Two-stage Liu estimator in a simultaneous equations model

被引:5
|
作者
Toker, Selma [1 ]
Kaciranlar, Selahattin [1 ]
Guler, Huseyin [2 ]
机构
[1] Cukurova Univ, Fac Sci & Letters, Dept Stat, Adana, Turkey
[2] Cukurova Univ, Fac Econ & Adm Sci, Dept Econometr, Adana, Turkey
关键词
Liu estimator; multicollinearity; ridge estimator; simultaneous equations model; two-stage estimation; RIDGE-REGRESSION; ERROR;
D O I
10.1080/00949655.2018.1450875
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Two-stage least squares estimation in a simultaneous equations model has several desirable properties under the problem of multicollinearity. So, various kinds of improved estimation techniques can be developed to deal with the problem of multicollinearity. One of them is ridge regression estimation that can be applied at both stages and defined in Vinod and Ullah [Recent advances in regression methods. New York: Marcel Dekker; 1981]. We propose three different kinds of Liu estimators that are named by their implementation stages. Mean square errors are derived to compare the performances of the mentioned estimators and two different choices of the biasing parameter are offered. Moreover, a numerical example is given with a data analysis based on the Klein Model I and a Monte Carlo experiment is conducted.
引用
收藏
页码:2066 / 2088
页数:23
相关论文
共 50 条