城市智能化、居民劳动供给与包容性就业——来自准自然实验的证据

李成明¹　王霄²　李博³

（1. 中央民族大学经济学院；2. 北京大学经济学院；3. 北京大学经济学院/人工智能研究院）

　　内容提要：数字化、网络化、智能化是经济社会发展的重要趋势。当前关于人工智能对就业影响的研究较为丰富，但多集中在企业劳动需求层面，较少着眼于居民劳动供给，更鲜有关注城市智能化对居民劳动参与的总体影响。本文基于2012—2014年国家智慧城市试点建设的准自然实验，利用2010—2018年中国家庭追踪调查（CFPS）数据，分析城市智能化对居民劳动参与率的影响。结果显示，城市智能化提高了居民的劳动参与率，该结论在经过一系列稳健性检验后依旧成立。机制分析结果显示，城市智能化对居民劳动参与具有“推拉效应”。一方面，城市智能化提升了居民对互联网信息的应用程度，产生了信息约束放松效应，推动居民劳动参与；另一方面，城市智能化促进了产业智能化转型，拉动居民劳动参与。进一步的分析结果显示，城市智能化对年龄较大、多个孩子、收入较低、技能较低、农业户籍个体的劳动参与率影响较大，城市智能化驱动下就业更具包容性。同时，城市智能化显著提高了居民的工资性收入。因此，要充分发挥城市智能化转型的“稳就业”作用，加快智慧城市建设，协同推进数字中国建设与共同富裕。

　　

　　关键词：城市智能化；劳动供给；劳动参与；人工智能；智慧城市；包容性就业

　　

　　作者简介：李成明，中央民族大学经济学院讲师，北京，100081；王霄，北京大学经济学院博士研究生，北京，100871；李博，北京大学经济学院/人工智能研究院助理教授，通信作者。

　　

　　基金项目：中华全国归国华侨联合会“华侨华人助力我国中小企业数字化转型的路径研究”（22CZQK204）；国家自然科学基金青年科学基金项目“最优房产税改革方案设计：基于异质性家户模型的量化研究”（72203005）；北京大学经济学院中青年教师科研种子基金资助课题（6309900019/228）

　　

　　引用格式：陈楠,蔡跃洲.人工智能技术创新与区域经济协调发展——基于专利数据的技术发展状况及区域影响分析[J].经济与管理研究,2023,44(3):16-40.DOI:10.13502/j.cnki.issn1000-7636.2023.03.002.

　　

　　

Urban Intelligence, Residents’ Labor Supply and Inclusive Employment
—Evidence from a Quasi-natural Experiment

LI Chengming¹, WANG Xiao², LI Bo²

(1. Minzu University of China, Beijing 100081;

2. Peking University, Beijing 100871)

　　

　　Abstract: Digitalization, networking and intelligence are important trends in economic and social development. However, most existing research focuses on the labor demand of enterprises, with little attention given to residents’ labor supply or the overall impact of urban intelligence on their labor participation. Based on the quasi-natural experiment of national smart city pilot construction, this paper matches the data of China Family Panel Studies (CFPS) from 2010 to 2018, and obtains 43,538 valid individual samples. Then, using the Probit model and multi-time difference-in-differences (DID) method, it investigates the impact of urban intelligence on residents’ labor participation, and explores the mechanism and heterogeneity with the mediating effect model and group regression methods.

　　The findings reveal that urban intelligence enhances residents’ labor participation. This conclusion remains valid after a series of robustness tests, such as parallel trend tests, policy exogeneity tests, counterfactual tests, placebo tests, and the replacement of estimation models and sample size. Mechanism analysis indicates that urban intelligence has a push-pull effect on residents’ labor participation. On the one hand, it enhances residents’ application of internet information, thus relaxing information constraints, and promoting their labor participation. On the other hand, it accelerates industrial intelligence transformation, creates new employment opportunities, and expands employment forms such as remote working, reducing the difficulty of employment and stimulating residents’ labor participation. Further analysis shows that urban intelligence has a significant impact on the labor participation rate of people with older age, multiple children, low income, low skills, and agricultural households. Additionally, urban intelligence significantly improves residents’ wage income, indicating an improvement in opportunities and quality of employment, thus fulfilling their aspiration for a happier and better life.

　　The marginal contributions are reflected as follows. First, from a micro-individual perspective, this paper investigates the impact of urban intelligence on labor participation based on smart city pilot policies. Second, combining macro-regional policies with microindividual employment, it examines the impact of urban intelligence on the labor participation rate and explores the possible influence mechanism and heterogeneous effects. Third, it discusses the impact of artificial intelligence application on labor participation from the perspective of urban intelligence, which makes up for the shortcomings of existing literature. Therefore, it is necessary to give full play to the role of urban intelligence transformation in stabilizing employment, accelerate the construction of smart cities, and jointly promote the strength in digital development and shared prosperity.

　　Keywords: urban intelligence; labor supply; labor participation; artificial intelligence; smart city; inclusive employment