Outliers and persistence in threshold autoregressive processes

被引：5

作者：

Ahmad, Yamin ^{[2
]}

Donayre, Luiggi ^{[1
]}

机构：

[1] Univ Minnesota, Dept Econ, 1318 Kirby Dr, Duluth, MN 55812 USA

[2] Univ Wisconsin, Dept Econ, 800 W Main St, Whitewater, WI 53190 USA

来源：

STUDIES IN NONLINEAR DYNAMICS AND ECONOMETRICS | 2016年 / 20卷 / 01期

关键词：

outliers; persistence; power; size; threshold autoregression; UNIT-ROOT; NONLINEAR APPROACH; MEAN-REVERSION; TIME-SERIES; TAR MODELS; ONE PRICE; INFERENCE; US; COINTEGRATION; LAW;

D O I：

10.1515/snde-2014-0058

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

This paper uses Monte Carlo simulations to investigate the effects of outlier observations on the properties of linearity tests against threshold autoregressive (TAR) processes. By considering different specifications and levels of persistence for the data-generating processes, we find that additive outliers distort the size of the test and that the distortion increases with the level of persistence. In addition, we also find that larger additive outliers can help to improve the power of the test in the case of persistent TAR processes.

引用

页码：37 / 56

页数：20

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