The interrelationships between bank risk and charter value in ASIAN-5

Nguyen Dat; Tu Dq Le Article The interrelationships between bank risk and charter value in ASIAN-5 Journal of Applied Economics Provided in Cooperation with: University of CEMA, Buenos Aires Suggested Citation: Nguyen Dat; Tu Dq Le (2022) : The interrelationships between bank risk and charter value in ASIAN-5, Journal of Applied Economics, ISSN 1667-6726, Taylor & Francis, Abingdon, Vol. 25, Iss. 1, pp. 1182-1199, https://doi.org/10.1080/15140326.2022.2118514 This Version is available at: https://hdl.handle.net/10419/314202 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by/4.0/ Journal of Applied Economics ISSN: (Print) (Online) Journal homepage: www.tandfonline.com/journals/recs20 The interrelationships between bank risk and charter value in ASIAN-5 Dat T Nguyen & Tu DQ Le To cite this article: Dat T Nguyen & Tu DQ Le (2022) The interrelationships between bank risk and charter value in ASIAN-5, Journal of Applied Economics, 25:1, 1182-1199, DOI: 10.1080/15140326.2022.2118514 To link to this article: https://doi.org/10.1080/15140326.2022.2118514 © 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. Published online: 13 Sep 2022. Submit your article to this journal Article views: 1078 View related articles View Crossmark data Citing articles: 3 View citing articles Full Terms & Conditions of access and use can be found at https://www.tandfonline.com/action/journalInformation?journalCode=recs20 The interrelationships between bank risk and charter value in ASIAN-5 Dat T Nguyen a,b and Tu DQ Le a,b a University of Economics and Law, Ho Chi Minh City, Vietnam; b Vietnam National University, Ho Chi Minh City, Vietnam ABSTRACT This study examines the interrelationships between bank risk and charter value in five countries in Southeast Asia (ASEAN-5) from 2006 to 2019 using a simultaneous equations model. The findings show a two-way relationship between bank risk and charter value. More specifically, the positive relationship between charter value and bank risk implies that banks with a more excellent charter value tend to pursue fast growth strategies and thus may face a higher risk. This positive link, however, only holds up to a certain level of charter value. On the other hand, the negative impact of bank risk on charter value argues that more risky banks tend to generate lower returns, thus reducing charter value. Additionally, a bidirectional relationship between them still holds when using an alternative measure of bank risk and controlling for the global financial crisis and governance indicators. Therefore, our findings provide critical implications for policymakers, managers, and academics. ARTICLE HISTORY Received 20 April 2022 Accepted 25 August 2022 KEYWORDS Bank risk-taking; charter value; ASEAN-5; 3SLS; SEM 1. Introduction The banking system is critical to most economies worldwide, particularly those that are bank-based. Indeed, since banks provide the primary funding to firms and households and facilitate payment management systems. The recent global financial crisis reemphasized factors that discipline bank risk-taking must be improved. These elements include regulatory discipline and bank capital charter (also known as bank self-discipline) (Gueyie & Lai, 2003). Additionally, Jones, Miller, and Yeager (2011) highlighted that charter value is one of the essential parts of the banking industry because of its ability to reduce moral hazard incentives that may arise from deposit insurance schemes. Furthermore, the charter value hypothesis also argues that charter value self-regulates bank risk-taking and offers a valuable source of monopoly power to banks (Demsetz, Saidenberg, & Strahan, 1996; Gan, 2004; Ghosh, 2009a; Gonzalez, 2005; Jones et al., 2011; Keeley, 1990). Consequently, the greater charter value could reduce risk-taking behaviours and improve bank capital because of more significant bankruptcy costs faced by banks if they fail. On the other hand, banks that often seek more returns, higher margins, and profitability tend to engage more in new financial instruments and rely more on CONTACT Dat T Nguyen [email protected] University of Economics and Law, Ho Chi Minh, Vietnam, 700000 and Vietnam National University, Ho Chi Minh, Vietnam, 700000; Tu DQ Le [email protected] University of Economics and Law, Ho Chi Minh City, Vietnam, and Vietnam National University, Ho Chi Minh City Vietnam JOURNAL OF APPLIED ECONOMICS 2022, VOL. 25, NO. 1, 1182–1199 https://doi.org/10.1080/15140326.2022.2118514 © 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/ licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. FINANCE AND BANKING ECONOMICS short-term debt. This shift towards new