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The banking industry plays a key role in China's financial industry. In the past decade, the speed of the development of China's commercial banks has gradually declined. Commercial banks with different ownership structures also have certain differences in terms of operating efficiency, and their monetary policies are often different. Therefore, the authors study the impact of ownership structure on the efficiency of commercial banks under different monetary policies. This study also provides relevant reference opinions with regard to the healthy, sustainable and stable development of China's banking industry.

This paper mainly uses the two-stage data envelope analysis (DEA) model under meta-frontier and group frontier to study the deposit and loan efficiency changes of 16 banks from 2007 to 2014 under ownership structure heterogeneity. Furthermore, the model introduces the balance parameters between deposits and loans, in order to realize the mathematical abstraction description of macro-monetary policy.

First, based on bank efficiency analysis, the paper finds that most banks' loan efficiency is higher than their deposits. Second, the paper concludes that different monetary policies have little effect on bank deposit and loan efficiency, while ownership heterogeneity has a significant impact on bank performance. Finally, through the decomposition of the sources of inefficiency in bank performance, this paper finds that management and technology are two factors that affect the inefficiency of banks.

The authors work contributes to the existing literature in the following ways: First, to the best of the authors’ knowledge, this is the first attempt to use the DEA model to study the relationship between monetary policies and bank supply chain efficiency. The results may provide additional managerial implications for the banking industry from the perspective of monetary policies. The result is helpful in terms of explaining how and why banks should strengthen risk management, as well as how to deal with non-performing loans in management terms and finally, why banks should make financial technology innovations in technology terms.

I contribute to the ongoing policy discourse on the challenges of monetary policy transmission in environments with consolidated financial sectors and high credit rates. I empirically investigate the lending rate pass-through in Azerbaijan – a small resource-rich economy in transition – by taking advantage of a unique set of high-frequency bank-level data. My bottom-line policy message is the following. First, lending rates are considerably irresponsive to monetary policy shocks, and the interest rate channel ought to be somehow improved. Second, macroeconomic fundamentals and the concentrated bank sector are surprisingly not among the reasons behind the policy-market disconnect. Third, domestic commercial banks are able to exert substantial monopolistic pricing capacities and keep credit rates high, particularly when the central bank loosens its policy stance. Fourth, the underlying cause of both monetary policy inefficacy and high interest rate stickiness appears to be structural excess liquidity. In fact, empirical results show that pass-through is substantially higher for less liquid banks. Extraction of excess liquidity from the system should mitigate the banks’ monopolistic pricing powers, improve the efficiency of the interest rate channel, and ultimately bring the credit rates down.

Causality between corporate financial performance (CFP) and corporate social performance (CSP) has been extensively debated in previous research works; however, little research has been done to investigate the long-run dynamics between these two constructs. The purpose of this paper is to enrich the CFP–CSP literature by estimating the long-run equilibrium relationship between financial performance and social performance in the banking sector in the Gulf Cooperation Council countries over the period 2009–2019.

The paper adopts an approach that is primarily used in financial economics: first, the authors perform panel long-run Granger causality following Canning and Pedroni’s procedure to indicate the direction of the causal relationship. Second, the authors estimate an error correction model using Chudik and Pesaran’s (2015) dynamic common correlated effects mean group estimator to determine the sign of the relationship.

The present research findings prove the existence of a long-run equilibrium relationship between CFP and CSP, while indicating at the same time that panel Granger causality runs positively from CSP to CFP, which means that changes in CSP produce lasting changes in CFP.

The findings of the paper would guide strategists to build fit for purpose corporate social responsibility (CSR) strategies in their firms and establish a continuous investment in CSR activities in the long run rather than harshly investing in CSR activities in the short run.

To the best of the authors’ knowledge, this paper is the first one to address heterogeneity in long-run Granger causality tests to estimate the relationship between CSP and CFP.

The purpose of this paper is to analyse the importance of interbank connections and shocks on banks’ capital ratios to financial stability by looking at a network comprising a large number of European and UK banks.

