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Using School Choice Lotteries to Test Measures of School Effectiveness

  • David J. Deming

Value-added models (VAMs) are increasingly used to measure school effectiveness. Yet random variation in school attendance is necessary to test the validity of VAMs, and to guide the selection of models for measuring causal effects of schools. In this paper, I use random assignment from a public school choice lottery to test the predictive power of VAM specifications. In VAMs with minimal controls and two or more years of prior data, I fail to reject the hypothesis that school effects are unbiased. Overall, many commonly used VAMs are accurate predictors of student achievement gains.

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File URL: http://www.nber.org/papers/w19803.pdf
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Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 19803.

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Date of creation: Jan 2014
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Publication status: published as David J. Deming, 2014. "Using School Choice Lotteries to Test Measures of School Effectiveness," American Economic Review, American Economic Association, vol. 104(5), pages 406-11, May.
Handle: RePEc:nbr:nberwo:19803
Note: CH ED LS
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  1. Jesse Rothstein, 2008. "Teacher Quality in Educational Production: Tracking, Decay, and Student Achievement," NBER Working Papers 14442, National Bureau of Economic Research, Inc.
  2. 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, Oxford University Press, vol. 126(2), pages 699-748.
  3. David J. Deming & Sarah Cohodes & Jennifer Jennings & Christopher Jencks, 2013. "School Accountability, Postsecondary Attainment and Earnings," NBER Working Papers 19444, National Bureau of Economic Research, Inc.
  4. David J. Deming, 2011. "Better Schools, Less Crime?," The Quarterly Journal of Economics, Oxford University Press, vol. 126(4), pages 2063-2115.
  5. LaLonde, Robert J, 1986. "Evaluating the Econometric Evaluations of Training Programs with Experimental Data," American Economic Review, American Economic Association, vol. 76(4), pages 604-20, September.
  6. 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 F3-F33, February.
  7. C. Kirabo Jackson, 2012. "Non-Cognitive Ability, Test Scores, and Teacher Quality: Evidence from 9th Grade Teachers in North Carolina," NBER Working Papers 18624, National Bureau of Economic Research, Inc.
  8. Raj Chetty & John N. Friedman & Jonah E. Rockoff, 2013. "Measuring the Impacts of Teachers I: Evaluating Bias in Teacher Value-Added Estimates," NBER Working Papers 19423, National Bureau of Economic Research, Inc.
  9. 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, American Educational Research Association, vol. 29(1), pages 67-101, March.
  10. Donald B. Rubin & Elizabeth A. Stuart & Elaine L. Zanutto, 2004. "A Potential Outcomes View of Value-Added Assessment in Education," Journal of Educational and Behavioral Statistics, American Educational Research Association, vol. 29(1), pages 103-116, March.
  11. 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.
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