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Bank Branch Location: a Count Analysis

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  • Charles Okeahalam

Abstract

Abstract This study undertakes an analysis of the association between socio-economic variables and the spatial distribution of bank branches in South Africa. To analyse retail bank branch location, parametric Poisson, negative binomial, Poisson-hurdle, and finite-mixture count models that accommodate unobserved heterogeneity have been estimated with a data set of bank branches in municipalities in South Africa. The key finding is that aggregate income in a municipal area is a statistically significant determinant of the number of bank branches. The results also suggest that the four core banks tend to cluster their branches in the same areas—suggesting the possibility of oligopolistic collusion. A more recent entrant locates its urban branches slightly away from the cluster and in some areas where the core banks have no presence. In addition, several socio-economic variables, some of which are unique to South Africa, do not appear to affect branch location. Situation des filiales de banques: une analyse à comptage RÉSUMÉ La présente étude entreprend une analyse de l'association entre des variables socio-économiques et la répartition de filiales de banques en République Sud Africaine. Pour analyser l'emplacement des filiales du secteur de la banque de détail, on a évalué des modèles de comptage de Poisson, de probabilités binomiales négatives, au taux étalon de Poisson, et aux mélanges finis, qui tiennent compte de l'hétérogénéité non observée au moyen d'un ensemble de données de filiales de banques dans des municipalités en Afrique du Sud. La principale conclusion est que le revenu total dans une zone municipale est un déterminant significatif statistiquement du nombre de filiales de banques. Les résultats semblent également indiquer que les quatre principales banques ont tendance à grouper leurs filiales dans les mêmes régions, ce qui semblerait indiquer la possibilité d'une collusion oligopolistique. Une banque arrivée plus récemment a réparti ses filiales légèrement hors de ce groupement, où les principales banques ne sont pas représentées. En outre, plusieurs variables socio-économiques, certaines desquelles sont particulières à l'Afrique du Sud, ne semblent pas affecter l'emplacement des filiales. Ubicación de sucursales bancarias: un análisis de recuento RÉSUMÉN Este estudio realiza un análisis de la asociación entre las variables socioeconómicas y la distribución espacial de sucursales bancarias en Sudáfrica. Para analizar la ubicación de sucursales de bancos minoristas, se han estimado modelos de recuento como el paramétrico de Poisson, binomial negativo, Poisson-hurdle (modelo en dos partes) y mezcla finita, que conllevan una heterogeneidad inadvertida, con un conjunto de datos de sucursales bancarias de municipalidades de Sudáfrica. El descubrimiento clave consiste en que los ingresos agregados en un área municipal representan un determinante estadísticamente significativo del número de sucursales bancarias. Los resultados también sugieren que los cuatro bancos principales tienden a agrupar sus sucursales en las mismas áreas, indicando la posibilidad de una colusión oligopolística. Un participante más reciente sitúa sus sucursales urbanas algo más alejadas del grupo, y en algunas áreas donde los bancos principales no están presentes. Asimismo, ciertas variables socioeconómicas, algunas de las cuales son exclusivas de Sudáfrica, no parecen afectar a la ubicación de la sucursal.

Suggested Citation

  • Charles Okeahalam, 2009. "Bank Branch Location: a Count Analysis," Spatial Economic Analysis, Taylor & Francis Journals, vol. 4(3), pages 275-300.
  • Handle: RePEc:taf:specan:v:4:y:2009:i:3:p:275-300
    DOI: 10.1080/17421770903114695
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    Cited by:

    1. Luisa Alamá & Emili Tortosa-Ausina, 2012. "Bank Branch Geographic Location Patterns in S pain: Some Implications for Financial Exclusion," Growth and Change, Wiley Blackwell, vol. 43(3), pages 505-543, September.
    2. repec:onb:oenbfi:y:2018:i:q1-18:b:2 is not listed on IDEAS

    More about this item

    Keywords

    Bank branches; count analysis; South Africa; C31; N27; R32;

    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • N27 - Economic History - - Financial Markets and Institutions - - - Africa; Oceania
    • R32 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Other Spatial Production and Pricing Analysis

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