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

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  • Kenneth Y. Chay
  • Patrick J. McEwan
  • Miguel Urquiola

Abstract

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 a 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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Bibliographic Info

Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 10118.

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Date of creation: Nov 2003
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Publication status: published as Chay, Kenneth Y., Patrick J. McEwan and Miguel Urquiola. "The Central Role Of Noise In Evaluating Interventions That Use Test Score To Rank Schools," American Economic Review, 2005, v95(4,Sep), 1237-1258.
Handle: RePEc:nbr:nberwo:10118

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  1. Thomas J. Kane & Douglas O. Staiger, 2002. "The Promise and Pitfalls of Using Imprecise School Accountability Measures," Journal of Economic Perspectives, American Economic Association, American Economic Association, vol. 16(4), pages 91-114, Fall.
  2. 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.
  3. Thomas J. Kane & Douglas O. Staiger, 2001. "Improving School Accountability Measures," NBER Working Papers 8156, National Bureau of Economic Research, Inc.
  4. Paul Glewwe & Nauman Ilias & Michael Kremer, 2010. "Teacher Incentives," American Economic Journal: Applied Economics, American Economic Association, vol. 2(3), pages 205-27, July.
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  6. Joshua Angrist & Alan Krueger, 1998. "Empirical Strategies in Labor Economics," Working papers 98-7, Massachusetts Institute of Technology (MIT), Department of Economics.
  7. 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, Columbia University, Department of Economics 0304-10, Columbia University, Department of Economics.
  8. 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.
  9. 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, MIT Press, vol. 115(2), pages 431-468, May.
  10. 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.
  11. Brian A. Jacob & Lars Lefgren, 2004. "The Impact of Teacher Training on Student Achievement: Quasi-Experimental Evidence from School Reform Efforts in Chicago," Journal of Human Resources, University of Wisconsin Press, vol. 39(1).
  12. Eric A. Hanushek & Margaret E. Raymond, 2002. "Improving educational quality: how best to evaluate our schools," Conference Series ; [Proceedings], Federal Reserve Bank of Boston, Federal Reserve Bank of Boston, vol. 47(Jun), pages 193-247.
  13. 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.
  14. 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, MIT Press, vol. 114(2), pages 533-575, May.
  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. Victor Lavy, 2002. "Evaluating the Effect of Teachers' Group Performance Incentives on Pupil Achievement," Journal of Political Economy, University of Chicago Press, University of Chicago Press, vol. 110(6), pages 1286-1317, December.
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