Approximate dynamic programming with post-decision states as a solution method for dynamic economic models

Isaiah Hull

Journal of Economic Dynamics and Control, 2015, vol. 55, issue C, 57-70

Abstract: I introduce and evaluate a new stochastic simulation method for dynamic economic models. It is based on recent work in the operations research and engineering literatures (Van Roy et al., 1997; Powell, 2007; Bertsekas, 2011), but also had an early application in economics (Wright and Williams, 1982, 1984). The baseline method involves rewriting the household׳s dynamic program in terms of post-decision states. This makes it possible to choose controls optimally without computing an expectation. I add a subroutine to the original algorithm that updates the values of states not visited frequently on the simulation path; and adopt a stochastic stepsize that efficiently weights information. Finally, I modify the algorithm to exploit GPU computing.

Keywords: Numerical solutions; Approximations; Heterogeneous agents; Nonlinear numerical solutions; Dynamic programming (search for similar items in EconPapers)
JEL-codes: C60 C61 C63 D52 (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (3)

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Working Paper: Approximate dynamic programming with postdecision states as a solution method for dynamic economic models (2013)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:dyncon:v:55:y:2015:i:c:p:57-70

DOI: 10.1016/j.jedc.2015.03.008

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