Empirical Properties of Crime Rate Trends

Abstract

This article considers the operation of the time series processes that underlie U.S. crime rate trends. These processes are important because they carry the influence of the variables that generate the rates. They limit the forms that explanations of crime trends can take, and they open avenues for new theoretical development. Using data from the nation and a panel of large cities, analysis finds that crime trends operate much like random walks or their smoothed cousins; that they rarely deviate from a constant pattern; and that they show little evidence of nonlinearity. The article discusses the substantive implications of these features for understanding crime trends, and it considers directions for expanding the study of their empirical properties.