人工智能应用、劳动报酬份额与失业率动态关系的实证分析

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摘要人工智能技术主要通过替代效应和补偿效应两大机制对劳动力就业和收入分配产生影响,在人工智能发展的不同阶段,其主导作用机制存在差别。利用2006~2019年省际面板数据构建PVAR模型,并进行脉冲响应和方差分解分析,探究人工智能应用、劳动就业和收入分配之间的动态关系,研究结果显示：就人工智能应用对失业率的影响而言,我国失业类型仍以自然失业和结构性失业为主,人工智能技术推广对于劳动力市场的挤出效应并不明显,反而缓解了就业压力,有效降低了失业率;就劳动报酬份额的变化而言,人工智能应用对于劳动报酬份额的抑制作用初步显现,且随着时期的推移,人工智能的冲击效果将会更加显著。与此同时,失业率和劳动报酬份额之间具有对称的负向关联,即失业率的攀升会抑制劳动报酬份额,反之亦然;但是二者对于人工智能应用程度均无显著作用,表明当前我国人工智能技术推广受劳动力市场反馈影响较小。

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	马国旺
	李焙尧

关键词 ：人工智能, 失业率, 劳动报酬份额, 收入分配, PVAR模型

Abstract：Artificial intelligence technology has dual effects on employment and income distribution through its own substitution and compensation effects. In different stages of the development of artificial intelligence, its dominant mechanisms are different. Based on the provincial panel data from 2006 to 2019, the PVAR model is constructed, and impulse response and variance decomposition are carried out to explore the dynamic relationship among the application of artificial intelligence, employment and income distribution. The findings show that: As for the impact of artificial intelligence application on the unemployment rate, the unemployment in China are mostly natural and structural. The crowding-out effect of the wide use of artificial intelligence technology on labor market is not obvious, on the contrary, it creates a number of new jobs and effectively relieves the employment pressure of workers. As for the change in the share of labor compensation, artificial intelligence has already shown its inhibitory effect, and this impact will grow with time. At the same time, the unemployment rate and share of labor compensation are negatively correlated. It means the rising unemployment rate brings down the share of labor compensation, and vice versa. However, both of them have no significant effect on the application degree of artificial intelligence, indicating that currently the wide use of artificial intelligence technology in China is less affected by the feedback of the labor market.

Key words： artificial intelligence unemployment rate share of labor compensation income distribution PVAR model

收稿日期: 2020-11-11

中图分类号:

F249.2

基金资助:天津市哲学社会科学规划重点项目“高质量发展阶段增强天津市民营经济‘三力'研究”（TJLJ19-002）

作者简介: 马国旺,天津财经大学经济学院教授、博士生导师,主要从事当代西方经济学流派比较、劳动力市场理论与政策研究;李焙尧,天津财经大学经济学院博士研究生,主要从事经济理论、劳动力市场理论与政策研究。

引用本文:

马国旺, 李焙尧. 人工智能应用、劳动报酬份额与失业率动态关系的实证分析[J]. 《深圳大学学报》（人文社科版）, 2021, 38(2): 61-70. MA Guo-wang, LI Bei-yao. An Empirical Analysis of the Dynamic Relationship among Application of Artificial Intelligence, Share of Labor Compensation and Unemployment Rate. , 2021, 38(2): 61-70.

链接本文:

https://xb.szu.edu.cn/CN/ 或 https://xb.szu.edu.cn/CN/Y2021/V38/I2/61

[1] 国务院.新一代人工智能发展规划[EB/OL].http://www.gov.cn/xinwen/2017-07/20/content_5212064.htm,2020-07-20.
[2] 陈永伟. 人工智能与经济学:近期文献的一个综述[J].东北财经大学学报,2018,(3):6-21.
[3] Nicholas Bloom,et al.The Distinct Effects of Information Technology and Communication Technology on Firm Organization[J].Management Science,2009,60(12):2859-2885.
[4] 马克思恩格斯文集(第八卷)[M]马克思恩格斯文集(第八卷)[M].北京:人民出版社,2009. 365-366.
[5] Alan Manning,Maarten Goos.Job Polarization in Europe[J].The American Economic Review,2009,99(2):58-63.
[6] Autor David.Why are There Still so Many Jobs?The History and Future of Workplace Automation[J].Journal of Economic Perspectives,2015,29(3):3-30.
[7] Acemoglu Daron,Restrepo Pascual.Automation and New Tasks:How Technology Displaces and Reinstates Labor[J].Journal of Economic Perspectives,2019,33(2):3-30.
[8] Benzell,Seth G.,et al.Robots Are Us:Some Economics of Human Replacement[R].NBER Working Papers NO.w209 41,2015.
[9] Francesco Caselli, Alan Manning.Robot Arithmetic: New Technology and Wages[J].American Economic Review Insights,2019,1(1):1-12.
[10] Georg Graetz,Guy Michaels.Robots at Work[J].The Review of Economics and Statistics,2018,100(5):753-768.
[11] Uma Lele,Sambuddha Goswami.The Fourth Industrial Revolution, Agricultural and Rural Innovation, and Implications for Public Policy and Investments: A Case of India[J].Agricultural Economics,2017,48(1):87-100.
[12] 蒋南平,邹宇.人工智能与中国劳动力供给侧结构性改革[J].四川大学学报(哲学社会科学版),2018,(1):130-138.
[13] 邓洲,黄娅娜.人工智能发展的就业影响研究[J].学习与探索,2019,(7):99-106.
[14] 杨伟国,邱子童,吴清军.人工智能应用的就业效应研究综述[J].中国人口科学,2018,(5):109-119.
[15] 谢萌萌,夏炎,潘教峰等.人工智能、技术进步与低技能就业——基于中国制造业企业的实证研究[J].中国管理科学,2019,(12):1-9.
[16] 吴清军,陈轩,王非等.人工智能是否会带来大规模失业? ——基于电商平台人工智能技术、经济效益与就业的测算[J].山东社会科学,2019,(3):73-80.
[17] 蔡昉. 经济学如何迎接新技术革命[J].劳动经济研究,2019,(6):3-20.
[18] 王裕国. 推进中国新科技消费发展的思考[J].经济与管理,2020,(2):1-6.
[19] 蔡跃洲,陈楠.新技术革命下人工智能与高质量增长、高质量就业[J].数量经济技术经济研究,2019, (5):3-22.
[20] 张鹏飞. 人工智能与就业研究新进展[J].经济学家,2018,(8):27-33.
[21] 张于喆. 人工智能、机器人的就业效应及对策建议[J].科学管理研究,2019,(1):43-45.
[22] Jeff Borland,Michael Coelli.Are Robots Taking Our Jobs?[J].Australian Economic Review,2017,50(4):377-397.
[23] Andrew Levin, et al.Unit Root Tests in Panel Data: Asymptotic and Finite-Sample Properties[J].Journal of Econometrics,2002,108(1):1-24.
[24] Inessa Love,Lea Zicchino.Financial Development and Dynamic Investment Behavior:Evidence from Panel VAR[J].The Quarterly Review of Economics and Finance,2006,46(2):190-210.