Using random forest to find the discontinuity points for carbon efficiency during COVID-19

Author:

Qu Yingchi1,Lim Ming K.2,Yang Mei1,Ni Du3ORCID,Xiao Zhi1

Affiliation:

1. Chongqing University

2. University of Glasgow

3. NUPT: Nanjing University of Posts and Telecommunications

Abstract

Abstract As there is a constant trade-off between carbon dioxide emissions against economic growth for every government, carbon efficiency is a key indicator to guide sustainable development. However, the energy crisis and COVID-19 recovery could affect carbon efficiency. Therefore, this paper combines the fuzzy regression discontinuity and random forest algorithm to estimate the discontinuity of the energy crisis and COVID-19 recovery on carbon efficiency. The results show that there are two cutoffs between carbon efficiency and coal prices. The positive treatment effect at cutoff 1 proves that the “zero-tolerance” policies effectively promote carbon efficiency. Besides, the negative treatment effect at cutoff 2 proves that electricity rationing has not always improved carbon efficiency during the energy crisis.

Publisher

Research Square Platform LLC

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