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Endogenous Precision of Performance Measures and Limited Managerial Attention

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  • Pierre Jinghong Liang
  • Lin Nan

Abstract

In this paper, we model two drivers that underlie the economic trade-off that shareholders face in designing incentives for optimal effort allocation by managers. The first driver is the presence of a performance-reporting task, by which we mean managers may exert effort to improve the precision of their performance measures. The second is limited managerial attention, where performing one task may have an adverse effect on the cost efficiency of performing another. We show that the subtle interactions of the two drivers may alter the characteristics of incentive provision. First, the interaction may lead to a positive relation between the strength of the incentive and the variance of the performance measures. Second, the interaction may cause an informative performance signal to not be used in equilibrium incentive contracts. In particular, it is possible that the principal will not use a signal whose precision can be improved by the manager in order to discourage the manager from diverting attention to the performance-reporting task. Finally, we apply the model to a project-selection setting and show that, in order to induce the agent to choose higher risk, higher return projects, the principal may need to raise the bonus rate when the choice of project is unobservable.

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  • Pierre Jinghong Liang & Lin Nan, 2014. "Endogenous Precision of Performance Measures and Limited Managerial Attention," European Accounting Review, Taylor & Francis Journals, vol. 23(4), pages 693-727, December.
    • Handle: RePEc:taf:euract:v:23:y:2014:i:4:p:693-727
    DOI: 10.1080/09638180.2013.864568
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    Cited by:

    1. Lin Nan & Xiaoyan Wen, 2019. "Penalties, Manipulation, and Investment Efficiency," Management Science, INFORMS, vol. 65(10), pages 4878-4900, October.
    2. 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.
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    4. Henry L. Friedman & John S. Hughes & Beatrice Michaeli, 2022. "A Rationale for Imperfect Reporting Standards," Management Science, INFORMS, vol. 68(3), pages 2028-2046, March.

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