IDEAS home Printed from https://ideas.repec.org/p/msh/ebswps/1996-9.html
   My bibliography  Save this paper

The Robustness of Estimators for Dynamic Panel Data Models to Misspecification

Author

Listed:
  • Harris, M.N.
  • Longmire, R.J.
  • Matyas, L.

Abstract

It is well known that the usual techniques for estimating random and fixed effects panel data models are inconsistent in the dynamic setting. As a consequence, numerous consistent estimators have been proposed in the literature. However, all such estimators rely on certain well defined assumption, which in practice my be violated.The purpose of this paper is to ascertain how robust the available estimators are to such misspecifications, thus providing guidance to applied researcher as to an appropriate choice of estimator in such situation.

Suggested Citation

  • Harris, M.N. & Longmire, R.J. & Matyas, L., 1996. "The Robustness of Estimators for Dynamic Panel Data Models to Misspecification," Monash Econometrics and Business Statistics Working Papers 9/96, Monash University, Department of Econometrics and Business Statistics.
    • Handle: RePEc:msh:ebswps:1996-9
    as

    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

    as
    1. Ruth A. Judson & Ann L. Owen, "undated". "Estimating Dynamic Panel Data Models: A Practical Guide for Macroeconomists," Finance and Economics Discussion Series 1997-03, Board of Governors of the Federal Reserve System (U.S.), revised 10 Dec 2019.
    2. László Mátyás & Patrick Sevestre (ed.), 2008. "The Econometrics of Panel Data," Advanced Studies in Theoretical and Applied Econometrics, Springer, number 978-3-540-75892-1, January.
    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. Aninday Banerjee & Markus Eberhardt & J James Reade, 2010. "Panel Estimation for Worriers," Discussion Papers 10-33, Department of Economics, University of Birmingham.
    2. Simon Feeny & Mark Harris & Mark Rogers, 2005. "A dynamic panel analysis of the profitability of Australian tax entities," Empirical Economics, Springer, vol. 30(1), pages 209-233, January.
    3. Magerman, Glenn & Studnicka, Zuzanna & Van Hove, Jan, 2016. "Distance and border effects in international trade: A comparison of estimation methods," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 10, pages 1-31.
    4. Mark N. Harris & Simon Feeny, 2000. "Habit Persistence in Effective Tax Rates: Evidence Using Australian Tax Entities," Melbourne Institute Working Paper Series wp2000n13, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
    5. Jan Kiviet & Milan Pleus & Rutger Poldermans, 2017. "Accuracy and Efficiency of Various GMM Inference Techniques in Dynamic Micro Panel Data Models," Econometrics, MDPI, vol. 5(1), pages 1-54, March.
    6. Zheka Vitaliy, 2010. "The impact of corporate governance practices on dynamic adjustment of capital structure of companies in Ukraine," EERC Working Paper Series 10/07e, EERC Research Network, Russia and CIS.
    7. Durand, Robert B. & Greene, William H. & Harris, Mark N. & Khoo, Joye, 2022. "Heterogeneity in speed of adjustment using finite mixture models," Economic Modelling, Elsevier, vol. 107(C).
    8. Michael Lee & Ritchard Longmire & Laszlo Matyas & Mark Harris, 1998. "Growth convergence: some panel data evidence," Applied Economics, Taylor & Francis Journals, vol. 30(7), pages 907-912.
    9. Jan F. Kiviet & Milan Pleus & Rutger Poldermans, 2014. "Accuracy and efficiency of various GMM inference techniques in dynamic micro panel data models," UvA-Econometrics Working Papers 14-09, Universiteit van Amsterdam, Dept. of Econometrics.
    10. Mark Harris & Simon Feeny, 2003. "Habit persistence in effective tax rates," Applied Economics, Taylor & Francis Journals, vol. 35(8), pages 951-958.

