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Cost structures of banks grouped by strategic conduct

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  • Jeffrey Brown
  • Dennis Glennon

Abstract

The hypothesis that the banking system consists of firms that use the same production technology is tested and rejected in this study. Six groupings of the population of commercial banks are identified using cluster analysis. The banks are grouped to reflect similar production technologies within groups but different technologies across groups as defined by the strategic conduct (i.e., activities) of the banks. The results suggest that banks in different clusters employ production processes that feature different degrees of substitutability between factors of production, and that the estimates of input substitutability for those groups look quite different from those estimated based on the full population of commercial banks. The impact of the homogeneity production technology assumption on the measurement of cost efficiency is also assessed. The results show that partitioning the industry by strategic conduct reduces the average inefficiency in the industry. These results support those found by others who used similar partitioning criteria but a more narrowly defined sample of banks.

Suggested Citation

  • Jeffrey Brown & Dennis Glennon, 2000. "Cost structures of banks grouped by strategic conduct," Applied Economics, Taylor & Francis Journals, vol. 32(12), pages 1591-1605.
    • Handle: RePEc:taf:applec:v:32:y:2000:i:12:p:1591-1605
    DOI: 10.1080/000368400418989
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    Cited by:

    1. Stefano Caiazza & Alberto Franco Pozzolo & Giovanni Trovato, 2016. "Bank efficiency measures, M&A decision and heterogeneity," Journal of Productivity Analysis, Springer, vol. 46(1), pages 25-41, August.
    2. Adrian Müller, 2002. "Finding Groups in Large Data Sets," CEPE Working paper series 02-18, CEPE Center for Energy Policy and Economics, ETH Zurich.
    3. Tsekouras, Kostas & Chatzistamoulou, Nikos & Kounetas, Kostas, 2017. "Productive performance, technology heterogeneity and hierarchies: Who to compare with whom," International Journal of Production Economics, Elsevier, vol. 193(C), pages 465-478.
    4. Emili Tortosa-Ausina, 2002. "Cost Efficiency and Product Mix Clusters across the Spanish Banking Industry," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 20(2), pages 163-181, March.
    5. Aysan, Ahmet Faruk & Ertek, Gurdal & Ozturk, Secil, 2009. "Assessing the adverse effects of interbank funds on bank efficiency through using semiparametric and nonparametric methods," MPRA Paper 38113, University Library of Munich, Germany.
    6. Pavlos Almanidis, 2013. "Accounting for heterogeneous technologies in the banking industry: a time-varying stochastic frontier model with threshold effects," Journal of Productivity Analysis, Springer, vol. 39(2), pages 191-205, April.

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