机器人在中国:现状、未来与影响——来自中国企业-劳动力匹配调查(CEES)的经验证据
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摘要
作为一个正处于经济转型关键期的制造业大国,中国工业机器人的发展现状、未来与影响是一个十分重要的研究课题。然而,由于一手调查数据的缺乏,现有文献并未就上述问题展开全面的实证分析。针对现有文献的缺憾,本文综合运用2015、2016和2018年连续三轮的"中国企业-劳动力匹配调查"(CEES)数据,就机器人在中国的发展趋势及其对企业的影响效应进行了深入的实证研究。运用加权统计、倾向得分匹配、预测分析等多种识别策略,本文研究发现:第一,近年来机器人在我国呈现爆发性增长趋势,已对中国近1/3以上的制造业企业产生影响。按照现有投资增速,我国机器人使用覆盖率、使用密度将在2025年前后逼近先进国家水平。第二,机器人对我国劳动力市场的整体替代效应为0.3%;并且,上述影响效应对不同技能劳动力存在非对称性影响,非技能劳动力受到机器人的"换人"冲击更大。第三,我国企业的机器人使用存在明显的微观差异,生产率异质性、政府的政策偏倚是造成机器人使用具有微观差异的重要原因。第四,因果推断表明,机器人使用对我国企业的生产效率、质量能力和管理效率具有重要的促进效应,并能在较大程度上降低企业经营的不确定性风险;根据现有机器人投资增速数据,我国机器人对劳动力市场的整体替代效应将在2025年前后攀升至4.7%。本文的研究结论对全面认知我国机器人的发展现状与宏观经济影响具有重要的借鉴意义。
As a manufacturing country that is in the critical period of economic transformation,the development status,future and impact of China's industrial robots is a very important research topic.However,due to the lack of first-hand survey data,the existing literature does not conduct a comprehensive empirical analysis of the above issues.In view of the shortcomings of the existing literature,this paper comprehensively uses the three consecutive rounds of " China Employer-Employee Survey"(CEES)data in 2015,2016 and 2018 to further explore the development trend of robots in China and its impact on enterprises.Empirical research.Using weighted statistics,propensity score matching,predictive analysis and other identification strategies,this paper finds that:First,in recent years,robots have experienced explosive growth in China,which has affected more than one-third of China's manufacturing enterprises.According to the current investment growth rate,China's robot coverage and use density will approach the advanced national level around 2025.Second,the overall substitution effect of robots on China's labor market is 0.3%;and,the above-mentioned influence effects have asymmetric effects on different skill labors,and unskilled labor is more impacted by robots' "substitution".Third,there are obvious microscopic differences in the use of robots in Chinese enterprises.Productivity heterogeneity and government policy bias are important reasons for the microscopic differences in robot use.Fourth,the causal inference shows that the use of robots has an important promoting effect on the production efficiency,quality capability and management efficiency of Chinese enterprises,and can reduce the uncertainty of business operations to a large extent;according to the growth rate of existing robot investment The overall substitution effect of China's robots on the labor market will climb to 4.7%around 2025.The conclusions of this paper have important reference significance for the comprehensive understanding of the development status and macroeconomic impact of Chinese robots.
As a manufacturing country that is in the critical period of economic transformation,the development status,future and impact of China's industrial robots is a very important research topic.However,due to the lack of first-hand survey data,the existing literature does not conduct a comprehensive empirical analysis of the above issues.In view of the shortcomings of the existing literature,this paper comprehensively uses the three consecutive rounds of " China Employer-Employee Survey"(CEES)data in 2015,2016 and 2018 to further explore the development trend of robots in China and its impact on enterprises.Empirical research.Using weighted statistics,propensity score matching,predictive analysis and other identification strategies,this paper finds that:First,in recent years,robots have experienced explosive growth in China,which has affected more than one-third of China's manufacturing enterprises.According to the current investment growth rate,China's robot coverage and use density will approach the advanced national level around 2025.Second,the overall substitution effect of robots on China's labor market is 0.3%;and,the above-mentioned influence effects have asymmetric effects on different skill labors,and unskilled labor is more impacted by robots' "substitution".Third,there are obvious microscopic differences in the use of robots in Chinese enterprises.Productivity heterogeneity and government policy bias are important reasons for the microscopic differences in robot use.Fourth,the causal inference shows that the use of robots has an important promoting effect on the production efficiency,quality capability and management efficiency of Chinese enterprises,and can reduce the uncertainty of business operations to a large extent;according to the growth rate of existing robot investment The overall substitution effect of China's robots on the labor market will climb to 4.7%around 2025.The conclusions of this paper have important reference significance for the comprehensive understanding of the development status and macroeconomic impact of Chinese robots.