    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. Michał Brzoza-Brzezina & Jacek Kotłowski & Kamil Wierus, 2015. "Can interest rate spreads stabilize the euro area?," Applied Economics, Taylor & Francis Journals, vol. 47(34-35), pages 3696-3709, July.
    2. Arturas Juodis, 2013. "Cointegration Testing in Panel VAR Models Under Partial Identification and Spatial Dependence," UvA-Econometrics Working Papers 13-08, Universiteit van Amsterdam, Dept. of Econometrics.
    3. repec:rri:wpaper:201303 is not listed on IDEAS
    4. Joseph P. Byrne & Alexandros Kontonikas & Alberto Montagnoli, 2013. "International Evidence on the New Keynesian Phillips Curve Using Aggregate and Disaggregate Data," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 45(5), pages 913-932, August.
    5. Cem Ertur & Antonio Musolesi, 2017. "Weak and Strong Cross‐Sectional Dependence: A Panel Data Analysis of International Technology Diffusion," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(3), pages 477-503, April.
    6. Francesca Iorio & Stefano Fachin, 2014. "Savings and investments in the OECD: a panel cointegration study with a new bootstrap test," Empirical Economics, Springer, vol. 46(4), pages 1271-1300, June.
    7. Karaman Örsal, Deniz Dilan & Droge, Bernd, 2014. "Panel cointegration testing in the presence of a time trend," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 377-390.
    8. Asgharian, Hossein & Hess, Wolfgang & Liu, Lu, 2013. "A spatial analysis of international stock market linkages," Journal of Banking & Finance, Elsevier, vol. 37(12), pages 4738-4754.
    9. Nicole Grunewald & Inmaculada Martínez-Zarzoso, 2009. "Driving Factors of Carbon Dioxide Emissions and the Impact from Kyoto Protocol," Ibero America Institute for Econ. Research (IAI) Discussion Papers 190, Ibero-America Institute for Economic Research.
    10. Nguyen Kim Phuoc, 2016. "Impacts of local characteristics on regional FDI inflows into Mekong Delta," HO CHI MINH CITY OPEN UNIVERSITY JOURNAL OF SCIENCE - ECONOMICS AND BUSINESS ADMINISTRATION, HO CHI MINH CITY OPEN UNIVERSITY JOURNAL OF SCIENCE, HO CHI MINH CITY OPEN UNIVERSITY, vol. 6(1), pages 89-103.
    11. Richard Harris & John Moffat, 2011. "R&D, Innovation and Exporting," SERC Discussion Papers 0073, Centre for Economic Performance, LSE.
    12. Vasudeva N. R. Murthy & Emmanuel Anoruo, 2009. "Are Per Capita Real GDP Series in African Countries Non-stationary or Non-linear? What does Empirical Evidence Reveal?," Economics Bulletin, AccessEcon, vol. 29(4), pages 2492-2504.
    13. Hjalmar Böhm & Michael Funke & Nikolaus A. Siegfried, 1999. "Discovering the Link between Uncertainty and Investment - Microeconometric Evidence from Germany," Quantitative Macroeconomics Working Papers 19906, Hamburg University, Department of Economics.
    14. Alexander Klemm & Stefan Parys, 2012. "Empirical evidence on the effects of tax incentives," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 19(3), pages 393-423, June.
    15. Ling Xiong & Shaozhou Qi, 2018. "Financial Development And Carbon Emissions In Chinese Provinces: A Spatial Panel Data Analysis," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 63(02), pages 447-464, March.
    16. Parent, Olivier & LeSage, James P., 2011. "A space-time filter for panel data models containing random effects," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 475-490, January.
    17. Nilsen, Øivind Anti & Raknerud, Arvid & Skjerpen, Terje, 2011. "Using the Helmert-transformation to reduce dimensionality in a mixed model: Application to a wage equation with worker and firm heterogeneity," Discussion Paper Series in Economics 11/2011, Norwegian School of Economics, Department of Economics, revised 04 Oct 2011.
    18. Jason P. Brown & Raymond J.G.M. Florax & Kevin T. McNamara, 2009. "Determinants Of Investme??T Flows In U.S. Manufacturing," Working Papers 09-10, Purdue University, College of Agriculture, Department of Agricultural Economics.
    19. Patrizia Ordine & Giuseppe Rose, 2008. "Local Banks Efficiency and Employment," LABOUR, CEIS, vol. 22(3), pages 469-493, September.
    20. Zouaghi, Ferdaous & Sánchez, Mercedes & Martínez, Marian García, 2018. "Did the global financial crisis impact firms' innovation performance? The role of internal and external knowledge capabilities in high and low tech industries," Technological Forecasting and Social Change, Elsevier, vol. 132(C), pages 92-104.
    21. Yeung, Matthew C.H. & Ramasamy, Bala & Chen, Junsong & Paliwoda, Stan, 2013. "Customer satisfaction and consumer expenditure in selected European countries," International Journal of Research in Marketing, Elsevier, vol. 30(4), pages 406-416.

    More about this item

    Keywords

    REGRESSION ANALYSIS; ECONOMIC MODELS; EVALUATION;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

    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:msh:ebswps:1996-9. 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: Professor Xibin Zhang (email available below). General contact details of provider: https://edirc.repec.org/data/dxmonau.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.