American Research Journal of Humanities and Social Sciences                cover
Open Access

American Research Journal of Humanities and Social Sciences

ISSN (Online): 2378-7031

DOI: 10.46568/arjhss

Vol. 1, Issue 1 2015 Open Access

Differentiation of the Age-Crime Curve Trajectory by Types of Crime

Roberto Flores De Apodaca1, Abigail M. Csik, Erica K. Odell, Jason R. O’Brien Erin R. Morris, Christopher W. Thorne 

Abstract
The observed relationship between age and criminal behavior in the general population is widely regarded as one of the more venerable findings in the field of criminology (Fagan & Western, 2005; Sweeten, Steinberg & Piquero, 2013). This phenomenon, in which crime rates have been consistently observed to rise through adolescence, peak in the mid to late 20’s and decline steadily with age, has been routinely referred to as the Age-Crime Curve (ACC). While this broad correspondence between age and crime has been widely observed, the particular sub-components and co-variants of this relationship are less well understood and have come under increasing investigation (Pratt & Cullen, 2005). The current study continued in this progression by examining the ACC arrest trajectories of various property versus violent crimes, as well as the relative pattern of specific crimes within those broad, categorical trajectories using state-wide arrest data, over the course of 7 years (2007-2013) compiled by the California State Department of Justice (CSDOJ). Our most fundamental finding was that Property and Violent crimes, in toto, conformed to the classic description of the ACC. Chi-Square analyses showed that Burglary and Robbery showed significantly different trajectories from their Property and Violent counterparts, respectively. Burglary arrests actually go down from the <20 category to the 20-29 age category. Although not as dramatically steep as Burglary, Robbery also showed a decline from the earliest (<20) to the next category (20-39). These findings challenge the invariance hypothesis of the ACC. Future researchers may want to include all forms of arrests in investigating ACC trajectories as well as analyze the data with different categorizations of age, or with no age categorizations at all; examining more nuanced relationships between aging and criminal conduct.