In this paper, we extend the results in Hansen (1982) regarding the asymptotic distribution of generalized method of moments (GMM) sample moment conditions. In particular, we show that the part of the scaled sample moment conditions that gives rise to degeneracy in the asymptotic normal distribution is T-consistent and has a nonstandard limiting distribution. We derive the asymptotic distribution for a given linear combination of the sample moment conditions and show how to conduct statistical inference. We demonstrate the finite-sample properties of the proposed asymptotic approximation using simulation.
Using many moment conditions can improve efficiency but makes the usual GMM inferences inaccurate. T...
To obtain consistency and asymptotic normality, a generalized method of moments (GMM) estimator typi...
The efficiency of the generalized method of moment (GMM) estimator is addressed by using a character...
This paper provides a first order asymptotic theory for generalized method of moments (GMM) estimato...
This paper provides a first order asymptotic theory for generalized method of moments (GMM) estimato...
This paper studies how identification is affected in GMM estimation as the number of moment conditio...
The GMM estimator is widely used in the econometrics literature. This thesis mainly focus on three a...
The efficiency of the generalized method of moment (GMM) estimator is addressed by using a character...
Using many moment conditions can improve efficiency but makes the usual GMM inferences inaccurate. T...
We propose a generalized method of moments (GMM) Lagrange multiplier statistic, i.e., the K statisti...
This paper develops asymptotic distribution theory for generalized method of moments (GMM) estimator...
The topic of this paper is inference in models in which parameters are defined by moment inequalities...
This paper investigates statistical properties of the local generalized method of moments (LGMM) est...
Procedures based on the Generalized Method of Moments (GMM) are basic tools in modern econometrics. ...
It is well-known that the method of moments (MM) estimator is usu-ally ine ¢ cient relative to the m...
Using many moment conditions can improve efficiency but makes the usual GMM inferences inaccurate. T...
To obtain consistency and asymptotic normality, a generalized method of moments (GMM) estimator typi...
The efficiency of the generalized method of moment (GMM) estimator is addressed by using a character...
This paper provides a first order asymptotic theory for generalized method of moments (GMM) estimato...
This paper provides a first order asymptotic theory for generalized method of moments (GMM) estimato...
This paper studies how identification is affected in GMM estimation as the number of moment conditio...
The GMM estimator is widely used in the econometrics literature. This thesis mainly focus on three a...
The efficiency of the generalized method of moment (GMM) estimator is addressed by using a character...
Using many moment conditions can improve efficiency but makes the usual GMM inferences inaccurate. T...
We propose a generalized method of moments (GMM) Lagrange multiplier statistic, i.e., the K statisti...
This paper develops asymptotic distribution theory for generalized method of moments (GMM) estimator...
The topic of this paper is inference in models in which parameters are defined by moment inequalities...
This paper investigates statistical properties of the local generalized method of moments (LGMM) est...
Procedures based on the Generalized Method of Moments (GMM) are basic tools in modern econometrics. ...
It is well-known that the method of moments (MM) estimator is usu-ally ine ¢ cient relative to the m...
Using many moment conditions can improve efficiency but makes the usual GMM inferences inaccurate. T...
To obtain consistency and asymptotic normality, a generalized method of moments (GMM) estimator typi...
The efficiency of the generalized method of moment (GMM) estimator is addressed by using a character...