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An Adverse Selection Model of Optimal Unemployment Insurance

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  • Marcus Hagedorn
  • Ashok Kaul

Abstract

We derive the shape of optimal unemployment insurance (UI) contracts when agents can exert search effort but face different search costs and have private information about their type. We derive a recursive solution of our dynamic adverse selection problem with repeated moral hazard. Conditions under which the UI agency should always offer separating contracts are identified. We show that the good searcher receives an information rent and that the bad searcher receives the minimal entitlement. From a methodological point of view, we achieve a precise characterization of the sets of jointly feasible entitlements. This allows us to map our analytical results one-to-one to a numerical algorithm. According to our results the contract for the good searcher has a decreasing benefit profile, as the one he would be offered in a pure moral hazard environment. In contrast, the contract of the bad searcher is distorted by an adverse selection effect, so that it tends to have an upward-sloping benefit profile. We provide a comparative static analysis of changes in various parameters of our model.

Suggested Citation

  • Marcus Hagedorn & Ashok Kaul, 2004. "An Adverse Selection Model of Optimal Unemployment Insurance," Computing in Economics and Finance 2004 154, Society for Computational Economics.
  • Handle: RePEc:sce:scecf4:154
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    References listed on IDEAS

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    1. Hagedorn, Marcus & Kaul, Ashok & Mennel, Tim, 2010. "An adverse selection model of optimal unemployment insurance," Journal of Economic Dynamics and Control, Elsevier, vol. 34(3), pages 490-502, March.
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    Citations

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    Cited by:

    1. Andreas Pollak, 2008. "Optimal Unemployment Insurance with Variable Skill Levels," Journal of Institutional and Theoretical Economics (JITE), Mohr Siebeck, Tübingen, vol. 164(4), pages 696-726, December.
    2. O'Flaherty, Brendan, 2009. "When should homeless families get subsidized apartments? A theoretical inquiry," Journal of Housing Economics, Elsevier, vol. 18(2), pages 69-80, June.
    3. Hairault, Jean-Olivier & Langot, François & Ménard, Sébastien & Sopraseuth, Thepthida, 2012. "Optimal unemployment insurance for older workers," Journal of Public Economics, Elsevier, vol. 96(5), pages 509-519.
    4. Anne Bucher & Sébastien Ménard, 2010. "Employment Protection Legislation and Adverse Selection at the Labor Market Entry," TEPP Working Paper 2010-21, TEPP.
    5. Hagedorn, Marcus & Kaul, Ashok & Mennel, Tim, 2010. "An adverse selection model of optimal unemployment insurance," Journal of Economic Dynamics and Control, Elsevier, vol. 34(3), pages 490-502, March.
    6. Anne Bucher & Sébastien Ménard, 2015. "The effects of firing costs on the wage contracts under adverse selection," Working Papers of BETA 2015-17, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    7. Fuller, David L., 2014. "Adverse selection and moral hazard: Quantitative implications for unemployment insurance," Journal of Monetary Economics, Elsevier, vol. 62(C), pages 108-122.
    8. Arpad Abraham & Nicola Pavoni, 2008. "Efficient Allocations with Moral Hazard and Hidden Borrowing and Lending: A Recursive Formulation," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 11(4), pages 781-803, October.

    More about this item

    Keywords

    Unemployment Insurance; Recursive Contracts; Adverse Selection; Repeated Moral Hazard;

    JEL classification:

    • J65 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Unemployment Insurance; Severance Pay; Plant Closings
    • J64 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Unemployment: Models, Duration, Incidence, and Job Search
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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