An approximate dynamic programming approach to solving dynamic oligopoly models
Name
Farias_An approximate dynamic.pdf
Size
382.07 KB
Format
Adobe PDF
Checksum (MD5)
6cd6dc84987050a175cd7e998469df57
Author(s)
Farias, Vivek F.
Saure, Denis
Weintraub, Gabriel Y.
Date Issued
June 2012
Journal
RAND Journal of Economics
Publisher
Wiley Blackwell
Citation
Farias, Vivek, Denis Saure, and Gabriel Y. Weintraub. “An Approximate Dynamic Programming Approach to Solving Dynamic Oligopoly Models.” The RAND Journal of Economics 43.2 (2012): 253–282.
Version
Author's final manuscript
Abstract
In this article, we introduce a new method to approximate Markov perfect equilibrium in large-scale Ericson and Pakes (1995)-style dynamic oligopoly models that are not amenable to exact solution due to the curse of dimensionality. The method is based on an algorithm that iterates an approximate best response operator using an approximate dynamic programming approach. The method, based on mathematical programming, approximates the value function with a linear combination of basis functions. We provide results that lend theoretical support to our approach. We introduce a rich yet tractable set of basis functions, and test our method on important classes of models. Our results suggest that the approach we propose significantly expands the set of dynamic oligopoly models that can be analyzed computationally.
MIT Department
Sloan School of Management
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike 3.0
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1111/j.1756-2171.2012.00165.x
