Bounded Rationality in Decisions and Games Summer School : Program Content

Discover the content of the PSE Summer School’s Bounded Rationality in Decisions and Games program.

An in-depth program content

The content of the Bounded Rationality in Decisions and Games program is composed of lectures, practical sessions and workshops. During these workshops, you will have the opportunity to submit a paper and those selected will be presented in front of participants and faculty.

The program addresses key questions such as: How do bounded rationality and behavioral factors influence economic decisions? What happens when agents have limited information or use simplified strategies in games? How can decision-making under uncertainty be better understood using new models?

The course is methodological in nature, focusing on equipping participants with the skills to apply these behavioral concepts to their own research and academic pursuits.

Course listing:

  • Games with strategy restrictions
  • Behavioral Game Theory
  • Analogy-based expectation equilibrium
  • Prospect theory and Ambiguity

Course details

by Olivier Compte

The Bayesian paradigm used in economic modelling often assumes that agents behave optimally as if they knew all details of the model (preferences, distributions etc). In this mini-course, we explore how strategy restrictions can help assess the robustness of models that use the Bayesian assumption, and also how these strategy restrictions, viewed as a family of available heuristics, can be used as a modelling device to limit the sophistication of the agents we model, including analyzing agents with differentiated levels of sophistication or different ways agents would frame their own environment. Recent work in this vein will be presented, as well as an analysis of how this line of research departs from other work in the bounded rationality literature.

Selected key reference

  • Compte O. & Postlewaite A., 2018, Ignorance and Uncertainty, Cambridge University Press.

by Evan Friedman

The goal of this course is to offer an introduction to the branch of behavioral game theory (BGT) based on bounded rationality (as opposed to, e.g., social preferences). We first motivate BGT by reviewing classic experiments that document deviations from Nash equilibrium in simple games of complete information. We discuss alternative concepts that can explain these anomalies, emphasizing how such models are commonly used in the analysis of experimental data. We then consider games with incomplete information and study models in which players neglect correlation between variables or misperceive their strategic environment.

Selected key references

  • Alaoui L. & Penta A., 2016, “Endogenous Depth of Reasoning”, The Review of Economic Studies, pp 1297-1333.
  • Esponda I. & Pouzo D., 2016, “Berk-Nash equilibrium: A framework for modeling”, The Econometric Society, 84(3), pp 1093-1130.
  • Friedman E., 2022, “Stochastic Equilibria: Noise in Actions or Beliefs?”, American Economic Journal: Microeconomics, 14(1), pp 94-142.
  • Goeree J. & Holt C., 2001, “Ten Little Treasures of Game Theory and Ten Intuitive Contradictions”, The American Economic Review, 91(5), pp 1402-1422.
  • Goeree J., Holt C. & Palfrey T., 2005, “Regular Quantal Response Equilibrium”, Experimental Economics, 8(4), pp 347-367.
  • McKelvey R. & Palfrey T., 1995, “Quantal Response Equilibrium in Normal Form Games”, Games and Economic Behavior, 10, pp 6-38.
  • Nagel R., 1995, “Unraveling in Guessing Games: an Experimental Study”, The American Economic Review, 85(5), pp 1313-1326.
  • Osborne M. & Rubinstein A., 2003, “Sampling Equilibrium, with an Application to Strategic Voting”, Games and Economic Behavior, 45(2), pp 434-441.
  • Spiegler R., 2016, “Bayesian Networks and Boundedly Rational Expectations”, The Quarterly Journal of Economics, 131(3), pp 1243-1290.

by Philippe Jehiel

The goal of this course is to expose students with a game theoretic model developed over the last twenty years that aims at relaxing the degree of fineness with which economic agents understand the reaction of their environment. The course will present the basics of the analogy-based expectation equilibrium as initially introduced in Jehiel (2005) as well as various applications covering bargaining, cooperation, investment strategy among others. At the end of the course, students should be equipped to apply the approach to whatever field of interest.

Selected key references

  • Ettinger D. & Jehiel P., 2010, “A Theory of Deception”, American Economic Journal: Microeconomics, 2(1), pp 1-20.
  • Huck S., Jehiel P. & Rutter T., 2011, “Learning spillover and analogy-based expectations: A multi-game experiment”, Games and Economic Behavior, 71(2), pp 351-365.
  • Jehiel P., 2005, “Analogy-based Expectation Equilibrium”, Journal of Economic Theory, 123(2), pp 81-104.
  • Jehiel P. & Koessler F., 2008, “Revisiting Games of Incomplete Information with Analogy-based Expectations”, Games and Economic Behavior, 62(2), pp 533-557.
  • Jehiel P., 2011, “Manipulative auction design”, Theoretical Economics, 6(2), pp 185-217.
  • Jehiel P., 2018, “Investment strategy and selection neglect: An equilibrium perspective on overoptimism”, American Economic Review, 10(6), pp 1582-97.
  • Jehiel P., 2022, Analogy-based expectation equilibrium and related concepts: Theory, applications, and beyond, halshs-03735680, HAL.

by Jean-Marc Tallon

Invoking probabilities when thinking about an uncertain future is rather common and yet, coming up with probabilistic representations on the one hand and using probabilities to take decisions on the other hand is extremely complex. In this mini-course, we will explore recent approaches to these issues, focusing on so-called “ambiguity” models.

Selected key references

  • Gilboa I., 2009, Theory of Decision under Uncertainty, Cambridge University Press.
  • M. Machina & Kip Viscusi W., 2013, Handbook of Economics of Risk and Uncertainty, North Holland.
  • Wakker P., 2010, Prospect Theory for risk and ambiguity, Cambridge University Press.