Six months in: pandemic crime trends in England and Wales (original) (raw)
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Crime in the Era of COVID-19: Evidence from England
SSRN Electronic Journal, 2021
The rapid spread of the COVID-19 pandemic and the prescribed countermeasures of restrictions to mobility and social distancing are disrupting economic activity around the world. This applies to legal economic activity but also to criminal behavior and illegal activity. In this study, we investigate the effects of COVID-19-induced lockdowns on recorded crime in England. The enforcement of lockdowns in the country at both the national and local levels, temporally and spatially, allows unveiling the impact on criminal activities by type of shutdown policy. We use official crime data across the universe of local authorities dating back to May 2013 for all recorded crime categories. We find that (1) National lockdowns decrease all types of criminal behavior, except for antisocial behavior, drug offences and crimes against public order which are recording increases. (2) Relaxing national lockdown restrictions attenuates the initial crime effects of strict lockdowns across all crimes. (3) Local lockdowns affect fewer crime categories, limited to increasing antisocial behavior and weapons possession offences and decreasing bicycle theft and other theft violations, with findings being driven by late-entry areas of such policies. (4) A change in the local lockdown scheme implemented by the government in October 2020 does not have a markedly dissimilar effect on criminal activity compared to the earlier scheme. (5) Back-of-the-envelope calculations suggest that government-mandated lockdowns reduced the economic costs of crime by approximately £4.3 billion for the country as a whole (in 2020 British pounds).
COVID-19 Influence on Crime Trends in Northern England: Distincting Rural from Urban Crime
Master Thesis: COVID-19 influence on Crime Trends in Northern England: Distincting Rural from Urban Crime, 2022
This dissertation analyses the trends of rural and urban crime during the pandemic of COVID-19. Previous studies have found that crime generally has decreased during stay-at-home orders and social distancing. However, rural crime has been an understudied topic in criminology, and crime in the pandemic is mainly studied from an urban perspective. Therefore, this study distinguishes between rural and urban crime trends for theoretical and practical reasons. The analysis uses police recorded data from 11 police forces in Northern England from January 2015 to March 2022. Throughout the study period, all crimes summed have growing trends on both rural and urban levels. Interrupted time series analysis shows that lockdowns have stopped it. Crime has dropped in all areas and most crime types. The first and third lockdowns significantly impacted crime drop, while the second has not made such a prominent effect. However, this may be due to the short time between the second and the third lockdown. Rural crime trends follow urban crime trends in general and during the pandemic. However, there are some discrepancies between rural and urban crime. It is noticed that lockdowns have had less effect on crime drop in rural areas. This may be due to the lower numbers of rural criminal events and the characteristics of rural environments. Considering that previous studies indicate that authorities are less present in rural areas, it is suggestible that rural communities were less affected by the enforcement of stay-at-home orders. Additionally, findings suggest that rural crimes were increasing during the summer months. This is expected, considering previous suggestions of population flow into rural areas during agricultural seasons. In conclusion, some practical implications are highlighted, considering situational crime prevention and rural policing. Theoretically, results support previous research on crime during the pandemic, finding that changes in routine activities and restricted mobility produced fewer opportunities for crime. Furthermore, increases in some types of crime, such as drugs, public order, criminal damage and arson, are discussed in terms of General Strain Theory and negative stimuli during restrictions that increased these offences.
2021
The objective of this paper is to assess the relationship between The Spring 2020 COVID-19 Lockdown and the levels of crime in New York City (NYC) and London. Our proposition, derived from the Routine Activity Theory (RAT), the ‘breaches’ theory and input from the 2020 research on lockdown and crime, hypothesised that lockdown measures would lead to reductions in crime. The crime categories selected for this study were: homicide, rape, robbery, violence against a person, burglary, theft and vehicle theft. T-test, F-test and the Ordinary Least Squares (OLS) regression calculations were used to test the hypotheses. The four-month lockdown period in 2020 produced a 15% and 31% crime reduction in NYC and London, respectively. In the case of London, the overall results indicate that changes in routine human activities were indeed largely correlated with the reduction in crime. However, crime patterns in NYC in spring 2020 turned out to be inconsistent. A comparison of crime patterns unde...
Changes in Crime Rates During the COVID-19 Pandemic
2021
Research Summary: We estimate changes in the rates of five FBI Part 1 crimes—homicide, auto theft, burglary, robbery, and larceny—during the COVID-19 pandemic from March through December 2020. Using publicly available weekly crime count data from 29 of the 70 largest cities in the U.S. from January 2018 through December 2020, three different linear regression model specifications are used to detect changes. One detects whether crime trends in four 2020 preand post-pandemic periods differ from those in 2018 and 2019. A second looks in more detail at the spring 2020 lockdowns to detect whether crime trends changed over successive biweekly periods into the lockdown. The third uses a city-level openness index that we created for the purpose of examining whether the degree of openness was associated with changing crime rates. For homicide and auto theft, we find significant increases during all or most of the pandemic. By contrast, we find significant declines in robbery and larceny duri...
