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An intersection test for panel unit roots

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  • Hanck, Christoph

Abstract

This paper proposes a new panel unit root test based on Simes' [Biometrika 1986, An Improved Bonferroni Procedure for Multiple Tests of Significance'] classical intersection test. The test is robust to general patterns of cross-sectional dependence and yet straightforward to implement, only requiring p-values of time series unit root tests of the series in the panel, and no resampling. Monte Carlo experiments show good size and power properties relative to existing panel unit root tests. Unlike previously suggested tests, the new test allows to identify the units in the panel for which the alternative of stationarity can be said to hold. We provide two empirical applications to panels of real gross domestic product (GDP) and real exchange rate data.

Suggested Citation

  • Hanck, Christoph, 2008. "An intersection test for panel unit roots," Technical Reports 2008,11, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
  • Handle: RePEc:zbw:sfb475:200811
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    References listed on IDEAS

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    Cited by:

    1. Hanck, Christoph, 2008. "Nonstationary-Volatility Robust Panel Unit Root Tests and the Great Moderation," MPRA Paper 11988, University Library of Munich, Germany.
    2. Hanck Christoph, 2009. "Nonstationary-Volatility Robust Panel Unit Root Tests and the Great Moderation," Research Memorandum 009, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
    3. Thomas Goda & Chris Stewart & Alejandro Torres García, 2016. "Absolute Income Inequality and Rising House Prices," DOCUMENTOS DE TRABAJO CIEF 015247, UNIVERSIDAD EAFIT.

    More about this item

    Keywords

    Multiple Testing; Panel Unit Root Test; Cross-Sectional Dependence;

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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