set in a selectivity framework [Willis, T., Rosen, S., 1979. Education and selfselection. Journal of Political Economy 87, S7-S36] to the recent literature, stimulated by [Keane, M.P., Wolpin, K., 1997. The career decisions of young men. Journal of Political Economy 105(3) 473-522], and which uses stochastic dynamic programming techniques. After reviewing the literature thoroughly, I compare the structural approach with the IV (experimental) approach. I present their commonalities and I also discuss their fundamental differences. To get an order of magnitude, most structural estimates reported for the US range between 4% and 7% per year. On the other hand, IV estimates between 10% and 15% per year are often reported. The discrepancy prevails even when comparable (if not identical) data sets are used. The discussion is focussed on understanding this divergence. The distinction between static and dynamic model specifications is a recurrent theme in the analysis. I show that structural and IV approaches differ mainly at the level of (i) the compatibility of the underlying models with dynamic behavior, (ii) the role of behavioral and statistical assumptions, (iii) the role of heterogeneity in ability and tastes, (iv) the consideration of post-schooling opportunities, and (v) the specification (and interpretation) of the Mincer wage equation. (c) 2007 Elsevier B.V. All rights reserved.
