IDEAS home Printed from https://ideas.repec.org/p/boc/usug04/2.html
   My bibliography  Save this paper

Approximating the bias of the LSDV estimator for dynamic panel data models

Author

Listed:
  • Giovanni S.F. Bruno

    () (Universita Commerciale Luigi Bocconi, Milano)

Abstract

It is well known that the LSDV estimator for dynamic panel data models is not consistent for N large and finite T. Nickell (1981) derives an expression for the inconsistency for N going to infinity, which is of order 1/T. Kiviet (1995) uses asymptotic expansion techniques to approximate the small sample bias of the LSDV estimator to also include terms of at most order 1/NT, thus offering a method to correct the LSDV estimator for samples where N is small or only moderately large. In Kiviet (1999) and Bun and Kiviet (2003) the bias expression is more accurate, including higher order terms. Monte Carlo evidence in Judson and Owen (1999) strongly supports the corrected LSDV estimator compared to more traditional GMM estimators when N is only moderately large. Bruno (2004) extends the bias approximation formulas in Bun and Kiviet (2003) to accommodate unbalanced panels with a strictly exogenous selection rule. This paper describes the Stata codes used in Bruno (2004) to compute the bias approximations and carry out the Monte Carlo experiment estimating the actual LSDV bias for various data generating processes. The analysis covers both balanced and unbalanced panels. It is found that the actual bias as estimated by Monte Carlo replications, besides following the same patterns as in Bun and Kiviet (2003), turns out non-increasing in the degree of unbalancedness. Moreover, the approximations are always accurate with a decreasing contribution to the actual bias of the higher order terms.

Suggested Citation

  • Giovanni S.F. Bruno, 2004. "Approximating the bias of the LSDV estimator for dynamic panel data models," United Kingdom Stata Users' Group Meetings 2004 2, Stata Users Group.
  • Handle: RePEc:boc:usug04:2
    as

    Download full text from publisher

    File URL: http://fmwww.bc.edu/repec/usug2004/LSDVC_slides.pdf
    File Function: Presentation slides
    Download Restriction: no

    File URL: http://fmwww.bc.edu/repec/usug2004/WP2004-1.pdf
    File Function: Paper underlying presentation
    Download Restriction: no

    References listed on IDEAS

    as
    1. Bun, Maurice J.G. & Carree, Martin A., 2005. "Bias-Corrected Estimation in Dynamic Panel Data Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 200-210, April.
    2. Bruno, Giovanni S.F., 2005. "Approximating the bias of the LSDV estimator for dynamic unbalanced panel data models," Economics Letters, Elsevier, vol. 87(3), pages 361-366, June.
    3. Bun, Maurice J. G. & Kiviet, Jan F., 2003. "On the diminishing returns of higher-order terms in asymptotic expansions of bias," Economics Letters, Elsevier, vol. 79(2), pages 145-152, May.
    4. Jeffrey M Wooldridge, 2010. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262232588, January.
    5. Nickell, Stephen J, 1981. "Biases in Dynamic Models with Fixed Effects," Econometrica, Econometric Society, vol. 49(6), pages 1417-1426, November.
    6. Kajal Lahiri, 2005. "Analysis of Panel Data," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 87(4), pages 1093-1095.
    7. Judson, Ruth A. & Owen, Ann L., 1999. "Estimating dynamic panel data models: a guide for macroeconomists," Economics Letters, Elsevier, vol. 65(1), pages 9-15, October.
    8. Jan F. Kiviet, 1986. "On the Rigour of Some Misspecification Tests for Modelling Dynamic Relationships," Review of Economic Studies, Oxford University Press, vol. 53(2), pages 241-261.
    9. Kiviet, Jan F., 1995. "On bias, inconsistency, and efficiency of various estimators in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 68(1), pages 53-78, July.
    Full references (including those not matched with items on IDEAS)

    More about this item

    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:boc:usug04:2. 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: (Christopher F Baum). General contact details of provider: http://edirc.repec.org/data/stataea.html .

    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.