The Effects of Digital Finance on Labor Demand: Evidence from 20 Million Online Recruitment Positions
CAI Weixing, WEI Qingfang, LIN Hangyu
School of Finance, Guangdong University of Finance & Economics; School of Economics and Finance, Huaqiao University; China School of Banking and Finance, University of International Business and Economics
Summary:
Employment is essential for individuals' livelihoods and directly affects economic and social factors such as income, consumption, and production. In addition, it serves as a crucial metric for evaluating high-quality development and collective prosperity. Over the past decade, China has rapidly embraced digital finance, becoming a global leader in this area. This advancement has digitally transformed the impact of technological progress on the labor market and broadened access to financial services to a wider demographic, changing labor market dynamics by lowering entry barriers to traditional financial services. However, there is a significant gap in the literature regarding the impact of digital finance development on online recruitment demands. The rapid growth of digital finance in China provides a good opportunity to study its impact on online recruitment demands. Theoretical considerations suggest that the development of digital finance has a dual effect on online recruitment demands. It may reduce demands for and lead to the elimination of certain positions (known as the “job substitution effect”), but it also has the potential to create new job requirements (the “job creation effect”) and to indirectly stimulate entrepreneurial activities (the “entrepreneurship-driven employment effect”), thereby increasing online recruitment demands. In this paper, we use a dataset of 20 million online job postings to create indicators for online recruitment demands and assess the development of digital finance using the Peking University Digital Inclusion Index of China. We systematically examine the impact of digital finance development on online recruitment demands. Our findings indicate a notably positive impact, suggesting that the development of digital finance facilitates both the “job creation effect” and the “entrepreneurship-driven employment effect.” In addition, heterogeneous results indicate that the labor demand effects of digital finance development are widely present across various educational backgrounds, experiences, and wage levels. This confirms the inclusiveness of digital finance development at the job level. This study contributes to the literature in the following aspects. First, it highlights the considerably positive impact of digital finance development on online recruitment demands. Despite extensive scholarly attention to the economic aspects of digital finance development, focusing on macroeconomic growth, micro-level corporate financing behavior, and household entrepreneurship and consumption, there remains a notable gap in understanding its effects on online recruitment demands, a gap which our research bridges. Second, we construct a large-scale database comprising 20 million online job postings, which exhibits excellent scalability. Using big data methodologies, we extract information from these postings as the foundational dataset for our study, which has gained prominence in recent academic research. In contrast to household surveys, our dataset not only has a more substantial sample size but also provides richer information. For instance, in testing the “job creation effect,” we use machine learning to identify digital positions based on the lexicon proposed by Chen and Srinivasan (2023). Given the advantages inherent in this dataset, we anticipate its broader application in the future. We conduct additional tests to explore the online recruitment demand implications of digital finance development, enhancing our understanding of its interplay with traditional finance and its role in responding to challenges posed by external shocks. Our findings indicate that the labor demand effects of digital finance development are more pronounced in areas with lower (vs. higher) bank branch density, confirming a clear complementary relationship between digital finance and traditional finance. Furthermore, the development of digital finance helps mitigate the adverse effects of external shocks on online recruitment demands. These tests refine our insights into the dynamics of digital finance development. This study has important policy implications. First, it is crucial to promote the healthy development of digital finance. Second, efforts should focus on improving the digital skills of the workforce to meet the growing demand for talent in the evolving digital finance landscape. Concurrently, greater support should be provided for entrepreneurial activities to maximize the employment effects of digital finance development. Third, initiatives should aim to encourage the development of digital finance in regions with weak traditional finance.
蔡卫星, 韦庆芳, 林航宇. 数字金融发展的劳动力需求效应 ——来自2000万在线招聘岗位的经验证据[J]. 金融研究, 2023, 521(10): 28-46.
CAI Weixing, WEI Qingfang, LIN Hangyu. The Effects of Digital Finance on Labor Demand: Evidence from 20 Million Online Recruitment Positions. Journal of Financial Research, 2023, 521(10): 28-46.
