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Which panel data estimator should I use?*

* This paper has been replicated

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  • W. Robert Reed
  • Haichun Ye

Abstract

This study employs Monte Carlo experiments to evaluate the performances of a number of common panel data estimators when serial correlation and cross-sectional dependence are both present. It focuses on fixed effects models with less than 100 cross-sectional units and between 10 and 25 time periods (such as are commonly employed in empirical growth studies). Estimator performance is compared on two dimensions: (i) root mean square error and (ii) accuracy of estimated confidence intervals. An innovation of our study is that our simulated panel data sets are designed to look like 'real-world' panel data. We find large differences in the performances of the respective estimators. Further, estimators that perform well on efficiency grounds may perform poorly when estimating confidence intervals and vice versa. Our experimental results form the basis for a set of estimator recommendations. These are applied to 'out of sample' simulated panel data sets and found to perform well.

Suggested Citation

  • W. Robert Reed & Haichun Ye, 2009. "Which panel data estimator should I use?," Applied Economics, Taylor & Francis Journals, vol. 43(8), pages 985-1000.
    • Handle: RePEc:taf:applec:v:43:y:2009:i:8:p:985-1000
    DOI: 10.1080/00036840802600087
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    References listed on IDEAS

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    1. David Roodman, 2009. "How to do xtabond2: An introduction to difference and system GMM in Stata," Stata Journal, StataCorp LP, vol. 9(1), pages 86-136, March.
    2. David Roodman, 2006. "How to Do xtabond2," North American Stata Users' Group Meetings 2006 8, Stata Users Group.
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    Citations

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    Cited by:

    1. Mantobaye Moundigbaye & William Rea & W. Robert Reed, 2016. "More Evidence On “Which Panel Data Estimator Should I Use?”," Working Papers in Economics 16/18, University of Canterbury, Department of Economics and Finance.
    2. Horst Entorf & Hannes Spengler, 2015. "Crime, prosecutors, and the certainty of conviction," European Journal of Law and Economics, Springer, vol. 39(1), pages 167-201, February.
    3. Aguirre, Mariana & Ibikunle, Gbenga, 2014. "Determinants of renewable energy growth: A global sample analysis," Energy Policy, Elsevier, vol. 69(C), pages 374-384.
    4. Moundigbaye, Mantobaye & Rea, William S. & Reed, W. Robert, 2018. "Which panel data estimator should I use? A corrigendum and extension," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 12, pages 1-31.
    5. Bergh, Andreas & Nilsson, Therese, 2010. "Good for Living? On the Relationship between Globalization and Life Expectancy," World Development, Elsevier, vol. 38(9), pages 1191-1203, September.
    6. Bergh, Andreas & Nilsson, Therese, 2009. "Good for living? On the relation between globalization and life expectancy," Working Papers 2009:9, Lund University, Department of Economics.
    7. Zewdie Habte SHIKUR, 2022. "Development And Enterprises’ Labor Demand In Sub-Saharan Africa: Evidence From Panel Data Of Four Countries," Applied Econometrics and International Development, Euro-American Association of Economic Development, vol. 22(2), pages 109-124.
    8. Aiman Sana & Farzana Naheed Khan & Umaima Arif, 2022. "ICT diffusion and climate change: The role of economic growth, financial development and trade openness," Netnomics, Springer, vol. 22(2), pages 179-194, October.
    9. Ibhagui, Oyakhilome, 2017. "How Does Foreign Direct Investment Affect Growth in Sub-Saharan Africa? New Evidence from Non-threshold and Threshold Analysis," MPRA Paper 85784, University Library of Munich, Germany.
    10. Akinwande A. Atanda & Andrea K. Menclova & W. Robert Reed, 2016. "Is Health Care Infected by Baumol’s Cost Disease? Test of a New Model Using an OECD Dataset," Working Papers in Economics 16/04, University of Canterbury, Department of Economics and Finance.
    11. Di Pietro, Giorgio, 2016. "The Impact of Television Programmes on Teenage Career Aspirations The 'MasterChef Effect'," IZA Discussion Papers 9804, Institute of Labor Economics (IZA).
    12. Aiman Sana & Farzana Naheed Khan & Umaima Arif, 2021. "ICT diffusion and climate change: The role of economic growth, financial development and trade openness," Netnomics, Springer, vol. 22(2), pages 179-194, December.
    13. Reed, W. Robert & Webb, Rachel S., 2011. "Estimating standard errors for the Parks model: Can jackknifing help?," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 5, pages 1-14.
    14. Rubeena Asghar & Sabeela Asghar & Hafsah Batool, 2021. "Position of Pakistani Basmati Rice in International Markets (A Comparative Analysis)," International Journal of Agriculture & Sustainable Development, 50sea, vol. 3(4), pages 94-98, December.
    15. Dr. Ameenullah Aman & Dr. Usman Ahmad & Sumera Muhammad Saleem, 2021. "Investigating the Link Between Macroeconomic Factors and Income Inequality of Asian Countries," iRASD Journal of Economics, International Research Alliance for Sustainable Development (iRASD), vol. 3(3), pages 376-387, December.
    16. Helder Ferreira de Mendonça & Igor da Silva Veiga, 2017. "The open economy trilemma in Latin America: A three-decade analysis," International Finance, Wiley Blackwell, vol. 20(2), pages 135-154, June.

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    Replication

    This item has been replicated by:
  • Moundigbaye, Mantobaye & Rea, William S. & Reed, W. Robert, 2018. "Which panel data estimator should I use? A corrigendum and extension," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 12, pages 1-31.

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