基于随机加权Bootstrap的AR(1)误差过程的单位根检验

IF 0.8 3区数学 Q2 MATHEMATICS

Acta Mathematica Sinica-English Series Pub Date : 2023-09-15 DOI:10.1007/s10114-023-1535-x

Xiao Hui Liu, Ya Wen Fan, Yu Zi Liu, Shi Hua Luo

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引用次数: 0

摘要

许多经济问题都与检测时间序列数据的稳定性有关，其中主要关注的是单位根检验。在本文中，我们考虑了具有GARCH结构的长存储过程中存在错误的单位根测试问题。利用随机加权自举方法建立了一种新的检验统计量。结果表明，无论过程是平稳的还是非平稳的，无论是否有截距项，所提出的统计量都具有渐近的卡方分布。仿真结果表明，该统计量在大小和功率方面都具有期望的有限样本性能。根据17个国家的通货膨胀率数据，给出了一个真实的数据应用程序。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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A Unit Root Test for an AR(1) Process with AR Errors by Using Random Weighted Bootstrap

A great deal of economic problems are related to detecting the stability of time series data, where the main interest is in the unit root test. In this paper, we consider the unit root testing problem with errors being long-memory processes with the GARCH structure. A new test statistic is developed by using the random weighted bootstrap method. It turns out that the proposed statistic has a chi-squared distribution asymptotically regardless of the process being stationary or nonstationary, and with or without an intercept term. The simulation results show that the statistic has a desired finite sample performance in terms of both size and power. A real data application is also given relying on the inflation rate data of 17 countries.

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来源期刊

Acta Mathematica Sinica-English Series 数学-数学

CiteScore

1.00

自引率

0.00%

发文量

138

审稿时长

14.5 months

期刊介绍： Acta Mathematica Sinica, established by the Chinese Mathematical Society in 1936, is the first and the best mathematical journal in China. In 1985, Acta Mathematica Sinica is divided into English Series and Chinese Series. The English Series is a monthly journal, publishing significant research papers from all branches of pure and applied mathematics. It provides authoritative reviews of current developments in mathematical research. Contributions are invited from researchers from all over the world.