Household Carbon Footprint Characteristics and Driving Factors: A Global Comparison Based on a Dynamic Input–Output Model

Xi Chen, Yingying Zhen () and Zhanming Chen ()
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Xi Chen: School of Applied Economics, Renmin University of China, Beijing 100872, China
Yingying Zhen: School of Applied Economics, Renmin University of China, Beijing 100872, China
Zhanming Chen: School of Applied Economics, Renmin University of China, Beijing 100872, China
Authors registered in the RePEc Author Service: 陈占 明 ()

Energies, 2023, vol. 16, issue 9, 1-18

Abstract: Carbon emissions are rapidly increasing with continuing global economic development, necessitating an urgent energy revolution. Often, when calculating carbon footprint, analysts have failed to account for changes in capital stock and the impact of indirect emissions caused by the consumption of imported products. Furthermore, the homogenization of industrial and resident sectors has reduced our understanding of the specific driving forces behind carbon emissions. To avoid such locational and temporal biases, this study employs a dynamic input–output model to re-estimate the carbon footprint of only residents. We deconstruct residential emissions into different consumption categories and conduct a comparative analysis between developed and developing countries from across the world. To this end, data from 44 global economies were obtained from the World Input–Output Database for the period from 2000 to 2014. For developing countries, food consumption had the highest share of embodied carbon emissions, maintaining a share of over 20%, whereas in developed countries, housing consumption had the highest share, remaining at over 30%. In most countries, the consumption level and emission intensity effects were the most important drivers of carbon emission increases and carbon emission decreases, respectively. However, the contributions of the two varied considerably in different countries, with the maximum impact of the emission intensity effect on the carbon footprint of a single category reaching 854.31% in the US and 99.34% in China. These findings will help countries tailor their emission reduction policies to local conditions and emphasize that emission reductions should start by reducing the emission intensity and consumption structure of the corresponding sectors.

Keywords: household consumption expenditure; household carbon footprint; input–output model; LMDI method (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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