Approximate dynamic programming with postdecision states as a solution method for dynamic economic models

Isaiah Hull

No 276, Working Paper Series from Sveriges Riksbank (Central Bank of Sweden)

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). 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)
Pages: 56 pages
Date: 2013-09-01
New Economics Papers: this item is included in nep-cmp, nep-dge and nep-ore
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Related works:
Journal Article: Approximate dynamic programming with post-decision states as a solution method for dynamic economic models (2015)
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Persistent link: https://EconPapers.repec.org/RePEc:hhs:rbnkwp:0276

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