This article estimates the loan spread equation taking into account the endogenous matching between banks and firms in the loan market. To overcome the endogeneity problem, I…
Abstract
This article estimates the loan spread equation taking into account the endogenous matching between banks and firms in the loan market. To overcome the endogeneity problem, I supplement the loan spread equation with a two-sided matching model and estimate them jointly. Bayesian inference is feasible using a Gibbs sampling algorithm that performs Markov chain Monte Carlo (MCMC) simulations. I find that medium-sized banks and firms tend to be the most attractive partners, and that liquidity is also a consideration in choosing partners. Furthermore, banks with higher monitoring ability charge higher spreads, and firms that are more leveraged or less liquid are charged higher spreads.
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Qian Long Kweh, Wen-Min Lu, Kaoru Tone and Mohammad Nourani
The purpose of this study is twofold. First, this research estimates banks' efficiencies from the perspectives of resource utilization and investment after incorporating risk…
Abstract
Purpose
The purpose of this study is twofold. First, this research estimates banks' efficiencies from the perspectives of resource utilization and investment after incorporating risk measures as an exogenous input in the investment-efficiency stage. Second, the current study examines the relationship between intellectual capital (IC) and banks' efficiencies.
Design/methodology/approach
First, this study uses a dynamic network data envelopment analysis approach in investigating the efficiencies of 24 Taiwanese banks in 2007–2018 from two perspectives. Second, this research utilizes various regression techniques, namely, ordinary least squares (OLS), robust least squares and truncated regression, to gauge the impact of IC on banks' efficiencies. Typically, IC is determined based on a monetary value-based measure and value-added intellectual coefficient (VAICTM).
Findings
Resource-utilization (investment) efficiencies were observed as 0.941 (0.964), thereby contributing to the mean overall efficiency of the sample banks at 0.952. However, the related efficiency changes decline over the sample period, thereby suggesting that the average banks' efficiencies hardly increase. Regression analyses show a significantly positive relationship between IC and banks' overall resource-utilization and investment efficiencies.
Research limitations/implications
Overall, this study suggests that researchers should consider risks when estimating banks' efficiencies owing to their connection to banks' investment performance. From banks' dynamic two-stage efficiencies, this study demonstrated that investments in IC will bring improved future economic benefits.
Originality/value
Different from prior studies, this study improves banks' efficiency evaluation models by incorporating risk measures and assuming weighted periods for the 2007–2008 global financial crisis. Moreover, the use of monetary value-based measure of IC provides consistent results as the commonly-used VAICTM does.
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Preeti Bangarwa and Supriyo Roy
Operational performance is critical for the banking sector for both managers and other stakeholders as it strongly affects the overall performance of the banking system…
Abstract
Purpose
Operational performance is critical for the banking sector for both managers and other stakeholders as it strongly affects the overall performance of the banking system. Traditional performance measures such as ratio analysis encountered certain shortcomings. At this juncture, data envelopment analysis (DEA) approaches are increasingly applied in bank efficiency studies. However, basic DEA models ignored the interactions between consecutive terms and focused primarily on measuring performance independently for each study period. All this is required to develop an operational performance model that can enable the long-term decision model.
Design/methodology/approach
An attempt has been made to develop a dynamic DEA within a non-radial category to measure interconnection activities considering non-performing loans as an undesirable link. This study uses the Indian banking dataset from 2015 to 2019. The study's research design directs three directions: ‘comparison of the dynamic DEA with the traditional static DEA model, areas of inefficiencies that are investigated for each factor using the factor efficiency index and the robustness results highlighting the performance difference between bank categories.'
Findings
Comparing with static DEA results, the study confirms that the dynamic model best measures long-term operational performance due to the linkage between consecutive terms. The efficiency analysis concludes that the input factor that requires the most improvement is ‘fixed assets' and ‘deposits'. The output factor that needs the most progress is ‘non-interest income'. The robustness of the developed model is proven by ownership categories present within the Indian banking system. At a significance level of 10%, the result of both the separate and dynamic model for privately owned banks is significantly better than that of publicly owned banks.
