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The mechanisms driving the nucleation, spread, and dissipation of crime hotspots are poorly understood. As a consequence, the ability of law enforcement agencies to use mapped crime patterns to design crime prevention strategies is severely hampered. We also lack robust expectations about how different policing interventions should impact crime. Here we present a mathematical framework based on reaction-diffusion partial differential equations for studying the dynamics of crime hotspots. The system of equations is based on empirical evidence for how offenders move and mix with potential victims or targets. Analysis shows that crime hotspots form when the enhanced risk of repeat crimes diffuses locally, but not so far as to bind distant crime together. Crime hotspots may form as either supercritical or subcritical bifurcations, the latter the result of large spikes in crime that override linearly stable, uniform crime distributions. Our mathematical methods show that subcritical crime hotspots may be permanently eradicated with police suppression, whereas supercritical hotspots are displaced following a characteristic spatial pattern. Our results thus provide a mechanistic explanation for recent failures to observe crime displacement in experimental field tests of hotspot policing.

Since its original publication, routine activity theory has proven most instructive for understanding temporal patterns in crime. The most prominent of the temporal crime patterns investigated is seasonality: crime (most often assault) increases during the summer months and decreases once routine activities are less often outside. Despite the rather widespread literature on the seasonality of crime, there is very little research investigating temporal patterns of crime at shorter time intervals such as within the week or even within the day. This paper contributes to this literature through a spatial-temporal analysis of crime patterns for different days of the week. It is found that temporal patterns are present for different days of the week (more crime on weekends, as would be expected) and there is a spatial component to that temporal change. Specifically, aside from robbery and sexual assault at the micro-spatial unit of analysis (street segments) the spatial patterns of crime changed. With regard to the spatial pattern changes, we found that assaults and theft from vehicle had their spatial patterns change in predictable ways on Saturdays: assaults increased in the bar district and theft from vehicles increased in the downtown and recreational car park areas.

Rooted in the near repeat phenomenon and police crime analysis, a crime “flare up” or micro-time hot spot is the emergence of several closely-related crimes within a few minutes’ travel distance from one another. It occurs within 1–2 weeks and can last several weeks or months before running its course and cooling down. A micro-time hot spot is a type of crime pattern identified by police crime analysts to guide short-term police response, particularly directed patrol. Published work by these authors has examined a subset of the 5 years of data to test the effectiveness of the Port St. Lucie, FL Police Department’s response to micro-time hot spots. Those quasi-experimental studies found separately for burglary and theft from vehicle occurring in residential areas that micro-time hot spots receiving police response had nearly 20 % fewer subsequent crimes than those receiving no police response. This study examines all 121 residential burglary and 163 residential theft from vehicle micro-time hot spots receiving police response to understand how two factors of police response dosage (i.e., the amount of directed patrol and how quickly directed patrol is deployed) are related to the amount of subsequent crime. Separate negative binominal analyses for each crime type showed that more directed patrols per day were related to lower levels of subsequent crime for both crime types, and a quicker response was related to lower crime for residential theft from vehicle. That is, the more and quicker the response, the quicker resolution and cooling off of the micro-time hot spot. The findings were stronger for residential burglary, and a visual examination of first standard deviation confident intervals of directed patrol rate by crime suggests that between four and six directed patrols per day in residential burglary micro-time hot spots was optimal. Although the data are from one police agency, these promising results support future research and provide guidance to police for implementing directed patrol in short-term hot spots of property crime.

In this paper we study the causal impact of police on crime, looking at what happened to crime and police before and after the terror attacks that hit central London in July 2005. The attacks resulted in a large redeployment of police officers to central London as compared to outer London. During this time, crime fell significantly in central relative to outer London. The instrumental variable approach we use uncovers an elasticity of crime with respect to police of approximately -0.3 to -0.4, so that a 10 percent increase in police activity reduces crime by around 3 to 4 percent. JEL: K42

Highly clustered event sequences are observed in certain types of crime data, such as burglary and gang violence, due to crime-specific patterns of criminal behavior. Similar clustering patterns are observed by seismologists, as earthquakes are well known to increase the risk of subsequent earthquakes, or aftershocks, near the location of an initial event. Space-time clustering is modeled in seismology by selfexciting point processes and the focus of this article is to show that these methods are well suited for criminological applications. We first review self-exciting point processes in the context of seismology. Next, using residential burglary data provided by the Los Angeles Police Department, we illustrate the implementation of self-exciting point process models in the context of urban crime. For this purpose we use a fully nonparametric estimation methodology to gain insight into the form of the space-time triggering function and temporal trends in the background rate of burglary.

