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Beyond Levels and Growth: Estimating Teacher Value-Added and its Persistence

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  • Josh Kinsler

Abstract

The levels and growth achievement functions make extreme and diametrically opposed assumptions about the rate at which teacher inputs persist. I first show that if these assumptions are incorrect, teacher value-added estimates can be significantly biased. I then develop a tractable, cumulative model of student achievement that allows for the joint estimation of unobserved teacher quality and its persistence. The model can accommodate varying persistence rates, student heterogeneity, and time-varying teacher attributes. I implement the proposed methodology using schooling data from North Carolina, and find that only a third of the contemporaneous teacher effect survives into the next grade.

Suggested Citation

  • Josh Kinsler, 2012. "Beyond Levels and Growth: Estimating Teacher Value-Added and its Persistence," Journal of Human Resources, University of Wisconsin Press, vol. 47(3), pages 722-753.
    • Handle: RePEc:uwp:jhriss:v:46:y:2012:iii:1:p:722-753
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    References listed on IDEAS

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    1. Harris, Douglas N. & Sass, Tim R., 2011. "Teacher training, teacher quality and student achievement," Journal of Public Economics, Elsevier, vol. 95(7-8), pages 798-812, August.
    2. Brian A. Jacob & Lars Lefgren & David P. Sims, 2010. "The Persistence of Teacher-Induced Learning," Journal of Human Resources, University of Wisconsin Press, vol. 45(4), pages 915-943.
    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. Daniel Aaronson & Lisa Barrow & William Sander, 2007. "Teachers and Student Achievement in the Chicago Public High Schools," Journal of Labor Economics, University of Chicago Press, vol. 25(1), pages 95-135.
    5. Scott E. Carrell & James E. West, 2010. "Does Professor Quality Matter? Evidence from Random Assignment of Students to Professors," Journal of Political Economy, University of Chicago Press, vol. 118(3), pages 409-432, June.
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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. Sean Corcoran & Dan Goldhaber, 2013. "Value Added and Its Uses: Where You Stand Depends on Where You Sit," Education Finance and Policy, MIT Press, vol. 8(3), pages 418-434, July.
    3. Mike Gilraine & Hugh Macartney & Rob McMillan, 2018. "Education Reform in General Equilibrium: Evidence from California's Class Size Reduction," Working Papers tecipa-594, University of Toronto, Department of Economics.
    4. Michael Gilraine & Hugh Macartney & Robert McMillan, 2018. "Estimating the Direct and Indirect Effects of Major Education Reforms," NBER Working Papers 24191, National Bureau of Economic Research, Inc.
    5. Garritt L. Page & Ernesto San Martín & David Torres Irribarra & Sébastien Van Bellegem, 2024. "Temporally Dynamic, Cohort-Varying Value-Added Models," Psychometrika, Springer;The Psychometric Society, vol. 89(3), pages 1074-1103, September.

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