This study introduces a new method of downscaling global population distribution. Its novelty is that it allows city size distributions to interact with socioeconomic variables. The contribution to the literature is twofold. One is a challenge to the conventional view that the proportionate growth dynamics underlies empirical rank–size regularities. It is shown that the city size distribution of a region can deviate substantially from a log-normal distribution with cross-regional and time variations, and that such variations can be explained by certain socioeconomic conditions that each region confronts at a particular time point. In addition, this study can pave the way for various research projects which need spatial distribution of global population at fine grid cell levels as key input. The model is applicable to the entire globe, including regions for which reliable sub-regional population datasets are limitedly available, and can be extended easily for predictive analysis.
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