Exploiting the coverage of administrative data to understand changing criminal careers and the causes of the crime drop: changing conviction patterns in the Scottish Offenders Index, 1989-2011

• Main Authors: Ben Matthews, Susan McVie, Chris Dibben
• Format: Article
• Language: English
• Published: Swansea University 2018-06-01
• Series: International Journal of Population Data Science
• Online Access: https://ijpds.org/article/view/528

Background The status of the Scottish Offenders Index (SOI) as a census (n=all) of conviction proceedings in Scotland allows the adoption of research designs that would be prohibitively costly and time consuming to implement with more traditional survey approaches. This paper argues that this flexibility, combined with the large time span covered by the SOI (1989-current), provides a way to bridge the typical individual (micro-) focus of developmental criminology and the (macro-) analysis of aggregate crime rates. Objectives By examining conviction patterns for multiple cohorts across multiple years, we can infer whether recent falls in aggregate conviction rates are most plausibly explained by period or cohort effects. In turn, this distinction between period and cohort effects can both suggest which potential explanations for these recent falls in conviction rates in Scotland are most feasible - thus helping to refine explanations for the recent ’crime drop’ - and help us understand the factors leading to change in criminal careers over time. Methods and Findings To support these claims, this paper presents the results of an exploratory analysis of change in convictions patterns in the SOI between 1989 and 2011, drawing on demographic information to account for change in population structure. Results show a complex pattern of change over time, with differences in convictions trends for young and old, for men and women and in different periods. Explanations of the crime drop must be able to account for these complex trends. Conclusions Administrative data provide a unique window into the recent crime drop, and we encourage similar studies on comparable datasets where possible.