IDEAS home Printed from https://ideas.repec.org/a/eee/econom/v29y1985i3p305-325.html
   My bibliography  Save this article

Some heteroskedasticity-consistent covariance matrix estimators with improved finite sample properties

Author

Listed:
  • MacKinnon, James G.
  • White, Halbert

Abstract

We examine several modified versions of the heteroskedasticity-consistent covariance matrix estimator of Hinkley and White. On the basis of sampling experiments which compare the performance of quasi t statistics, we find that one estimator, based on the jackknife, performs better in small samples than the rest. We also examine finite-sample properties using modified critical values based on Edgeworth approximations, as proposed by Rothenberg. In addition, we compare the power of several tests for heteroskedasticity and find that it may be wise to employ the jackknife heteroskedasticity-consistent covariance matrix even in the absence of detected heteroskedasticity.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • MacKinnon, James G. & White, Halbert, 1985. "Some heteroskedasticity-consistent covariance matrix estimators with improved finite sample properties," Journal of Econometrics, Elsevier, vol. 29(3), pages 305-325, September.
  • Handle: RePEc:eee:econom:v:29:y:1985:i:3:p:305-325
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/0304-4076(85)90158-7
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Breusch, T S & Pagan, A R, 1979. "A Simple Test for Heteroscedasticity and Random Coefficient Variation," Econometrica, Econometric Society, vol. 47(5), pages 1287-1294, September.
    2. Koenker, Roger, 1981. "A note on studentizing a test for heteroscedasticity," Journal of Econometrics, Elsevier, vol. 17(1), pages 107-112, September.
    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. Dastoor, Naorayex K., 1997. "Testing for conditional heteroskedasticity with misspecified alternative hypotheses," Journal of Econometrics, Elsevier, vol. 82(1), pages 63-80.
    2. Richard H. Spady & Sami Stouli, 2018. "Simultaneous Mean-Variance Regression," Bristol Economics Discussion Papers 18/697, School of Economics, University of Bristol, UK.
    3. Machado, Jose A. F. & Silva, J. M. C. Santos, 2000. "Glejser's test revisited," Journal of Econometrics, Elsevier, vol. 97(1), pages 189-202, July.
    4. Kermit Daniel & Dan Black & Jeffery Smith, 1996. "College Characteristics and the Wages of Young Women," HEW 9604002, University Library of Munich, Germany.
    5. Michael O'Connor Keefe & David Gallagher, 2014. "Does the effect of revealed private information on initial public offering (IPO) first trading day return differ by IPO market heat?," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 54(3), pages 921-964, September.
    6. Guilhem Bascle, 2008. "Controlling for endogeneity with instrumental variables in strategic management research," Post-Print hal-00576795, HAL.
    7. Azimi, Mohammad Naim, 2016. "An economic growth model: Evaluating the interaction of market consumption with GDP growth rate in Afghanistan," MPRA Paper 69517, University Library of Munich, Germany, revised 11 Jan 2016.
    8. Jones, A.M, 2010. "Models For Health Care," Health, Econometrics and Data Group (HEDG) Working Papers 10/01, HEDG, c/o Department of Economics, University of York.
    9. Christopher F Baum & Mark E. Schaffer & Steven Stillman, 2003. "Instrumental variables and GMM: Estimation and testing," Stata Journal, StataCorp LP, vol. 3(1), pages 1-31, March.
    10. Pedro Delicado & Juan Romo, 1998. "Constant coefficient tests for random coefficient regression," Economics Working Papers 329, Department of Economics and Business, Universitat Pompeu Fabra.
    11. Gaynor, Martin & Anderson, Gerard F., 1995. "Uncertain demand, the structure of hospital costs, and the cost of empty hospital beds," Journal of Health Economics, Elsevier, vol. 14(3), pages 291-317, August.
    12. Dufour, Jean-Marie & Khalaf, Lynda & Bernard, Jean-Thomas & Genest, Ian, 2004. "Simulation-based finite-sample tests for heteroskedasticity and ARCH effects," Journal of Econometrics, Elsevier, vol. 122(2), pages 317-347, October.
    13. Kendix, Michael & Walls, W.D., 2010. "Oil industry consolidation and refined product prices: Evidence from US wholesale gasoline terminals," Energy Policy, Elsevier, vol. 38(7), pages 3498-3507, July.
    14. Born, Benjamin & Pfeifer, Johannes, 2014. "Policy risk and the business cycle," Journal of Monetary Economics, Elsevier, vol. 68(C), pages 68-85.
    15. Juhl, Ted & Sosa-Escudero, Walter, 2014. "Testing for heteroskedasticity in fixed effects models," Journal of Econometrics, Elsevier, vol. 178(P3), pages 484-494.
    16. LE GALLO, Julie, 2000. "Econométrie spatiale 2 -Hétérogénéité spatiale," LATEC - Document de travail - Economie (1991-2003) 2001-01, LATEC, Laboratoire d'Analyse et des Techniques EConomiques, CNRS UMR 5118, Université de Bourgogne.
    17. Fortin, Bernard & Ragued, Safa, 2017. "Does temporary interruption in postsecondary education induce a wage penalty? Evidence from Canada," Economics of Education Review, Elsevier, vol. 58(C), pages 108-122.
    18. van Dijk, Dick & Franses, Philip Hans & Lucas, Andre, 1999. "Testing for ARCH in the Presence of Additive Outliers," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 14(5), pages 539-562, Sept.-Oct.
    19. Zaman, Asad, 1995. "On the inconsistency of the Breusch-Pagan test," MPRA Paper 9904, University Library of Munich, Germany.
    20. Farbmacher, Helmut & Kögel, Heinrich, 2015. "Inference Problems under a Special Form of Heteroskedasticity," MEA discussion paper series 201503, Munich Center for the Economics of Aging (MEA) at the Max Planck Institute for Social Law and Social Policy.

    More about this item

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: 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:eee:econom:v:29:y:1985:i:3:p:305-325. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Nithya Sathishkumar). General contact details of provider: http://www.elsevier.com/locate/jeconom .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.