Profiling Crime in Pakistan: An Aggregated and Disaggregated Socioeconomic Analysis

Crime is more than just a sociological and psychological phenomenon. The economic effects of any criminal activity are intriguing and vice versa. This paper attempts to profile crime scenario in Pakistan in the socio-economic context at aggregated and disaggregated level. Three crime supply models have been constructed using formal econometric techniques i.e., aggregated crime, crime against person and crime against property. These models depict the various socioeconomic variables effecting different crimes. The paper also captures the deterrence effect but on a very limited scale using police strength as proxy. The paper has drawn many conclusions indicating effects of social and economic injustices making people choose illegal activities over lawful ways of earnings and the role of government to intervene and promote socio-economic equity. Government should introduce effective social security programs to create more jobs and to minimize income inequalities. Policing and effective justice system is key to control crime.

Race, Politics, and Public Safety: A Panel Study of U.S. Highway Patrol and State Police Strength, 1981-2015

This study assesses the social, political, economic, and traffic-/travel-related predictors of sworn highway patrol and state police strength in the United States between 1981 and 2015. Fixed-effects estimates based on analyses of 1,635 state-years indicate that theoretical accounts centered on racial threat theory, partisan politics, and gendered politics in part explain variation in this outcome. Findings suggest that changes in population density, the tax base, the percentage of the population without a high school degree, violent crime rates, and spending on social welfare at the state level, as well as shifts in local law enforcement strength, also influence state police and patrol organization strength over this period. Surprisingly, fluctuations in the number of state traffic fatalities per million vehicle miles traveled and the number of driver’s licenses per 100,000 state population—two seemingly important traffic-/travel-related factors—have no impact on the rate of state police and patrol officers per 100,000 population.

Police staffing levels: disaggregating the variation

Purpose – The purpose of this paper is to examine the relationship between community type classifications and police strength. Prior research has examined other correlates, but no attempts have been made previously to examine the relationship between community type (as outlined and defined by Chinni and Gimpel, 2010) and police staffing levels. Design/methodology/approach – Using a combination of NDLEA data on police strength, Uniform Crime Report data on crime, census data, and Chinni and Gimpel’s (2010) community classifications, this paper analyzes the relationship between a variety of correlates and police strength in 15,917 communities. Findings – The study found that police staffing does differ by community type as well as by a variety of other key community characteristics. Research limitations/implications – This implies that further research on appropriate tools to determine appropriate staffing levels is needed. Practical implications – This work indicates that traditional “peer benchmarking” approaches used to determine police strength should not be considered the best practice. Other approaches may be more appropriate and should be examined. Originality/value – This is the first study to incorporate classifications of community type in the analysis of police strength.

Economics of Property Crime Rate in Punjab

This study intends to ascertain the impact of socio-economic, demographic and deterrent variables and the effect of technical criminal know-how and past criminal experience on property crime rate. The property crime equation comprises of the following independent variables: population density, unemployment rate, literacy rate, police strength and number of police proclaimed offenders in a society. The property crime equation has been estimated by using a time-series data set for Punjab from 1978 to 2012. We have applied Johansen cointegration approach to test the long run relationship among the variables. Empirical findings suggest that police strength has a deterrent effect while past criminal experience enhances property crime rate in Punjab. The study finds population density has a significant positive relationship while education has a significant negative relationship with property crime rate. Further we also find a negative relationship between unemployment and property crime which is supported by the concept of ‘consensus of doubt’ in the discipline of crime and economics. JEL Classification: D6