IDEAS home Printed from https://ideas.repec.org/a/ebl/ecbull/eb-01c10005.html
   My bibliography  Save this article

Fully restricted linear regression: A pedagogical note

Author

Listed:
  • Harry Haupt

    (University of Regensburg)

  • Walter Oberhofer

    (University of Regensburg)

Abstract

This paper presents a comprehensive approach to estimation and hypothesis testing under a set of full restrictions, some of these arising from adding-up conditions on the endogenous variable. In contrast to the existing statistical literature, this paper uses an argumentation style familiar from classical econometric textbooks, to provide an insightful, straightforward, and nevertheless rigorous exposition of this topic.

Suggested Citation

  • Harry Haupt & Walter Oberhofer, 2002. "Fully restricted linear regression: A pedagogical note," Economics Bulletin, AccessEcon, vol. 3(1), pages 1-7.
    • Handle: RePEc:ebl:ecbull:eb-01c10005
    as

    Download full text from publisher

    File URL: http://www.accessecon.com/pubs/EB/2002/Volume3/EB-01C10005A.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Rao, C. Radhakrishna, 1973. "Representations of best linear unbiased estimators in the Gauss-Markoff model with a singular dispersion matrix," Journal of Multivariate Analysis, Elsevier, vol. 3(3), pages 276-292, September.
    2. Harry Haupt & Walter Oberhofer, 2000. "Estimation of Constrained Singular Seemingly Unrelated Regression Models," Econometric Society World Congress 2000 Contributed Papers 0398, Econometric Society.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Haupt, Harry & Oberhofer, Walter, 2006. "Generalized adding-up in systems of regression equations," Economics Letters, Elsevier, vol. 92(2), pages 263-269, August.
    2. Yongge Tian & M. Beisiegel & E. Dagenais & C. Haines, 2008. "On the natural restrictions in the singular Gauss–Markov model," Statistical Papers, Springer, vol. 49(3), pages 553-564, July.
    3. Haupt, Harry & Oberhofer, Walter, 2006. "Best affine unbiased representations of the fully restricted general Gauss-Markov model," Journal of Multivariate Analysis, Elsevier, vol. 97(3), pages 759-764, March.
    4. Yuqin Sun & Rong Ke & Yongge Tian, 2014. "Some overall properties of seemingly unrelated regression models," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 98(2), pages 103-120, April.
    5. Tian, Yongge & Jiang, Bo, 2016. "Equalities for estimators of partial parameters under linear model with restrictions," Journal of Multivariate Analysis, Elsevier, vol. 143(C), pages 299-313.
    6. repec:ebl:ecbull:v:3:y:2005:i:54:p:1-3 is not listed on IDEAS
    7. Harry Haupt & Walter Oberhofer, 2005. "On autoregressive errors in singular systems of equations," Economics Bulletin, AccessEcon, vol. 3(54), pages 1-3.
    8. Kunkler, Michael, 2023. "Multilateral exchange rates: A multivariate regression framework," Journal of Economics and Business, Elsevier, vol. 125.
    9. Yongge Tian, 2010. "On equalities of estimations of parametric functions under a general linear model and its restricted models," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 72(3), pages 313-330, November.
    10. Ren, Xingwei, 2014. "On the equivalence of the BLUEs under a general linear model and its restricted and stochastically restricted models," Statistics & Probability Letters, Elsevier, vol. 90(C), pages 1-10.
    11. Ren, Xingwei, 2016. "Estimation in singular linear models with stepwise inclusion of linear restrictions," Journal of Multivariate Analysis, Elsevier, vol. 148(C), pages 60-72.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. repec:ebl:ecbull:v:3:y:2002:i:1:p:1-7 is not listed on IDEAS
    2. Haupt, Harry & Oberhofer, Walter, 2006. "Best affine unbiased representations of the fully restricted general Gauss-Markov model," Journal of Multivariate Analysis, Elsevier, vol. 97(3), pages 759-764, March.
    3. Guang Jing Song & Qing Wen Wang, 2014. "On the weighted least-squares, the ordinary least-squares and the best linear unbiased estimators under a restricted growth curve model," Statistical Papers, Springer, vol. 55(2), pages 375-392, May.
