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,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的检验功效及其优势。
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 tNG test proposed by Ling et al. （2003） and the standard Dickey-Fuller test, we found that our proposed test has the best test power.
出处
《统计研究》
CSSCI
北大核心
2014年第7期85-91,共7页
Statistical Research
