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When Incentives Matter Too Much: Explaining Significant Responses to Irrelevant Information

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  • Tom Ahn
  • Jacob L. Vigdor

Abstract

When agents observe a continuous variable and a discrete signal based on that variable, theory suggests that the signal should not impact behavior conditional on the variable. Numerous empirical studies, many based on regression discontinuity design, contradict this basic prediction. We propose two rationalizations with testable implications. One is based on information acquisition costs and the other on learning and imperfect information. Using education data from North Carolina and exploiting a pay-for-performance system, we find support for the model of learning. This implies that rational responses to policy interventions may emerge gradually, and evaluations with short-term data may understate treatment effects.

Suggested Citation

  • Tom Ahn & Jacob L. Vigdor, 2021. "When Incentives Matter Too Much: Explaining Significant Responses to Irrelevant Information," Journal of Human Capital, University of Chicago Press, vol. 15(4), pages 629-664.
    • Handle: RePEc:ucp:jhucap:doi:10.1086/716785
    DOI: 10.1086/716785
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    1. Chakrabarti, Rajashri, 2014. "Incentives and responses under No Child Left Behind: Credible threats and the role of competition," Journal of Public Economics, Elsevier, vol. 110(C), pages 124-146.
    2. Ahn, Tom, 2014. "A regression discontinuity analysis of graduation standards and their impact on students’ academic trajectories," Economics of Education Review, Elsevier, vol. 38(C), pages 64-75.
    3. El-Gamal, Mahmoud A. & Sundaram, Rangarajan K., 1993. "Bayesian economists ... Bayesian agents : An alternative approach to optimal learning," Journal of Economic Dynamics and Control, Elsevier, vol. 17(3), pages 355-383, May.
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    5. David Card & Alexandre Mas & Jesse Rothstein, 2008. "Tipping and the Dynamics of Segregation," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 123(1), pages 177-218.
    6. repec:mpr:mprres:6364 is not listed on IDEAS
    7. Chiang, Hanley, 2009. "How accountability pressure on failing schools affects student achievement," Journal of Public Economics, Elsevier, vol. 93(9-10), pages 1045-1057, October.
    8. Allcott, Hunt, 2011. "Social norms and energy conservation," Journal of Public Economics, Elsevier, vol. 95(9-10), pages 1082-1095, October.
    9. Bala, Venkatesh & Goyal, Sanjeev, 1995. "A Theory of Learning with Heterogeneous Agents," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 36(2), pages 303-323, May.
    10. Jonah Berger & Devin Pope, 2011. "Can Losing Lead to Winning?," Management Science, INFORMS, vol. 57(5), pages 817-827, May.
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    Cited by:

    1. Figlio, D. & Karbownik, K. & Salvanes, K.G., 2016. "Education Research and Administrative Data," Handbook of the Economics of Education,, Elsevier.
    2. Julie Berry Cullen & Cory Koedel & Eric Parsons, 2021. "The Compositional Effect of Rigorous Teacher Evaluation on Workforce Quality," Education Finance and Policy, MIT Press, vol. 16(1), pages 7-41, Winter.
    3. Tom Ahn, 2017. "Strategic Matching of Teachers and Schools with (and without) Accountability Pressure," Education Finance and Policy, MIT Press, vol. 12(4), pages 516-535, Fall.
    4. Brehm, Margaret & Imberman, Scott A. & Lovenheim, Michael F., 2017. "Achievement effects of individual performance incentives in a teacher merit pay tournament," Labour Economics, Elsevier, vol. 44(C), pages 133-150.

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    More about this item

    JEL classification:

    • D03 - Microeconomics - - General - - - Behavioral Microeconomics: Underlying Principles
    • I2 - Health, Education, and Welfare - - Education
    • J33 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Compensation Packages; Payment Methods

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