market-based instruments at a larger scale and riskier business models is challenging for banks with more excellent charter value (Martynova, Ratnovski, & Vlahu, 2014). Several studies have attempted to examine the relationship between bank risk and charter value. On the one hand, early studies have shown that banks with high charter value tend to face lower default risk (Demsetz et al., 1996; Gropp & Vesala, 2004; Herring & Vankudre, 1987; Keeley, 1990; Marcus, 1984). On the other hand, Agusman, Gasbarro, and Zumwalt (2006) demonstrated that charter value is positively associated with bank risk. 1 Furthermore, a few studies indicated that greater risk may weaken charter value (Ghosh, 2009a). All in all, prior studies have suggested the possibility that a bidirectional relationship between charter value and bank risk may exist. That is a gap that this study aims to address. When considering the size and impact of some emerging markets like Southeast Asia on the world economy, it is surprising that no empirical studies have attempted to investigate the interrelationship between bank risk and charter value in this region. This study focuses on the original five members of the Association of Southeast Asian Nations (ASEAN-5), including Vietnam, Indonesia, Thailand, Malaysia, and the Philippines. With an average growth rate of 5.3 percent between 2006 and 2019, ASEAN-5 is considered one of the world’s fastest-growing economies (WB, 2019). Some of them (e.g., Vietnam) are regarded as Asia’s next dragons (Nguyen, Roca, & Sharma, 2014). As a crucial pillar of the financial sector, the development of the banking system is essential to the remarkable economic growth of ASEAN-5. For instance, 16– 18% of the Vietnamese economic growth was attributed to the banking system (Stewart, Matousek, & Nguyen, 2016). Thus, bank stability has attracted much attention from academics, practitioners, and policymakers. The ASEAN-5 banking sectors have undergone regulatory adjustments due to past financial crises such as the Asian Financial Crisis and the Global Financial Crisis (GFC) (Noman & Isa, 2021). The ASIAN-5 banks have approached Basel III by gradually increasing their average capital to assets from 8.4% in 2006 to 11.5% in 2019 (IMF, 2019). Theoretically, this requirement was supposed to reduce bank instability by limiting more considerable exposure to riskier investments. However, increased capital requirements pressure may cause banks to have a lower charter value, ultimately increasing bank risk-taking (Le, 2018, 2019; Zhang & Jiang, 2018). The present study contributes to the existing literature in two main ways. First, most studies have examined the one-way relationship between bank risk and charter value. For instance, several studies have investigated the effect of charter value on bank risk (Bakkar, Rugemintwari, & Tarazi, 2020; Daher, Masih, & Ibrahim, 2019; Ghosh, 2009b). Other studies, however, have examined the effect of bank risk on charter value (Ghosh, 2009a). As argued above, the possible two-way relationship between bank risk and charter value may exist. Examining this interrelationship in ASEAN-5 banking systems will add more evidence to the extant literature in emerging markets, especially Southeast Asia. Second, the impact of charter value on bank risk and vice versa would differ given the regulatory environments and economic conditions confronted by banks across countries and the 1 For most (but not all) metrics of bank risk, Agusman et al. (2006) showed a positive relationship between charter value and bank risk. JOURNAL OF APPLIED ECONOMICS 1183 various level and quality of services related to deposits and loans among nations. Therefore, the lessons drawn from prior studies may not automatically apply to other markets. By providing evidence on the bidirectional relationship between charter value and bank risk in ASEAN-5, this study would provide significant implications for bank practitioners and policymakers in strengthening the regional banking systems. Using a unique dataset of 79 listed banks from 2006 to 2019, the findings show a twoway relationship between charter value and bank risk in ASEAN-5. More specifically, the charter value may increase bank risk-taking. However, the findings document an inverted U-shaped relationship between them. Simultaneously, the results indicate a negative impact of bank risk on charter value. Similar results are still obtained when running several robustness checks. The rest of this paper is structured as follows: Section 2 presents a brief literature review on the relationships between charter value and bank risk. Section 3 presents the methodology and data used. Section 4 reports empirical results, while Section 5 concludes this study. 