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Estimating Treatment Effects from Contaminated Multiperiod Education Experiments: The Dynamic Impacts of Class Size Reductions

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  • Weili Ding

    (Queen's University)

  • Steven F Lehrer

    (Queen's University and NBER)

Abstract

This paper introduces an empirical strategy to estimate dynamic treatment effects in randomized trials that provide treatment in multiple stages and in which various noncompliance problems arise, such as attrition and selective transitions between treatment and control groups. Our approach is applied to the highly influential four-year randomized class size study, Project STAR. We find benefits from attending small classes in all cognitive subject areas in kindergarten and first grade. We do not find any statistically significant dynamic benefits from continuous treatment versus never attending small classes following grade 1. Finally, statistical tests support accounting for both selective attrition and noncompliance with treatment assignment. (c) 2010 The President and Fellows of Harvard College and the Massachusetts Institute of Technology.

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Bibliographic Info

Article provided by MIT Press in its journal The Review of Economics and Statistics.

Volume (Year): 92 (2010)
Issue (Month): 1 (06)
Pages: 31-42
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Handle: RePEc:tpr:restat:v:92:y:2010:i:1:p:31-42

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  1. Andrew Chesher, 2003. "Identification in Nonseparable Models," Econometrica, Econometric Society, vol. 71(5), pages 1405-1441, 09.
  2. John Fitzgerald & Peter Gottschalk & Robert Moffitt, 1998. "An Analysis of Sample Attrition in Panel Data: The Michigan Panel Study of income Dynamics," Economics Working Paper Archive 379, The Johns Hopkins University,Department of Economics.
  3. Guido Imbens, 2000. "Efficient Estimation of Average Treatment Effects Using the Estimated Propensity Score," Econometric Society World Congress 2000 Contributed Papers 1166, Econometric Society.
  4. Yau L.H.Y. & Little R.J., 2001. "Inference for the Complier-Average Causal Effect From Longitudinal Data Subject to Noncompliance and Missing Data, With Application to a Job Training Assessment for the Unemployed," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 1232-1244, December.
  5. Horowitz, Joel L & Manski, Charles F, 1995. "Identification and Robustness with Contaminated and Corrupted Data," Econometrica, Econometric Society, vol. 63(2), pages 281-302, March.
  6. Sean Becketti & William Gould & Lee Lillard & Finis Welch, 1985. "The Panel Study of Income Dynamics After Fourteen Years: An Evaluation," UCLA Economics Working Papers 361, UCLA Department of Economics.
  7. J.D. Angrist & Guido W. Imbens & D.B. Rubin, 1993. "Identification of Causal Effects Using Instrumental Variables," NBER Technical Working Papers 0136, National Bureau of Economic Research, Inc.
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Cited by:
  1. Ding, Weili & Lehrer, Steven F., 2011. "Experimental Estimates of the Impacts of Class Size on Test Scores: Robustness and Heterogeneity," CLSRN Working Papers clsrn_admin-2011-12, UBC Department of Economics, revised 26 Jun 2011.
  2. Michael Baker, 2011. "Industrial Actions in Schools: Strikes and Student Achievement," NBER Working Papers 16846, National Bureau of Economic Research, Inc.

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