Around the world, policymakers and news reports have warned that domestic violence could increase as a result of the Covid-19 pandemic. The attendant restrictions on individual mobility and commercial activity could leave victims trapped with their abusers. This concern has featured prominently in news coverage of the pandemic going back to the first lockdown in China and in policy responses from international organizations and national and local governments.
These concerns are well-founded: the pandemic, related economic disruption, and public health policies could increase domestic violence incidence among cohabiting couples who are under increased stress and spending more time together. However, the scale of the impact is uncertain, as well as how it depends on specific local policies and contextual factors. It is also possible for some domestic violence cases to be averted by the pandemic, for example, among couples and former couples that live apart and spend less time together, or if new relationships form more slowly.
Real-time empirical evidence on the impact of the pandemic on domestic violence is therefore valuable for assessing the spillover impacts of alternative pandemic policies, such as school closures, business shutdowns, and mobility restrictions, and also for directing domestic violence-specific supplemental resources to areas with greatest need.
Unfortunately, measuring domestic violence suffers from a fundamental challenge that is exacerbated by the pandemic. Domestic violence is a crime that tends to occur in private and frequently goes unreported to police or other authorities. Because real-time domestic violence measures tend to be based on reported cases, they are affected by both incidence and reporting rates. The pandemic likely affected reporting rates as well as incidence, and possibly in opposite directions. This means that changes in reported domestic violence rates could understate the impact of the pandemic, for example, if incidence increased but reporting dropped. If the decline in reporting rates was large enough, reported domestic violence rates could fall even if underlying incidence increased.
The usual data sources that researchers employ to measure domestic violence incidence, including unreported crimes, such as victimization surveys, intimate partner homicide rates, and medical treatment for injuries, are not available in real-time during the pandemic. This makes it particularly challenging to interpret initial findings and to reconcile conflicting patterns across sources. Various news reports and academic studies have found increases in certain measures of domestic violence and locations, while others have found declining domestic violence rates using other measures and locations.
We address this conflict by using real-time daily data from multiple sources within a single large US city: Los Angeles, California. We compare changes in domestic violence outcomes following Covid-19 shutdowns in 2020 to changes over the same time period in 2019 and 2018. The effects vary even within that single city and even across measures from the same source. Domestic violence calls to police and to a domestic violence hotline increased during the initial shutdown, but domestic violence crimes decreased. We also find varying effects between the initial shutdown period and the one following the initial re-opening. The re-opening period showed a continued decrease in domestic violence crimes, as well as decreases in arrests for those crimes and in calls to the police and to the hotline.
The inconsistent effects of the pandemic across domestic violence measures within Los Angeles suggest caution in extrapolating any findings from real-time police data to other measures or other cities. Our results highlight the need for better data collection and greater transparency and distribution of police and non-police data on domestic violence across cities. They also suggest that reports assuming universal effects of the Covid-19 crisis on domestic violence may be quite unreliable.
© Amalia R. Miller, Carmit Segal, and Melissa K. Spencer
Amalia R. Miller is professor of economics at the University of Virginia, USA, and a Research Fellow of the IZA.
Carmit Segal is associate professor of business administration at the University of Zürich, Switzerland.
Melissa K. Spencer is a PhD student in economics at the University of Virginia, USA.
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