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

Isaiah Hull
Research Division, Sveriges Riksbank, SE-103 37, Stockholm, Sweden
Sveriges Riksbank Working Paper Series, No. 276, 2013
@article{riksbank2013approximate,

   title={Approximate dynamic programming with post-decision states as a solution method for dynamic economic models},

   author={RIKSBANK, SVERIGES},

   year={2013}

}

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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.
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