Energy technology patents–CO2 emissions nexus: An empirical analysis from China

By Zhaohua Wang, Zhongmin Yang, Yixiang Zhang, Jianhua Yin. 2012

236 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Renewable Energy, Sustainability and the Environment

View Paper: https://www.semanticscholar.org/paper/853a9927659f8856b16bd2fba0677910cbe394cc

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

1. Ye Li
2. Qiang Cui
3. Wenping Wang
4. Antonios Garas
5. Wen-wen Li
6. Hong-jun Yin
7. Chen Li
8. Meng Zeng

In Renewable Energy, Sustainability and the Environment

1. Qiang Cui
2. Ye Li
3. Wenping Wang
4. Antonios Garas
5. Wen-wen Li
6. Yu Wang
7. Baolong Yuan
8. A. Kyriakou

Citations in the corpus

• A Survey of the Literature on Environmental Innovation Based on Main Path Analysis (2016, unknown): “Wang et al. (2012) analyze the impact of both fossil fuel and carbon-free technological advancements on CO2 emissions across 30 Chinese provinces between 1997 and 2008.”
• Economic Complexity and Environmental Performance: Evidence from a World Sample (2019, background): “There are works such as [135] showing that green patents significantly contribute to the environmental cleanup; however, our hypothesis here is that patents (and articles) impact environmental performance only indirectly, through the enhanced sophistication of products and means of production.”
• Green innovation and China’s CO2 emissions – the moderating effect of institutional quality (2021, background): “Drawing on Hashmi and Alam (2019), Wang et al. (2012), Du, Li, and Yan (2019), Sun et al. (2019), and other research, we use the number of authorized green patents to measure green innovation.”
• Evaluating energy efficiency for airlines: An application of VFB-DEA (2015, methodology): “The energy efficiencies of different countries, regions and industries have been evaluated (Herring, 2006; Zhou et al., 2008; Worrell et al., 2009; Kaufman and Palmer, 2012; Wang et al., 2012; Hasanbeigi et al., 2013; Cui et al., 2014; Cui and Li, 2015), and the main research method is Data Envelopm”
• Industrial structure, technological progress and CO2 emissions in China: Analysis based on the STIRPAT framework (2017, methodology): “The first method is to select proxy variables based on the perspective of research and development, for example, the number of patents, scientific personnel and R&D expenditures (Yang et al. 2014; Wang et al. 2011; Ang 2009; Liu et al. 2015c).”