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The role of bank affiliation in bank efficiency: a fuzzy multi-objective data envelopment analysis approach

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Abstract

This paper examines differences in bank efficiency between banks affiliated with single-bank holding companies and those affiliated with multi-bank holding companies by applying a fuzzy multi-objective two-stage data envelopment analysis technique. Using a sample of U.S. commercial banks covering 1994–2018, the results show that banks affiliated with multi-bank holding companies are more efficient than those affiliated with single-bank holding companies, suggesting that the former takes advantage of their parents’ resources to enhance their efficiency, consistent with the internal capital market theory. They also show that banks with a powerful CEO exhibit lower efficiency than others. Moreover, there is an inverted U shape relationship between multi-bank holding company structure and bank efficiency, suggesting the presence of an optimal number of multi-bank holding subsidiaries that maximizes efficiency.

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Notes

  1. A diversified bank structure is defined as a bank that owns two or more bank units while focused bank structure is a bank that has only one bank unit.

  2. We define banks at the subsidiary (or affiliate) level as banks that belong to BHCs. A single-BHC has one bank unit while a multi-BHC has two or more bank units. We interchangeably use affiliates, affiliated banks, and subsidiaries throughout our paper. More specifically, banks that belong to a single-BHC are called single-BHC affiliates whereas those belonging to a multi-BHC are considered as multi-BHC affiliates.

  3. Correlation matrix and VIF are available from the authors upon a request. They suggest the absence of multicollinearity as correlation coefficients between control variables and VIFs are low.

  4. In an unreported falsification test, the interaction effect (Treat*Post) is no more statistically significant at conventional levels when we randomly assign treated and non-treated banks, which means that our difference-in-difference results are unlikely to be driven by concurrent unobserved events other than that changing the status from Single-BHC to Multi-BHC.

  5. The number of bank subsidiaries varies in our sample from 2 to 64. The natural logarithm of 20 is almost 3.

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Authors and Affiliations

  1. EM Normandie Business School, Métis Lab, Le Havre, France

    Sabri Boubaker

  2. International School, Vietnam National University, Hanoi, Vietnam

    Sabri Boubaker

  3. School of Management, Swansea University, Swansea, United Kingdom

    Duc Trung Do

  4. Rennes School of Business, Rennes, France

    Helmi Hammami

  5. Nottingham University Business School, University of Nottingham, Nottingham, United Kingdom

    Kim Cuong Ly

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  1. Sabri Boubaker
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  2. Duc Trung Do
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  4. Kim Cuong Ly
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Correspondence to Sabri Boubaker.

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Table 10 List of variables
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Boubaker, S., Do, D.T., Hammami, H. et al. The role of bank affiliation in bank efficiency: a fuzzy multi-objective data envelopment analysis approach. Ann Oper Res 311, 611–639 (2022). https://doi.org/10.1007/s10479-020-03817-z

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