Assessing the Efficiency of commercial Tunisian Banks using Fuzzy Data Envelopment Analysis

Tlig, Houssine; Hamed, Adel ben

doi:10.5899/2017/dea-00146

Cited by 10 publications

(7 citation statements)

References 40 publications

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“…Size was found to be significant and negatively related to technical efficiency in all bootstrap regressions. Hence, unlike Ayadi (2014) and Chenini and Jarboui (2018) who found that bank size is insignificant in explaining technical efficiency over the period of 2000, and contrary to Ben Romdhane (2013 and Tlig and Hamed (2017), we can conclude that larger banks in terms of total assets are characterized by being less technically efficient. Thus, larger banks in Tunisia are likely more difficult to manage due to the bureaucracy and mismanagement of public banks.…”

Section: Table 5 Comparison Of Average Original and Bias-corrected Technical Efficiency Of Banks By Type Of Ownership Before And After Thcontrasting

confidence: 94%

What explains the technical efficiency of banks in Tunisia? Evidence from a two-stage data envelopment analysis

Jelassi

Delhoumi

2021

Financ Innov

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In this study we examine the potential determinants of technical efficiency for the Tunisian commercial banking sector over the period of 1995–2017. First, we estimate banking technical efficiency with a radial and non-radial bootstrap data envelopment analysis. For the radial technique, we use an input-oriented approach and for non-radial we use the Range Adjusted Measure (RAM). Second, we use a double bootstrapping regression technique to estimate the influence of a set of eventual determinants on technical efficiency. Finally, based on all possible regressions, we gauge the overall effect of each determinant. Our results reveal that the input-oriented and RAM approach gave somewhat similar results. We found that the return on equity, the expense to income ratio, the loan to deposit ratio, and the growth rate are insignificant to Tunisian banking technical efficiency. In particular, banking technical efficiency increases with capitalization and inflation, whereas, it decreases with size, number of bank branches, management to staff ratio, and loan to asset ratio. In addition, we identified evidence supporting the moderate success of the last decade of reforms and a noticeable one for the post-revolution reforms in helping improve banking technical efficiency. The post-revolution reforms, largely revolving around reinforcing the rules of good governance and banking supervision, coupled with the restructuring of public banks, were found to be insufficient to raise overall banking technical efficiency despite improvement in the technical efficiency of private banks.

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Section: Table 5 Comparison Of Average Original and Bias-corrected Technical Efficiency Of Banks By Type Of Ownership Before And After Thcontrasting

confidence: 94%

What explains the technical efficiency of banks in Tunisia? Evidence from a two-stage data envelopment analysis

Jelassi

Delhoumi

2021

Financ Innov

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“…The findings show that the efficiency results of many PuSBs varied with the variation in α during the selected period [18]. Similarly, Tlig and ben Hamed [19] evaluated the efficiency of commercial Tunisian banks in terms of several crisp and imprecise datasets. Fuzzy data envelopment analysis (FDEA), the possibility approach, and an approach based on relations between fuzzy numbers (BRONF) were used to obtain the efficiency score of each bank.…”

Section: Literature Overviewmentioning

confidence: 90%

“…Fuzzy data envelopment analysis (FDEA), the possibility approach, and an approach based on relations between fuzzy numbers (BRONF) were used to obtain the efficiency score of each bank. The results show that, in a competitive environment, non-financial inputs and outputs should be taken into account in order to obtain credible and realistic efficiency scores [19]. Further, fully fuzzy cost-efficiency (FFCE) and fully fuzzy revenue-efficiency (FFRE) models, where input-output data and prices include uncertainty of fuzzy forms, were proposed and compared with existing approaches for proving their effectiveness in real-world situations [20].…”

Section: Literature Overviewmentioning

confidence: 99%

The Efficiency Analysis of Large Banks Using the Bootstrap and Fuzzy DEA: A Case of an Emerging Market

Kedžo

Sjauš

2021

Information

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In this study, banks’ business performance efficiency was analysed using data envelopment analysis (DEA), with expense categories as inputs and income categories as outputs. By incorporating a bootstrap method and a fuzzy data approach into a DEA model, additional insights and sensitivity analysis of the results were obtained. This study shows how fuzzy and bootstrap DEA can be used for investigating real market problems with uncertain data in an uncertain sample. The empirical analysis was based on the period of 2009–2018 for a sample of seven of Croatia’s largest private banks. The aim of the study was also to interpret the DEA results with regards to the specific market, legal, and macroeconomic conditions, caused by the changes introduced in the last decade. The results, and the changes in the inputs and outputs over time, revealed that the market processes occurring in the observed period had a significant impact on banks’ business performance, but led to a more efficient banking system. Two banks were found to be dominant over the others regardless of the changes in the sample and data fuzziness. DEA results were additionally compared to the most important financial indicators and accounting ratios, as an alternative or additional measure of banks’ efficiency and profitability.

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“…6) Tlig and Hamed [25], estimate the efficiency of Tunisian banks by using DEA in the case of imprecise data (fuzzy data).they use fuzzy DEA by using two approaches, possibility and based on relations between fuzzy numbers (BRONF) approach. They evaluate the efficiency score of Tunisian banks for the period 2011-2013 by possibility and BRONF approaches.…”

Section: B Dea Applications Papers In Banking Sector Publish In Yearmentioning

confidence: 99%

Data Envelopment Analysis Recent Applications in Banking Sector: A Survey

Kumari¹

2019

IJRASET

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The present study review and surveys the number of research papers based on the applications of Data Envelopment Analysis (DEA) in the banking sector. This study focus on the development of DEA application only in the banking sector and includes the papers from 2016 to 2019, which published in reputed journals. Data envelopment analysis is one of the most effective and popular methods applied to measuring efficiency of banking sector. The author made a search for DEA application in banking industry related papers in Google Scholar database. The number of papers I get is rather impressive. I select the recent papers on DEA application.

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Assessing the Efficiency of commercial Tunisian Banks using Fuzzy Data Envelopment Analysis

Cited by 10 publications

References 40 publications

What explains the technical efficiency of banks in Tunisia? Evidence from a two-stage data envelopment analysis

What explains the technical efficiency of banks in Tunisia? Evidence from a two-stage data envelopment analysis

The Efficiency Analysis of Large Banks Using the Bootstrap and Fuzzy DEA: A Case of an Emerging Market

Data Envelopment Analysis Recent Applications in Banking Sector: A Survey

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