ABSTRACT: The data presented in this study were obtained from a novel approach to estimate a comprehensive loan acquisition cost. The latter includes commute costs and wage losses in addition to the monthly installment payments. These cost estimates represent the monetary value (in U.S. dollars) of the costs of driving to and from the installment lender storefront and that of the potential hourly wage losses, that is, wage loss from the driving time and the time spent at the loan office filling out the required paperwork to obtain the loan. Borrowers only get the net loan proceeds, that is, the original loan amount minus the comprehensive loan acquisition costs. The study area has 160 counties. It was created from the ESRI ArcGIS Map (a mapping software) using the spatial data from the U.S. Census, Topologically Integrated Geographic Encoding and Referencing (TIGER) Cartographic boundary files representing the geographies of states and counties. Using the U.S. road networks, the origin of the trip is a county seat in Arkansas and the destination of the trip is a county seat in a surrounding state of Tennessee, Mississippi, Louisiana, Texas, Oklahoma, and Missouri. The transportation networks were established using Google Earth/Directions to efficiently measure the travel time (distance). The average cost of a trip of 17 cents (U.S. dollar) was calculated based on the U.S. Department of Transportation Survey data, which identify important attributes of a typical vehicle used in a county such as model make, age of the vehicle, fuel consumption, etc. There are 10 occupational industry sectors where a typical borrower has a job. To estimate wage loss, the data were gathered from the U.S. Department of Labor, Bureau of Labor Statistics, namely, the Occupational Employment Statistics. Putting the missing pieces together, the data contain in this study improve our understanding of extra costs borne by borrowers located in the "loan desert" area. As expected, interior counties post high loan acquisition costs compared with border counties. The data from this study are useful to the public, businesses, policymakers, and researchers working on consumer finance.
