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Teacher Quality at the High-School Level: The Importance of Accounting for Tracks

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  • C. Kirabo Jackson

Abstract

Unlike in elementary school, high-school teacher effects may be confounded with both selection to tracks and unobserved track-level treatments. I document sizable confounding track effects, and show that traditional tests for the existence of teacher effects are likely biased. After accounting for these biases, high-school algebra and English teachers have much smaller test-score effects than found in previous studies. Moreover, unlike in elementary school, value-added estimates are weak predictors of teachers’ future performance. Results indicate that either (a) teachers are less influential in high school than in elementary school, or (b) test scores are a poor metric to measure teacher quality at the high-school level.

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Bibliographic Info

Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 17722.

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Date of creation: Jan 2012
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Publication status: published as "Teacher Quality at the High-School Level: The Importance of Accounting for Tracks" forthcoming Journal of Labor Economics. (available as NBER Working Paper 17722)
Handle: RePEc:nbr:nberwo:17722

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  1. C. Kirabo Jackson, 2011. "School Competition and Teacher Labor Markets: Evidence from Charter School Entry in North Carolina," NBER Working Papers 17225, National Bureau of Economic Research, Inc.
  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. 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.
  4. Jesse Rothstein, 2010. "Teacher Quality in Educational Production: Tracking, Decay, and Student Achievement," The Quarterly Journal of Economics, MIT Press, vol. 125(1), pages 175-214, February.
  5. Brian A. Jacob & Lars Lefgren, 2008. "Can Principals Identify Effective Teachers? Evidence on Subjective Performance Evaluation in Education," Journal of Labor Economics, University of Chicago Press, vol. 26, pages 101-136.
  6. Koedel, Cory, 2008. "Teacher quality and dropout outcomes in a large, urban school district," Journal of Urban Economics, Elsevier, vol. 64(3), pages 560-572, November.
  7. 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.
  8. 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.
  9. Cory Koedel, 2008. "An Empirical Analysis of Teacher Spillover Effects in Secondary School," Working Papers 0808, Department of Economics, University of Missouri.
  10. C. Kirabo Jackson & Elias Bruegmann, 2009. "Teaching Students and Teaching Each Other: The Importance of Peer Learning for Teachers," NBER Working Papers 15202, National Bureau of Economic Research, Inc.
  11. Charles T. Clotfelter & Helen F. Ladd & Jacob L. Vigdor, 2007. "Teacher Credentials and Student Achievement in High School: A Cross-Subject Analysis with Student Fixed Effects," NBER Working Papers 13617, National Bureau of Economic Research, Inc.
  12. Daniel Aaronson & Lisa Barrow & William Sander, 2002. "Teachers and student achievement in the Chicago public high schools," Working Paper Series WP-02-28, Federal Reserve Bank of Chicago.
  13. Raj Chetty & John N. Friedman & Jonah E. Rockoff, 2011. "The Long-Term Impacts of Teachers: Teacher Value-Added and Student Outcomes in Adulthood," NBER Working Papers 17699, National Bureau of Economic Research, Inc.
  14. C. Kirabo Jackson, 2009. "Student Demographics, Teacher Sorting, and Teacher Quality: Evidence from the End of School Desegregation," Journal of Labor Economics, University of Chicago Press, vol. 27(2), pages 213-256, 04.
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Cited by:
  1. Eric Isenberg & Bing-ru Teh & Elias Walsh, 2013. "Elementary School Data Issues: Implications for Research Using Value-Added Models," Mathematica Policy Research Reports 7948, Mathematica Policy Research.
  2. Ali Protik & Elias Walsh & Alexandra Resch & Eric Isenberg & Emma Kopa, 2013. "Does Tracking of Students Bias Value-Added Estimates for Teachers?," Mathematica Policy Research Reports 7727, Mathematica Policy Research.
  3. Stephen B. Billings & David J. Deming & Jonah E. Rockoff, 2012. "School Segregation, Educational Attainment and Crime: Evidence from the end of busing in Charlotte-Mecklenburg," NBER Working Papers 18487, National Bureau of Economic Research, Inc.
  4. Brian Gill & Julie Bruch & Kevin Booker, 2013. "Using Alternative Student Growth Measures for Evaluating Teacher Performance: What the Literature Says," Mathematica Policy Research Reports 7896, Mathematica Policy Research.

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