IDEAS home Printed from https://ideas.repec.org/p/nbr/nberte/0094.html
   My bibliography  Save this paper

Heteroscedasticity Diagnostics Based on "Corrected" Standard Errors

Author

Listed:
  • Edward E. Leamer

Abstract

Weights are found for weighted least squares estimates such that a selected coefficient (a) changes by one standard deviation or (b) changes in sign. The length of the vector of weight changes is equal to the usual OLS standard error divided by the White-corrected standard errors. Thus the White-corrected standard errors can help decide if it is necessary to adjust the location of the confidence sets to correct for heteroscedasticity. The vector of weight changes is similar to the effect of omitting observations, one at a time. The sensitivity diagnostics of Belsley, Kuh and Welsch are therefore linked with heteroscedasticity issues.

Suggested Citation

  • Edward E. Leamer, 1991. "Heteroscedasticity Diagnostics Based on "Corrected" Standard Errors," NBER Technical Working Papers 0094, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberte:0094
    Note: PE
    as

    Download full text from publisher

    File URL: http://www.nber.org/papers/t0094.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. 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.
    2. Leamer, Edward E & Leonard, Herman B, 1983. "Reporting the Fragility of Regression Estimates," The Review of Economics and Statistics, MIT Press, vol. 65(2), pages 306-317, May.
    3. Edward E. Leamer, 1983. "Global Sensitivity Results for Generalized Least Squares Estimates," UCLA Economics Working Papers 006, UCLA Department of Economics.
    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. Adrian C. Darnell, 1994. "A Dictionary Of Econometrics," Books, Edward Elgar Publishing, number 118.
    2. Leroi RAPUTSOANE, 2016. "Financial Stress Indicator Variables and Monetary Policy in South Africa," Journal of Economics Bibliography, KSP Journals, vol. 3(2), pages 203-214, June.
    3. Stephan B. Bruns, 2013. "Identifying Genuine Effects in Observational Research by Means of Meta-Regressions," Jena Economics Research Papers 2013-040, Friedrich-Schiller-University Jena.
    4. Guo, Li-Yang & Feng, Chao & Yang, Jun, 2022. "Can energy predict the regional prices of carbon emission allowances in China?," International Review of Financial Analysis, Elsevier, vol. 82(C).
    5. Luc Anselin, 1988. "Model Validation in Spatial Econometrics: A Review and Evaluation of Alternative Approaches," International Regional Science Review, , vol. 11(3), pages 279-316, December.
    6. Dominik Schreyer, 2019. "Football spectator no-show behaviour in the German Bundesliga," Applied Economics, Taylor & Francis Journals, vol. 51(45), pages 4882-4901, September.
    7. S. Arunachalam & Sridhar N. Ramaswami & Pol Herrmann & Doug Walker, 2018. "Innovation pathway to profitability: the role of entrepreneurial orientation and marketing capabilities," Journal of the Academy of Marketing Science, Springer, vol. 46(4), pages 744-766, July.
    8. Timothy Erickson & Toni M. Whited, 2000. "Measurement Error and the Relationship between Investment and q," Journal of Political Economy, University of Chicago Press, vol. 108(5), pages 1027-1057, October.
    9. Paul W. Miller & Barry R. Chiswick, 2002. "Immigrant earnings: Language skills, linguistic concentrations and the business cycle," Journal of Population Economics, Springer;European Society for Population Economics, vol. 15(1), pages 31-57.
    10. Fors, Gunnar & Zejan, Mario, 1996. "Overseas R&D by Multinationals in foreign Centers of Excellence," SSE/EFI Working Paper Series in Economics and Finance 111, Stockholm School of Economics.
    11. Rodrigo M. S. Moita & Claudio Paiva, 2013. "Political Price Cycles in Regulated Industries: Theory and Evidence," American Economic Journal: Economic Policy, American Economic Association, vol. 5(1), pages 94-121, February.
    12. Evens Salies & Catherine Waddams, 2003. "Pricing structure in the deregulated UK electricity market," SciencePo Working papers Main hal-03592457, HAL.
    13. Butler, Marty & Leone, Andrew J. & Willenborg, Michael, 2004. "An empirical analysis of auditor reporting and its association with abnormal accruals," Journal of Accounting and Economics, Elsevier, vol. 37(2), pages 139-165, June.
    14. Baiyegunhi, L.J.S. & Oppong, B.B., 2016. "Commercialisation of mopane worm (Imbrasia belina) in rural households in Limpopo Province, South Africa," Forest Policy and Economics, Elsevier, vol. 62(C), pages 141-148.
    15. MacKinnon, J G, 1989. "Heteroskedasticity-Robust Tests for Structural Change," Empirical Economics, Springer, vol. 14(2), pages 77-92.
    16. Fenech, Jean-Pierre & Skully, Michael & Xuguang, Han, 2014. "Franking credits and market reactions: Evidence from the Australian convertible security market," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 32(C), pages 1-19.
    17. François Desmoulins-Lebeault & Jean-François Gajewski & Luc Meunier, 2018. "Personality and Risk Aversion," Economics Bulletin, AccessEcon, vol. 38(1), pages 472-489.
    18. Benjamin M. Blau & Ryan J. Whitby, 2014. "Speculative Trading In Reits," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 37(1), pages 55-74, February.
    19. Bliss, Mark A. & Gul, Ferdinand A., 2012. "Political connection and leverage: Some Malaysian evidence," Journal of Banking & Finance, Elsevier, vol. 36(8), pages 2344-2350.
    20. Gu, Chen & Kurov, Alexander & Wolfe, Marketa Halova, 2018. "Relief Rallies after FOMC Announcements as a Resolution of Uncertainty," Journal of Empirical Finance, Elsevier, vol. 49(C), pages 1-18.

    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:nbr:nberte:0094. 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: https://edirc.repec.org/data/nberrus.html .

    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.