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Determinants of the Locations of Alternative Financial Service Providers

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Many low-to-moderate income US households rely upon alternative financial service providers (AFSPs) for a variety of credit products and transaction services. The social welfare implications of this segment of the financial services industry are quite controversial. One aspect of the controversy involves the location decisions of AFSPs. This study examines the determinants of the locations of three types of AFSPs: payday lenders, pawnshops, and check-cashing outlets. Using county-level data for the entire country, I find that the number of AFSP outlets per capita is significantly related to demographic characteristics of the county population, measures of the population’s creditworthiness, and the stringency of state laws and regulations that govern AFSPs.

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  1. Fellowes and Mabanta (2008) estimated that, in 2007, US households purchased more than $40 billion in high-cost short-term loans at retail locations and cashed about $60 billion in checks at non-bank check-cashing establishments.

  2. See, for example, Melzer (2011) and Morse (2011) for estimates of the consumer welfare effects of access to payday loans.

  3. Pew Charitable Trusts (2013a) finds that in many cases borrowers themselves feel conflicted about payday loans: They appreciate the short-term relief that is provided when they receive the credit, but find it much more difficult and costly than they had expected to pay back the loans. Mann (2013) finds that about 60 % of respondents in a survey of payday loan borrowers (conducted at the time that the loan was issued) accurately predicted how long it would take them completely to repay their payday loan, while about 40 % substantially underestimated the time required to repay their loan. Predictions were deemed “accurate” if the borrower repaid the loan no more than 2 weeks after the predicted date.

  4. Source: EZCORP, Inc. (2007).

  5. Rotella (2003) discusses pawnbroking in ancient times.

  6. The information in this paragraph regarding the history of pawnbroking in the US is derived from Caskey (1994, 2005).

  7. Source: Fellowes and Mabanta (2008).

  8. Source: Cash America International, Inc. (2007).

  9. Much of the information in this paragraph and the next is derived from Caskey (1994, 2005).

  10. Note that throughout this essay the term “check-cashing outlet” is used to refer to establishments whose primary business is providing alternative financial services that include cashing checks for a fee. Other entities, among them banks, grocery stores, and liquor stores, often cash checks for a fee. Those entities are not included in any check-cashing data that are referenced in this paper.

  11. Source: Fellowes and Mabanta (2008).

  12. Source: Advance America, Cash Advance Centers, Inc. (2007).

  13. See Elliehausen (2006).

  14. Industry growth largely ceased in 2007, following legislative and regulatory reforms in a number of states that adversely affected the profitability of the payday lending business.

  15. Source: QC Holdings, Inc. (2006).

  16. Source: Stephens, Inc. (2007).

  17. Hynes (2012) provides a table that indicates which states passed laws that explicitly legalized payday lending during this period. Pew Charitable Trusts (2013b) points to such laws as the primary reason for rapid growth in payday lending during the 1990s.

  18. The Talent-Nelson Amendment limits annual interest rates on loans to military borrowers to 36 %.

  19. Apgar and Herbert (2006, p. II-21).

  20. The 11 states that effectively prohibited payday lending as of the end of 2007 were: Connecticut, Maine, Maryland, Massachusetts, New Jersey, New York, North Carolina, Oregon, Pennsylvania, Vermont, and West Virginia. In 2008, New Hampshire and Ohio passed legislation that effectively prohibited payday lending, as well.

  21. Consumer Financial Protection Bureau (2013, p. 44).

  22. The positive correlation between the number of payday loan stores and the number of bank branches may be partially attributable to the fact that payday loan customers are required to have a checking account.

  23. The seven metropolitan counties are associated with the following cities: Chicago, IL; Atlanta, GA; Houston, TX; Kansas City, MO; Los Angeles, CA; Miami, FL; and Memphis, TN.

  24. Although Fellowes and Mabanta collected more micro-level data, they could only share data that were aggregated to the county level.

  25. From this point forward, the term “bank branch” will include both bank and thrift branches.

  26. An urban county is defined as a county that is part of a metropolitan statistical area (MSA); a rural county is a county that is not part of an MSA.

  27. Consistent with previous studies, I find that the number of bank branches in a county is significantly positively correlated with the numbers of each of the other types of financial service providers in the county; however, when considered on a per capita basis, this is no longer the case.

    Table 1 County-level financial service provider per million population correlations
  28. The demographic data were obtained from the Census Bureau; the creditworthiness measures were constructed from credit score data that were obtained from Equifax; and the information on state laws and regulations was gathered from various state government websites.

  29. Estimation of a full structural model of AFSP locations is possible, but is not undertaken in this paper.

  30. For each type of AFSP, a test was conducted to determine whether the rural and urban counties could be combined into a single equation. In each case, the hypothesis that the coefficients on all of the variables were the same for the two types of counties was rejected.

  31. POVERTY is used as the income measure in order to test the hypothesis that AFSPs tend to locate in communities where a large percentage of the population is poor. It is the income measure that is used in Caskey (1991) and in Shackman and Tenney (2006). Replacing poverty with per capita income in the models does not lead to any substantive changes in the results.

  32. Note that credit score data were not available for some very small counties due to confidentiality considerations. Those counties are excluded from the analysis.

  33. The omitted category is the share of the county population with a credit score in the prime range.

  34. The 25 % rate was chosen as the threshold because, for each type of loan, it appears to be a good approximation for the unconstrained rate. Note, however, that a 25 % interest rate corresponds to a different APR for a 2-week payday loan than for a 1-month pawn loan.

  35. It might be argued that \({ NOPAYDAY}\) could be endogenous in the \({ PAWNSHOP}\) equation. This would be true if state legislators decided to ban payday lending because they thought there were enough pawnshops in their state to meet the borrowing needs of their residents. Such endogeneity would bias the estimated coefficient on \({ NOPAYDAY}\) to be positive. However, the estimated coefficient is either negative or insignificant in the results reported below.

  36. Note that in the payday loan store regressions, counties that are located in states that ban payday lending are excluded from the analysis.

  37. The data do not distinguish between locations that only provide check cashing services and those that provide both check cashing and payday loans.


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I am grateful to Matt Fellowes and Mia Mabanta for providing data on the number of payday loan stores, pawnshops, check-cashing outlets, and credit union branches in each US county; the editor and two anonymous referees for valuable comments and suggestions; and Stefanie Ramirez and Sharada Sridhar for outstanding research assistance

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Correspondence to Robin A. Prager.

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The views expressed in this paper are those of the author and do not necessarily reflect the views of the Board of Governors of the Federal Reserve System or its staff.

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Prager, R.A. Determinants of the Locations of Alternative Financial Service Providers. Rev Ind Organ 45, 21–38 (2014).

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