Stability of a crime level equilibrium

We consider crime level in an economic market with a supply of potential criminals. These criminals differ in their opportunity cost for committing crime, reflecting differences in the value of foregone opportunities such as performing productive labor. The realized demand is influenced by the expected value for crime, which depends on several socio-economic variables including wealth, police enforcement, and police arrest ability. After determining the equilibria level suggested by our approach, we propose a dynamic setup and study the stability of this system. Two critical enforcement levels are determined. Exceeding the lower enforcement threshold will push crime to stabilize (converge) to an equilibrium level. Correspondingly, exceeding the higher enforcement threshold will collapse the crime market to zero.     

The deterrence hypothesis revisited

This study explores the causes of crime and the differences in deterrent effects of policing on crimes among rural, suburban, and urban communities. We hypothesize that certain numbers of all crimes are unaffected by policing due to their high net return; policing deters only marginal crimes. That is, unlike other research efforts, we recognize that there is a level of crime indigenous to a given type of community about which little can be done, although a particular community can affect deviations from this level. By introducing this ‘natural rate' of crime we are able to empirically reveal the deterrence effect of police expenditures upon all types of property crimes except robberies. The study analyzes 230 communities in a system of six simultaneous equations, using police, crime, and other socio-economic variables. The model can be used by state and regional policy-makers to more effectively allocate resources to the different types of communities under their jurisdiction and among the various police functions designed to deter specific types of crime.     

Modelling and predicting recorded property crime trends in England and Wales—a retrospective

In 1999 the Home Office published, for the first time ever, 3-year ahead projections of property crime in England and Wales. The projections covered the period 1999–2001 and indicated strong upward pressure after five full years of falling crime. This pressure was generated by three factors: the number of young men in the general population, the state of the economy and the fact that property crime appeared to be well below its underlying trend level. The projections received a mixed response, with some agreeing that crime was set to rise while questioning the scale of any increase, to others who doubted the value of this type of econometric modelling. In fact, property crime did increase in 1999, although not at the rate suggested by the models—and indeed levels of burglary continued to fall. This paper addresses some of the reasons for this disparity as well as considering various criticisms of the Home Office approach.     

Is there a compensating wage differential for high crime levels? First evidence from Europe

This paper investigates whether high regional crime levels lead to a compensating wage differential paid by firms in the respective region. Using data from German social-security records, official police statistics and official statistics for 2003–2006, I consider both violent and non-violent crimes and use three-way error-components estimators to control for individual and regional heterogeneity. The findings suggest that wages are practically unrelated to changes in crime rates. This result is robust over a wide range of subgroups. There is, however, some evidence that crime rates influence land prices.     

Short-term forecasting of crime

The major question investigated is whether it is possible to accurately forecast selected crimes 1 month ahead in small areas, such as police precincts. In a case study of Pittsburgh, PA, we contrast the forecast accuracy of univariate time series models with naïve methods commonly used by police. A major result, expected for the small-scale data of this problem, is that average crime count by precinct is the major determinant of forecast accuracy. A fixed-effects regression model of absolute percent forecast error shows that such counts need to be on the order of 30 or more to achieve accuracy of 20% absolute forecast error or less. A second major result is that practically any model-based forecasting approach is vastly more accurate than current police practices. Holt exponential smoothing with monthly seasonality estimated using city-wide data is the most accurate forecast model for precinct-level crime series.     

Crime Rates,Clearance Rates and Enforcement Effort: The Case of Houston,Texas*

Abstract . Two time series relationships with respect to police and criminal activities are analyzed. These relationships are: 1. That between police input and police output where the latter was measured by arrest and convictions rates and the former by expenditures and number of officers and, 2. The hypothetical one between the probability of arrest (the clearance ratio; i.e., the proportion of reported crimes for which arrests were made) and crime rates. Theoretically, an increase in expenditures for police effort would cause an increase in the clearance rate and a concomitant reduction in the crime rate. The results of this study showed little or no response in clearance and crime rates to small changes in police expenditures. However, there was evidence that large changes in police effort did produce some response in both clearance and crime rates. The implication of these findings was that the marginal product of police input was small.     