2. A brief overview of the literature The literature on the relationship between bank risk and charter value can be divided into two strands. The first strand has focused on the one-way relationship between charter value and bank risk. The second strand has attempted to examine the impact of bank risk on charter value. These will be discussed in turn. In the first strand, the early work of Hellmann, Murdock, and Stiglitz (2000) and Repullo (2004) has proposed theoretical models about the disciplining effects of charter value on bank risk-taking. The charter value is conventionally measured by the gap between a bank’s market value and its book value. Since regulatory decisions are based on book-value capital measurements, banks have more incentive to maintain a high book capital ratio and minimize risk. Similarly, a seminal work by Buser, Chen, and Kane (1981) claimed that charter value is a critical factor that is the ability to limit banks’ risktaking incentives. Early studies in the US market have provided a negative relationship between charter value and bank risk-taking. Keeley (1990) argued that once bank charter value is reduced due to the increasingly competitive environment, banks are more incentive to take more risks. Similarly, Brewer and Saidenberg (1996) showed a negative association between bank charter value and the volatility of the daily stock price. In a consistent manner, other studies have demonstrated that a greater charter value provides banks more incentives to self-regulate their risk-taking behavior (Galloway, Lee, & Roden, 1997; Herring & Vankudre, 1987; Marcus, 1984). When considering the impact of the global financial crisis, Jones et al. (2011) found that the overall reduction in charter value contributes to increasing bank risk-taking, which ultimately results in the subprime financial crisis. Using the European data, Gropp and Vesala (2004) also found similar findings. Because the charter value of a bank belongs to its shareholders, a greater charter value should discourage bank risk-taking (Haq, Avkiran, & Tarazi, 2019). Regarding emerging markets, Zhang and Jiang (2018), using Chinese data, confirmed that a lower charter value caused by increased capital requirement pressure may induce banks to take more risk. In the same vein, Ghosh (2009b), using Indian data, showed that banks with lower charter values tend to take a greater risk. 1184 D. T. NGUYEN AND T. D. LE However, other studies have indicated opposite findings. Using a moral-hazard framework, Park (1997) contended that increasing charter value may lead to a more incredible risk interior solution. Using large banks in the US and Europe, Bakkar et al. (2020) found that higher charter value amplifies standalone and systemic risk if banks pursue a focus strategy. Similarly, Hoang, Faff, and Haq (2014), using banks from G7 nations, emphasized that charter value is positively related to banking system risk. Using the sample of Asian banks, Agusman et al. (2006) also provided the same conclusion, and the results are still robust when using different measures of bank risk. In the second strand, limited studies have attempted to examine the impact of bank risk and charter value. A study by Ghosh (2009a) has indicated that banks that face higher risk tend to have diminished charter value. All in all, the literature may suggest the interrelationships between bank risk and charter value. Therefore, the first hypothesis is formed as follows: H 1: There is a bidirectional relationship between charter value and bank risk. One may argue that the positive impact of charter value on bank risk may exist up to a certain level. Ghosh (2009a) found a quadratic relationship between charter value and bank risk in the Indian banking system. Following their suggestion, the second hypothesis is established as follows: H 2: There is a non-linear relationship between charter value and bank risk. 3. Methodology and data 3.1. Methodology As explained in Section 2, charter value (CVÞand bank risk (RISKÞare considered the two endogenous variables in this study. Following the suggestion of Ngo and Le (2019), Le, Ho, Nguyen, and Ngo (2021), and among others, a simultaneous equations model (SEM) is used to deal with the concurrent relationship between CV and RISK. It is acknowledged that several techniques could be used within the SEM framework, such as the Granger causality test (Fiordelisi, Marques-Ibanez, & Molyneux, 2011), three-stage least squares (3SLS) (Le, 2019; Nguyen & Le, 2022), two-stage least squares (2SLS) (Kwan & Eisenbeis, 1997), generalized methods of moments (Le et al., 2021), and seemingly unrelated regressions (Altunbas, Carbo, Gardener, & Molyneux, 2007). The advantages