摘要
本文运用贝叶斯因子和可信区间两种方法来研究厚尾时间序列中单位根检验问题.通过Monte Carlo模拟证实了这两种方法的有效性,并对两种方法进行对比和分析.然后,考察了先验信息和自由度对单位根检验结果的影响.最后,将这两种方法运用到检验美国失业率和居民消费物价指数时间序列中,发现这两列序列均存在单位根.
In this paper,based on Bayes factor and credible interval methods,we deal with the unit root test for time series with heavy distribution.Monte Carlo simulations demonstrate the validity of the Bayes factor approach and the credible interval approach in this paper.We compare and analyze these two methods.In addition,we consider the effect of prior information and degree of freedom on unit test results.At last,these two methods are applied to the time series of the unemployment rate and consumer price index in the United States,and we find that there are unit roots in these time series.
作者
刘维奇
何瑞霞
LIU Wei-qi;HE Rui-xia(Institute of Management and Decision-making,Shanxi University,Taiyuan 030006;School of Mathematical Sciences,Shanxi University,Taiyuan 030006;School of Finance,Shanxi University of Finance and Economics,Taiyuan 030006)
出处
《工程数学学报》
CSCD
北大核心
2018年第2期168-178,共11页
Chinese Journal of Engineering Mathematics
基金
国家社会科学基金(15BJY164)
教育部人文社会科学基金(14YJA790034)~~
