We develop a stylized dynamic model of highway policing in which a non-racist police officer is given incentives to arrest criminals, but faces a per stop cost of stop which increases when the racial mix of the persons he stops di.ers from the racial mix of the population.We define the fair jail rate to be when the racial composition of the jail population is identical to the racial composition of the criminal population.We study the long-term racial composition of the jail population when the policeman decides whom to stop based only on his last period successes in arresting criminals.The study of this "imperfect recall" case shows, consistent with empirical findings, that the long term racial jail rate is always greater than the fair one and the gap increases when incentives are made more powerful.We then study this rate when policemen are provided with data concerning conviction rates for each race, similar to the data which is now being collected in many states.In this case, we find that although the long term rate is still greater than the fair rate, it is smaller than that obtained in the imperfect recall case.We discuss the desirability of such data collection and dissemination of information among police officers.
|Place of Publication||Tilburg|
|Number of pages||23|
|Publication status||Published - 2003|
|Name||CentER Discussion Paper|
- dynamic models