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Highly accurate likelihood analysis for the seemingly unrelated regression problem

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  • Fraser, D.A.S.
  • Rekkas, M.
  • Wong, A.

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  • 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.
  • Handle: RePEc:eee:econom:v:127:y:2005:i:1:p:17-33
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    References listed on IDEAS

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    1. Attfield, C. L. F., 1998. "Bartlett adjustments for systems of linear equations with linear restrictions," Economics Letters, Elsevier, vol. 60(3), pages 277-283, September.
    2. Rilstone, Paul & Veall, Michael, 1996. "Using Bootstrapped Confidence Intervals for Improved Inferences with Seemingly Unrelated Regression Equations," Econometric Theory, Cambridge University Press, vol. 12(3), pages 569-580, August.
    3. Oberhofer, W & Kmenta, J, 1974. "A General Procedure for Obtaining Maximum Likelihood Estimates in Generalized Regression Models," Econometrica, Econometric Society, vol. 42(3), pages 579-590, May.
    4. Attfield, C. L. F., 1995. "A Bartlett adjustment to the likelihood ratio test for a system of equations," Journal of Econometrics, Elsevier, vol. 66(1-2), pages 207-223.
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    Cited by:

    1. Wang, Min & Sun, Xiaoqian, 2012. "Bayesian inference for the correlation coefficient in two seemingly unrelated regressions," Computational Statistics & Data Analysis, Elsevier, vol. 56(8), pages 2442-2453.
    2. 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.
    3. Tiong, Kah Yong & Ma, Zhenliang & Palmqvist, Carl-William, 2023. "Analyzing factors contributing to real-time train arrival delays using seemingly unrelated regression models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 174(C).
    4. Chwu-Shiun Tarng, 2014. "Third-order likelihood-based inference for the log-normal regression model," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(9), pages 1976-1988, September.
    5. Meuer, Johannes & Rupietta, Christian & Backes-Gellner, Uschi, 2015. "Layers of co-existing innovation systems," Research Policy, Elsevier, vol. 44(4), pages 888-910.
    6. Zellner, Arnold & Ando, Tomohiro, 2010. "Bayesian and non-Bayesian analysis of the seemingly unrelated regression model with Student-t errors, and its application for forecasting," International Journal of Forecasting, Elsevier, vol. 26(2), pages 413-434, April.
    7. 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.

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