A Four-Dimensional Decomposition of Relative Poverty in China from the Perspective of Heterogeneity

Ending poverty in all its forms is the first of the 17 Sustainable Development Goals of the 2030 Agenda for Sustainable Development. Therefore, it is of great significance to study poverty in the context of sustainable development. After eradicating absolute poverty, constructing a long-term mechanism to solve relative poverty is an inevitable requirement for achieving common prosperity in China. Therefore, it is extremely important that relative poverty is accurately identified and quantitatively decomposed. This paper adjusts the Foster–Greer–Thorbecke poverty index to propose a new methodology for relative poverty decomposition comprising growth, dispersion, heterogeneity, and identification effect. Based on China Family Panel Studies data from 2014 to 2018, the empirical analysis reveals the contributions to relative poverty made by growth, dispersion, heterogeneity, and identification effects. Specifically, the growth effect reduces the incidence of relative poverty; dispersion effect worsens relative poverty by affecting the depth of poverty; the heterogeneity effect depends on the heterogeneous characteristics of the population; the identification effect aggregates relative poverty by acting mainly on poverty incidence. We also compare the four relative poverty effects in urban versus rural areas. The findings show that dispersion effect and heterogeneity effect are keys to the differences. In particular, dispersion effect differences arise from income disparities, while heterogeneity effect differences depend on heterogeneous characteristics such as education, health insurance, and migrant work.