Unraveling the nexus: China's economic policy uncertainty and carbon emission efficiency through advanced multivariate quantile-on-quantile regression analysis

B-Tier
Journal: Energy Policy
Year: 2024
Volume: 188
Issue: C

Authors (5)

Yu, Yang (not in RePEc) Jian, Xin (not in RePEc) Wang, Hongxiang (not in RePEc) Jahanger, Atif (Hainan University) Balsalobre-Lorente, Daniel (not in RePEc)

Score contribution per author:

0.402 = (α=2.01 / 5 authors) × 1.0x B-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

Abstract

The pursuit of green economic development, coupled with the endeavor towards achieving dual carbon objectives, has opened new pathways for sustainable progress in China. Nevertheless, the realization of the Sustainable Development Goals is closely intertwined with economic policy fluctuations. In this context, our study investigates the influence of economic policy uncertainty on the efficiency of carbon emissions in China over the period from 2005 to 2021. We employ the Multivariate Quantile-on-Quantile (m-QQR) Regression approach to dissect the tail dependence of model parameters amidst this uncertainty. The findings highlight how China's carbon emission efficiency is influenced by exogenous factors, including GDP per capita, energy consumption intensity, green building integration, and international trade openness. Furthermore, the analysis reveals nuanced dependencies across various quantiles. By elucidating these dynamics, this research provides valuable insights aimed at guiding China toward its dual-carbon goals and promoting the growth of a sustainable green economy.

Technical Details

RePEc Handle
repec:eee:enepol:v:188:y:2024:i:c:s0301421524000776
Journal Field
Energy
Author Count
5
Added to Database
2026-01-25