Econometrics application of partial least squares regression: an endogeneous growth model for Turkey

被引:6
作者
Korkmazoglu, Ozlem Berak [1 ]
Kemalbay, Gulder [1 ]
机构
[1] Yildiz Tekn Univ, Fac Art&Sci, Dept Stat, TR-34220 Esenler, Istabul, Turkey
来源
WORLD CONFERENCE ON BUSINESS, ECONOMICS AND MANAGEMENT (BEM-2012) | 2012年 / 62卷
关键词
Partial least squares; multicollinearity; economic growth; PLS;
D O I
10.1016/j.sbspro.2012.09.153
中图分类号
F [经济];
学科分类号
02 ;
摘要
Many Econometric models which included time series data have multicollinearity problem. Partial least square regression (PLS) is one of the popular multivariate regression methods in a a wide range of fields.The reason of that PLS have been designed to confront the situation that many correlated predictor variables and few samples situation. Growth rate is determined endogenously in endogenous growth models. In this study different algoritms (like Kernel, NIPALS, etc) of PLS are applied to an endogenous growth model starting with works of Romer (1986) and Lucas (1988). We study on real data for Turkey to illustrate the econometric applications and interpretations of various PLS algoritms using R programming. (C) 2012 Published by Elsevier Ltd. Selection and/or peer review under responsibility of Prof. Dr. Huseyin Arasli
引用
收藏
页码:906 / 910
页数:5
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