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2008, Journal of Economic Behavior & Organization
Criminals impose costs on society that go beyond the direct losses suffered by their victims; crime casts a shadow of uncertainty over our daily economic and social activities. Consequently, individuals and society as a whole choose to direct resources to crime prevention. In this study we analyze a virtual society facing such choices. Individuals, neighborhoods, and cities make crime prevention decisions and adjust their decisions over time as they attempt to balance the cost of crime with the cost of fighting it. The society that ultimately emerges exhibits aggregate criminal characteristics that mimic patterns of crime observable in the natural world. We then use this virtual society to conduct a series of anti-crime policy experiments, the results of which illustrate how different approaches to crime protection and incarceration can vary in their efficiency at reducing crime. As expected, more effective anti-crime measures tend to reduce crime, but the impact of prison is less clear. The model suggests that throwing more criminals into prison may reduce crime in the short run but may actually increase it in the long run.
Physica A: Statistical Mechanics and its Applications, 2012
Crime is the result of a rational distinctive balance between the benefits and costs of an illegal act. This idea was proposed by Becker more than forty years ago [1]). In this paper, we simulate a simple artificial society, in which agents earn fixed wages and can augment (or lose) wealth as a result of a successful (or not) act of crime. The probability of apprehension depends on the gravity of the crime, and the punishment takes the form of imprisonment and fines. We study the costs of the law enforcement system required for keeping crime within acceptable limits, and compare it with the harm produced by crime. A sharp phase transition is observed as a function of the probability of punishment, and this transition exhibits a clear hysteresis effect, suggesting that the cost of reversing a deteriorated situation might be much higher than that of maintaining a relatively low level of delinquency. Besides, we analyze economic consequences that arise from crimes under different scenarios of criminal activity and probabilities of apprehension.
Discrete and Continuous Dynamical Systems - Series S, 2010
Criminals are common to all societies. To fight against them the community takes different security measures as, for example, to bring about a police. Thus, crime causes a depletion of the common wealth not only by criminal acts but also because the cost of hiring a police force. In this paper, we present a mathematical model of a criminal-prone self-protected society that is divided into socio-economical classes. We study the effect of a non-null crime rate on a free-of-criminals society which is taken as a reference system. As a consequence, we define a criminal-prone society as one whose free-ofcriminals steady state is unstable under small perturbations of a certain socioeconomical context. Finally, we compare two alternative strategies to control crime: (i) enhancing police efficiency, either by enlarging its size or by updating its technology, against (ii) either reducing criminal appealing or promoting social classes at risk. 1. Introduction. The techniques of population dynamics and compartment models have been extensively used to study the influence of sociological and economical factors on the evolution of criminality [17], [3], [18], [1], [10]
The standard economic model of crime emphasizes the individual rationality and agency of criminals. On the other hand, sociological theories typically emphasize the importance of social forces. This essay surveys a recent strand of literature on law enforcement that bridges these two approaches. Using the tools of game theory, it investigates crime as the outcome of the interaction between rational individuals. The survey shows that this analysis leads to a substantially richer set of hypotheses regarding the effect of enforcement than the standard economic model, depending on the classification of the social context, or game, in which agents operate. In doing so, it brings rational choice theories in line with long-standing insights in the field of criminology, as well as providing new analytical distinctions and generalizations.
The Milken Institute Review, 2005
2013
It is not unusual these days to have a group of economists gather to discuss their research on crime. In Europe and the Americas, a critical mass of academic economists have specialized in the study of crime and its control, and there is now a steady flow of economics doctoral dissertations on this topic. As we near the 50 th anniversary of Gary Becker's seminal contribution to this field (Becker, 1968), it is fair to say that the economics of crime is no longer a "fringe" topic, but part of the standard portfolio that makes up economics. Among the markers of progress are these: • The National Bureau of Economic Research (NBER) created a working group on crime that has had regular meetings since 2007 and published an edited conference volume in 2011 (Cook, Ludwig, and McCrary); • A new organization within LACEA (the Latin American and Caribbean Economic Association), with the acronym AL CAPONE (The America Latina Crime and Policy Network) held its first annual meeting in 2011; 1 • The Transatlantic Workshop on the Economics of Crime has been running annually since
Crime prevention studies, 1994
Preoccupation with the threat of displacement has led crime prevention researchers to overlook the phenomenon of "diffusion of benefits," the unexpected reduction of crimes not directly targeted by the preventive action. This phenomenon, which can bring considerable added value to sltuatlonal measures, has been described as the "complete reverse" of displacement. Two processes underlying diffusion are Identified Involving, on the one hand, offenders' uncertainty about the extent of the Increased risk, and, on the other, their exaggerated perception that the rewards of particular crimes are no longer commensurate with the effort These processes are labeled, respectively, deterrence and discouragement. Recent research provides numerous examples of both kinds of diffusion. Ways of enhancing diffusion are explored, and a program of research Is advocated on offender perceptions of the opening and closing of criminal opportunities.
