An addition of 10 cases per officer per month is related to a three percentage point increase in the likelihood of victim withdrawal.
Domestic abuse cases are widespread in countries across the world. In the United States, nearly 20 people per minute are physically abused by an intimate partner. Across the European Union, at least two women are killed daily by an intimate partner or family member. Meanwhile, in the UK, partners or family members are responsible for nearly half of all female homicides.
Given the profound impact of domestic violence on individuals and society at large, and the potential risk of escalation of harm, domestic abuse cases in which a high risk of future harm has been identified are a high priority for law enforcement agencies.
Despite that, across England and Wales, we see a steeply increasing number of domestic abuse cases that are closed because victims withdraw their complain.
In our recent CEP discussion paper, we explore the connection between the workload of police officers and the likelihood of victims withdrawing from high-risk domestic abuse cases, using the data from Greater Manchester Police spanning January 2014 to March 2019.
Our findings reveal that an addition of 10 cases per officer per month is related to a three percentage point increase in the likelihood of victim withdrawal.
A staggering increase
This study focuses specifically on domestic abuse incidents involving female victims deemed at high risk of future harm. Given the critical nature of these cases, they are presumably less susceptible to variations in recording and officer attendance over time and across different locations. Our analysis employs the number of cases assigned to an officer in a given month as a proxy for their workload.
During the observation period, the proportion of cases resulting in victim withdrawal surged from 5% to 38%, a staggering increase of 33 percentage points. Our result suggests that the increased workload accounts for 9% of the total rise in withdrawals – a significant portion.
By exploiting individual officer’s variation in workload over time, we show that adding 10 more cases to an officer’s monthly workload is related, on average, with an increase of three percentage points in the probability of a victim withdrawing from a high-risk domestic abuse case.
During the observation period, the proportion of cases resulting in victim withdrawal surged from 5% to 38%, a staggering increase of 33 percentage points. Our result suggests that the increased workload accounts for 9% of the total rise in withdrawals – a significant portion.
These conclusions hold after controlling for the characteristics of the crime, the victim, the potential perpetrator, and the details of the police response such as the response time and length of investigation.
We also identify characteristics that are associated with a higher probability of victim withdrawal. Notably, victims of sexual offences are 20 percentage points more likely to retract their complaints than those involved in other types of violent incidents.
Furthermore, victim intoxication at the time of the incident increases the likelihood of withdrawal, whereas alleged perpetrator intoxication reduces this likelihood.
The relationship between the victim and the alleged perpetrator also plays a significant role, with victims more inclined to withdraw complaints against family members and less so against former partners. Additionally, our data reveal a seasonal pattern, with withdrawals more common in the latter part of the year, particularly from September to December.
Compounded by austerity
The backdrop to these findings is a period of significant institutional change within the sector, characterised by a 29% rise in recorded crimes across Greater Manchester from 2014 to 2019, alongside a 9% reduction in available police officers.
Our suggested interpretations of these findings, informed by the institutional knowledge, is that subjecting officers to time pressure leads to policing practices that affect how victims react and engage with the process.
This imbalance has led to an increased average workload per officer and reduced opportunities for meaningful victim engagement. These challenges are compounded by austerity policies implemented across England and Wales, leading to significant cuts in public spending, including the resources allocated to policing, courts and prisons.
While the data and setup do not allow us to conclusively argue for a causal relation, we nevertheless believe that this is likely to be the case as we do not observe any other fundamental change in policy that would negatively affect the handling of domestic abuse cases across Greater Manchester.
Our main result comes from comparing victim withdrawal rates for the same officer in months when they have more cases and months when they have fewer cases. Any policy change that could affect this result would need to impact both workload and withdrawal rates at the individual level.
Our suggested interpretations of these findings, informed by the institutional knowledge, is that subjecting officers to time pressure leads to policing practices that affect how victims react and engage with the process.
It is likely that the effect of workload on withdrawals for lower-priority crimes is even higher than our estimate for high-risk domestic abuse case withdrawal.
The heightened focus on domestic abuse and other priority offences puts pressure on police forces and officers to conduct thorough investigations, a pressure not necessarily shared across all types of offences. As such, the secondary costs of austerity policies, in terms of reduced victim engagement, may be more pronounced than initially indicated by our findings.
This article first appeared on the LSE British Politics and Policy blog, and is republished under a Creative Commons Licence; you can read the original here.
About the Authors
Professor Tom Kirchmaier is Director of the Policing and Crime research group at the LSE’s Centre for Economic Performance (CEP), focusing on understanding the full spectrum of questions relating to policing and crime, with a special focus currently on police organizational efficiency, demand prediction, anti-money laundering and organised crime, and domestic abuse, as well as serious violence (knife crime, gangs, and drug markets). He works with very large datasets from the police and other sources. Prior to the CEP, Tom was with the Financial Markets Group, and the Manchester Business School; he holds a PhD in Management from the LSE.
Dr Ekaterina Oparina is a post-doctoral Research Economist in the Community Wellbeing Programme of the Centre for Economic Performance at the LSE. She completed her PhD in Economics at the University of Surrey in autumn 2020, and is a Fellow of the Higher Education Academy. Dr Oparina’s current areas of research include methodological approaches to the analysis of wellbeing data, and individual-level determinants of wellbeing.
Picture © panitanphoto / Shutterstock
