A Panic Attack on Unit Roots and Cointegration
A Panic Attack on Unit Roots and Cointegration
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DOI：
10.2139/ssrn.294808
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发表时间：
2001-12
期刊：
影响因子：
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通讯作者：
Jushan Bai;Serena Ng
中科院分区：
文献类型：
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作者：
Jushan Bai;Serena Ng
本文开发了一种新方法，该方法利用大维面板的因子结构来理解数据中非平稳性的性质，我们将其称为恐慌 - 对特质和共同组成部分中非平稳性的面板分析'由单变量和面板测试组成，具有许多新颖的功能，它可以检测到非平稳性是普遍性还是可变特异性，或者两者都测试组件因此，当组件具有不同的集成顺序恐慌顺序时，数据而不是观察到的串联推断也更准确，即使当横截面相关性无效使用观察到的数据构建的统计数据时，也允许构建有效的面板测试。对组件的一致估计即使回归是单独虚假的，我们也为蒙特卡洛模拟的估计和推断提供了严格的理论，测试的尺寸非常好Power Panic应用于通货膨胀系列小组
This paper develops a new methodology that makes use of the factor structure of large dimensional panels to understand the nature of non-stationarity in the data We refer to it as PANIC - a 'Panel Analysis of Non-stationarity in Idiosyncratic and Common components' PANIC consists of univariate and panel tests with a number of novel features It can detect whether the nonstationarity is pervasive or variable-specific or both It tests the components of the data instead of the observed series Inference is therefore more accurate when the components have different orders of integration PANIC also permits the construction of valid panel tests even when cross-section correlation invalidates pooling of statistics constructed using the observed data The key to PANIC is consistent estimation of the components even when the regressions are individually spurious We provide a rigorous theory for estimation and inference In Monte Carlo simulations the tests have very good size and power PANIC is applied to a panel of inflation series