Please wait a minute...
金融研究  2023, Vol. 521 Issue (11): 115-131    
  本期目录 | 过刊浏览 | 高级检索 |
中国制造业的产能过剩与就业波动
皮建才, 宋大强
南京大学经济学院,江苏南京 210093
Manufacturing Overcapacity and Employment Volatility in China
PI Jiancai, SONG Daqiang
School of Economics, Nanjing University
下载:  PDF (602KB) 
输出:  BibTeX | EndNote (RIS)      
摘要 本文测算了各地区行业层面的产能过剩指数和就业增长率,分析了产能过剩与就业波动之间的内在联系。结果表明:产能过剩对我国整体就业增长率的抑制作用显著;分地区来看,产能过剩对东部地区就业增长率的抑制作用是全国水平的2倍以上,而产能过剩对就业增长率的负向影响在中西部地区不明显;分企业所有制来看,产能过剩对就业增长的排斥作用只在民营企业中显著;分行业性质来看,由制造业产能过剩引起的就业排斥现象,在劳动密集型行业中表现得较为明显,在技术密集型行业与资本密集型行业中表现得不明显;剔除去产能因素对劳动力需求的影响,产能过剩的就业波动效应依然显著。机制检验发现,金融化程度对制造业产能过剩引起的就业波动起正向调节作用,而企业社会责任和产业结构升级对制造业产能过剩引起的就业波动起负向调节作用。本文为我国优化稳就业政策提供了有益参考。
服务
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章
皮建才
宋大强
关键词:  产能过剩  就业波动  就业创造  就业破坏    
Summary:  In light of China's transition to a new phase of economic development, the focus on quality is gaining prominence in driving economic growth. Enterprises that fail to meet criteria regarding scale, technology, and environmental protection experience a gradual accumulation of excess production capacity. Generally speaking, the longer overcapacity persists, the more profound its impact on the economy becomes. On the one hand, the rapid growth of the economy may be hindered by the existence of overcapacity, which in turn may slow down employment expansion. On the other hand, overcapacity will also force the adjustment of domestic industrial structure, leading to an increased demand for innovative and high skilled labor by enterprises. Thus, questions arise: What is the impact of overcapacity on employment? Are there region, ownership, and industry-related disparities in this impact? If so, what factors contribute to these differences? Answering the above questions will not only enhance our understanding of the relationship between overcapacity and employment volatility, but also aid in identifying countermeasures to mitigate the adverse effect of overcapacity.
To explore this topic, this article utilizes industrial enterprise data from China spanning 1998 to 2007, as well as panel data from various manufacturing sub-industries across different regions in China from 1999 to 2020. The employment growth rate of different industries in different regions is calculated, and the capacity utilization rate is measured using the stochastic frontier analysis (SFA) method. Subsequently, we delve into the relationship between overcapacity and employment growth in detail. In addition, we eliminate the potential impact of resolving overcapacity on labor demand and re-examine the relationship between overcapacity and employment volatility. Furthermore, we characterize manufacturing employment volatility from three dimensions: the employment creation rate, the employment destruction rate, and the employment net growth rate. Meanwhile, we endeavor to identify the mechanisms through which overcapacity affects employment volatility, thereby providing a test of employment creation and destruction theory in the context of Chinese style overcapacity.
Our study yields five key findings. Firstly, overcapacity significantly suppress employment growth overall. Secondly, only overcapacity in the eastern region exhibits a notable inhibition effect on the employment growth rate from a regional perspective. Thirdly, only the overcapacity of private enterprises exerts a significant exclusion effect on employment growth while considering enterprise ownership. Fourthly, the decline in the employment growth rate caused by overcapacity in the manufacturing industries is primarily evident in labor-intensive ones from an industry nature standpoint. Finally, the mechanism analysis shows that a high degree of financialization strengthens the employment destruction caused by overcapacity in the manufacturing industries, while corporate social responsibility and industrial structure upgrading mitigate employment volatility stemming from overcapacity. Building upon these conclusions, we tentatively propose the following policy recommendations: (1) regions should continue to address overcapacity and minimize its adverse impact on employment; (2) skill training should be provided to enhance and diversify the vocational skills of ordinary workers; (3) private enterprises ought to accelerate their transformation pace, while state-owned enterprises need to establish suitable internal competition mechanisms; (4) labor-intensive industries should regard the improvement of technological content of products as the direction of industrial transformation; and (5) local governments should focus on creating a healthy and orderly financial market environment, guiding manufacturing enterprises to manage financial assets prudently and focus on their main business.
