Empirical analysis of spillover effects across key carbon-emitting sectors using quantile regression: perspectives from China

Wei Jiang (), Chunxing Gao (), Julien Chevallier () and Jiangnan Bao ()
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Wei Jiang: Qingdao University
Chunxing Gao: Qingdao University
Julien Chevallier: University Paris VIII Vincennes Saint-Denis
Jiangnan Bao: Macau University of Science and Technology

SN Business & Economics, 2025, vol. 5, issue 10, 1-25

Abstract: Abstract The spillover effects among key carbon emission sectors have emerged as a significant concern in the context of coordinated emission reduction efforts. This study utilizes daily carbon emission data from key industries in China and globally, spanning the years 2019 to 2023, and applies the Quantile Vector Autoregression (QVAR) methodology to develop a carbon emission spillover network for critical industries in China across various different time and frequency domains. Additionally, it investigates the influence of China's key carbon emission sectors on global carbon emissions from an international perspective. The principal findings of the study are as follows: (1) Under extreme conditions, median-based estimates tend to underestimate approximately 60% of the carbon emission spillover effects, primarily due to the insufficient accounting of the reciprocal spillover effects between the construction and ground transportation sectors; (2) In scenarios of extreme carbon emissions, the spillover effects are predominantly short-term; (3) The spillover effects of carbon emissions demonstrate seasonal fluctuations, with alterations in production activities resulting from the onset and resolution of the COVID-19 pandemic significantly affecting both the magnitude and direction of these effects; (4) In extreme conditions, the construction and ground transportation sectors exert influence on various high carbon industries on a global scale. These findings carry substantial policy implications for the coordination of emission reduction initiatives across sectors during crises and for the promotion of global collaborative strategies aimed at low-carbon development.

Keywords: Carbon emission spillover network; Key carbon-emitting sectors in China; Quantile Vector Autoregressive (QVAR) method; Global sectoral carbon emissions (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s43546-025-00916-6

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