The Effects of Criminal Experience on the Incidence of Crime

A bstract . A hypothesis has been analyzed that criminals learn by doing, that with experience criminals increase their activity so that with level outlays on police the incidence of crime may be increasing. This hypothesis is tested by statistical analysis of time series cross sectional data on crime levels, police outlays and various socioeconomic variables. The results confirm that "learning by doing"—accumulating criminal experience—increases criminal activity, that police outlays have a negative and significant effect on crime and that certain socioeconomic characteristics have a significant effect on crime.     

Optimal expenditures on police protection

The object of this paper is to propose an approach for operationalizing Rubin's (Minimizing Harm: a New Crime Policy for modern America, Westview Press, Boulder, CO, 1999) idea that minimizing harm is a solution to the crime policy conundrum. Harm is defined to be the total cost of damages due to crime plus the cost of police protection. Its minimization determines optimal expenditures for protection. This is an appropriate basis for specifying the optimal size of a police force, and provides a term of reference for actual policy decisions. Data for the states of the US are used to make the presentation more concrete and to clarify some of the problems that must be solved in actual applications of the method suggested. This does not eliminate the applicability of the approach to any other country or to the geo-political subdivisions within a country. The results obtained are of interest to policy makers dealing specifically with expenditures for police at local, regional or national levels or, more generally, with similar uses of public or private financial resources.     

The Difference Between Short and Long Run Effects of Police Outlays on Crime: Policing Deters Criminals Initially, But Later They May 'Learn by Doing'

Abstract . In the long run a positive relationship of police expenditurescrime is derived in models which explain criminal behavior In the short run, however, the statistical results point to the possible deterring effect of police expenditures. A theoretical model is constructed to explain the statistical difference of the short and long run effect of police outlays on crime. As police expenditures increase, crime level diminishes. As time elapses, criminals may adjust to the new level of police effort, improve their performance and at the same level of outlays, increase their criminal activities. This phenomenon could be termed “Criminals’Learning by Doing”. It could explain why, over the long run, the level of crime is positively associated with police expenditures. The empirical analysis examines pooled cross sectional time series of 47 states over the period 1970 to 1980—a total of 517 cases.     

The Economics of the Criminal Behavior of Young Adults

A bstract This study uses a combination of individual-level and county-level data to estimate an economic model of crime for young adults similar to that used by Becker (1968) and Trumbull (1989). In order to estimate a model of crime in which both individual-level and county-level data are used, it is necessary to take account of the bias introduced by using aggregate-level data in conjunction with individual-level data. In order to eliminate this bias, a technique derived by Moulton (1990) is employed. Results from a logit regression model indicate that race, sex. and peer pressure have statistically significant effects on the probability that a young adult will commit a crime. Results also suggest that police presence, as measured by county-level per capita police expenditures, does not deter young adults from committing crimes.     

POLICING FOR THE PEOPLE

Increased spending on law and order over the last decade has not been matched by reductions in crime. The government's claim to have reduced crime does not reflect reality and the public know this. The way to rebuild public confidence and tackle crime is to put more police officers back on the streets. This article argues that in order to do this, four key reforms of the police are needed: a reduction in bureaucracy and central intervention; greater accountability to local communities; more co-operation between forces; and the modernisation of working practices.     

Criminal incident prediction using a point-pattern-based density model

Law enforcement agencies need crime forecasts to support their tactical operations; namely, predicted crime locations for next week based on data from the previous week. Current practice simply assumes that spatial clusters of crimes or “hot spots” observed in the previous week will persist to the next week. This paper introduces a multivariate prediction model for hot spots that relates the features in an area to the predicted occurrence of crimes through the preference structure of criminals. We use a point-pattern-based transition density model for space–time event prediction that relies on criminal preference discovery as observed in the features chosen for past crimes. The resultant model outperforms the current practices, as demonstrated statistically by an application to breaking and entering incidents in Richmond, VA.     

Marked point process hotspot maps for homicide and gun crime prediction in Chicago

Crime hotspot maps are a widely used and successful method of displaying spatial crime patterns and allocating police resources. However, hotspot maps are often created over a single timescale using only one crime type. In the case of short-term hotspot maps that utilize several weeks of crime data, risk estimates suffer from a high variance, especially for low frequency crimes such as homicide. Long-term hotspot maps that utilize several years of data fail to take into account near-repeat effects and emerging hotspot trends. In this paper we show how point process models of crime can be extended to include leading indicator crime types, while capturing both short-term and long-term patterns of risk, through a marked point process approach. Several years of data and many different crime types are systematically combined to yield accurate hotspot maps that can be used for the purpose of predictive policing of gun-related crime. We apply the methodology to a large, open source data set which has been made available to the general public online by the Chicago Police Department.     

