A restricted Liu estimator for binary regression models and its application to an applied demand system. Issue 6 (25th April 2016)

• Record Type: Journal Article
• Authors: Månsson, Kristofer; Golam Kibria, B.M.; Shukur, Ghazi
• Is Part Of: Journal of applied statistics. Volume 43:Issue 6(2016)
• Page Start: 1119
• Page End: 1127
• Publication Date: 2016-04-25
• Subjects: Liu estimator -- logit model -- MLE -- multicollinearity -- MSE -- simulation study; 62J05 -- 62J07; Statistics -- Periodicals; 519.5
• DOI: 10.1080/02664763.2015.1092110
• Languages: English
• ISSNs: 0266-4763

Abstract

Abstract : In this article, we propose a restricted Liu regression estimator (RLRE) for estimating the parameter vector, β, in the presence of multicollinearity, when the dependent variable is binary and it is suspected that β may belong to a linear subspace defined by Rβ = r . First, we investigate the mean squared error (MSE) properties of the new estimator and compare them with those of the restricted maximum likelihood estimator (RMLE). Then we suggest some estimators of the shrinkage parameter, and a simulation study is conducted to compare the performance of the different estimators. Finally, we show the benefit of using RLRE instead of RMLE when estimating how changes in price affect consumer demand for a specific product.