Approximate dynamic programming with postdecision states as a solution method for dynamic economic models - Isaiah Hull (Sveriges Riksbank, 2013)
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: C60; C61; C63; D52; 330; Numerical Solutions; Approximations; Heterogeneous Agents; Nonlinear Numerical Solutions; Dynamic Programming