Quantification of the task performance of a uniformed police patrol officer: A group process approach

This paper describes the development of a police task performance index (PTPI). This measure, a quantitative indicator of task performance, consists primarily of a ratio of weighted tasks performed to weighted tasks required for a particular situation. Quantification of the index was based on the consensus of an expert panel of police officers. Consensus was obtained through the use of both the Delphi technique and a modified nominal group process.The PTPI was developed for the special case of those police tasks performed by a uniformed patrolman at the scene of a medical emergency. Four categories of medical emergencies were examined—medical emergency only, crime scene with injuries, traffic accident with injuries, and a situation with injuries involving a threat to public safety (e.g. a fire). Application of the index is illustrated in two case examples.     

Lethal Police Response as a Crime Deterrent:

A bstract . Since Gary Becker's article on the economics of crime and punishment , economists have explored extensively the possible deterrence effect of standard enforcement variables , not only for their public policy implications but to test the hypothesis that illegitimate behavior is sensitive to measures of risk and reward (loss) as well as social, psychological and cultural forces. Research has been needed on the probability of death to the offender caused by official police action—"lethal response." To measure the criminal reaction to intercity variations in the rate of civilian killings of police in the line of duty, a cross-sectional study of 57 cities was undertaken. Variations in non-homicide violent crime rate were found to be inversely related to variations in the intercity lethal response rate. this suggests the presence of a deterrence effect, a one Sixth of one percent decrease in the rate of non-homicide violent crime being associated with a one percent increase in the lethal response rate.     

The market for street crime: An economic analysis of victim-offender interaction

This paper views the economic explanation of crime rates from a new perspective by explicitly deriving an economic model of the behavior of potential victims and considering the interaction of the behavior of potential victims with the behavior of offenders. Crime is produced through offenders supplying time in search of victims and victims demanding to expose themselves to the environment. A model is set up in which the crime rate, the probability of being a victim per unit of exposure time, and the probability of finding a victim per unit of offenders' search time are simultaneously determined. The model leads us to distinguish the “real” crime rate (the probability of being a victim per unit of exposure time) from the “nominal” crime rate (the number of crimes per capita). The nominal crime rate can be inversely related to the real crime rate.     

The deterrent impact of police: An examination of a locally provided public service

This paper develops and empirically tests a model of crime deterrence in an urban area. There are two important departures from past efforts to study the impact of criminal sanctions. The first is that the provision of sanctions from the local public sector is modeled; this is accomplished by specifying the distributional goals of local government and by specifying the production of safety. The second departure is that actual crime and reported crime are differentiated theoretically and in the empirical work. An empirical test of the model, using a unique neighborhood data set, shows that police deter crime significantly; however, this deterrent impact cannot be demonstrated without the distinction between actual and reported crime.     

Family attachment and the decision to move by race

Blacks in the United States move less than Whites despite having many characteristics that are commonly associated with high geographical mobility such as high unemployment, low rate of home ownership, low marriage rate and settlement in areas where unemployment is high. We find that this puzzle can be explained by the effects of family ties—both nuclear and extended families—which we proxy using data from the University of Michigan's PSID. The results are robust to different specifications and estimation techniques.     

Applied nonlinear dynamical system in social science. A nonlinear model for social control system: an application to Italian coercion system

Does an increase in police strength discourage an increase in crime levels? It would seem very likely so, despite the many platitudes common everywhere, even in the most serious literature on the subject. This research study, using Non-Linear Analysis on the Italian crime situation from 1985 to 2003, shows an almost non controvertible result. The police force really does seem to have a deterrence function on crime, particularly evident from the 90s on, where, as police strength increases, the number of crimes decrease. One of the most interesting aspects deriving from the non-linear model used, is the specific measurement of the number of crimes that might have been committed and that were not in virtue of the deterrent action of the Police Force. Up to now, such an acquisition seems to be lacking from other so called ‘traditional’ research, where such ‘indirect’ deterrence appears easily hypothesized, but impossible to determine. For this reason too, the adoption of a non-linear analysis logic shows its heuristic superiority able to shed light on certain aspects that in other analysis models would remain in the shadows.