Originality/value
This paper proposes an operational efficiency model for Indian banks in line with undesirable output. The mean factor efficiency analysis related to non-radial DEA modelling enhances managerial flexibilities in determining improvement initiatives.
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Abdel Latef M. Anouze and Imad Bou-Hamad
This paper aims to assess the application of seven statistical and data mining techniques to second-stage data envelopment analysis (DEA) for bank performance.
Abstract
Purpose
This paper aims to assess the application of seven statistical and data mining techniques to second-stage data envelopment analysis (DEA) for bank performance.
Design/methodology/approach
Different statistical and data mining techniques are used to second-stage DEA for bank performance as a part of an attempt to produce a powerful model for bank performance with effective predictive ability. The projected data mining tools are classification and regression trees (CART), conditional inference trees (CIT), random forest based on CART and CIT, bagging, artificial neural networks and their statistical counterpart, logistic regression.
Findings
The results showed that random forests and bagging outperform other methods in terms of predictive power.
Originality/value
This is the first study to assess the impact of environmental factors on banking performance in Middle East and North Africa countries.
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Jose Eduardo Gomez-Gonzalez, Ali Kutan, Jair N. Ojeda-Joya and Camila Ortiz
This paper tests the impact of the financial structure of banks on the bank lending channel of monetary policy transmission in Colombia.
Abstract
Purpose
This paper tests the impact of the financial structure of banks on the bank lending channel of monetary policy transmission in Colombia.
Design/methodology/approach
We use a monthly panel of 51 commercial banks for the period 1996:4–2014:8.
Findings
An increase in the monetary policy interest rate significantly reduces bank loan growth. The magnitude of this effect depends on banks’ financial structure. Additionally, we identify an asymmetric effect in which the bank lending channel is stronger in monetary contractions than during expansions. We show that this behavior is due to the heterogeneous response of banks with different levels of solvency. This finding has important implications for the design and implementation of monetary policy and coordination of central bank’s policy with key economic agents.
Practical implications
The fact that the BLC is stronger in times of monetary contraction is quite interesting for central banking, as it shows that monetary policy transmission is harder during macroeconomic downturns. When investment plans are depressed, monetary stimulus may prove insufficient to reactivate credit demand. This has proven to be true in advanced economies after a strong recession and our results suggest that is also true in emerging market economies for economic downturns in general. Central banks may have to provide stronger shocks to reactivate private credit when the economy is facing a slow economic recovery.
Originality/value
Our findings point out that an increase in the monetary policy interest rate significantly reduces bank loan growth. However, the magnitude of this effect critically depends on two aspects. First, bank heterogeneity matters. Particularly, the loan supply of better capitalized banks is less sensitive to monetary policy shocks. Second, the response of credit supply to shifts in short-term interest rates critically depends on the monetary policy stance. The BLC is stronger in times of monetary contraction than during expansions. Moreover, we show that this asymmetric behavior is due to the heterogeneous response of banks with different levels of solvency to the monetary policy stance.
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Imaduddin Sahabat, Tumpak Silalahi, Ratih Indrastuti and Marizsa Herlina
The financial turbulence resulting from the global financial crisis sparked the interest in improving understanding of financial risks. The transmission of financial institution…
Abstract
Purpose
The financial turbulence resulting from the global financial crisis sparked the interest in improving understanding of financial risks. The transmission of financial institution failures can be determined from the prevailing network structures between banks. The purpose of this study is to identify relationship between payment system network characteristics and financial system condition.
Design/methodology/approach
The characteristics of the interbank network structure in the payment system are identified using a graph theory and the relationship between the network characteristics of interbank transactions in the payment system and financial system stability is examined using a vector auto regression model.
Findings
This study shows that the connectedness of large-value payment transaction is more segmented compared to that of retail value payments. A significant relationship is observed between the characteristics of the network and the large-value payment transactions.
Research limitations/implications
This study found the connectedness of large-value transactions is more segmented when compared to retail-value transactions. It also shows a causal effect of the network characteristic on the financial system stability.
