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Nerlovian revenue inefficiency in a bank production context: evidence from Shinkin banks

Fukuyama, Hirofumi; Matousek, Roman

Authors

Hirofumi Fukuyama

Roman Matousek



Abstract

The paper further advances the contemporary methodological and empirical research on bank efficiency. We introduce a bank two-stage network revenue decomposition analysis based on the slack-based directional inefficiency measurement framework, by building upon the approaches of Epure and Lafuente (2015), Fukuyama and Weber (2009, 2010), Fukuyama and Matousek (2017) and Färe, Fukuyama, Grosskopf and Zelenyuk (2015, 2016). We apply the model on the segment of Japanese financial institutions – Shinkin banks. We examine the efficiency performance of Shinkin banks during the period from March 2007 to March 2015. This covers the recent years after the turmoil in the US subprime residential mortgage market which started early 2007. The applied innovative framework is particularly suitable for this type of banks since the financing of their business activities is mainly dependent on the different types of deposits that the proposed model takes into consideration.

Citation

Fukuyama, H., & Matousek, R. (2018). Nerlovian revenue inefficiency in a bank production context: evidence from Shinkin banks. European Journal of Operational Research, 271(1), 317-330. https://doi.org/10.1016/j.ejor.2018.05.008

Journal Article Type Article
Acceptance Date Apr 4, 2018
Online Publication Date May 16, 2018
Publication Date Nov 16, 2018
Deposit Date May 8, 2018
Publicly Available Date Mar 29, 2024
Journal European Journal of Operational Research
Print ISSN 0377-2217
Electronic ISSN 1872-6860
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 271
Issue 1
Pages 317-330
DOI https://doi.org/10.1016/j.ejor.2018.05.008
Keywords Data envelopment analysis (DEA); revenue efficiency; directional distance function; slack-based technical inefficiency, banking
Public URL https://nottingham-repository.worktribe.com/output/950833
Publisher URL https://www.sciencedirect.com/science/article/pii/S0377221718303862
Additional Information This is a post-peer-review, pre-copyedit version of an article published in Central European Journal of Operations Research. The final authenticated version is available online at: http://dx.doi.org/10.1016/j.ejor.2018.05.008

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