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Environmental regulations, capacity utilization, and high-quality development of manufacturing: an analysis based on Chinese provincial panel data.
Wang, Hongyang; Li, Baizhou.
Afiliación
  • Wang H; School of Economics and Management, Harbin Engineering University, Harbin, 150001, China.
  • Li B; School of Economics and Management, Harbin Engineering University, Harbin, 150001, China. libaizhouheu@126.com.
Sci Rep ; 11(1): 19566, 2021 10 01.
Article en En | MEDLINE | ID: mdl-34599231
The high-quality development of the manufacturing industry is an important strategic task for Chinese economic development. The rapid development of the manufacturing industry is also accompanied by problems such as overcapacity and environmental pollution. This paper analyzes the impact of capacity utilization on the high-quality development of manufacturing and establishes a nonlinear threshold regression model on this basis, and studies and analyzes environmental regulations as a threshold variable under the influence of capacity utilization rate on the high-quality development of the manufacturing industry. The research results show that: capacity utilization, profitability, foreign direct investment, and government participation all have a significant positive impact on the high-quality development of the manufacturing industry; environmental regulations have a significant negative impact on the high-quality development of the manufacturing industry. And in the model of the effect of capacity utilization on the high-quality development of the manufacturing industry, environmental regulation has a single threshold effect. With the increase in the intensity of environmental regulation, the coefficient and significance of the effect of capacity utilization on the high-quality development of the manufacturing industry have changed. Finally, this article puts forward corresponding policies and suggestions based on the results of data analysis.

Texto completo: 1 Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Sci Rep Año: 2021 Tipo del documento: Article

Texto completo: 1 Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Sci Rep Año: 2021 Tipo del documento: Article