Truncated Product Methods for Panel Unit Root Tests*
提出两种基于截断乘积方法的面板单位根检验，一种假设P值间恒定相关，另一种用筛子自助法处理截面依赖。蒙特卡洛模拟显示检验效果良好，并应用于实际GDP和通胀密度预测面板，发现专业预测者可能未按最优贝叶斯方式更新预测精度。
Abstract 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.