Bounding the effect of a dichotomous regressor with arbitrary measurement errors

This note considers a nonlinear regression model containing a 0–1 dichotomous regressor when it is subject to arbitrary measurement errors in the sample. The key identification assumption requires that the third conditional moment of the regression error is zero. This note suggests that the effect o...

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Bibliographic Details
Published inEconomics letters Vol. 105; no. 3; pp. 256 - 260
Main Authors Deng, Ping, Hu, Yingyao
Format Journal Article
LanguageEnglish
Published Elsevier B.V 01.12.2009
Elsevier
SeriesEconomics Letters
Subjects
Arbitrary measurement error
Arbitrary measurement error Misclassification Bounds Dichotomous variable
Bounds
Dichotomous variable
Error
Identification
Measurement
Misclassification
Non-linear models
Regression analysis
Arbitrary measurement error
Misclassification
Dichotomous variable
Bounds
C2
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Summary:This note considers a nonlinear regression model containing a 0–1 dichotomous regressor when it is subject to arbitrary measurement errors in the sample. The key identification assumption requires that the third conditional moment of the regression error is zero. This note suggests that the effect of the latent dichotomous variable may be bounded away from zero using the observed moments.
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:0165-1765
1873-7374
DOI:10.1016/j.econlet.2009.08.009