[1]蔡卫星,2019,《银行业市场结构对企业生产率的影响——来自工业企业的经验证据》,《金融研究》第4期,第39～55页。 [2]方芳和蔡卫星,2016,《银行业竞争与企业成长:来自工业企业的经验证据》,《管理世界》第7期,第63～75页。 [3]郭峰、王靖一、王芳、孔涛、张勋和程志云,2020,《测度中国数字普惠金融发展:指数编制与空间特征》,《经济学(季刊)》第4期,第1401～1418页。 [4]黄祖辉、宋文豪和叶春辉,2023,《数字普惠金融对新型农业经营主体创立的影响与机理——来自中国1845个县域的经验证据》,《金融研究》第4期,第92～110页。 [5]黄益平和黄卓,2018,《中国的数字金融发展:现在与未来》,《经济学(季刊)》第4期,第1489～1502页。 [6]江飞涛和蔡卫星,2020,《新冠肺炎疫情防控中城市交通管制效果的经验评估》,《产业经济评论》第4期,第59～74页。 [7]莫怡青和李力行,2022,《零工经济对创业的影响——以外卖平台的兴起为例》,《管理世界》第2期,第31～45+3页。 [8]宋晓玲,2017,《数字普惠金融缩小城乡收入差距的实证检验》,《财经科学》第6期,第14～25页。 [9]孙鲲鹏、罗婷和肖星,2021,《人才政策、研发人员招聘与企业创新》,《经济研究》第8期,第143～159页。 [10]王馨,2015,《互联网金融助解长尾小微企业融资难问题研究》,《金融研究》第9期,第128～139页。 [11]王靖一、郭峰和李勇国,2020,《新冠肺炎疫情对线下微型商户短期冲击的定量估算——兼论数字金融缓解冲击的价值》,北京大学数字金融研究中心工作论文。 [12]谢绚丽、沈艳、张皓星和郭峰,2018,《数字金融能促进创业吗？——来自中国的证据》,《经济学(季刊)》第4期,第1557～1580页。 [13]张勋、万广华、张佳佳和何宗樾,2019,《数字经济、普惠金融与包容性增长》,《经济研究》第8期,第71～86页。 [14]张勋、杨桐、汪晨和万广华,2020,《数字金融发展与居民消费增长:理论与中国实践》,《管理世界》第11期,第48～63页。 [15]Acemoglu, D. and P. Restrepo, 2018, “The Race between Man and Machine:Implications of Technology for Growth, Factor Shares and Employment”, American Economic Review, 108(6), pp.1488～1542. [16]Acemoglu, D. and P. Restrepo, 2019, “Automation and New Tasks: How Technology Displaces and Reinstates Labor”, Journal of Economic Perspectives, 33(2), pp.3～30. [17]Agrawal, A., J. S. Gans and A. Goldfarb, 2019, “Artificial Intelligence:The Ambiguous Labor Market Impact of Automating Prediction”, Journal of Economic Perspectives, 33(2), pp.31～50. [18]Autor, D. H. and D. Dorn, 2013, “The Growth of Low-skill Service Jobs and the Polarization of the US Labor Market”, American Economic Review, 103(5), pp.1553～1597. [19]Baumol,W. J., 1968, “Entrepreneurship in Economic Theory”, American Economic Review, 58(2), pp.64～71. [20]Chen, W. and S. Srinivasan, 2023, “Going Digital: Implications for Firm Value and Performance”, Review of Accounting Studies28(1), pp.1～47. [21]Frey, C. B. and M. A. Osborne, 2017, “The Future of Employment: How Susceptible Are Jobs to Computerisation？”, Technological Forecasting and Social Change, 114, pp.254～280. [22]Grossman, J. and M. Tarazi, 2014, “Serving Smallholder Farmers: Recent Developments in Digital Finance”, CGAP Working Paper,No.94. [23]Goos, M. and A. Manning, 2007, “Lousy and Lovely Jobs: The Rising Polarization of Work in Britain”, Review of Economics & Statistics, 89(1) , pp.118～133. [24]Graetz, G. and G. Michaels, 2018, “Robots at Work”, Review of Economics and Statistics, 100(5), pp.753～768. [25]Hau, H., Y. Huang, H. Shan and Z. Sheng, 2019, “How Fintech Enters China's Credit Market”,AEA Papers and Proceedings,109,pp.60~64. [26]Kapoor, A., 2013, “Financial Inclusion and the Future of the Indian Economy”, Futures, 56,pp.35～42. [27]King, R. G. and R. Levine, 1993, “Finance and Growth: Schumpeter Might be Right”, The Quarterly Journal of Economics, 108(3), pp.717～737. [28]Korinek, A. and J. E. Stiglitz, 2018, “Artificial Intelligence and Its Implications for Income Distribution and Unemployment”,The Economcs of Artificial Intellisence:An agenda.University of chiago Press,pp.349~390. [29]Samila, S. and O. Sorenson, 2011, “Venture Capital, Entrepreneurship, and Economic Growth”, Review of Economics & Statistics, 93(1), pp.338～349.
