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Alternative financial service providers and the spatial void hypothesis

  • Smith, Tony E.
  • Smith, Marvin M.
  • Wackes, John
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    This paper studies the spatial relationship between traditional banking services (Banks) and alternative financial service providers (AFSPs). The main objective is to test the so-called spatial void hypothesis that AFSPs tend to locate in markets where traditional banking services are under-provided. The key question of interest here is whether or not AFSPs serve markets with significantly lower income levels than those of Banks. One of the main contributions of this paper is to develop a statistical methodology for addressing this question that builds on previous studies. The present approach is based largely on K-function analyses of both individual and paired point patterns. These Monte Carlo testing procedures are applied to Banks and AFSPs in the four-county region around Philadelphia, Pennsylvania, and are also compared with previous methods. In contrast to previous work, the key finding of the present research is that there is indeed strong empirical support for the spatial void hypothesis in this Philadelphia region.

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    Article provided by Elsevier in its journal Regional Science and Urban Economics.

    Volume (Year): 38 (2008)
    Issue (Month): 3 (May)
    Pages: 205-227

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    Handle: RePEc:eee:regeco:v:38:y:2008:i:3:p:205-227
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    1. Burkey, Mark L. & Simkins, Scott P., 2004. "Factors affecting the location of payday lending and traditional banking services in North Carolina," MPRA Paper 36043, University Library of Munich, Germany.
    2. Gilles Duranton & Henry Overman, 2002. "Testing for Localisation Using Micro-Geographic Data," CEP Discussion Papers dp0540, Centre for Economic Performance, LSE.
    3. Mark Flannery & Katherine Samolyk, 2005. "Payday lending: do the costs justify the price?," Proceedings 949, Federal Reserve Bank of Chicago.
    4. Kulldorff, Martin, 2006. "Tests of Spatial Randomness Adjusted for an Inhomogeneity: A General Framework," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 1289-1305, September.
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