The technical efficiency of large bank production

Miller, Stephen M.; Noulas, Athanasios G.

doi:10.1016/0378-4266(95)00017-8

Cited by 378 publications

(235 citation statements)

References 15 publications

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“…Berger and Humphrey (1997), Berg et al (1993), Sherman and Gold (1985), Worthington (1998), Athanassoupoulos (1997), English et al (1993), Miller and Noulas (1996), and Wheelock and Wilson (1999). Mixmarket defines it as: "the outstanding principal balance of all of the MFI's outstanding loans including current, delinquent and restructured loans, but not loans that have been written off.…”

Section: Gross Loan Portfolio (Output L)mentioning

confidence: 99%

Social efficiency in microfinance institutions

Nieto

Serrano‐Cinca

Molinero

2009

Journal of the Operational Research Society

222

174

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Microfinance Institutions (MFIs) are a special case in the financial world. They have a double financial and social role and need to be efficient at both. In this paper we try to measure the efficiency of MFIs in relation to financial and social outputs using Data Envelopment Analysis. For the analysis of financial efficiency we rely on existing literature for traditional financial institutions. To this we have added two indicators of social performance: impact on women, and a poverty reach index. A series of hypotheses on MFIs have been entertained, that concern the relationship between social and financial efficiency, and the relationship between efficiency and other indicators, such as profitability. Other aspects studied are the relation between social efficiency and type of institution -Non-Governmental Organisation (NGO), non-NGO-, and the importance of geographical region of activity. The results reveal the importance of social efficiency assessment. JEL Classification: G290

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Section: Gross Loan Portfolio (Output L)mentioning

confidence: 99%

Social efficiency in microfinance institutions

Nieto

Serrano‐Cinca

Molinero

2009

Journal of the Operational Research Society

222

174

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“…2 for a flow chart of a typical two-stage analysis (e.g., Rangan et al 1988;Elyasiani and Mehdian 1990;Aly et al 1990;Favero and Papi 1995;Miller and Noulas 1996;Bhattacharyya et al 1997;Chen 1998;Chu and Lim 1998;Barr et al 1994;Barr and Siems 1997;Pasiouras 2008;Wanke and Barros 2014;Kwon and Lee 2015;Du et al 2018). Note however that the efficiency scores obtained with a two-stage analysis would still be environmentally-biased, because the inputs and outputs used in the first stage are not adjusted for environment.…”

Section: Landscape Of Research On Efficiency Assessment In Bankingmentioning

confidence: 99%

“…With respect to the type of assessment perspective, which drives the choices of inputs and outputs, we classify the literature into six categories; namely, the intermediation approach or perspective (e.g., Rangan et al 1988;Ferrier and Lovell 1990;Charnes et al 1990;Mehdian 1990, 1992;Aly et al 1990;Yue 1992;Grabowski et al 1993;Fukuyama 1993;Zaim 1995;Favero and Papi 1995;Miller and Noulas 1996;Taylor et al 1997;Chen 1998;Drake et al 2006;Liu 2018), the asset approach (e.g., Favero and Papi 1995), the production approach (e.g., Drake et al 2006;Liu and Tone 2008), the value added approach (e.g., Bhattacharyya et al 1997;Pastor et al 1997;Chu and Lim 1998;Pastor 2002;Das and Ghosh 2006), the profit-oriented approach (e.g., Berger and Mester 2003;Drake et al 2006;Liu and Tone 2008), and the user cost approach (e.g., Hancock 1985a, b;Fixler and Zieschang 1992).…”

Section: Landscape Of Research On Efficiency Assessment In Bankingmentioning

confidence: 99%

“…The first category consists of single country focused studies and covers US Banks (Rangan et al 1988;Ferrier and Lovell 1990;Mehdian 1990, 1992;Aly et al 1990;Yue 1992;Miller and Noulas 1996;Kwon and Lee 2015), UK Banks (Drake 2001;Webb 2003;Webb et al 2010;Tanna et al 2011), Italian Banks (Favero and Papi 1995), Turkish Banks (Zaim 1995;Kutlar et al 2017), Japanese Banks (Fukuyama 1993;Liu and Tone 2008), Taiwanese Banks (Chen 1998;Liu 2018), Hong Kong Banks (Drake et al 2006), Singaporean Banks (Chu and Lim 1998), Indian Banks (Bhattacharyya et al 1997), Mozambique Banks (Wanke et al 2016), and Korean Banks (Lee et al 2017). The second category consists of multi-country focused studies and covers banks in several countries such as US, Australian, New Zealand, Austrian, Spanish, German, UK, Italian, Belgian, French, Danish, Luxembourg, Dutch, and Portuguese Banks (e.g., Pastor et al 1997;Pastor 2002;Lozano-Vivas et al 2002;Casu and Molyneux 2003;Pasiouras 2008;Avkiran 2009).…”

Section: Landscape Of Research On Efficiency Assessment In Bankingmentioning

confidence: 99%

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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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“…Despite, the support and promotion of Islamic banking system, their overall performance remains lower in comparison to their counter parts, due to among others: First, the requirement to apply strict sharia rules to develop or modify products and services, an issue raising operational costs; second, their small size in the financial sector (Chapra, 2007). Empirically, size plays a prominent role in bank performance (Miller & Noulas, 1996). Finally, almost all Islamic banks are domestically owned.…”

Section: Problem Statementmentioning

confidence: 99%

Impact of Macroeconomic Factors on Banking Profitabilty

Lutf

Omarkhil²

2018

IFB

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This study comparatively focuses on the impact of macroeconomic determinants and the internal indicators on performance of conventional and Islamic banks in Pakistan. It evaluates the differential effects of macroeconomic variables and bank specific variables with a baseline study of five banks from each system. To determine the short-run and long-run impact of these factors, co-integration & general to specific approach are adopted. This study also considers bank specific and macroeconomic variables in two separate models (Return on Assets and Return on Equity). Our objective is to find the extent to which each system of banking is performing in the country. The results indicate that in the long run, Gross Domestic Product, and inflation, is positively related to performance, while Interest rate has no effect on the performance of banking sector in Pakistan. Similarly, bank size, capital adequacy, expenses, interest income and non-interest income are the bank related factors that significantly influence the performance of financial sector.

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The technical efficiency of large bank production

Cited by 378 publications

References 15 publications

Social efficiency in microfinance institutions

Social efficiency in microfinance institutions

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

Impact of Macroeconomic Factors on Banking Profitabilty

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