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Financial costs, operating costs, and specialization of Spanish banking firms as distribution dynamics

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  • Emili Tortosa-Ausina

Abstract

There exists a remarkable concern among financial analysts and policy makers about the high level of cost dispersion in banking. A model of distribution dynamics is applied to the Spanish banking companies in order to analyse whether such a dispersion is so high and if some factors like, for instance, specialization factors might somewhat influence the dynamics of both financial and operating expenses. Results show that there does not appear to exist a decrease in the level of cost dispersion, although firms' relative positions are changing. Yet, when controlling for the varying output mixes, firms produce results which differ much, as dispersion - assessed by means of density functions estimated nonparametrically - decreases substantially, suggesting concurrence is higher among firms with similar output mixes.

Suggested Citation

  • Emili Tortosa-Ausina, 2002. "Financial costs, operating costs, and specialization of Spanish banking firms as distribution dynamics," Applied Economics, Taylor & Francis Journals, vol. 34(17), pages 2165-2176.
    • Handle: RePEc:taf:applec:v:34:y:2002:i:17:p:2165-2176
    DOI: 10.1080/00036840210138400
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    Cited by:

    1. Jose Pastor & Lorenzo Serrano, 2006. "The Effect of Specialisation on Banks' Efficiency: An International Comparison," International Review of Applied Economics, Taylor & Francis Journals, vol. 20(1), pages 125-149.
    2. Tortosa-Ausina, Emili & Grifell-Tatje, Emili & Armero, Carmen & Conesa, David, 2008. "Sensitivity analysis of efficiency and Malmquist productivity indices: An application to Spanish savings banks," European Journal of Operational Research, Elsevier, vol. 184(3), pages 1062-1084, February.
    3. Iveta Palečková, 2019. "Cost Efficiency Measurement Using Two-Stage Data Envelopment Analysis in the Czech and Slovak Banking Sectors," Acta Oeconomica, Akadémiai Kiadó, Hungary, vol. 69(3), pages 445-466, September.
    4. Hani Samawi & Haresh Rochani & JingJing Yin & Daniel Linder & Robert Vogel, 2018. "Notes on kernel density based mode estimation using more efficient sampling designs," Computational Statistics, Springer, vol. 33(2), pages 1071-1090, June.

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