In this paper I explore the issue of nonlinearity (both in the datageneration process and in the functional form that establishes therelationship between the parameters and the data) regarding the poorperformance of the Generalized Method of Moments (GMM) in small samples.To this purpose I build a sequence of models starting with a simple linearmodel and enlarging it progressively until I approximate a standard (nonlinear)neoclassical growth model. I then use simulation techniques to find the smallsample distribution of the GMM estimators in each of the models
This paper provides a first order asymptotic theory for generalized method of moments (GMM) estimator...
The generalized method of moments (GMM) is a very popular estimation and inference procedure based o...
The first two chapters of this thesis develop a new methodology in the Generalized Method of Moments...
In this paper I explore the issue of nonlinearity (both in the data generation process and in the fu...
We show that the Generalized Method of Moments (GMM) methodology is a useful tool to obtain the asym...
The GMM estimator is widely used in the econometrics literature. This thesis mainly focus on three a...
The GMM estimator is widely used in the econometrics literature. This thesis mainly focus on three a...
The generalized method of moments (GMM) is an extremely popular estimation technique in empirical wo...
This paper studies the application of the simulated method of moments (SMM) for the estimation of no...
This paper studies the application of the simulated method of moments (SMM) for the estimation of no...
Procedures based on the Generalized Method of Moments (GMM) are basic tools in modern econometrics. ...
This paper provides a first order asymptotic theory for generalized method of moments (GMM) estimato...
This paper determines the properties of standard generalized method of moments (GMM) estimators, tes...
This paper provides a first order asymptotic theory for generalized method of moments (GMM) estimator...
The generalized method of moments (GMM) is the centrepiece of semiparametric estimation frameworks. ...
This paper provides a first order asymptotic theory for generalized method of moments (GMM) estimator...
The generalized method of moments (GMM) is a very popular estimation and inference procedure based o...
The first two chapters of this thesis develop a new methodology in the Generalized Method of Moments...
In this paper I explore the issue of nonlinearity (both in the data generation process and in the fu...
We show that the Generalized Method of Moments (GMM) methodology is a useful tool to obtain the asym...
The GMM estimator is widely used in the econometrics literature. This thesis mainly focus on three a...
The GMM estimator is widely used in the econometrics literature. This thesis mainly focus on three a...
The generalized method of moments (GMM) is an extremely popular estimation technique in empirical wo...
This paper studies the application of the simulated method of moments (SMM) for the estimation of no...
This paper studies the application of the simulated method of moments (SMM) for the estimation of no...
Procedures based on the Generalized Method of Moments (GMM) are basic tools in modern econometrics. ...
This paper provides a first order asymptotic theory for generalized method of moments (GMM) estimato...
This paper determines the properties of standard generalized method of moments (GMM) estimators, tes...
This paper provides a first order asymptotic theory for generalized method of moments (GMM) estimator...
The generalized method of moments (GMM) is the centrepiece of semiparametric estimation frameworks. ...
This paper provides a first order asymptotic theory for generalized method of moments (GMM) estimator...
The generalized method of moments (GMM) is a very popular estimation and inference procedure based o...
The first two chapters of this thesis develop a new methodology in the Generalized Method of Moments...