Title of article :
Estimation of possibly misspecified semiparametric conditional moment restriction models with different conditioning variables
Author/Authors :
Ai، نويسنده , , Chunrong and Chen، نويسنده , , Xiaohong، نويسنده ,
Issue Information :
دوفصلنامه با شماره پیاپی سال 2007
Pages :
39
From page :
5
To page :
43
Abstract :
Newey and Powell [2003. Instrumental variable estimation of nonparametric models. Econometrica 71, 1565–1578] and Ai and Chen [2003. Efficient estimation of conditional moment restrictions models containing unknown functions. Econometrica 71, 1795–1843] propose sieve minimum distance (SMD) estimation of both finite dimensional parameter ( θ ) and infinite dimensional parameter (h) that are identified through a conditional moment restriction model, in which h could depend on endogenous variables. This paper modifies their SMD procedure to allow for different conditioning variables to be used in different equations, and derives the asymptotic properties when the model may be misspecified. Under low-level sufficient conditions, we show that: (i) the modified SMD estimators of both θ and h converge to some pseudo-true values in probability; (ii) the SMD estimators of smooth functionals, including the θ estimator and the average derivative estimator, are asymptotically normally distributed; and (iii) the estimators for the asymptotic covariances of the SMD estimators of smooth functionals are consistent and easy to compute. These results allow for asymptotically valid tests of various hypotheses on the smooth functionals regardless of whether the semiparametric model is correctly specified or not.
Keywords :
Weighted average derivatives , Conditional moment models with different conditioning sets , Nonparametric endogeneity , Sieve minimum distance , Misspecification
Journal title :
Journal of Econometrics
Serial Year :
2007
Journal title :
Journal of Econometrics
Record number :
1559234
Link To Document :
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