and disadvantages of these techniques are well explained by Nguyen and Nghiem (2015), Nosier and El-Karamani (2018), and Nguyen and Le (2022). For the want of space, the explanations are not repeated. Following Ngo and Le (2019) in cross-country and Nguyen and Nghiem (2015) in India, a SEM with the 3SLS estimator is used in this study because 3SLS is proved to be more efficient than 2SLS (Belsley, 1988; Intriligator, 1978). Our baseline model is formed as follows: RISK ¼f CV;Bank controls;Macro Controlsð Þ (1) JOURNAL OF APPLIED ECONOMICS 1185 CV ¼f RISK;Bank controls;Macro Controlsð Þ (2) where CV is measured by the natural logarithm of the book value of assets minus the book value of equity minus deferred taxes plus the market value of common stocks (González-Rodríguez, 2008). Additionally, we follow Martinez-Miera and Repullo (2010) to use squared charter value (SQCV) in the model to investigate whether a non-linear relationship between charter value and bank risk may exist. Because listed banks are included in our analysis, RISK is preferably proxied by the yearly volatility of weekly stock returns (Galloway et al., 1997; Ghosh, 2009a; Hovakimian & Kane, 2000). Accordingly, higher risk means higher volatility in stock returns. For robustness checks, we use ZSCORE as a measure of bank stability (Le, 2021; Lepetit & Strobel, 2013; Nguyen, Le, & Ho, 2021). ZSCORE ¼ROAi;tþEQUITYi;t σROAi where ROAi;t and EQUITYi;t are the current value of ROA and the ratio of total equity to total assets, respectively while σROAi is the standard deviation of ROA over the sample period. In addition, the natural logarithm of ZSCORE value is used to reduce the problem of a highly skewed distribution of ZSCORE. Because a greater value of ZSCORE means lowered bank insolvency risk, we use the inverse of ZSCORE to maintain consistency with the analysis of RISK. For ease of exposition, ZSCORE is still labeled as the inverse of the natural logarithm of ZSCORE in the remainder of our study. A number of independent variables are included in equations 1–2 to determine the critical factors that affect bank risk and charter value. It is worth noting that these variables are similar but not identical to those in prior studies, so as to better reflect the ASEAN-5 institutional and regulatory framework. For the determinants of bank risk (Eq. 1), we control for bank profitability ROAð Þ, bank liquidity (LATA), banking openness (FREE), and economic growth (GDP). Bank profitability, as measured by returns on assets (ROA), can withstand financial shocks better, thus improving bank stability (Athanasoglou, Brissimis, & Delis, 2008). Higher profitability, however, may imply high-risk premia when there is insufficient bank regulation and asymmetric information (Hellmann et al., 2000). LATA, the ratio of liquid assets to total assets, is used to control for liquidity risk. A high value of LATA implies a more stable bank (Shim, 2013; Vithessonthi, 2014). However, banks that hold more liquid assets tend to yield lower risk-adjusted returns because these assets often generate lower returns than others (Delis & Staikouras, 2011; Ho et al., 2021). Following Mercieca, Schaeck, and Wolfe (2007) and Le and Nguyen (2021), FREE, the banking freedom index is used to control for the effect of the openness of the banking system. The higher value of FREE is, the greater degree of the banking system’s openness is. Le et al., (2020) argued that higher banking freedom is associated with more stability since a more open condition may encourage banks to engage in those activities that are the most relevant to their strategies and goals to manage risk appropriately. Furthermore, GDP, as measured by the annual growth rate of the economy, is used to account for the economic conditions that may affect bank risk-taking behaviour (Le & Nguyen, 2021; Le et al., 2020). For the determinants of charter value CVð Þ (Eq. 2), we control for bank size SIZEð Þ, lending specialization LOANð Þ, bank funding DEPOð Þ, bank diversification NICð Þ, and economic growth GDPð Þ. SIZE, the natural logarithm of total assets, may affect bank charter value (Keeley, 1990) because large banks with more market power will attract 1186 D. T. NGUYEN AND T. D. LE more depositors, thus increasing charter value (Akhtar & Saleem, 2021; Gonzalez, 2005). LOAN, the ratio of total loans to total assets, and DEPO, the ratio of total deposits to total assets are used to examine whether bank charter value is affected by rents earned from the loan and deposit markets (Ghosh, 2009a). NIC, the ratio of non-interest income to total income, is used to study whether a shift toward non-traditional activities may increase bank profitability, thus improving charter value (Ghosh, 