Uniform Crime Report Data Research Articles

Hate Crime Victimization Data in Pennsylvania: A Useful Complement to the Uniform Crime Reports

Data on the incidence and prevalence of hate crimes in the United States come primarily from the Uniform Crime Reports (UCR). Although UCR data undercount most crimes, hate crimes are particularly underreported, especially for some groups. We compare 2000–2011 UCR data in Pennsylvania to data from a state agency that came from police, media, and citizen reports. First, we find that the state-agency database is generally consistent with the UCR data, in terms of absolute counts, correlations, and predictors. Second, we find that UCR data underestimate hate crime rates by a factor of about 1.6 overall and by a factor of 2.5 for rural areas. Moreover, although UCR data on hate crimes show a decrease in the most recent 5-year period, the state agency data show that hate crime incident counts have not dropped. We suggest that using a broader index that includes both the UCR and a database like that in Pennsylvania will give a more complete picture of hate crime.

Hate Crime Victimization Data in Pennsylvania: A Useful Complement to the Uniform Crime Reports.

Data on the incidence and prevalence of hate crimes in the United States come primarily from the Uniform Crime Reports (UCR). Although UCR data undercount most crimes, hate crimes are particularly underreported, especially for some groups. We compare 2000-2011 UCR data in Pennsylvania to data from a state agency that came from police, media, and citizen reports. First, we find that the state-agency database is generally consistent with the UCR data, in terms of absolute counts, correlations, and predictors. Second, we find that UCR data underestimate hate crime rates by a factor of about 1.6 overall and by a factor of 2.5 for rural areas. Moreover, although UCR data on hate crimes show a decrease in the most recent 5-year period, the state agency data show that hate crime incident counts have not dropped. We suggest that using a broader index that includes both the UCR and a database like that in Pennsylvania will give a more complete picture of hate crime.

Gender diversity and organisational performance: assessing the effects of gender diversity in US law enforcement agencies

As one of the first endeavours in the public sector that assess organisational consequences of hiring female employees in male-dominated occupations, this study examined organisational consequences that gender diversity would bring to male-dominated occupations, using a sample of law enforcement agencies. With law enforcement agencies' data from 464 cities with more than 50,000 residents in the USA, as well as Uniform Crime Reports Data, multiple regression analyses were conducted to find the effects of gender diversity. According to the findings, as more female sworn officers were hired in law enforcement agencies, conflicts between genders among sworn officers increased, but crime control performance was not significantly affected. Managerial implications are discussed.

Do parole abolition and Truth-in-Sentencing deter violent crimes in Virginia?

This paper examines the treatment effect of the justice reform enacted on January 1, 1995, in Virginia. Using FBI’s Uniform Crime Report data about crime rates per 100,000 population from 1960 to 2010, we find that after the reform the reported aggregated violent crime rate declined significantly and is mainly driven down by the decrease in robbery. We also consider property crime and find that the reported property crime rate does not decline until 4 years later, indicating that the justice reform in Virginia also has lagged treatment effect on property crime.

Assessing the Representativeness of NIBRS Arrest Data

This article examines the coverage of the National Incident-Based Reporting System (NIBRS) arrest data as of 2016. We use NIBRS and Uniform Crime Report (UCR), Summary Reporting System on persons arrested. We examine the correspondence of arrests measures between the UCR and NIBRS for overall arrests, and arrests by sex, race, and age. We found that NIBRS arrest data are a close match to UCR data overall and the differences across demographic measures are very slight.

