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Optimality of Debt under Flexible Information Acquisition

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  • Ming Yang

Abstract

This article studies a security design problem featuring flexible information acquisition. To raise liquidity, a seller issues a security backed by her asset in place at the price she proposes to a buyer. Before deciding whether to accept the offer, the buyer can acquire costly information about the underlying asset. This case differs from the existing literature on security design, in that the buyer has the full flexibility of choosing not only the amount of resources to spend in information acquisition, but also how to allocate them, depending on the shape of the security. Debt is shown to be the unique optimal security for the seller, as its payoff is the least sensitive to the value of its underlying asset. This minimizes the buyer’s incentive to acquire information and mitigates the resulting adverse selection. I do not assume monotonicity of the feasible securities nor impose various distributional assumptions on information structures. Instead, I identify conditions for general information costs that support the results.

Suggested Citation

  • Ming Yang, 2020. "Optimality of Debt under Flexible Information Acquisition," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 87(1), pages 487-536.
  • Handle: RePEc:oup:restud:v:87:y:2020:i:1:p:487-536.
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    File URL: http://hdl.handle.net/10.1093/restud/rdz035
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    Cited by:

    1. Takalo, Tuomas & Tanayama, Tanja & Toivanen, Otto, 2022. "Welfare effects of R&D support policies," Research Discussion Papers 2/2022, Bank of Finland.
    2. Bartosz Maćkowiak & Filip Matějka & Mirko Wiederholt, 2023. "Rational Inattention: A Review," Journal of Economic Literature, American Economic Association, vol. 61(1), pages 226-273, March.
    3. Takalo, Tuomas & Tanayama, Tanja & Toivanen, Otto, 2017. "Welfare effects of R&D support policies," Bank of Finland Research Discussion Papers 30/2017, Bank of Finland.
    4. Doron Ravid, 2020. "Ultimatum Bargaining with Rational Inattention," American Economic Review, American Economic Association, vol. 110(9), pages 2948-2963, September.
    5. Jan Starmans, 2023. "Technological Determinants of Financial Constraints," Management Science, INFORMS, vol. 69(5), pages 3003-3024, May.
    6. Babus, Ana & Hachem, Kinda, 2023. "Markets for financial innovation," Journal of Economic Theory, Elsevier, vol. 208(C).
    7. Benjamin Hébert & Michael Woodford, 2021. "Neighborhood-Based Information Costs," American Economic Review, American Economic Association, vol. 111(10), pages 3225-3255, October.
    8. Glode, Vincent & Opp, Christian C. & Sverchkov, Ruslan, 2022. "To pool or not to pool? Security design in OTC markets," Journal of Financial Economics, Elsevier, vol. 145(2), pages 508-526.
    9. Asano, Koji, 2024. "Managing financial expertise," International Review of Economics & Finance, Elsevier, vol. 89(PA), pages 351-365.
    10. Cai, Zhifeng & Dong, Feng, 2023. "Public disclosure and private information acquisition: A global game approach," Journal of Economic Theory, Elsevier, vol. 210(C).
    11. Chaigneau, Pierre, 2023. "Capital Structure with Information about the Upside and the Downside," MPRA Paper 121397, University Library of Munich, Germany.
    12. Kim, Kyungmin & Koh, Youngwoo, 2022. "Auctions with flexible information acquisition," Games and Economic Behavior, Elsevier, vol. 133(C), pages 256-281.
    13. Dunhong Jin & Thomas Noe, 2022. "The Golden Mean: The Risk‐Mitigating Effect of Combining Tournament Rewards with High‐Powered Incentives," Journal of Finance, American Finance Association, vol. 77(5), pages 2907-2947, October.
    14. repec:zbw:bofrdp:2022_002 is not listed on IDEAS

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