Date of Award


Document Type

Union College Only

Degree Name

Bachelor of Arts



First Advisor

Stephen Schmidt




gambling, casino, crime, demographics, economics


Expanding on economic studies concerning casinos causing an increase in street crime, in this study I look at white-collar crime as a result of the presence and characteristics of different gambling institutions. Therefore, future policy changes regarding constructing casinos could reflect the characteristics of gambling institutions instead of taking a one size fits all approach. In this study I analyze 2,867 counties nationwide to determine if the presence, size, hours of operation and type of casino increase the white-collar crime rate. The regression model mimics that used by Grinols and Mustard (2006). The rate of white-collar crime including larceny, embezzlement, fraud, forgery and counterfeiting is determined by the presence of a casino, economic and demographic variables, and new casino characteristics. The data are gathered from 2007 crime data in the Uniform Crime Report, 2006 economic data from the BEA, 2000 demographic data from the County and City Data Books from University of Virginia Library, and casino data from both and 2009 American Casino Guide. Through regression analysis I find that the presence of certain types of gambling establishments in a county increases the white-collar crime rate in that same county. Since particular types of gambling institutions affect the crime rate more, policies should address type of establishment instead of presence of an establishment. The size of a casino does not affect the white-collar crime rate and the effect of hours of operation is inconclusive.