| LSTAR-GARCH模型的单位根检验 |
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| 引用本文： | 汪卢俊. LSTAR-GARCH模型的单位根检验[J]. 统计研究, 2014, 31(7): 85-91 |
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| 作者姓名： | 汪卢俊 |
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| 摘 要： | LSTAR模型的单位根检验往往易忽视其条件方差的时变性，实际上，对许多经济变量尤其是金融变量建立LSTAR模型后，经常发现其条件方差存在GARCH效应。针对LSTAR-GARCH模型的平稳性检验，本文构建了检验统计量tNG，之后在极大似然估计的基础上，推导出tNG的渐近分布，通过蒙特卡洛模拟方法得到该统计量的渐近临界值，并在此基础上研究了tNG检验的检验功效。在与刘雪燕和张晓峒(2009)提出的tNL检验、Ling等(2003)提出的tLG检验以及DF单位根检验进行比较后，发现tNG检验具备明显优势。
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| 关 键 词： | LSTAR-GARCH模型 单位根检验 极大似然估计 蒙特卡洛模拟 |
The Unit Root Test of LSTAR-GARCH Model |
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| Wang Lujun. The Unit Root Test of LSTAR-GARCH Model[J]. Statistical Research, 2014, 31(7): 85-91 |
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| Authors: | Wang Lujun |
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| Abstract: | The unit root test of LSTAR model often ignores its time-varying conditional variance, in fact, for many economic variables, especially the financial variables, after LSTAR model set up, we often found the conditional variances exist GARCH effects. In view of the problem of stationarity test of LSTAR-GARCH model, this paper constructs the test statistics tNG, then on the basis of the maximum likelihood estimation, derived the asymptotic distribution of tNG, asymptotic critical value of the statistic is obtained by the Monte Carlo simulation method, and on the basis, studies the test power. Comparing with the tNG test proposed by Liu and Zhang(2009)、the tLG test proposed by Ling et al.(2003) and the standard Dickey-Fuller test, we found that our proposed test has the best test power. |
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| Keywords: | LSTAR-GARCH Model Unit Root Test Maximum Likelihood Estimation Monte Carlo Simulation |
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