Research Abstracts Online
2008 - March 2009
University of Minnesota Twin Cities
College of Liberal Arts
Department of Economics
PI: Patrick L. Bajari
Estimation of Discrete Stochastic Dynamic Programming Models of Economic Behavior Using Monte Carlo Integration
The goal of this research is to develop new methods to solve and estimate discrete stochastic dynamic programming (DS-DP) models, and use these to study decision-making in areas such as human capital investment, occupational choice, investment in health, and others. In recent years it has become common in economics to model individuals who are making choices in dynamic environments as if they were solving a DS-DP problem to determine their optimal decisions. But empirical implementation of such models has been hampered because their solution and estimation requires that very high order numerical integrations be performed. This group investigated the use of simulation methods to circumvent these integration problems.
The research involves three projects. The first is a model of life cycle decisions of young women, with a focus on their human capital investment (i.e., school attendance and work), fertility and marriage decisions, and how these are affected by public welfare programs. The second project is a model of the childcare use and return-to-work decisions of working women after childbirth. The third is a model of the impact of education on marriage market opportunities for women.
Michael P. Keane, Department of Economics and Finance, University of Technology, Sydney, New South Wales, Australia