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Econometric Analysis of Panel Data Models with Multifactor Error Structures

Author

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  • Hande Karabiyik
  • Franz C. Palm
  • Jean-Pierre Urbain
Abstract
Economic panel data often exhibit cross-sectional dependence, even after conditioning on appropriate explanatory variables. Two approaches to modeling cross-sectional dependence in economic panel data are often used: the spatial dependence approach, which explains cross-sectional dependence in terms of distance among units, and the residual multifactor approach, which explains cross-sectional dependence by common factors that affect individuals to a different extent. This article reviews the theory on estimation and statistical inference for stationary and nonstationary panel data with cross-sectional dependence, particularly for models with a multifactor error structure. Tests and diagnostics for testing for unit roots, slope homogeneity, cointegration, and the number of factors are provided. We discuss issues such as estimating common factors, dealing with parameter plethora in practice, testing for structural stability and nonlinearity, and dealing with model and parameter uncertainty. Finally, we address issues related to the use of these economic panel models.

Suggested Citation

  • Hande Karabiyik & Franz C. Palm & Jean-Pierre Urbain, 2019. "Econometric Analysis of Panel Data Models with Multifactor Error Structures," Annual Review of Economics, Annual Reviews, vol. 11(1), pages 495-522, August.
    • Handle: RePEc:anr:reveco:v:11:y:2019:p:495-522
    DOI: 10.1146/annurev-economics-063016-104338
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    Cited by:

    1. Eibinger, Tobias & Deixelberger, Beate & Manner, Hans, 2024. "Panel data in environmental economics: Econometric issues and applications to IPAT models," Journal of Environmental Economics and Management, Elsevier, vol. 125(C).
    2. Hugo Freeman & Martin Weidner, 2021. "Linear panel regressions with two-way unobserved heterogeneity," CeMMAP working papers CWP39/21, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    3. Saban Nazlioglu & Cagin Karul, 2024. "Testing for Granger causality in heterogeneous panels with cross-sectional dependence," Empirical Economics, Springer, vol. 67(4), pages 1541-1579, October.
    4. Li, Qi & Sarafidis, Vasilis & Westerlund, Joakim, 2020. "Essays in Honor of Professor Badi H Baltagi: Editorial," MPRA Paper 104751, University Library of Munich, Germany.
    5. Saif Ullah & Atta Ullah & Mubasher Zaman, 2024. "Nexus of governance, macroeconomic conditions, and financial stability of banks: a comparison of developed and emerging countries," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-38, December.
    6. Freeman, Hugo & Weidner, Martin, 2023. "Linear panel regressions with two-way unobserved heterogeneity," Journal of Econometrics, Elsevier, vol. 237(1).
    7. Hugo Freeman & Martin Weidner, 2021. "Linear Panel Regressions with Two-Way Unobserved Heterogeneity," Papers 2109.11911, arXiv.org, revised Aug 2022.

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