Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/103845
Authors: 
Wüthrich, Kaspar
Year of Publication: 
2013
Series/Report no.: 
Discussion Papers, Department of Economics, Universität Bern 13-04
Abstract: 
This paper studies the identification of coefficients in generalized linear predictors where the outcome variable suffers from non-classical measurement errors. Combining a mixture model of data errors with the bounding procedure proposed by Stoye (2007), I derive bounds on the coefficient vector under different non-parametric assumptions about the structure of the measurement error. The method is illustrated by analyzing a simple earnings equation.
Subjects: 
Generalized linear predictor
Non-classical measurement error
Contaminated sampling
Corrupt sampling
Multiplicative mean independence
Stochastic dominance
Nonparametric bounds
JEL: 
C2
C21
J24
Document Type: 
Working Paper

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