Modelling bank performance: A network DEA approach

Fukuyama, Hirofumi; Matoušek, Roman

doi:10.1016/j.ejor.2016.10.044

Cited by 191 publications

(109 citation statements)

References 65 publications

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“…We also would like to point out that other DEA methodologies have been used to assess the efficiency of banks; for example, Network DEA (e.g., Matthews 2013; Grigoroudis et al 2013;Akther et al 2013;Fukuyama and Matousek 2017;Gulati and Kumar 2017), Network DEA with undesirable variables (e.g., An et al 2015;Liu et al 2015), Dynamic DEA (e.g., Avkiran and Goto 2011;Fukuyama andWeber 2015, 2017), Dynamic Network DEA (e.g., Avkiran 2015;Chao et al 2015;Fukuyama andWeber 2015, 2017;Zha et al 2016;Wu et al 2016;Fukuyama and Weber 2017b), Fuzzy DEA (e.g., Wang et al 2014;Wanke et al 2016;Hatami-Marbini et al 2017), DEA with Bootstrapping (e.g., Ferrier and Hirschberg 1997), Fuzzy DEA with Bootstrapping (e.g., Wanke et al 2016), and Stochastic DEA (e.g., Kao and Liu 2009). For a recent survey, we refer the reader to Kaffash and Marra (2017).…”

Section: Landscape Of Research On Efficiency Assessment In Bankingmentioning

confidence: 99%

Assessing efficiency profiles of UK commercial banks: a DEA analysis with regression-based feedback

Ouenniche

Carrales

2018

Ann Oper Res

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Data envelopment analysis (DEA) has witnessed increasing popularity in banking studies since 1985. In this paper, we propose a new DEA-based analysis framework with a regression-based feedback mechanism, where regression analysis provides DEA with feedback that informs about the relevance of the inputs and the outputs chosen by the analyst. Unlike previous studies, the DEA models used within the proposed framework could use both inputs and outputs, only inputs, or only outputs. So far, the UK banking sector remains relatively under researched despite its crucial importance to the UK economy. We use the proposed framework to address several research questions related to both the efficiency of the UK commercial banking sector and DEA analyses with and without regression-based feedback. Empirical results suggest that, on average, the commercial banks operating in the UK-whether domestic or foreign-are yet to achieve acceptable levels of overall technical efficiency, pure technical efficiency, and scale efficiency. On the other hand, DEA analyses with and without a linear regression-based feedback mechanism seem to provide consistent findings; however, in general DEA analyses without feedback tend to over-or under-estimate efficiency scores depending on the orientation of the analyses. Furthermore, in general, a linear regression-based feedback mechanism proves effective at improving discrimination in DEA analyses unless the initial choice of inputs and outputs is well informed.Keywords Data envelopment analysis · Efficiency · UK commercial banks · DEA models without explicit inputs · DEA models without explicit outputs

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Section: Landscape Of Research On Efficiency Assessment In Bankingmentioning

confidence: 99%

Assessing efficiency profiles of UK commercial banks: a DEA analysis with regression-based feedback

Ouenniche

Carrales

2018

Ann Oper Res

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“…Epure and Lafuente (2015) propose a bank performance model which separates desirable outputs into those outputs (loans) linked directly to joint undesirable by-products (NPL) and those desirable outputs (securities and service fees) not linked to undesirable outputs. Their model is extended by Fukuyama and Matousek (2015), who estimate a revenue function controlling for NPL incurred by Japanese regional banks. Fukuyama and Weber (2010) propose a two-stage network model for Japanese cooperative Shinkin banks.…”

Section: Bank Production Studies Controlling For Riskmentioning

confidence: 99%

Japanese Bank Productivity, 2007–2012: A Dynamic Network Approach

Fukuyama

Weber

2017

Pacific Economic Review

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We estimate a dynamic network (DN) directional output distance function for 100 Japanese banks operating during 2007–2012. Network production occurs in that deposits and other funds raised are produced as intermediate products in stage 1 and those intermediate products are used to generate a portfolio of assets in stage 2. The dynamic technology links production periods via nonperforming loans (NPL) and carryover assets, which take the form of excess reserves. Carryover assets expand the future production possibility set while NPL shrink future production possibilities. We extend previous DN methods to measure the performance of three types of Japanese commercial banks: city banks, regional banks and second regional banks. We test for and find differences in the three bank technologies relative to a common technology. Such differences are likely due to different institutional and regulatory structures. Unlike previous DN studies, we also allow for a non‐uniform abatement factor between previously‐produced NPL and other inputs in stage 1 and between performing loans and NPL in the current period. Measured productivity change is greater when each bank faces their own group technology rather than the pooled technology consisting of all bank types.

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“…Banker et al [48] then relaxed the constant returns to scale hypothesis and developed a BCC model based on a variable return to scale assumption. The DEA method has been widely used for industrial efficiency analyses in the financial industry [49], the transportation industry [50], the service industry [51], and the manufacturing industry [52]. As environmental issues have become a greater public concern, applications have been developed [10,11] to measure energy and environmental efficiencies.…”

Section: Methodsmentioning

confidence: 99%

Regional Energy, CO2, and Economic and Air Quality Index Performances in China: A Meta-Frontier Approach

Liu

Chiu

2018

Energies

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Abstract:Rapid economic development has resulted in a significant increase in energy consumption and pollution such as carbon dioxide (CO 2 ), particulate matter (PM 2.5 ), particulate matter 10 (PM 10 ), SO 2 , and NO 2 emissions, which can cause cardiovascular and respiratory diseases. Therefore, to ensure a sustainable future, it is essential to improve economic efficiency and reduce emissions. Using a Meta-frontier Non-radial Directional Distance Function model, this study took energy consumption, the labor force, and fixed asset investments as the inputs, Gross domestic product (GDP) as the desirable output, and CO 2 and the Air Quality Index (AQI) scores as the undesirable outputs to assess energy efficiency and air pollutant index efficiency scores in China from 2013-2016 and to identify the areas in which improvements was necessary. It was found that there was a large gap between the western and eastern cities in China. A comparison of the CO 2 and AQI in 31 Chinese cities showed a significant difference in the CO 2 emissions and AQI efficiency scores, with the lower scoring cities being mainly concentrated in China's western region. It was therefore concluded that China needs to pay greater attention to the differences in the economic levels, stages of social development, and energy structures in the western cities when developing appropriately focused improvement plans.

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Modelling bank performance: A network DEA approach

Abstract: The version in the Kent Academic Repository may differ from the final published version. Users are advised to check http://kar.kent.ac.uk for the status of the paper. Users should always cite the published version of record.

Cited by 191 publications

References 65 publications

Assessing efficiency profiles of UK commercial banks: a DEA analysis with regression-based feedback

Assessing efficiency profiles of UK commercial banks: a DEA analysis with regression-based feedback

Japanese Bank Productivity, 2007–2012: A Dynamic Network Approach

Regional Energy, CO2, and Economic and Air Quality Index Performances in China: A Meta-Frontier Approach

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