This thesis analyzes wage theft in Hamilton County, Ohio, through formal complaints to government agencies dedicated to enforcing labor law, including the US Department of Labor and the Ohio Department of Labor Compliance. Wage theft is the violation of labor laws, on the federal, state or local level, designed to protect the wages and earnings of workers. These laws can include minimum wage, overtime, unpaid wage and workers’ compensation laws. The data set that forms the core of the analysis is formed by every state and federal wage complaint, including minimum wage, unpaid wages and overtime, in Hamilton County from 2000-2010. This work is the first large-scale and thorough analysis of wage theft in Hamilton County. The paper examines the distribution of violating firms and workers who have suffered from wage theft. It also develops a novel methodology for aggregating, comparing and analyzing wage theft data at the local/county scale. It analyzes variables that correlate with wage theft on the jurisdictional level throughout the county through regression analysis and identifies hotspots of wage theft through geospatial statistics, including the Gedis Ord statistic.
Findings feature large concentrations of wage theft and victims of wage theft in downtown Cincinnati and the large suburbs along I-75, including Blue Ash, Springdale and Springfield Township. The thesis concludes by making policy recommendations for individual municipalities suffering from wage theft as well as the county as a whole, including an increase in resources for enforcement agencies and a clearinghouse for information on firms that engage in wage theft. The work also provides a framework for municipalities, regional governments and civil groups to collect and analyze their own wage theft rates.