大数据发展与劳动收入份额:来自中国国家大数据综合试验区的证据

IF 7.9 2区 经济学 Q1 ECONOMICS Economic Analysis and Policy Pub Date : 2024-10-21 DOI:10.1016/j.eap.2024.10.031
Yuanbin Xu , Yuan Wei , Xin Zeng , Haiqing Yu , Hongjie Chen
{"title":"大数据发展与劳动收入份额:来自中国国家大数据综合试验区的证据","authors":"Yuanbin Xu ,&nbsp;Yuan Wei ,&nbsp;Xin Zeng ,&nbsp;Haiqing Yu ,&nbsp;Hongjie Chen","doi":"10.1016/j.eap.2024.10.031","DOIUrl":null,"url":null,"abstract":"<div><div>In the midst of the rapid development of the digital economy, data has emerged as a new core production factor. It not only creates value for producers but also benefits the majority of ordinary workers, playing a crucial role in optimizing income distribution and promoting common prosperity. Utilizing data from Chinese A-share listed companies from 2012 to 2021, this study evaluates the impact of big data development on the labor income share of enterprises, employing the establishment of China's national big data comprehensive pilot zones as a quasi-natural experiment. Additionally, it examines the heterogeneity of this impact across regional, industry, and firm levels. The findings reveal that big data development significantly increases the labor income share of firms, mainly through mitigating labor mismatch, improving innovation capability, and upgrading human capital. Heterogeneity analysis shows that big data development exerts a stronger effect on eastern and labor-rich regions, high-tech and non-labor-intensive industries, big-data industries and low-competition industries, as well as state-owned and mature enterprises. This study provides policy insights on fully harnessing the benefits of big data pilot policy to increase labor income share, with important implications for developing countries.</div></div>","PeriodicalId":54200,"journal":{"name":"Economic Analysis and Policy","volume":"84 ","pages":"Pages 1415-1437"},"PeriodicalIF":7.9000,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Big data development and labor income share: Evidence from China's national big data comprehensive pilot zones\",\"authors\":\"Yuanbin Xu ,&nbsp;Yuan Wei ,&nbsp;Xin Zeng ,&nbsp;Haiqing Yu ,&nbsp;Hongjie Chen\",\"doi\":\"10.1016/j.eap.2024.10.031\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>In the midst of the rapid development of the digital economy, data has emerged as a new core production factor. It not only creates value for producers but also benefits the majority of ordinary workers, playing a crucial role in optimizing income distribution and promoting common prosperity. Utilizing data from Chinese A-share listed companies from 2012 to 2021, this study evaluates the impact of big data development on the labor income share of enterprises, employing the establishment of China's national big data comprehensive pilot zones as a quasi-natural experiment. Additionally, it examines the heterogeneity of this impact across regional, industry, and firm levels. The findings reveal that big data development significantly increases the labor income share of firms, mainly through mitigating labor mismatch, improving innovation capability, and upgrading human capital. Heterogeneity analysis shows that big data development exerts a stronger effect on eastern and labor-rich regions, high-tech and non-labor-intensive industries, big-data industries and low-competition industries, as well as state-owned and mature enterprises. This study provides policy insights on fully harnessing the benefits of big data pilot policy to increase labor income share, with important implications for developing countries.</div></div>\",\"PeriodicalId\":54200,\"journal\":{\"name\":\"Economic Analysis and Policy\",\"volume\":\"84 \",\"pages\":\"Pages 1415-1437\"},\"PeriodicalIF\":7.9000,\"publicationDate\":\"2024-10-21\",\"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/S0313592624002868\",\"RegionNum\":2,\"RegionCategory\":\"经济学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ECONOMICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Economic Analysis and Policy","FirstCategoryId":"96","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0313592624002868","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

摘要

在数字经济迅猛发展的今天,数据已成为新的核心生产要素。它不仅为生产者创造价值,也惠及广大普通劳动者,在优化收入分配、促进共同富裕方面发挥着重要作用。本研究利用 2012 年至 2021 年中国 A 股上市公司的数据,以中国国家大数据综合试验区的设立为准自然实验,评估了大数据发展对企业劳动收入占比的影响。此外,研究还考察了这种影响在地区、行业和企业层面的异质性。研究结果表明,大数据发展主要通过缓解劳动力错配、提高创新能力和提升人力资本,显著提高了企业的劳动收入占比。异质性分析表明,大数据发展对东部地区和劳动力富裕地区、高科技产业和非劳动密集型产业、大数据产业和低竞争产业以及国有企业和成熟企业的影响更大。本研究为充分利用大数据试点政策的优势提高劳动收入占比提供了政策启示,对发展中国家具有重要的借鉴意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Big data development and labor income share: Evidence from China's national big data comprehensive pilot zones
In the midst of the rapid development of the digital economy, data has emerged as a new core production factor. It not only creates value for producers but also benefits the majority of ordinary workers, playing a crucial role in optimizing income distribution and promoting common prosperity. Utilizing data from Chinese A-share listed companies from 2012 to 2021, this study evaluates the impact of big data development on the labor income share of enterprises, employing the establishment of China's national big data comprehensive pilot zones as a quasi-natural experiment. Additionally, it examines the heterogeneity of this impact across regional, industry, and firm levels. The findings reveal that big data development significantly increases the labor income share of firms, mainly through mitigating labor mismatch, improving innovation capability, and upgrading human capital. Heterogeneity analysis shows that big data development exerts a stronger effect on eastern and labor-rich regions, high-tech and non-labor-intensive industries, big-data industries and low-competition industries, as well as state-owned and mature enterprises. This study provides policy insights on fully harnessing the benefits of big data pilot policy to increase labor income share, with important implications for developing countries.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
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.
期刊最新文献
From restriction to relaxation: The impact of fertility policy on household savings across countries Issuance of urban investment bonds and high-quality urban economic development Beyond the ivory tower: Professors on the board and corporate performance in China Does the incentive policy for renewable energy grid connection affect the technical efficiency of power grid companies? Empirical analysis based on China and Japan Reformation of government officials’ performance evaluation and corporate environmental investment: The moderating effect of corporate bargaining power
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1