EFFICIENT INSTRUMENTAL VARIABLES ESTIMATION OF NONLINEAR MODELS

This paper considers asymptotically efficient instrumental variables estimation of nonlinear models in an i.i.d. environment. The optimal instruments are estimated by nonparametric methods, either nearest neighbor or series regression. Ways of choosing the degree of approximation of the nonparametric instruments are discussed. Asymptotic efficiency is shown. The finite sample properties of the estimators are examined in a small sampling study of an endogenous dummy variable model. Copyright 1990 by The Econometric Society.

[1]  Charles F. Manski,et al.  Monte Carlo evidence on adaptive maximum likelihood estimation of a regression , 1987 .

[2]  Whitney K. Newey,et al.  Adaptive estimation of regression models via moment restrictions , 1988 .

[3]  L. Hansen Large Sample Properties of Generalized Method of Moments Estimators , 1982 .

[4]  J. Heckman,et al.  Longitudinal Analysis of Labor Market Data: Alternative methods for evaluating the impact of interventions , 1985 .

[5]  J. Heckman Dummy Endogenous Variables in a Simultaneous Equation System , 1977 .

[6]  P. Robinson Asymptotically efficient estimation in the presence of heteroskedasticity of unknown form , 1987 .

[7]  A. Ronald Gallant,et al.  On unification of the asymptotic theory of nonlinear econometric models , 1982 .

[8]  W. Härdle,et al.  How Far are Automatically Chosen Regression Smoothing Parameters from their Optimum , 1988 .

[9]  Harry H. Kelejian,et al.  Two-Stage Least Squares and Econometric Systems Linear in Parameters but Nonlinear in the Endogenous Variables , 1971 .

[10]  C. J. Stone,et al.  Consistent Nonparametric Regression , 1977 .

[11]  Bronwyn H Hall,et al.  Estimation and Inference in Nonlinear Structural Models , 1974 .

[12]  P. Robinson Instrumental Variables Estimation of Differential Equations , 1976 .

[13]  T. MaCurdy Using Information on the Moments of Disturbances to Increase the Efficiency of Estimation , 1982 .

[14]  A. Gallant,et al.  On the bias in flexible functional forms and an essentially unbiased form : The fourier flexible form , 1981 .

[15]  Dale W. Jorgenson,et al.  EFFICIENT ESTIMATION OF NONLINEAR SIMULTANEOUS EQUATIONS WITH ADDITIVE DISTURBANCES , 2022 .

[16]  Takeshi Amemiya,et al.  The Maximum Likelihood and the Nonlinear Three-Stage Least Squares Estimator in the General Nonlinear Simultaneous Equation Model , 1977 .

[17]  A. Gallant Explicit Estimators of Parametric Functions in Nonlinear Regression , 1980 .