Method of moments estimation and identifiability of semiparametric nonlinear errors-in-variables models |
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Authors: | Liqun Wang |
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Affiliation: | a Department of Statistics, University of Manitoba, Winnipeg, Manitoba, Canada R3T 2N2b Department of Economics, University of Southern California, Los Angeles, CA 90089-0253, USAc Wang Yanan Institute for Studies in Economics, Xiamen University, Chinad City University of Hongkong, Hongkong, China |
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Abstract: | 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. |
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Keywords: | C13 C14 C15 |
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