Abstract

Income polarization is a critical issue of social development. This study analyzes the role of polycentric cities in alleviating income polarization using monthly household electricity consumption data to identify income polarization based on the application of proxy variable analysis and an artificial neural network. The polycentric structure of cities is identified using unique satellite nighttime light data. It is found that polycentric structure is significant for alleviating income polarization, which exhibits a nonlinear effect. As the polycentric structure index increases, the inhibitory effect of polycentric cities on income polarization will increase. Relevant policy implications are proposed based on the study's findings.

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