考虑结构突变的单位根检验程序研究——基于“新息异常值模型”的Perron检验分析

Perron检验是一种考虑结构突变的单位根检验方法,检验统计量的分布依赖于数据生成过程中所包含的确定性趋势和所选取的检验回归式;而在实证分析中真实的数据生成过程是未知的,这使得单位根检验缺乏必要依据,因而探寻科学有效的单位根检验程序是受到广泛关注的问题。基于此,本文在"IO模型"分析框架下,依据Perron检验提出了一套考虑结构突变的单位根检验程序,并通过蒙特卡洛模拟分析了该程序在有限样本情形下的表现。本研究完善了带有结构突变的单位根检验理论,为实证分析提供了有益的建议和参考。     

多种单位根检验法的比较研究

本文基于单位根检验基本原理,比较了5种单位根检验的方法,说明在小样本情况下,为提高检验功效,应针对数据生成过程的特点联合多种检验法进行检验。如果检验变量为非平稳,则需要进行进一步的结构突变检验,本文主张选用结构突变点内生的Perron检验法与外生检验法相结合来判断变量的平稳性。     

含结构突变的趋势平稳过程的虚假单位根研究

本文发现Perron（1989）在趋势突变情形下的结论“统计量的极限分布会随着突变点位置参数的变化收敛在0到1/2之间”值得商榷,原因在于模型设定中出现了错误,导致在结构突变的趋势平稳过程的数据生成过程下,统计量的极限分布在截距突变的情况下发散而在斜率突变的情况下退化。本文对其进行修正并补充推导了三种含结构突变的趋势平稳过程的单位根检验统计量的分布,并给出能够证实和证伪的蒙特卡洛模拟结果。     

考虑结构突变时确定性趋势的估计与单位根检验式的选择——基于可行广义最小二乘估计的分析

单位根的检验功效依赖于回归检验式中的确定性趋势,而趋势估计量的分布又取决于序列的平稳性,两者相互制约。鉴于此,本文借鉴了Perron和Yabu(2009)提出的可行广义最小二乘估计,推导了相关统计量的分布,在考虑结构突变的情况下,构造了一套确定性趋势的估计和推断程序,并通过蒙特卡罗模拟对该程序的有限样本性质进行了分析。结论显示,大多数情形下根据该程序进行的单位根检验具有较高功效。     

单位根检验统计量MGLS的有限样本性质与应用

Ng—Perron单位根检验是值得在实际分析中广泛应用的检验方法。本文在详述M^GLS统计量的构造方法基础上，应用蒙特卡罗模拟试验分析了该统计量的有限样本分布特征，并拟合了常用显著性水平下临界值关于样本容量的响应面函数；此外，针对实际应用中检验回归式中差分变量滞后阶数的确定，本文总结了几种常用的方法，从而完善了依据M^GLS统计量进行单位根检验的程序和步骤。     

泛函中心极限定理渐进性与具有GARCH误差项的金融时序单位根检验

本文基于分析泛函中心极限定理在高频金融数据单位根检验中的特征与性质，从随机模拟的角度，探讨了有限样本情况下具有GARCH-GED误差项金融时序的ADF单位根检验统计量乙、乙的统计性质，着重研究了不同水平下的分位数、模型滞后阶的设定及GED分布参数的变动对其检验统计特性的影响。随机模拟结果显示，若数据生成模型设定为AR-GARCH-GED过程，常用的ADF单位根检验统计量存在不同的统计性质，并对出现这种现象的原因进行了探索。     

同期相关面板数据退势单位根检验的小样本性质

本文基于SUR回归将时间序列的两种单位根检验（ADF—GLS检验）推广到面板数据，得到了同期相关面板数据退势单位根检验，称为SUR—ADF—GLS检验。通过蒙特卡洛试验研究发现，SUR—ADF—GLS检验具有良好的小样本性质。并且，SUR—ADF—GLS检验关于面板数据的同期相关性结构存在着较强的“依存性”。     

ADF单位根检验法的替代方法

研究目标：ADF单位根检验法的替代方法——消除趋势检验法。研究方法：通过蒙特卡罗仿真估算了消除趋势法、ADF法和差分法的检验临界值和检验功效;估算了三种方法检验临界值关于样本容量的响应面函数;估算了消除趋势回归中趋势项和截距项的t统计量的检验临界值及其响应面函数。研究发现：在各种情形下,消除趋势法的检验功效均大于ADF法,而且在误差项相关时更为明显,说明消除趋势法优于ADF法,可以完全替代ADF法;在某些情况下,差分法的检验功效较大。研究创新：对ADF检验模型进行了改进,提出了消除趋势检验法。研究价值：在单位根检验时,可以用消除趋势法代替一直以来被广泛采用的ADF法,提高单位根检验的功效。     

结构突变时间序列单位根的"伪检验"

利用蒙特卡罗分析方法,本文对含一个结构变化点的经济变量单位根检验的有效性进行了探讨。分析的结果表明,当经济变量的数据生成过程存在一个结构性突变时,不考虑这种变化而进行常规的单位根检验只有在特定条件下才不会“失效”:只有当突变前后两期的样本数相差极大,或者选取的样本期总数很小时,单位根检验才不会“失效”。并且,随着结构变化程度的增大,不考虑结构变化而进行常规单位根检验得出“伪检验”的可能性也会增大。     

关于机理变化型变结构非线性协整的研究

变结构非线性协整是协整理论发展的必然的趋势,也是经济系统复杂多变的必然需求,文章补充了变结构非线性协整的定义,并提出了机理变化型变结构非线性协整,指出其本质问题即单位根的结构突变检验,总结了几种结构突变的单位根检验方法,讨论了变结构点的估计方法,给出了基于Chow统计量的变结构协整检验和建模方法。     