2009b). GDP, the economic growth rate, accounts for the economic conditions that may influence bank charter value. Following prior studies such as Le and Pham (2021), and Nguyen (2012), we employ the pairwise Granger causality test to examine whether CV and RISK are possibly endogenous. The pairwise Granger causality model is constructed as follows: RISKi;t¼α0;iþX k j¼1 α1;iRISKi;tjþX k j¼1 α2;iCVi;tjþεi;t(3) CVi;t¼β0;iþX k j¼1 β1;iCVi;tjþX k j¼1 β2;iRISKi;tjþvi;t(4) where i represents the number of banks in the panel (i¼1;2;3...;N), t denotes the time period (t¼1;2;3;...;T), and j is the lag length. Error terms, εt and vt;account for white noise and are possibly correlated for a given bank. The Granger causality between CVt and RISKt exists if the sets of their coefficients in equations 3–4 are statistically significant (Granger, 1969). Table 1 shows the results of the pairwise Granger causality tests using the panel regression with one and two lags as suggested by Nguyen (2012) and Wooldridge (2001). The findings show that the bi-directional relationship between CV and RISK may exist in most cases. Similar results are also obtained when observing the Granger causality between ZSCORE and CV. Once the factors that affect charter value and bank risk are identified, Equations 1–2 should be entered in a simultaneous model because of two main reasons. The first reason is that the error terms from both equations are possibly correlated due to using the same dataset. Since random errors and endogenous parameters are correlated, inconsistent and biased estimators may be derived from the simultaneous equation bias if ignored. The second reason is that a contemporaneous relation between error terms exists as they may contain factors that were excluded from the equations. Because banks provide universal products and services across countries in the region, the impact of the excluded factors on the association between CV and RISK for one entity is similar to another. Consequently, these errors should be connected and yield consistent findings. As endogenous issues may cause inconsistent estimators of biased SEM, the use of a system estimating technique should consider these matters. To validate the reliability of Table 1. Pairwise Granger-causality tests. Number of Lags 1 2 Null Hypothesis F-Statistics Prob. F-Statistics Prob. RISK does not Granger cause CV 55.161 0.000 0.653 0.524 CV does not Granger cause RISK 12.854 0.000 11.902 0.000 RISK ¼the yearly volatility of weekly stock returns; CV ¼the natural logarithm of the book value of assets minus the book value of equity minus deferred taxes plus the market value of common stocks. JOURNAL OF APPLIED ECONOMICS 1187 a simultaneous equations system, the identification test is used. The process of excluding exogenous and counting endogenous variables in the equation must meet the ordinary order condition for individual equation calculation with instrument variables. Baum (2007) suggested that the rank of the instrument matrix can be solved by the sufficient rank criterion. In our analysis of the 3SLS estimator embedded a SEM, each equation may meet the individual-equation order and rank criteria for identification, but the system is still undetermined. Therefore, the identifiability in the system is the association between the reduced form of the linear system and the structural coefficient matrices. According to the rule of thumb, the values of the structural coefficients that range from −0.5 to 0.5 are considered an identification benchmark in SEM (Greene, 2003; Wooldridge, 2001). The data in Table 2 reveal the consistent values of endogenous and exogenous variables in the equations. The same results are true when using ZSCORE as an alternative measure of RISK although they cannot be presented due to the length restriction. 3.2. Data Our data was gathered from three main databases. We only focus on listed banks because we use both market and accounting measures of bank risk for robustness. Listed banks were primarily collected from Refinitiv Eikon deposited at Thomson Reuter. Initially, a sample of 100 listed banks in ASEAN-5 was obtained. To examine the interrelationship between charter value and bank risk, banks with data availability of more than four consecutive years were analyzed in our study. After excluding banks with insufficient data to calculate our main dependent variable, this arrived at a sample of 79 banks between 2006 and 2019, yielding a total of 1,106 observations. 