برنامه ریزی تقریبی پویا با حالت های پس از تصمیم به عنوان یک روش راه حل برای مدل های اقتصادی پویا

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 and Bertsekas, 2011), but also had an early application in economics (Wright and Williams, 1982 and Wright and Williams, 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.