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Panel Cointegration Techniques and Open Challenges

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Abstract

This chapter discusses the challenges that shape panel cointegration techniques, with an emphasis on the challenge of maintaining the robustness of cointegration methods when temporal dependencies interact with both cross sectional heterogeneities and dependencies. It also discusses some of the open challenges that lie ahead, including the challenge of generalizing to nonlinear and time varying cointegrating relationships. The chapter is written in a nontechnical style that is intended to be assessable to nonspecialists, with an emphasis on conveying the underlying concepts and intuition.

Suggested Citation

  • Peter Pedroni, 2018. "Panel Cointegration Techniques and Open Challenges," Department of Economics Working Papers 2018-09, Department of Economics, Williams College.
    • Handle: RePEc:wil:wileco:2018-09
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    References listed on IDEAS

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    1. M. Hashem Pesaran, 2007. "A simple panel unit root test in the presence of cross-section dependence," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(2), pages 265-312.
    2. Nicholas M. Kiefer & Timothy J. Vogelsang, 2002. "Heteroskedasticity-Autocorrelation Robust Standard Errors Using The Bartlett Kernel Without Truncation," Econometrica, Econometric Society, vol. 70(5), pages 2093-2095, September.
    3. Kao, Chihwa, 1999. "Spurious regression and residual-based tests for cointegration in panel data," Journal of Econometrics, Elsevier, vol. 90(1), pages 1-44, May.
    4. Jaroslava Hlouskova & Martin Wagner, 2006. "The Performance of Panel Unit Root and Stationarity Tests: Results from a Large Scale Simulation Study," Econometric Reviews, Taylor & Francis Journals, vol. 25(1), pages 85-116.
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    More about this item

    Keywords

    Panel Time Series; Cointegration; Nonstationary Panels; Nonlinear Panels;
    All these keywords.

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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