2 While data on GDP was achieved from the World Bank database (WB, 2019), the data on FREE was acquired from the Heritage Foundation database. Nonetheless, the country that had the most banks was Indonesia (43%), and the least was Vietnam (11.39%). The Philippines, Malaysia, and Thailand accounted for 18.98%, 13.92%, and 12.65%, respectively. Note that Singapore is not considered in our study because it is identified as a developed country. Table 3 indicates the mean of RISK is 80.2% with a greater standard deviation, implying a large difference in stock returns’ volatility of banks across nations in ASEAN-5. Furthermore, the mean bank charter value CVð Þ is $US 85,100 billion with a high standard deviation, suggesting a significant difference in the charter value of banks in the region. Also, the mean of LATA and NIC is 12.7% and 28.8%, respectively. The average ratio of total deposit to total assets DEPOð Þ is 76.7%, while the average ratio of total loans to total assets LOANð Þ is 0.6%. FREE has a value of 49.36 with a higher standard deviation, arguing a substantially different degree of the banking systems’ openness among these nations. 4. Results 4.1. Our baseline results Table 4 indicates a negative association between CV and two measures of bank risk. Also, the correlations between independent regressors are relatively not high. Based on the 2 For instance, Vietnamese banks were required to publish their audited financial information since 2006 (Le, 2019). 1188 D. T. NGUYEN AND T. D. LE However, this study may suffer some limitations. This study used a panel data of 79 listed banks in ASEAN-5 from 2006 to 2019. Perhaps, further research may extend period coverage and the number of banks in different areas to confirm our findings. Especially, the negative impact of the COVID-19 pandemic on the banking system is acknowledged in the literature (Boubaker, Le, & Ngo, 2022; Elnahass, Trinh, & Li, 2021; Le, Ho, Nguyen, & Ngo, 2022) thus, this impact should be considered in future studies when examining the interrelationship among bank risk and charter value. Last but not least, the emergence of alternative digital lending (e.g., fintech credit and bigtech credit) may challenge the function of the banking system (Le, 2022; Le et al., 2021). Future research may consider the impact of fintech development when investigating the interrelationships between charter value and bank risk. Disclosure statement No potential conflict of interest was reported by the author(s). Funding This research is funded by the University of Economics and Law, Vietnam National University, Ho Chi Minh, Vietnam. Notes on contributors Dat T Nguyen is a lecturer at Bac Lieu University and is currently a Ph.D. candidate at the University of Economics and Laws, Vietnam. His works focus on econometrics in banking and finance. Tu DQ Le is a researcher at the Institute for Development & Research in Banking Technology, University of Economics and Law, Vietnam. His works focus on efficiency and productivity measurement in the field of banking and finance, the industry sector, and the impact of ecommerce on economic growth. His recent papers have been published in CogentEconomics & Finance, International Journal of Managerial Finance, Managerial Finance, pacific Accounting Review, and Post-Communist Economies. ORCID Dat T Nguyen http://orcid.org/0000-0002-4165-3249 Tu DQ Le http://orcid.org/0000-0002-5629-5288 References Agusman, A., Gasbarro, D., & Zumwalt, J. K. (2006). Bank moral hazard and the disciplining factors of risk taking: Evidence from Asia Banks during 1998-2003. Financial Management Association (FMA) European Conference, Stockholm, Sweden. Akhtar, T. (2021). Market multiples and stock returns among emerging and developed financial markets. Borsa Istanbul Review, 21(1), 44–56. Akhtar, M. N., & Saleem, S. (2021). The impact of market discipline on charter value of commercial banks: Empirical evidence from Pakistan stock exchange. The Journal of Asian Finance, Economics and Business, 8(4), 249–261. https://doi.org/10.13106/jafeb.2021.vol8.no4.0249 JOURNAL OF APPLIED ECONOMICS 1195 Altunbas, Y., Carbo, S., Gardener, E. P. M., & Molyneux, P. (2007). Examining the relationships between capital, risk and efficiency in European banking. European Financial Management, 13 (1), 49–70. Athanasoglou, P. P., Brissimis, S. N., & Delis, M. D. (2008). Bank-specific, industry-specific and macroeconomic determinants of bank profitability. Journal of International Financial Markets, Institutions and Money, 18(2), 121–136. Bahadir, B., & Valev, N. (2019). Credit information sharing and the shift in bank lending towards households. International Journal of Finance & Economics, 26(1), 60–72. https://doi.org/10. 