The Impact of Drinking Age Laws on Perpetration of Sexual Assault Crimes in Canada, 2009–2013

PurposeSexual-assault crimes, primarily perpetrated by males against female victims, impose a substantial burden on societies worldwide, especially on youth. Given that approximately half of all sexual assaults involve alcohol consumption by the perpetrator or victim, it is reasonable to expect that minimum legal drinking age (MLDA) restrictions might have an effect on sexual-assault patterns. Canadian MLDA laws are 18 years in Quebec, Alberta, and Manitoba (MLDA-18), and 19 years in the rest of the country (MLDA-19). The present study assesses whether MLDA laws might have an impact on sexual-assault crimes. MethodsA regression-discontinuity design was applied to sexual-assault crime data (n = 12,980 incidents) from the national Uniform Crime Reporting survey 2009–2013, a population-level registry of all police-reported crimes in Canada. Uniform Crime Reporting data does not include an explicit alcohol involvement indicator. ResultsNationally, in comparison to males slightly younger than the MLDA, those just older had significant and immediate increases in sexual-assault perpetration of 31.9% (95% confidence interval: 8.7%–54.5%, p = .007). In MLDA-19 provinces, there was an immediate post-MLDA increase of 56.0% (95% confidence interval: 18.9%–90.8%, p = .004) in sexual-assault crimes by males just older than 19 years, whereas in MLDA-18 provinces no significant effect was found. For females, there was no evidence of MLDA effects on sexual-assault crimes. ConclusionsRelease from Canadian MLDA law restrictions was strongly associated with increases in sexual-assault perpetration by young men. These findings lend support to the potential effectiveness of population-level alcohol control policies for sexual-assault prevention among youth.

The Implications of Marijuana Decriminalization and Legalization on Crime in the United States

Through 2014 Uniform Crime Report (UCR) data for all 50 U.S. states, this research explores the relationship between decriminalization and recreational and medical marijuana legalization and crime ...

Crime Seasonality across Multiple Jurisdictions in British Columbia, Canada

Seasonal changes in crime have been documented since the mid-1800s, but no definitive consensus has been reached regarding universal annual patterns. Researchers also tend to focus on a single city over a particular time period, and, due to methodological differences, studies can often be difficult to compare. As such, this study investigates the seasonal fluctuations of crime across eight cities in British Columbia, Canada, between 2000 and 2006. Uniform Crime Report data, representing four crime types (assault, robbery, motor vehicle theft, and break and enter) were used in negative binomial or Poisson count models and regressed against trend, weather, and illumination variables. Results suggest that temperature changes impacted assault levels, few weather variables affected the occurrence of robberies, and fluctuations in property crime types were variable across the cities. Moreover, rain and snow had a deterrent effect on crime in cities that were not used to such weather conditions. These findings imply that (a) changes in weather patterns modify peoples’ routine activities and, in turn, influence when crime is committed; (b) universal crime seasonality patterns should not be assumed across all cities; and (c) crime seasonality should be studied at a disaggregate or crime-specific level.

Likelihood‐Based Inference and Prediction in Spatio‐Temporal Panel Count Models for Urban Crimes

SummaryWe develop a panel count model with a latent spatio‐temporal heterogeneous state process for monthly severe crimes at the census‐tract level in Pittsburgh, Pennsylvania. Our dataset combines Uniform Crime Reporting data with socio‐economic data. The likelihood is estimated by efficient importance sampling techniques for high‐dimensional spatial models. Estimation results confirm the broken‐windows hypothesis whereby less severe crimes are leading indicators for severe crimes. In addition to ML parameter estimates, we compute several other statistics of interest for law enforcement such as spatio‐temporal elasticities of severe crimes with respect to less severe crimes, out‐of‐sample forecasts, predictive distributions and validation test statistics. Copyright © 2016 John Wiley & Sons, Ltd.

Surveying Residential Burglaries: A Case Study of Local-Level Crime Measurement

Our goal is to document the general issues that arise in estimating and comparing local crime rates over time and for different cities. Data are drawn from police-based residential burglary counts and the National Crime Victimization Survey to obtain interval estimates of residential burglary incidence at the local level. Ambiguity exists when making point estimates of crime that are based entirely on Uniform Crime Reports data. Sources of this ambiguity include (a) the “Hierarchy Rule,” (b) population estimates used in estimating the burglary rate, and (c) variation in the probability that a residential burglary victim reports the incident to the police. Analyses document uncertainty of burglary rates when comparing across cities and over time. We think it will be useful to begin reporting crime patterns in terms of a range of uncertainty that expresses both what is known and unknown about the numbers that are used to measure those patterns.