Crime and coronavirus: social distancing, lockdown, and the mobility elasticity of crime
Crime Science
Governments around the world restricted movement of people, using social distancing and lockdowns, to help stem the global coronavirus (COVID-19) pandemic. We examine crime effects for one UK police force area in comparison to 5-year averages. There is variation in the onset of change by crime type, some declining from the WHO 'global pandemic' announcement of 11 March, others later. By 1 week after the 23 March lockdown, all recorded crime had declined 41%, with variation: shoplifting (− 62%), theft (− 52%), domestic abuse (− 45%), theft from vehicle (− 43%), assault (− 36%), burglary dwelling (− 25%) and burglary non-dwelling (− 25%). We use Google Covid-19 Community Mobility Reports to calculate the mobility elasticity of crime for four crime types, finding shoplifting and other theft inelastic but responsive to reduced retail sector mobility (MEC = 0.84, 0.71 respectively), burglary dwelling elastic to increases in residential area mobility (− 1), with assault inelastic but responsive to reduced workplace mobility (0.56). We theorise that crime rate changes were primarily caused by those in mobility, suggesting a mobility theory of crime change in the pandemic. We identify implications for crime theory, policy and future research.
Crime and mobility during the COVID-19 lockdown: a preliminary empirical exploration
New Zealand Economic Papers
In this research note, we document the decrease in victimisation rates during the COVID-19 lockdown period in New Zealand. We show that the changes in mobility patterns in the same period are significantly correlated with these changes in crime rates. We discuss how our preliminary empirical results accord with the theories of crime in economics and criminology.
Crime Rates in a Pandemic: the Largest Criminological Experiment in History
American Journal of Criminal Justice, 2020
The COVID-19 pandemic of 2020 has impacted the world in ways not seen in generations. Initial evidence suggests one of the effects is crime rates, which appear to have fallen drastically in many communities around the world. We argue that the principal reason for the change is the government ordered stay-at-home orders, which impacted the routine activities of entire populations. Because these orders impacted countries, states, and communities at different times and in different ways, a naturally occurring, quasi-randomized control experiment has unfolded, allowing the testing of criminological theories as never before. Using new and traditional data sources made available as a result of the pandemic criminologists are equipped to study crime in society as never before. We encourage researchers to study specific types of crime, in a temporal fashion (following the stay-at-home orders), and placed-based. The results will reveal not only why, where, when, and to what extent crime chan...
2021
Much research has shown that the first lockdowns imposed in response to the COVID-19 pandemic were associated with changes in routine activities and, therefore, changes in crime. While several types of violent and property crime decreased immediately after the first lockdown, online crime rates increased. Nevertheless, little research has explored the relationship between multiple lockdowns and crime in the mid-term. Furthermore, few studies have analysed potentially contrasting trends in offline and online crimes using the same dataset. To fill these gaps in research, the present article employs interrupted time-series analysis to examine the effects on offline and online crime of the three lockdown orders implemented in Northern Ireland. We analyse crime data recorded by the police between April 2015 and May 2021. Results show that many types of traditional offline crime decreased after the lockdowns but that they subsequently bounced back to pre-pandemic levels. In contrast, results appear to indicate that cyber-enabled fraud and cyber-dependent crime rose alongside lockdown-induced changes in online habits and remained higher than before COVID-19. It is likely that the pandemic accelerated the long-term upward trend in online crime. We also find that lockdowns with stay-at-home orders had a clearer impact on crime than those without. Our results contribute to understanding how responses to pandemics can influence crime trends in the mid-term as well as helping identify the potential long-term effects of the pandemic on crime, which can strengthen the evidence base for policy and practice.
A global analysis of the impact of COVID-19 stay-at-home restrictions on crime
Nature Human Behaviour
The stay-at-home restrictions to control the spread of COVID-19 led to unparalleled sudden change in daily life, but it is unclear how they affected urban crime globally. We collected data on daily counts of crime in 27 cities across 23 countries in the Americas, Europe, the Middle East and Asia. We conducted interrupted time series analyses to assess the impact of stay-at-home restrictions on different types of crime in each city. Our findings show that the stay-at-home policies were associated with a considerable drop in urban crime, but with substantial variation across cities and types of crime. Meta-regression results showed that more stringent restrictions over movement in public space were predictive of larger declines in crime.
Humanities and Social Sciences Communications
This paper seeks to evaluate the impact of the removal of restrictions (partial and complete) imposed during COVID-19-induced lockdowns on property offences such as robbery, burglary, and theft during the milder wave one and the more severe wave two of the pandemic in 2020 and 2021, respectively. Using 10-year data of the daily counts of crimes, the authors adopt an auto-regressive neural networks method to make counterfactual predictions of crimes, representing a scenario without the pandemic-induced lockdowns. The difference between the actual and forecast is the causal impact of the lockdown in all phases. Further, the research uses Google Mobility Community Reports to measure mobility. The analysis has been done at two levels: first, for the state of Tamil Nadu, which has a sizeable rural landscape, and second for Chennai, the largest metropolitan city with an urban populace. During the pandemic-induced lockdown in wave one, there was a steep decline in the incidence of property...