IDEAS home Printed from https://ideas.repec.org/p/upf/upfgen/127.html
   My bibliography  Save this paper

Compact matrix expressions for generalized Wald tests of equality of moment vectors

Author

Listed:

Abstract

Asymptotic chi-squared test statistics for testing the equality of moment vectors are developed. The test statistics proposed are generalized Wald test statistics that specialize for different settings by inserting and appropriate asymptotic variance matrix of sample moments. Scaled test statistics are also considered for dealing with situations of non-iid sampling. The specialization will be carried out for testing the equality of multinomial populations, and the equality of variance and correlation matrices for both normal and non-normal data. When testing the equality of correlation matrices, a scaled version of the normal theory chi-squared statistic is proven to be an asymptotically exact chi-squared statistic in the case of elliptical data.

Suggested Citation

  • Albert Satorra & Heinz Neudecker, 1995. "Compact matrix expressions for generalized Wald tests of equality of moment vectors," Economics Working Papers 127, Department of Economics and Business, Universitat Pompeu Fabra.
    • Handle: RePEc:upf:upfgen:127
    as

    Download full text from publisher

    File URL: https://econ-papers.upf.edu/papers/127.pdf
    File Function: Whole Paper
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Andrews, Donald W. K., 1987. "Asymptotic Results for Generalized Wald Tests," Econometric Theory, Cambridge University Press, vol. 3(3), pages 348-358, June.
    2. Neudecker, Heinz & Satorra, Albert, 1996. "The algebraic equality of two asymptotic tests for the hypothesis that a normal distribution has a specified correlation matrix," Statistics & Probability Letters, Elsevier, vol. 30(2), pages 99-103, October.
    3. Wilson, Jeffrey R & Koehler, Kenneth J, 1991. "Hierarchical Models for Cross-Classified Overdispersed Multinomial Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 9(1), pages 103-110, January.
    Full references (including those not matched with items on IDEAS)

    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. Kleibergen, Frank & Paap, Richard, 2006. "Generalized reduced rank tests using the singular value decomposition," Journal of Econometrics, Elsevier, vol. 133(1), pages 97-126, July.
    2. Peñaranda, Francisco & Sentana, Enrique, 2012. "Spanning tests in return and stochastic discount factor mean–variance frontiers: A unifying approach," Journal of Econometrics, Elsevier, vol. 170(2), pages 303-324.
    3. Kim, Jinyong & Kim, Kun Ho & Lee, Jeong Hwan, 2021. "Cross-sectional tests of asset pricing models with full-rank mimicking portfolios," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    4. Christoph Breunig & Stefan Hoderlein, 2016. "Nonparametric Specification Testing in Random Parameter Models," Boston College Working Papers in Economics 897, Boston College Department of Economics.
    5. Gabriele Fiorentini & Enrique Sentana, 2021. "Specification tests for non‐Gaussian maximum likelihood estimators," Quantitative Economics, Econometric Society, vol. 12(3), pages 683-742, July.
    6. Christoph Breunig & Stefan Hoderlein, 2018. "Specification testing in random coefficient models," Quantitative Economics, Econometric Society, vol. 9(3), pages 1371-1417, November.
    7. Komunjer, Ivana & Zhu, Yinchu, 2020. "Likelihood ratio testing in linear state space models: An application to dynamic stochastic general equilibrium models," Journal of Econometrics, Elsevier, vol. 218(2), pages 561-586.
    8. Joakim Westerlund & Milda Norkutė & Ovidijus Stauskas, 2022. "The factor analytical approach in trending near unit root panels," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(3), pages 501-508, May.
    9. Xu, Ke-Li, 2018. "A semi-nonparametric estimator of regression discontinuity design with discrete duration outcomes," Journal of Econometrics, Elsevier, vol. 206(1), pages 258-278.
    10. Guerron-Quintana, Pablo & Inoue, Atsushi & Kilian, Lutz, 2017. "Impulse response matching estimators for DSGE models," Journal of Econometrics, Elsevier, vol. 196(1), pages 144-155.
    11. Geert Dhaene & Olivier Scaillet, 2000. "Reversed Score and Likelihood Ratio Tests," Econometric Society World Congress 2000 Contributed Papers 1746, Econometric Society.
    12. Gouriéroux, Christian & Monfort, Alain & Renne, Jean-Paul, 2017. "Statistical inference for independent component analysis: Application to structural VAR models," Journal of Econometrics, Elsevier, vol. 196(1), pages 111-126.
    13. Hiroyuki Kasahara & Katsumi Shimotsu, 2014. "Non-parametric identification and estimation of the number of components in multivariate mixtures," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 76(1), pages 97-111, January.
    14. Kentaro Hayashi & Akihito Kamata, 2005. "A note on the estimator of the alpha coefficient for standardized variables under normality," Psychometrika, Springer;The Psychometric Society, vol. 70(3), pages 579-586, September.
    15. Myoung‐jae Lee, 2008. "Method‐of‐moment view of linear simultaneous equation systems," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 62(2), pages 230-238, May.
    16. Joan Alegre & Juan Carlos Escanciano, 2023. "Robust Minimum Distance Inference in Structural Models," Papers 2310.05761, arXiv.org.
    17. Lanne, Markku & Saikkonen, Pentti, 2007. "A Multivariate Generalized Orthogonal Factor GARCH Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 61-75, January.
    18. Lee, Wei-Ming & Kuan, Chung-Ming & Hsu, Yu-Chin, 2014. "Testing over-identifying restrictions without consistent estimation of the asymptotic covariance matrix," Journal of Econometrics, Elsevier, vol. 181(2), pages 181-193.
    19. Zaka Ratsimalahelo, 2003. "Rank Test Based On Matrix Perturbation Theory," Econometrics 0306008, University Library of Munich, Germany.
    20. Lütkepohl, Helmut & Staszewska-Bystrova, Anna & Winker, Peter, 2020. "Constructing joint confidence bands for impulse response functions of VAR models – A review," Econometrics and Statistics, Elsevier, vol. 13(C), pages 69-83.

    More about this item

    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:upf:upfgen:127. 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: the person in charge (email available below). General contact details of provider: http://www.econ.upf.edu/ .

    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.