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Does innovation facilitate meeting the CO2 emission reduction targets of China: A non-linear approach

China has been implementing energy efficiency and CO2 emission reduction schemes at the provincial level that have been embedded in the National Five Year Plans of the country. We set out to investigate the relationship between R&D expenditures and CO2 emissions in China at the province level in the context of the planned emissions reduction targets. We explore the possibility of the existence of a non-linear relationship between R&D expenditures and CO2 emissions with a non-parametric methodology, a fixed effect panel data quantile (FEQR) regression estimator applied to a panel of 30 provinces. We stratify the sample according to the five emissions reduction target tiers of the 12th Five-Year National Plan of China and we investigate the role of R&D expenditures in emissions reduction within each of the tiers. We find an inverse U relationship with different turning points for the three middle tiers and a U-shaped relationship for the tier under the most stringent environmental regulation. We find no effect in the tier with the least stringent emissions reduction targets. A further investigation shows that the above results are attributed to sectors with relatively low energy intensity and not to the sectors of heavy industry. The results allow us to draw broad conclusions about the effectiveness of investment in new technologies as a means of meeting the CO2 targets in China.
- Hebei University of Technology China (People's Republic of)
- Teesside University United Kingdom
- Teesside University United Kingdom
- University of Economics Ho Chi Minh City Viet Nam
- Hebei University of Technology China (People's Republic of)
Q5, Q4, Regional economics. Space in economics, HT388, C31, C21, B23, C33
Q5, Q4, Regional economics. Space in economics, HT388, C31, C21, B23, C33
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).4 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
