Nightlife activity and crime: The impact of COVID-19 related nightlife restrictions on violent crime.

OBJECTIVES: The present study examines how varying levels of restrictions on the nightlife economy have impacted violent crime during the COVID-19 pandemic and the extent to which the crime preventive side-effects of restrictions are associated with the density of alcohol outlets. METHODS: The Data stems from geocoded locations of violent crimes combined with data on the density of on-premises alcohol outlets and the level of COVID-19 restrictions in Copenhagen, Denmark. We use a negative binomial count model with cluster robust standard error to assess the effect of the interaction between alcohol outlet density and COVID-related restriction levels on the nightlife economy on the frequency of violent crime. RESULTS: The article reveals how both the level of restrictions on the nightlife economy and the density of alcohol outlets significantly impacted the frequency of violent crime. The regression analysis shows that the effect of restrictions on the nightlife economy depends on the concentration of on-premises alcohol outlets in the area. In areas with a high concentration of outlets, we observe a much higher reduction in crime as consequence of the COVID-19 related restrictions. CONCLUSIONS: The results shows that a more restricted nightlife economy, including earlier closing times, could have a crime preventive effect, especially in areas with a high density of alcohol outlets.

A quasi-experimental study of ethnic and gender bias in university grading.

This paper contributes to the debate on race- and gender-based discrimination in grading. We apply a quasi-experimental research design exploiting a shift from open grading in 2018 (examinee's name clearly visible on written assignments), to blind grading in 2019 (only student ID number visible). The analysis thus informs name-based stereotyping and discrimination, where student ethnicity and gender are derived from their names on written assignments. The case is a quantitative methods exam at Roskilde University (Denmark). We rely on OLS regression models with interaction terms to analyze whether blind grading has any impact on the relative grading differences between the sexes (female vs. male examinees) and/or between the two core ethnic groups (ethnic minorities vs. ethnic majority examinees). The results show no evidence of gender or ethnic bias based on names in the grading process. The results were validated by several checks for robustness. We argue that the weaker evidence of ethnic discrimination in grading vis-à-vis discrimination in employment and housing suggests the relevance of gauging the stakes involved in potentially discriminatory activities.