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Teacher Complementarities in Test Score Production: Evidence from Primary School

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  • Josh Kinsler

Abstract

The existence of teacher complementarities across grades can have important implications for the efficient assignment of students to teachers and for the evaluation of teachers using standard value-added models (VAMs). In this paper, I extend the basic VAM to allow for interactive effects between teachers. Using data from North Carolina's primary schools, I find that teacher complementarities within schools are extremely small. This finding suggests that there is little to gain by assigning students to particular teacher sequences. Moreover, measures of teacher effectiveness generated from a typical VAM are not likely to be biased by interactions with past teacher inputs.

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  • Josh Kinsler, 2016. "Teacher Complementarities in Test Score Production: Evidence from Primary School," Journal of Labor Economics, University of Chicago Press, vol. 34(1), pages 29-61.
    • Handle: RePEc:ucp:jlabec:doi:10.1086/682331
    DOI: 10.1086/682331
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    1. Steven G. Rivkin & Eric A. Hanushek & John F. Kain, 2005. "Teachers, Schools, and Academic Achievement," Econometrica, Econometric Society, vol. 73(2), pages 417-458, March.
    2. C. Kirabo Jackson, 2013. "Match Quality, Worker Productivity, and Worker Mobility: Direct Evidence from Teachers," The Review of Economics and Statistics, MIT Press, vol. 95(4), pages 1096-1116, October.
    3. Daniel F. McCaffrey & Tim R. Sass & J. R. Lockwood & Kata Mihaly, 2009. "The Intertemporal Variability of Teacher Effect Estimates," Education Finance and Policy, MIT Press, vol. 4(4), pages 572-606, October.
    4. Sass, Tim R. & Semykina, Anastasia & Harris, Douglas N., 2014. "Value-added models and the measurement of teacher productivity," Economics of Education Review, Elsevier, vol. 38(C), pages 9-23.
    5. 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.
    6. Peter Arcidiacono & Gigi Foster & Natalie Goodpaster & Josh Kinsler, 2012. "Estimating spillovers using panel data, with an application to the classroom," Quantitative Economics, Econometric Society, vol. 3(3), pages 421-470, November.
    7. Josh Kinsler, 2012. "Assessing Rothstein's critique of teacher value‐added models," Quantitative Economics, Econometric Society, vol. 3(2), pages 333-362, July.
    8. Dale Ballou & William Sanders & Paul Wright, 2004. "Controlling for Student Background in Value-Added Assessment of Teachers," Journal of Educational and Behavioral Statistics, , vol. 29(1), pages 37-65, March.
    9. Cory Koedel & Julian R. Betts, 2011. "Does Student Sorting Invalidate Value-Added Models of Teacher Effectiveness? An Extended Analysis of the Rothstein Critique," Education Finance and Policy, MIT Press, vol. 6(1), pages 18-42, January.
    10. Thomas S. Dee, 2004. "Teachers, Race, and Student Achievement in a Randomized Experiment," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 195-210, February.
    11. J. R. Lockwood & Daniel F. McCaffrey & Louis T. Mariano & Claude Setodji, 2007. "Bayesian Methods for Scalable Multivariate Value-Added Assessment," Journal of Educational and Behavioral Statistics, , vol. 32(2), pages 125-150, June.
    12. Raj Chetty & John N. Friedman & Jonah E. Rockoff, 2014. "Measuring the Impacts of Teachers II: Teacher Value-Added and Student Outcomes in Adulthood," American Economic Review, American Economic Association, vol. 104(9), pages 2633-2679, September.
    13. Jesse Rothstein, 2010. "Teacher Quality in Educational Production: Tracking, Decay, and Student Achievement," The Quarterly Journal of Economics, Oxford University Press, vol. 125(1), pages 175-214.
    14. J. R. Lockwood & Daniel F. McCaffrey, 2009. "Exploring Student-Teacher Interactions in Longitudinal Achievement Data," Education Finance and Policy, MIT Press, vol. 4(4), pages 439-467, October.
    15. Petra E. Todd & Kenneth I. Wolpin, 2003. "On The Specification and Estimation of The Production Function for Cognitive Achievement," Economic Journal, Royal Economic Society, vol. 113(485), pages 3-33, February.
    16. Jonah E. Rockoff, 2004. "The Impact of Individual Teachers on Student Achievement: Evidence from Panel Data," American Economic Review, American Economic Association, vol. 94(2), pages 247-252, May.
    17. Daniel F. McCaffrey & J. R. Lockwood & Daniel Koretz & Thomas A. Louis & Laura Hamilton, 2004. "Models for Value-Added Modeling of Teacher Effects," Journal of Educational and Behavioral Statistics, , vol. 29(1), pages 67-101, March.
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