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Optimal Contracting with Costly State Verification, with an Application to Crowdsourcing

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Listed:
  • Aislinn Bohren

    (Department of Economics, University of Pennsylvania)

  • Troy Kravitz

    (FDIC)

Abstract

A firm employs workers to obtain costly unverifiable information - for example, categorizing the content of images. Workers are monitored by comparing their messages. The optimal contract under limited liability exhibits three key features: (i) the monitoring technology depends crucially on the commitment power of the firm - virtual monitoring, or monitoring with arbitrarily small probability, is optimal when the firm can commit to truthfully reveal messages from other workers, while monitoring with strictly positive probability is optimal when the firm can hide messages (partial commitment), (ii) bundling multiple tasks reduces worker rents and monitoring inefficiencies; and (iii) the optimal contract is approximately efficient under full but not partial commitment. We conclude with an application to crowdsourcing platforms, and characterize the optimal contract for tasks found on these platforms.

Suggested Citation

  • Aislinn Bohren & Troy Kravitz, 2016. "Optimal Contracting with Costly State Verification, with an Application to Crowdsourcing," PIER Working Paper Archive 16-023, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 15 Jun 2016.
    • Handle: RePEc:pen:papers:16-023
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    References listed on IDEAS

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    Cited by:

    1. Szydlowski, Martin, 2019. "Incentives, project choice, and dynamic multitasking," Theoretical Economics, Econometric Society, vol. 14(3), July.

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