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Do We Follow Others When We Should? A Simple Test of Rational Expectations

  • Weizsäcker, Georg


    (DIW Berlin)

The paper presents a new meta data set covering 13 experiments on the social learning games by Bikhchandani, Hirshleifer, and Welch (1992). The large amount of data makes it possible to estimate the empirically optimal action for a large variety of decision situations and ask about the economic significance of suboptimal play. For example, one can ask how much of the possible payoffs the players earn in situations where it is empirically optimal that they follow others and contradict their own information. The answer is 53% on average across all experiments – only slightly more than what they would earn by choosing at random. The players’ own information carries much more weight in the choices than the information conveyed by other players’ choices: the average player contradicts her own signal only if the empirical odds ratio of the own signal being wrong, conditional on all available information, is larger than 2:1, rather than 1:1 as would be implied by rational expectations. A regression analysis formulates a straightforward test of rational expectations, which rejects, and confirms that the reluctance to follow others generates a large part of the observed variance in payoffs, adding to the variance that is due to situational differences.

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Paper provided by Institute for the Study of Labor (IZA) in its series IZA Discussion Papers with number 3616.

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Length: 38 pages
Date of creation: Jul 2008
Date of revision:
Publication status: published in: American Economic Review, 2010, 100 (5), 2340-2360
Handle: RePEc:iza:izadps:dp3616
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  1. Jonathan E. Alevy & Michael S. Haigh & John List, 2006. "Information Cascades: Evidence from An Experiment with Financial Market Professionals," NBER Working Papers 12767, National Bureau of Economic Research, Inc.
  2. Kraemer, Carlo & Nöth, Markus & Weber, Martin, 2000. "Information Aggregation with Costly Information and Random Ordering: Experimental Evidence," Sonderforschungsbereich 504 Publications 00-35, Sonderforschungsbereich 504, Universität Mannheim;Sonderforschungsbereich 504, University of Mannheim.
  3. Guarino, Antonio & Harmgart, Heike & Huck, Steffen, 2011. "Aggregate information cascades," Games and Economic Behavior, Elsevier, vol. 73(1), pages 167-185, September.
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  14. Dorothea Kübler & Georg Weizsäcker, 2005. "Are Longer Cascades More Stable?," Journal of the European Economic Association, MIT Press, vol. 3(2-3), pages 330-339, 04/05.
  15. Alevy, Jonathan E. & Haigh, Michael S. & List, John A., 2003. "Information Cascades: Evidence From A Field Experiment With Financial Market Professionals," Working Papers 28608, University of Maryland, Department of Agricultural and Resource Economics.
  16. Dominitz, Jeff & Hung, Angela A., 2009. "Empirical models of discrete choice and belief updating in observational learning experiments," Journal of Economic Behavior & Organization, Elsevier, vol. 69(2), pages 94-109, February.
  17. Kübler, Dorothea & Weizsäcker, Georg, 2000. "Limited depth of reasoning and failure of cascade formation in the laboratory," SFB 373 Discussion Papers 2001,3, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
  18. Harless, David W & Camerer, Colin F, 1994. "The Predictive Utility of Generalized Expected Utility Theories," Econometrica, Econometric Society, vol. 62(6), pages 1251-89, November.
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  27. Syngjoo Choi & Douglas Gale & Shachar Kariv, 2005. "Learning in Networks: An Experimental Study," Levine's Bibliography 122247000000000044, UCLA Department of Economics.
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