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.     

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.     

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.     

The Marshallian macroeconomic model: A progress report

In this progress report, we first indicate the origins and early development of the Marshallian macroeconomic model (MMM) and briefly review some of our past empirical forecasting experiments with the model. Then we present recently developed one-sector, two-sector and n-sector models of an economy that can be employed to explain past experience, predict future outcomes and analyze policy problems. The results of simulation experiments with various versions of the model are provided to illustrate some of its dynamic properties that include “chaotic” features. Last, we present comments on planned future work with the model.     

A positional version of Arrow’s theorem

Arrow’s theorem is based on two “vertical” aggregation conditions expressed in terms of the relative positions of two alternatives in a preference ranking. This note obtains the same result for the strict preference case using instead two “horizontal” aggregation conditions expressed in terms of the absolute position of an alternative in a preference ranking.     

Immigration,socio-economic conditions and crime: a cross-sectional versus cross-sectional time-series perspective

This study purpose is to verify if there is an association between foreign immigration and crime. In doing this, the study investigates also some satellite aspects revolving around this possible association: the range of offences affected by immigration, the relationship between immigrant and native crime, and whether the immigration impact on crime is direct or indirect. The present study has addressed these issues by both a cross-sectional and a longitudinal analysis, the latter including an instrument. The study is based on data of the Italian provinces. Italy represents a critical case for studying the migration–crime relationship, because in this country the rise in foreign immigration has been sudden and its pace feverish. The cross-sectional analysis findings show that crime intensities are affected by time-invariant factors and marginally by immigration. On the contrary, the longitudinal analysis shows that variations in immigration had a positive impact on both the most serious and the most common offences, on property crimes as well as on crimes of violence. There is no evidence of indirect effects of immigration on crime or of a link with native crime. In contrast to previous literature regarding the U.S., Canada, and Australia, these results suggest that a spiralling immigration can affect crime. In terms of methods, these findings show that the standard synchronic analysis models can be biased by non-observed factors and that therefore cross-sectional time-series models can offer significant advantages.     

Shaping buyer–supplier relationships in manufacturing contexts: Design and test of a contingency model

Although the idea that buyer–supplier partnerships can yield considerable benefits to firms is largely diffused among researchers and practitioners, the approach adopted in this paper is that no “one best way” exists in buyer–supplier relationships, but rather a “best way” for each specific exchange context. Hence, this paper proposes a contingency model for shaping and managing buyer–supplier relationships in manufacturing contexts. In order to test the model, an empirical study was performed on a sample of 45 buyer–supplier relationships within the Italian white goods industry. A three-dimensional performance indicator was computed to compare supplier performance achieved within relations matching the model's suggestions with those set differently. The results strongly suggest that suppliers involved in relationships set accordingly to the contingency model are likely to enjoy superior performance.     

Crime in urban areas: New evidence and results

Crime supply functions are reestimated in this paper using data corrected for victim underreporting. It is found in both a mean-variance specification and a conventional crime supply function, which includes measures of the offender's gains and losses involved in property crimes, that certainty and severity of punishment still deter. When correction for underreporting is made, the effects on the rates of robbery, burglary, larceny, and auto theft of increases in prison admission rates and prison sentence lengths remain negative. This seeming support for the “deterrence hypothesis” must be balanced against the strong evidence that improved legitimate opportunities have a negative effect on crime. Use of improved crime data and a more intuitive economic specification of the offense supply function leads to the conclusion that higher income is a better deterrent to some crimes than increased punishment.     

Panel data estimates of the effects of different types of crime on housing prices

One of the most studied effects of crime is the impact that neighborhood crime has on housing values. A major drawback of these studies is that, although crime is undoubtedly endogenous in property value models because of either simultaneity, omitted variables or measurement error, the vast majority of studies treat crime measures as exogenous independent variables. We exploit a unique nine-year crime panel at the neighborhood level to estimate models that properly address the endogeneity of crime and allow us to overcome other specification errors that have plagued previous studies. Of the seven different types of crime we investigate, only robbery and aggravated assault crimes (per acre) exert a meaningful influence upon neighborhood housing values.     

Fear of crime and housing prices: Household reactions to sex offender registries

Megan's Law requires public dissemination of information from sex offender registries. Opponents to this controversial law have questioned whether households misinterpret or even use this information. One concern was that the information might simply induce a “fear of crime.” This study finds evidence for both use and misinterpretation of the publicly available information on sex offenders. Using a unique dataset that tracks sex offenders in Hillsborough County, Florida, the results indicate that after a sex offender moves into a neighborhood, nearby housing prices fall by 2.3% ($3500 on average). However, once a sex offender moves out of a neighborhood, housing prices appear to immediately rebound. Surprisingly, these price impacts do not appear to differ in areas near high risk offenders labeled as “predators.”     

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).     

