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Risk Aversion, Reservation Utility and Bargaining Power: An Evolutionary Algorithm Approximation of Incentive Contracts

Author

Listed:
  • Itza Tlaloc Quetzalcoatl Curiel-Cabral

    (El Colegio de México A.C.
    CIDE)

  • Sonia Giannatale

    (Centro de Investigación y Docencia Económicas (CIDE), División de Economía)

  • Giselle Labrador-Badía

    (University of Wisconsin-Madison)

Abstract

In this paper we analyze the links between the agent’s reservation utility, bargaining power, and risk aversion in terms of their simultaneous effects on the structure of optimal static contracts. We compare the following principal-agent models in the symmetric and asymmetric information environments: the standard approach, which includes a participation constraint, and a multi-objective (MO) optimization approach in which the objective function is a convex combination of the expected utilities of the principal and the agent. The MO model does not include a participation constraint, but it includes a parameter for the agent’s bargaining power. We also study an Evolutionary Algorithm implementation of the static principal-agent model to support and extend our analytical results. We show that the numerical solution approximated by our implementation of an evolutionary algorithm is in line with the analytical solutions mentioned before. That is, for every admissible value of the agent’s reservation utility, there is a corresponding admissible value of the agent’s bargaining parameter, both in the MO approach and the EA implementation.

Suggested Citation

  • Itza Tlaloc Quetzalcoatl Curiel-Cabral & Sonia Giannatale & Giselle Labrador-Badía, 2024. "Risk Aversion, Reservation Utility and Bargaining Power: An Evolutionary Algorithm Approximation of Incentive Contracts," Computational Economics, Springer;Society for Computational Economics, vol. 63(2), pages 477-511, February.
    • Handle: RePEc:kap:compec:v:63:y:2024:i:2:d:10.1007_s10614-022-10349-0
    DOI: 10.1007/s10614-022-10349-0
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    References listed on IDEAS

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    More about this item

    Keywords

    Moral hazard; Optimization; Evolutionary algorithms;
    All these keywords.

    JEL classification:

    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • C62 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Existence and Stability Conditions of Equilibrium
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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