Police staffing levels: disaggregating the variation

Purpose – The purpose of this paper is to examine the relationship between community type classifications and police strength. Prior research has examined other correlates, but no attempts have been made previously to examine the relationship between community type (as outlined and defined by Chinni and Gimpel, 2010) and police staffing levels. Design/methodology/approach – Using a combination of NDLEA data on police strength, Uniform Crime Report data on crime, census data, and Chinni and Gimpel’s (2010) community classifications, this paper analyzes the relationship between a variety of correlates and police strength in 15,917 communities. Findings – The study found that police staffing does differ by community type as well as by a variety of other key community characteristics. Research limitations/implications – This implies that further research on appropriate tools to determine appropriate staffing levels is needed. Practical implications – This work indicates that traditional “peer benchmarking” approaches used to determine police strength should not be considered the best practice. Other approaches may be more appropriate and should be examined. Originality/value – This is the first study to incorporate classifications of community type in the analysis of police strength.

Likelihood Based Inference and Prediction in Spatio-Temporal Panel Count Models for Urban Crimes

We develop a panel data count model combined with a latent Gaussian spatio-temporal heterogenous state process to analyze monthly severe crimes at the census tract level in Pittsburgh, Pennsylvania. Our data set combines Uniform Crime Reporting data with socio-economic data from the 2000 census. The likelihood of the model is accurately estimated by adapting recently developed efficient importance sampling techniques applicable to high-dimensional spatial models with sparse precision matrices. Our estimation results confirm socio-economic explanations for crime and, foremost, the broken-windows hypothesis, whereby less severe crimes in a region is a leading indicator for severe crimes. In addition to ML parameter estimates, we compute several other statistics of interest for law enforcement such as elasticities (idiosyncratic, total, short-term as well as long-term) of severe crimes w.r.t. less severe crimes, one-month-ahead out-of-sample forecasts, predictive cumulative distribution functions and validation test statistics based on these cdf's.

Intra- and inter-neighborhood income inequality and crime

One important factor in many macro-level theories of crime is income inequality. Although research generally shows that low levels of neighborhood income are associated with crime, research studies have been less clear on whether income inequality is a robust, independent predictor of crime, particularly in small area studies, and few studies have explicitly considered income inequality between neighborhoods, and those that do typically focus on homicide. The current study examines whether within and between neighborhood income inequality is associated with variation in violent and property crime. We employ geocoded Uniform Crime Report data from the Indianapolis police department and economic and demographic characteristics of the population from the American Community Survey for 2005–2009. Consistent with prior research, lower levels of income were associated with higher violent and property crime counts. Within-tract income inequality was also associated with higher Uniform Crime Reports violent and property crimes in most models. Results also showed that the ratio of tract income levels to neighboring tracts is associated with variation in crime. Thus, both local and nearby income inequality affect crime. Implications for theory and policy are discussed.

Erratum to: Effects of the Repeal of Missouri’s Handgun Purchaser Licensing Law on Homicides

