Trends of cost efficiency in response to financial deregulation

Gulati, Rachita

doi:10.1108/bij-06-2013-0065

Cited by 16 publications

(16 citation statements)

References 79 publications

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“…The findings corroborate those by Arora (2014), Maghyereh and Awartani (2014), Alrafadi, Kamaruddin and Yusuf (2014), Othman, et al, (2014), Srairi (2010) and Sufian (2009). However, Gulati (2015) found negative relationship. It reveals that most efficient DTSs were on an average characterized by higher profitability.…”

Section: Regression Resultssupporting

confidence: 91%

Selected Firm Characteristics and Financial Intermediation Efficiency of Deposit Taking Saving and Credit Co-Operative Societies in Kenya

2018

JASETD

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There has been growing concerns over the financial soundness of SACCOs with a few having collapsed in the recent past. Empirical evidence indicates that there exists a strong association between efficiency and stability of financial institutions and that an efficient banking sector is better able to withstand negative shocks in case of financial crises. The study first sought to evaluate the financial intermediation efficiency of deposit taking SACCOs (DTSs) and subsequently determine the relationship between selected firm characteristics and financial intermediation efficiency. Specifically, the relationship between asset quality, income diversification, profitability & size and financial intermediation efficiency was assessed. A balanced panel data for 103 DTSs over the period 2011-2014 was collected and analyzed using a two staged methodology. In the first stage, efficiency scores were generated using data envelopment analysis (DEA). DEA Computer Program Version 2.1 was used to generate the efficiency scores. In the second stage, firm characteristics were regressed on the efficiency scores using fixed effects panel regression model. The bias corrected efficiency score were used instead of conventional DEA scores and incorporated into EViews version 8 for regression analysis. Fixed effect model with robust standard errors was used for analysis. The study revealed that asset quality had a direct relationship with intermediation efficiency. This implies that as the asset quality improves, efficiency of a DTS increases. Diversification was found to be hurting efficiency. More profitable DTSs were found to be more efficient indicating that profitability is efficiency enhancing. The results also revealed a positive relationship between size and efficiency. The study recommends that managers and policy makers should concentrate on how to improve the managerial efficiency and also increase the size of SACCOs. Policy framework should also be directed towards encouraging DTSs to consolidate their operations and limit their diversification into noninterest income.

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Section: Regression Resultssupporting

confidence: 91%

Selected Firm Characteristics and Financial Intermediation Efficiency of Deposit Taking Saving and Credit Co-Operative Societies in Kenya

2018

JASETD

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“…DIVERSE is an index for income diversification of banks and is measured as ratio of non-interest income to total assets. Gulati (2015) finds a significantly and positive impact of diversification on the bank efficiency. PRIORITY is measured by the ratio of priority sector advances (i.e.…”

Section: Bootstrapped Truncated Regression Resultsmentioning

confidence: 94%

Analysing banks’ intermediation and operating efficiencies using the two-stage network DEA model

Gulati

Kumar

2017

IJPPM

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Purpose The purpose of this paper is to present a holistic approach for measuring overall bank efficiency and its decomposition in intermediation and operating efficiencies. Design/methodology/approach Recently developed two-stage network data envelopment analysis model by Liang et al. (2008) has been used for obtaining intermediation and operational efficiencies along with overall bank efficiency. The bootstrapped truncated regression algorithm as proposed by Simar and Wilson (2007) has been employed to explore the influential determinants of intermediation and operating efficiencies. Findings The empirical results reveal that the operating inefficiency is the dominant source of overall bank inefficiency in Indian banking sector. Another interesting finding is that public sector banks are more efficient than private banks in the intermediation stage of production process, while private banks are more efficient in the operating stage of production process. Finally, the results of bootstrapped truncated regression show that variations in intermediation efficiency are explained by bank size, liquidity position, directed lending and intermediation cost, while inter-bank differences in operating efficiency are influenced by profitability and income diversification. Practical implications The most significant practical implication that has been derived from the research findings is that at the industry level, overall efficiency enhancement needs improvement both in terms of resource-utilization and income-generating abilities of the banks. However, the relatively easy way to achieve higher bank efficiency is to improve the efficiency of banks in generating incomes from interest and fee-based sources. Originality/value This paper is the first to provide a comprehensive assessment of performance of Indian banks by examining the efficiency of individual banks considering both the intermediation and operating approaches simultaneously.

