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Measuring Bank Performance: From Static Black Box to Dynamic Network Models

In: Handbook of Operations Analytics Using Data Envelopment Analysis

Author

Listed:
  • Hirofumi Fukuyama

    (Fukuoka University)

  • William L. Weber

    (Southeast Missouri State University)

Abstract

This chapter presents the recently developed dynamic-network bank technology and performance measures of Fukuyama and Weber (Efficiency and productivity growth: Modelling in the financial services industry. Wiley, London, pp. 193–213, 2013; J Product Anal 44(3):249–264, 2015a; Ann Oper Res, in press, 2015b; Japanese bank productivity, 2007-2012: A dynamic network approach. Mimeo, 2016). The method uses DEA to represent the production technology and directional distance functions to measure bank performance. A two stage bank technology where an intermediate product is produced in a first stage and then used to produce final outputs in a second stage is extended over time. The performance measure allows the researcher to compare observed inputs and outputs, including undesirable outputs, with the outputs and inputs that might be produced if a producer were able to optimally choose production plans relative to a dynamic benchmark technology. Although Fukuyama and Weber’s studies apply the dynamic network technology to measure the performance of Japanese banks, the method can be applied to banks in other countries and to other types of financial institutions.

Suggested Citation

  • Hirofumi Fukuyama & William L. Weber, 2016. "Measuring Bank Performance: From Static Black Box to Dynamic Network Models," International Series in Operations Research & Management Science, in: Shiuh-Nan Hwang & Hsuan-Shih Lee & Joe Zhu (ed.), Handbook of Operations Analytics Using Data Envelopment Analysis, chapter 0, pages 241-266, Springer.
    • Handle: RePEc:spr:isochp:978-1-4899-7705-2_10
    DOI: 10.1007/978-1-4899-7705-2_10
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    Cited by:

    1. Fukuyama, Hirofumi & Matousek, Roman, 2018. "Nerlovian revenue inefficiency in a bank production context: Evidence from Shinkin banks," European Journal of Operational Research, Elsevier, vol. 271(1), pages 317-330.

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