Erratum to: J Urban Health DOI 10.1007/s11524-014-9865-8 The authors would like to publish this erratum to correct estimates generated from regression analyses due to errors identified in the data for certain covariates used in those analyses. The authors apologize that they did not identify the errors prior to publication. The corrected data presented below are very similar to, but are more accurate than, the findings previously published. ABSTRACT 1. The fourth and fifth sentences should be deleted and replaced with, “Using death certificate data available through 2010, the repeal of Missouri’s PTP laws was associated with an increase in the annual firearm homicide rates of 1.18 per 100,000 (+25 %) representing 68 additional firearm homicides annually, but was unrelated to changes in non-firearm homicide rates. Using Uniform Crime Reports data from police available through 2012, the law’s repeal was associated with increased annual murder rates of 0.81 per 100,000 (+14 %) representing 49 additional murders per year.” 2. The last sentence should be deleted. (The corrected data from the prior sentence are integrated into the corrected sentences above.) RESULTS 1. Table 2 should be deleted and replaced with corrected Table 2 below. 2. The last sentence of the third paragraph should be deleted and replaced with, “After controlling for changes in rates of unemployment, poverty, burglary, incarceration, and law enforcement officers along with other state laws, the estimated increase in annual firearm homicide rates associated with the repeal of Missouri’s PTP handgun law was 1.18 per 100,000 population per year (p 3. The last sentence of the 4th paragraph should read, “Regression analyses indicated that Missouri’s repeal of its PTP handgun law was associated with no change in the age-adjusted non-firearm homicide rate (β = −0.07, p = .468, 95 % CI −0.27 to 0.12) and an increase in annual homicide rates for all methods of 1.08 (Table 2, p 4. The last sentence of the 5th paragraph should read, “A model which only controlled for state- and year fixed effects estimated a 1.34 increase in annual murder rates through the end of 2012 associated with the repeal of the PTP handgun law (β = 1.34, p = .001, 95 % CI 0.58 to 2.11); however, the estimated effect of the policy change was reduced to an increase of 0.81 murders per 100,000 per year after all covariates were included in the model (Table 2, β = 0.81, p = .004, 95 % CI 0.26 to 1.35), a 14 % increase relative to the counterfactual.” 5. The second sentence of the 6th paragraph should read, “New unsafe handgun bans adopted in California and Massachusetts were associated with an increase in firearm, non-firearm, and total homicide rates (β = 0.28, p = .014, 95 % CI 0.06 to 0.50; β = 0.19, p = .007, 95 % CI 0.05 to 0.32; β = 0.46, p = .008, 95 % CI 0.13 to 0.70).” 6. Supplemental Tables 1–4 should be replaced with the corrected Supplemental Tables below. DISCUSSION 1. The last sentence of the first paragraph should read, “Our estimates suggest that the repeal of the law was associated with an additional 68 firearm homicides per year in Missouri between 2008 and 2010 and 49 additional murders per year between 2008 and 2012 than the forecasted counterfactual.” Language: en

State Residence Restrictions and Forcible Rape Rates

This study examines whether the presence of state residence restrictions resulted in changes in statewide rates of forcible rape. It builds on the limited geographic coverage of prior studies by including state-level Uniform Crime Report (UCR) data across 19 years for 49 states and the District of Columbia. It uses a quasi-experimental research method based on a longitudinal fixed-effects panel model design, which can help control for relatively static differences between states. Results indicate that when a state residence restriction was present, regardless of how it was measured, rates of UCR forcible rape were higher in the state than when the policy was not present. This suggests that residence restrictions, at least at the state level, are not useful as an overall crime prevention measure, but may be useful for increasing detection or reporting levels of such crimes. However, results also suggest that the size of the increase varied by whether the policy only applied to offenders with child victims or also included those with adult victims. Implications for research and policy are discussed.

Evaluating the Availability of Uniform Crime Reporting Data, and Using Data Management to Make It More Powerful and Accessible

Existing true raw for Uniform Crime Reporting (UCR) Hate Crime Data is available in ASCII, with each year as a separate file, or on the FBI website, where the abridged summary information omits most of the additional demographic information obtained from the switch to a National Incident Based Reporting System (NIBRS). The attached NIBRS information is critical, because it provides additional data for social science researchers, citizens, and law enforcement to most accurately assess at-risk groups and areas and determine the causes of hate crime offenses. The fully-detailed ASCII format data has been reformatted and recoded into a single unified Microsoft Excel database. The process to do so is described step-by-step.

Abstract P184: Neighborhood Crime and Poverty is Associated with Systemic Inflammation in Children

