The National Incident-Based Reporting System: Research and Policy Applications

The National Incident-Based Reporting System (NIBRS) offers a new source ofdata for measuring crime. Though far from national in coverage, NIBRS datacan address research and policy questions outside the scope of the UniformCrime Reports and the National Crime Victimization Survey. Comparisons ofthe three sources of crime data are presented, with particular emphasis onwhat can be learned from incident-based police data that cannot be learnedfrom other sources. Like all data on crime, the NIBRS is subject to variousproblems with validity and measurement error. Two general categories of suchproblems are discussed: those evident in the design of the NIBRS and thoselinked to more general issues in the organizational production of data.     

NIBRS Data Available for Secondary Analysis

The NIBRS data program currently being implemented by the FBI and local lawenforcement agencies has by now produced sufficient data for archiving anddistribution. Although not representative of crime in the United States, existing NIBRS data can be used to investigate the nature of crimesknown to the police compared to the traditional UCR data. The Bureau ofJustice Statistics has requested the National Archive of Criminal JusticeData to store and make NIBRS data available to interested users. The datafrom 1996 will shortly be available from the NACJD web site. The 1996 datacontain almost 6.5 million records and the FBI's full file includes about 361 Mbytes of data. The data have been disaggregated from the FBI's complex single file into 11 segment levels or record types. This makes theindividual record types easier and faster to analyze than using the fullfile, which more closely resembles a relational database than a hierarchicalfile. However, splitting apart the record types requires that specialprocedures be used to merge files of different record types, which would benecessary if a user were interested in analyzing variables appearing in morethan one record type (e.g., comparing offender and victim ages). These procedures are described, and a test comparing the time to run a simple frequencycount using the full file against the merged files shows that using themerged files is considerably more efficient. Also discussed are some futuredevelopments to facilitate the analysis of NIBRS data.     

Using the National Incident-Based Reporting System (NIBRS) to Test Estimates of Arrestee and Offender Characteristics

National-Incident Based Reporting System (NIBRS) information for 1993 iscompared with two other sets of homicide data to assess the acuracy ofprocedures for estimating age-, sex-, and race-specific arrest counts fromtraditional Uniform Crime Report (UCR) data. The simultaneous age, race, andsex characteristics of offenders provided in the NIBRS arrest and offender segmentsare compared with estimates of the same characteristics derived from summaryUCR arrest data. The results suggest that using UCR marginal totals toestimate arrest counts by race and sex produces reasonably accurateestimates of the number of black and nonblack male arrests for murder andother offenses. Estimates of arrests of females by race and sex are lessaccurate, probably because of the relatively small number of arrests ofwomen and girls. Estimating male arrest counts for specific age groups alsoproduces reasonably accurate estimates. The results suggest that previousresearch employing such estimates may have been misleading in the estimatesof female arrests by race but accurate in the estimates of male arrests byrace. Although the use of summary UCR-based estimates in futurecross-sectional research will become increasingly unnecessary as the NIBRSreplaces the current UCR program, time series research designs on arrest andcrime trends will continue to require estimates.     

Crime Clearance and Temporal Variation in Police Investigative Workload: Evidence from National Incident-Based Reporting System (NIBRS) Data

Objectives

Police workload’s relationship with crime clearance has been studied widely. In the challenging environment now facing police, even small and possibly temporary changes in investigative workload could harm clearance. However existing workload-clearance research either used only a yearly average that obscures temporal variability in caseload, or explored proxy rather than direct measures of workload’s short-term variation. Our improved workload measures capture caseload’s daily changes as crimes are reported, cleared, or remain uncleared but reach the end of active investigation. We examine relationships between clearance and both long- and short-term variability in workload.

Methods

Using NIBRS and LEMAS data, we calculated between-agency (typical or long-term) and time-varying, within-agency (daily fluctuating or short-term) workload measures. We used these and other agency/jurisdiction- and incident-level variables in multi-level survival analysis of clearance by arrest for serious violent incidents from 2007 NIBRS.