This article offers three innovative contributions. Firstly, by covering the four stages of overcapacity experienced by China since the 1990s, this article uses two sets of data: panel data on Chinese industrial enterprises from 1998 to 2007 and panel data on manufacturing sub-industries in various regions from 1999 to 2020. Secondly, this article comprehensively considers region, ownership, and industry-related differences in the impact of overcapacity on employment volatility, enabling the identification of targeted measures to address the impact of overcapacity. Thirdly, we attempt to clarify the mechanism through which overcapacity affects employment volatility by examining the degree of financialization development, corporate social responsibility, and industrial structure upgrading.
For future research, an interesting direction would be to compare the effect of overcapacity on employment volatility between developed and developing countries and uncover the underlying reasons behind national disparities. Obviously, such a study would enrich the research on the employment volatility effects of overcapacity.
Keywords:  Overcapacity    Employment Volatility    Job Creation    Job Destruction
JEL分类号:  D24   E24   L60  
基金资助: * 本文感谢江苏省第五期“333工程”科研资助项目(BRA2019041)和江苏省“卓博计划”(20220ZB71)的资助。感谢匿名审稿人的宝贵意见,文责自负。
作者简介:  皮建才,经济学博士,教授,南京大学经济学院,E-mail:pi2008@nju.edu.cn.
宋大强,经济学博士,博士后,南京大学经济学院,E-mail:1278801085@qq.com.
引用本文:    
皮建才, 宋大强. 中国制造业的产能过剩与就业波动[J]. 金融研究, 2023, 521(11): 115-131.
PI Jiancai, SONG Daqiang. Manufacturing Overcapacity and Employment Volatility in China. Journal of Financial Research, 2023, 521(11): 115-131.
链接本文:  
http://www.jryj.org.cn/CN/  或          http://www.jryj.org.cn/CN/Y2023/V521/I11/115
[1]陈爱贞、葛海燕和何诚颖,2021,《行业产能过剩如何影响正常企业出口?》,《经济学动态》第7期,第82~98页。
[2]范林凯、吴万宗、余典范和苏婷,2019,《中国工业产能利用率的测度、比较及动态演化——基于企业层面的经验研究》,《管理世界》第8期,第84~96页。
[3]高晓娜和兰宜生,2016,《产能过剩对出口产品质量的影响——来自微观企业数据的证据》,《国际贸易问题》第10期,第50~61页。
[4]顾雷雷、郭建鸾和王鸿宇,2020,《企业社会责任、融资约束与企业金融化》,《金融研究》第2期,第109~127页。
[5]黄信灶和赵波,2019,《产能过剩倒逼我国产业结构升级了吗?》,《经济社会体制比较》第2期,第18~29页。
[6]黄赜琳,2006,《技术进步与就业波动变化的影响分析——基于可分劳动RBC模型的实证检验》,《统计研究》第6期,第34~38页。
[7]金智和黄承浩,2022,《税收征管与企业社会责任——基于“金税三期”的证据》,《会计研究》第10期,第71~84页。
[8]纪志宏和纪敏,2018,《中国式产能过剩:风险·症结·治理》,中国金融出版社2018年3月第1版。
[9]李娟和吴建利,2015,《中国劳动力市场需求弹性估算》,《人口学刊》第6期,第93~102页。
[10]林毅夫、巫和懋和邢亦青,2010,《“潮涌现象”与产能过剩的形成机制》,《经济研究》第10期,第4~19页。
[11]刘斌和张列柯,2018,《去产能粘性粘住了谁:国有企业还是非国有企业》,《南开管理评论》第4期,第109~121+147页。
