Abstract
With the increasing intensity of domestic environmental regulation policies, while effectively curbing the pollution problem, it also has a great impact on the production and operation of enterprises, management methods, entry or exit from the market and other aspects, which will inevitably be accompanied by the transfer and flow of labor. Therefore, how to effectively solve environmental problems while ensuring employment stability and promoting the optimal allocation of labor force is an urgent problem to be solved. This paper takes the “Environmental Protection Regulatory Talk” implemented since 2014 as the policy impact, and uses instrumental variable method to analyze environmental governance, technological innovation and employment structure under the same framework. The study found that: (1) Environmental governance can optimize the employment structure of enterprises, and the intermediary channel of technological innovation plays a significant role. (2) From the heterogeneity analysis results, the employment structure optimization effect of environmental governance in the eastern region and the First-tier cities is stronger, which also widens the innovation gap and employment gap between regions. In addition, in heavy pollution enterprises, non-state-owned enterprises and large-scale enterprises, the effect of environmental governance on employment structure optimization is more significant. The above research conclusions have important implications for achieving a win–win situation between environmental protection and employment structure optimization. The results demonstrate that policy makers should promote the deep integration of environmental policies and employment policies, improve the incentive mechanism of environmental governance for technological innovation of enterprises, give play to the demonstration and driving role of developed regions, and implement differentiated support policies for heterogeneous enterprises.
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Data availability
The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.
Notes
As shown in the Graphical Abstract, in the face of serious environmental pollution problems, the government has demonstrated its determination to control polluting enterprises and solve prominent environmental problems through environmental governance policies. Of course, increasingly strict environmental governance policies will have two effects on enterprises: “compliance costs” and “innovation compensation”. Among them, labor is not only an important cost for enterprises but also a source of innovation. This will inevitably be accompanied by the transfer and flow of labor, as well as changes and adjustments in the structure of the employment market.
“Environmental Protection Regulatory Talk” is a policy issued by China in 2014, in which the Ministry of Environmental Protection issued the “Interim Measures for Interviews with the Ministry of Environmental Protection”. It is an administrative measure to meet with relevant leaders of local governments and relevant departments who have not fulfilled their environmental protection duties or have not fulfilled their duties properly, conduct warning talks, point out relevant issues, propose rectification requirements, and supervise the rectification in accordance with the law. This article mainly uses the Difference in Difference (DID) method to estimate the model. Among them, “Environmental Protection Regulatory Talk” is taken as the estimated policy shock.
As of 2021, 67 local governments have been regulatory talked by the Ministry of ecological environment (formerly the Ministry of environmental protection). The data is available from the corresponding author on reasonable request.
This paper classifies the samples based on the classification criteria of cities in the “New First- tier Cities Summit” (held by the new First-tier cities Research Institute of China Business News on May 24, 2019). The summit evaluated 337 cities in China according to five dimensions of business resource concentration, urban hub, urban activity, lifestyle diversity and future plasticity. A total of 4 First-tier cities, 15 new First-tier cities, 30 Second-tier cities, 70 Third -tier cities, 90 Fourth-tier cities and 128 Fifth-tier cities were selected. In this paper, 4 First-tier cities and 15 new First-tier cities are collectively referred to as “First-tier cities”. The criteria for the division of new first-tier cities began at the “New First-tier Cities Summit” (2019). The latest “New First-tier Cities Summit” has be held in 2021. By 2021, the division of cities has not changed compared with 2019.
Based on the “Announcement on the Implementation of Special Emission Limits for Air Pollutants” issued by the Ministry of Environmental Protection, the heavy pollution industries in this paper include six major industries such as thermal power, steel, petrochemical, cement, non-ferrous metals, and chemical industry. The above industries are combined with the standards of the “Guidelines for Industry Classification of Listed Companies” to match the heavily polluting enterprises. In addition, the scale of enterprises is ranked by total assets, and the top 25% of enterprises are large-scale enterprises.
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Acknowledgements
This study was funded by the General Research Project of Philosophy and Social Sciences in Universities of Jiangsu Province (Grant Number:2023SJYB0182), Youth Science Foud Project of National Natural Science Foundation of China (Grant Number: 72304148), the Startup Foundation for Introducing Talent of NUIST (Grant Number: 2023r068).
Funding
This study was funded by the Youth Science Foud Project of National Natural Science Foundation of China (Grant Number: 72304148), General Research Project of Philosophy and Social Sciences in Universities of Jiangsu Province (Grant Number: 2023SJYB0182), the Startup Foundation for Introducing Talent of NUIST (Grant Number: 2023r068).
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Yang, L., Liu, Y. Environmental governance, technological innovation and employment structure change: evidence from China. Environ Dev Sustain (2024). https://doi.org/10.1007/s10668-023-04414-3
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DOI: https://doi.org/10.1007/s10668-023-04414-3