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Estimating Treatment Effects from Contaminated Multi-Period Education Experiments: The Dynamic Impacts of Class Size Reductions

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  • Weili Ding
  • Steven F. Lehrer

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 class in all cognitive subject areas in kindergarten and the first grade. We do not find any statistically significant dynamic benefits from continuous treatment versus never attending small classes following grade one. Finally, statistical tests support accounting for both selective attrition and noncompliance with treatment assignment.

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Bibliographic Info

Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 15200.

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Date of creation: Aug 2009
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Publication status: published as Weili Ding & Steven F Lehrer, 2010. "Estimating Treatment Effects from Contaminated Multiperiod Education Experiments: The Dynamic Impacts of Class Size Reductions," The Review of Economics and Statistics, MIT Press, vol. 92(1), pages 31-42, 06.
Handle: RePEc:nbr:nberwo:15200

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  1. Lechner, Michael, 2004. "Sequential Matching Estimation of Dynamic Causal Models," IZA Discussion Papers 1042, Institute for the Study of Labor (IZA).
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  4. 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.
  5. James Heckman & Neil Hohmann & Jeffrey Smith & Michael Khoo, 2000. "Substitution And Dropout Bias In Social Experiments: A Study Of An Influential Social Experiment," The Quarterly Journal of Economics, MIT Press, vol. 115(2), pages 651-694, May.
  6. 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.
  7. Keisuke Hirano & Guido W. Imbens & Geert Ridder, 2000. "Efficient Estimation of Average Treatment Effects Using the Estimated Propensity Score," NBER Technical Working Papers 0251, National Bureau of Economic Research, Inc.
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  12. Alan B. Krueger, 1999. "Experimental Estimates Of Education Production Functions," The Quarterly Journal of Economics, MIT Press, vol. 114(2), pages 497-532, May.
  13. Steven Lehrer & Weili Ding, 2004. "Estimating Dynamic Treatment Effects from Project STAR," Econometric Society 2004 North American Summer Meetings 252, Econometric Society.
  14. Ruth Miquel, 2002. "Identification of Dynamic Treatment Effects by Instrumental Variables," University of St. Gallen Department of Economics working paper series 2002 2002-11, Department of Economics, University of St. Gallen.
  15. Newey, Whitney K., 1984. "A method of moments interpretation of sequential estimators," Economics Letters, Elsevier, vol. 14(2-3), pages 201-206.
  16. Michael Lechner & Ruth Miquel, 2005. "Identification of the Effects of Dynamic Treatments by Sequential Conditional Independence Assumptions," University of St. Gallen Department of Economics working paper series 2005 2005-17, Department of Economics, University of St. Gallen.
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  18. Yoram Ben-Porath, 1967. "The Production of Human Capital and the Life Cycle of Earnings," Journal of Political Economy, University of Chicago Press, vol. 75, pages 352.
  19. 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.
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Citations

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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," CLSSRN working papers clsrn_admin-2011-12, Vancouver School of Economics, revised 26 Jun 2011.
  2. Frölich, Markus & Huber, Martin, 2014. "Treatment evaluation with multiple outcome periods under endogeneity and attrition," Economics Working Paper Series 1404, University of St. Gallen, School of Economics and Political Science.
  3. Shu Wen Ng & Edward C. Norton & David K. Guilkey & Barry M. Popkin, 2010. "Estimation of a Dynamic Model of Weight," NBER Working Papers 15864, National Bureau of Economic Research, Inc.
  4. Khan, Adnan Q. & Lehrer, Steven F., 2013. "The Impact of Social Networks on Labour Market Outcomes: New Evidence from Cape Breton," CLSSRN working papers clsrn_admin-2013-7, Vancouver School of Economics, revised 25 Feb 2013.
  5. Ding, Weili & Lehrer, Steven F., 2014. "Understanding the role of time-varying unobserved ability heterogeneity in education production," Economics of Education Review, Elsevier, vol. 40(C), pages 55-75.
  6. Michael Baker, 2013. "Industrial actions in schools: strikes and student achievement," Canadian Journal of Economics, Canadian Economics Association, vol. 46(3), pages 1014-1036, August.
  7. Frölich, Markus & Huber, Martin, 2014. "Treatment Evaluation with Multiple Outcome Periods under Endogeneity and Attrition," IZA Discussion Papers 7972, Institute for the Study of Labor (IZA).

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