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

Fukuyama, Hirofumi; Tan, Yong

doi:10.1002/ijfe.2185

Cited by 17 publications

(7 citation statements)

References 86 publications

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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%

“…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%

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Bank efficiency estimation in China: DEA-RENNA approach

et al. 2021

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The current study proposes a new DEA model to evaluate the efficiency of 39 Chinese commercial banks over the period 2010–2018. The paper also, in the second stage, investigates the inter-relationships between efficiency and some bank-specific variables (i.e. bank profitability, bank size, expenses management, traditional business and non-traditional business) under the Robust Endogenous Neural Network Analysis. The findings suggest that the sample of Chinese banks experiences a consistent increase in the level of bank efficiency up to 2015; the efficiency score is 0.915, after which the efficiency level declines and then experiences a slight volatility, while finally ending up with an efficiency score of 0.746 by the end of 2018. We also find that among different bank ownership types, the state-owned banks have the highest efficiency, the rural commercial banks are found to be least efficient and the foreign banks experience the strongest volatility over the examined period. The second-stage analysis shows that bank size exerts a positive influence on the development of non-traditional banking business and a proactive expense management, bank size and non-traditional businesses have a positive impact on efficiency levels, while bank profitability, traditional businesses and expenses management have negative influences on bank efficiency.

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Section: Fig 3 Correlogram and Joint Variation Profile Between Efficiency Scores And Contextual Variables In Chinese Bankscontrasting

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Bank efficiency estimation in China: DEA-RENNA approach

et al. 2021

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“…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%

The Studies on Efficiency Analysis in Applied Economics Using a Three-Stage Data Envelopment Analysis

2022

Central European Management Journal

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This review work focuses on the utilization of the three-stage DEA model in applied economic research. The review studies were to unearth the tendency of utilization of non-parametric methods, i.e., the three-stage DEA model, in West Africa and some parts of Asia. However, the study revealed that there exists a large body of scholarly works that employ the CCR-Conventional DEA model in their works. Methodologically, extensive google search was the technique used for the literature, and during the process of gathering the literature, studies from Africa were highly minimal, but studies from Asia on a three-stage DEA model were dominant. A broad literature survey for the review revealed that studies on efficiency analysis in applied economic research using frontier methodologies such as a three-stage DEA model were moderately used in empirical studies, particularly in Asia like China. However, the usage of a three-stage data envelopment analysis has a large technical gap. Finally, there is a huge body of research which used traditional DEA that has abandoned the threestage DEA procedures that are limited in use in the African domains. This review work recommends and advocates intensive usage of a three-stage DEA model in efficiency analysis due to its robustness.

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“…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%