Temporal dependence and bank efficiency drivers in OECD: A stochastic DEA-ratio approach based on generalized auto-regressive moving averages

Rojas, Fernando; Tan, Yong; Antunes, Jorge

doi:10.1016/j.eswa.2022.119120

Cited by 14 publications

(5 citation statements)

References 109 publications

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“…At present, there are parameter method and non-parameter method to measure environmental efficiency at home and abroad; the former includes Cobb-Douglas production function regression method, Solow residual method, and random frontier production function method, and the latter mainly includes DEA method. DEA, as a widely adopted and effective method for evaluating the efficiency scores of decision-making units (DMUs), has been extensively utilized across various fields to assess the performance of DMUs with multiple inputs and outputs, such as efficiency evaluation of commercial banks (Wanke et al, 2023), efficiency measurement of high-tech industry (Miriam et al, 2022), and probabilistic linguistic information (Jin et al, 2023). This problem can be solved by game model.…”

Section: Literature Overviewmentioning

confidence: 99%

Measuring of environment efficiency of pharmaceutical companies: Robust game cross‐efficiency data envelope analysis model

Shi,

Qu,

et al. 2024

Manage Decis Econ

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With people's increasing attention to public health issues, biomedical enterprises have ushered in a good development opportunity. However, the rapid expansion of industrial scale makes the contradiction between enterprise development and environmental governance gradually emerge. This requires us to form a set of perfect environmental efficiency evaluation framework to make the evaluation of environmental development efficiency of pharmaceutical companies more objective and accurate. At present, many literatures on environmental efficiency assessment in the fields of green finance ignore the bias in comparison between different companies due to factors such as competition or resource allocation. At the same time, the existing studies lack the influence of disturbance factors on the output of efficiency evaluation data. Based on the sustainable development report of Shanghai Pharmaceutical as the research background, this study establishes an efficiency evaluation framework, which mainly includes three parts: (1) data preprocessing. Establish efficiency evaluation standard framework according to research background, collect relevant data, and process the data. (2) Calculate the game cross‐efficiency DEA model. We calculate the efficiency considering the game situation and compared with the efficiency calculated by the traditional DEA model. (3) Three different scenarios in robust optimization are introduced to reduce the uncertainty in efficiency evaluation. This paper uses the efficiency evaluation framework to evaluate the environmental efficiency of 13 pharmaceutical companies and finally gives policy recommendations.

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Section: Literature Overviewmentioning

confidence: 99%

Measuring of environment efficiency of pharmaceutical companies: Robust game cross‐efficiency data envelope analysis model

Shi,

Qu,

et al. 2024

Manage Decis Econ

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“…Deposits (z 1 ) is selected as the intermediate element, and it is both the input of Stage 1 and the output of Stage 2, which is the most important intermediate variable within the bank [37,38]. Interest income (y 1 ) and non-interest income (y 2 ) are selected as desirable outputs, which represent the returns of commercial banks [1], while non-performing loan balance (b 1 ) is selected as undesirable outputs, which is the key indicator to reflect the risks of commercial banks [25][26][27]. Specifically, x 1 , x 2 , and x 3 are inputs in Stage 1 of the commercial bank to produce z 1 , and then z 1 is regarded as the inputs in Stage 2 of the commercial bank to produce y 1 , y 2 , and b 1 .…”

Section: Case Descriptionmentioning

confidence: 99%

“…Wang et al (2014) claimed that the Chinese commercial banking system has a two-stage internal structure [21]; Azad et al (2021) [22], Tan et al (2021) [23], and Yang et al (2023) [24] all emphasized that it is necessary to consider the internal system structure of banks when evaluating their efficiency; otherwise, the accuracy of commercial bank efficiency evaluation would be affected. Safiullah and Shamsuddin (2022) [25], Shah et al (2022) [26], and Wanke et al (2023) [27] all claimed that nonperforming loans should be considered undesirable outputs in the efficiency evaluation of commercial banking because they represent the risks of commercial banking and hinder its sustainable development. Therefore, considering the internal structure and undesirable outputs are of great significance in the resource allocation of commercial banks based on efficiency evaluation, but they are often overlooked in existing research.…”

Section: Introductionmentioning

confidence: 99%

A New Resource Allocation Multiple Criteria Decision-Making Method in a Two-Stage Inverse Data Envelopment Analysis Framework for the Sustainable Development of Chinese Commercial Banks

Liao,

Chen,

Wang

2024

Sustainability

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The resource allocation of commercial banks is a multiple-criteria decision-making issue with complex internal structure, and traditional inverse data envelopment analysis cannot meet its decision-making needs. A two-stage structure with undesirable outputs is constructed to describe the operations of a Chinese commercial bank, and then a new two-stage inverse data envelopment analysis with undesirable outputs is proposed to address its resource allocation multiple criteria decision-making issue. The new method can be used to calculate the minimum input increment required to achieve the goals of desirable and undesirable output under a certain efficiency, and then a specific resource allocation plan can be obtained to promote the sustainable development of commercial banks. Finally, the new method is applied to the resource allocation of 16 Chinese listed commercial banks in 2013, and the application results fully demonstrate the effectiveness of the new method.

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“…The literature has also examined the socioeconomic factors and their impact on different industries (Wanke et al, 2023b;Antunes et al, 2023aAntunes et al, , 2023bZhao et al, 2022). More specifically, in the banking context, Wanke et al (2023b) investigate the impact of a series of contextual variables, including inflation, human development index, GDP growth, infant mortality, life expectancy, and energy use on bank efficiency through a generalized linear autoregressive moving average model. Compared to other methods, the proposed model is more flexible, easy to estimate and interpret.…”

Section: Literature Reviewmentioning

confidence: 99%

Foreign Direct Investment Performance Drivers at the Country Level: A Robust Compromise Multi-Criteria Decision-Making Approach

Wanke,

Tan,

Antunes

et al. 2024

Technological and Economic Development of Economy

Self Cite

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This paper focuses on the performance drivers of Foreign Direct Investment (FDI) at the country level, exploring the socio-demographic specifics of donor and receiver countries. To this end, a novel Robust Compromise (RoCo) Multi-Criteria Decision-Making (MCDM) model is proposed using non-linear programming solved by genetic algorithms. The model builds upon established traditional models for alternative ranking and criteria weighting. Subsequently, a stochastic robust regression is performed, building upon previously computed bootstrapped Tobit, Simplex, and Beta regressions to handle performance scores ranging between 0 and 1. The goal is to test FDI performance against a set of contextual variables. The findings suggest that the performance of FDI is relatively low, and relevant improvements should be made. Our second stage analysis reports that higher GDP per capita and good social welfare, including lower infant mortality and higher life expectancy, contribute to the improvement in FDI performance. Furthermore, it is found that a large percentage of women in the total population, wealth concentration in the destination country, as well as the degree of urbanization, are helpful to improve FDI performance. Finally, we find that FDI performance is mainly concentrated on industries that are high-tech and high value-added.

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Temporal dependence and bank efficiency drivers in OECD: A stochastic DEA-ratio approach based on generalized auto-regressive moving averages

Cited by 14 publications

References 109 publications

Measuring of environment efficiency of pharmaceutical companies: Robust game cross‐efficiency data envelope analysis model

Measuring of environment efficiency of pharmaceutical companies: Robust game cross‐efficiency data envelope analysis model

A New Resource Allocation Multiple Criteria Decision-Making Method in a Two-Stage Inverse Data Envelopment Analysis Framework for the Sustainable Development of Chinese Commercial Banks

Foreign Direct Investment Performance Drivers at the Country Level: A Robust Compromise Multi-Criteria Decision-Making Approach

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