引文
[1]CEES研究团队,2017,《中国制造业企业如何应对劳动力成本上升?--中国企业-劳动力匹配调查(cees)报告(2015-2016)》,《宏观质量研究》第2期。[CEES Research Team,2017,How do Chinese manufacturing companies cope with rising labor costs?--China Employer Employee Survey(CEES)Report(2015-2016),Journal of Macro-quality Research,2.]
[2]程虹、许伟,2016:《质量创新战略:质量管理的新范式与框架体系研究》,《宏观质量研究》第4期。[Cheng Hong,Xu Wei,2016,Quality Innovation Strategy:A New Paradigm and Framework of Quality Management,Journal of Macro-quality Research,4.]
[3]蔡昉,2013:《中国经济增长如何转向全要素生产率驱动型》,《中国社会科学,》第1期。[Cai Fang,2013,How Can Chinese Economy Achieve the Transition toward Total Factor Productivity Growth?Social Sciences in China,1.]
[4]戴翔、徐柳,2018:《如何破解我国出口增速下降困局》,《宏观质量研究》第1期,[Dai Xiang,Xu liu,2018,How to Decipher the Decline Dilemma of China’s Export Growth,Journal of Macro-quality Research,1.]
[5]邓悦、黄诗雅,2016,《技术进步如何影响我国产品质量?——基于劳动倦怠视角的实证研究》,《宏观质量研究》第2期。[Deng Yue,Huang Shiya,2016,How Technological Advances Affect the Quality of the Products:Based on Labor Burnout Empirical Research Perspective,Journal of Macro-quality Research,2.]
[6]李唐、董一鸣、王泽宇,2018:《管理效率、质量能力与企业全要素生产率——基于“中国企业-劳动力匹配调查”的实证研究》,《管理世界》第7期。[Li Tang,Dong Yiming,Wang Zeyu,2018,Management efficiency,quality capability and enterprise total factor productivity,Management World,7]
[7]李丫丫、潘安、彭永涛、杨文斌,2018:《工业机器人对省域制造业生产率的异质性影响》,《中国科技论坛》第6期。[Yaya Li,An Pan,Yongtao Peng and Wenbin Yang,2018,Effects of Industrial Robots on the Productivity Heterogeneity of Chinese Provincial Manufacturing Industry,Forum on Science and Technology in China,6.]
[8]吕洁、杜传文、李元旭,2017:《工业机器人应用会倒逼一国制造业劳动力结构转型吗?——基于1990—2015年间22个国家的经验分析》,《科技管理研究》第22期。[Jie Lv,Chuanwen Du and Yuanxu Li,2017,Do the Application of Industrial Robots Force a Country's Manufacturing Labor Structures Transforming?—Based on the Empirical Analysis of 22Countries in 1990-2015,Science and Technology Management Research,22.]
[9]余淼杰、张睿,2016:《国际贸易中的产品质量研究:一个综述》,《宏观质量研究》第3期。[Yu Miaojie,Zhang Yui,2016,Product Quality in International Trade:A Review,Journal of Macro-quality Research,3.]
[10]庄子银,2007:《创新、企业家活动配置与长期经济增长》,《经济研究》第8期。[Zhuang Ziyin,2007,Innovation,Allocation of Entrepreneurial Activities and Long Run Economic Growth,Economic Research Journal,8.]
[11]周文斌,2017:《机器人应用对人力资源管理的影响研究》,《南京大学学报(哲学·人文科学·社会科学》第6期。[Wenbin Zhou,2017,Research on the Influence of Robot Application on Human Resource Management,Journal of Nanjing University(Philosophy.Humanities and Social Sciences),6.]
[12]Acemoglu,D.,&Restrepo,P.,2017,Robots and Jobs:Evidence from US Labor Markets,National Bureau of Economic Research:(No.w23285).
