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Generalized canonical correlation variables improved estimation in high dimensional seemingly unrelated regression models

Li Zhao and Xingzhong Xu

Statistics & Probability Letters, 2017, vol. 126, issue C, 119-126

Abstract: After defining generalized canonical correlation variable pairs, this study proposes a new estimator of regression coefficients in seemingly unrelated regression models. The properties of the estimator are also discussed. The results of simulations show that the proposed estimator outperforms the ordinary least squares estimator.

Keywords: Generalized canonical correlation variable; High dimensional seemingly unrelated regression model; Improved estimator; Zellner’s two-stage estimator (search for similar items in EconPapers)
Date: 2017
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Handle: RePEc:eee:stapro:v:126:y:2017:i:c:p:119-126