Examining energy poverty in Chinese households: An Engel curve approach

This article is first to model energy poverty in Chinese households using an Engel curve approach. To analyse the determinants of energy poverty and energy expenditures across households, we avail the 2015 wave of the Chinese General Social Survey (CGSS). Possible presence of endogeneity is accounted for in the model specification as well as by using the Lewbel heteroscedasticity identified endogenous variables estimator. In addition, we are the first to scrutinise disparity and discrimination by conducting the Blinder–Oaxaca decomposition of energy poverty model by gender, ethnicity, region (Eastern vs. non-Eastern provinces), and urbanisation status (rural vs. urban residents). Our analysis shows: (i) education is the key determinant of various energy poverty measures and energy expenditure shares across Chinese households; (ii) other determinants including fossil fuel mix and electricity price discrimination are found to worsen energy poverty, on average. However, fossil fuel mix is found to increase expenditure share of total energy, electricity, and coal and decrease that of biomass; and (iii) the Blinder–Oaxaca decomposition analyses show no statistically significant gender or ethnic discrimination in energy poverty rates. However, there is substantial divide between Eastern and non-Eastern provinces and between rural and urban households—with these groups also discriminated against when accessing clean cooking fuels and technologies. The Blinder–Oaxaca results also generally support the logistic and the Lewbel energy poverty model findings.