The impact of civil registration-based demographic heterogeneity on community thefts

Because of China's unique civil registration system (Hukou), using the proportion of floating population or domestic migrants as an index of racial/ethnic heterogeneity is a common practice to apply social disorganization theory to explain crime in Chinese cities. However, this method does not fully reflect the substantive connotation of racial/ethnic heterogeneity in Chinese cities. In this study, we add the heterogeneity of civil registration, i.e. Hukou, in addition to the proportion of floating population when studying crime in a big Chinese city. Following social disorganization theory, we use negative binomial regression models with theft data in 2017, the Sixth National Population Census data, and Point of interests (POI) to delineate effects of the heterogeneity of civil registration and proportion of floating population on thefts. We have four major findings: 1) the Hukou-based ethnic heterogeneity index can better illustrate the ethnic heterogeneity in the Chinese context and have a significant impact on thefts; 2) communities with more rental housing units tend to experience more thefts; 3) there are more thefts in communities that are under the jurisdiction of neighborhood committee; and 4) the agglomeration of Internet cafes, banks, supermarkets, and restaurants tend to exacerbate the thefts in communities. This study subdivides the community residents' civil registration categories to delineate racial/ethnic heterogeneity, explores its impact on community thefts, and constructs a more optimized indicator that better suits communities in China. This is a meaningful supplement to crime theory and existing methods in non-western societies.