Unit root tests allowing for a break in the trend function at an unknown time under both the null and alternative hypotheses

Perron [Perron, P., 1989. The great crash, the oil price shock and the unit root hypothesis. Econometrica 57, 1361–1401] introduced a variety of unit root tests that are valid when a break in the trend function of a time series is present. The motivation was to devise testing procedures that were invariant to the magnitude of the shift in level and/or slope. In particular, if a change is present it is allowed under both the null and alternative hypotheses. This analysis was carried under the assumption of a known break date. The subsequent literature aimed to devise testing procedures valid in the case of an unknown break date. However, in doing so, most of the literature and, in particular the commonly used test of Zivot and Andrews [Zivot, E., Andrews, D.W.K., 1992. Further evidence on the great crash, the oil price shock and the unit root hypothesis. Journal of Business and Economic Statistics 10, 251–270], assumed that if a break occurs, it does so only under the alternative hypothesis of stationarity. This is undesirable since (a) it imposes an asymmetric treatment when allowing for a break, so that the test may reject when the noise is integrated but the trend is changing; (b) if a break is present, this information is not exploited to improve the power of the test. In this paper, we propose a testing procedure that addresses both issues. It allows a break under both the null and alternative hypotheses and, when a break is present, the limit distribution of the test is the same as in the case of a known break date, thereby allowing increased power while maintaining the correct size. Simulation experiments confirm that our procedure offers an improvement over commonly used methods in small samples.     

Break Point Estimation and Spurious Rejections With Endogenous Unit Root Tests

This paper examines the accuracy of break point estimation using the endogenous break unit root tests of Zivot and Andrews (1992) and Perron (1997). We find that these tests tend to identify the break point incorrectly at one-period behind ( T_B -1) the true break point ( T_B ), where bias in estimating the persistence parameter and spurious rejections are the greatest. In addition, this outcome occurs under the null and alternative hypotheses, and more so as the magnitude of the break increases. Consequences of utilizing these endogenous break tests are similar to (incorrectly) omitting the break term B_t in Perron's (1989) exogenous test.     

Spurious Rejections by Perron Tests in the Presence of a Break

In this paper, we concentrate on the case of an exogeneously chosen break date, but entertain the possibility that an incorrect choice is made. In fact, the Perron test statistics considered are invariant to any break in the generating process at the assumed break date. Our results therefore apply equally to the case of a generating process with two breaks, only one of which is specifically accounted for in the analysis. As in Leybourne et al . (1998), we find that a neglected relatively early break can lead to spurious rejections of the unit root null hypothesis. Moreover, for all but one of the tests analyzed, spurious rejections now also arise if a true break occurs relatively soon after the assumed break date.     

Unit Root Testing under a Local Break in Trend using Partial Information on the Break Date*

We consider unit root testing allowing for a break in trend when partial information is available regarding the location of the break date. This takes the form of knowledge of a relatively narrow window of data within which the break takes place, should it occur at all. For such circumstances, we suggest employing a union of rejections strategy, which combines a unit root test that allows for a trend break somewhere within the window with a unit root test that makes no allowance for a trend break. Asymptotic and finite sample evidence shows that our suggested strategy works well, provided that, when a break does occur, the partial information is correct. An empirical application to UK interest rate data containing the 1973 ‘oil shock’ is also considered.     

Testing for Unit Roots with Breaks: Evidence on the Great Crash and the Unit Root Hypothesis Reconsidered

Nelson and Plosser (1982), in a classic paper, failed to find strong evidence against the null hypothesis of a generating process with a unit autoregressive root for thirteen US macroeconomic time series. Perron (1989) claimed that such evidence was available for a majority of these series if the alternative hypothesis was of trend stationarity with a break in 1929. Zivot and Andrews (1992) treated the break date as endogenous, then finding strong evidence agcainst the null for a minority of these series. Our own analysis extends theirs by permitting a break under the null as well as the alternative hypothesis, and allowing for the sequential nature of the testing. Our empirical findings complete the circle. We find no strong evidence against the unit root hypothesis for any of the thirteen Nelson–Plosser series.     

International evidence on persistence in output in the presence of an episodic change

This paper uses some newly developed methods and techniques to examine the dynamic properties of international output in the presence of a structural break. We provide statistical evidence to show that the unit root test results can, in some cases, be sensitive to whether a one-time structural break in the data is modelled exogenously or endogenously. However, in most cases the unit root test results remain robust to specification of the structural break exogenously or endogenously; moreover, we find that the null hypothesis of a unit root in output can be rejected in favour of a ‘flexible’ trend alternative for a number of countries such as Canada, Denmark, France, and the United States.     

Unit Root Testing Using Covariates: Some Theory and Evidence

This paper analyzes the conditions under which power gains can be achieved using the Covariate Augmented Dickey-Fuller test (CADF) rather than the conventional Augmented Dickey-Fuller (ADF), and argues that this method has the advantage, relative to univariate unit root tests, of increasing power without suffering from the large size distortions affecting the latter. The inclusion of covariates affects unit root testing by: (a) reducing the standard error of the estimate of the autoregressive parameter without affecting the estimate itself, and/or (b) reducing both the standard error and the absolute value of the estimate itself. Conditions in terms of contemporaneous correlation and Granger causality are derived for case (a) or (b) to arise. As an illustration, it is shown that applying the more powerful CADF (rather than the ADF) test reverses the finding of a unit root for many US macroeconomic series.     

我国银行和地产类股票价格的联动性研究

本文采用ADF单位根检验、Granger因果检验、Johansen协整检验等计量方法,对银行类股价和地产类股价变动的的相关关系进行了实证研究,结果发现两者之间存在长期的协整关系,并且银行股指是地产股指变动的原因。