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On the implementation and use of factor-augmented regressions in panel data

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  • Westerlund, Joakim
  • Urbain, Jean-Pierre

Abstract

Practitioners are generally well aware of the fact that most standard approaches for estimation and inference in panel data regressions are based on assuming that the cross-sectional units are independent of each other, an assumption that is surely mistaken in applications, especially in macroeconomics and finance. Yet, applications involving anything but these standard approaches are very rare. The current paper can be seen as a reaction to this. The purpose is to point to some of the recent advances in the area of factor-augmented panel regressions, and to also provide some guidance regarding their implementation.

Suggested Citation

  • Westerlund, Joakim & Urbain, Jean-Pierre, 2013. "On the implementation and use of factor-augmented regressions in panel data," Journal of Asian Economics, Elsevier, vol. 28(C), pages 3-11.
    • Handle: RePEc:eee:asieco:v:28:y:2013:i:c:p:3-11
    DOI: 10.1016/j.asieco.2013.02.002
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    20. Simplice A. Asongu & Joseph I. Uduji & Elda N. Okolo-Obasi, 2020. "Foreign aid volatility and lifelong learning," International Journal of Education Economics and Development, Inderscience Enterprises Ltd, vol. 11(4), pages 370-406.
    21. Asongu, Simplice A & Nwachukwu, Jacinta C., 2015. "Foreign aid instability and bundled governance dynamics in Africa," MPRA Paper 71783, University Library of Munich, Germany.
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    More about this item

    Keywords

    Factor-augmented panel regressions; Principal components; Cross-sectional averages; China; Predictive regression;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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