Profiles or subtypes of white-collar offenders in a Spanish sample

• In Event: EUROC 13 White-collar and corporate offender profiles

Abstract

Previous studies have examined the differences between white-collar offenders and other common offenders (Alalehto, 2015; Benson & Kerley, 2002; Holtfreter, 2005; Ribeiro et al., 2019; Stevens et al., 2012) to show empirically that white-collar offenders have a high social and educated profile as first shown by David Sutherland (Sutherland, 1939). White-collar offenders have also been compared with businessmen, particularly in terms of psychological differences (Alalehto, 2003; Blicke et al., 2006; Ragatz, 2012; Walters & Geyer, (2004). Scant attention has been devoted to identifying subtypes of White-collar offenders and their associated characteristics. This holds significant utility in gene rating accurate preventive and intervention strategies, given the broad spectrum of criminal offences included in the term white collar crime, each requiring different expertise, knowledge and occupational positions. Some studies have identified groups regarding prior criminal records (Walters & Geyers, 2004). Longitudinal studies have identified different white-collar criminal trajectories revealing disparities in the duration and frequency of offending (Benson & Kerley, 2001; Onna et al., 2014; Piquero & Weisburd, 2009; Weisburd & Waring, 2001).

The present study endeavors to explore the typologies arising from a sample of persons who are serving a prison sentence for a white-collar offense (n=350). Data were derived from a self-administrated questionnaire collected across 23 Spanish correctional facilities. The offenses perpetrated by the participants predominantly included: fraud (73%), tax evasion (8%), corruption (7%), money laundering and insolvency or bankruptcy (12%). To analyse the structure underlying structural patterns within the dataset and identify different profiles a three-phase analytical approach was adopted: a multiple correspondence analysis, a hierarchical cluster analysis and an inter-cluster comparison utilizing the Chi-square test. Results will be discussed with the existing literature and may have a great impact on elucidating their potential to reduce white-collar crime recidivism.

Authors

• Andrea Gimenez-Salinas, Universidad Pontificia Comillas

• Ana Martinez Catena, University of Barcelona

• Florencia Pozuelo, General Secretariat of Penitentiary Institutions

• Sandra Chiclana de la Fuente, Universidad Nacional de Educación a Distancia (UNED)