Introduction: The neighborhood environment may contribute to cardiovascular disease risk by promoting physical inactivity and/or unhealthy eating, as well as through exposure to chronic psychosocial stress. Elevated serum C-reactive protein (CRP) concentrations have been associated with increased cardiovascular risk in adults and may also be a marker for stress-related inflammation. Whether CRP is associated with stressful neighborhood conditions among children is unknown. Hypothesis: We hypothesized that children and adolescents living in neighborhoods characterized by high levels of poverty or crime have higher concentrations of CRP, independent of adiposity. Methods: The sample included 395 children 5-18 years of age (50% African American, 46% white, 4% other race; 48% male, 52% female) from 262 households and 102 census tracts in southeastern Louisiana. Serum CRP levels were measured with a high-sensitivity chemiluminescent immunoassay. High risk neighborhoods were defined as those in the upper tertile of either census-tract family poverty (US Census 2000) or of an index of total crime derived from Uniform Crime Report data (CrimeRisk, Applied Geographic Solutions). Multilevel logistic regression analyses that accounted for both family and neighborhood clustering compared children and adolescents with CRP levels >3mg/L to those with levels ≤3 mg/L across high versus low risk census tracts. Analyses also controlled for race, sex, age, and total body fat (kg) measured by dual-energy x-ray absorptiometry. Results: In this sample, 16.0% of children had CRP levels higher than 3 mg/L. After adjustment for covariates, and family and neighborhood clustering, total body fat was positively associated with high CRP levels (p<0.0001) and age was negatively associated with higher CRP levels (p=0.001). Race and sex showed no associations. Independent of adiposity, children from census tracts with the highest levels of either crime or poverty had 2.4 (95% CI: 1.1-5.1) times the odds of having high CRP levels when compared to children from other census tracts. Conclusions: Children from neighborhoods characterized by high levels of poverty or crime appear to have higher levels of C-reactive protein, a marker of systemic inflammation and cardiovascular risk. Stress may initiate cardiovascular disease starting in childhood. This research identifies neighborhoods at high risk, where early disease screening and prevention efforts may have maximal impact.

The impact of community policing on crime rates: does the effect of community policing differ in large and small law enforcement agencies?

This study utilized three major data-sets consisting of Law Enforcement Management and Administrative Statistics 2003, two waves of Uniform Crime Report data, and the US Census 2000 data to examine whether the relationship between community policing and crime differs based on the agency size. To operationalize community policing, the authors employed factor analyses. The results yielded three dimensions for the construct of community policing. The multiple-regression analyses indicate that all dimensions of community policing have a significant relationship to crime rates in small agencies; whereas, in large agencies, only problem-solving partnership has a significant positive association with property and violent crime rates. The level of implementation of problem-solving partnership dimension has a positive effect on both small and large agencies, but this effect is more prominent for small agencies. These findings along with possible policy implications are discussed.

Assessing the Impact of Changes in Gender Equality on Female Homicide Victimization

Numerous studies have tested the feminist hypothesis that gender inequality affects homicide rates by analyzing Census and Uniform Crime Report data for a single time period. Although these “snapshot” tests are important, they do not capture the “change” element that is implied by these hypotheses. According to feminist perspectives, gender inequality and gender equality could increase homicide rates, the former increasing the structural disadvantage of women relative to men and the latter representing a “backlash” effect. Women’s absolute status may also be an important predictor of homicide victimization. Furthermore, it is quite possible that this process is dynamic and therefore the change in equality over time may be more important than the actual level of equality at any given time. The present study measures the impact of gender equality and women’s absolute status on female homicide victimization using city-level data from 1980 to 2000. In general, the results suggest that changes in gender equality and women’s absolute status have decreased women’s rate of homicide victimization, and the negative effect of gender equality appears to have grown stronger over time; however, these results are not uniform across victim–offender relationships.

Comparing large and small metropolitan newspaper coverage of delinquency with arrest data: differential coverage or more of the same?

It is generally assumed and expected that newspapers do not portray an accurate picture of crime. However, little research exists to confirm this misrepresentation as it relates to juvenile offenders in small compared to large metropolitan areas. The purpose of this study is to assess how accurate small and large Metropolitan Statistical Area (MSA) newspapers are in their depiction of juvenile offenders compared to Uniform Crime Report (UCR) data and whether or not the degree of accuracy differs across different sized metropolitan areas. An analysis of 953 articles reveals that small and large MSAs differentially cover juvenile offenders and that this coverage differs by gender. It is equally clear that newspaper coverage of delinquency in both small and large MSAs does not accurately represent arrest statistics and that this accuracy also differs by both MSA size and gender.