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Multiple equilibria and selection by learning in an applied setting

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  • Lee, Robin S.
  • Pakes, Ariel

Abstract

We explore two complementary approaches to counterfactual analysis in an empirical ATM network example with multiple equilibria. First we simply enumerate and compare the possible equilibria. Second, we examine how different learning algorithms select among them.

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Bibliographic Info

Article provided by Elsevier in its journal Economics Letters.

Volume (Year): 104 (2009)
Issue (Month): 1 (July)
Pages: 13-16

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Handle: RePEc:eee:ecolet:v:104:y:2009:i:1:p:13-16

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Web page: http://www.elsevier.com/locate/ecolet

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Keywords: Multiple equilibria Learning Counterfactuals in applied work;

References

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  1. Panle Jia, 2008. "What Happens When Wal-Mart Comes to Town: An Empirical Analysis of the Discount Retailing Industry," Econometrica, Econometric Society, vol. 76(6), pages 1263-1316, November.
  2. Young, H. Peyton, 2004. "Strategic Learning and its Limits," OUP Catalogue, Oxford University Press, number 9780199269181, September.
  3. Andrew McLennan, 2005. "The Expected Number of Nash Equilibria of a Normal Form Game," Econometrica, Econometric Society, vol. 73(1), pages 141-174, 01.
  4. Drew Fudenberg & David K. Levine, 1998. "The Theory of Learning in Games," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262061945, December.
  5. McLennan, Andrew & Berg, Johannes, 2005. "Asymptotic expected number of Nash equilibria of two-player normal form games," Games and Economic Behavior, Elsevier, vol. 51(2), pages 264-295, May.
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Cited by:
  1. Hunt Allcott, 2012. "The Smart Grid, Entry, and Imperfect Competition in Electricity Markets," NBER Working Papers 18071, National Bureau of Economic Research, Inc.

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