Lee R. McPheters

Some Law Enforcement Operations Implications of Crime Seasonality

Abstract Criminal justice system policy makers have recently begun to utilize sophisticated techniques of analysis to explore questions of resource allocation and program evaluation.1, 2, 6, 8, 10 All too often, however, the benefits of such techniques have been denied to the large proportion of criminal justice units which lack access to extensive computer facilities and large technical staffs. This paper illustrates how one important crime data time series property—seasonal variation— may be adjusted for and utilized with some fairly simple procedures. The police operations and planning implications of the presence of seasonality in crime data are then examined. The authors develop their discussion with reference to seasonal variation in monthly data on major crimes for a large United States urban area, Miami, Florida. The time period of the study is 1949–1972.

Spectral analysis of reported crime data

This paper applies spectral analysis to data on reported crimes for a medium-sized city. The objective is to examine certain aspects of the statistical properties of crime data, as well as to illustrate the utility of the spectral-analytic method for criminal justice research. A discussion of the theoretical underpinnings of the spectral analysis technique is provided through analogy with familiar least squares regression methods. Both spectral and cross-spectral analysis are then employed to test selected hypotheses concerning the data.

Testing for seasonality in reported crime data

Abstract In spite of the apparent importance of crime statistics to policy-makers and the public, these data are not often analyzed or refined in the same manner as other social series such as unemployment. In this paper, seasonal variation in FBI index crimes is investigated for a major urban area. Using Miami data for 1949–1970, a test for seasonality is developed and seasonal indices are constructed for a number of crime types. A definite seasonal pattern in Miami crime data is found to exist, although its importance seems to be declining in recent years. Some applications of seasonally adjusted data to public information and operations are also briefly discussed.