IDEAS home Printed from https://ideas.repec.org/a/taf/emetrv/v22y2003i1p29-58.html
   My bibliography  Save this article

Bias Correction in the Dynamic Panel Data Model with a Nonscalar Disturbance Covariance Matrix

Author

Listed:
  • Maurice J. G. Bun

Abstract

Approximation formulae are developed for the bias of ordinary and generalized Least Squares Dummy Variable (LSDV) estimators in dynamic panel data models. Results from Kiviet [Kiviet, J. F. (1995), on bias, inconsistency, and efficiency of various estimators in dynamic panel data models, J. Econometrics 68:53-78; Kiviet, J. F. (1999), Expectations of expansions for estimators in a dynamic panel data model: some results for weakly exogenous regressors, In: Hsiao, C., Lahiri, K., Lee, L-F., Pesaran, M. H., eds., Analysis of Panels and Limited Dependent Variables , Cambridge: Cambridge University Press, pp. 199-225] are extended to higher-order dynamic panel data models with general covariance structure. The focus is on estimation of both short- and long-run coefficients. The results show that proper modelling of the disturbance covariance structure is indispensable. The bias approximations are used to construct bias corrected estimators which are then applied to quarterly data from 14 European Union countries. Money demand functions for M 1, M 2 and M 3 are estimated for the EU area as a whole for the period 1991: I-1995: IV. Significant spillovers between countries are found reflecting the dependence of domestic money demand on foreign developments. The empirical results show that in general plausible long-run effects are obtained by the bias corrected estimators. Moreover, finite sample bias, although of moderate magnitude, is present underlining the importance of more refined estimation techniques. Also the efficiency gains by exploiting the heteroscedasticity and cross-correlation patterns between countries are sometimes considerable.

Suggested Citation

  • Maurice J. G. Bun, 2003. "Bias Correction in the Dynamic Panel Data Model with a Nonscalar Disturbance Covariance Matrix," Econometric Reviews, Taylor & Francis Journals, vol. 22(1), pages 29-58, February.
    • Handle: RePEc:taf:emetrv:v:22:y:2003:i:1:p:29-58
    DOI: 10.1081/ETC-120017973
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1081/ETC-120017973
    Download Restriction: Access to full text is restricted to subscribers.

    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. Kajal Lahiri, 2005. "Analysis of Panel Data," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 87(4), pages 1093-1095.
    2. Kiviet, Jan F. & Phillips, Garry D. A. & Schipp, Bernhard, 1995. "The bias of OLS, GLS, and ZEF estimators in dynamic seemingly unrelated regression models," Journal of Econometrics, Elsevier, vol. 69(1), pages 241-266, September.
    3. Carlo C. A. Winder & Martin M. G. Fase, 1998. "Wealth and the demand for money in the European union," Empirical Economics, Springer, vol. 23(3), pages 507-524.
    4. Pesaran, M. H. & Zhao, Z., 1998. "Bias Reduction in Estimating Long-run Relationships from Dynamic Heterogenous Panels," Cambridge Working Papers in Economics 9802, Faculty of Economics, University of Cambridge.
    5. Kiviet, Jan F. & Phillips, Garry D. A., 1994. "Bias assessment and reduction in linear error-correction models," Journal of Econometrics, Elsevier, vol. 63(1), pages 215-243, July.
    6. den Butter, F. A. G. & Fase, M. M. G., 1981. "The demand for money in EEC countries," Journal of Monetary Economics, Elsevier, vol. 8(2), pages 201-230.
    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. Chudik, Alexander & Pesaran, M. Hashem & Yang, Jui-Chung, 2016. "Half-panel jackknife fixed effects estimation of panels with weakly exogenous regressor," Globalization and Monetary Policy Institute Working Paper 281, Federal Reserve Bank of Dallas.
    2. Chudik, Alexander & Pesaran, M. Hashem, 2015. "Common correlated effects estimation of heterogeneous dynamic panel data models with weakly exogenous regressors," Journal of Econometrics, Elsevier, vol. 188(2), pages 393-420.
    3. Chudik, Alexander & Pesaran, M. Hashem, 2017. "A Bias-Corrected Method of Moments Approach to Estimation of Dynamic Short-T Panels," Globalization and Monetary Policy Institute Working Paper 327, Federal Reserve Bank of Dallas.
    4. G. Everaert, 2009. "Using Backward Means to Eliminate Individual Effects from Dynamic Panels," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 09/553, Ghent University, Faculty of Economics and Business Administration.
    5. Ignace De Vos & Gerdie Everaert & Ilse Ruyssen, 2015. "Bootstrap-based bias correction and inference for dynamic panels with fixed effects," Stata Journal, StataCorp LP, vol. 15(4), pages 986-1018, December.
    6. Ilse Ruyssen & Gerdie Everaert & Glenn Rayp, 2014. "Determinants and dynamics of migration to OECD countries in a three-dimensional panel framework," Empirical Economics, Springer, vol. 46(1), pages 175-197, February.
    7. repec:eee:juipol:v:48:y:2017:i:c:p:12-21 is not listed on IDEAS
    8. Everaert, Gerdie & Pozzi, Lorenzo, 2007. "Bootstrap-based bias correction for dynamic panels," Journal of Economic Dynamics and Control, Elsevier, vol. 31(4), pages 1160-1184, April.
    9. G. Everaert & L. Pozzi, 2004. "Bootstrap Based Bias Correction for Homogeneous Dynamic²² Panels," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 04/263, Ghent University, Faculty of Economics and Business Administration.

    More about this item

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: 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:taf:emetrv:v:22:y:2003:i:1:p:29-58. 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: (). General contact details of provider: http://www.tandfonline.com/LECR20 .

    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.