• Graduate Programs
    • Facilities
    • Tinbergen Institute Research Master in Economics
      • Why Tinbergen Institute?
      • Research Master
      • Admissions
      • PhD Vacancies
      • Selected PhD Placements
    • Research Master Business Data Science
    • Education for external participants
    • Summer School
    • Tinbergen Institute Lectures
    • PhD Vacancies
  • Research
  • Browse our Courses
  • Events
    • Summer School
      • Applied Public Policy Evaluation
      • Deep Learning
      • Development Economics
      • Economics of Blockchain and Digital Currencies
      • Economics of Climate Change
      • The Economics of Crime
      • Foundations of Machine Learning with Applications in Python
      • From Preference to Choice: The Economic Theory of Decision-Making
      • Inequalities in Health and Healthcare
      • Marketing Research with Purpose
      • Markets with Frictions
      • Modern Toolbox for Spatial and Functional Data
      • Sustainable Finance
      • Tuition Fees and Payment
      • Business Data Science Summer School Program
    • Events Calendar
    • Events Archive
    • Tinbergen Institute Lectures
    • 2026 Tinbergen Institute Opening Conference
    • Annual Tinbergen Institute Conference
  • News
  • Summer School
  • Alumni
    • PhD Theses
    • Master Theses
    • Selected PhD Placements
    • Key alumni publications
    • Alumni Community

Arifovic, J., Hommes, C. and Salle, I. (2019). Learning to believe in simple equilibria in a complex OLG economy - evidence from the lab Journal of Economic Theory, 183:106--182.


  • Journal
    Journal of Economic Theory

We set up a laboratory experiment to empirically investigate equilibrium selection in a complex economic environment. We use the overlapping-generation model of Grandmont (1985), which displays multiple perfect-foresight equilibria, including periodic and chaotic dynamics. The equilibrium selection problem is not solved under learning, as each outcome is predicted by at least one existing learning theory. We find that subjects in the lab systematically coordinate on an equilibrium despite the complexity of the environment. Coordination only happens on simple equilibria, in this case the steady state or the period-two cycle, a result which is predicted only if the subjects follow simple learning rules. This suggests that relevant perfect-foresight equilibria should be robust to the use of simple rules.