RESUMO
As an important indicator of sustainable development, industrial eco-efficiency (IEE) has aroused growing attention from governments all over the world including China, in recent decades. The Chinese government has introduced numerous environmental regulations; however, the environmental pollution issue does not appear to have been solved. Moreover, although several earlier studies have shown that environmental regulations may promote innovation, there is no consensus on their ultimate effects on IEE. Therefore, this study took a critical look at the connection between environmental regulations and IEE in 36 Chinese sub-sectors from 2009 to 2018. Based on the weak Porter hypothesis (weak PH) and strong Porter hypothesis (strong PH), this paper constructed two panel regression models and conducted group analysis by pollution intensity to check the relationships among environmental regulations, technological innovation, and IEE. It was found that environmental regulations can improve technological innovation and IEE, but these impacts vary across different pollution groups. Specifically, environmental regulations have a U-shaped or inverted U-shaped relationship with technological innovation and IEE. Of the 36 sub-sectors, 26 prove the existence of the Weak PH while 10 verify the Strong PH, indicating that environmental regulations generally advocate technological innovation for most sub-sectors but only promote IEE in a few sub-sectors at present. Finally, differentiated policy implications for environmental regulations and technological innovation are provided for decision-makers.
Assuntos
Eficiência , Indústrias , Invenções , China , Desenvolvimento Sustentável , Desenvolvimento EconômicoRESUMO
China has been the world's largest market for industrial robots since 2013. Industrial robots improve accuracy, safety, and efficiency in industrial production but have a substantial impact on the labor market. This investigation uses the task-based model to explore the relationship between industrial robots and employment across industries. This study uses industrial robot data from the International Federation of Robotics and employment data from the China Statistical Yearbook from 2010 to 2019 to examine robot applications' influencing mechanisms on labor demand in different industries in China. The results show a significant positive correlation between robots' exposure and labor demand for IT, health and social services, science research and technical services, and management of water conservancy and environmental industries. Based on the results, the use of robots promotes high-skilled talent employment and some third-sector employment, like education, food and beverages, utilities, household appliances, and transport. However, multiple regression analysis reveals that the use of robots has reduced employment in traditional industries such as agriculture and mining.