Results

Both workload measures were significantly and negatively related to the clearance hazard rate; higher long- and short-term workloads are associated with reduced chance of a case being cleared. The estimated relationship between longterm workload and clearance became progressively stronger (more negative) as the crime incident’s legal seriousness decreased. However, estimates indicated greater sensitivity of the clearance hazard to short-term workload fluctuations for more serious crimes, though the workload-clearance relationship remained negative for all crime types.

Conclusion

Crime clearance should be considered by police agency planners when addressing workload through staffing decisions. Refinement of our workload measures will require additional information, and should be considered in future agency- and incident-level data collection.

     

Methods for Understanding and Analyzing NIBRS Data

The National Incident-Based Reporting System (NIBRS) is an incident-basedcrime reporting program for local, state, and federal law enforcementagencies. Within each criminal incident, NIBRS captures information onoffenses, victims, offenders, property, and persons arrested, as well asinformation about the incident itself. The ability to link and analyze thisdetailed information is a significant improvement to the existing UniformCrime Reporting (UCR) summary reporting system. As one might expect,however, this increase in crime data significantly complicates the life ofthe data analyst, particularly when cross tabulating the NIBRS data. To dealwith the complexity of NIBRS data, one must understand its structure. Thisarticle provides an overview of the NIBRS structure and methods formaneuvering within it to present and interpret correctly cross tabulationsof the NIBRS data.     

Victims and Offenders in Two Crime Statistics Programs: A Comparison of the National Incident-Based Reporting System (NIBRS) and the National Crime Victimization Survey (NCVS)

The National Incident-Based Reporting System (NIBRS) overcomes a basiclimitation of the traditional summary Uniform Crime Reporting program (UCR)by collecting victim information. Using this new victim information tocompare National Crime Victimization Survey (NCVS) and NIBRS results, wefind some similarities as well as some differences in the characteristics ofvictims and offenders suggested by the two programs. Similarities appear inthe proportions of men and women involved as victims and offenders forrobbery and assault. Comparisons are more difficult and the proportions lesssimilar for property offenses. Nevertheless, the results suggest that whenthe NIBRS is fully developed, it will be an important source of informationon the characteristics of both victims and offenders. Even before theredesigned program is fully implemented, one of the most important featuresof NIBRS reports will be their ability to provide local area victimizationinformation. In addition, the NIBRS will provide much more information onarrests and the characteristic of offenders than any existing program.     

The Relationship Between Crime Reporting and Police: Implications for the Use of Uniform Crime Reports

Empirical studies that use reported crime data to evaluate policies for reducing crime will understate the true effectiveness of these policies if crime reporting/recording behavior is also affected by the policies. For instance, when the size of the police force increases, changes in the perceived likelihood that a crime will be solved may lead a higher fraction of victimizations to be reported to the police. In this paper, three data sets are employed to measure the magnitude of this reporting bias. While each of these analyses is subject to individual criticisms, all of the approaches yield similar estimates. Reporting bias appears to be present but relatively small in magnitude: each additional officer is associated with an increase of roughly five Index crimes that previously would have gone unreported. Taking reporting bias into account makes the hiring of additional police substantially more attractive from a cost–benefit perspective but cannot explain the frequent inability of past studies to uncover a systematic negative relationship between the size of the police force and crime rates.     

Estimates of Repeat Victimization Using the National Crime Victimization Survey

Many crime victims experience multiple victimizations over time. Estimating the rate of repeat victimization from a longitudinal survey, however, is difficult because individuals often have missing data for some of the interviews. We use data from the 1996–98 U.S. National Crime Victimization Survey to explore potential effects of missing data on estimated rates of repeat violent victimizations in individuals. We introduce two algorithms for estimating repeat victimization rates, using logistic models to impute values for individuals who have partial data. These models are applied to estimate rates of repeat victimization for all violent crimes, and separately for crimes of domestic violence. Estimates show substantial sensitivity to the form of the model used.     

Reconsidering the Relationship Between Welfare Spending and Serious Crime: A Panel Data Analysis with Implications for Social Support Theory

Several researchers have found an inverse relationship between welfare spending and serious crime. With few exceptions, these findings have been based on cross‐sectional designs, single measures of welfare spending, and few indicators of crime. In response to these limitations, the relationship between welfare spending and crime was reconsidered using panel data from California counties. Fixed‐effects regressions revealed virtually no relationship between several measures of welfare spending and five types of serious crime: (1) homicide; (2) robbery; (3) assault; (4) burglary; and (5) larceny. The estimates were resistant to numerous robustness checks and alternative specifications. The most plausible explanation for the findings is that heterogeneity was not controlled for in previous studies. Implications for social support theory are discussed.     

论视频监控的犯罪预防功能及犯罪侦查价值

各国的犯罪预防理论发展至今,已经形成了比较完善的犯罪预防体系,主要包括司法预防、社会预防和情景预防三种模式。在我国的犯罪预防体系中,向来重视司法预防和社会预防,而对情景预防关注不够,情景预防措施尚不完善。作为一种对犯罪的干预,视频监控是一种对情境犯罪的干预,研究发掘其在犯罪预防中的作用对完善犯罪预防体系具有重要意义。同时,视频监控系统在犯罪侦查方面也具有重要作用。     

Poisson-Based Regression Analysis of Aggregate Crime Rates

This article introduces the use of regression models based on the Poissondistribution as a tool for resolving common problems in analyzing aggregatecrime rates. When the population size of an aggregate unit is small relativeto the offense rate, crime rates must be computed from a small number ofoffenses. Such data are ill-suited to least-squares analysis. Poisson-basedregression models of counts of offenses are preferable because they arebuilt on assumptions about error distributions that are consistent withthe nature of event counts. A simple elaboration transforms the Poissonmodel of offense counts to a model of per capita offense rates. Todemonstrate the use and advantages of this method, this article presentsanalyses of juvenile arrest rates for robbery in 264 nonmetropolitancounties in four states. The negative binomial variant of Poisson regressioneffectively resolved difficulties that arise in ordinary least-squaresanalyses.     

犯罪网络分析:社会网络分析在有组织犯罪研究中的应用

在刑事司法领域所使用的"网络"(networks)一词通常是指犯罪组织。一个犯罪网络首先也是一个社会网络,社会网络分析是对社会关系结构及其属性加以分析的一套规范和方法。它主要分析的是不同社会单位(个体、群体或社会)所构成的关系的结构及其属性。自美国"9.11事件"以来,世界各国政府、学者、媒体逐渐认识到社会网络分析在有组织犯罪防控研究中的重要作用,纷纷使用社会网络分析方法对恐怖主义犯罪等有组织犯罪进行犯罪网络分析、研究,通过解构犯罪组织,发现犯罪成员体系、结构特征与行动目标,从而对有组织犯罪进行有效预防和打击。我国应充分认识社会网络分析在现代有组织犯罪防控研究中的重要价值,全面了解国外有关理论与应用发展,积极采取政府资助项目研发与直接设立研究机构等多种手段,促进犯罪网络分析理论与方法在我国的迅速发展。     

职务犯罪的经济分析及其防范

职务犯罪行为人利用职权谋取私利具有经济学理性特征,因此,其行为必然遵从经济学的基本法则。用经济分析的方法研究其产生机理,探讨预防措施具有现实意义。基于犯罪经济成本收益理论,通过对职务犯罪的研究,得出如下结论：应增大犯罪成本,控制犯罪收益,从而最终预防和减少职务犯罪。     

经济犯罪死刑立法的多维解析

经济犯罪的概念对破坏市场经济秩序罪具有评价功能,而后者对前者具有载体功能。这一命题使得经济犯罪死刑立法的分析更具明确性。经济犯罪死刑立法的本质问题是刑法的政治性过度侵蚀刑法的道德性。经济刑法过度政治化的约束条件主要有4个,即工具主义刑法观、民主性不足的立法程序、老一代政治家的政治情感、法典主义的立法技术。随着这4个因素的先后变化,预计经济犯罪的死刑立法将很快得到改观。     