[13]Acemoglu,D.,&Restrepo,P.,2018,The Race between Man and Machine:Implications of Technology for Growth,Factor Shares and Employment.American Economic Review,108(6):1488-1542.
[14]Brandt,Loren&Zhu,Xiaodong,2010,Accounting for China's Growth,IZA Discussion Papers 4764,Institute for the Study of Labor(IZA).
[15]Benhabib,J.,Perla,J.,&Tonetti,C.,2014,Catch-up and fall-back through innovation and imitation,Journal of Economic Growth:19(1),1-35.
[16]Bloom,N.,Davis,S.J.,Foster,L.,Lucking,B.,Ohlmacher,S.,&Saporta Eksten,I.,2017,Businesslevel expectations and uncertainty.Social Science Electronic Publishing.
[17]Brandt,L.,2015,“Policy Perspectives from the Bottom Up:What Do Firm-Level Data Tell Us China Needs to Do?”,In:Glick R.,Spiegel,M.M.(Eds.),Policy Challenges in A Diverging Global Economy,AsiaEconomic Policy Conference,San Francisco:pp(151-172).
[18]Coe,D.T.,&Helpman,E.,1995,International r&d spillovers.,European economic review:39(5),859-887.
[19]Cheng Hong,Ruixue Jia&Hongbin Li,2018,The rise of robots in China,Forthcoming in Journal of Economic Perspectives.
[20]Korinek,A.,&Stiglitz,J.E.,2017,Artificial intelligence and its implications for income distribution and unemployment,National Bureau of Economic Research:(No.w24174).
[21]Li,H.,Liu,P.W.,&Zhang,J.,2012,Estimating returns to education using twins in urban china,Journal of Development Economics:97(2),494-504.
[22]Li,H.,Li,L.,Wu,B.,&Xiong,Y.,2012,The end of cheap Chinese labor,Journal of Economic Perspectives:26(4),57-74.
[23]Li,H.,Loyalka,P.,Rozelle,S.,&Wu,B.,2017,Human capital and China's future growth.Journal of Economic Perspectives:31(1),25-48.
[24]Naughton,B.,2017,Is China socialist.Journal of Economic Perspectives,31(1):3-24.
[25]Sachs,J.D.,&Kotlikoff,L.J.,2012,Smart machines and long-term misery,National Bureau of Economic Research:(No.w18629).
(1)选择规模、所有制、出口、资本-劳动比、行业类型等变量作为匹配变量,基于k近邻匹配的原则构造1:1配对的子样本。
(1)根据“中国企业-劳动力匹配调查”的问卷设计,本地市场是指本县区、本地市或本省的销售市场。
[2]程虹、许伟,2016:《质量创新战略:质量管理的新范式与框架体系研究》,《宏观质量研究》第4期。[Cheng Hong,Xu Wei,2016,Quality Innovation Strategy:A New Paradigm and Framework of Quality Management,Journal of Macro-quality Research,4.]
[3]蔡昉,2013:《中国经济增长如何转向全要素生产率驱动型》,《中国社会科学,》第1期。[Cai Fang,2013,How Can Chinese Economy Achieve the Transition toward Total Factor Productivity Growth?Social Sciences in China,1.]
[4]戴翔、徐柳,2018:《如何破解我国出口增速下降困局》,《宏观质量研究》第1期,[Dai Xiang,Xu liu,2018,How to Decipher the Decline Dilemma of China’s Export Growth,Journal of Macro-quality Research,1.]
[5]邓悦、黄诗雅,2016,《技术进步如何影响我国产品质量?——基于劳动倦怠视角的实证研究》,《宏观质量研究》第2期。[Deng Yue,Huang Shiya,2016,How Technological Advances Affect the Quality of the Products:Based on Labor Burnout Empirical Research Perspective,Journal of Macro-quality Research,2.]
[6]李唐、董一鸣、王泽宇,2018:《管理效率、质量能力与企业全要素生产率——基于“中国企业-劳动力匹配调查”的实证研究》,《管理世界》第7期。[Li Tang,Dong Yiming,Wang Zeyu,2018,Management efficiency,quality capability and enterprise total factor productivity,Management World,7]
[7]李丫丫、潘安、彭永涛、杨文斌,2018:《工业机器人对省域制造业生产率的异质性影响》,《中国科技论坛》第6期。[Yaya Li,An Pan,Yongtao Peng and Wenbin Yang,2018,Effects of Industrial Robots on the Productivity Heterogeneity of Chinese Provincial Manufacturing Industry,Forum on Science and Technology in China,6.]
