期刊
JOURNAL OF ECONOMETRICS
卷 165, 期 1, 页码 30-44出版社
ELSEVIER SCIENCE SA
DOI: 10.1016/j.jeconom.2011.05.004
关键词
Fourier deconvolution; Identifiability; Instrumental variables; Measurement error; Method of moments; Root-n consistency; Semiparametric estimator; Simulation-based estimator
资金
- National Science Foundation [SBR 94-09540, SBR 96-19330]
- Swiss National Science Foundation
- Natural Sciences and Engineering Research Council of Canada (NSERC)
This paper deals with a nonlinear errors-in-variables model where the distributions of the unobserved predictor variables and of the measurement errors are nonparametric. Using the instrumental variable approach, we propose method of moments estimators for the unknown parameters and simulation-based estimators to overcome the possible computational difficulty of minimizing an objective function which involves multiple integrals. Both estimators are consistent and asymptotically normally distributed under fairly general regularity conditions. Moreover, root-n consistent semiparametric estimators and a rank condition for model identifiability are derived using the combined methods of the nonparametric technique and Fourier deconvolution. (C) 2011 Elsevier B.V. All rights reserved.
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