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The Incentive Channel of Capital Market Interventions

Author

Listed:
  • Michael Lee

    (Federal Reserve Bank of New York)

  • Daniel Neuhann

    (UT Austin, McCombs School of Business)

Abstract

We develop a tractable dynamic model of collateralized lending in which the degree of adverse selection evolves endogenously due to moral hazard. We use this model to study how government interventions designed to boost liquidity in frozen markets af- fect private incentives to maintain high-quality assets. We show that small interventions can lead to “intervention traps” – expectations concerning future interventions destroy private incentives to improve the quality of collateral, which stunts recovery and war- rants continued market intervention – even when they restore market liquidity. Bigger interventions may lead to faster recoveries, and it may be efficient to continue to inter- vene even after market liquidity is restored. This runs counter to previous findings in static environments where it is optimal to keep interventions as small as possible, and to intervene only when markets are illiquid.

Suggested Citation

  • Michael Lee & Daniel Neuhann, 2018. "The Incentive Channel of Capital Market Interventions," 2018 Meeting Papers 840, Society for Economic Dynamics.
  • Handle: RePEc:red:sed018:840
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    References listed on IDEAS

    as
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    5. Braz Camargo & Kyungmin Kim & Benjamin Lester, 2016. "Information Spillovers, Gains from Trade, and Interventions in Frozen Markets," The Review of Financial Studies, Society for Financial Studies, vol. 29(5), pages 1291-1329.
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    7. Jonathan Chiu & Thorsten V. Koeppl, 2016. "Trading Dynamics with Adverse Selection and Search: Market Freeze, Intervention and Recovery," Review of Economic Studies, Oxford University Press, vol. 83(3), pages 969-1000.
    8. Ana Fostel & John Geanakoplos, 2012. "Leverage and Default in Binomial Economies: A Complete Characterization," Cowles Foundation Discussion Papers 1877R3, Cowles Foundation for Research in Economics, Yale University, revised Mar 2015.
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