What drives the banks' diversification decision? A dynamic nonlinear panel data approach

Ammar, N.; Boughrara, Adel

doi:10.1002/mde.3079

Cited by 7 publications

(17 citation statements)

References 48 publications

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“…Thus, the credit policy of banks is dynamic and depends on market conditions. Further, this paper offers empirical support for the growing body of nonlinear modelling in the finance literature (Abuzayed et al , 2018; Ammar and Boughrara, 2019; Brana et al ., 2019; Ngambou Djatche, 2019; Gambacorta and Rossi, 2010; Gambacorta et al ., 2014; Jiang et al ., 2019; Jiménez, Lopez and Saurina, 2013; Lien et al ., 2017; Martinez-Miera and Repullo, 2010; Musumeci and Peterson, 2011).…”

Section: Introductionsupporting

confidence: 59%

Nonlinear linkages between bank asset quality and profitability: evidence from dynamic and quantile approaches using a global sample

Alqahtani

Hamdi

Skully

2021

IJMF

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PurposeThe purpose of this study is to examine whether the relationship between asset quality and profitability is linear or nonlinear, using a global dataset containing 2,943 banks from advanced and emerging economies.Design/methodology/approachThe authors use the U-shape test to investigate the existence of a nonlinear relationship between asset quality and profitability. In addition, the dynamic panel generalised method of moments (GMM) and quantile regression are used to examine the nonlinear effect of profitability on nonperforming loans (NPLs).FindingsAfter controlling for macroeconomic and bank internal factors, the authors find empirical evidence supporting the existence of a nonlinear relationship in the form of a U-shape. This is also confirmed through the three-stage U test procedure. After distinguishing between advanced and emerging economies, the authors also find that, in advanced markets, the credit policy responds more rapidly to changes in credit market conditions than in emerging markets, providing insights into credit market dynamics.Research limitations/implicationsFurther research can check the robustness of this study’s findings in different markets and investigate the existence of nonlinearity in other bank variables.Practical implicationsIn a nutshell, the results demonstrate potential implications for policymakers who need to carefully monitor banks' lending behaviour to ensure that banks do not lower lending standards. In addition, banking regulators and supervisors should consider the possible nonlinear relationship in their risk assessments and macrostress tests. Further, these results are important for bank managers, who should monitor the performance of their loan portfolios to ensure that their credit officers do not lower credit standards. Likewise, for banks located in an emerging economy, investing in human capital and advanced technologies can enable them to respond more effectively to changes in the credit market.Originality/valueTo the best of the authors' knowledge, this study is considered the first to provide empirical evidence for the nonlinear relationship between asset quality and profitability.

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Section: Introductionsupporting

confidence: 59%

Nonlinear linkages between bank asset quality and profitability: evidence from dynamic and quantile approaches using a global sample

Alqahtani

Hamdi

Skully

2021

IJMF

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“…The second issue is related to stakeholder management. Depositors and not shareholders are often the main source of a bank's assets (Ammar & Boughrara, 2019). In addition, it is generally the government that bails out a bank in distress or takes it over at taxpayer expense.…”

Section: Csr and Banking Activitymentioning

confidence: 99%

“…For instance, HSBC provides tax equity financing for renewable energy activities and launched a green fund to help economies transition to a low‐carbon future (HSBC, 2020). Furthermore, in carrying out these activities, they draw on considerable social resources and are thus required to provide more response to the community than other sectors (Ammar & Boughrara, 2019). For example, the Australian bank Westpac is working with indigenous communities to help access to financial services and to build financial independence for them (Westpac, 2019).…”

Section: Introductionmentioning

confidence: 99%

Managing corporate social responsibility in the bank sector: A fuzzy and disaggregated approach

Laguir

Stekelorum

Laguir

et al. 2021

Corp Soc Responsibility Env

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This study investigates how different activities of corporate social responsibility influence financial performance in the bank sector. In a sample of publicly listed French banks, we use a fuzzy set qualitative comparative analysis to show that financial performance is dependent on the type of activity. The results show that various combinations of corporate social responsibility activities and bank characteristics determine the level of financial performance. Overall, our findings support and extend the recent contingent perspective, which emphasizes the interest of examining the conditions under which banks are more profitable.

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“…Another important factor that influences diversification decisions is the capital ratio (book value of equity over total assets) as a proxy of financial leverage (Ismail et al, 2015). Equity capital acts as a buffer against adverse shocks when the value of assets declines, reducing IJLMA 66,2 the probability of financial distress (Gamra and Plihon, 2011;Ammar and Boughrara, 2019b). A high capitalization indicates a high degree of solvability, which encourages banks to use innovative business models and develop new activities that can raise non-interest incomes, thus explaining a positive relationship between capital ratio and non-traditional activities (Rogers and Sinkey, 1999;Kick and Busch, 2009;Nguyen et al, 2012;Senyo et al, 2015;Hahm, 2017;Meng et al, 2018;Cuong et al, 2020).…”

Section: Empirical Literature and Hypothesis Developmentmentioning

confidence: 99%

Determinants of income diversification: empirical evidence from Indian banks

Thakur,

Arora

2023

IJLMA

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Purpose This study aims to explore the determinants (bank-specific, industry-specific and macroeconomic) of income diversification across interest income and non-interest income as well as for non-traditional income sources (non-interest income) from 2004–2005 to 2021–2022. Design/methodology/approach An unbalanced data set comprising 110 Indian commercial banks with 1480 observations is sampled in this study. Because of the bounded nature of the dependent variables (proxies of income diversification), the panel Tobit regression model is used. Findings The findings reveal that income diversification is positively influenced by bank size, technological advancements, cost–income ratio, return on assets, market competition and inflation in the economy. However, the decision to diversify income sources is adversely impacted by the capital ratio, GDP and financial intermediation ratio. Moreover, factors such as asset quality (loan loss provisions) and liquidity ratio do not directly influence the diversification strategies in the Indian banking industry. Practical implications The present study uses an extensive set of variables to provide insights into key factors for bank managers, regulators and policymakers to consider before developing diversification strategies. Originality/value To the best of the authors’ knowledge, this is the first study to examine the various bank-specific and macroeconomic determinants that affect income diversification in the Indian banking sector. The current study also investigates new variables such as technological advancements and a market concentration index for measuring competition, which have not been investigated in existing literature concerning bank income diversification in the Indian context.

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What drives the banks' diversification decision? A dynamic nonlinear panel data approach

Cited by 7 publications

References 48 publications

Nonlinear linkages between bank asset quality and profitability: evidence from dynamic and quantile approaches using a global sample

Nonlinear linkages between bank asset quality and profitability: evidence from dynamic and quantile approaches using a global sample

Managing corporate social responsibility in the bank sector: A fuzzy and disaggregated approach

Determinants of income diversification: empirical evidence from Indian banks

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