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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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File URL: http://hdl.handle.net/10.1111/j.1468-0084.2012.00705.x
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Bibliographic Info

Article provided by Department of Economics, University of Oxford in its journal Oxford Bulletin of Economics and Statistics.

Volume (Year): 75 (2013)
Issue (Month): 4 (08)
Pages: 624-636

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Handle: RePEc:bla:obuest:v:75:y:2013:i:4:p:624-636

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References

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Cited by:
  1. 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.
  2. Xuguang Sheng & Lan Cheng, 2012. "Combination of "Combinations of P-values," Working Papers 2012-11, American University, Department of Economics.

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