This paper presents a comprehensive approach to estimation and hypothesis testing under a set of full restrictions, some of these arising from adding-up conditions on the endogenous variable. In contrast to the existing statistical literature, this paper uses an argumentation style familiar from classical econometric textbooks, to provide an insightful, straightforward, and nevertheless rigorous exposition of this topic.Restricted least squares Adding-up Singularity Wald-Test SUR.
Asymptotic properties of L_{1}-estimates in linear regression have been studied by many authors, see...
Thesis (Ph.D.)--University of Washington, 2020This dissertation studies the problem of uniform infer...
Linear models are statistical models that are linear in their parameters. This class of models incl...
This paper presents a comprehensive approach to estimation and hypothesis testing under a set of ful...
Chapter 4. The treatment of linear restrictions 4.1. Estimation subject to linear restrictions. In t...
This paper extend, in an asymptotic sense, the strong and the weaker mean square error criteria and ...
A new method for testing linear restrictions in linear regression models is suggested. It allows to ...
A new method for testing linear restrictions in linear regression models is suggested. It allows to ...
A new method for testing linear restrictions in linear regression models is suggested. It allows to ...
A new method for testing linear restrictions in linear regression models is suggested. It allows to ...
AbstractThe linear regression model is considered where the parameter vector may be simultaneously c...
There is a useful but not widely known framework for jointly implementing Durbin-Wu-Hausman exogenei...
A fully-fledged alternative to Two-Stage Least-Squares (TSLS) inference is developed for general lin...
A fully-fledged alternative to Two-Stage Least-Squares (TSLS) inference is developed for general lin...
AbstractAn extension or modification of the output of least-squares computer subroutines is proposed...
Asymptotic properties of L_{1}-estimates in linear regression have been studied by many authors, see...
Thesis (Ph.D.)--University of Washington, 2020This dissertation studies the problem of uniform infer...
Linear models are statistical models that are linear in their parameters. This class of models incl...
This paper presents a comprehensive approach to estimation and hypothesis testing under a set of ful...
Chapter 4. The treatment of linear restrictions 4.1. Estimation subject to linear restrictions. In t...
This paper extend, in an asymptotic sense, the strong and the weaker mean square error criteria and ...
A new method for testing linear restrictions in linear regression models is suggested. It allows to ...
A new method for testing linear restrictions in linear regression models is suggested. It allows to ...
A new method for testing linear restrictions in linear regression models is suggested. It allows to ...
A new method for testing linear restrictions in linear regression models is suggested. It allows to ...
AbstractThe linear regression model is considered where the parameter vector may be simultaneously c...
There is a useful but not widely known framework for jointly implementing Durbin-Wu-Hausman exogenei...
A fully-fledged alternative to Two-Stage Least-Squares (TSLS) inference is developed for general lin...
A fully-fledged alternative to Two-Stage Least-Squares (TSLS) inference is developed for general lin...
AbstractAn extension or modification of the output of least-squares computer subroutines is proposed...
Asymptotic properties of L_{1}-estimates in linear regression have been studied by many authors, see...
Thesis (Ph.D.)--University of Washington, 2020This dissertation studies the problem of uniform infer...
Linear models are statistical models that are linear in their parameters. This class of models incl...