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Model specification in panel data unit root tests with an unknown break

机译:未知中断的面板数据单元根测试中的模型规范

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Although the impact of structural breaks on testing for unit root has been studied extensively for univariate time-series, such impact on panel data unit root tests is still relatively unknown. A major issue is the choice of model in accommodating different types of break prior to testing for unit root. Model misspecification has been known to affect unit root tests performance in the univariate case but the effect of misspecification on panel tests is still unknown. This paper has two objectives: (i) it proposes a new test for unit root in the presence of structural break for panel data. The test allows the intercepts, the trend coefficients or both to change at different date for different individuals. Moreover, the test allows for the possibility that only some, but not all, of the individuals experienced structural breaks. Under some mild assumptions, the test statistics is shown to be asymptotically normal which greatly facilitates valid inferences. (ii) This paper provides a systematic study on the impact of structural instability on testing for unit root using Monte Carlo Simulation. The results show that correct specification is crucial for unit root testing in the presence of structural instability. In addition, the proportion of individuals experienced structural instability can also affect the performance of the test substantially.
机译:尽管已经针对单变量时间序列广泛研究了结构破坏对单位根测试的影响,但对面板数据单位根测试的影响仍然相对未知。一个主要问题是在测试单位根之前适应不同类型中断的模型选择。在单变量情况下,已知模型错误指定会影响单位根测试的性能,但对面板测试的错误指定影响仍然未知。本文有两个目标:(i)提出了针对面板数据存在结构性断裂的单位根的新测试。该测试允许截距,趋势系数或两者在不同的日期针对不同的个人进行更改。而且,该测试考虑了仅部分但并非全部个体经历结构性断裂的可能性。在一些温和的假设下,测试统计量被证明是渐近正常的,这极大地促进了有效的推论。 (ii)本文使用蒙特卡洛模拟系统研究了结构不稳定性对单位根测试的影响。结果表明,正确的规范对于在结构不稳定的情况下进行单元根测试至关重要。另外,经历结构不稳定性的个体比例也会大大影响测试的性能。

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