Dynamic hysteresis effects

IF 1.9 3区 经济学 Q2 ECONOMICS
Mengheng Li , Ivan Mendieta-Muñoz
{"title":"Dynamic hysteresis effects","authors":"Mengheng Li ,&nbsp;Ivan Mendieta-Muñoz","doi":"10.1016/j.jedc.2024.104870","DOIUrl":null,"url":null,"abstract":"<div><p>We study how the output gap affects potential output over time—<em>i.e.</em>, the dynamic hysteresis effect. To do so, we introduce novel unobserved components (UC) models that consider hysteresis as a sequence of lagged effects, thus separating the long-run recession-induced adverse effects from other trend-cycle interactions. The proposed models nest several existing UC models in the literature and accommodate two key characteristics of output dynamics: non-neutrality in the long-run and time-to-build effects. Using Bayesian estimation methods, we find robust evidence supporting the presence of hysteresis effects after the 1970s, with the negative long-run effect of the Global Financial Crisis and the COVID-19 recessions robustly identified. Via Bayesian model averaging, we provide precise and intuitive output gap estimates that highlight the relationship between business cycle fluctuations and the decline in economic growth. Our findings indicate that output trend-cycle decompositions that do not consider hysteresis effects can alter stabilization policy trade-offs.</p></div>","PeriodicalId":48314,"journal":{"name":"Journal of Economic Dynamics & Control","volume":null,"pages":null},"PeriodicalIF":1.9000,"publicationDate":"2024-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0165188924000629/pdfft?md5=4893c1c51384dab00d05a5f11914ace4&pid=1-s2.0-S0165188924000629-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Economic Dynamics & Control","FirstCategoryId":"96","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0165188924000629","RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ECONOMICS","Score":null,"Total":0}
引用次数: 0

Abstract

We study how the output gap affects potential output over time—i.e., the dynamic hysteresis effect. To do so, we introduce novel unobserved components (UC) models that consider hysteresis as a sequence of lagged effects, thus separating the long-run recession-induced adverse effects from other trend-cycle interactions. The proposed models nest several existing UC models in the literature and accommodate two key characteristics of output dynamics: non-neutrality in the long-run and time-to-build effects. Using Bayesian estimation methods, we find robust evidence supporting the presence of hysteresis effects after the 1970s, with the negative long-run effect of the Global Financial Crisis and the COVID-19 recessions robustly identified. Via Bayesian model averaging, we provide precise and intuitive output gap estimates that highlight the relationship between business cycle fluctuations and the decline in economic growth. Our findings indicate that output trend-cycle decompositions that do not consider hysteresis effects can alter stabilization policy trade-offs.

动态滞后效应
我们研究产出缺口如何随着时间的推移影响潜在产出,即动态滞后效应。为此,我们引入了新的非观测成分(UC)模型,将滞后效应视为一系列滞后效应,从而将长期衰退引发的不利效应与其他趋势-周期相互作用区分开来。所提出的模型是对文献中几个现有 UC 模型的嵌套,并考虑了产出动态的两个关键特征:长期非中性和建立时间效应。利用贝叶斯估计方法,我们发现了支持 20 世纪 70 年代后存在滞后效应的有力证据,全球金融危机和 COVID-19 经济衰退的长期负效应也被有力地识别出来。通过贝叶斯模型平均法,我们提供了精确直观的产出缺口估计值,突出了商业周期波动与经济增长下降之间的关系。我们的研究结果表明,不考虑滞后效应的产出趋势周期分解可以改变稳定政策的权衡。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
CiteScore
3.10
自引率
10.50%
发文量
199
期刊介绍: The journal provides an outlet for publication of research concerning all theoretical and empirical aspects of economic dynamics and control as well as the development and use of computational methods in economics and finance. Contributions regarding computational methods may include, but are not restricted to, artificial intelligence, databases, decision support systems, genetic algorithms, modelling languages, neural networks, numerical algorithms for optimization, control and equilibria, parallel computing and qualitative reasoning.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信