Bank Failure Prediction Using Dea to Measure Management Quality

Barr, Ronald E.; Siems, Thomas F.

doi:10.1007/978-1-4615-4102-8_15

Cited by 77 publications

(85 citation statements)

References 9 publications

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“…7 Failed banks tend to be more cost inefficient. See Berger and Humphrey (1992), Barr and Siems (1994), Wheelock and Wilson (1995) and Becher, De Young and Lutton (1995). 8 Berger and De Young (1997) call this origin of bad debt "bad luck".…”

Section: The Concepts Of Cost Efficiency and Profit Efficiencymentioning

confidence: 99%

Efficiency, endogenous and exogenous credit risk in the banking systems of the Euro area

Pastor

Serrano

2005

Applied Financial Economics

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The implantation of the Euro in 11 of the EU states has driven the big banks to expand their presence in other European countries, which may have negative consequences on their credit risk in view of the disadvantages involved in entering new markets. The aim of this study is to analyse the efficiency and the credit risk of the banks of the most important countries of the Euro area, using a one-stage parametric stochastic procedure that allows one to identify whether the behaviour towards risk of the banks analysed was more cautious or more reckless during the period analysed. The results indicate that adjustments for risk are important in the case of profit efficiency but not in the case of cost efficiency.

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Section: The Concepts Of Cost Efficiency and Profit Efficiencymentioning

confidence: 99%

Efficiency, endogenous and exogenous credit risk in the banking systems of the Euro area

Pastor

Serrano

2005

Applied Financial Economics

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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%

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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“…In recent years DEA has been applied to a wide spectrum of practical problems. For example, bank failure prediction [11], electric utilities evaluation [12], commercial banks profitability [13], portfolio evaluation [14]. See Gattoufi et al [15,16] for a collection of more DEA applications.…”

Section: Deamentioning

confidence: 99%

Measuring the Performance of Teams in the Indian Premier League

Singh¹

2011

AJOR

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In this paper, using the Data Envelopment Analysis (DEA), we have measured the technical efficiency of cricket teams in the Indian Premier League. Taking the data for the 2009 season, the input used by the teams is approached by the total expenses which include players' wage bill and wage of the support staff and other miscellaneous expenses. Output is measured by the points awarded, net run rate, profit and revenues. Effiiency scores are highly correlated with the performance in the league with a few exception, and when decomposing inefficiency into technical inefficiency and scale inefficiency it can be shown that the largest part of inefficiency can be explained by suboptimal scale of production and ineffficient transformation of inputs into outputs.

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Bank Failure Prediction Using Dea to Measure Management Quality

Cited by 77 publications

References 9 publications

Efficiency, endogenous and exogenous credit risk in the banking systems of the Euro area

Efficiency, endogenous and exogenous credit risk in the banking systems of the Euro area

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

Measuring the Performance of Teams in the Indian Premier League

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