Abstract

Over the years, the household sector has become the main source of carbon emissions. Thus, it is crucial to study the green transformation of household consumption patterns (HCPs) and its driving factors from the perspective of carbon emissions (CEs). This study used the Tapio decoupling method to analyze the green transformation of HCPs, employed the logarithmic mean divisia index (LMDI) method to find the driving factors of green transformation of HCPs, and conducted marginal effect analysis to identify the marginal effects of the major driving factors of green transformation of HCPs, based on the China Family Panel Studies (CFPS) database from 2012 to 2018. It was found through statistical analysis that dominant types of direct HCPs included electricity and fuel, and dominant types of indirect HCPs included necessities, health, transportation, and education. The results of empirical analysis indicated that direct household consumption structure and the per capita residential area promoted the green transformation of HCPs, while direct household per square meter residential consumption and per capita net income inhibited it. Furthermore, other factors had varying positive or negative impacts on the green transformation of HCPs, depending on regions, income levels, and urban–rural areas. The results of marginal effect analysis suggested that the marginal effects of residential area on per capita household carbon emissions (HCEs) present a trend from increasing to decreasing, while the marginal effect of household income on per capita HCEs presents an increasing trend. However, the marginal effect of household size on per capita HCEs presents a decreasing trend only for the low-income group and the western region when household size increased from five to six persons. This paper enriches the research on the green transformation of HCPs, and provides references for the formulation of green transformation policies for HCPs in different regions, income levels, and urban–rural areas.

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