IDEAS home Printed from https://ideas.repec.org/a/vrs/stintr/v19y2018i3p433-452n7.html
   My bibliography  Save this article

Dealing With Heteroskedasticity Within The Modeling Of The Quality Of Life Of Older People

Author

Listed:
  • Jabłońska Katarzyna

    (Department of Medical Sociology, Chair of Epidemiology and Preventive Medicine, Jagiellonian University Medical College, Kopernika 7a, 31-034 Krakow, Poland)

Abstract

Using the estimation method of ordinary least squares leads to unreliable results in the case of heteroskedastic linear regression model. Other estimation methods are described, including weighted least squares, division of the sample and heteroskedasticity-consistent covariance matrix estimators, all of which can give estimators with better properties than ordinary least squares. The methods are presented giving the example of modelling quality of life of older people, based on a data set from the first wave of the COURAGE – Poland study. The comparison of estimators and their practical application may teach how to choose methodologically the most appropriate estimation tool after detection of heteroscedasticity.

Suggested Citation

  • Jabłońska Katarzyna, 2018. "Dealing With Heteroskedasticity Within The Modeling Of The Quality Of Life Of Older People," Statistics in Transition New Series, Statistics Poland, vol. 19(3), pages 433-452, September.
    • Handle: RePEc:vrs:stintr:v:19:y:2018:i:3:p:433-452:n:7
    DOI: 10.21307/stattrans-2018-024
    as

    Download full text from publisher

    File URL: https://doi.org/10.21307/stattrans-2018-024
    Download Restriction: no
    File URL: https://libkey.io/10.21307/stattrans-2018-024?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Cribari-Neto, Francisco, 2004. "Asymptotic inference under heteroskedasticity of unknown form," Computational Statistics & Data Analysis, Elsevier, vol. 45(2), pages 215-233, March.
    2. Francisco Cribari-Neto & Wilton Silva, 2011. "A new heteroskedasticity-consistent covariance matrix estimator for the linear regression model," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 95(2), pages 129-146, June.
    3. White, Halbert, 1980. "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity," Econometrica, Econometric Society, vol. 48(4), pages 817-838, May.
    4. Chesher, Andrew & Jewitt, Ian, 1987. "The Bias of a Heteroskedasticity Consistent Covariance Matrix Estimator," Econometrica, Econometric Society, vol. 55(5), pages 1217-1222, September.
    5. 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.
    6. Cragg, John G, 1983. "More Efficient Estimation in the Presence of Heteroscedasticity of Unknown Form," Econometrica, Econometric Society, vol. 51(3), pages 751-763, May.
    7. 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.
    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. Katarzyna Jabłońska, 2018. "Dealing With Heteroskedasticity Within The Modeling Of The Quality Of Life Of Older People," Statistics in Transition New Series, Polish Statistical Association, vol. 19(3), pages 423-452, September.
    2. Romano, Joseph P. & Wolf, Michael, 2017. "Resurrecting weighted least squares," Journal of Econometrics, Elsevier, vol. 197(1), pages 1-19.
    3. Eric S. Lin & Ta-Sheng Chou, 2018. "Finite-sample refinement of GMM approach to nonlinear models under heteroskedasticity of unknown form," Econometric Reviews, Taylor & Francis Journals, vol. 37(1), pages 1-28, January.
    4. Pötscher, Benedikt M. & Preinerstorfer, David, 2021. "Valid Heteroskedasticity Robust Testing," MPRA Paper 107420, University Library of Munich, Germany.
    5. Pötscher, Benedikt M. & Preinerstorfer, David, 2023. "How Reliable Are Bootstrap-Based Heteroskedasticity Robust Tests?," Econometric Theory, Cambridge University Press, vol. 39(4), pages 789-847, August.
    6. Hartigan, Luke, 2018. "Alternative HAC covariance matrix estimators with improved finite sample properties," Computational Statistics & Data Analysis, Elsevier, vol. 119(C), pages 55-73.
    7. Richard H. Spady & Sami Stouli, 2018. "Simultaneous Mean-Variance Regression," Bristol Economics Discussion Papers 18/697, School of Economics, University of Bristol, UK.
    8. Cheng, Tsung-Chi, 2012. "On simultaneously identifying outliers and heteroscedasticity without specific form," Computational Statistics & Data Analysis, Elsevier, vol. 56(7), pages 2258-2272.
    9. Francisco Cribari-Neto & Maria da Gloria Lima, 2010. "Approximate inference in heteroskedastic regressions: A numerical evaluation," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(4), pages 591-615.
    10. Kenneth W. Clements & H. Y. Izan & Yihui Lan, 2009. "A Stochastic Measure of International Competitiveness," International Review of Finance, International Review of Finance Ltd., vol. 9(1‐2), pages 51-81, March.
    11. Michael O'Hara & Christopher F. Parmeter, 2013. "Nonparametric Generalized Least Squares in Applied Regression Analysis," Pacific Economic Review, Wiley Blackwell, vol. 18(4), pages 456-474, October.
    12. Francisco Cribari-Neto & Wilton Silva, 2011. "A new heteroskedasticity-consistent covariance matrix estimator for the linear regression model," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 95(2), pages 129-146, June.
    13. Emmanuel Flachaire, 2005. "More Efficient Tests Robust to Heteroskedasticity of Unknown Form," Econometric Reviews, Taylor & Francis Journals, vol. 24(2), pages 219-241.
    14. Sin, C.Y. (Chor-yiu) & Lee, Cheng-Few, 2021. "Using heteroscedasticity-non-consistent or heteroscedasticity-consistent variances in linear regression," Econometrics and Statistics, Elsevier, vol. 18(C), pages 117-142.
    15. repec:bla:ecorec:v:64:y:1988:i:185:p:81-101 is not listed on IDEAS
    16. James G. MacKinnon, 2012. "Thirty Years Of Heteroskedasticity-robust Inference," Working Paper 1268, Economics Department, Queen's University.
    17. Paul Dudgeon, 2017. "Some Improvements in Confidence Intervals for Standardized Regression Coefficients," Psychometrika, Springer;The Psychometric Society, vol. 82(4), pages 928-951, December.
    18. José Curto & José Pinto & Ana Morais & Isabel Lourenço, 2011. "The heteroskedasticity-consistent covariance estimator in accounting," Review of Quantitative Finance and Accounting, Springer, vol. 37(4), pages 427-449, November.
    19. MacKinnon, James G, 1992. "Model Specification Tests and Artificial Regressions," Journal of Economic Literature, American Economic Association, vol. 30(1), pages 102-146, March.
    20. Francisco Cribari-Neto & Maria Lima, 2010. "Sequences of bias-adjusted covariance matrix estimators under heteroskedasticity of unknown form," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 62(6), pages 1053-1082, December.
    21. MacKinnon, J G, 1989. "Heteroskedasticity-Robust Tests for Structural Change," Empirical Economics, Springer, vol. 14(2), pages 77-92.

    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:vrs:stintr:v:19:y:2018:i:3:p:433-452:n:7. 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: Peter Golla (email available below). General contact details of provider: https://stat.gov.pl/en/ .

    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.