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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

Many programs reward or penalize schools based on students' average performance. Mean reversion is a potentially serious hindrance to the evaluation of such interventions. Chile's 900 Schools Program (P-900) allocated resources based on cutoffs in schools' mean test scores. This paper shows that transitory noise in average scores and mean reversion lead conventional estimation approaches to overstate the impacts of such programs. It further shows how a regression-discontinuity design can be used to control for reversion biases. It concludes that P-900 had significant effects on test score gains, albeit much smaller than is widely believed.

Suggested Citation

  • Kenneth Y. Chay & Patrick J. McEwan & Miguel Urquiola, 2005. "The Central Role of Noise in Evaluating Interventions That Use Test Scores to Rank Schools," American Economic Review, American Economic Association, vol. 95(4), pages 1237-1258, September.
  • Handle: RePEc:aea:aecrev:v:95:y:2005:i:4:p:1237-1258
    Note: DOI: 10.1257/0002828054825529
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    1. Ashenfelter, Orley & Card, David, 1985. "Using the Longitudinal Structure of Earnings to Estimate the Effect of Training Programs," The Review of Economics and Statistics, MIT Press, vol. 67(4), pages 648-660, November.
    2. John H. Tyler & Richard J. Murnane & John B. Willett, 2000. "Estimating the Labor Market Signaling Value of the GED," The Quarterly Journal of Economics, Oxford University Press, vol. 115(2), pages 431-468.
    3. Angrist, Joshua D. & Krueger, Alan B., 1999. "Empirical strategies in labor economics," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 3, chapter 23, pages 1277-1366, Elsevier.
    4. 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.
    5. Chang-Tai Hsieh & Miguel Urquiola, 2002. "When Schools Compete, How Do They Compete? An Assessment of Chile's Nationwide School Voucher Program," Working Papers 123, Princeton University, Department of Economics, Center for Economic Policy Studies..
    6. 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.
    7. 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.
    8. 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.
    9. Paul Glewwe & Nauman Ilias & Michael Kremer, 2010. "Teacher Incentives," American Economic Journal: Applied Economics, American Economic Association, vol. 2(3), pages 205-227, July.
    10. 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.
    11. Kenneth Y. Chay & Patrick J. McEwan & Miguel Urquiola, 2005. "The Central Role of Noise in Evaluating Interventions That Use Test Scores to Rank Schools," American Economic Review, American Economic Association, vol. 95(4), pages 1237-1258, September.
    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. 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.
    14. 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).
    15. Thomas J. Kane & Douglas O. Staiger, 2001. "Improving School Accountability Measures," NBER Working Papers 8156, National Bureau of Economic Research, Inc.
    16. Joshua D. Angrist & Victor Lavy, 1999. "Using Maimonides' Rule to Estimate the Effect of Class Size on Scholastic Achievement," The Quarterly Journal of Economics, Oxford University Press, vol. 114(2), pages 533-575.
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    • I2 - Health, Education, and Welfare - - Education

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