Building a Data Series on Federal White Collar Offenses: Challenges and Opportunities

• In Event: Linking Administrative Data from the BJS’ Federal Justice Statistics Program

Abstract

The prospect of a national statistical series on white collar violations of federal laws carries immense promise for both research and public policy. It also presents numerous challenges, from the conceptual to the technical. In this paper we first identify the conceptual requirements for such a series and describe solutions for meeting them. Next, we address the practical and technical matters involved in building the series, including identifying administrative sources of relevant violations and enforcement data and determining the prospects and means of obtaining them. The initial stages of series construction also require a sampling scheme for selecting data on types of offenses that adequately represent the domains and lay a solid foundation for future inclusion of additional data. Given broad variation in the types and quality of data available from regulatory, civil and criminal law sources (including the FJSP), technical challenges include devising general coding categories that allow the capture of key offense, offender and sanctions variables and the need to link cases of offending that are processed across the distinct legal fields. We conclude with an assessment of the opportunities for overcoming these various challenges toward building a durable data series on federal white collar offenses.

Authors

• Sally S. Simpson, University of Maryland

• Peter Cleary Yeager, Boston University

• Justin Bernstein, University of Maryland

• Megan Eileen Collins, University of Maryland

• Miranda A. Galvin, University of Maryland, College Park