Traffic crashes and crime both impose significant economic and social burdens through injury and loss of life, as well as property damage and loss. Efforts to reduce crashes and crime often result in competing demands on limited public resources. Comparable and up-to-date cost data on crashes and crime contribute to informed decisions about allocation of these resources in important ways. As a first step, cost data provide information about the magnitude of the problems of crashes and crime by allowing us to estimate associated dollar losses to society. More importantly, cost data on crashes and crime are essential to evaluating costs and benefits of various policy alternatives that compete for resources. This paper presents the first comparable comprehensive cost estimates for crashes and crime and applies them to crash and crime incidence data for Michigan to generate dollar losses for the state. An example illustrates how cost estimates can be used to evaluate costs and benefits of crash-reduction and crime-reduction policies in making resource allocation decisions. Traffic crash and selected index crime incidence data from the calendar year 1988 were obtained from the Michigan State Police. Costs for crashes and index crimes were generated and applied to incidence data to estimate dollar losses from crashes and index crimes for the state of Michigan. In 1988, index crimes in Michigan resulted in $0.8 billion in monetary costs and $2.4 billion in total monetary and nonmonetary quality-of-life costs (using the willingness-to-pay approach). Traffic crashes in Michigan resulted in $2.3 billion in monetary costs and $7.1 billion in total monetary and nonmonetary quality-of-life costs, nearly three times the costs of index crimes. Based on dollar losses to the state, the magnitude of the problem of traffic crashes clearly exceeded that of index crimes in Michigan in 1988. From a policy perspective, summing the total dollar losses from crashes or crime is of less importance than understanding the costs and benefits of various policy alternatives. This paper therefore concludes with an example of how our cost estimates can be used to compare the costs and benefits of competing policies.