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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.

Previous research has found that when faced with dangerous environments, women may have an evolved preference for physically strong and aggressive men. This phenomenon has been named as the Bodyguard hypothesis. The aim of the present studies was to explore whether the same principle exists in non-romantic male friend selection. In Study 1, (n = 118), an on-line sample of British women was assessed for objective crime rates in their childhood and current environment, subjective vulnerability to crime, and preference for aggressive and formidable opposite-sex friends. Women’s subjective fear of crime predicted their preference for aggressive-formidable ideal male friends, as well as aggressive-formidable actual male friends. In Study 2 (n = 228), an internet sample of both sexes was assessed for their subjective fear of crime, as well as their preference for aggressive-formidability and other characteristics in same and opposite-sex friends. Fear of crime was not correlated with characteristics (intelligence, funniness, kindness) that were unrelated to aggressive-formidability. There was a small positive correlation between fear of crime and preference for aggressive-formidable friends in both sexes. The correlation between fear of crime and preference for ideal male friend’s aggression-formidability was the only statistically significant one, and none of the correlations differed significantly from each other. Together, these two studies provide some tentative evidence for the Bodyguard hypothesis in preferred friendship characteristics. Environmental influence on friendship selection is an under-investigated area of research, benefiting from future research replicating the methodology from studies on romantic partner characteristics.

Social support, institutional anomie, and macrolevel general strain perspectives have emerged as potentially important explanations of aggregate levels of crime. Drawing on insights from each of these perspectives in a cross‐national context, the analyses show that 1) our measure of social support is inversely related to homicide rates, 2) economic inequality also maintains a direct relationship with homicide rates, and 3) social support significantly interacts with economic inequality to influence homicide rates. The implications of the analysis for ongoing discourse concerning the integration of these criminological theories and the implications for the development of effective crime control policies are discussed.

Largely overlooked in the theoretical and empirical literature on the crime decline is a long tradition of research in criminology and urban sociology that considers how violence is regulated through informal sources of social control arising from residents and organizations internal to communities. In this article, we incorporate the \"systemic\" model of community life into debates on the U.S. crime drop, and we focus on the role that local nonprofit organizations played in the national decline of violence from the 1990s to the 2010s. Using longitudinal data and a strategy to account for the endogeneity of nonprofit formation, we estimate the causal effect on violent crime of nonprofits focused on reducing violence and building stronger communities. Drawing on a panel of 264 cities spanning more than 20 years, we estimate that every 10 additional organizations focusing on crime and community life in a city with 100,000 residents leads to a 9 percent reduction in the murder rate, a 6 percent reduction in the violent crime rate, and a 4 percent reduction in the property crime rate.

This study considers the degree to which the crime rates of US cities follow a uniform national trend. A nationwide trend has consequences for theories that explain aggregate changes in crime, but how closely subnational units hold to a common time path has received almost no research attention. Using annual panel data, the current study presents analyses that attempt to measure the correspondence between city-level and national-level crime rates. The results of each analysis are consistent with a clear single pattern that operates across the nation's major urban areas. This supports the idea that a meaningful national trend exists, and it suggests the desirability of continuing efforts to explain it.

This paper investigates the spatial aspect of criminal activity in Vancouver, Canada, employing social disorganization theory, routine activity theory and multiple measures of crime. Crime counts and crime rates with residential and ambient populations as denominators are calculated using the calls for service made to the Vancouver Police Department. The ambient population—a 24-hour average estimate of a population in a spatial unit to capture the population at risk—is obtained from the LandScan Global Population Database and calculated at a spatial resolution relevant to criminological research. Utilizing a spatial regression technique, strong support is found for routine activity theory across space and the use of ambient populations when calculating crime rates and measuring the population at risk.

Despite recent theoretical attention to \"social capital\" and its impact on a range of public problems, including crime, few studies have evaluated the relationship between crime rates and levels of social capital across populations. That research gap is due, in part, to the absence of macro-level empirical indicators of social capital. In this article, we measure social capital as a latent construct with aggregated voting and organizational membership data, and survey data on social trust, and examine its relationship with homicide rates for a nationally representative sample of geographic areas. Structural equation models show that the construct of social capital has a significant direct effect on homicide rates, net of other structural covariates, and controlling for the reciprocal influence of homicide on social capital. Although social capital mediates little of the effect on homicide of levels of economic deprivation, it explains more than two-thirds of the effect of Southern regional location. The results indicate that depleted social capital contributes to high levels of homicide, and provide a promising basis for future research on the mechanisms linking social capital to crime at the macro level.

While past research has suggested possible seasonal trends in crime rates, this study employs a novel methodology that directly models these changes and predicts them with explanatory variables. Using a nonlinear latent curve model, seasonal fluctuations in crime rates are modeled for a large number of communities in the U.S. over a three-year period with a focus on testing the theoretical predictions of two key explanations for seasonal changes in crime rates: the temperature/aggression and routine activities theories. Using data from 8,460 police units in the U.S. over the 1990 to 1992 period, we found that property crime rates are primarily driven by pleasant weather, consistent with the routine activities theory. Violent crime exhibited evidence in support of both theories.

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

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 changed, but also how to influence future crime reduction.