An economic model of social sensitivity: The case of individual criminal behavior

In general, economists have modeled criminal behavior as a problem in time allocation under uncertainty. Their Friedman-Savage utility models have been based on the binomial probability distribution and then tested using aggregate data on crime rates and neglect the nonpecuniary aspects of crime. This paper overcomes the shortcomings of previous work. Specifically, criminal activity is modeled with an underlying geometric probability process and explicitly accounts for the moral and social compromise involved in becoming a criminal. The empirical model enables the quantification of the criminal's moral and social sensitivity using data based on a consolidated file of police records and a cohort survey of criminals and noncriminals. On the basis of this unique data set, it is found that the included individual criminals are risk averse and that gang membership reduces social sensitivity.     

A local regulator's rewards for conformity in policy

This note is an empirical investigation of the benefits that accrue to local building departments for a regulatory policy that conforms to the relative strength of local interest groups. The study uses an interest group model and applies it to data for building departments in 1100 municipalities. It finds that material benefits in terms of budgets and salaries go to building agencies which set a strictness of regulation that reflects the balance of interest group strengths in the locality.     

The long view

He is the author of many books covering human resource allocation, conditions of health and welfare among the poor, and economic anthropologies of people ranging from blacks in the United States to the coal miners of Wales. He is recognized as a pioneer in the crossover of social problems and economic solutions.     

Police Manipulations of Crime Reporting: Insiders’ Revelations

Social scientists have theorized about the corruption of crime reports (Bayley, 1983; Campbell, 1976). Yet, scant empirical research has examined the impact of modern policing methods on the accuracy of crime reporting. Our research uses an anonymous survey of 1,770 retired New York City police officers examining retirees’ experiences with crime report manipulations across their years of retirement. This includes retirees from the community policing as well as police performance management eras. We subject the data to various statistical tests including tabular analysis, graphical trends to visualize the data, MANOVA, and logistic regression to explain report manipulations. Results indicate that the misuse of the performance management system and pressures on officers from management are key explanations for manipulating crime reports. Individual explanatory variables such as gender, educational status, rank, race, and marital status had no effect. Our research supports Bayley’s and Campbell’s theories. We recommend greater transparency to remedy this.