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THE EFFECTS OF EXTREME CLIMATE EVENTS ON GREEN TECHNOLOGY INNOVATION IN MANUFACTURING ENTERPRISES

The increasing intensity and frequency of extreme climate events have made improving the adaptability to extreme climate events a strategic imperative for manufacturing companies. This paper investigates whether manufacturing enterprises increase green technology innovation affected by different extreme climate events. Based on panel data of Chinese listed manufacturing enterprises, we show that extreme precipitation events can positively promote green technology innovation, yet extreme temperature events do not. Heterogeneity analyses suggest that the effect of extreme precipitation events on green technology innovation is more significant for non-state-owned enterprises, poor performance enterprises, and high R&D intensity enterprises than other enterprises. Furthermore, the facilitating effect of extreme precipitation events on green technology innovation is merely temporary.
- University of Science and Technology of China China (People's Republic of)
- Hefei University of Technology China (People's Republic of)
- University of Science and Technology of China China (People's Republic of)
- Hefei University of Technology China (People's Republic of)
Economics and Econometrics, Economics, Social Sciences, Economic Impact of Environmental Policies and Resources, Geology, Energy Consumption, FOS: Earth and related environmental sciences, Oceanography, Economics, Econometrics and Finance, Natural resource economics, Climate change, Business, Industrial organization
Economics and Econometrics, Economics, Social Sciences, Economic Impact of Environmental Policies and Resources, Geology, Energy Consumption, FOS: Earth and related environmental sciences, Oceanography, Economics, Econometrics and Finance, Natural resource economics, Climate change, Business, Industrial organization
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).0 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average
