Interbank funding, bank risk exposure and performance in the UK: A three-stage network DEA approach

Lartey, Theophilus; James, Gregory A.; Danso, Albert

doi:10.1016/j.irfa.2021.101753

Cited by 22 publications

(7 citation statements)

References 134 publications

(131 reference statements)

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“…En el primer enfoque, los bancos utilizan mano de obra y capital para proporcionar préstamos y servicios de depósito (Cofré et al, 2019), mientras que en el segundo enfoque los bancos fungen como intermediarios entre prestatarios y prestamistas. Sin embargo, ninguno de los enfoques es perfecto y la selección de entradas y salidas es flexible, ya que, por ejemplo, lo usual es que los depósitos se empleen como entradas (Amin & Ibn-Boamah, 2020;Razipour-GhalehJough et al, 2021) y los préstamos como salidas (Lartey et al, 2021), pero también hay casos en que los depósitos se utilizan como productos (Maudos et al, 2002) o como insumos y productos (Li et al, 2021).…”

Section: Issn Online 2007-9621unclassified

Contribución de las inversiones en recursos humanos según el tipo de eficiencia técnica de la banca múltiple peruana

Flores Gutiérrez,

Castillo Inche,

Tejada Portilla

2023

Acta Universitaria

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Se evaluó la contribución de las inversiones en recursos humanos (RRHH) a la eficiencia técnica de la banca múltiple peruana durante el 2021. Además, se demostró qué tipo de frontera de producción prevalece y se generó un plan benchmarking. A una muestra censal de 16 bancos se les midieron tres inputs (remuneraciones al personal, gastos del directorio y activos) y dos outputs (total de depósitos y total de créditos vigentes). Se identificaron siete bancos en la frontera de eficiencia técnica global (ETG), 12 bancos en la de eficiencia técnica pura (ETP) y siete bancos en la de eficiencia de escala (EE). La media de la ETG fue 0.86, la de ETP fue 0.95 y la de EE fue 0.91. Se determinó que prevalecen los rendimientos variables a escala, que la eficiencia de los bancos no varía con el nivel de inversión en recursos humanos, y se formuló un plan de mejoras potenciales.

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Section: Issn Online 2007-9621unclassified

Contribución de las inversiones en recursos humanos según el tipo de eficiencia técnica de la banca múltiple peruana

Flores Gutiérrez,

Castillo Inche,

Tejada Portilla

2023

Acta Universitaria

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“…In the first approach, banks use labor and capital to provide loans and deposit services, whereas in the second approach, banks serve as intermediaries between borrowers and lenders. However, while neither approach is perfect, the selection of inputs and outputs is nevertheless very flexible, where generally deposits are used as inputs (Amin & Ibn Boamah, 2020 ; Razipour-GhalehJough et al, 2021 ) and loans are used as outputs (Lartey et al, 2021 ), but there are also examples where deposits are used as outputs (Maudos et al, 2002 ) or both inputs and outputs (Li et al, 2021 ).…”

Section: Data and Variable Selectionmentioning

confidence: 99%

Bank efficiency and failure prediction: a nonparametric and dynamic model based on data envelopment analysis

Chen

Tang

2022

Ann Oper Res

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For decades, the prediction of bank failure has been a popular topic in credit risk and banking studies. Statistical and machine learning methods have been working well in predicting the probability of bankruptcy for different time horizons prior to the failure. In recent years, bank efficiency has attracted much interest from academic circles, where low productivity or efficiency in banks has been regarded as a potential reason for failure. It is generally believed that low efficiency implies low-quality management of the organisation, which may lead to bad performance in the competitive financial markets. Previous papers linking efficiency measures calculated by Data Envelopment Analysis (DEA) to bank failure prediction have been limited to cross sectional analyses. A dynamic analysis with the updated samples is therefore recommended for bankruptcy prediction. This paper proposes a nonparametric method, Malmquist DEA with Worst Practice Frontier, to dynamically assess the bankruptcy risk of banks over multiple periods. A total sample of 4426 US banks over a period of 15 years (2002–2016), covering the subprime financial crisis, is used to empirically test the model. A static model is used as the benchmark, and we introduce more extensions for comparisons of predictive performance. Results of the comparisons and robustness tests show that Malmquist DEA is a useful tool not only for estimating productivity growth but also to give early warnings of the potential collapse of banks. The extended DEA models with various reference sets and orientations also show strong predictive power.

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“…, 2017), and very few studies on three-stage network DEA models with shared inputs. However, three stages of economic activity are common in real life, for instance, bank performance management is divided interbank funding, bank risk exposure, and performance in the UK (Lartey et al. , 2021).…”

Section: Introductionmentioning

confidence: 99%

“…Overall, most existing studies on network DEA models with shared inputs are two-stage (Wang et al, 2019;Wu et al, 2017), and very few studies on three-stage network DEA models with shared inputs. However, three stages of economic activity are common in real life, for instance, bank performance management is divided interbank funding, bank risk exposure, and performance in the UK (Lartey et al, 2021). Accordingly, it is necessary to improve the three-stage network DEA using the shared input.…”

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confidence: 99%

Applying an improved three-stage DEA model to evaluate the innovation resource allocation efficiency in industrial enterprises

Zhu

Jie

2022

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PurposeThe existing three-stage network Data Envelopment Analysis (DEA) models with shared input are self-assessment model that are prone to extreme efficiency scores in pursuit of decision-making units (DMUs) efficiency maximization. This study aims to solve the sorting failure problem of the three-stage network DEA model with shared input and applies the proposed model to evaluate innovation resource allocation efficiency of Chinese industrial enterprises.Design/methodology/approachA three-stage network cross-DEA model considering shared input is proposed by incorporating the cross-efficiency model into the three-stage network DEA model. An application of the proposed model in the innovation resource allocation of industrial enterprise is implemented in 30 provinces of China during 2015–2019.FindingsThe efficiency of DMU would be overestimated if the decision-maker preference is overlooked. Moreover, the innovation resource allocation performance of Chinese industrial enterprises had a different spatial distribution, with high in eastern and central China and low in western China. Eastern China was good at knowledge production and technology development but not good at commercial transformation. Northeast China performed well in technology development and commercial conversion but not in knowledge production. The central China did not perform well in terms of technology development.Originality/valueA three-stage network DEA model with shared input is proposed for the first time, which makes up for the problem of sorting failure of the general three-stage network model.

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Interbank funding, bank risk exposure and performance in the UK: A three-stage network DEA approach

Cited by 22 publications

References 134 publications

Contribución de las inversiones en recursos humanos según el tipo de eficiencia técnica de la banca múltiple peruana

Contribución de las inversiones en recursos humanos según el tipo de eficiencia técnica de la banca múltiple peruana

Bank efficiency and failure prediction: a nonparametric and dynamic model based on data envelopment analysis

Applying an improved three-stage DEA model to evaluate the innovation resource allocation efficiency in industrial enterprises

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