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.
(This abstract was borrowed from another version of this item.)
If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Volume (Year): 28 (2010)
Issue (Month): 1 ()
|Contact details of provider:|| Web page: http://www.amstat.org/publications/jbes/index.cfm?fuseaction=main |
|Order Information:||Web: http://www.amstat.org/publications/index.html|
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Kaestner, Robert, 1991.
"The Effect of Illicit Drug Use on the Wages of Young Adults,"
Journal of Labor Economics,
University of Chicago Press, vol. 9(4), pages 381-412, October.
- Robert Kaestner, 1990. "The Effect of Illicit Drug Use on the Wages of Young Adults," NBER Working Papers 3535, National Bureau of Economic Research, Inc.
- Horowitz, J.L. & Manski, C.F., 1995.
"Censoring of Outcomes and Regressors Due to Survey Nonresponse: Identification and estimation Using Weights and Imputations,"
95-12, University of Iowa, Department of Economics.
- 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, vol. 84(1), pages 37-58, May.
- Joel L. Horowitz & Charles F. Manski, 1996. "Censoring of Outcomes and Regressors Due To Survey Nonresponse: Identification and Estimation Using Weights and Imputations," Econometrics 9602007, EconWPA, revised 06 Mar 1996.
- Robert Kaestner, 1992.
"The Effect of Illicit Drug Use on the Labor Supply of Young Adults,"
NBER Working Papers
4187, National Bureau of Economic Research, Inc.
- 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.
- 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, vol. 85(2), pages 55-60, May.
- 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.
- Pizer, William & Imbens, Guido, 2000. "The Analysis of Randomized Experiments with Missing Data," Discussion Papers dp-00-19, Resources For the Future.
- 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.
- Charles A. Register & Donald R. Williams, 1992. "Labor Market Effects of Marijuana and Cocaine Use among Young Men," ILR Review, Cornell University, ILR School, vol. 45(3), pages 435-448, April.
- 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.
- Charles F. Manski & John V. Pepper, 2000. "Monotone Instrumental Variables, with an Application to the Returns to Schooling," Econometrica, Econometric Society, vol. 68(4), pages 997-1012, July.
- Charles F. Manski & John V. Pepper, 1998. "Monotone Instrumental Variables: With an Application to the Returns to Schooling," Virginia Economics Online Papers 308, University of Virginia, Department of Economics.
- Mullahy, John & Sindelar, Jody, 1996.
"Employment, unemployment, and problem drinking,"
Journal of Health Economics,
Elsevier, vol. 15(4), pages 409-434, August.
- 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.
- 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.
- Juan Carlos Chavez-Martin del Campo, 2004. "Partial Identification of Poverty Measures with Contaminated Data," Econometric Society 2004 Latin American Meetings 221, Econometric Society.
When requesting a correction, please mention this item's handle: RePEc:bes:jnlbes:v:28:i:1:y:2010:p:82-95. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Christopher F. Baum)
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.