Estimating two-stage network Slacks-based inefficiency: An application to Bangladesh banking

Akther, Syed; Fukuyama, Hirofumi; Weber, William

doi:10.1016/j.omega.2011.02.009

Cited by 157 publications

(83 citation statements)

References 28 publications

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“…Moreover, it is interesting to note that our decomposition method can be extended to Briec's (2000) slack-based directional distance function and Fukuyama and Weber's (2010) and Akther et al's (2013) two-stage network directional distance models. …”

Section: Discussionmentioning

confidence: 99%

Cost decompositions and the efficient subset

Färe

Fukuyama

Grosskopf

et al. 2016

Omega

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This paper develops two cost decompositions based on the multiplicative Russell and additive slack-based (in)efficiency measurement frameworks. While the multiplicative cost decomposition is a straightforward extension of the standard cost decomposition, the decomposition we develop in this paper incorporates slacks directly so that efficiency is measured relative to the efficient subset. To show the applicability of our novel approach, we provide an illustration using a data set used in the literature.

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Section: Discussionmentioning

confidence: 99%

Cost decompositions and the efficient subset

Färe

Fukuyama

Grosskopf

et al. 2016

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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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“…Starting with the work of Fukuyama and Weber (2010), there have been an increasing number of studies in the banking field (Akther et al, 2013;Fukuyama and Matousek, 2011;Lin and Chiu, 2013;Mukherjee et al 2003;Yang and Liu, 2012;Wang et al 2014a,b;Wanke and Barros, 2014;Wu et al, 2016) using the two stage-DEA model. The general concept of two-stage DEA models is based on the pioneering work of Färe and Grosskopf (1996a), who were the first to analyze the sources of efficiency.…”

Section: A Brief Overview Of "Deposit Dilemma" and Dea Two-stage Netwmentioning

confidence: 99%

Investigating bank efficiency in transition economies: A window-based weight assurance region approach

et al. 2017

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This paper examines the efficiency of 116 banks for 9 new EU members in Central and Eastern European (CEE) countries over the period [2004][2005][2006][2007][2008][2009][2010][2011][2012][2013][2014][2015]. We employ the Weight Assurance Region (WAR) and we treat deposits as an intermediate variable in a two-stage data-envelopment analysis model. We then expand the WAR model by including a window-based approach to take into account the patterns of efficiency over time. The results indicate a low level of efficiency over the entire period of analysis, especially for Eastern European and Balkan countries rather than Central European countries. Overall, we find that inefficiency in CEE countries is mainly driven by the profitability stage rather than the value added activity stage.

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Estimating two-stage network Slacks-based inefficiency: An application to Bangladesh banking

Cited by 157 publications

References 28 publications

Cost decompositions and the efficient subset

Cost decompositions and the efficient subset

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

Investigating bank efficiency in transition economies: A window-based weight assurance region approach

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