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Testing for Stationarity in Panel Data when Errors are Serially Correlated. Finite-Sample Results

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  • Jönsson, Kristian

    (Sveriges Riksbank)

Abstract

In this paper, we study the small sample properties of the panel data stationarity test of Hadri (2000). We find that the previously suggested moments, that are to be used when standardizing the panel data stationarity test, cause size distortions when samples are small and serial correlation in the disturbance terms is allowed for. Instead, we supply standardizing moments that are to be used in a panel data stationarity test when samples are small and serial correlation in the disturbances may be an issue. We also document a serious small-sample bias in the panel data stationarity test when a linear trend is present in the data.

Suggested Citation

  • Jönsson, Kristian, 2005. "Testing for Stationarity in Panel Data when Errors are Serially Correlated. Finite-Sample Results," Working Papers 2005:16, Lund University, Department of Economics.
    • Handle: RePEc:hhs:lunewp:2005_016
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    References listed on IDEAS

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    Cited by:

    1. Kristian Jonsson, 2009. "Time-specific disturbances in a panel stationarity test," Applied Economics, Taylor & Francis Journals, vol. 43(7), pages 845-853.

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    More about this item

    Keywords

    Panel Data; Stationarity; Serial Correlation; Monte Carlo Simulation;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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