[8]吕洁、杜传文、李元旭,2017:《工业机器人应用会倒逼一国制造业劳动力结构转型吗?——基于1990—2015年间22个国家的经验分析》,《科技管理研究》第22期。[Jie Lv,Chuanwen Du and Yuanxu Li,2017,Do the Application of Industrial Robots Force a Country's Manufacturing Labor Structures Transforming?—Based on the Empirical Analysis of 22Countries in 1990-2015,Science and Technology Management Research,22.]
[9]余淼杰、张睿,2016:《国际贸易中的产品质量研究:一个综述》,《宏观质量研究》第3期。[Yu Miaojie,Zhang Yui,2016,Product Quality in International Trade:A Review,Journal of Macro-quality Research,3.]
[10]庄子银,2007:《创新、企业家活动配置与长期经济增长》,《经济研究》第8期。[Zhuang Ziyin,2007,Innovation,Allocation of Entrepreneurial Activities and Long Run Economic Growth,Economic Research Journal,8.]
[11]周文斌,2017:《机器人应用对人力资源管理的影响研究》,《南京大学学报(哲学·人文科学·社会科学》第6期。[Wenbin Zhou,2017,Research on the Influence of Robot Application on Human Resource Management,Journal of Nanjing University(Philosophy.Humanities and Social Sciences),6.]
[12]Acemoglu,D.,&Restrepo,P.,2017,Robots and Jobs:Evidence from US Labor Markets,National Bureau of Economic Research:(No.w23285).
[13]Acemoglu,D.,&Restrepo,P.,2018,The Race between Man and Machine:Implications of Technology for Growth,Factor Shares and Employment.American Economic Review,108(6):1488-1542.
[14]Brandt,Loren&Zhu,Xiaodong,2010,Accounting for China's Growth,IZA Discussion Papers 4764,Institute for the Study of Labor(IZA).
[15]Benhabib,J.,Perla,J.,&Tonetti,C.,2014,Catch-up and fall-back through innovation and imitation,Journal of Economic Growth:19(1),1-35.
[16]Bloom,N.,Davis,S.J.,Foster,L.,Lucking,B.,Ohlmacher,S.,&Saporta Eksten,I.,2017,Businesslevel expectations and uncertainty.Social Science Electronic Publishing.
[17]Brandt,L.,2015,“Policy Perspectives from the Bottom Up:What Do Firm-Level Data Tell Us China Needs to Do?”,In:Glick R.,Spiegel,M.M.(Eds.),Policy Challenges in A Diverging Global Economy,AsiaEconomic Policy Conference,San Francisco:pp(151-172).
[18]Coe,D.T.,&Helpman,E.,1995,International r&d spillovers.,European economic review:39(5),859-887.
[19]Cheng Hong,Ruixue Jia&Hongbin Li,2018,The rise of robots in China,Forthcoming in Journal of Economic Perspectives.
[20]Korinek,A.,&Stiglitz,J.E.,2017,Artificial intelligence and its implications for income distribution and unemployment,National Bureau of Economic Research:(No.w24174).
[21]Li,H.,Liu,P.W.,&Zhang,J.,2012,Estimating returns to education using twins in urban china,Journal of Development Economics:97(2),494-504.
[22]Li,H.,Li,L.,Wu,B.,&Xiong,Y.,2012,The end of cheap Chinese labor,Journal of Economic Perspectives:26(4),57-74.
[23]Li,H.,Loyalka,P.,Rozelle,S.,&Wu,B.,2017,Human capital and China's future growth.Journal of Economic Perspectives:31(1),25-48.
[24]Naughton,B.,2017,Is China socialist.Journal of Economic Perspectives,31(1):3-24.
[25]Sachs,J.D.,&Kotlikoff,L.J.,2012,Smart machines and long-term misery,National Bureau of Economic Research:(No.w18629).
(1)选择规模、所有制、出口、资本-劳动比、行业类型等变量作为匹配变量,基于k近邻匹配的原则构造1:1配对的子样本。
(1)根据“中国企业-劳动力匹配调查”的问卷设计,本地市场是指本县区、本地市或本省的销售市场。