A multiple regression model for the measurement of the public policy impact on big city crime

Abstract

By utilizing the multiple regression technique, this paper examines whether various measures of public policies have significant effect in reducing serious crimes and in suppressing the upward trends of crime rates in the 50 largest U.S. cities in recent years. The public policies examined are two conceptually distinct types—control and service policies. The control policies refer to those policies directly concerned with law enforcement and administration of justice, while the service policies are those policies which are designed to promote the general well-being and amenities in the community. The crime indicators used are the so-called “index crime” as reported by the FBI.