Abstract
ABSTRACT From the start of the COVID-19 outbreak, government measures impacted citizens’ behavior, particularly regarding social distancing and confinement. Whether or not these measures influenced criminal behavior is an area of particular interest. Findings, mainly concerned with the routine activity theory, have correlated restrictions on movement and circulation with a general decrease in crime. In this analysis, we use the case of Mexico City to estimate the impact of the national health crisis, and the corresponding government measures implemented, as well as their subsequent relaxation, on the daily crime count for six types of crimes (assault, burglary -residential and commercial-, domestic violence, larceny, robbery, and vehicle theft). We use generalized autoregressive conditional heteroscedasticity (GARCH) models to control for the volatility of the time series. While there is a growing body of literature that focuses on the study of criminal behavior during the pandemic, there is a scarcity of work that uses time series to analyze the impact of government measures and their consequences on criminal activity. Our results show a significant reduction in criminal reports for the analyzed crimes during the period of strictest social distancing measures, followed by an increase as these were gradually lifted or lightened.
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