ABSTRACT

Criminology has a historic interest in measuring the severity of crimes. While normative rankings of the severity of crime have dominated criminology since the 1960s, a parallel interest in economics has developed crime severity measures on the basis of the costs crimes impose on victims or society. Robust estimates of the severity of crime, measured as the costs of crime to victims, inform a wide range of theory and policy interests. Prior studies of the price of crime, however, have been constrained by limited data that rely on indirect methods to estimate prices. As a result, these studies cannot adjust for sampling bias and do not account for uncertainty. This study demonstrates a more robust approach to estimating the severity of crimes that relies on individual-level data from two sources: jury award and injury data from the RAND Institute of Civil Justice (ICJ) and crime and injury data from the National Incident-Based Reporting System (NIBRS). Propensity score weights are developed to account for heterogeneity in jury awards. Data from the jury awards are interpolated onto the NIBRS data using the 38combination of attributes observable in both data sets. From the combined data, estimates are developed of the price of crime to victims for thirty-one crime categories.