IDEAS home Printed from
   My bibliography  Save this paper

Adaptive Estimation in the Panel Data Error Component Model with Heteroskedasticity of Unknown Form


  • Stengos, T.
  • Li, Q.


The authors show that the adaptive estimation result for the heteroskedasticity of an unknown form time-series (or cross-section) model can be generalized to the panel data error components model. The authors give recursive transformations that change the error term of a random effects model and the first differenced error term of a fixed effects model into classical errors. They also propose a modified Breusch-Pagan test for testing the random individual effects. Monte Carlo evidence suggests that the proposed estimator performs adequately in small samples. Copyright 1994 by Economics Department of the University of Pennsylvania and the Osaka University Institute of Social and Economic Research Association.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Stengos, T. & Li, Q., 1993. "Adaptive Estimation in the Panel Data Error Component Model with Heteroskedasticity of Unknown Form," Working Papers 1993-4, University of Guelph, Department of Economics and Finance.
  • Handle: RePEc:gue:guelph:1993-4

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Other versions of this item:

    References listed on IDEAS

    1. Apps, Patricia & Savage, Elizabeth, 1989. "Labour supply, welfare rankings and the measurement of inequality," Journal of Public Economics, Elsevier, vol. 39(3), pages 335-364, August.
    2. Killingsworth, Mark R. & Heckman, James J., 1987. "Female labor supply: A survey," Handbook of Labor Economics,in: O. Ashenfelter & R. Layard (ed.), Handbook of Labor Economics, edition 1, volume 1, chapter 2, pages 103-204 Elsevier.
    3. Manser, Marilyn & Brown, Murray, 1980. "Marriage and Household Decision-Making: A Bargaining Analysis," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 21(1), pages 31-44, February.
    4. Apps, Patricia F. & Rees, Ray, 1988. "Taxation and the household," Journal of Public Economics, Elsevier, vol. 35(3), pages 355-369, April.
    5. Rees, Ray, 1988. "Taxation and the Household," Munich Reprints in Economics 3411, University of Munich, Department of Economics.
    6. Pollak, Robert A & Wales, Terence J, 1979. "Welfare Comparisons and Equivalence Scales," American Economic Review, American Economic Association, vol. 69(2), pages 216-221, May.
    7. Chiappori, Pierre-Andre, 1988. "Rational Household Labor Supply," Econometrica, Econometric Society, vol. 56(1), pages 63-90, January.
    8. Mroz, Thomas A, 1987. "The Sensitivity of an Empirical Model of Married Women's Hours of Work to Economic and Statistical Assumptions," Econometrica, Econometric Society, vol. 55(4), pages 765-799, July.
    9. Chiappori, Pierre-Andre, 1992. "Collective Labor Supply and Welfare," Journal of Political Economy, University of Chicago Press, vol. 100(3), pages 437-467, June.
    10. Patricia Apps & Glenn Jones, 1986. "Selective taxation of couples," Journal of Economics, Springer, vol. 5(1), pages 1-15, December.
    11. Deaton, Angus S & Muellbauer, John, 1980. "An Almost Ideal Demand System," American Economic Review, American Economic Association, vol. 70(3), pages 312-326, June.
    12. Mark R. Killingsworth, 1987. "Heterogeneous Preferences, Compensating Wage Differentials, and Comparable Worth," The Quarterly Journal of Economics, Oxford University Press, vol. 102(4), pages 727-742.
    13. McElroy, Marjorie B & Horney, Mary Jean, 1981. "Nash-Bargained Household Decisions: Toward a Generalization of the Theory of Demand," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 22(2), pages 333-349, June.
    14. Apps, Patricia, 1982. "Institutional inequality and tax incidence," Journal of Public Economics, Elsevier, vol. 18(2), pages 217-242, July.
    Full references (including those not matched with items on IDEAS)


    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.

    Cited by:

    1. Thanasis Stengos & Ximing Wu, 2005. "Partially Adaptive Estimation via Maximum Entropy Densities," University of Cyprus Working Papers in Economics 6-2005, University of Cyprus Department of Economics.
    2. Eduardo Fé, 2012. "Instrumental variable estimation of heteroskedasticity adaptive error component models," Statistical Papers, Springer, vol. 53(3), pages 577-615, August.
    3. Juhl, Ted & Sosa-Escudero, Walter, 2014. "Testing for heteroskedasticity in fixed effects models," Journal of Econometrics, Elsevier, vol. 178(P3), pages 484-494.
    4. Georges Bresson & Cheng Hsiao & Alain Pirotte, 2011. "Assessing the contribution of R&D to total factor productivity—a Bayesian approach to account for heterogeneity and heteroskedasticity," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 95(4), pages 435-452, December.
    5. Yiguo Sun & Thanasis Stengos, 2008. "The absolute health income hypothesis revisited: a semiparametric quantile regression approach," Empirical Economics, Springer, vol. 35(2), pages 395-412, September.
    6. Badi H. Baltagi & Peter H. Egger & Michaela Kesina, 2016. "Firm‐Level Productivity Spillovers in China's Chemical Industry: A Spatial Hausman‐Taylor Approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(1), pages 214-248, January.
    7. Nilanjana Roy, 2002. "Is Adaptive Estimation Useful For Panel Models With Heteroskedasticity In The Individual Specific Error Component? Some Monte Carlo Evidence," Econometric Reviews, Taylor & Francis Journals, vol. 21(2), pages 189-203.
    8. You, Jinhong & Zhou, Xian & Zhou, Yong, 2010. "Statistical inference for panel data semiparametric partially linear regression models with heteroscedastic errors," Journal of Multivariate Analysis, Elsevier, vol. 101(5), pages 1079-1101, May.
    9. Baltagi, Badi H. & Bresson, Georges & Pirotte, Alain, 2006. "Joint LM test for homoskedasticity in a one-way error component model," Journal of Econometrics, Elsevier, vol. 134(2), pages 401-417, October.
    10. Baltagi, Badi H. & Jung, Byoung Cheol & Song, Seuck Heun, 2010. "Testing for heteroskedasticity and serial correlation in a random effects panel data model," Journal of Econometrics, Elsevier, vol. 154(2), pages 122-124, February.
    11. Eduardo Fé Rodríguez, 2009. "Adaptive Instrumental Variable Estimation of Heteroskedastic Error Component Models," The School of Economics Discussion Paper Series 0921, Economics, The University of Manchester.
    12. Baltagi, Badi H. & Song, Seuck Heun & Kwon, Jae Hyeok, 2009. "Testing for heteroskedasticity and spatial correlation in a random effects panel data model," Computational Statistics & Data Analysis, Elsevier, vol. 53(8), pages 2897-2922, June.
    13. Platoni, Silvia & Sckokai, Paolo & Moro, Daniele, 2008. "Panel Data Estimation Techniques for Farm-level Data Model," 2008 International Congress, August 26-29, 2008, Ghent, Belgium 44268, European Association of Agricultural Economists.

    More about this item




    Access and download statistics


    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:gue:guelph:1993-4. 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: (Stephen Kosempel). General contact details of provider: .

    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.

    We have no references for this item. You can help adding them by using 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.