2020
DOI: 10.1002/ijfe.2185
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Deconstructing three‐stage overall efficiency into input, output and stability efficiency components with consideration of market power and loan loss provision: An application to Chinese banks

Abstract: The current study proposes a new three-stage network data envelopment analysis (DEA) model to estimate three different types of efficiencies. More specifically, the input efficiency is estimated in the first stage, followed by the evaluation of stability efficiency in the second stage, and finally, the output efficiency is derived from the final stage. In particular, we consider market power in deposits and market power in loans in the banking production process. Rather than using non-performing loans as an un… Show more

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Cited by 16 publications
(7 citation statements)
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“…The findings show that the Chinese banking industry experiences stronger volatility in the efficiency scores over the period, while in general there is a consistently increasing trend for the efficiency level up to 2015, after which we can see that the efficiency level declines in 2016, and although a slight increase in the efficiency level in 2017 is observed compared to 2016, the efficiency score experiences another drop in 2018, compared to the previous year, reaching 0.746. Our results are in contrast with results from Fukuyama and Tan (2020). The difference is mainly attributed to the fact that not only do we use a different method in the efficiency analysis, but also the inputs and outputs used in the method are different.…”
Section: Fig 3 Correlogram and Joint Variation Profile Between Efficiency Scores And Contextual Variables In Chinese Bankscontrasting
confidence: 99%
See 1 more Smart Citation
“…The findings show that the Chinese banking industry experiences stronger volatility in the efficiency scores over the period, while in general there is a consistently increasing trend for the efficiency level up to 2015, after which we can see that the efficiency level declines in 2016, and although a slight increase in the efficiency level in 2017 is observed compared to 2016, the efficiency score experiences another drop in 2018, compared to the previous year, reaching 0.746. Our results are in contrast with results from Fukuyama and Tan (2020). The difference is mainly attributed to the fact that not only do we use a different method in the efficiency analysis, but also the inputs and outputs used in the method are different.…”
Section: Fig 3 Correlogram and Joint Variation Profile Between Efficiency Scores And Contextual Variables In Chinese Bankscontrasting
confidence: 99%
“…A new three-stage network DEA model is proposed by Fukuyama and Tan (2020) to evaluate three different types of efficiencies, including input efficiency, stability efficiency and output efficiency. The study considers the role of market power in loans and deposits in the production process and treats loan loss provisions as the good intermediate product in a network model.…”
Section: Literature Reviewmentioning
confidence: 99%
“…New second-stage models were introduced; they are compared and contrasted against simulated data. Fukuyama and Tan, [2022] to estimate three different types of efficiencies, the current study suggests a new three-stage network DEA methodology. In more detail, the first step estimates input efficiency, the second stage evaluates stability efficiency and the last stage calculates output efficiency.…”
Section: Qingmentioning
confidence: 99%
“…Recent applications of a three-stage approach in the banking literature include Zhou et al (2019), who developed a multi-period, multi-stage DEA model to measure bank efficiencies over consecutive periods. Fukuyama and Tan (2020) also used a three-stage model to deconstruct overall bank efficiency into input, output and stability efficiency components with consideration of market power and loan loss provision. This paper, however, contributes to the empirical banking literature by proposing a new threestage network evaluation framework with feedback (Liang et al, 2011) and alliance (Galagedera et al, 2018).…”
Section: Introductionmentioning
confidence: 99%