大数据发展和企业劳动收入份额——来自“国家级大数据综合试验区”的证据

Big Data and Labor Income Share:Evidence from National Big Data Comprehensive Pilot Zone

本文通过构建理论模型刻画了大数据影响劳动收入份额的经济逻辑,并利用“国家级大数据综合试验区”作为准自然实验,使用双重差分法来检验大数据发展对中国上市公司劳动收入份额的影响。研究发现,大数据发展显著降低了企业的劳动收入份额。异质性结果表明,“国家级大数据综合试验区”显著降低了劳动密集型企业、融资约束更高的企业以及高新技术行业的劳动收入份额。进一步的影响机制分析发现,大数据发展通过促进企业技术进步对劳动收入份额产生影响;大数据发展促进了企业数字化转型,企业增加数字化资产投入,挤出了劳动投入,进而导致劳动收入份额下降。

As information technologies,notably AI,Blockchain,Cloud Computing,and Big Data,rapidly evolve,digital information and knowledge play an increasingly pivotal role in the real economy.However,the swift progress of information technology has raised concerns about its potential to displace labor.Concurrently,China has been consistently advancing income distribution system reforms since the initiation of reform and opening up.Despite these efforts,the issue of income inequality remains prominent.Therefore,it is worthwhile to explore the research question of how data factor influences the labor income share.This paper investigates the direction of the impact of big data on the labor income share in enterprises and its pathways.Firstly,this paper constructs a static model based on production tasks,delineating the economic logic of how big data influences the labor income share.Subsequently,it utilizes the policy of the National Big Data Comprehensive Pilot Zone as a quasi-natural experiment to identify causality.The National Big Data Comprehensive Pilot Zone stands as China’s first policy experiment in the digital economy,aiming to propel innovation and elevate economic transformation through experimental explorations in areas such as public data openness,the aggregation of the big data industry,and international collaboration.Employing micro-data from Chinese A-share listed companies and city statistical yearbook data from 2011 to 2019,this paper uses difference-in-differences(DID)method and finds that the development of big data significantly reduces firms’labor income share.This result is validated through placebo tests.When we employ different methods to measure labor income share,eliminate the influence of concurrent policies,and utilize the propensity score matching with difference-in-differences(PSM-DID)method,the conclusion remains robust.Furthermore,heterogeneous analysis indicates that the National Big Data Comprehensive Experimental Zone has different impacts on different companies,significantly reducing the labor income share in highly labor-intensive enterprises,enterprises facing higher financial constraints,and those in the high-tech industry.Lastly,this paper explores the two pathways through which the National Big Data Comprehensive Pilot Zone affects the labor income share of listed companies in China.On one hand,the development of big data stimulates technological progress,and enhances total factor productivity,particularly for labor-intensive enterprises,consequently influencing the labor income share.On the other hand,the development of big data affects factor allocation in enterprises,promoting digital transformation and investments in digital assets,thereby displacing labor input and reducing average wages.In the meantime,the total number of employees and the number of employees in different positions do not exhibit significant changes,ultimately resulting in a decline in the labor income share.This paper holds significant theoretical and practical implications.Theoretically,it contributes to the literature on the economic consequences of informatization.While existing literature generally finds positive impacts of information technology on enterprises and the macroeconomy,this paper explores the potential adverse effects from the perspective of income distribution.Simultaneously,the paper reveals the pathways through which the development of big data influences labor income share from perspectives of both theoretical model and empirical evidence.Unlike existing literature,which primarily focuses on the employment-promoting and substituting effects of digital technology,this paper conducts the mechanism analysis from the perspectives of technological progress and factor allocation.In terms of policy implications,the paper finds that the National Big Data Comprehensive Pilot Zone has a negative impact on the labor income share.This underscores the need for an objective and comprehensive understanding of the pros and cons brought about by the development of information technologies.As the government continues to promote the integration of the digital economy and the real economy,attention should be paid to the negative effects,including labor displacement,arising from enterprise digital transformation and industrial structural transformation.