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

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  • Zhao, Li
  • Xu, Xingzhong

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.

Suggested Citation

  • Zhao, Li & Xu, Xingzhong, 2017. "Generalized canonical correlation variables improved estimation in high dimensional seemingly unrelated regression models," Statistics & Probability Letters, Elsevier, vol. 126(C), pages 119-126.
    • Handle: RePEc:eee:stapro:v:126:y:2017:i:c:p:119-126
    DOI: 10.1016/j.spl.2017.02.037
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    References listed on IDEAS

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    1. Fraser, D.A.S. & Rekkas, M. & Wong, A., 2005. "Highly accurate likelihood analysis for the seemingly unrelated regression problem," Journal of Econometrics, Elsevier, vol. 127(1), pages 17-33, July.
    2. Dufour, Jean-Marie & Khalaf, Lynda, 2002. "Exact tests for contemporaneous correlation of disturbances in seemingly unrelated regressions," Journal of Econometrics, Elsevier, vol. 106(1), pages 143-170, January.
    3. Ma, Tiefeng & Wang, Songgui, 2009. "Estimation of the parameters in a two linear regression equations system with identical parameter vectors," Statistics & Probability Letters, Elsevier, vol. 79(9), pages 1135-1140, May.
    4. Zhao, Junguang & Xu, Xingzhong, 2016. "A generalized likelihood ratio test for normal mean when p is greater than n," Computational Statistics & Data Analysis, Elsevier, vol. 99(C), pages 91-104.
    5. Denzil Fiebig & Jae Kim, 2000. "Estimation and inference in sur models when the number of equations is large," Econometric Reviews, Taylor & Francis Journals, vol. 19(1), pages 105-130.
    6. Zhong, Ping-Shou & Chen, Song Xi, 2011. "Tests for High-Dimensional Regression Coefficients With Factorial Designs," Journal of the American Statistical Association, American Statistical Association, vol. 106(493), pages 260-274.
    7. Kargin, Vladislav, 2015. "On estimation in the reduced-rank regression with a large number of responses and predictors," Journal of Multivariate Analysis, Elsevier, vol. 140(C), pages 377-394.
    8. Wang, Lichun & Lian, Heng & Singh, Radhey S., 2011. "On efficient estimators of two seemingly unrelated regressions," Statistics & Probability Letters, Elsevier, vol. 81(5), pages 563-570, May.
    9. Liu, Aiyi, 2002. "Efficient Estimation of Two Seemingly Unrelated Regression Equations," Journal of Multivariate Analysis, Elsevier, vol. 82(2), pages 445-456, August.
    10. Katayama, Shota & Imori, Shinpei, 2014. "Lasso penalized model selection criteria for high-dimensional multivariate linear regression analysis," Journal of Multivariate Analysis, Elsevier, vol. 132(C), pages 138-150.
    11. Zellner, Arnold & Ando, Tomohiro, 2010. "A direct Monte Carlo approach for Bayesian analysis of the seemingly unrelated regression model," Journal of Econometrics, Elsevier, vol. 159(1), pages 33-45, November.
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    Citations

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    Cited by:

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    3. Junqian Xu & Yong Liu & Liling Yang, 2018. "A Comparative Study of the Role of China and India in Sustainable Textile Competition in the U.S. Market under Green Trade Barriers," Sustainability, MDPI, vol. 10(5), pages 1-21, April.
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    6. Jiang, Hong & Qian, Jianwei & Sun, Yuqin, 2020. "Best linear unbiased predictors and estimators under a pair of constrained seemingly unrelated regression models," Statistics & Probability Letters, Elsevier, vol. 158(C).

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