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Learning by doing vs. learning from others in a principal-agent model

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  • Arifovic, Jasmina
  • Karaivanov, Alexander

Abstract

We introduce learning in a principal-agent model of output sharing under moral hazard. We use social evolutionary learning to represent social learning and reinforcement, experience-weighted attraction (EWA) and individual evolutionary learning (IEL) to represent individual learning. Learning in the principal-agent model is difficult due to: the stochastic environment; the discontinuity in payoffs at the optimal contract; and the incorrect evaluation of foregone payoffs for IEL and EWA. Social learning is much more successful in adapting to the optimal contract than standard individual learning algorithms. A modified IEL using realized payoffs evaluation performs better but still falls short of social learning.

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Bibliographic Info

Article provided by Elsevier in its journal Journal of Economic Dynamics and Control.

Volume (Year): 34 (2010)
Issue (Month): 10 (October)
Pages: 1967-1992

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Handle: RePEc:eee:dyncon:v:34:y:2010:i:10:p:1967-1992

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Web page: http://www.elsevier.com/locate/jedc

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Keywords: Learning Principal-agent model Moral hazard;

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