Efficient Estimation of Two Seemingly Unrelated Regression Equations
Author
Abstract
Suggested Citation
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- 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.
- 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.
- Ryan H. L. Ip & Dmitry Demskoi & Azizur Rahman & Lihong Zheng, 2021. "Evaluation of COVID-19 Mitigation Policies in Australia Using Generalised Space-Time Autoregressive Intervention Models," IJERPH, MDPI, vol. 18(14), pages 1-17, July.
- 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.
- Shun Matsuura & Hiroshi Kurata, 2022. "Optimal estimator under risk matrix in a seemingly unrelated regression model and its generalized least squares expression," Statistical Papers, Springer, vol. 63(1), pages 123-141, February.
- Jinhong You & Xian Zhou, 2010. "Statistical inference on seemingly unrelated varying coefficient partially linear models," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 64(2), pages 227-253, May.
- Shun Matsuura & Hiroshi Kurata, 2020. "Covariance matrix estimation in a seemingly unrelated regression model under Stein’s loss," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 29(1), pages 79-99, March.
- 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.
- 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.
- Xu, Qinfeng & You, Jinhong & Zhou, Bin, 2008. "Seemingly unrelated nonparametric models with positive correlation and constrained error variances," Economics Letters, Elsevier, vol. 99(2), pages 223-227, May.
More about this item
Keywords
two-stage estimates finite sample efficiency mean square error;Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:jmvana:v:82:y:2002:i:2:p:445-456. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.