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.     

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.     

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 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.     

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.     

Economies of scale and market power in policing

The objective of this paper is to use a simultaneous equations method for estimating police production and demand to determine whether or not there are economies of scale in policing. In addition, the effect of market power on productivity, using the Herfindahl–Hirschmann Index, is to be measured. The estimation yields the result that there are diseconomies of scale with respect to the amount of crime beyond about 22 000 people in the policing jurisdiction and diseconomies of scale in numbers of police beyond about 36 000 people. Efficiency is also reduced where there is greater market power. This is conjectured to be the public sector equivalent of taking market power profits. Copyright © 2005 John Wiley & Sons, Ltd.     

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.     

An analytic approach to the study of gun control policies

This paper explores the theoretic and policy implications of the assumption that the objective of gun ownership is to enhance the security of gun owners and their associates. Security is defined as the probability of not being victimized in a criminal assault and not suffering accidental injury or death in a gun-related incident. An elementary mathematical model is constructed and analyzed. This model and controversial data currently available lead to the conclusion that the percentage of the population owning guns should be larger than now it is. This result does not imply that gun ownership should be made more accessible. Gun ownership may be one possible way to reduce crime. Other ways to achieve this objective are better police control, education, socio-economic justice, etc. The possibility that these alternatives are more effective crime deterrents is not explored in this paper, nor in the studies that provided the data. This evaluation is needed before deciding whether increased gun ownership is the policy that should be adopted in order to reduce crime.     

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.     

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.     

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.     

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.     

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.     

《公安文书写作》教学应重在学生应用能力的培养

公安文书写作是我国公安警察院校课程体系中的一门必修的专业基础课,是保证公安机关"政令畅通"和"警令畅通"的重要工具,具有很强的实用性与实践性的特点,但由于种种因素的制约,其教学效果一直不能适用公安工作的实际需要。因此,有必要对公安公文写作的教学模式进行深入的改革,加强对学生应用能力的培养,真正做到教学服务于公安工作的实际需要。     

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.     

Predicting the geo-temporal variations of crime and disorder

Traditional police boundaries—precincts, patrol districts, etc.—often fail to reflect the true distribution of criminal activity and thus do little to assist in the optimal allocation of police resources. This paper introduces methods for crime incident forecasting by focusing upon geographical areas of concern that transcend traditional policing boundaries. The computerised procedure utilises a geographical crime incidence-scanning algorithm to identify clusters with relatively high levels of crime (hot spots). These clusters provide sufficient data for training artificial neural networks (ANNs) capable of modelling trends within them. The approach to ANN specification and estimation is enhanced by application of a novel and noteworthy approach, the Gamma test (GT).     

Analysis of arrest rates for trends in criminality

During the 1960s, the United States experienced a substantial increase in crime with the rates of reported crime more than doubling. It has been postulated that the increase in the proportion of young adults in the population which also occurred during the Sixties is a primary factor in the increase in crime. In this paper, we attempt to explore this question by partitioning the recent increases in rates between an increasing crime-committing propensity for various demographic groups on one hand, and a changing demographic mix to the other. We do this by analyzing arrest rates by demographic group over time. However, since arrest rates are a complex function of both criminality and police activity, a model is developed which attempts to distinguish between these phenomena. The model is estimated using data on age, race, and sex-specific arrest rates for Pittsburgh residents over the period 1967–1972. The results of the analysis suggest that there has been no significant increase in criminality for men in the Pittsburgh population, while there is some evidence of increased criminality for women. However, this increase may reflect an increased willingness of the police to arrest women. We hesitate to generalize our conclusions too widely from the experience of a single urban center. Additional analysis, using the model developed here, of arrest rates from other cities or regions would do much to illuminate this very significant issue.     

Improving social harm indices with a modulated Hawkes process

Communities are affected adversely by a range of social harm events, such as crime, traffic crashes, medical emergencies, and drug use. The police, fire, health and social service departments are tasked with mitigating such social harm through various types of interventions. While various different social harm indices have been proposed for allocating resources to spatially fixed hotspots, the risk of social harm events is dynamic, and new algorithms and software systems that are capable of quickly identifying risks and triggering appropriate public safety responses are needed. We propose a novel modulated Hawkes process for this purpose that offers flexible approaches to both (i) the incorporation of spatial covariates and leading indicators for variance reduction in the case of rarer event categories, and (ii) the capture of dynamic hotspot formation through self-excitation. We present an efficient l1-penalized EM algorithm for estimating the model that performs feature selection for the spatial covariates of each incident type simultaneously. We provide simulation results using data from the Indianapolis Metropolitan Police Department in order to illustrate the advantages of the modulated Hawkes process model of social harm over various recently introduced social harm indices and property crime Hawkes processes.     

Organized crime and public spending: a panel data analysis

The aim of this paper is to investigate, empirically, what components of public spending imply a decreasing effect on organized crime and what components create opportunities for organized crime, discussing also the role of government efficiency. Using a panel data analysis, the results show a strikingly consistent pattern for the EU Member States. Organized crime mainly operates in the distribution of government spending for local public goods and public provision of private services. There is a decreasing effect on organized crime of the public expenditure devoted to education and social policy. Government efficiency in public spending is beneficial to limit the opportunities of the organized crime.