Beijing Law Review
There is currently no generally accepted method of estimating the costs of crime. After presenting the most commonly used methods of estimating crime, the authors attempt to explore the situation in Hungary. Taking 2009 as a base year, they recon the crime-related social expenditure accounts. The authors, with the help of other Hungarian research data and databases, have also taken into account the costs of the secondary social effects. The results of the calculations depend on the applied approach to crime and the interpretations of the social impacts of the delinquency. According to the authors calculations the social cost caused by crime was about 2.17 billion USA dollar: ($) (1.6 billion euro (EUR) in 2009. The authors deduct the sum that was drawn by the offenders as a benefit/profit from committing crime; therefore the crime caused 1.17 billion $ as a net social damage in 2009 in Hungary. The amount of 1.63 billion $ was spent on the crime control (e.g. law enforcement, judiciary, prison and crime prevention) in 2009. The results show that delinquency caused a total of 3.8 billion $ as a damage, or as an expenditure spent by the government in 2009.
Models of criminal behavior, where a person is assumed to act rationally on the basis of costs and benefits of legal and illegal opportunities, are presented in this chapter. Most of these models are similar to models of portfolio choice and of supply of labor. The empirical studies that are surveyed use various types of regression analyses and employ data from states and police regions down to campuses and individuals. Most studies corroborate the hypothesis that the probability of punishment, and to a lesser degree also the severity of punishment, has a deterrent effect on crime. The effects of various economic factors are less clear, although unemployment seems to increase crime. Methodological problems relating to the assumption of rationality, to statistical identification of equations, to measurement errors, and to operationalization of theoretical variables are discussed. JEL classification: K42
Criminology, 2009
Crimes have many features, and the mix of those features can change over time and space. In this paper, we introduce the concept of a crime regime to provide some theoretical leverage on collections of crime features and how the collection of features can change. Key tools include the use of principal components analysis to determine the dimensions of crime regimes, visualization methods to help reveal the role of time, summary statistics to quantify crime regime patterns, and permutation procedures to examine the role of chance. Our approach is used to analyze temporal and spatial crime patterns for the City of Los Angeles over an 8 year period. We focus on the number of violent crimes over time and their potential lethality. * Richard Berk's work on this paper was funded by a grant from the National Science Foundation: SES-0437169, "Ensemble methods for Data Analysis in the Behavioral, Social and Economic Sciences." A special thanks goes to Andreas Buja for a number of helpful suggestions on how to analyze the data. We are also indebted to the Los Angles Police Department for providing the data used in this paper. Finally, we benefitted enormously from comments made when an earlier version of this paper was given at the
Health Education & Behavior, 2013
Objective-Develop a conceptual computational agent-based model (ABM) to explore community-wide versus spatially focused crime reporting interventions to reduce community crime perpetrated by youth. Methods-Agents within the model represent individual residents and interact on a twodimensional grid representing an abstract community. Juvenile agents are assigned initial random probabilities of perpetrating a crime and adults are assigned random probabilities of witnessing and reporting crimes. The agents' behavioral probabilities modify depending upon the individual's experience with criminal behavior and punishment, and exposure community crime interventions. Cost-effectiveness analyses assessed the impact of activating different percentages of adults to increase reporting and reduce community crime activity. Community-wide interventions were compared with spatially focused interventions, in which activated adults were focused in areas of highest crime prevalence. Results-The ABM suggests that both community-wide and spatially focused interventions can be effective in reducing overall offenses, but their relative effectiveness may depend on the intensity and cost of the interventions. While spatially focused intervention yielded localized reductions in crimes, such interventions were shown to move crime to nearby communities. Community-wide interventions can achieve larger reductions in overall community crime offenses than spatially focused interventions, as long as sufficient resources are available. Conclusion-The ABM demonstrates that community-wide and spatially focused crime strategies produce unique intervention dynamics influencing juvenile crime behaviors through the decisions and actions of community adults. It shows how such models might be used to investigate community-supported crime intervention programs by integrating community input and expertise
This paper examines what would happen in the New York's criminal justice system if two primary changes were made. Those changes are an exogenous doubling of the number of new criminals entering the system (new people becoming criminals) and a doubling of the productivity of police officers. These inputs were selected because they represent changes on the front or upstream end of the criminal justice system, and the effects of these changes on the whole system could be observed. Changes in police capacity, number of people in prison and the total number of active criminals are examined to understand the implications that technological improvements that increase police productivity may have on other parts of the criminal justice system.
Journal of Experimental Criminology, 2008
This paper argues that simulated experiments of crime prevention interventions are an important class of research methods that compare favorably with empirical experiments. It draws on Popper's demarcation between science and non-science (Conjectures and refutations: the growth of scientific knowledge. Routledge, London, 1992) and Epstein's principle of generative explanation (Generative social science: studies in agent-based computational modeling. Princeton University Press, Princeton, NJ, 2006) to show how simulated experiments can falsify theory. The paper compares simulated and empirical experiments and shows that simulations have strengths that empirical methods lack, but they also have important relative weaknesses. We identify three threats to internal validity and two forms of external validity peculiar to simulated experiments. The paper also looks at the problem of validating simulations with crime data and suggests that simulations need to mimic the error production processes involved in the creation of empirical data. It concludes by listing ways simulations can be used to improve empirical experiments and discussing the differing operating assumption of empirical and simulation experimentalists.
