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Learning by (limited) forward looking players

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  • Mengel Friederike

    (METEOR)

Abstract

We present a model of adaptive economic agents that are k periods forward looking. Agents in our model are randomly matched to interact in finitely repeated games. They form beliefs by relying on their past experience in the same situation (after the same recent history) and then best respond to these beliefs looking k periods ahead. We establish almost sure convergence of our stochastic process and characterize absorbing sets. These can be very different from the predictions in both the fully rational model and the adaptive, but myopic case. In particular we find that also Non-Nash outcomes can be sustained almost all the time whenever they are individually rational and satisfy an efficiency condition. We then characterize stochastically stable states in 2×2 games and show that under certain conditions the efficient action in Prisoner''s Dilemma games and Coordination games can be singled out as uniquely stochastically stable. We show that our results are consistent with typical patterns observed in experiments on finitely repeated Prisoner''s Dilemma games. Finally, if populations are composed of some myopic and some forward looking agents parameter constellations exists such that either might obtain higher average payoffs.

Suggested Citation

  • Mengel Friederike, 2008. "Learning by (limited) forward looking players," Research Memorandum 053, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
  • Handle: RePEc:unm:umamet:2008053
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    References listed on IDEAS

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    Cited by:

    1. Marco Mantovani, 2015. "Limited backward induction: foresight and behavior in sequential games," Working Papers 289, University of Milano-Bicocca, Department of Economics, revised Jan 2015.
    2. Aidas Masiliunas, 2016. "Inefficient Lock-in with Sophisticated and Myopic Players," Working Papers halshs-01304178, HAL.
    3. Charness, Gary & Feri, Francesco & Meléndez-Jiménez, Miguel A. & Sutter, Matthias, 2012. "Equilibrium Selection in Experimental Games on Networks," University of California at Santa Barbara, Economics Working Paper Series qt51v6w9hd, Department of Economics, UC Santa Barbara.
    4. Holger Herz & Armin Schmutzler & André Volk, 2016. "Cooperation and Mistrust in Relational Contracts," ECON - Working Papers 233, Department of Economics - University of Zurich.
    5. Norton, Douglas A., 2015. "Killing the (coordination) moment: How ambiguity eliminates the restart effect in voluntary contribution mechanism experiments," Economics Letters, Elsevier, vol. 126(C), pages 1-5.
    6. Aidas Masiliunas, 2016. "Inefficient Lock-in with Sophisticated and Myopic Players," Working Papers halshs-01304178, HAL.

    More about this item

    Keywords

    Economics (Jel: A);

    JEL classification:

    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games
    • C90 - Mathematical and Quantitative Methods - - Design of Experiments - - - General
    • D03 - Microeconomics - - General - - - Behavioral Microeconomics: Underlying Principles

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