Measuring the impact of the COVID-19 lockdown on crime in a medium-sized city in China

Abstract

Abstract: Objectives: The study examines thevariation in the daily incidence of eight acquisitive crimes: automobile theft,electromobile theft, motorcycle theft, bicycle theft, theft from automobiles,pickpocketing, residential burglary, and cyber-fraud before the lockdown andthe duration of the lockdown for a medium-sized city in China. Methods: Regression discontinuity intime (RDiT) models are used to test the effect of the lockdown measures oncrime by examining the daily variation of raw counts and rate. Results: It is indicated that incontrast to numerous violent crime categories such as domestic violence wherefindings have repeatedly found increases during the COVID-19 pandemic,acquisitive crimes in this city were reduced during the lockdown period for allcategories, while “cyber-fraud” was found more resilient in the sense that itsdecrease was not as salient as for most other crime types, possibly due topeople’s use of the internet during the lockdown period. Conclusions: The findings providefurther support to opportunity theories of crime that are contingent upon theneed for a motivated offender to identify a suitable target in physical space.