Abstract This paper studies testing of shifts in a time trend panel data model with serially correlated error component disturbances, without any prior knowledge of whether the error term is stationary or nonstationary. This is done in case the shift is known as well as unknown. Following the time series literature, we propose a Wald type test statistic that uses a fixed effects feasible generalized least squares (FE-FGLS) estimator. The proposed test has a chi-square limiting distribution and is valid for both I(0) and I(1) errors. The finite sample size and power of this Wald test is investigated using Monte Carlo simulations

中文翻译：

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测试具有串行相关误差分量干扰的时间趋势面板数据模型中的偏移

摘要 本文研究了具有序列相关误差分量扰动的时间趋势面板数据模型中的偏移测试，而无需事先了解误差项是平稳的还是非平稳的。这是在已知和未知偏移的情况下完成的。根据时间序列文献，我们提出了 Wald 类型检验统计量，该统计量使用固定效应可行广义最小二乘 (FE-FGLS) 估计量。建议的检验具有卡方极限分布，对 I(0) 和 I(1) 误差均有效。使用蒙特卡罗模拟研究了此 Wald 检验的有限样本大小和功效