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The purpose of this paper is to present a holistic approach for measuring overall bank efficiency and its decomposition in intermediation and operating efficiencies.

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.

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.

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.

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.

By incorporating the role of nonperforming loans (NPLs), the study aims to assess the impact of global financial crisis (GFC) on the intermediation efficiency of Indian banks for the period of 1998/99 to 2016/17.

To obtain efficiency level of Indian banks, this study applied sequential data envelopment analysis (DEA) based directional distance function (DDF) approach, which performed simultaneous expansion of desirable output and reduction of undesirable output in the bank's loan production structure. Additionally, using fixed effect regression approach in the panel data framework, this study assesses both the phenomenon of σ- and unconditional β-efficiency convergence in public sector banks (PSBs), private banks (PBs), foreign banks (FBs) and overall scheduled commercial banks (SCBs) during the pre-crisis, crisis and post-crisis years in India.

Irrespective of the bank's production model, the evidence suggests that the accounting NPLs as an undesirable output significantly deteriorating the intermediation technical efficiency levels of Indian banks, especially after the crisis years until the last year of the study period. This reflects that Indian banks failed more to achieve their financial intermediation objective in the post-crisis years as compared to the crisis and pre-crisis years. In-depth, statistical evidence of commercial bank ownership groups reveals that public sector banks exhibit a higher level of efficiency in pursuance of traditional loan-based activity followed by private and foreign banks. The study also found the existence of sigma convergence in technical efficiency levels of Indian banks and ownership groups as well.

This study is perhaps the first one, which present the robust evolution of Indian banks intermediation efficiency by taking into account both endogenous (i.e. NPLs as an undesirable output and equity as a quasi-fixed input in the bank production process) crisis and exogenous (i.e. global financial and economic stress) crises. Moreover, none of the existing studies have conducted sub-period wise analysis to show the apparent occurrence of both convergence properties in technical efficiency, adding novelty in the literature.

The main objective of this paper is to present a holistic approach for measuring overall bank efficiency and its decomposition in intermediation and profitability efficiencies.

Two-stage network data envelopment analysis (NDEA) model has been used for obtaining intermediation and profitability efficiencies along with overall bank efficiency. Additionally, bootstrap truncated regression has also been adopted to explore the influential predictors of two stages.

A comparative analysis between Indian private-sector and public-sector banks showed that the former is efficient than the latter in profitability efficiency stage. Another interesting finding is that none of the banks is efficient in overall study tenure. Finally, outcomes of bootstrap truncated regression show that differences in intermediation efficiency are explained by firm size, return on asset, market share and ownership while profitability stage is determined by diverse, gross domestic product and ownership.

This study will guide the Indian banking sector to act on which they are lagging, for the betterment of their overall performances. Finally, parameters like loan waives and disposal income of non-performing assets (NPAs) are not considered because of the unavailability of information in the output measures of NDEA model.

This paper not only provides a detailed performance assessment of Indian banks but also examines banks’ internal efficiency by deposits as an intermediary measure.

Asymmetric information impedes the efficiency of financial intermediation by widening the gap between lending and deposit rates. The cost of information gathering is high and often translates into high borrowing costs. Consequently, high borrowing costs may make it hard for borrowers to repay loans and increase the volume of non-performing loans – a recipe for financial instability. This study first compares the application of the simple GARCH (1,1) and BGARCH (1,1,1) models in the estimation of macroeconomic volatility and finds that the latter is more suitable for this purpose. Moreover, the choice of BGARCH (1,1,1) over the simple GARCH (1,1) implies different outcomes for Granger causality tests. This finding implies that the BGARCH (1,1,1) model minimises loss of important information when estimating macroeconomic volatility in developing countries. Second, the study uses bootstrap panel Granger causality to test the hypothesis that there is a causal relationship between financial instability and the financial intermediation spread in Southern African Customs Union (SACU). The findings support this hypothesis and underscore the importance of implementing sound macroeconomic policies for high and stable growth as well as effective monetary policy to attain and maintain low and stable prices in order to narrow the financial intermediation spread in SACU. The paper aims to discuss these issues.

This study uses bootstrap panel Granger causality to test the hypothesis that there is a causal relationship between financial instability and the financial intermediation spread in SACU.

The findings support this hypothesis and underscore the importance of implementing sound macroeconomic policies for high and stable growth as well as effective monetary policy to attain and maintain low and stable prices in order to narrow the financial intermediation spread in SACU.

Application of panel bootstrap Granger causality test to test for a casual relationship between financial intermediation spread and financial stability in the context of SACU.

The purpose of this paper is to examine the dynamics between income diversification and performance (cost, profit, revenue, technical, pure technical and scale efficiency) for 38 listed Indian banks within panel data framework during the period 2004-2005 to 2015-16.

This study computes bank’s cost, profit, revenue, technical, pure technical and scale efficiency within intermediation approach with data envelopment analysis (DEA) as a performance indicator, followed by exploring the association between income diversification and bank performance using truncated Tobit regression within panel data framework.

Tobit regression results revealed inverted U-shaped relationship between the income diversification and estimated efficiency parameters for the overall panel. Size and bank intermediation ratio seems to be a major factor in exploiting the potential benefits of income diversification. The author reconfirmed the inverted U-shaped relationship with these efficiency parameters for exclusive subsamples consisting of government-owned and private sector banks.

