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Multiple equilibria and selection by learning in an applied setting

  • Lee, Robin S.
  • Pakes, Ariel

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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File URL: http://www.sciencedirect.com/science/article/B6V84-4VWB13V-1/2/0e594e343c8a2c923f16362e7bc9e728
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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
Contact details of provider: Web page: http://www.elsevier.com/locate/ecolet

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  1. McLennan, A., 1999. "The Expected Number of Nash Equilibria of a Normal Form Game," Papers 306, Minnesota - Center for Economic Research.
  2. Drew Fudenberg & David K. Levine, 1996. "The Theory of Learning in Games," Levine's Working Paper Archive 624, David K. Levine.
  3. Young, H. Peyton, 2004. "Strategic Learning and its Limits," OUP Catalogue, Oxford University Press, number 9780199269181, March.
  4. 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.
  5. 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.
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