Publication in refereed journal
香港中文大学研究人员 ( 现职)
| 陈伟森教授 (金融学系) |
| 张绍洪教授 (统计学系) |
全文
| 数位物件识别号 (DOI) http://dx.doi.org/10.1002/for.2344 |
引用次数
Web of Sciencehttp://aims.cuhk.edu.hk/converis/portal/Publication/0WOS source URL
其它资讯
摘要There is growing interest in exploring potential forecast gains from the nonlinear structure of multivariate threshold autoregressive (MTAR) models. A least squares-based statistical test has been proposed in the literature. However, previous studies on univariate time series analysis show that classical nonlinearity tests are often not robust to additive outliers. The outlier problem is expected to pose similar difficulties for multivariate nonlinearity tests. In this paper, we propose a new and robust MTAR-type nonlinearity test, and derive the asymptotic null distribution of the test statistic. A Monte Carlo experiment is carried out to compare the power of the proposed test with that of the least squares-based test under the influence of additive time series outliers. The results indicate that the proposed method is preferable to the classical test when observations are contaminated by outliers. Finally, we provide illustrative examples by applying the statistical tests to two real datasets. Copyright (c) 2http://aims.cuhk.edu.hk/converis/portal/Publication/015John Wiley & Sons, Ltd.
着者Chan WS, Cheung SH, Chow WK, Zhang LX
期刊名称Journal of Forecasting
出版年份2http://aims.cuhk.edu.hk/converis/portal/Publication/015
月份9
日期1
卷号34
期次6
出版社Wiley: 24 months
页次441 - 454
国际标準期刊号http://aims.cuhk.edu.hk/converis/portal/Publication/0277-6693
电子国际标準期刊号1http://aims.cuhk.edu.hk/converis/portal/Publication/099-131X
语言英式英语
关键词macroeconomic forecasting; nonlinear time series; outliers; robustness; vector autoregression models
Web of Science 学科类别Business & Economics; Economics; Management
