Truncated Product Methods for Panel Unit Root Tests


  • This paper was presented at the 16th International Panel Data Conference (2010) in Amsterdam, the Netherlands and 81st Southern Economic Association Annual Meeting (2011) in Washington, D.C. We thank Stefano Fachin, Christoph Hanck, Joachim Hartung, James MacKinnon, Serena Ng, Hashem Pesaran, Dmitri Zaykin and participants in the conference for helpful comments and suggestions. We also thank the editor Anindya Banerjee and two anonymous referees for the comments that have significantly improved the paper. Dr. Yang's research was supported by Award Number P50DA010075-15 from the National Institute on Drug Abuse. The usual disclaimer applies.


This paper proposes two 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 second one uses sieve bootstrap to allow for general forms of cross-section dependence in the panel units. Monte Carlo simulation shows that both tests have reasonably good size and are powerful in cases of some very large P-values. The proposed tests are applied to a panel of real GDP and inflation density forecasts, resulting in evidence that professional forecasters may not update their forecast precision in an optimal Bayesian way.