Inequality and Crime: Separating the Effects of Permanent and Transitory Income*

Earlier studies on income inequality and crime have typically used total income or total earnings. However, it is quite likely that it is the changes in permanent rather than in transitory income that affects crime rates. The purpose of this paper is therefore to disentangle the two effects by, first, estimating region‐specific inequality in permanent and transitory income and, second, estimating crime equations with the two separate income components as explanatory variables. The results indicate that it is important to separate the two effects; while an increase in the inequality in permanent income yields a positive and significant effect on total crimes and three different property crimes, an increase in the inequality in transitory income has no significant effect. Using a traditional, aggregate, measure of income yields insignificant effects on crime.     

On the possibility of extinction in a class of Markov processes in economics

We analyze the possibility of eventual extinction of a replenishable economic asset (natural resource or capital) whose stocks follow a stationary Markov process with zero as an absorbing state. In particular, the stochastic process of stocks is determined by a given sequence of i.i.d. random variables with bounded support and a positive-valued transition function that maps the current level of the stock and the current realization of the random variable to the next period’s stock. Such processes arise naturally in stochastic dynamic models of economic growth and exploitation of natural resources. Under a minimal set of assumptions, the paper identifies conditions for almost sure extinction from all initial stocks as well as conditions under which the stocks enter every neighborhood of zero infinitely often almost surely. Our results emphasize the crucial role played by the nature of the transition function under the worst realization of the random shock and clarifies the role of the “average” rate of growth in the context of extinction.     

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.     

Turning from crime: A dynamic perspective

This paper examines criminal choice using a variant of the human capital model. The innovation of our approach is that it attempts to disaggregate individual capital, not unlike production-based studies which disaggregate physical capital into equipment and structures. We disaggregate an individual’s capital stock into the standard human capital component as well as a utility generating component that we call social capital. In our set-up, social capital is used to account for the influence of social norms on the decision to participate in crime. This is done by modeling the stigma of arrest as a reduction in the individual’s social capital stock. We also allow individuals to account for the impact of their criminal actions on their probability of arrest. In order to estimate the structural parameters underlying the model, we make use of computationally intensive methods involving simulated generalized method of moments and value function approximation. The empirical results, based on panel data from the Delinquency in a Birth Cohort II Study, support the social capital model of crime and reveal significant state dependence in the decision to participate in crime.     

Buyer information and the hedonic: The impact of a seller disclosure on the implicit price for airport noise

Revealed preference methods like the hedonic model generally assume economic agents have access to publicly available information and use it effectively. In the housing market, the recent proliferation of seller disclosure laws suggests that policymakers perceive buyers to be less than “fully informed,” presumably since they face higher information acquisition costs than sellers. The introduction of an airport noise disclosure in the residential housing market surrounding the Raleigh–Durham International Airport is used as a quasi-random experiment to analyze the impact of this type of information asymmetry between buyers and sellers on housing prices. The results from a regression analysis that controls for potential spatial and temporal confounders, suggest that the airport noise disclosure reduced the value of houses most heavily impacted by airport noise by 2.9 percent. This represents approximately a 37 percentage point increase in the implicit price of airport noise. The results provide evidence that publicly available information, such as that available for airport noise, may not be adequately considered by all buyers. They also suggest that the information environment should be carefully considered when using housing data and the hedonic model to value urban amenities and disamenities.     

A note on multi-step forecasting with functional coefficient autoregressive models

This paper presents and evaluates alternative methods for multi-step forecasting using univariate and multivariate functional coefficient autoregressive (FCAR) models. The methods include a simple “plug-in” approach, a bootstrap-based approach, and a multi-stage smoothing approach, where the functional coefficients are updated at each step to incorporate information from the time series captured in the previous predictions. The three methods are applied to a series of U.S. GNP and unemployment data to compare performance in practice. We find that the bootstrap-based approach out-performs the other two methods for nonlinear prediction, and that little forecast accuracy is sacrificed using any of the methods if the underlying process is actually linear.     

Some Determinants of Property Crime: Economic Factors Influence Criminal Behavior But Cannot Completely Explain the Syndrome

Abstract . An empirical analysis of the property crimes, robbery, burglary and larceny, is presented for all 120 counties in Kentucky. While this analysis is based on an economic model of crime, certain sociological and legal variables are included as well in the system of equations. Overall, the empirical results support prior studies’findings with the exception that a quadratic relationship is found to exist between urbanization and each of the property crimes. Furthermore, neither the economic nor the non economic influences measured appear more important for affecting crime rates. Specifically, results indicate that the level of poverty, the degree of tourism, the presence of police, the unemployment rate and the apprehension rate all affect property crimes. In contrast, the length of sentence, the degree of industrialization, the level of public assistance payments and the proportion of youth in the county have no affect on property crime rates in these areas.     

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.     

The economic system as an end or as a means, the socialization of consumption, and the future of socialism and capitalism

After the demise of “real” socialism, socialism can be salvaged as a social preference system oriented towards equality and social justice, to be implemented without systemic constraints in the organizational and institutional sense. At the same time there is a case for creating an institutional framework allowing different forms of economic organization, capitalist and non-capitalist, to compete on equal footing, in an evolutionary perspective. Another way for a spontaneous extension of the domain of socialism could derive from the socialization of consumption, if the consumption of public goods continues to make up a growing component of real consumption.