Description:
<jats:title>Abstract</jats:title><jats:p>Understanding the potential mechanisms of population mobility is important in population studies. The current study calculates a place attractivity score and collects 12 socioeconomic and natural condition factors at the prefecture‐level in China. A full spectrum of spatial autoregression and eigenfunction‐based spatial filtering models are employed to investigate the relationship between place attractivity and the factors at the global level, which assumes the relationship stays the same everywhere. A random‐effects eigenfunction‐based spatial filtering spatially varying coefficient model is used to check the relationships at local level, which admits that relationships might be different in different locations. Results suggest that the eigenvector spatial filtering analysis models perform better than other models. China's population mobility is primarily driven by economic push‐pull factors. Accessibility, job opportunity, temperature and terrain also play roles in determining a prefecture's attractivity. Local analysis suggests that the relationships are likely only true in large migration destinations.</jats:p>