Carbon Footprint Inequality and Its Driving Forces: Evidence from Chinese Household Survey Data

Posted: 24 Jun 2019

See all articles by Yuning Gao

Yuning Gao

Tsinghua University; Tsinghua University - School of Public Policy and Management


Tsinghua University - Tsinghua University, School of Public Policy and Management

Bo Meng

Institute of Developing Economies (IDE-JETRO)

Date Written: June 21, 2019


This paper draws on household survey data to assess carbon footprint inequality and analyze its driving forces. Most existing literature assesses carbon footprint inequality on a more macro level using aggregated residential expenditure data of each income group, ignoring individual difference that may result in social inequality and decrease of social welfare. In order to overcome this problem, this paper integrates an Environmentally Extended Input–Output model and a Consumer Lifestyle Approach to assess individual carbon footprint. The analysis adopts both micro level household survey data and the estimation of macro level consumption-based carbon intensity.

The micro level household survey data used in this paper include: 1) Chinese Urban Household Survey (UHS), covering urban household data from 2002 to 2009 with 127,234 samples in total; 2) Chinese Household Income Project Survey (CHIP), covering rural, urban as well as migrating population in year 2002, 2007 and 2013; 3) and China Household Finance Survey (CHFS), covering both rural and urban data in years 2011 and 2013.The driving forces of carbon footprint inequality are studied using regression models at both household and per capita levels with detailed consideration of: 1) demographic characteristics like gender, age, family size, elder people rate, and children rate; 2) financial characteristics like disposable income, housing ownership, and vehicle ownership; 3) controlled factors like year, province and urban identity, as well as other variables of interest.

The main findings of this study reveal that: 1) carbon inequality widely exists at both household level and individual level, and the main contributing factors are urban-rural differences, income disparities, education inequalities as well as living condition differences. An inverted U-shaped curve exists between household carbon footprint and the age of the household head, and household carbon emission peaks when the household head is between his (her) 40s and 50s. Family living conditions significantly affect the family’s carbon footprint, carbon footprint of residents living in bungalows or smaller houses are significantly lower than that of others. Households that prefer service-oriented and one-time expenditure emit more carbon emissions. 2) The urban-rural duality has great impact on the carbon footprint inequality. The carbon footprint of rural residents is generally 20%-50% lower than that of urban residents. The aggravating of population ageing and urban-rural dichotomy may further exacerbate carbon footprint inequality among residents. 3) Inequality of carbon footprint is higher than that of income and expenditure, and serious for rural residents comparing to that for urban residents and migrants. 4) While carbon footprint inequality has slightly declined on overall level and within-group level respectively for urban, rural and migrating residents; between-group inequality has been increasing, which may become an important source of future carbon footprint inequality.

As for policy implication, this analysis indicates that: 1) reducing the income gap between urban and rural residents improves carbon footprint equity; 2) encouraging energy-saving lifestyle contributes to carbon emission reduction through the decrease of service-oriented and one-time expenditure.

Keywords: carbon footprint, carbon inequality, household inequality

JEL Classification: D10, D12, D31, D63

Suggested Citation

Gao, Yuning and LI, MENG and Meng, Bo, Carbon Footprint Inequality and Its Driving Forces: Evidence from Chinese Household Survey Data (June 21, 2019). Abstract Proceedings of 2019 International Conference on Resource Sustainability - Cities (icRS Cities), Available at SSRN:

Yuning Gao

Tsinghua University ( email )

Beijing, 100084

Tsinghua University - School of Public Policy and Management ( email )

Beijing, 100084
+86-10-62772927 (Phone)


MENG LI (Contact Author)

Tsinghua University - Tsinghua University, School of Public Policy and Management ( email )

Beijing, 100084

Bo Meng

Institute of Developing Economies (IDE-JETRO) ( email )

3-2-2 Wakaba, Mihama-ku
Chiba, 261-8545

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