Association for Public Policy Analysis & Management

The majority of acts of violence against women, including homicides, are committed by intimate partners or ex-partners. Domestic violence imposes a burden on society by reducing victims’ physical and psychological wellbeing as well as their productivity in the labor market. Despite the heavy costs, the causes of domestic violence are still poorly understood. Previous research has uncovered some of the factors that affect domestic violence, including women’s potential wages relative to men, unilateral divorce laws and emotional cues. However, the relationship between housing security, homelessness and domestic violence has not been well disentangled. Domestic violence can be a cause of homelessness but also a consequence, if for example fear of homelessness reduces a victim’s ability to escape the abusive situation or to report incidents to the police.

In this paper, we estimate the causal impact of local nuisance laws on reporting and actual incidence of domestic violence. Criminal activity nuisance ordinances (CANOs) penalize property owners when certain types of activity occur on or near their property, reported primarily through 911 calls to a residence. A large body of qualitative research links CANOs directly to tenant eviction. This eviction threat may create a strong disincentive for tenants to call for police assistance, even when their own physical safety is at risk.

Our analysis examines the first order effect of CANOs on eviction risk, and the effect of CANOs on intimate partner violence (IPV) reporting and incidence rates. Our data include police reported municipal level crime incidents from the National Incident-Based Reporting System, municipal level evictions data from Matthew Desmond’s Eviction Lab, and CANO legislation for cities and towns in Ohio collected from municipal websites or municipal town hall offices. We also incorporate other data on assault outcomes, including the CDC’s National Electronic Injury Surveillance System-All Injury Program, domestic violence prevalence collected by the National Coalition Against Domestic Violence, and the FBI’s Supplementary Homicide Report.

Our identification strategy is a difference-in-differences model: we exploit the staggered implementation and repeal of laws across cities, and compare the change in aforementioned outcomes before and after CANOs were in effect, compared to these outcomes in non-CANO municipalities. Our dataset includes roughly 300 cities in Ohio over the period 2000-2016. Preliminary results show a statistically significant decrease in IPV reporting within cities with an active CANO.