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To Leave or Not to Leave? A Regression Discontinuity Analysis of the Impact of Failing the High School Exit Exam

  • Dongshu Ou

The high school exit exam (HSEE) is rapidly becoming a standardized assessment procedure for educational accountability in the United States. I use a unique state-specific dataset to identify the effect of failing the HSEE on the likelihood that a student drops out early based on a Regression Discontinuity design. It shows that students who barely fail the exam are more likely to exit than those who barely pass despite being offered retest opportunities. The discontinuity amounts to a large proportion of the dropout probability of barely-failers, particularly for minority and low-income students, suggesting that the potential benefit of raising educational standards might come at the cost of increasing inequalities in the educational system.

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Paper provided by Centre for Economic Performance, LSE in its series CEP Discussion Papers with number dp0907.

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Date of creation: Jan 2009
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Handle: RePEc:cep:cepdps:dp0907
Contact details of provider: Web page: http://cep.lse.ac.uk/_new/publications/series.asp?prog=CEP

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  1. Dongshu Ou, 2009. "To Leave or Not to Leave? A Regression Discontinuity Analysis of the Impact of Failing High School Exit Exam," CEE Discussion Papers 0107, Centre for the Economics of Education, LSE.
  2. Imbens, Guido W. & Lemieux, Thomas, 2008. "Regression discontinuity designs: A guide to practice," Journal of Econometrics, Elsevier, vol. 142(2), pages 615-635, February.
  3. Julie Berry Cullen & Randall Reback, 2006. "Tinkering Toward Accolades: School Gaming Under a Performance Accountability System," NBER Working Papers 12286, National Bureau of Economic Research, Inc.
  4. 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.
  5. Wilbert van der Klaauw, 2008. "Regression-Discontinuity Analysis: A Survey of Recent Developments in Economics," LABOUR, CEIS, vol. 22(2), pages 219-245, 06.
  6. 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.
  7. Milligan, Kevin & Lemieux, Thomas, 2006. "Incentive Effects of Social Assistance: A Regression Discontinuity Approach," Analytical Studies Branch Research Paper Series 2006280e, Statistics Canada, Analytical Studies Branch.
  8. John P. Papay & Richard J. Murnane & John B. Willett, 2008. "The Consequences of High School Exit Examinations for Struggling Low-Income Urban Students: Evidence from Massachusetts," NBER Working Papers 14186, National Bureau of Economic Research, Inc.
  9. Lee, David S. & Card, David, 2008. "Regression discontinuity inference with specification error," Journal of Econometrics, Elsevier, vol. 142(2), pages 655-674, February.
  10. Thomas J. Kane, 2003. "A Quasi-Experimental Estimate of the Impact of Financial Aid on College-Going," NBER Working Papers 9703, National Bureau of Economic Research, Inc.
  11. Wilbert van der Klaauw, 2002. "Estimating the Effect of Financial Aid Offers on College Enrollment: A Regression-Discontinuity Approach," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 43(4), pages 1249-1287, November.
  12. 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.
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