A dataset of income distribution on provincial, urban, and rural levels for China from 2020 to 2100.

ABSTRACT: Projections of future income distributions at subnational levels are becoming increasingly important for a variety of analyses and evaluations. However, relevant datasets are currently limited. This study presents a methodological framework that introduces machine learning algorithms to a top-down approach used for generating income distribution datasets. We project per capita disposable income and income inequality for 31 Chinese provinces from 2020 to 2100, considering different scenarios based on China's local circumstances, and then estimate income distributions based on these. After accounting for necessary consistency between provincial, urban, and rural income datasets, we further generate the same data products at the urban and rural level for each province. We validate our project

SUBMITTER: Lei M 

PROVIDER: S-EPMC11681057 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature