Exploring Some Analytical Characteristics of Finite Mixture Models

Finite mixture models have become increasingly prevalent in criminology over the past two decades. Yet there is no consensus about the appropriate criterion for model selection with finite mixture specifications. In this paper, we use simulation evidence to examine model selection criteria. Our focus is on mixture models for event count data like those often encountered in criminology. We use two indices to measure model selection performance. First, we examine how often each criterion chooses the correct specification. Then, we investigate how closely the finite mixture models selected by these criteria approximate the true mixing distribution used to simulate the event count data. We consider three sets of simulations. In the first set, the underlying model is itself a three component Poisson-based finite mixture model. In the two other sets of simulations, the underlying distribution of the Poisson rate parameter follows a continuous distribution. The analysis shows that both AIC and BIC perform well under certain sets of circumstances likely to be encountered by criminologists.

Researching the use of force: the background to the international project

This article provides the background to an international project on use of force by the police that was carried out in seven countries. Force is often considered to be the defining characteristic of policing and much research has been conducted on the determinants, prevalence and control of the use of force, particularly in the United States. However, little work has looked at police officers’ own views on the use of force, in particular the way in which they justify it. Using a hypothetical encounter developed for this project, researchers in each country conducted focus groups with police officers in which they were encouraged to talk about the use of force. The results show interesting similarities and differences across countries and demonstrate the value of using this kind of research focus and methodology.

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Singing the same tune? International continuities and discontinuities in how police talk about using force

This article focuses on a research project conducted in six jurisdictions: England, The Netherlands, Germany, Australia, Venezuela, and Brazil. These societies are very different ethnically, socially, politically, economically, historically and have wildly different levels of crime. Their policing arrangements also differ significantly: how they are organised; how their officers are equipped and trained; what routine operating procedures they employ; whether they are armed; and much else besides. Most relevant for this research, they represent policing systems with wildly different levels of police shootings, Police in the two Latin American countries represented here have a justified reputation for the frequency with which they shoot people, whereas at the other extreme the police in England do not routinely carry firearms and rarely shoot anyone. To probe whether these differences are reflected in the way that officers talk about the use of force, police officers in these different jurisdictions were invited to discuss in focus groups a scenario in which police are thwarted in their attempt to arrest two youths (one of whom is a known local criminal) by the youths driving off with the police in pursuit, and concludes with the youths crashing their car and escaping in apparent possession of a gun, It might be expected that focus groups would prove starkly different, and indeed they were, but not in the way that might be expected. There was little difference in affirmation of normative and legal standards regarding the use of force. It was in how officers in different jurisdictions envisaged the circumstances in which the scenario took place that led Latin American officers to anticipate that they would shoot the suspects, whereas officers in the other jurisdictions had little expectation that they would open fire in the conditions as they imagined them to be.

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Measuring corporate environmental crime rates: progress and problems

The problem of corporate crime rates has been the subject of debate, speculation and operationalization for decades, largely stemming from the complexity of measuring this type of crime. Examining corporate environmental crime poses challenges and creates opportunities for advancing the discussion of corporate crime rates, but criminologists are less familiar with environmental data. In the current paper, we review the strengths and weaknesses of existing environmental data that can be used to construct the components of an environmental crime rate. We also present a corporate environmental crime rate derived from data on violations of the Clean Water Act and describe problems with using it in real world data. Implications for theory, practice and future research are discussed.

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Does Incapacitation Reduce Crime?

Questions and answers about incapacitation abound in all discussions about criminal justice policy. They are among the most pressing of all research issues, yet estimates about the incapacitation effect on crime vary considerably, and most are based on very old and incomplete estimates of the longitudinal pattern of criminal careers. This paper provides an overview of the incapacitation issue, highlights information on recent estimates of criminal careers that are useful to the incapacitation model, and outlines an ambitious research agenda for continued and expanded work on incapacitation and crime that centers on developing better estimates of the characteristics of criminal careers and their relevance to policy choices.

Thinking Critically About Rural Gender Relations: Toward a Rural Masculinity Crisis/Male Peer Support Model of Separation/Divorce Sexual Assault

After decades of neglect, a growing number of scholars have turned their attention to issues of crime and criminal justice in the rural context. Despite this improvement, rural crime research is underdeveloped theoretically, and is little informed by critical criminological perspectives. In this article, we introduce the broad tenets of a multi-level theory that links social and economic change to the reinforcement of rural patriarchy and male peer support, and in turn, how they are linked to separation/divorce sexual assault. We begin by addressing a series of misconceptions about what is rural, rural homogeneity and commonly held presumptions about the relationship of rurality, collective efficacy (and related concepts) and crime. We conclude by recommending more focused research, both qualitative and quantitative, to uncover specific link between the rural transformation and violence against women. This paper was presented at the 2006 annual meeting of the American Society of Criminology, Los Angeles, California. Some of the research reported here was supported by National Institute of Justice Grant 2002-WG-BX-0004 and financial assistance provided by the College of Arts and Sciences and the Office of the Vice President for Research at Ohio University. Arguments and findings included in this article are those of the authors and do not represent the official position of the US Department of Justice or Ohio University. Please send all correspondence to Walter S. DeKeseredy, e-mail: walter.dekeseredy@uoit.ca. All of the names of the women who participated in DeKeseredy and colleagues’ rural Ohio study and who are quoted have been changed to maintain confidentiality.

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Criminal victimization in contemporary China: a review of the evidence and challenges for future research

The rapid economic growth in China over recent decades has been accompanied by higher levels of crime, but there have been few studies of the Chinese experience of criminal victimization. A recent victimization survey of a representative sample of households in Tianjin represents a major effort to fill this gap in the literature. The present paper reviews the research based on the Tianjin survey along with other studies of crime and criminal victimization in China that have been published since 1990. We summarize the major findings, discuss the theoretical perspectives and methodological strategies that have been applied, identify the limitations of the research to date, and offer suggestions for future research.

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The impact of the US legislation on company measures of control and prevention

The spectacular business scandals in recent years have led both the legislative and business companies to rethink and redesign their strategies. This article analyzes the worldwide impact of reforms in economic crime legislation emanating from the USA. Empirical data are reported showing that the US regulations are generating a spillover effect spreading beyond its sphere of operation. It is particularly notable that international stock-exchange-listed companies are orienting themselves increasingly toward the legal standards of the USA. Translated from the German by Jonathan Harrow, Bielefeld.

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Using Booking Data to Model Drug User Arrest Rates: A Preliminary to Estimating the Prevalence of Chronic Drug Use

Public policy is often concerned with the size and characteristics of special populations that are difficult to reach in household surveys. Chronic drug users, who often live outside conventional households, provide the illustration motivating this paper. An alternative to household surveys is to question chronic drug users where they congregate—jails, treatment programs, and shelters, for example. Using such opportunistic data for prevalence estimation raises difficult problems for statistical inference: Study subjects who arrive at the collection points cannot be deemed a random sample of the general population. However, if we could estimate the rates at which chronic drug users arrive at the collection points, then we could use those estimates to weight the sample to represent the population. This paper presents a modified Poisson mixture model used to estimate the stochastic process that accounts for how chronic drug users get arrested. It uses that model to estimate arrest rates for 38 counties using up to sixteen quarters of data from the Arrestee Drug Abuse Monitoring survey.

Modeling the Deviant Y in Criminology: An Examination of the Assumptions of Censored Normal Regression and Potential Alternatives

Many dependent variables of criminological interest have censored distributions. Investigations that use such variables increasingly have turned to the Tobit model, a censored regression technique that is specified based on a latent dependent variable. When used under suitable circumstances, this model provides appropriate estimates. This paper discusses key assumptions of the Tobit model. It then highlights the risk of violating these assumptions and reviews alternative flexible parametric and semiparametric modeling techniques, currently used sparingly in criminology, which researchers may find helpful when assumptions regarding the error terms are untenable. By using an empirical example focused on sentencing outcomes and comparing estimates across analytic methods, this study illustrates the potential utility of simultaneously estimating the Tobit model along with some alternatives.

Estimating the Number of Crimes Averted by Incapacitation: An Information Theoretic Approach

This paper presents an information theoretic approach for estimating the number of crimes averted by incapacitation. It first develops models of the criminal history accumulation process of a sample of prison releasees using their official recorded arrest histories prior to incarceration. The models yield individual offending trajectories that are then used to compute the number of crimes these releasees could reasonably have been expected to commit had they not been incarcerated—the counterfactual of interest. The models also afford the opportunity to conduct a limited set of policy simulations. The data reveal a fair amount of variation among individuals both in terms of the number of crimes averted by their incarceration and the responsiveness of these estimates to longer incarceration terms. Estimates were found not to vary substantially across demographic groups defined by offender race, gender, or ethnicity; variations across states and offense types were more pronounced. Implications of the findings and promising avenues for future research are discussed.

Bankruptcy law: a mechanism of governance for financially distressed firms

This paper explores the various governance models for financially distressed firms. We offer a new typology of major bankruptcy models and provide a connection between this bankruptcy law puzzle and the variables depicting the governance of healthy firms in order to shed light on two topics: (1) the factors that the lawyer should consider before changing its national bankruptcy law, and (2) the risks associated with each bankruptcy model according to the economic literature on bankruptcy law. Our final aim is to test whether the various bankruptcy models detailed in the paper perform in separate economic and legal environments.

Analyzing Criminal Trajectory Profiles: Bridging Multilevel and Group-based Approaches Using Growth Mixture Modeling

Over the last 25 years, a life-course perspective on criminal behavior has assumed increasing prominence in the literature. This theoretical development has been accompanied by changes in the statistical models used to analyze criminological data. There are two main statistical modeling techniques currently used to model longitudinal data. These are growth curve models and latent class growth models, also known as group-based trajectory models. Using the well known Cambridge data and the Philadelphia cohort study, this article compares the two “classical” models—conventional growth curve model and group-based trajectory models. In addition, two growth mixture models are introduced that bridge the gap between conventional growth models and group-based trajectory models. For the Cambridge data, the different mixture models yield quite consistent inferences regarding the nature of the underlying trajectories of convictions. For the Philadelphia cohort study, the statistical indicators give stronger guidance on relative model fit. The main goals of this article are to contribute to the discussion about different modeling techniques for analyzing data from a life-course perspective and to provide a concrete step-by-step illustration of such an analysis and model checking.

Investment sensitivity to interest rates in an uncertain context: is a positive relationship possible?

This paper shows a non-linear relationship between investment and interest rates under uncertainty. Since the interest rate’s variance is positively related to the investment’s value (through the discount factor) and, generally, is also positively related to the interest rate’s level, then, at the same time, a negative (classical) and a positive (through the interest rate’s variance) relationship links interest rates to investment. Hence, an ultimate and even positive relationship between investment and interest rates’ (expected) level may occur. A specific model is proposed and the conditions upon which the positive effect occurs are derived. Some estimates are also proposed.

Incapacitation: Revisiting an Old Question with a New Method and New Data

We use the National Longitudinal Survey of Youth 1997 to obtain estimates of the number of crimes avoided through incapacitation of individual offenders. Incarcerated individuals are matched to comparable non-incarcerated counterparts using propensity score matching. Propensity scores for incarceration are calculated using a wide variety of time-stable and time-varying confounding variables. We separately analyze juvenile (age 16 or 17) and adult (age 18 or 19) incapacitation effects. Our best estimate is that between 6.2 and 14.1 offenses are prevented per year of juvenile incarceration, and 4.9 to 8.4 offenses are prevented per year of adult incarceration.

Simulation for Theory Testing and Experimentation: An Example Using Routine Activity Theory and Street Robbery

Achieving a better understanding of the crime event in its spatio-temporal context is an important research area in criminology with major implications for improving policy and developing effective crime prevention strategies. However, significant barriers related to data and methods exist for conducting this type of research. The research requires micro-level data about individual behavior that is difficult to obtain and methods capable of modeling the dynamic, spatio-temporal interaction of offenders, victims, and potential guardians at the micro level. This paper presents simulation modeling as a method for addressing these challenges. Specifically, agent-based modeling, when integrated with geographic information systems, offers the ability to model individual behavior within a real environment. The method is demonstrated by operationalizing and testing routine activity theory as it applies to the crime of street robbery. Model results indicate strong support for the basic premise of routine activity theory; as time spent away from home increases, crime will increase. The strength of the method is in providing a research platform for translating theory into models that can be discussed, shared, tested and enhanced with the goal of building scientific knowledge.

Bank regulation and supervision in bank-dominated financial systems: a comparison between Japan and Germany

This paper compares bank regulation and supervision in Japan and Germany. We consider these countries because they both have bank-dominated financial systems and their banking systems are often lumped together as one model, yet, bank stability differs significantly. We show that Japan and Germany have chosen different approaches to bank regulation and supervision and ask why they made their choices. We argue that bank regulation and supervision were less efficient in Japan than in Germany and that these differences were decisive for bank behavior.

A new approach to measuring technology with an application to the shape of the diffusion curves

This paper documents the sources and measures of the cross-country historical adoption technology (CHAT) data set that covers the diffusion of about 115 technologies in over 150 countries over the last 200 years. We use this comprehensive data set to explore the shape of the diffusion curves. Our main finding is that, once the intensive margin is measured, technologies do not diffuse in a logistic way.

Estimating Mean Length of Stay in Prison: Methods and Applications

This paper examines various approaches to studying the mean length of stay in prison. The literature contains a wide range of estimates of this quantity. The discrepancies that appear in these estimates and in the conclusions reached from them have been the subject of several reviews. We build upon that work, using the life table as the gold standard, to demonstrate the inaccuracy of common measures such as the ratio of the population size to the annual number of entrances or the mean length of time served by those exiting in a particular period. This demonstration is conducted in two parts. One part uses model populations with constant growth rates; the second part relies upon simulated prison populations with time-varying rates of entrance and exit. In addition, we introduce two new indirect measures that are more accurate than several existing indirect measures and that are relatively easy to use. The new measures are based on the entrance rate or the exit rate and adjust for the growth rate of the prison population.

Measuring and Modeling Repeat and Near-Repeat Burglary Effects

We develop a mathematical framework aimed at analyzing repeat and near-repeat effects in crime data. Parsing burglary data from Long Beach, CA according to different counting methods, we determine the probability distribution functions for the time interval τ between repeat offenses. We then compare these observed distributions to theoretically derived distributions in which the repeat effects are due solely to persistent risk heterogeneity. We find that risk heterogeneity alone cannot explain the observed distributions, while a form of event dependence (boosts) can. Using this information, we model repeat victimization as a series of random events, the likelihood of which changes each time an offense occurs. We are able to estimate typical time scales for repeat burglary events in Long Beach by fitting our data to this model. Computer simulations of this model using these observed parameters agree with the empirical data.