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“…4.4.2 Inputs-outputs selection. The most important and difficult task in the DEA procedure is to select the relevant inputs and outputs (Athanassopoulos, 1997;Sathye, 2003;Kumar and Gulati, 2014;Gulati, 2015;Arora et al, 2018). The MFIs' empirical literature follows mainly two approaches: first, the production approach (see Benston, 1965) and second, intermediation approach (see Sealey and Lindley, 1997) as adopted from bank efficiency literature.…”

Section: Bootstrap Truncated Regressionmentioning

confidence: 99%

“…Further, the MFIs are considered to be mainly credit providers and not the deposit takers, so production approach is also not feasible to be adopted for all MFIs (Kumar and Sensarma, 2017). Therefore, neither of two approaches is perfect to adopt in case of bank industry (Berger and Humphrey, 1997;Kumar and Gulati, 2014;Gulati, 2015) or in the microfinance industry (Guti errez-Nieto et al, 2009;Kumar and Sensarma, 2017;Fall et al, 2018). Therefore, based on our specific objectives and the existing microfinance literature, the study opts for three different inputs: (1) total assets, (2) operating expenses and (3) interest expense on borrowings.…”

Section: Bootstrap Truncated Regressionmentioning

confidence: 99%

Drivers of financial and operational efficiency of MFIs: empirical evidences from Eastern Europe and Central Asia

Khan

Shireen²

2020

BIJ

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PurposeThe study attempts to examine the bias-adjusted financial and operational efficiency estimates of microfinance institutions (MFIs) operating in the Eastern Europe and Central Asia (ECA) region during the financial year 2017–2018. In addition, the study also identifies the responsible factors determining the financial and operational performances of MFIs operating in the ECA region.Design/methodology/approachThe study employs two-stage bootstrap data envelopment analysis (DEA). In the first stage, the authors incorporate the bootstrap procedure in the DEA framework as suggested by Simar and Wilson (2000) to estimate the bias-corrected efficiency scores of 67 sample MFIs. In order to identify the drivers of efficiency level, the study deploys the bootstrap truncated regression model following the Simar and Wilson (2007) guidelines in the second stage of analysis.FindingsThe authors note from the empirical results that MFIs operating in the ECA region are relatively more financially efficient (0.588) than socially efficient (0.496). However, none of the MFIs were found to be operating at best-practice frontier while considering the bias-adjusted efficiency estimates. Further, the results of second stage of analysis confirm that corporate governance, that is, board size has positive and statistically significant impact on MFIs’ performances. In addition, the bad credit quality deteriorates both financial revenue and operational efficiency. Moreover, the MFIs’ size, profit status and debt-to-equity ratio were also found to be statistically significant to determine the operational and financial efficiency of MFIs in the ECA region.Practical implicationsThe study provides the robust efficiency estimates and factors responsible to determine the financial and operational efficiency of MFIs operating in the ECA region. Further, the empirical results of the study provide the inputs and further direction to the policymakers, regulators, practitioners and managers in framing the policy and optimal operating strategies for ECA MFIs industry.Originality/valueThe study extends the DEA analysis by incorporating the bootstrap procedure in DEA model to estimate the bias-adjusted efficiency scores which are more reliable and robust. In addition, bootstrap truncated regression has been applied to identify the drivers of efficiency. Moreover, in the literature there is no single study which has deployed the double bootstrap DEA framework to examine the financial and operational efficiency estimates and its drivers.

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Trends of cost efficiency in response to financial deregulation

Cited by 16 publications

References 79 publications

Selected Firm Characteristics and Financial Intermediation Efficiency of Deposit Taking Saving and Credit Co-Operative Societies in Kenya

Selected Firm Characteristics and Financial Intermediation Efficiency of Deposit Taking Saving and Credit Co-Operative Societies in Kenya

Analysing banks’ intermediation and operating efficiencies using the two-stage network DEA model

Drivers of financial and operational efficiency of MFIs: empirical evidences from Eastern Europe and Central Asia

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