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Measurement of carbon finance level and exploration of its influencing factors

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  • Peng Zhang
  • Yuwei Zhang
  • Nuo Xu

Abstract

Faced with increasingly severe environmental problems, carbon trading markets and related financial activities aiming at limiting carbon dioxide emissions are booming. Considering the complexity and urgency of carbon market, it is necessary to construct an effective evaluation index system. This paper selected carbon finance index as a composite indicator. Taking Beijing, Shanghai, and Guangdong as examples, we adopted the classic method of multiple criteria decision analysis (MCDA) to analyze the composite indicator. Potential impact factors were screened extensively and calculated through normalization, weighting by coefficient of variation and different aggregation methods. Under the measurement of Shannon-Spearman Measure, the method with the least loss of information was used to obtain the carbon finance index (CFI) of the pilot areas. Through panel model analysis, we found that company size, the number of patents per 10,000 people and the proportion of new energy generation were the factors with significant influence. Based on the research, corresponding suggestions were put forward for different market entities. Hopefully, this research will contribute to the steady development of the national carbon market.

Suggested Citation

  • Peng Zhang & Yuwei Zhang & Nuo Xu, 2022. "Measurement of carbon finance level and exploration of its influencing factors," Papers 2206.00189, arXiv.org.
  • Handle: RePEc:arx:papers:2206.00189
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    1. Zhou, P. & Ang, B.W. & Poh, K.L., 2006. "Comparing aggregating methods for constructing the composite environmental index: An objective measure," Ecological Economics, Elsevier, vol. 59(3), pages 305-311, September.
    2. Diaz-Balteiro, Luis & Romero, Carlos, 2004. "In search of a natural systems sustainability index," Ecological Economics, Elsevier, vol. 49(3), pages 401-405, July.
    3. P. Zhou & B. Ang, 2009. "Comparing MCDA Aggregation Methods in Constructing Composite Indicators Using the Shannon-Spearman Measure," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 94(1), pages 83-96, October.
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