Date of Award
1988
Document Type
Dissertation
Degree Name
Doctor of Philosophy (PhD)
Department
Economics
First Advisor
R. Carter Hill
Abstract
The dissertation addresses three issues in the use of Stein-like estimators of the classical normal linear regression model. The St. Louis equation is used to generate out-of-sample forecasts using least squares. These forecasts are compared to those produced by restricted least squares, pretest, and members of a general family of minimax shrinkage estimators using the root-mean-square error criterion. Bootstrap confidence intervals and ellipsoids are constructed which are centered at least squares and James-Stein estimators and their coverage probability and size is explored in a Monte Carlo experiment. A Stein-like estimator of the probit regression model is suggested and its quadratic risk properties are explored in a Monte Carlo experiment.
Recommended Citation
Adkins, Lee Chester, "Stein-Like Estimation and Inference." (1988). LSU Historical Dissertations and Theses. 4552.
https://repository.lsu.edu/gradschool_disstheses/4552
Pages
353
DOI
10.31390/gradschool_disstheses.4552