Identification of the Binary Choice Model with Misclassification
Misclassification in binary choice (binomial response) models occurs when the dependent variable is measured with error, that is, when an actual "one" response is sometimes recorded as a zero, and vice versa. This paper shows that binary choice models with misclassification are semiparametrically identified, even when the probabilities of misclassification depend in unknown ways on model covariates, and the distribution of the errors is unknown.
|Date of creation:||31 Jan 2000|
|Date of revision:|
|Publication status:||published, Econometric Theory, 2000, 16, 603-609|
|Contact details of provider:|| Postal: Boston College, 140 Commonwealth Avenue, Chestnut Hill MA 02467 USA|
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- repec:cup:etheor:v:11:y:1995:i:3:p:560-96 is not listed on IDEAS
- 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.
- Andrews, Donald W.K., 1995. "Nonparametric Kernel Estimation for Semiparametric Models," Econometric Theory, Cambridge University Press, vol. 11(03), pages 560-586, June.
- Brown, James N & Light, Audrey, 1992. "Interpreting Panel Data on Job Tenure," Journal of Labor Economics, University of Chicago Press, vol. 10(3), pages 219-57, July.
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