The “crime drop” is the most important criminological phenomenon of modern times. In North America, Europe, and Australasia, many common crimes have fallen by half or more since the early 1990s, albeit with variation in the specifics. Seventeen explanations are examined here including demographics, policing, imprisonment, drug markets, and lead poisoning. Pioneering research relevant only to the United States now appears, with the benefit of hindsight, somewhat parochial. Sixteen of the 17 hypotheses fail one or more of four evidence-based standardized tests on which they are assessed. The one that passes is the security hypothesis, underpinned by crime opportunity theories. Here there is strong evidence that vehicle theft fell because of more and better security, and mounting evidence that improved security was critical in reducing burglary and other acquisitive crime. Many crime types are interrelated, while most criminal careers are dominated by property crime, so removing these volume crimes might be expected to reduce violence.

Objectives This study investigated the extent to which immigrant concentration is associated with reductions in neighborhood crime rates in the City of Los Angeles. Methods A potential outcomes model using two-stage least squares regression was estimated, where immigrant concentration levels in 1990 were used as an instrumental variable to predict immigrant concentration levels in 2000. The instrumental variables design was used to reduce selection bias in estimating the effect of immigrant concentration on changes in official crime rates between 2000 and 2005 for census tracts in the City of Los Angeles, holding constant other demographic variables and area-level fixed effects. Non-parametric smoothers were also employed in a two-stage least squares regression model to control for the potential influence of heterogeneity in immigrant concentration on changes in crime rates. Results The results indicate that greater predicted concentrations of immigrants in neighborhoods are linked to significant reductions in crime. The results are robust to a number of different model specifications. Conclusions The findings challenge traditional ecological perspectives that link immigrant settlement to higher rates of crime. Immigration settlement patterns appear to be associated with reducing the social burden of crime. Study conclusions are limited by the potential for omitted variables that may bias the observed relationship between immigrant concentration and neighborhood crime rates, and the use of only official crime data which may under report crimes committed against immigrants. Understanding whether immigrant concentration is an important dynamic of changing neighborhood patterns of crime outside Los Angeles will require replication with data from other U. S. cities.

Geography and social links shape economic interactions. In industries, schools, and markets, the entire network determines outcomes. This paper analyzes a large class of games and obtains a striking result. Equilibria depend on a single network measure: the lowest eigenvalue. This paper is the first to uncover the importance of the lowest eigenvalue to economic and social outcomes. It captures how much the network amplifies agents' actions. The paper combines new tools—potential games, optimization, and spectral graph theory—to solve for all Nash and stable equilibria and applies the results to R&D, crime, and the econometrics of peer effects.

Over the last 40 years, the question of how crime varies across places has gotten greater attention. At the same time, as data and computing power have increased, the definition of a 'place' has shifted farther down the geographic cone of resolution. This has led many researchers to consider places as small as single addresses, group of addresses, face blocks or street blocks. Both cross-sectional and longitudinal studies of the spatial distribution of crime have consistently found crime is strongly concentrated at a small group of 'micro' places. Recent longitudinal studies have also revealed crime concentration across micro places is relatively stable over time. A major question that has not been answered in prior research is the degree of block to block variability at this local 'micro' level for all crime. To answer this question, we examine both temporal and spatial variation in crime across street blocks in the city of Seattle Washington. This is accomplished by applying trajectory analysis to establish groups of places that follow similar crime trajectories over 16 years. Then, using quantitative spatial statistics, we establish whether streets having the same temporal trajectory are collocated spatially or whether there is street to street variation in the temporal patterns of crime. In a surprising number of cases we find that individual street segments have trajectories which are unrelated to their immediately adjacent streets. This finding of heterogeneity suggests it may be particularly important to examine crime trends at very local geographic levels. At a policy level, our research reinforces the importance of initiatives like 'hot spots policing' which address specific streets within relatively small areas.

Evidence-based policing is a method of making decisions about “what works” in policing: which practices and strategies accomplish police missions most cost-effectively. In contrast to basing decisions on theory, assumptions, tradition, or convention, an evidence-based approach continuously tests hypotheses with empirical research findings. While research on all aspects of policing grew substantially in the late twentieth century, the application of research to police practice intensified in the early twenty-first century, especially for three tasks that make up the “triple-T” strategy of policing: targeting, testing, and tracking. Evidence-based targeting requires systematic ranking and comparison of levels of harm associated with various places, times, people, and situations that policing can lawfully address. Evidence-based testing helps assure that police neither increase crime nor waste money. Tracking whether police are doing what police leaders decide should be done may grow most rapidly in coming years by the use of GPS records of where police go and body-worn video records of what happens in encounters with citizens.