An approximate dynamic programming approach to solving dynamic oligopoly models.
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 bes...
| Publicado en: | RAND Journal of Economics (Wiley-Blackwell) Vol. 43; no. 2; pp. 253 - 283 |
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| Autores principales: | , , |
| Formato: | Artículo |
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Wiley-Blackwell
Summer2012
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=76917928&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 76917928 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 07416261 56RJ jtl: RAND Journal of Economics (Wiley-Blackwell) issn: 07416261 maglogo: Y pubinfo: dt: Summer2012 vid: 43 iid: 2 pid: 480 pub: Wiley-Blackwell artinfo: ui: 76917928 10.1111/j.1756-2171.2012.00165.x ppf: 253 ppct: 30 formats: fmt: @attributes: type: P size: 816KB tig: atl: An approximate dynamic programming approach to solving dynamic oligopoly models. aug: au: Farias, Vivek Saure, Denis Weintraub, Gabriel Y. affil: Massachusetts Institute of Technology; . University of Pittsburgh; . Columbia University; . su: Oligopolies Dynamic programming Mathematical models Algorithms Approximation theory Dimension reduction (Statistics) Mathematical functions sug: subj: Oligopolies Dynamic programming Mathematical models Algorithms Approximation theory Dimension reduction (Statistics) Mathematical functions ab: 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. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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