Nonparametric Estimation of Semiparametric Transformation Models
AbstractIn this paper we develop a nonparametric estimation technique for semiparametric transformation models of the form: H(Y)=P(Z)+X'B+U where H,P and B and are unknown and the variables (Y,Z) are endogenous. Identification of the model and asymptotic properties of the estimator are analyzed under the mean independence assumption between the error term and the instruments. We show that the estimators are consistent and root N convergence rate for the estimate of B can be attained. The simulations demonstrate that our nonparametric estimates fits the data well.
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Bibliographic InfoPaper provided by Department of Economics, University of Bristol, UK in its series Bristol Economics Discussion Papers with number 12/625.
Length: 45 pages
Date of creation: Jul 2012
Date of revision:
Nonparametric IV Regression; Inverse problems; Tikhonov Regularization; Regularization Parameter;
Find related papers by JEL classification:
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
- C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General
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