Combining Kibria-Lukman and Principal Component Estimators for the Distributed Lag Models
Abstract
Researchers are likely to encounter the problem of multicollinearity in the distributed lag model due to its nature. To address multicollinearity, biased estimation techniques such as the Almon ridge estimator may be preferred over the Almon estimator. By integrating the principal component (PC) approach with the Almon Kibria-Lukman (KL) estimator, the Almon principal component Kibria-Lukman estimator is proposed in this paper. The new technique possesses the advantage of the principal component estimator and the Almon-KL estimator. Almon-PC-KL estimator dominates the other estimators considered in this study in terms of theoretical comparison and simulation.
Type
Publication
Behaviormetrika
