GEL methods that generalize and extend previous contributions are defined and analyzed for moment condition models specified in terms of weakly dependent data. These procedures offer alternative one-step estimators and tests that are asymptotically equivalent to their efficient two-step GMM counterparts. The basis for GEL estimation is via a smoothed version of the moment indicators using kernel function weights that incorporate a bandwidth parameter. Examples for the choice of bandwidth parameter and kernel function are provided. Efficient moment estimators based on implied probabilities derived from the GEL method are proposed, a special case of which is estimation of the stationary distribution of the data. The paper also presents a unif...
Using many moment conditions can improve efficiency but makes the usual GMM inferences inaccurate. T...
Using many moment conditions can improve efficiency but makes the usual GMM inferences inaccurate. T...
Properties of GMM estimators are sensitive to the choice of instruments. Using many instruments lead...
GEL methods which generalize and extend previous contributions are defined and analysed for moment c...
This paper studies the properties of generalised empirical likelihood (GEL) methods for the estimati...
This paper considers the first order large sample properties of the GEL class of estimators for mode...
This paper considers the first-order large sample properties of the generalized empirical likelihood...
The principal purpose of this paper is to adapt to the conditional moment context the GEL unconditio...
This paper proposes novel methods for the construction of tests for models specified by unconditiona...
Using many moment conditions can improve efficiency but makes the usual generalized method of moment...
The central concern of this paper is the provision in a time series moment condition framework of pr...
The central concern of this paper is parameter heterogeneity in models specified by a number of unco...
The aim of this thesis is to investigate Generalised Empirical Likelihood (GEL) and related informat...
This paper considers the maximum generalized empirical likelihood (GEL) estimation and inference on ...
The study of the generalized method of moments (GMM) and alternative estimation methods for models w...
Using many moment conditions can improve efficiency but makes the usual GMM inferences inaccurate. T...
Using many moment conditions can improve efficiency but makes the usual GMM inferences inaccurate. T...
Properties of GMM estimators are sensitive to the choice of instruments. Using many instruments lead...
GEL methods which generalize and extend previous contributions are defined and analysed for moment c...
This paper studies the properties of generalised empirical likelihood (GEL) methods for the estimati...
This paper considers the first order large sample properties of the GEL class of estimators for mode...
This paper considers the first-order large sample properties of the generalized empirical likelihood...
The principal purpose of this paper is to adapt to the conditional moment context the GEL unconditio...
This paper proposes novel methods for the construction of tests for models specified by unconditiona...
Using many moment conditions can improve efficiency but makes the usual generalized method of moment...
The central concern of this paper is the provision in a time series moment condition framework of pr...
The central concern of this paper is parameter heterogeneity in models specified by a number of unco...
The aim of this thesis is to investigate Generalised Empirical Likelihood (GEL) and related informat...
This paper considers the maximum generalized empirical likelihood (GEL) estimation and inference on ...
The study of the generalized method of moments (GMM) and alternative estimation methods for models w...
Using many moment conditions can improve efficiency but makes the usual GMM inferences inaccurate. T...
Using many moment conditions can improve efficiency but makes the usual GMM inferences inaccurate. T...
Properties of GMM estimators are sensitive to the choice of instruments. Using many instruments lead...