IDEAS home Printed from https://ideas.repec.org/a/adr/anecst/y2003i70p53-75.html
   My bibliography  Save this article

Consistent estimation of dynamic panel data models with time-varying individual effects

Author

Listed:
  • Céline Nauges
  • Alban Thomas

Abstract

This paper proposes a new specification for dynamic panel data models, where unobserved heterogeneity is modeled by the sum of the usual additive individual effect, and a multiplicative, time varying individual effect. We show that usual GMM estimators based on first-difference or quasi-difference transformations are generally inconsistent with our model specification, and we propose a consistent GMM estimation procedure based on a double-difference transformation. Small sample properties of alternative GMM estimators are investigated through Monte Carlo experiments.

Suggested Citation

  • Céline Nauges & Alban Thomas, 2003. "Consistent estimation of dynamic panel data models with time-varying individual effects," Annals of Economics and Statistics, GENES, issue 70, pages 53-75.
    • Handle: RePEc:adr:anecst:y:2003:i:70:p:53-75
    as

    Download full text from publisher

    File URL: http://www.jstor.org/stable/20076374
    Download Restriction: no
    ---><---

    Citations

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


    Cited by:

    1. Kazuhiko Hayakawa & Vanessa Smith & M. Hashem Pesaran, 2014. "Transformed Maximum Likelihood Estimation of Short Dynamic Panel Data Models with interactive effects," Cambridge Working Papers in Economics 1412, Faculty of Economics, University of Cambridge.
    2. Kazuhiko Hayakawa & M. Hashem Pesaran & L. Vanessa Smith, 2023. "Short T dynamic panel data models with individual, time and interactive effects," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(6), pages 940-967, September.
    3. Artūras Juodis & Vasilis Sarafidis, 2018. "Fixed T dynamic panel data estimators with multifactor errors," Econometric Reviews, Taylor & Francis Journals, vol. 37(8), pages 893-929, September.
    4. Juodis, Artūras & Sarafidis, Vasilis, 2022. "An incidental parameters free inference approach for panels with common shocks," Journal of Econometrics, Elsevier, vol. 229(1), pages 19-54.
    5. Naima Chrid & Sami Saafi & Mohamed Chakroun, 2021. "Export Upgrading and Economic Growth: a Panel Cointegration and Causality Analysis," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 12(2), pages 811-841, June.
    6. Yan Sun & Wei Huang, 2022. "Quasi-maximum likelihood estimation of short panel data models with time-varying individual effects," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 85(1), pages 93-114, January.
    7. Céline Nauges & Alban Thomas, 2003. "Long-run Study of Residential Water Consumption," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 26(1), pages 25-43, September.
    8. Robertson, Donald & Sarafidis, Vasilis, 2015. "IV estimation of panels with factor residuals," Journal of Econometrics, Elsevier, vol. 185(2), pages 526-541.
    9. Vasilis Sarafidis & Tom Wansbeek, 2012. "Cross-Sectional Dependence in Panel Data Analysis," Econometric Reviews, Taylor & Francis Journals, vol. 31(5), pages 483-531, September.
    10. Ignace De Vos & Gerdie Everaert, 2016. "Bias-Corrected Common Correlated Effects Pooled Estimation In Homogeneous Dynamic Panels," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 16/920, Ghent University, Faculty of Economics and Business Administration.
    11. Kim, Yong-seong & Kim, Taebong, 2017. "The Effects of Institutions on the Labour Market Outcomes: Cross-country Analysis," KDI Journal of Economic Policy, Korea Development Institute (KDI), vol. 39(4), pages 69-94.
    12. Daniel L. Millimet & Ian K. McDonough, 2017. "Dynamic Panel Data Models With Irregular Spacing: With an Application to Early Childhood Development," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(4), pages 725-743, June.
    13. Hendricks, Nathan P. & Smith, Aaron D., 2012. "Comparing the Bias of Dynamic Panel Estimators in Multilevel Panels: Individual versus Grouped Data," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 124548, Agricultural and Applied Economics Association.
    14. Mohamed Chakroun & Naima Chrid & Sami Saafi, 2021. "Does export upgrading really matter to economic growth? Evidence from panel data for high‐, middle‐ and low‐income countries," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 5584-5609, October.

    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:adr:anecst:y:2003:i:70:p:53-75. 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.

    We have no bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Secretariat General or Laurent Linnemer (email available below). General contact details of provider: https://edirc.repec.org/data/ensaefr.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.