IDEAS home Printed from https://ideas.repec.org/p/ver/wpaper/15-2010.html
   My bibliography  Save this paper

Negative variance estimates in panel data models

Author

Listed:
  • Laura Magazzini

    (Department of Economics (University of Verona))

  • Giorgio Calzolari

    (University of Florence)

Abstract

Negative values for estimated variances can arise in a panel data context. Empirical and theoretical literature dismisses the problem as not serious and a practical solution is to replace negative variances by its boundary value, i.e. zero. While this is not a concern when the individual variance components is "small" with respect to idiosyncratic variance component (making it indistinguishable from zero in practice), we claim that a negative estimated variance can also arise with a "large" individual variance component, when the orthogonality condition between the individual effects and regressors fails. Estimation problems are considered in the (feasible) generalized least squares and maximum likelihood frameworks.

Suggested Citation

  • Laura Magazzini & Giorgio Calzolari, 2010. "Negative variance estimates in panel data models," Working Papers 15/2010, University of Verona, Department of Economics.
    • Handle: RePEc:ver:wpaper:15/2010
    as

    Download full text from publisher

    File URL: http://dse.univr.it//workingpapers/WP1510.pdf
    File Function: First version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Berzeg, Korhan, 1979. "The error components model : Conditions for the existence of the maximum likelihood estimates," Journal of Econometrics, Elsevier, vol. 10(1), pages 99-102, April.
    2. Fuller, Wayne A. & Battese, George E., 1974. "Estimation of linear models with crossed-error structure," Journal of Econometrics, Elsevier, vol. 2(1), pages 67-78, May.
    3. Hausman, Jerry, 2015. "Specification tests in econometrics," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 38(2), pages 112-134.
    4. Maddala, G S, 1971. "The Use of Variance Components Models in Pooling Cross Section and Time Series Data," Econometrica, Econometric Society, vol. 39(2), pages 341-358, March.
    5. Swamy, P A V B & Arora, S S, 1972. "The Exact Finite Sample Properties of the Estimators of Coefficients in the Error Components Regression Models," Econometrica, Econometric Society, vol. 40(2), pages 261-275, March.
    6. Amemiya, Takeshi, 1971. "The Estimation of the Variances in a Variance-Components Model," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 12(1), pages 1-13, February.
    7. Schreiber Sven, 2008. "The Hausman Test Statistic can be Negative even Asymptotically," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 228(4), pages 394-405, August.
    8. Wallace, T D & Hussain, Ashiq, 1969. "The Use of Error Components Models in Combining Cross Section with Time Series Data," Econometrica, Econometric Society, vol. 37(1), pages 55-72, January.
    9. Arellano, Manuel, 2003. "Panel Data Econometrics," OUP Catalogue, Oxford University Press, number 9780199245291.
    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. Psychoyios, Dimitrios & Missiou, Olympia & Dergiades, Theologos, 2021. "Energy based estimation of the shadow economy: The role of governance quality," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 797-808.
    2. Xiaobing Le & Xinxin Shao & Kuo Gao, 2023. "The Relationship between Urbanization and Consumption Upgrading of Rural Residents under the Sustainable Development: An Empirical Study Based on Mediation Effect and Threshold Effect," Sustainability, MDPI, vol. 15(10), pages 1-19, May.

    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. Marius C. O. Amba, 2021. "Simultaneous Equations with Three Way Error Components," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(3), pages 583-596, September.
    2. Badi H. Baltagi, 1987. "On Estimating from a More General Time-Series Cum Cross-Section Data Structure," The American Economist, Sage Publications, vol. 31(2), pages 69-71, October.
    3. Dong Kim, 2012. "What is an oil shock? Panel data evidence," Empirical Economics, Springer, vol. 43(1), pages 121-143, August.
    4. repec:jss:jstsof:27:i02 is not listed on IDEAS
    5. Baltagi, Badi H. & Pirotte, Alain, 2010. "Panel data inference under spatial dependence," Economic Modelling, Elsevier, vol. 27(6), pages 1368-1381, November.
    6. Subhash C. Sharma & Anil K. Bera, 2021. "Estimation of Random Components and Prediction in One and Two-Way Error Component Regression Models," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 419-441, December.
    7. Psychoyios, Dimitrios & Missiou, Olympia & Dergiades, Theologos, 2021. "Energy based estimation of the shadow economy: The role of governance quality," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 797-808.
    8. Marcel die Dama & Boniface ngah Epo & Galex syrie Soh, 2013. "Developing a two way error component estimation model with disturbances following a special autoregressive (4) for quarterly data," Economics Bulletin, AccessEcon, vol. 33(1), pages 625-634.
    9. Hamid Beladi & Nicholas S. P. Tay & Reza Oladi, 2011. "On Competition for Listings," Working Papers 0003, College of Business, University of Texas at San Antonio.
    10. Issler, João Victor & Lima, Luiz Renato, 2009. "A panel data approach to economic forecasting: The bias-corrected average forecast," Journal of Econometrics, Elsevier, vol. 152(2), pages 153-164, October.
    11. G.A. Karathanassis & A.A. Drakos, 2004. "A note on equity ownership and corporate value in Greece," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 25(8), pages 537-547.
    12. Jan Ámos Víšek, 2015. "Estimating the Model with Fixed and Random Effects by a Robust Method," Methodology and Computing in Applied Probability, Springer, vol. 17(4), pages 999-1014, December.
    13. Rachel A. Rosenfeld & Franã‡Ois Nielsen, 1984. "Inequality and Careers," Sociological Methods & Research, , vol. 12(3), pages 279-321, February.
    14. Adrian C. Darnell, 1994. "A Dictionary Of Econometrics," Books, Edward Elgar Publishing, number 118.
    15. Croissant, Yves & Millo, Giovanni, 2008. "Panel Data Econometrics in R: The plm Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 27(i02).
    16. Ahn, Seung C. & Lee, Young H. & Schmidt, Peter, 2013. "Panel data models with multiple time-varying individual effects," Journal of Econometrics, Elsevier, vol. 174(1), pages 1-14.
    17. Esfandiar Maasoumi & Almas Heshmati & Inhee Lee, 2021. "Green innovations and patenting renewable energy technologies," Empirical Economics, Springer, vol. 60(1), pages 513-538, January.
    18. Baltagi, Badi H. & Blien, Uwe, 1998. "The German wage curve: evidence from the IAB employment sample," Economics Letters, Elsevier, vol. 61(2), pages 135-142, November.
    19. Swarnjit S. Arora, 1973. "Error Components Regression Models and Their Applications," NBER Working Papers 0003, National Bureau of Economic Research, Inc.
    20. Juan Carlos Bou & Albert Satorra, 2014. "Univariate versus multivariate modeling of panel data," Economics Working Papers 1417, Department of Economics and Business, Universitat Pompeu Fabra.
    21. Dagher, Leila & Bird, Lori & Heeter, Jenny, 2017. "Residential green power demand in the United States," Renewable Energy, Elsevier, vol. 114(PB), pages 1062-1068.

    More about this item

    Keywords

    Panel data; random effect estimation; negative variances; maximum likelihood;
    All these keywords.

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:ver:wpaper:15/2010. 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: Michael Reiter (email available below). General contact details of provider: https://edirc.repec.org/data/isverit.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.