Technological progress and economic dynamics: Unveiling the long memory of total factor productivity

IF 7.9 2区 经济学 Q1 ECONOMICS
Anran Xiao , Zeshui Xu , Tong Wu , Yong Qin , Marinko Skare
{"title":"Technological progress and economic dynamics: Unveiling the long memory of total factor productivity","authors":"Anran Xiao ,&nbsp;Zeshui Xu ,&nbsp;Tong Wu ,&nbsp;Yong Qin ,&nbsp;Marinko Skare","doi":"10.1016/j.eap.2024.09.004","DOIUrl":null,"url":null,"abstract":"<div><p>This study aims to explore the dynamics of total factor productivity (TFP) in 40 advanced economies and its implications for economic stability, growth patterns, and technological integration. Understanding the concept of long memory in TFP is crucial in comprehending the diverse paths of economic development and technological advancement in different nations. The study endeavors to clarify the concept of long memory in TFP and analyze its impact on economic stability, growth patterns, and technological integration on a global scale. The research employs a sophisticated methodological framework that integrates a combination of unit root tests, non-parametric methods, fractional integration techniques, and ARFIMA models. This multifaceted approach provides a nuanced understanding of the persistence in TFP series and helps distinguish between stable and mean-reverting TFP dynamics across different nations. The analysis highlights the varying trajectories of TFP across these economies, which sheds light on the diverse paths of economic development and technological advancement. The findings of this research are pivotal in comprehending the role of TFP in shaping growth convergence, influencing business cycle fluctuations, and technological progress. The study contributes to policy discourse by proposing strategic policy measures that harness the long-term trends of TFP. These recommendations encompass key areas such as labor, capital, institutional frameworks, and innovation policies. Countries can optimize sustainable economic development and foster effective technological integration in an increasingly interconnected global economy by implementing these measures.</p></div>","PeriodicalId":54200,"journal":{"name":"Economic Analysis and Policy","volume":"84 ","pages":"Pages 326-343"},"PeriodicalIF":7.9000,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Economic Analysis and Policy","FirstCategoryId":"96","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0313592624002297","RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}
引用次数: 0

Abstract

This study aims to explore the dynamics of total factor productivity (TFP) in 40 advanced economies and its implications for economic stability, growth patterns, and technological integration. Understanding the concept of long memory in TFP is crucial in comprehending the diverse paths of economic development and technological advancement in different nations. The study endeavors to clarify the concept of long memory in TFP and analyze its impact on economic stability, growth patterns, and technological integration on a global scale. The research employs a sophisticated methodological framework that integrates a combination of unit root tests, non-parametric methods, fractional integration techniques, and ARFIMA models. This multifaceted approach provides a nuanced understanding of the persistence in TFP series and helps distinguish between stable and mean-reverting TFP dynamics across different nations. The analysis highlights the varying trajectories of TFP across these economies, which sheds light on the diverse paths of economic development and technological advancement. The findings of this research are pivotal in comprehending the role of TFP in shaping growth convergence, influencing business cycle fluctuations, and technological progress. The study contributes to policy discourse by proposing strategic policy measures that harness the long-term trends of TFP. These recommendations encompass key areas such as labor, capital, institutional frameworks, and innovation policies. Countries can optimize sustainable economic development and foster effective technological integration in an increasingly interconnected global economy by implementing these measures.

技术进步与经济活力:揭示全要素生产率的长期记忆
本研究旨在探讨 40 个发达经济体全要素生产率(TFP)的动态及其对经济稳定、增长模式和技术一体化的影响。理解全要素生产率长期记忆的概念对于理解不同国家经济发展和技术进步的不同路径至关重要。本研究致力于澄清全要素生产率长期记忆的概念,并分析其对全球经济稳定、增长模式和技术一体化的影响。研究采用了一个复杂的方法框架,将单位根检验、非参数方法、分数积分技术和 ARFIMA 模型结合在一起。这种多元方法提供了对全要素生产率序列持久性的细微理解,并有助于区分不同国家稳定的全要素生产率动态和均值回归的全要素生产率动态。分析突出了这些经济体全要素生产率的不同轨迹,揭示了经济发展和技术进步的不同路径。这项研究的结果对于理解全要素生产率在形成增长趋同、影响商业周期波动和技术进步方面的作用至关重要。本研究通过提出利用全要素生产率长期趋势的战略性政策措施,为政策讨论做出了贡献。这些建议涉及劳动力、资本、制度框架和创新政策等关键领域。各国可通过实施这些措施优化可持续经济发展,并在联系日益紧密的全球经济中促进有效的技术整合。
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
9.80
自引率
9.20%
发文量
231
审稿时长
93 days
期刊介绍: Economic Analysis and Policy (established 1970) publishes articles from all branches of economics with a particular focus on research, theoretical and applied, which has strong policy relevance. The journal also publishes survey articles and empirical replications on key policy issues. Authors are expected to highlight the main insights in a non-technical introduction and in the conclusion.
×
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