Misclassification In Binary Choice Models
We derive the asymptotic bias from misclassification of the dependent variable in binary choice models. Measurement error is necessarily non-classical in this case, which leads to bias in linear and non-linear models even if only the dependent variable is mismeasured. A Monte Carlo study and an application to food stamp receipt show that the bias formulas are useful to analyze the sensitivity of substantive conclusions, to interpret biased coefficients and imply features of the estimates that are robust to misclassification. Using administrative records linked to survey data as validation data, we examine estimators that are consistent under misclassification. They can improve estimates if their assumptions hold, but can aggravate the problem if the assumptions are invalid. The estimators differ in their robustness to such violations, which can be improved by incorporating additional information. We propose tests for the presence and nature of misclassification that can help to choose an estimator.
|Date of creation:||May 2013|
|Date of revision:|
|Contact details of provider:|| Postal: 4600 Silver Hill Road, Washington, DC 20233|
Phone: (301) 763-6460
Fax: (301) 763-5935
Web page: http://www.census.gov/ces
More information through EDIRC
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.:
- Steven D. Levitt, 1998.
"Juvenile Crime and Punishment,"
Journal of Political Economy,
University of Chicago Press, vol. 106(6), pages 1156-1185, December.
- Horowitz, Joel L, 1992. "A Smoothed Maximum Score Estimator for the Binary Response Model," Econometrica, Econometric Society, vol. 60(3), pages 505-31, May.
- Imbens, G.W. & Lancaster, T., 1993.
"Case-Control Studies with Contaminated Controls,"
1993-7, Tilburg University, Center for Economic Research.
- Imbens, G. & Lancaster, T., 1992. "Case-Control Studies with Contaminated Controls," Harvard Institute of Economic Research Working Papers 1612, Harvard - Institute of Economic Research.
- Imbens, G. & Lancaster, T., 1993. "Case-Control Studies with Contaminated Controls," Papers 9307, Tilburg - Center for Economic Research.
- Bruce D. Meyer & Wallace K. C. Mok & James X. Sullivan, 2009.
"The Under-Reporting of Transfers in Household Surveys: Its Nature and Consequences,"
NBER Working Papers
15181, National Bureau of Economic Research, Inc.
- Bruce D. Meyer & Wallace K. C. Mok & James X. Sullivan, 2009. "The Under-Reporting of Transfers in Household Surveys: Its Nature and Consequences," Working Papers 0903, Harris School of Public Policy Studies, University of Chicago.
- Guido W. Imbens & Tony Lancaster, 1994.
"Combining Micro and Macro Data in Microeconometric Models,"
Review of Economic Studies,
Oxford University Press, vol. 61(4), pages 655-680.
- Imbens, G.W. & Lancaster, T., 1991. "Combining Micro and Macro Data in Microeconometric Models," Harvard Institute of Economic Research Working Papers 1578, Harvard - Institute of Economic Research.
- Hausman, J. A. & Abrevaya, Jason & Scott-Morton, F. M., 1998. "Misclassification of the dependent variable in a discrete-response setting," Journal of Econometrics, Elsevier, vol. 87(2), pages 239-269, September.
- Black, Dan & Sanders, Seth & Taylor, Lowell, 2003. "Measurement of Higher Education in the Census and Current Population Survey," Journal of the American Statistical Association, American Statistical Association, vol. 98, pages 545-554, January.
- Bollinger, Christopher R & David, Martin H, 2001.
"Estimation with Response Error and Nonresponse: Food-Stamp Participation in the SIPP,"
Journal of Business & Economic Statistics,
American Statistical Association, vol. 19(2), pages 129-41, April.
- Christopher Bollinger & Martin H. David, 2000. "Estimation with Response Error and Non-Response: Food Stamp Participation in the SIPP," Econometric Society World Congress 2000 Contributed Papers 0198, Econometric Society.
- Hausman, J.A. & Morton, F.M.S., 1994. "Misclassification of Dependent Variable in a Discrete Response Setting," Working papers 94-19, Massachusetts Institute of Technology (MIT), Department of Economics.
- Han, Aaron K., 1987. "Non-parametric analysis of a generalized regression model : The maximum rank correlation estimator," Journal of Econometrics, Elsevier, vol. 35(2-3), pages 303-316, July.
- Bollinger, Christopher R., 1996. "Bounding mean regressions when a binary regressor is mismeasured," Journal of Econometrics, Elsevier, vol. 73(2), pages 387-399, August.
- Ruud, Paul A., 1986. "Consistent estimation of limited dependent variable models despite misspecification of distribution," Journal of Econometrics, Elsevier, vol. 32(1), pages 157-187, June.
- Zvi Eckstein & Kenneth I. Wolpin, 1999. "Why Youths Drop Out of High School: The Impact of Preferences, Opportunities, and Abilities," Econometrica, Econometric Society, vol. 67(6), pages 1295-1340, November.
- Aigner, Dennis J., 1973. "Regression with a binary independent variable subject to errors of observation," Journal of Econometrics, Elsevier, vol. 1(1), pages 49-59, March.
When requesting a correction, please mention this item's handle: RePEc:cen:wpaper:13-27. 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: (Fariha Kamal)
If references are entirely missing, you can add them using this form.