    4. Yongge Tian & Jieping Zhang, 2011. "Some equalities for estimations of partial coefficients under a general linear regression model," Statistical Papers, Springer, vol. 52(4), pages 911-920, November.
    5. Changli Lu & Yuqin Sun & Yongge Tian, 2013. "On relations between weighted least-squares estimators of parametric functions under a general partitioned linear model and its small models," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 76(5), pages 707-722, July.
    6. Ignacio, Escañuela Romana, 2019. "The elasticities of passenger transport demand in the Northeast Corridor," Research in Transportation Economics, Elsevier, vol. 78(C).
    7. Yongge Tian, 2017. "Transformation approaches of linear random-effects models," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 26(4), pages 583-608, November.
    8. Lu, Changli & Gan, Shengjun & Tian, Yongge, 2015. "Some remarks on general linear model with new regressors," Statistics & Probability Letters, Elsevier, vol. 97(C), pages 16-24.
    9. Alan J. Rogers, 2013. "Concentration Ellipsoids, Their Planes of Support, and the Linear Regression Model," Econometric Reviews, Taylor & Francis Journals, vol. 32(2), pages 220-243, February.
    10. He, Daojiang & Wu, Jie, 2014. "Admissible linear estimators of multivariate regression coefficient with respect to an inequality constraint under matrix balanced loss function," Journal of Multivariate Analysis, Elsevier, vol. 129(C), pages 37-43.
    11. Jürgen Groß, 2004. "The general Gauss-Markov model with possibly singular dispersion matrix," Statistical Papers, Springer, vol. 45(3), pages 311-336, July.
    12. T. Caliński & S. Czajka & Z. Kaczmarek & P. Krajewski & W. Pilarczyk & I. Siatkowski & M. Siatkowski, 2017. "On a mixed model analysis of multi-environment variety trials: a reconsideration of the one-stage and the two-stage models and analyses," Statistical Papers, Springer, vol. 58(2), pages 433-465, June.
    13. Tian, Yongge, 2009. "On an additive decomposition of the BLUE in a multiple-partitioned linear model," Journal of Multivariate Analysis, Elsevier, vol. 100(4), pages 767-776, April.
    14. Dong, Baomin & Guo, Wenxing & Tian, Yongge, 2014. "On relations between BLUEs under two transformed linear models," Journal of Multivariate Analysis, Elsevier, vol. 131(C), pages 279-292.
    15. Nesrin Güler & Melek Eriş Büyükkaya & Melike Yiğit, 2022. "Comparison of Covariance Matrices of Predictors in Seemingly Unrelated Regression Models," Indian Journal of Pure and Applied Mathematics, Springer, vol. 53(3), pages 801-809, September.
    16. Stephen Haslett & Simo Puntanen, 2011. "On the equality of the BLUPs under two linear mixed models," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 74(3), pages 381-395, November.
    17. S. J. Haslett & X. Q. Liu & A. Markiewicz & S. Puntanen, 2020. "Some properties of linear sufficiency and the BLUPs in the linear mixed model," Statistical Papers, Springer, vol. 61(1), pages 385-401, February.
    18. Huang, Yunying & Zheng, Bing, 2015. "The additive and block decompositions about the WLSEs of parametric functions for a multiple partitioned linear regression model," Journal of Multivariate Analysis, Elsevier, vol. 133(C), pages 123-135.
    19. Ren, Xingwei, 2014. "On the equivalence of the BLUEs under a general linear model and its restricted and stochastically restricted models," Statistics & Probability Letters, Elsevier, vol. 90(C), pages 1-10.
    20. Yongge Tian & Wenxing Guo, 2016. "On comparison of dispersion matrices of estimators under a constrained linear model," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 25(4), pages 623-649, November.
    21. Bo Jiang & Yuqin Sun, 2019. "On the equality of estimators under a general partitioned linear model with parameter restrictions," Statistical Papers, Springer, vol. 60(1), pages 273-292, February.

    More about this item

    Keywords

    Restricted least squares Adding-up Singularity Wald-Test SUR.;

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General

    Statistics

    Access and download statistics

    Corrections

    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:ebl:ecbull:eb-01c10005. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: John P. Conley (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.