Using Dasymetric Mapping for Spatially Aggregated Crime Data

With availability of crime data to the public via sources such as the Uniform Crime Reports, and increasing geographic information system (GIS) capabilities for mapping crime, macro-level studies of crime have advanced knowledge of how crime is distributed over large areas. Choropleth mapping, commonly used in macro-level studies, visually displays data by assigning the number of crimes or crime rate to the corresponding spatial unit and using different shades or textures for each value or classified values creating a thematic map. However, crime incidents or crime rates are not dispersed evenly within spatial units, and choropleth mapping masks the underlying nuances of the distribution. Artificial boundaries, along with variations in the size of the unit of analysis, can further distort the true distribution of crime. Dasymetric mapping provides a methodology for refining the distribution of crime within a spatial unit. It does so by using additional data, such as land use and census data, to provide a realistic estimate of how crime may be distributed within the units of analysis. Dasymetric mapping is also useful in creating density maps to reveal clusters of crime normally masked with choropleth maps. This paper will show how dasymetric mapping can estimate the spatial distribution of aggregate level residential burglary within political boundaries in Massachusetts based on land use and housing data.     

罪数判断标准研究

作为罪数理论的核心,罪数的判断不只是计算犯罪的单复,更关乎刑法目的的实现。然而现有的罪数标准由于种种缺陷均无法承载一罪、数罪的区分功能。从罪数论在整个刑法体系中的定位来看,其为连接犯罪论与刑罚论的桥梁,因此,犯罪个数的量定必须考虑相关犯罪要素的齐备和刑罚效果的适当,应在法益的基础上,综合行为、犯意等各种要素,并结合刑罚的充分必要性而为认定。     

有组织犯罪的政治经济分析

当前,在现代工业文明日趋成熟、民主政治日渐完善的同时,有组织犯罪集团正在试图建立一种可以使犯罪活动职业化、企业化、合法化的黑秩序,严重破坏了各国的政治稳定和经济繁荣。有组织犯罪的主要特点和表现形式都说明,它有着较深的政治经济根源,并不是简单的社会治安问题。对此应运用政治经济学的理论和方法研究这种现象的本质特征、内在规律和发展趋势,并从国外入手结合我国实际,探讨行之有效的对策。     

视频监控系统在犯罪侦防中的运用及其法律问题

在犯罪问题复杂化与警力资源相对有限的背景下,利用视频监控系统预防与侦查犯罪已经成为许多国家采取的策略。在犯罪预防领域,视频监控系统的运用得到了日常活动理论、理性选择理论、情境犯罪预防、新机会理论、犯罪被害理论与死角理论等学说的支持;在犯罪侦查领域,透过视频监控系统的实时监控与影像存录功能,侦查部门的战斗力得到显著提高。与此同时,视频监控系统在犯罪侦防中的运用也引发了一系列法律问题,故有必要遵循一定的法律原则,以法律规范视频监控系统的正确运用。     

Testing Theory and the Analysis of Time Series Data

Although the relationship between unemployment and crime has been a longstanding interest in criminology, there is little agreement about appropriate models for analyzing this relationship. David Greenberg's (this issue) discussion highlights two issues that raise questions about recent research on the unemployment–crime relationship. First, he extends the work of Hale and Sabbagh (1991) and argues that cointegration methods should be used instead of first-differenced regression models to analyze unemployment and crime time series data. Second, he argues that previous attempts to test his strain theory linking unemployment to the age distribution of crime rely on flawed hypotheses, inappropriate data, and faulty measurement. In this paper, I address both of Greenberg's claims. I begin with a discussion of the relative utility of cointegration analysis and of first-differenced regression models for the analysis of the unemployment–crime relationship, focusing on the link between theory and statistical model. I then discuss the possibility of ever testing and falsifying Greenberg's strain theory.     

Closing Off Opportunities for Crime: An Evaluation of Alley-Gating

A new situational crime prevention measure recently introduced into Great Britain involves the fitting of gates to alleyways running along the back of terraced properties to restrict access to local residents and reduce opportunities for offenders. A number of quantitative techniques were used to assess the success of the intervention in reducing burglary in the City of Liverpool. The results demonstrate that, relative to a suitable comparison area, burglary was reduced by approximately 37%, there was a diffusion of benefit to properties in the surrounding areas, and the scheme was cost beneficial with a saving of £1.86 for every pound spent. The analyses provide persuasive evidence that these reductions were attributable to the intervention. We argue that the methodological techniques demonstrated here can be applied more widely to crime prevention evaluations.