Evaluating the Efficiency of Banking Systems During a Pre-Crisis and Crisis Period by Using Cluster Analysis (2004-2009)

Reverchuk, Serhiy; Lobozynska, Sophia; Megits, Nikolay

doi:10.1177/2158244013504575

Cited by 5 publications

(2 citation statements)

References 2 publications

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“…C. Vu et al, 2018; Zheng et al, 2017). Reverchuk et al (2013) investigate the efficiency of the banking sector in developing countries, before and during the period of the 2007 financial crisis, by employing cluster analysis. However, literature on the role of ownership structure in liquidity management is still disputed and scarce.…”

Section: Literature Reviewmentioning

confidence: 99%

The Role of Regulatory Capital and Ownership Structure in Bank Liquidity Creation: Evidence From Emerging Asian Economies

et al. 2021

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We examine the effect of regulatory capital and ownership structure on banks’ liquidity creation in emerging Asian economies. We find a positive association between regulatory capital and bank liquidity creation, which is consistent with the risk-absorption hypothesis. Bank size has a positive relation with liquidity creation, implying that large banks have more capacity to create liquidity as they enjoy more of the safety net provided by lenders of last resort in the event of crisis, the advantage of reputational benefit, and easier access to external market funding. The negative effect of the bank funding structure is that, as the subordinate debt is typically uninsured, higher funding costs lead banks to reduce liquidity creation. The results imply that an increase in interest rates worsens liquidity creation. For ownership structure, the results show the significance of the impact of ownership concentration on liquidity creation. Banking institutions having higher equity and higher concentration ownership leads to improved liquidity creation.

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Section: Literature Reviewmentioning

confidence: 99%

The Role of Regulatory Capital and Ownership Structure in Bank Liquidity Creation: Evidence From Emerging Asian Economies

et al. 2021

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“…(ii) Cost and profit efficiency by Kamarudin and Yahya (2013), Girardone et al (2009), Al-Delaimi and Batall ( 2006), Ahmad Mokhtar et al (2007), and Fries and Taci (2004). (iii) Bank efficiency and crisis by Ftiti et al (2013), Reverchuk et al (2013), Barra et al (2013), Forughi andZoysa (2012), andSufian (2009). Recently, with the increasing challenges faced by financial institutions, the banking act is being reviewed and redefined.…”

Section: Literature Review 21 Banking Regulation Maqasid Shariah Index and Bank Efficiencymentioning

confidence: 99%

Do Regulation, Maqasid Shariah and Institutional Parameter Improve Islamic Bank Efficiency?

Ibrahim

Ismail

2020

JIMF

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We use a new dataset on Islamic banks to link regulation and bank efficiency. Specifically, we examine how bank efficiency is influenced by: (i) bank regulation, (ii) institutional variables, (iii) economic freedom, and (iv) Shariah law parameters. Our hypothesis attempts to prove that better regulation will produce a higher level ofefficiency. We will also try to prove that the Shariah law parameter will promote better efficiency among Islamic banks. Data Envelopment Analysis (DEA) is used to measure efficiency, while the panel data method is used to analyse the data. Specifically, our results suggest that a significant relationship exists between bank efficiency and greater restrictions on Islamic bank activities. The results also show that regulatory quality hasa positive and significant impact on bank efficiency. The negative coefficient of the economic freedom indicates that Islamic banks have a greater ability to enter into the banking industry and obtain an easy licence, create products and services, and close the business. All would dampen bank efficiency. Overall, our findings support the argument that regulation should be adapted to the risk and size level of the Islamic banks that are being regulated.

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Banks’ business models in the euro area: a cluster analysis in high dimensions

Farné

Vouldis

2021

Ann Oper Res

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In this paper, we investigate the credit risk in the loan portfolio of banks following different business models. We develop a data-driven methodology for identifying the business models of the 365 largest European banks that is suitable for very granular harmonised supervisory data. Our dataset allows us to take into account the full range of the activities in which banks are involved. The proposed method combines in an optimal way data clustering, dimensionality reduction and outlier detection. We identify four business models and exclude as 'outliers' banks that follow idiosyncratic business models. Furthermore, empirical evidence is provided that banks following different business models differ significantly with respect to the credit risk they undertake in their loan portfolios. Traditional commercial banks are characterized by the lowest levels of credit risk while the loan portfolios of securities holding banks are riskier compared to the other banks.

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Evaluating the Efficiency of Banking Systems During a Pre-Crisis and Crisis Period by Using Cluster Analysis (2004-2009)

Cited by 5 publications

References 2 publications

The Role of Regulatory Capital and Ownership Structure in Bank Liquidity Creation: Evidence From Emerging Asian Economies

The Role of Regulatory Capital and Ownership Structure in Bank Liquidity Creation: Evidence From Emerging Asian Economies

Do Regulation, Maqasid Shariah and Institutional Parameter Improve Islamic Bank Efficiency?

Banks’ business models in the euro area: a cluster analysis in high dimensions

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