Originality/value
Unlike existing studies, this study considers both the connectedness in large-value transactions and retail-value transactions.
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Ken-Yien Leong, Mohamed Ariff, Zarei Alireza and M. Ishaq Bhatti
The objective of this paper is to investigate the validity of stock valuation theories and their forecasting ability by conducting an empirical study. It employs four most…
Abstract
Purpose
The objective of this paper is to investigate the validity of stock valuation theories and their forecasting ability by conducting an empirical study. It employs four most commonly used theories which are then tested using 19-year banking-firm market data. The usefulness of these models demonstrates with promising results.
Design/methodology/approach
This paper conducts a multi-country study using the multi-model testing approach to evaluate validity of theories and forecast accuracy of banking firms. It employs four methodology models used in finance literature; (1) P/E multiples model, (2) accounting-information-based clean surplus model, (3) theoretical model based on Gordon and Shapiro (1956) method and (4) the Damodaran-Kottler Free Cash Flow or FCF theory based on discounting model.
Findings
The tests show that the four theories under tests have a significant fit with actual price formation. The explained variation ranges from 72 to 92%, so the explanatory power of the theories accounting for variations in bank prices over 19-year period is substantial. The models fit suggest that the P/E model has superior predictive power followed by the RIM, DDM and FCFE. These findings shed new lights on the relative performance of valuation models.
Research limitations/implications
The study is limited in terms of the sample period size for 1999–2019. The availability of essential financial data prior to 2000 is very limited, so one can understand interpretation of statistical results under certain assumptions.
Practical implications
The paper suggests that one-factor model is better than the two-factor model.
Originality/value
The work done in this paper is unpublished and original contribution to banking and finance literature and also not under consideration for publication in any other journal.
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Richard S. Barr, Kory A. Killgo, Thomas F. Siems and Sheri Zimmel
Reviews previous research on the efficiency and performance of financial institutions and uses Siems and Barr’s (1998) data envelopment analysis (DEA) model to evaluate the…
Abstract
Reviews previous research on the efficiency and performance of financial institutions and uses Siems and Barr’s (1998) data envelopment analysis (DEA) model to evaluate the relative productive efficiency of US commercial banks 1984‐1998. Explains the methodology, discusses the input and output measures used and relates bank performance measures to efficiency. Describes the CAMELS rating system used by bank examiners and regulators; and finds that banks with high efficiency scores also have strong CAMELS ratings. Summarizes the other relationship identified and recommends the use of DEA to help analysts and policy makers understand organizations in greater depth, regulators and examiners to develop monitoring tools and banks to benchmark their processes.
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Suman Das and Ambika Prasad Pati
Over the past three decades, financial deregulation and various reforms have significantly transformed the competitive environment for banks in Indonesia. These changes have…
Abstract
Purpose
Over the past three decades, financial deregulation and various reforms have significantly transformed the competitive environment for banks in Indonesia. These changes have introduced new challenges for banks to retain their market power and ensure their survival. In light of this, the article aims to assess the current levels of market power held by Indonesian banks and explore the factors that influence it.
Design/methodology/approach
The paper measured the degree of market power and identified its impacting factors for 22 listed commercial banks using the Adjusted Lerner Index (ALI) and appropriate regression technique over a period of 2011–2023.
Findings
The empirical findings reveal that banks in Indonesia enjoy high market power, and factors such as capitalization, diversification, operational inefficiency, asset quality and GDP growth rate significantly impact banks’ market power. Additionally, the findings contradict the structure-conduct-performance paradigm, which advocates that a concentrated banking system impairs competition.
Research limitations/implications
The study suggests that regulatory authorities should closely monitor the market power levels and promote strategies to enhance competition within the banking sector. Additionally, banks should prioritize implementing measures to reduce operational costs and improve the quality of assets.
Originality/value
This research represents one of the early attempts to gauge the market power of publicly listed conventional commercial banks in Indonesia by employing the Adjusted Lerner Index. Additionally, it introduces “technology adoption” as a novel variable to the analysis alongside other established variables.
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Hannah R. Marston, Linda Shore, Laura Stoops and Robbie S. Turner