Law and economics scholars have traditionally modeled criminal deterrence as a function two factors: (i) severity of punishment, and (ii) probability of punishment. Gary Becker’s (1968) seminal essay suggested that optimizing on the benefits of crime reduction and the cost of punishment and policing should be the policy objective of the criminal law (at least with respect to deterrence). However, this model has been attacked on two fronts. First, criminological data on crime rates fails to show a strong correlation between the predictions of economic models and crime rates in the real world. Second, developments in behavioral economics suggest that individuals (criminals in this case) often fail to respond rationally to incentives. This paper seeks to reconcile the tension between the results of economic theory, criminological data, and behavioral psychology, offering a more realistic goal for the criminal law: inducing second-order biases not to commit crime.
Mathematical Models and Methods in Applied Sciences, 2010
We extend an agent-based model of crime-pattern formation initiated in Short et al. by incorporating the effects of law enforcement agents. We investigate the effect that these agents have on the spatial distribution and overall level of criminal activity in a simulated urban setting. Our focus is on a two-dimensional lattice model of residential burglaries, where each site (target) is characterized by a dynamic attractiveness to burglary and where criminal and law enforcement agents are represented by random walkers. The dynamics of the criminal agents and the target-attractiveness field are, with certain modifications, as described in Short et al. Here the dynamics of enforcement agents are affected by the attractiveness field via a biasing of the walk, the detailed rules of which define a deployment strategy. We observe that law enforcement agents, if properly deployed, will in fact reduce the total amount of crime, but their relative effectiveness depends on the number of agents...
Foundations and Trends® in Microeconomics, 2006
This paper starts with a review the economics of criminal behavior. Then, the authors discuss the theory of public enforcement. The economic analysis of criminal behavior and criminal law has been a hugely successful enterprise. As an academic enterprise, it has achieved the goal of research-it has generated a large and growing literature. More important than academic success, however, has been the influence of this branch of learning on actual practice. The understanding of deterrence effects and rational responses by criminals has substantially changed the purpose and functioning of the criminal justice system.
Empirical Economics
Despite an abundance of empirical evidence on crime spanning over 40 years, there exists no consensus on the impact of the criminal justice system on crime activity. We construct a new panel data set that contains all relevant variables prescribed by economic theory. Our identification strategy allows for a feedback relationship between crime and deterrence variables, and it controls for omitted variables and measurement error. We deviate from the majority of the literature in that we specify a dynamic model, which captures the essential feature of habit formation and persistence in aggregate behaviour. Our results show that the criminal justice system exerts a large influence on crime activity. Increasing the risk of apprehension and conviction is more influential in reducing crime than raising the expected severity of punishment.
2009
This work develops an agent-based model to study the emergent properties due to public enforcement of criminal law. In order to build a model of criminal behavior suitable to the project the economic analysis of crime is used as the basic framework, most specially Becker's (1968) seminal work, but also Shavell and Polinsky (2000), Shavell (2004), Cohen and Felson (1979) and Clarke (1995). The mainstream has been the economic analysis of law, which considers the agent as a rational decision maker. The model was implemented using NetLogo 3.1.4, a multiagent software platform (Wilensky, 1999). The simulation program provides a wide range of dynamic options making it easy to perform any kind of test in order to assess the behavior of a given criminal rule in its dynamic operation. Validation and experimental tests were performed. The resulting responses were consistent with the theoretical basis on which the model was based on.
Advances in applied sociology, 2024
This paper studies and theorizes the impact of law enforcement in cities on criminal activities. Exploring primarily causing elements, the results from two IV approaches show that increasing police officers per capita in regions does not reduce the corresponding crimes. There are two sets of data used in this research for each IV strategy-the US's city-level and state-level data. Falsification tests are conducted to validate the empirical conclusion. The results show that increasing the number of law enforcements does not lead to a lower crime rate in the US. Based on the results, I propose an alternative theoretical model compared to the conventional framework, in which there is a trade-off between budgeting police forces-leading to lower crimes-and higher unemployment rates-leading to more crimes. This new framework provides more insights on the roots of such societal tragedy and narrows the gap between the theoretical and empirical findings. Thus, an alternative to control crimes could be legalizing and taxing (possible) illicit activities reduces the crimes and provides funds for creating new jobs while alleviating the pressure on the police forces document.
J. Legal Stud., 2001
A higher expected sanction lowers the crime rate. This intuitive cornerstone of deterrence theory has garnered extensive theoretical and empirical research. The present study focuses on the opposite effects-the effects of the crime rate on the expected sanction. It turns out that these effects are versatile and rich in both the direction and the magnitude of their influence on the expected sanction. After analyzing these countereffects of the crime rate on the expected sanction, we present a new model of deterrence that explicitly incorporates the crime rate as one of the determinants of the expected sanction. The adjusted model is then used to study the effects of the crime rate on deterrence and on optimal law enforcement policy.
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