The first two chapters of this thesis develop a new methodology in the Generalized Method of Moments. Typically, researchers assume that the data come from an unknown ideal distribution. In the first two chapters, we relax this assumption by assuming shrinking neighborhoods of this ideal distribution. We show the conditions that are needed for GMM estimators to have a stable behaviour in these neighborhoods and propose a robust GMM estimator based on these conditions. Finally, we show how to perform Moment and Model Selection based on the robust GMM estimators. The third chapter is an extension of the framework introduced by J. Taylor in 1993. We propose a more flexible setting that can capture asymmetric preferences of the Central Bank bet...
This paper shows how to estimate models by the generalized method of moments and the generalized emp...
OnlinePublThis paper proposes a robust moment selection method aiming to pick the best model even if...
<p>This dissertations presents the estimation methods of financial models for which the density func...
The first two chapters of this thesis develop a new methodology in the Generalized Method of Moments...
This paper studies inference in models that are identified by moment restrictions. We show how insta...
The GMM estimator is widely used in the econometrics literature. This thesis mainly focus on three a...
Presents the main statistical tools of econometrics, focusing specifically on modern econometric met...
Procedures based on the Generalized Method of Moments (GMM) are basic tools in modern econometrics. ...
We describe an intuitive, simple, and systematic approach to generating moment conditions for genera...
In econometrics, models stated as conditional moment restrictions are typically estimated by means o...
In this paper, the authors describe the selection methods for moments and the application of the gen...
We describe an intuitive, simple, and systematic approach to generating moment conditions for genera...
The generalized method of moments (GMM) is the centrepiece of semiparametric estimation frameworks. ...
Thesis: Ph. D., Massachusetts Institute of Technology, Department of Economics, 2015.Title as it app...
This paper presents a Generalized Method of Moments algorithm for estimating the structural paramete...
This paper shows how to estimate models by the generalized method of moments and the generalized emp...
OnlinePublThis paper proposes a robust moment selection method aiming to pick the best model even if...
<p>This dissertations presents the estimation methods of financial models for which the density func...
The first two chapters of this thesis develop a new methodology in the Generalized Method of Moments...
This paper studies inference in models that are identified by moment restrictions. We show how insta...
The GMM estimator is widely used in the econometrics literature. This thesis mainly focus on three a...
Presents the main statistical tools of econometrics, focusing specifically on modern econometric met...
Procedures based on the Generalized Method of Moments (GMM) are basic tools in modern econometrics. ...
We describe an intuitive, simple, and systematic approach to generating moment conditions for genera...
In econometrics, models stated as conditional moment restrictions are typically estimated by means o...
In this paper, the authors describe the selection methods for moments and the application of the gen...
We describe an intuitive, simple, and systematic approach to generating moment conditions for genera...
The generalized method of moments (GMM) is the centrepiece of semiparametric estimation frameworks. ...
Thesis: Ph. D., Massachusetts Institute of Technology, Department of Economics, 2015.Title as it app...
This paper presents a Generalized Method of Moments algorithm for estimating the structural paramete...
This paper shows how to estimate models by the generalized method of moments and the generalized emp...
OnlinePublThis paper proposes a robust moment selection method aiming to pick the best model even if...
<p>This dissertations presents the estimation methods of financial models for which the density func...