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Estimation of nonlinear models with mismeasured regressors using marginal information
Author(s) -
Hu Yingyao,
Ridder Geert
Publication year - 2012
Publication title -
journal of applied econometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.878
H-Index - 99
eISSN - 1099-1255
pISSN - 0883-7252
DOI - 10.1002/jae.1202
Subject(s) - estimator , econometrics , parametric statistics , welfare , sample (material) , distribution (mathematics) , marginal distribution , estimation , mathematics , economics , nonlinear system , statistics , asymptotic distribution , observational error , parametric model , random variable , mathematical analysis , chemistry , physics , management , chromatography , quantum mechanics , market economy
We consider the estimation of nonlinear models with mismeasured explanatory variables, when information on the marginal distribution of the true values of these variables is available. We derive a semi‐parametric MLE that is shown to be $\sqrt{n}$ consistent and asymptotically normally distributed. In a simulation experiment we find that the finite sample distribution of the estimator is close to the asymptotic approximation. The semi‐parametric MLE is applied to a duration model for AFDC welfare spells with misreported welfare benefits. The marginal distribution of the correctly measured welfare benefits is obtained from an administrative source. Copyright © 2010 John Wiley & Sons, Ltd.