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Truncated Product Methods for Panel Unit Root Tests

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  • Xuguang Sheng
  • Jingyun Yang

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.
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Suggested Citation

  • Xuguang Sheng & Jingyun Yang, 2013. "Truncated Product Methods for Panel Unit Root Tests," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 75(4), pages 624-636, August.
  • Handle: RePEc:bla:obuest:v:75:y:2013:i:4:p:624-636
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    File URL: http://hdl.handle.net/10.1111/j.1468-0084.2012.00705.x
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    Cited by:

    1. In Choi, 2014. "Unit root tests for dependent and heterogeneous micropanels," Working Papers 1404, Nam Duck-Woo Economic Research Institute, Sogang University (Former Research Institute for Market Economy).
    2. 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.
    3. In Choi, 2019. "Unit Root Tests for Dependent Micropanels," The Japanese Economic Review, Springer, vol. 70(2), pages 145-167, June.
    4. Lan Cheng & Xuguang Simon Sheng, 2017. "Combination of “combinations of p values”," Empirical Economics, Springer, vol. 53(1), pages 329-350, August.
    5. Juan Carlos Aquino & N. R. Ramírez-Rondán, 2020. "Estimating factor shares from nonstationary panel data," Empirical Economics, Springer, vol. 58(5), pages 2353-2380, May.
    6. Manzan, Sebastiano, 2021. "Are professional forecasters Bayesian?," Journal of Economic Dynamics and Control, Elsevier, vol. 123(C).

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    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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