4.4 Article

Estimating the Unrestricted and Restricted Liu Estimators for the Poisson Regression Model: Method and Application

Journal

COMPUTATIONAL ECONOMICS
Volume 58, Issue 2, Pages 311-326

Publisher

SPRINGER
DOI: 10.1007/s10614-020-10028-y

Keywords

Liu estimator; Maximum likelihood; Monte Carlo simulations; MSE; Multicollinearity; Poisson regression; Restricted estimator

Funding

  1. Jonkoping University

Ask authors/readers for more resources

This paper explores both unrestricted and restricted Liu estimators in the context of multicollinearity in the Poisson regression model, introducing new estimators for the shrinkage parameter. Through simulation and empirical application, it is found that the restricted estimator outperforms the unrestricted one, with the restricted Liu estimator showing superior performance to both the unrestricted Liu and restricted Liu estimators. This new method is therefore preferred when the coefficient vector may belong to a linear sub-space.
This paper considers both unrestricted and restricted Liu estimators in the presence of multicollinearity for the Poisson regression model. It also considers some new estimators of the shrinkage parameter for both unrestricted and restricted Liu estimators. Based on a simulation study and its empirical application, we found that the restricted estimator outperforms the unrestricted one. Further, the restricted Liu estimator also outperforms both the unrestricted Liu and restricted Liu estimators. Hence, this new method is a preferred option when the coefficient vector beta may belong to a linear sub-space defined byR beta = r.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.4
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available