[12]刘晨跃、徐盈之和刘晴,2021,《产能过剩偏向性与环境污染——基于中介效应的检验》,《管理工程学报》第1期,第57~68页。
[13]马红旗和申广军,2021,《规模扩张、“创造性破坏”与产能过剩——基于钢铁企业微观数据的实证分析》,《经济学(季刊)》第1期,第71~92页。
[14]毛其淋和王玥清,2023,《ESG的就业效应研究:来自中国上市公司的证据》,《经济研究》第7期,第86~103页。
[15]毛其淋和杨晓冬,2022,《破解中国制造业产能过剩的新路径:外资开放政策的视角》,《金融研究》第7期,第38~56页。
[16]聂辉华、张彧和江艇,2014,《中国地区腐败对企业全要素生产率的影响》,《中国软科学》第5期,第37~48页。
[17]皮建才和宋大强,2021,《中国制造业体制性产能过剩的测度与比较》,《中南财经政法大学学报》第5期,第135~143页。
[18]曲玥,2014,《产能过剩与就业风险》,《劳动经济研究》第5期,第130~147页。
[19]任继球,2017,《我国钢铁和煤炭去产能对就业的影响——基于投入产出表的实证分析》,《宏观经济研究》第10期,第83~91页。
[20]沈坤荣、金刚和方娴,2017,《环境规制引起了污染就近转移吗?》,《经济研究》第5期,第44~59页。
[21]唐晓华、张欣钰和李阳,2018:《中国制造业与生产性服务业动态协调发展实证研究》,《经济研究》第3期,第79~93页。
[22]王君斌和刘河北,2021,《提高出口退税能够“稳就业”和“稳外贸”吗?》,《金融研究》第12期,第152~169页。
[23]宣烨,2019,《要素价格扭曲、制造业产能过剩与生产性服务业发展滞后》,《经济学动态》第3期,第91~104页。
[24]阳立高、龚世豪、王铂和晁自胜,2018,《人力资本、技术进步与制造业升级》,《中国软科学》第1期,第138~148页。
[25]杨振兵和张诚,2015,《中国工业部门产能过剩的测度与影响因素分析》,《南开经济研究》第6期,第92~109页。
[26]于斌斌和陈露,2019,《新型城镇化能化解产能过剩吗?》,《数量经济技术经济研究》第1期,第22~41页。
[27]于斌斌、孙波约和郭东,2022,《企业金融化与产能过剩治理:“雪中送炭”还是“雪上加霜”》,《经济学家》第10期,第84~95页。
[28]张成思和张步昙,2016,《中国实业投资率下降之谜:经济金融化视角》,《经济研究》第12期,第32~46页。
[29]Acemoglu, D. and P. Restrepo, 2022, “Tasks, Automation, and the Rise in U. S. Wage Inequality”, Econometrica, 90(5), pp.1973~2016.
[30]Bas, M., P. Bombarda, S. Jean and G. Orefice, 2021, “Firms' Exports, Volatility and Skills: Evidence from France”, European Economic Review, 140, 103941.
[31]Berndt, E. R. and C. J. Morrison, 1981, “Capacity Utilization Measures: Underlying Economic Theory and an Alternative Approach”, American Economic Review, 71(2), pp.48~52.
[32]Belke, A., A. Oeking and R. Setzer, 2015, “Domestic Demand, Capacity Constraints and Exporting Dynamics: Empirical Evidence for Vulnerable Euro Area Countries”, Economic Modelling, 48(C), pp.315~325.
[33]Brandt, L., J. V. Biesebroeck and Y. Zhang, 2012, “Creative Accounting or Creative Destruction? Firm-level Productivity Growth in Chinese Manufacturing”, Journal of Development Economics, 97(2), pp.339~351.
[34]Dinopoulos, E., W. H. Grieben and F. Sener, 2023, “A Policy Conundrum: Schumpeterian Growth or Job Creation?”, Economic Modelling, 126, 106378.
[35]Feng, Y., D. Lagakos and J. E. Rauch, 2018, “Unemployment and Development”, NBER Working Paper, No.25171.
[36]Fisman, R. and J. Svensson, 2007, “Are Corruption and Taxation Really Harmful to Growth? Firm Level Evidence”, Journal of Development Economics, 83(1), pp.63~75.