The authors model interbank contagion using insights from the Susceptible Infected Recovered model. The authors construct scale-free networks with preferential attachment and growth, applying simulated interbank data to capture the size and scale of connections in the network. The authors proceed to shock these networks per country and perform Monte Carlo simulations to calculate mean total losses and duration of infection. Finally, the authors examine the effects of contagion in terms of Core Tier 1 Capital Ratios for the affected banking systems.

The authors find that shocks in smaller banking systems may cause smaller overall losses but tend to persist longer, leading to important policy implications for crisis containment.

The authors infer the interbank domestic and cross-border exposures of banks employing an iterative proportional fitting procedure, called the RAS algorithm. The authors use an extend sample of 169 European banks, that also captures effects on the UK as well as the Eurozone interbank markets. Finally, the authors provide evidence of the contagion effect on each bank by allowing heterogeneity. The authors compare the bank’s relative financial strength with the contagion effect which is modelled by the number and the volume of bilateral connections.

The paper aims to enrich previous findings for an emerging banking industry such as Vietnam, reporting the difference between the parametric and nonparametric methods when measuring cost efficiency. The purpose of the study is to assess the consistency in issuing policies to improve the cost efficiency of Vietnamese commercial banks.

The cost efficiency of banks is assessed through the data envelopment analysis (DEA) and the stochastic frontier analysis (SFA). Next, five tests are conducted in succession to analyze the differences in cost efficiency measured by these two methods, including the distribution, the rankings, the identification of the best and worst banks, the time consistency and the determinants of efficiency frontier. The data are collected from the annual financial statements of Vietnamese banks during 2005–2017.

The results show that the cost efficiency obtained under the SFA models is more consistent than under the DEA models. However, the DEA-based efficiency scores are more similar in ranking order and stability over time. The inconsistency in efficiency characteristics under two different methods reminds policy makers and bank administrators to compare and select the appropriate efficiency frontier measure for each stage and specific economic conditions.

This paper shows the need to control for heterogeneity over banking groups and time as well as for random noise and outliers when measuring the cost efficiency.

The purpose of this paper is to investigate the impact of ownership structure on bank performance in EU-15 countries. Specifically, it examines to what extent shareholder type and the degree of shareholder concentration affect the banks’ profitability, risk and technical efficiency.

This study uses a sample of 1,459 banks operating in EU-15 countries from 2011 to 2015. It constructs a set of continuous variables capturing the ownership nature, the concentration and their interactions, and estimates an instrumental variable random effect (IV-RE) model. In addition, a panel data stochastic frontier analysis is conducted to estimate the time-varying technical efficiency for profitability and costs.

The empirical analysis shows that bank performance is affected by shareholder type. When regressed against the entrenchment behavior of the controlling owner hypothesis, banks with large-block shareholders are more profitable, less risky and more profit efficient. Further, ownership concentration reverts the negative effect related to the institutional, bank and industry ownership.

The results support the hypothesis that concentrated ownership helps to overcome agency problems. They also confirm that managerial involvement in banks’ capital enhances a bank’s profit and its volatility.

To the best of the authors’ knowledge, this is the first study to consider the ownership nature, the concentration and their interaction using continuous variables, which allows for more precise inferences. The results provide new evidence that bank profitability, cost efficiency and risk are affected by the type of direct shareholders.

The purpose of this paper is to provide a method that can better evaluate the credit risk (CR) under PPP project finance.

The principle to evaluate the CR of PPP projects is to calculate three critical indicators: the default probability (DP), the recovery rate (RR) and the exposure at default (EAD). The RR is determined by qualitative analysis according to Standard & Poor’s Recovery Scale, and the EAD is estimated by NPV analysis. The estimation of the DP is the focus of CR assessment because the future cash flow is not certain, and there are no trading records and market data that can be used to evaluate the credit condition of PPP projects before financial close. The modified CreditMetrics model and Monte Carlo simulation are applied to evaluate the DP, and the application is illustrated by a PPP project finance case.

