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The Central Role of Noise in Evaluating Interventions that Use Test Scores to Rank Schools

  • Kenneth Chay

    ()

    (University of California, Berkeley - Department of Economics)

  • Patrick J. McEwan

    ()

    (Wellesley College, Department of Economics)

  • Miguel Urquiola

    ()

    (Columbia University - Department of Economics)

Several countries have implemented programs that use test scores to rank schools, and to reward or penalize them based on their students' average performance. Recently, Kane and Staiger (2002) have warned that imprecision in the measurement of school-level test scores could impede these efforts. There is little evidence, however, on how seriously noise hinders the evaluation of the impact of these interventions. We examine these issues in the context of Chile's P-900 program country-wide intervention in which resources were allocated based on cutoffs in schools' mean test scores. We show that transitory noise in average scores and mean reversion lead conventional estimation approaches to greatly overstate the impacts of such programs. We then show how a regression discontinuity design that utilizes the discrete nature of the selection rule can be used to control for reversion biases. While the RD analysis provides convincing evidence that the P-900 program had significant effects on test score gains, these effects are much smaller than is widely believed.

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File URL: http://www.econ.columbia.edu/RePEc/pdf/DP0304-10.pdf
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Paper provided by Columbia University, Department of Economics in its series Discussion Papers with number 0304-10.

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Length: 34 pages
Date of creation: 2003
Date of revision:
Handle: RePEc:clu:wpaper:0304-10
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  1. Ashenfelter, Orley C, 1978. "Estimating the Effect of Training Programs on Earnings," The Review of Economics and Statistics, MIT Press, vol. 60(1), pages 47-57, February.
  2. Chang-Tai Hsieh & Miguel Urquiola, 2003. "When Schools Compete, How Do They Compete? An Assessment of Chile's Nationwide School Voucher Program," NBER Working Papers 10008, National Bureau of Economic Research, Inc.
  3. Joshua Angrist & Alan Krueger, 1998. "Empirical Strategies in Labor Economics," Working Papers 780, Princeton University, Department of Economics, Industrial Relations Section..
  4. Orley Ashenfelter & David Card, 1984. "Using the Longitudinal Structure of Earnings to Estimate the Effect of Training Programs," Working Papers 554, Princeton University, Department of Economics, Industrial Relations Section..
  5. Michael Kremer & Nauman Ilias & Paul Glewwe, 2003. "Teacher incentives," Natural Field Experiments 00257, The Field Experiments Website.
  6. Kenneth Chay & Patrick J. McEwan & Miguel Urquiola, 2003. "The Central Role of Noise in Evaluating Interventions that Use Test Scores to Rank Schools," Discussion Papers 0304-10, Columbia University, Department of Economics.
  7. 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.
  8. John H. Tyler & Richard J. Murnane & John B. Willett, 2000. "Estimating The Labor Market Signaling Value Of The GED," The Quarterly Journal of Economics, MIT Press, vol. 115(2), pages 431-468, May.
  9. Brian A. Jacob & Lars Lefgren, 2004. "Remedial Education and Student Achievement: A Regression-Discontinuity Analysis," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 226-244, February.
  10. Brian A. Jacob & Lars Lefgren, 2002. "The Impact of Teacher Training on Student Achievement: Quasi-Experimental Evidence from School Reform Efforts in Chicago," NBER Working Papers 8916, National Bureau of Economic Research, Inc.
  11. Eric A. Hanushek & Margaret E. Raymond, 2002. "Improving educational quality: how best to evaluate our schools," Conference Series ; [Proceedings], Federal Reserve Bank of Boston, vol. 47(Jun), pages 193-247.
  12. Victor Lavy, 2002. "Evaluating the Effect of Teachers' Group Performance Incentives on Pupil Achievement," Journal of Political Economy, University of Chicago Press, vol. 110(6), pages 1286-1317, December.
  13. Joshua D. Angrist & Victor Lavy, 1999. "Using Maimonides' Rule To Estimate The Effect Of Class Size On Scholastic Achievement," The Quarterly Journal of Economics, MIT Press, vol. 114(2), pages 533-575, May.
  14. Urquiola, Miguel, 2001. "Identifying class size effects in developing countries : evidence from rural schools in Bolivia," Policy Research Working Paper Series 2711, The World Bank.
  15. Jonathan Guryan, 2001. "Does Money Matter? Regression-Discontinuity Estimates from Education Finance Reform in Massachusetts," NBER Working Papers 8269, National Bureau of Economic Research, Inc.
  16. Thomas J. Kane & Douglas O. Staiger, 2001. "Improving School Accountability Measures," NBER Working Papers 8156, National Bureau of Economic Research, Inc.
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