Marginal abatement cost curve of carbon emissions in China: a functional data analysis

Marginal abatement cost curve (MACC) of carbon emissions, characterizing relationship between abatement cost and associated abatement potential, is an important instrument for setting emission reduction tasks and planning emission reduction paths. Since it is complex to formulate exclusive carbon emission reduction policies for each industry, we classify different industries according to MACC and provide corresponding carbon emission reduction policies for each category. Functional data analysis (FDA) is a powerful method for analyzing MACC which can reduce interference of noise in estimation of MACC, and deeply identify characteristics of MACC. We explore firm-level MACCs of 441 industries in China during 2008 and 2015 by utilizing FDA-based principal component analysis, cluster analysis, and linear regression analysis. We found that (i) China’s major industries tend to have a clear trend change around 50% in MACCs. (ii) Four hundred forty-one industries can be clustered into 3 categories or 6 subcategories based on value difference or both value and form differences in MACCs. (iii) Correlation between MACC and carbon intensity varies among industries, and most energy-intensive industries show a significant S-shaped relationship: MACC has a positive effect on reducing carbon intensity in its first half of curve, while a negative effect in its second half of curve.