2019
DOI: 10.3390/su11205740
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Unveiling Key Drivers of Indirect Carbon Emissions of Chinese Older Households

Abstract: The rapid urbanization and growing population aging have become salient features in China. Understanding their impacts on household emissions is crucial for designing mitigation policies for household carbon emissions. By integrating Chinese older household survey data with an unconditional quantile regression model, this paper examines the heterogeneous impacts of household characteristics on indirect carbon emissions of older Chinese households. There are three main findings: (1) The effects of urbanization … Show more

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Cited by 11 publications
(9 citation statements)
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“…Moreover, ridge regression is introduced to solve the multicollinearity problem in multivariate OLS estimation (Ma et al, 2019). In recent years, some studies applied quantile regression to analyze the differential effects of covariates along with the distribution of carbon emissions (Rong et al, 2018;Seriño, 2017;H. Zhang et al, 2019).…”
Section: J O U R N a L P R E -P R O O Fmentioning
confidence: 99%
See 1 more Smart Citation
“…Moreover, ridge regression is introduced to solve the multicollinearity problem in multivariate OLS estimation (Ma et al, 2019). In recent years, some studies applied quantile regression to analyze the differential effects of covariates along with the distribution of carbon emissions (Rong et al, 2018;Seriño, 2017;H. Zhang et al, 2019).…”
Section: J O U R N a L P R E -P R O O Fmentioning
confidence: 99%
“…Our datasets were comprised of three main components: behavior (Xie and Hu, 2014), including energy and emissions issues (Shi et al, 2020;Hongwu Zhang et al, 2019;Zhang et al, 2020). We obtained information about the consumption expenditures of each household from the CFPS dataset.…”
Section: Datamentioning
confidence: 99%
“…The household carbon footprint is heterogeneous among different age groups. The lifestyles and consumption behaviors of older people are significantly distinct from those of other groups [15]. Previous research has found that the carbon footprint of older people is mainly caused by basic living needs [1].…”
Section: Introductionmentioning
confidence: 99%
“…First, we constructed a population ageing index at the household level from two dimensions: age structure (measured by the proportion of older adults) and life cycle (measured by the age of the head of the household), which facilitated a comprehensive micro-scale exploration of the impact of population ageing on carbon emissions. Second, unlike previous studies that only measured household carbon emissions indirectly, such as Xu and Han (2017), Zhang et al (2019), andLiu et al (2020), this study also considered direct carbon emissions based on household electricity and gas expenditure information. Third, we identified the potential mechanisms through which household population ageing affects carbon emissions by discerning subjective mediating factors including life attitude, future income expectations, and environmental awareness, which revealed new insights into this topic.…”
Section: Introductionmentioning
confidence: 99%