The Geography of Payday Lending: Living in the Path of a Payday Lender

Payday loans—cash advances secured with the borrower’s next paycheck as collateral—have joined the array of negative aspects of living in disadvantaged communities along with a proliferation of liquor stores and lack of food options. Due to the shortage of cash and assets, coupled with the exorbitant costs of payday loan borrowing (e.g., high annual interest charges and fees), the payday loan industry has been subjected to a number of regulatory efforts. In the absence of federal- and state-level regulation, cities have employed zoning strategies to place limits on the density of stores relative to residential population size in order to regulate the distance (a) between stores and (b) between stores and residential areas. This study aims to address the gap in the payday loan literature by estimating the likelihood that a consumer uses payday loans as a function of distance and density.

Using the distance decay rule and density measures, this study draws on the theory that the intensity of spatial interaction is related to “nearness.” In other words, given equally desirable services, spatial interaction decreases in intensity as distance increases. Likewise, more ubiquitous presence of services will likely encourage payday loan use among customers. Thus, it is hypothesized that increases in distance of payday lenders from the consumers’ residence would be associated with a decreased likelihood of payday loan use, and increases in density of payday lenders would be associated with an increased likelihood of payday loan use.  

This study utilized data collected from 277 Chapter 7 Bankruptcy filers’ who filed for bankruptcy in June 2005 in a southern United States Bankruptcy Court. The bankruptcy filers’ home addresses were furnished in the bankruptcy data and geocoded with a geographic information systems (GIS) program. The distance model utilized a subset of 172 filers with complete point addresses; the density model utilized data from all 277 filers. The dependent variable is payday loan use. The first major independent variable, distance, is operationalized as the Euclidean distance (i.e., straight-line distance) in miles between the consumers’ home addresses and the nearest payday lender; the second major independent variable, density, is operationalized as the number of payday lenders per square mile in the consumers’ home zip-codes. Logistic regression was employed to analyze the relationship between distance and payday loan use in one model and density and the same dependent variable in another model, with both models controlling for the presence of mainstream banks and credit unions in the consumers’ zip codes, community-level poverty rates, unemployment rates, renter-occupied housing rates, population size, and other individual-level characteristics.

Increases in distance of payday lenders from the consumers’ residence were associated with a decreased likelihood of payday loan use (Odds Ratio [OR] = 0.75, p = 0.05). In addition, increases in density of payday lenders within the consumers’ zip codes were associated with an increased likelihood of payday loan use (OR = 1.1e+163, p =0.05). These findings have implications for payday lender zoning laws and the consequent financial wellbeing of cash-strapped, low-income households.