Trends in Indian Private Sector Bank Efficiency: Non-Stochastic Frontier DEA Window Analysis Approach

Kumar, Ashish; Anand, Nakul; Batra, Vikas

doi:10.13106/jafeb.2020.vol7.n10.729

Cited by 10 publications

(4 citation statements)

References 62 publications

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“…Conversely, the perceived interest rate risks led to holding back loan growth for banks' sensitivity to interest rate changes (Nguyen & Dang, 2020). Kumar et al (2020) tested the efficiency of the Indian private banking sector using the DEA approach from 2005-2017. The results showed that 59.9% of banks operate at more than 0.9 level of proficiency.…”

Section: Literature Reviewmentioning

confidence: 99%

How Banks’ Resources at the Retail Level Affect Their Output?

Alothman¹,

Al-Mahish²

2020

JAFEB

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The study aims to measure the productivity of the Saudi banking sector at the retail level using secondary data for 11 local banks from the period 2015-2019. The study uses an extended version of the Cobb-Douglas production function to account for the fact that as banks openup more retail branches, they will need to employ more labor. The extended Cobb-Douglas production function was estimated using the two-way fixed effect model to account for unobserved heterogeneity across Saudi banks resulting from differences in labor competencies and leadership style. Besides, the model accounts for unobserved heterogeneity among Saudi banks due to the advancement in electronic services over time. The results showed that labor, branches, customers' deposits, and fixed deposits have a positive effect on the total value of generated loans. Conversely, ATM has an insignificant effect on generated loans. The average scale elasticity shows that the Saudi banks at the retail level are operating under decreasing returns to scale. The average marginal rate of technical substitution shows that Saudi banks need at least one ATM to replace one unit of labor at the retail level while keeping the same level of output.

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Section: Literature Reviewmentioning

confidence: 99%

How Banks’ Resources at the Retail Level Affect Their Output?

Alothman¹,

Al-Mahish²

2020

JAFEB

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“…This potential for expansion has amplified competition, and banks are facing hurdles in keeping productive in order to compete. Consequently, academicians, administrators, and regulators have all expressed a strong interest in banking sector productive efficiency studies (Andries, 2011;Sharma et al, 2013;Giolongo and Gomila, 2016;Kumar et al, 2020) and a critical part of management in practice (Wanke et al, 2015). Every decision-making unit (DMU) benefits from implementing productive performance analysis (Hatami-Marbini and Toloo, 2019).…”

Section: Introductionmentioning

confidence: 99%

“…Consequently, academicians, administrators, and regulators have all expressed a strong interest in banking sector productive efficiency studies (Andries, 2011; Sharma et al. , 2013; Giolongo and Gomila, 2016; Kumar et al. , 2020) and a critical part of management in practice (Wanke et al.…”

Section: Introductionmentioning

confidence: 99%

Resource-based productivity in the closed banking sector: the case of Ethiopian banks

Tarekegn

Liu²,

Xiao³

2022

IJPPM

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PurposeThe current paper's goal is to examine the productivity of the closed banking sector evidenced from Ethiopia. In addition, the inclusion of intangibles on productivity was examined in the current paper.Design/methodology/approachFirst, the standard Malmquist Productivity Index (MPI) was employed for 13 commercial banks for both stages. Second, by excluding the state-owned commercial bank, the analysis employed a bootstrapped MPI for the robust and comprehensive conclusion. Furthermore, from 2010 to 2019, the fixed effect Ordinary Least Square (OLS) regression with balanced panel data was used.FindingsThe standard MPI in both stages shows that the productivity of Ethiopian commercial banks is declining. The technological shock was the main reason for the loss. The catch-up in both stages scored above unity, mainly due to the pure efficiency change. Besides, when combined with tangible resources, the inclusion of resource-based view (RBV) proxy variables reduces technological shock regress and ultimately improves productivity change. The bootstrapped MPI also reveals that technological shock is the primary source of the productivity decline. However, efficiency change also contributes to the productivity decline based on this estimation.Research limitations/implicationsFuture research could examine the more extensive productivity analysis by considering the primary sources of data collections for resource-based variables.Practical implicationsAccording to the study's results, banking regulatory authorities and bank management, including the shareholders, should continue to invest in cutting-edge technology to improve the productivity of the banking sector.Originality/valueThis is the first comprehensive study of productivity for Ethiopian commercial banks based on the standard MPI, bootstrapped MPI, and OLS by incorporating all resources into the analysis.

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“…In this situation, very few studies have focused on the bi-directional relationship between risk-taking, capital regulation, and efficiency (Altunbas et al, 2007;Deelchand & Padgett, 2009;Fiordelisi et al, 2011;Tan & Floros, 2013). Besides, there is an increasing number of research interests on capital regulation (Nguyen & Dang, 2020;Zheng et al, 2017), risk-taking (Hossain, Moudud-Ul-Huq, & Kader, 2020;Tran, Do, & Nguyen, 2020), and efficiency (Kumar, Anand, & Batra, 2020;Moudud-Ul-Huq et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

How Do the Banks Determine Regulatory Capital, Risk, and Cost Inefficiency in Bangladesh?

Rahman¹,

Chowdhury²,

Moudud‐Ul‐Huq³

2020

JAFEB

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This study examines simultaneous relationships between regulatory capital, risk, and cost-inefficiency for a sample of 30 commercial banks in Bangladesh from 2006 to 2018. To conduct the analysis, we used the Generalized Methods of Moments (GMM) in an unbalanced panel data framework. The empirical results show that there is a negative and significant relationship between capital regulation and credit, and overall risk. It is also evident from the results that the capital adequacy ratio is positively and significantly related to default risk and liquidity risk. Therefore, higher capitalized banks take an effort to prevent more credit risk and promote financial stability by reducing liquidity risk. Results also report that banks have been characterized as inefficient, less capitalized, and high risk. On the other hand, efficient banks are more stable but have a high level of liquidity risk. Besides, from the size of the bank, large banks are defined as having lower regulatory capital, are more risk seekers but stable with higher cost-efficiency. Notably, higher capitalized banks are more profitable and cost-efficient by reducing risk. Finally, this study also provides some insightful policy suggestions to the stakeholders.

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Trends in Indian Private Sector Bank Efficiency: Non-Stochastic Frontier DEA Window Analysis Approach

Cited by 10 publications

References 62 publications

How Banks’ Resources at the Retail Level Affect Their Output?

How Banks’ Resources at the Retail Level Affect Their Output?

Resource-based productivity in the closed banking sector: the case of Ethiopian banks

How Do the Banks Determine Regulatory Capital, Risk, and Cost Inefficiency in Bangladesh?

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