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

Arbeitspapier

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.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: Sveriges Riksbank Working Paper Series ; No. 276

Classification and Topics

• Classification: Wirtschaft ; Mathematical Methods; Programming Models; Mathematical and Simulation Modeling: General ; Optimization Techniques; Programming Models; Dynamic Analysis ; Computational Techniques; Simulation Modeling ; Incomplete Markets
• Subject: Numerical Solutions ; Approximations ; Heterogeneous Agents ; Nonlinear Numerical Solutions ; Dynamic Programming

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Hull, Isaiah
• Event: Veröffentlichung
• (who): Sveriges Riksbank
• (where): Stockholm
• (when): 2013

Further information

• Handle: http://hdl.handle.net/10419/103824
• Last update: 10.03.2025, 11:42 AM CET