Some Liu Type Estimators for the dynamic OLS estimator: With an application to the carbon dioxide Kuznets curve for Turkey

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Abstract

This paper suggests some Liu type shrinkage estimators for the dynamic ordinary least squares (DOLS) estimator that may be used to combat the multicollinearity problem. DOLS is an estimator suggested to solve the finite sample bias of OLS caused by endogeneity issue when estimating regression models based on cointegrated variables. In this paper using simulation techniques it is shown that multicollinearity and non-normality of the error term is a problem in finite samples for the DOLS model. The merit of proposed Liu type estimator are shown by means of a Monte Carlo simulation study and using an empirical application.

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Månsson, K., Kibria, B. M. G., & Shukur, G. (2017). Some Liu Type Estimators for the dynamic OLS estimator: With an application to the carbon dioxide Kuznets curve for Turkey. Communications in Statistics Case Studies Data Analysis and Applications, 3(3–4), 55–61. https://doi.org/10.1080/23737484.2018.1424589

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