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Targeting the Wrong Teachers? Linking Measurement with Theory to Evaluate Teacher Incentive Schemes

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Abstract
Measurement is crucial to the implementation of output-based incentive schemes. This paper uses models to study the performance of teacher quality estimators that enter teacher incentive schemes. I model an administrator tasked with (i) categorizing teachers with respect to a cutoff, (ii) retaining teachers in a hidden type environment, and (iii) compensating teachers in a hidden action environment. The preferred estimator would be the same in each model and depends on the relationship between teacher quality and class size. I use data from Los Angeles to show that simple fixed effects would almost always outperform more popular empirical Bayes.

Suggested Citation

  • Nirav Mehta, 2017. "Targeting the Wrong Teachers? Linking Measurement with Theory to Evaluate Teacher Incentive Schemes," University of Western Ontario, Centre for Human Capital and Productivity (CHCP) Working Papers 20171, University of Western Ontario, Centre for Human Capital and Productivity (CHCP).
    • Handle: RePEc:uwo:hcuwoc:20171
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    2. Propper, Carol & Kunz, Johannes & Staub, Kevin & Winkelmann, Rainer, 2020. "Assessing the Quality of Public Services: Does Hospital Competition Crowd Out the For-Profit Quality Gap?," CEPR Discussion Papers 15045, C.E.P.R. Discussion Papers.
    3. Michael Gilraine & Jiaying Gu & Robert McMillan, 2020. "A New Method for Estimating Teacher Value-Added," NBER Working Papers 27094, National Bureau of Economic Research, Inc.

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    More about this item

    Keywords

    Teacher Incentive Pay; Teacher Quality;

    JEL classification:

    • J01 - Labor and Demographic Economics - - General - - - Labor Economics: General
    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
    • I28 - Health, Education, and Welfare - - Education - - - Government Policy
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty

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