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Validating Teacher Effect Estimates Using Changes in Teacher Assignments in Los Angeles

Author

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  • Andrew Bacher-Hicks
  • Thomas J. Kane
  • Douglas O. Staiger

Abstract

In a widely cited study, Chetty, Friedman, and Rockoff (2014a; hereafter CFR) evaluate the degree of bias in teacher value-added estimates using a novel "teacher switching" research design with data from New York City. They conclude that there is little to no bias in their estimates. Using the same model with data from North Carolina, Rothstein (2014) argued that the CFR research design is invalid, given a relationship between student baseline test scores and teachers' value-added. In this paper, we replicated the CFR analysis using data from the Los Angeles Unified School District and similarly found that teacher value-added estimates were valid predictors of student achievement. We also demonstrate that Rothstein's test does not invalidate the CFR design and instead reflects a mechanical relationship, given that teacher value-added scores from prior years and baseline test scores can be based on the same data. In addition, we explore the (1) predictive validity of value-added estimates drawn from the same, similar, and different schools, (2) an alternative way of estimating differences in access to effective teaching by taking teacher experience into account, and (3) the implications of alternative ways of imputing value-added when it cannot be estimated directly.

Suggested Citation

  • Andrew Bacher-Hicks & Thomas J. Kane & Douglas O. Staiger, 2014. "Validating Teacher Effect Estimates Using Changes in Teacher Assignments in Los Angeles," NBER Working Papers 20657, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:20657
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    References listed on IDEAS

    as
    1. LaLonde, Robert J, 1986. "Evaluating the Econometric Evaluations of Training Programs with Experimental Data," American Economic Review, American Economic Association, vol. 76(4), pages 604-620, September.
    2. Jesse Rothstein, 2010. "Teacher Quality in Educational Production: Tracking, Decay, and Student Achievement," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 125(1), pages 175-214.
    3. Thomas J. Kane & Douglas O. Staiger, 2008. "Estimating Teacher Impacts on Student Achievement: An Experimental Evaluation," NBER Working Papers 14607, National Bureau of Economic Research, Inc.
    4. Thomas J. Kane & Douglas O. Staiger, 2002. "The Promise and Pitfalls of Using Imprecise School Accountability Measures," Journal of Economic Perspectives, American Economic Association, vol. 16(4), pages 91-114, Fall.
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    7. David J. Deming, 2014. "Using School Choice Lotteries to Test Measures of School Effectiveness," American Economic Review, American Economic Association, vol. 104(5), pages 406-411, May.
    8. Hanushek, Eric, 1971. "Teacher Characteristics and Gains in Student Achievement: Estimation Using Micro Data," American Economic Review, American Economic Association, vol. 61(2), pages 280-288, May.
    9. Donald Boyd & Hamilton Lankford & Susanna Loeb & Jonah Rockoff & James Wyckoff, 2008. "The narrowing gap in New York City teacher qualifications and its implications for student achievement in high-poverty schools," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 27(4), pages 793-818.
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    11. Atila Abdulkadiroğlu & Joshua D. Angrist & Susan M. Dynarski & Thomas J. Kane & Parag A. Pathak, 2011. "Accountability and Flexibility in Public Schools: Evidence from Boston's Charters And Pilots," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 126(2), pages 699-748.
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    More about this item

    JEL classification:

    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
    • J45 - Labor and Demographic Economics - - Particular Labor Markets - - - Public Sector Labor Markets

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