An approximate dynamic programming approach to solving dynamic oligopoly models

By Vivek F. Farias, Denis Sauré, Gabriel Y. Weintraub. 2012

621 citations recorded by the source corpus.

In this article, we introduce a new method to approximate Markov perfect equilibrium in largescale 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.

Subfields: Economics and Econometrics, Marketing

View Paper: https://www.semanticscholar.org/paper/9754cedaaec628919630c8b3a5312b650cdbb6ed

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In Economics and Econometrics

1. Stephen Ryan
2. M. Fowlie
3. Mar Reguant
4. Patrick Bajari
5. S. Houghton
6. S. Tadelis
7. O. Williamson
8. Matthew Gibson

In Marketing

1. S. Tadelis
2. S. Houghton
3. Mar Reguant
4. Stephen Ryan
5. Patrick Bajari
6. M. Fowlie
7. John Geweke
8. Hiroshi Ohashi

Citations in the corpus

• Bidding for Incomplete Contracts: An Empirical Analysis of Adaptation Costs (2014, methodology): “Our model is an independent private values setting that is similar to the multidimensional-type models of Che (1993) and is in many ways a simple special case of Asker and Cantillon (2006) where the project is xed, and the principal s (buyer s) objective is trivially xed given that the scoring rule…”
• Market-Based Emissions Regulation and Industry Dynamics (2016, methodology): “The interested reader can find a detailed description of the methodology inonline appendixB,wherewealsodiscuss themain strengths and limitations of this methodology ðsee also Doraszelski and Pakes 2007; Farias, Saure, and Weintraub 2012; Arcidiacono et al. 2013Þ.”