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分类依据与纠错

AI 根据所提供的论文材料归类:摘要以非线性协整、平滑转换和误差修正检验为核心,直接对应时间序列方向。

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关注这篇论文的作者
George Kapetanios
Yongcheol Shin
Andy Snell

非线性平滑转换误差修正模型中的协整检验

研究问题
研究如何识别服从全局平稳平滑转换过程的协整关系,以及线性协整检验为何可能难以检出这类非线性调整。
方法与思路
作者在非线性平滑转换误差修正模型中,分别构造基于模型和基于残差的检验,推导渐近分布并开展模拟与应用。
材料陈述的贡献
摘要称,两类检验在所考察的非线性备择下比线性检验功效更高;价格与股利应用中检出线性检验未检出的协整。
阅读关注点
应核对全局平稳的条件、平滑转换函数和检验构造,并检查模拟是否控制尺寸,以及价格与股利应用的稳健性。
阅读边界
所给出版社摘要未列出模型限制、功效数值及应用设定,不能将所述优势推广到所有非线性过程或全部经济数据。

原文摘要

This paper proposes a new testing procedure to detect the presence of a cointegrating relationship that follows a globally stationary smooth transition process. In the context of nonlinear smooth transition error correction models (ECMs) we provide two simple operational versions of the tests. First, we obtain the associated nonlinear ECM-based tests. Second, we derive the nonlinear analogue of the residual-based test for cointegration in linear models. We derive the asymptotic distributions of the proposed tests. Monte Carlo simulation exercises confirm that our proposed tests have much better power than the linear counterparts against the alternative of a globally stationary nonlinear cointegrating process. In an application to the price-dividend relationship, our test is able to find cointegration, whereas the linear-based tests fail to do so.We are grateful to an associate editor, two anonymous referees, Richard Baillie, In Choi, Atanas Christev, Hira Koul, Richard Harris, Cheng Hsiao, Changjin Kim, Joon Park, Peter Schmidt, Yoonjae Whang, Jeff Wooldridge, and seminar participants at University of Edinburgh, Heriot-Watt University, Korea University, University of Leeds, Michigan State University, University of Newcastle, and Sungkunkwan University for their helpful comments. Partial financial support from the ESRC (grant R000223399) is gratefully acknowledged. The usual disclaimer applies.

笔记与分组
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