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Truncated Product Methods for Panel Unit Root Tests

Author

Listed:
  • Xuguang Sheng

    () (American University)

  • Jingyun Yang

    () (Pennsylvania State University)

Abstract

This paper proposes three new panel unit root tests based on Zaykin et al. (2002)’s truncated product method. The first one assumes constant correlation between p-values and the latter two use sieve bootstrap that allows for general forms of cross-section dependence in the panel units. Monte Carlo simulation shows that these tests have reasonably good size, are robust to varying degrees of cross-section dependence and are powerful in cases where there are some very large p-values. The proposed tests are applied to a panel of real GDP and inflation density forecasts and provide evidence that professional forecasters may not update their forecast precision in an optimal Bayesian way.

Suggested Citation

  • Xuguang Sheng & Jingyun Yang, 2013. "Truncated Product Methods for Panel Unit Root Tests," Working Papers 2013-004, The George Washington University, Department of Economics, Research Program on Forecasting.
  • Handle: RePEc:gwc:wpaper:2013-004
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    File URL: https://www2.gwu.edu/~forcpgm/2013-004.pdf
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. In Choi, 2014. "Unit root tests for dependent and heterogeneous micropanels," Working Papers 1404, Research Institute for Market Economy, Sogang University.
    2. Xuguang Sheng & Lan Cheng, 2012. "Combination of "Combinations of P-values," Working Papers 2012-11, American University, Department of Economics.
    3. Clements, Michael P., 2014. "Probability distributions or point predictions? Survey forecasts of US output growth and inflation," International Journal of Forecasting, Elsevier, vol. 30(1), pages 99-117.

    More about this item

    Keywords

    Density Forecast; Panel Unit Root; P-value; Sieve Bootstrap; Truncated Product Method;

    JEL classification:

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

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