Unveiling the Dynamic Interplay of Industrial Carbon Emissions: Insights from Quantile Time–Frequency Analysis

Wei Jiang (), Xiaoliang Guo, Xin Li, Xuantao Wang and Dianguang Liu
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Wei Jiang: School of Economics, Qingdao University, Qingdao 266100, China
Xiaoliang Guo: School of Economics, Qingdao University, Qingdao 266100, China
Xin Li: School of Economics, Qingdao University, Qingdao 266100, China
Xuantao Wang: School of Business Administration, Guangdong University of Finance, Guangzhou 510521, China
Dianguang Liu: School of Business, Qingdao University, Qingdao 266100, China

Sustainability, 2025, vol. 17, issue 19, 1-21

Abstract: Reducing carbon emissions in the industrial sector is a critical component of achieving green and sustainable development. We employ quantile vector autoregressive methods to analyze the dynamic interactions of industrial carbon emissions across various countries. Initially, we observe that, under normal conditions, developed countries led by the EU exhibit a significant total spillover effect. Secondly, during extreme quantile conditions, the spillover effects of EU-led developed countries shift from positive to negative, whereas in the UK, the opposite trend is observed. This highlights the importance of considering carbon transfer’s role in emission reduction during extreme quantile scenarios. Thirdly, we find that China’s industrial carbon emissions spillover effects remain relatively stable at all times. Lastly, total spillover effects are highly volatile during extreme market conditions, such as the COVID-19 pandemic. These findings will help clarify each country’s emission reduction responsibilities within the international industrial system and facilitate a more equitable allocation of emission reduction tasks.

Keywords: industrial carbon emissions; carbon transfer; quantile vector autoregression; spillover effects (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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