[37]Haltiwanger, J., R. S. Jarmin and J. Miranda, 2013, “Who Create Jobs? Small versus Large versus Young”, The Review of Economics and Statistics, 95(2), pp.347~361.
[38]Klein, L. R., 1960, “Some Theoretical Issues in the Measurement of Capacity”, Econometrica, 28(2), pp.272~286.
[39]Klein, L. R. and R. S. Preston, 1967, “Some New Results in the Measurement of Capacity Utilization”, American Economic Review, 57(1), pp.34~58.
[40]Kurz, C. and M. Z. Senses, 2016, “Importing, Exporting, and Firm-Level Employment Volatility”, Journal of International Economics, 98(C), pp.160~175.
[41]Long, J. B. and C. Plosser, 1983, “Real Business Cycles”, Journal of Political Economy, 91(1), pp.39~69.
[42]Ma, H., X. Qiao and Y. Xu, 2015, “Job Creation and Job Destruction in China during 1998-2007”, Journal of Comparative Economics, 43(4), pp.1085~1100.
[43]Mortensen, D. T. and C. A. Pissarides, 1994, “Job Creation and Job Destruction in the Theory of Unemployment”, Review of Economic Studies, 61(3), pp.397~415.
[1] 朱宁, 曾恒煜, 于之倩. 中国商业银行运营效率研究 ——基于多阶段合作型网络DEA的实证分析[J]. 金融研究, 2023, 518(8): 37-54.
[2] 冀云阳, 周鑫, 张谦. 数字化转型与企业创新——基于研发投入和研发效率视角的分析[J]. 金融研究, 2023, 514(4): 111-129.
[3] 罗长远, 曾帅. “一带一路”建设对要素配置效率的影响——基于中国上市工业企业的研究[J]. 金融研究, 2022, 505(7): 154-170.
[4] 李丽芳, 谭政勋, 叶礼贤. 改进的效率测算模型、影子银行与中国商业银行效率[J]. 金融研究, 2021, 496(10): 98-116.
[5] 刘贯春, 司登奎, 刘芳. 人力资本偏向金融部门如何影响实体经济增长?[J]. 金融研究, 2021, 496(10): 78-97.
[6] 朱宁, 刘伟其, 于之倩, 王兵. 中国银行业结构性全要素生产率增长研究[J]. 金融研究, 2021, 493(7): 1-18.
[7] 公衍磊, 邓辛, 杨金强. 全要素生产率、产能利用率与企业金融资源配置——基于中国上市企业委托贷款公告数据的经验分析[J]. 金融研究, 2020, 481(7): 57-74.
[8] 丁宁, 任亦侬, 左颖. 绿色信贷政策得不偿失还是得偿所愿?——基于资源配置视角的PSM-DID成本效率分析[J]. 金融研究, 2020, 478(4): 112-130.
[9] 蔡卫星. 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[J]. 金融研究, 2019, 466(4): 39-55.
[10] 王兵, 肖文伟. 环境规制与中国外商直接投资变化——基于DEA多重分解的实证研究[J]. 金融研究, 2019, 464(2): 59-77.
[11] 朱宁, 梁林, 沈智扬, 杜文洁. 经济新常态背景下中国商业银行内生性效率变化及分解[J]. 金融研究, 2018, 457(7): 108-123.
[12] 祝树金, 赵玉龙. 资源错配与企业的出口行为——基于中国工业企业数据的经验研究[J]. 金融研究, 2017, 449(11): 49-64.
[13] 罗知, 张川川. 信贷扩张、房地产投资与制造业部门的资源配置效率[J]. 金融研究, 2015, 421(7): 60-75.
[14] 陈经伟, 姜能鹏. 中国OFDI技术创新效应的传导机制——基于资本要素市场扭曲视角的分析[J]. 金融研究, 2020, 482(8): 74-92.
No Suggested Reading articles found!
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
版权所有 © 《金融研究》编辑部
本系统由北京玛格泰克科技发展有限公司设计开发 技术支持:support@magtech.com.cn
京ICP备11029882号-1