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中国工业与应用数学学会会刊
主管：中华人民共和国教育部
主办：西安交通大学
ISSN 1005-3085  CN 61-1269/O1
工程数学学报

工程数学学报 ›› 2018, Vol. 35 ›› Issue (2): 168-178.doi: 10.3969/j.issn.1005-3085.2018.02.004

• • 上一篇    下一篇

基于厚尾时间序列的贝叶斯单位根检验

刘维奇1,2,3,   何瑞霞2   

  1. 1- 山西大学管理与决策研究中心，太原  030006
    2- 山西大学数学科学学院，太原  030006
    3- 山西财经大学财政金融学院，太原  030006
  • 收稿日期:2017-08-14 接受日期:2017-11-30 出版日期:2018-04-15 发布日期:2018-06-15
  • 基金资助:
    国家社会科学基金(15BJY164)；教育部人文社会科学基金(14YJA790034).

Bayesian Unit Root Testing for Time Series with Heavy Distribution

LIU Wei-qi1,2,3,   HE Rui-xia2   

  1. 1- Institute of Management and Decision-making, Shanxi University, Taiyuan 030006
    2- School of Mathematical Sciences, Shanxi University, Taiyuan 030006
    3- School of Finance, Shanxi University of Finance and Economics, Taiyuan 030006
  • Received:2017-08-14 Accepted:2017-11-30 Online:2018-04-15 Published:2018-06-15
  • Supported by:
    The National Social Science Fund of China (15BJY164); the Ministry of Education of Humanities and Social Science Project (14YJA790034).

PDF (PC)

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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．

关键词: 单位根检验, 先验分布函数, 贝叶斯因子, 可信区间

Abstract: 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.

Key words: unit root test, prior density function, Bayes factor, credible interval

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