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Incomplete Information, Dynamic Stability and the Evolution of Preferences: Two Examples

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  • Jean Rabanal
  • Daniel Friedman
Abstract
We illustrate general techniques for assessing dynamic stability in games of incomplete information by re-analyzing two models of preference evolution, the Arce (Econ. Inq. 45(4):708–720, 2007 ) Employer–Worker game and the Friedman and Singh (Games Econ. Behav. 66:813–829, 2009 ) Noisy Trust game. The techniques include extensions of replicator and gradient dynamics, and for both models they confirm local stability of the key static equilibria. That is, we obtain convergence in time average for initial conditions sufficiently near equilibrium values. Copyright Springer Science+Business Media New York 2014

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  • Jean Rabanal & Daniel Friedman, 2014. "Incomplete Information, Dynamic Stability and the Evolution of Preferences: Two Examples," Dynamic Games and Applications, Springer, vol. 4(4), pages 448-467, December.
    • Handle: RePEc:spr:dyngam:v:4:y:2014:i:4:p:448-467
    DOI: 10.1007/s13235-013-0096-5
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    Cited by:

    1. Daniel G. Arce, 2018. "On the cooperative and competitive aspects of strategic monitoring," Rationality and Society, , vol. 30(3), pages 377-390, August.
    2. Ulrich Berger, 2016. "Learning to trust, learning to be trustworthy," Department of Economics Working Papers wuwp212, Vienna University of Economics and Business, Department of Economics.
    3. Jean Paul Rabanal, 2017. "On the Evolution of Continuous Types Under Replicator and Gradient Dynamics: Two Examples," Dynamic Games and Applications, Springer, vol. 7(1), pages 76-92, March.
    4. Fulei Shi & Chuansheng Wang & Cuiyou Yao, 2022. "A New Evolutionary Game Analysis for Industrial Pollution Management Considering the Central Government’s Punishment," Dynamic Games and Applications, Springer, vol. 12(2), pages 677-688, June.

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