First, the proposed method can evaluate the influence of the project’s cash flow uncertainty on the potential loss of the bank. Second, instead of outputting a certain default loss value, the method can derive an interval of the potential loss for the bank. Third, the method can effectively analyze how different repayment schedules and risk preference of banks influence the evaluating result.

The proposed method offers an approach for the bank to value the CR under PPP project finance. The method took into consideration of the uncertainty and other characteristics of PPP project finance, adopted and improved the CreditMetrics model, and provided a possible loss range under different project cash flow volatilities through interval estimation under certain confident level. In addition, the bank’s risk preference is considered in the CR evaluating method proposed in this study where the bank’s risk preference is first investigated in the CR evaluating process of PPP project finance.

This paper aims to examine the efficiency of Islamic vs conventional banks in Malaysia by unveiling the traditional efficiency concept – black box – with a three-stage network structure of bank operations.

This paper applies data envelopment analysis (DEA) for examining bank efficiency. An adaptive three-step network DEA (NDEA) model is demonstrated for redefining the traditional black box of banking operations. Slack-based variable returns to scale approach is used. Data from all 43 commercial banks in Malaysia are examined over a six-year study period (2010-2015). Inputs and outputs of the model are selected based on CAMELS rating. Undesired output is also considered in time of examining bank efficiency in Malaysia.

The empirical results of this study signify that only a few banks in Malaysia have been performing well in converting deposits and equities into profit as well as minimizing loan loss provisions. Islamic banks in Malaysia have performed better both in production (converting deposits and equities into earning assets) and profitability (converting loans into net income). Conventional banks, however, have over scored in intermediation (converting earning assets into loans).

An adaptive NDEA approach proposed in this paper defines the core banking process instead of traditional approaches in examining bank efficiency based on individual functions (nodes in the network model). This approach has proven to provide better benchmark capacity.

This study aims to explore the relationship between risk governance characteristics (chief risk officer [CRO], chief financial officer [CFO] and senior directors [SENIOR]) and regulatory adjustments (RAs) in Organization for Economic Cooperation and Development public commercial banks.

Using principal component analysis (PCA) and regression models, the research analyzes a representative data set of these banks.

A significant negative correlation between risk governance characteristics and RAs is found. Sensitivity analysis on the regulatory Tier 1 capital ratio and the total capital ratio indicates mixed outcomes, suggesting a complex relationship that warrants further exploration.

The study’s limited sample size calls for further research to confirm findings and explore risk governance’s impact on banks’ capital structures.

Enhanced risk governance could reduce RAs, influencing banking policy.

The study advocates for improved banking regulatory practices, potentially increasing sector stability and public trust.

This study contributes to understanding risk governance’s role in regulatory compliance, offering insights for policymaking in banking.

The present study assesses the commercial bank profit efficiency and its relationship to banking sector competition in a rapidly growing emerging economy, India from 2009 to 2019 using stochastic frontier analysis (SFA).

Lerner indices, conventional and efficiency-adjusted, quantify competition. Two SFA models are employed to calculate alternative profit efficiency (inefficiency) scores: the two-step time-decay approach proposed by Battese and Coelli (1992) and the recently developed single-step pairwise difference estimator (PDE) by Belotti and Ilardi (2018). In the first step of the BC92 framework, profit inefficiency is calculated, and in the second step, Tobit and Fractional Regression Model (FRM) are utilized to evaluate profit inefficiency correlates. PDE concurrently solves the frontier and inefficiency equations using the maximum likelihood process.

The results suggest that foreign banks are less profit efficient than domestic equivalents, supporting the “home-field advantage” hypothesis in India. Further, increasing competition drives bank managers to make riskier lending and investment choices, decreasing bank profit efficiency. However, this effect varies depending on bank ownership and size.

Literature on the competition bank efficiency link is conspicuously scant, with a focus on technical and cost efficiency. Less is known regarding the influence of competition on bank profit efficiency. The article is one of the first to examine commercial bank profit efficiency and its relationship to banking sector competition. Additionally, the study work represents one of the first applications of the FRM presented by Papke and Wooldridge (1996) and the PDE provided by Belotti and Ilardi (2018).