Inverted U-shaped relationship between the income diversification and estimated efficiency parameters suggest that banks should go for limited diversification to improve performance. Thus, regulators and banks should pursue limited diversification strategy for improving banking efficiency.

This study computes bank performance (cost, profit, revenue, technical, pure technical and scale efficiency) based on DEA followed by exploring the association between performance and income diversification for 38 Bombay stock exchange listed banks.

The purpose of this paper is to empirically assess the efficiency (transaction efficiency, intermediation efficiency and profit efficiency) of the retail branches of a large bank and identify the driver parameters of the same.

The authors use the non-parametric data envelopment analysis approach to analyze the financial performance of 247 branches in 2014, spread over 14 states of a country. After checking for possible misspecification bias, the authors use the fractional regression approach in the second stage of the analysis to assess possible drivers of the efficiency of bank branches in terms of the size of business, funding mix, per employee contribution to business and profit and business per transaction. In addition, the authors included spatial parameters like economic condition and competitive position of branches in their analysis.

The authors find that on an overall basis, there might be a deliberate initiative of the top management of the bank to over-branch in order to improve the output at the aggregate level which is above the level of cost minimization. The study clearly indicates to the top management that low-cost deposit is a significant driver of branch efficiency apart from business per transaction, income per employee. Moreover, it is found that branches located in areas of high branch concentration are more efficient, and local economic condition does drive efficiency of branches.

The authors address the dilemma faced by the top management of banks in arriving at an appropriate scientific benchmark to assess the performance of branches based on the drivers of efficiency and initiate suitable strategic interventions to improve their efficiency.

The integrated assessment of the efficiency of bank branches and arriving at the drivers of efficiency using the fractional regression model framework are likely to prove beneficial in the benchmarking exercise of the performance of bank branches.

This study aims to investigate the relative efficiency pattern of Jordanian banks during the period between 1998 and 2004.

The deterministic data envelopment analysis (DEA) as a quantitative approach was used to obtain the efficiency of individual commercial banks in Jordan.

The results of the DEA Charnes, Cooper and Rhodes model show an increase in bank efficiency in the entire period except in 2003 and 2004 where a decrease in bank efficiency was shown for few banks in the sample. The total efficiency scores suggest that the liberalisation programme has provided the anticipated efficiency gains. Most efficiency scores showed consistent increases after the introduction of the policy with the exception of few banks which have responded differently and shown decreased in efficiency. This may be taken to imply that the banks have responded differently to the new system. The analysis further shows that both assets utilisation and the labour factor had an adverse effect on bank efficiency, especially in terms of number of employees.

The effect of the Jordanian Government liberalisation programme may not be readily discerned in such a relatively short period of time, which may require that a longer time period elapses before this effect becomes noticeable.

The paper analyses the performance of Jordanian banks with regard to their efficiency.

A major lesson of the European Monetary Union (EMU) crisis is that serious disequilibria result from regional monetary arrangements not designed to be robust to a variety of shocks. The purpose of this paper is to assess these disequilibria within the Economic and Monetary Community of Central Africa (CEMAC), West African Economic and Monetary Union (UEMOA) and Financial Community of Africa (CFA) zones.

In the assessments, monetary policy targets inflation and financial dynamics of depth, efficiency, activity and size while real sector policy targets economic performance in terms of GDP growth. The author also provides the speed of convergence and time required to achieve a 100 percent convergence.

But for financial intermediary size within the CFA zone, findings, for the most part, support only unconditional convergence. There is no form of convergence within the CEMAC zone.

The broad insignificance of conditional convergence results has substantial policy implications. Monetary and real policies, which are often homogenous for member states, are thwarted by heterogeneous structural and institutional characteristics, which give rise to different levels and patterns of financial intermediary development. Therefore, member states should work towards harmonizing cross‐country differences in structural and institutional characteristics that hamper the effectiveness of monetary policies.

The paper provides warning signs to the CFA zone in the heat of the Euro zone crises.

This paper aims to investigate the influence of the central bank’s regulatory capital on commercial banks specific performance outcomes such as credit supply, interest rate spread (as a measure of efficiency) and non-performing loans (NPLs).

Using specific commercial bank-level panel data from 2002-2012, a system of equations was modeled that allows us to apply the system generalized methods of moment approach and estimate the equations, while controlling for specific bank level, industry and macroeconomic variables.

The study finds a positive relationship between a net minimum capital ratio and the net interest margin. Although this is in contrast with the study expectations, the result suggests that a high net minimum capital requirement would widen the spread between the lending and saving rates. The study further finds evidence to support the fact that high minimum capital requirement and excess capital above the minimum required drive credit growth in the banking sector of Ghana. However, high excess capital increases risk-taking activities of the banks, as excess capital is found to be associated with high NPL ratios.

Given the economic benefits and costs of sharply increasing bank regulatory capital, our results speak to the ongoing debates on the right level of capital, the effectiveness of the Bank of Ghana policy rate (PR) and the high lending rates that appear to respond only slowly to macroeconomic indicators such as the PR and the inflation rate. The finding also has practical implications for the adoption of the Basel III accord.

The empirical literature has not paid enough attention to the impact of regulatory capital on the three specific bank-level outcomes – NPLs, interest rate spread and the nature of interrelationships among these variables, particularly in the African context.