A Simple Panel Unit-Root Test with Smooth Breaks in the Presence of a Multifactor Error Structure

Chingnun Lee, Jyh‐Lin Wu, Lixong Yang
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Abstract

This paper proposes a new simple panel unit-root test by extending the cross-sectionally augmented panel unit-root test (CIPS) developed by Pesaran et al. (2013) to allow for smoothing structural changes in deterministic terms, approximated by a Fourier series. The proposed statistic is the simple average of the individual statistics constructed from the breaks and cross-sectional dependence augmented Dickey-Fuller (BCADF) regression and is called the BCIPS statistic. We initially develop the tests by assuming that the number of factors in the model is known and show that the limiting distribution of the BCADF statistic is free of nuisance parameters. The nonstandard limiting distribution of the (truncated) BCIPS statistic is also shown to exist and its critical values are tabulated. Monte-Carlo experiments point out that the sizes and powers of the BCIPS statistic are generally satisfactory as long as T is greater than or equal to fifty and a hundred, respectively. By using two different methods to determine the number of factors, both the BCIPS and CIPS tests are applied to examine the validity of long-run purchasing power parity. The proposed test complements the panel unit-root tests with breaks using dummy variables.
多因素误差结构下光滑断裂的简单面板单位根检验
本文通过扩展Pesaran等人(2013)开发的横截面增强面板单位根检验(CIPS),提出了一种新的简单面板单位根检验,以允许平滑确定性项的结构变化,由傅里叶级数近似。所提出的统计量是由断裂和横截面依赖增强的Dickey-Fuller (BCADF)回归构建的单个统计量的简单平均值,称为BCIPS统计量。我们最初通过假设模型中的因素数量是已知的来开发测试,并表明BCADF统计量的极限分布没有讨厌的参数。截断后的BCIPS统计量存在非标准极限分布,并将其临界值制成表格。蒙特卡罗实验指出,只要T分别大于等于50和100,BCIPS统计量的大小和幂通常是令人满意的。通过使用两种不同的方法来确定因素的数量,BCIPS和CIPS测试都被应用于检验长期购买力平价的有效性。提议的测试使用假变量来补充面板单位根测试。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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