时间序列分析中的等式平衡:经验教训和需要的教训

IF 2.5 2区 社会学 Q1 POLITICAL SCIENCE Political Science Research and Methods Pub Date : 2022-10-01 DOI:10.1017/psrm.2022.51
Mark Pickup
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引用次数: 2

摘要

摘要本次研讨会的论文使用蒙特卡罗模拟来演示估计具有不同积分阶的变量的时间序列模型的后果。在这个总结中,我做了以下几点:非常简要地概述我们从论文中学到的东西;找出一个明显的矛盾,它可能会增加而不是减少围绕平衡时间序列模型概念的混淆;提出解决方案;并确定一些研究领域,这些研究领域可以进一步增加我们对具有不同动态的变量如何组合的理解。在做这些事情时,我认为研究从业者如何展示平衡,以及皮卡和凯尔斯泰特(2021)所说的I(0)平衡,仍然缺乏清晰度。
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Equation balance in time series analysis: lessons learned and lessons needed
Abstract The papers in this symposium use Monte Carlo simulations to demonstrate the consequences of estimating time series models with variables that are of different orders of integration. In this summary, I do the following: very briefly outline what we learn from the papers; identify an apparent contradiction that might increase, rather than decrease, confusion around the concept of a balanced time series model; suggest a resolution; and identify a few areas of research that could further increase our understanding of how variables with different dynamics might be combined. In doing these things, I suggest there is still a lack of clarity around how a research practitioner demonstrates balance, and demonstrates what Pickup and Kellstedt (2021) call I(0) balance.
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来源期刊
CiteScore
8.10
自引率
0.00%
发文量
54
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