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Missing Treatments

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  • Molinari, Francesca

    (Cornell U)

Abstract

The existing literature on treatment e¤ects assumes perfect observability of the treatments received by the population of interest. Even in cases of imperfect compliance, it is usually as- sumed that both the assigned and administered treatment are observed (or missing completely at random). This paper abandons such assumptions. Imperfect observability of the received treatment can arise as a result of survey nonresponse in observational studies, or noncompliance with randomly assigned treatments that are not directly monitored. I study the problem in the context of observational studies. I derive sharp worst case bounds without assuming anything about treatment selection, and I show that the bounds are a function of the available prior information on the distribution of the missing treatments. Under the maintained assumption of monotone treatment response, I show that no prior information on the distribution of missing treatments is necessary to get sharp informative bounds. I apply the methodologies recently proposed by Imbens and Manski (2004) and Chernozhukov, Hong, and Tamer (2004) to derive two types of confidence intervals for the partially identi.ed parameters. The results are illustrated with an empirical analysis of drug use and employment using data from the National Longitudinal Survey of Youth.

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Bibliographic Info

Paper provided by Cornell University, Center for Analytic Economics in its series Working Papers with number 05-11.

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Date of creation: May 2005
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Handle: RePEc:ecl:corcae:05-11

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  1. Charles A. Register & Donald R. Williams, 1992. "Labor market effects of marijuana and cocaine use among young men," Industrial and Labor Relations Review, ILR Review, Cornell University, ILR School, vol. 45(3), pages 435-451, April.
  2. John Mullahy & Jody L. Sindelar, 1995. "Employment, Unemployment, and Problem Drinking," NBER Working Papers 5123, National Bureau of Economic Research, Inc.
  3. Charles F. Manski & John V. Pepper, 1998. "Monotone Instrumental Variables with an Application to the Returns to Schooling," NBER Technical Working Papers 0224, National Bureau of Economic Research, Inc.
  4. Kaestner, Robert, 1991. "The Effect of Illicit Drug Use on the Wages of Young Adults," Journal of Labor Economics, University of Chicago Press, University of Chicago Press, vol. 9(4), pages 381-412, October.
  5. Robert Kaestner, 1994. "The Effect of Illicit Drug Use on the Labor Supply of Young Adults," Journal of Human Resources, University of Wisconsin Press, vol. 29(1), pages 126-155.
  6. Juan Carlos Chavez-Martin del Campo, 2004. "Partial Identification of Poverty Measures with Contaminated Data," Econometric Society 2004 Latin American Meetings, Econometric Society 221, Econometric Society.
  7. Horowitz, Joel L. & Manski, Charles F., 1998. "Censoring of outcomes and regressors due to survey nonresponse: Identification and estimation using weights and imputations," Journal of Econometrics, Elsevier, Elsevier, vol. 84(1), pages 37-58, May.
  8. Pizer, William & Imbens, Guido, 2000. "The Analysis of Randomized Experiments with Missing Data," Discussion Papers, Resources For the Future dp-00-19, Resources For the Future.
  9. E. Tamer & V. Chernozhukov & H. Hong, 2004. "Parameter Set Inference in a Class of Econometric Models," Econometric Society 2004 North American Winter Meetings 382, Econometric Society.
  10. Horowitz, Joel L & Manski, Charles F, 1995. "Identification and Robustness with Contaminated and Corrupted Data," Econometrica, Econometric Society, Econometric Society, vol. 63(2), pages 281-302, March.
  11. Andrew M. Gill & Robert J. Michaels, 1992. "Does drug use lower wages?," Industrial and Labor Relations Review, ILR Review, Cornell University, ILR School, vol. 45(3), pages 419-434, April.
  12. Kaestner, Robert & Grossman, Michael, 1995. "Wages, Workers' Compensation Benefits, and Drug Use: Indirect Evidence of the Effect of Drugs on Workplace Accidents," American Economic Review, American Economic Association, American Economic Association, vol. 85(2), pages 55-60, May.
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Cited by:
  1. Campo, Juan Carlos Chavez-Martin del, 2006. "Does Conditionality Generate Heterogeneity and Regressivity in Program Impacts? The Progresa Experience," Working Papers, Cornell University, Department of Applied Economics and Management 127042, Cornell University, Department of Applied Economics and Management.
  2. Arthur Lewbel, 2003. "Estimation of Average Treatment Effects With Misclassification," Boston College Working Papers in Economics, Boston College Department of Economics 556, Boston College Department of Economics, revised 04 Sep 2006.
  3. Gundersen, Craig & Kreider, Brent, 2009. "Bounding the effects of food insecurity on children's health outcomes," Journal of Health Economics, Elsevier, Elsevier, vol. 28(5), pages 971-983, September.
  4. Adam Rosen, 2006. "Confidence sets for partially identified parameters that satisfy a finite number of moment inequalities," CeMMAP working papers, Centre for Microdata Methods and Practice, Institute for Fiscal Studies CWP25/06, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  5. Gundersen, Craig & Kreider, Brent & Pepper, John, 2012. "The impact of the National School Lunch Program on child health: A nonparametric bounds analysis," Journal of Econometrics, Elsevier, Elsevier, vol. 166(1), pages 79-91.
  6. Kreider, Brent & Pepper, John V. & Gundersen, Craig & Jolliffe, Dean, 2012. "Identifying the Effects of SNAP (Food Stamps) on Child Health Outcomes When Participation is Endogenous and Misreported," Staff General Research Papers 13124, Iowa State University, Department of Economics.
  7. Hoshino, Tadao, 2013. "Partial identification in binary response models with nonignorable nonresponses," Economics Letters, Elsevier, Elsevier, vol. 121(1), pages 74-78.
  8. Bollinger, Christopher R. & Hirsch, Barry, 2005. "Match Bias from Earnings Imputation in the Current Population Survey: The Case of Imperfect Matching," IZA Discussion Papers 1846, Institute for the Study of Labor (IZA).
  9. Brent Kreider & Steven C. Hill, 2009. "Partially Identifying Treatment Effects with an Application to Covering the Uninsured," Journal of Human Resources, University of Wisconsin Press, vol. 44(2).
  10. Robert P. Sherman & Jeff Dominitz, 2006. "Identification and estimation of bounds on school performance measures: a nonparametric analysis of a mixture model with verification," Journal of Applied Econometrics, John Wiley & Sons, Ltd., John Wiley & Sons, Ltd., vol. 21(8), pages 1295-1326.

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