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Implementation in Principal-Agent Models of Adverse Selection

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  • Arya, Anil
  • Glover, Jonathan
  • Rajan, Uday

Abstract

This paper studies implementation in a principal-agent model of adverse selection. We explore ways in which the additional structure of principal agent models (compared to general implementaion models) simplifies the implementation problem. We develop a connection between the single crossing property and monotonicity conditions which are necessary for Nash and Bayesian Nash implementation.
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  • Arya, Anil & Glover, Jonathan & Rajan, Uday, 2000. "Implementation in Principal-Agent Models of Adverse Selection," Journal of Economic Theory, Elsevier, vol. 93(1), pages 87-109, July.
  • Handle: RePEc:eee:jetheo:v:93:y:2000:i:1:p:87-109
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    3. Pereira, Samuel C.A., 2009. "Ignorance in a multi-agent setting," Economics Letters, Elsevier, vol. 105(3), pages 264-266, December.
    4. Malachy James Gavan & Antonio Penta, 2022. "Safe Implementation," Working Papers 1363, Barcelona School of Economics.
    5. Saran, Rene, 2016. "Bounded depths of rationality and implementation with complete information," Journal of Economic Theory, Elsevier, vol. 165(C), pages 517-564.
    6. Gavan, Malachy James & Penta, Antonio, 2022. "Safe Implementation," TSE Working Papers 22-1369, Toulouse School of Economics (TSE).
    7. Friedman, Henry L., 2014. "Implications of power: When the CEO can pressure the CFO to bias reports," Journal of Accounting and Economics, Elsevier, vol. 58(1), pages 117-141.
    8. Nalinaksha Bhattacharyya & Amin Mawani & Cameron Morrill, 2008. "Dividend payout and executive compensation: theory and evidence," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 48(4), pages 521-541, December.

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    More about this item

    JEL classification:

    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design

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