1002/ijfe.1776 Bakkar, Y., Rugemintwari, C., & Tarazi, A. (2020). Charter value, risk-taking and systemic risk in banking before and after the global financial crisis of 2007-2008. Applied Economics, 52(36), 3898–3918. Barth, J. R., Caprio, G., & Levine, R. (2004). Bank regulation and supervision: What works best? Journal of Financial Intermediation, 13(2), 205–248. http://dx.doi.org/10.1016/j.jfi.2003.06.002 Baum, C. (2007). Checkreg3: Stata module to check identification status of simultaneous equations system. Working Paper No. 667, Boston College Department of Economics, Massachusetts. Belsley, D. A. (1988). Two-or three-stage least squares? Computer Science in Economics and Management, 1(1), 21–30. https://doi.org/10.1007/BF00435200 Berger, A. N., & Bouwman, C. H. (2009). Bank liquidity creation. The Review of Financial Studies, 22(9), 3779–3837. BIS. (2010). 80th annual report. Bank for International Settlements, Basel. Bordeleau, É., & Graham, C. (2010). The impact of liquidity on bank profitability. Working Paper No. 2010-38, Bank of Canada, Ontario. Boubaker, S., Le, T. D., & Ngo, T. (2022). Managing bank performance under COVID-19: A novel inverse DEA efficiency approach. International Transactions in Operational Research. https:// doi.org/10.1111/itor.13132 Bourke, P. (1989). Concentration and other determinants of bank profitability in Europe, North America and Australia. Journal of Banking & Finance, 13(1), 65–79. Brewer, E., & Saidenberg, M. R. (1996). Franchise value, ownership structure, and risk at savings institutions. Research Paper No. 9632, Federal Reserve Bank of New York, New York. Buser, S. A., Chen, A. H., & Kane, E. J. (1981). Federal deposit insurance, regulatory policy, and optimal bank capital. The Journal Of Finance, 36(1), 51–60. https://doi.org/10.1111/j.1540-6261. 1981.tb03534 Daher, H., Masih, M., & Ibrahim, M. (2019). The impact of charter values on bank capital in Asia: A threshold regression analysis. Emerging Markets Finance and Trade, 55(3), 655–670. De Nicolo, G. (2000). Size, charter value and risk in banking: An international perspective. Washington DC: International Finance Discussion Papers No. 689, Board of Governors of the Federal Reserve System. Delis, M. D., & Staikouras, P. K. (2011). Supervisory effectiveness and bank risk. Review of Finance, 15(3), 511–543. Demsetz, R. S., Saidenberg, M. R., & Strahan, P. E. (1996). Banks with something to lose: The disciplinary role of franchise value. Economic Policy Review, 2(2). http://dx.doi.org/10.2139/ ssrn.1028769 Elnahass, M., Trinh, V. Q., & Li, T. (2021). Global banking stability in the shadow of Covid-19 outbreak. Journal of International Financial Markets, Institutions and Money, 72, 101322. Fiordelisi, F., Marques-Ibanez, D., & Molyneux, P. (2011). Efficiency and risk in European banking. Journal of Banking & Finance, 35(5), 1315–1326. http://dx.doi.org/10.1016/j.jbank fin.2010.10.005 Fu, X. M., Lin, Y. R., & Molyneux, P. (2015). Bank capital and liquidity creation in Asia Pacific. Economic Inquiry, 54(2), 966–993. https://doi.org/10.1111/ecin.12308 Galloway, T. M., Lee, W. B., & Roden, D. M. (1997). Banks’ changing incentives and opportunities for risk taking. Journal of Banking & Finance, 21(4), 509–527. https://doi.org/10.1016/S03784266(96)00052-0 1196 D. T. NGUYEN AND T. D. LE Gan, J. (2004). Banking market structure and financial stability: Evidence from the Texas real estate crisis in the 1980s. Journal of Financial Economics, 73(3), 567–601. Ghosh, S. (2009a). Bank risk, charter value and depositor discipline: A simultaneous equations approach. Applied Economics Letters, 16(6), 639–644. Ghosh, S. (2009b). Charter value and risk-taking: Evidence from Indian banks. Journal of the Asia Pacific Economy, 14(3), 270–286. Godlewski, C. J. (2005). Bank capital and credit risk taking in emerging market economies. Journal of Banking Regulation, 6(2), 128–145. Gonzalez, F. (2005). Bank regulation and risk-taking incentives: An international comparison of bank risk. Journal of Banking & Finance, 29(5), 1153–1184. González-Rodríguez, F. (2008). The relationship between charter value and bank market concentration: The influence of regulations and institutions. Applied Financial Economics, 18(2), 153–172. Granger, C. W. (1969). Investigating causal relations by econometric models and cross-spectral methods. Econometrica: Journal of the Econometric Society, 37(3), 424–438. Greene, W. H. (2003). Econometric analysis. India: Pearson Education. Gropp, R., & Vesala, J. (2004). Deposit insurance, moral hazard and market monitoring. Review of Finance, 8(4), 571–602. Gueyie, J.-P., & Lai, V. S. (2003). Bank moral hazard and the introduction of official deposit insurance in Canada. International Review of Economics & Finance, 12(2), 247–273. Haq, M., Avkiran, N. K., & Tarazi, A. (2019). Does market discipline impact bank charter value? The case for Australia and Canada. Accounting & Finance, 59(1), 253–276. https://doi.org/10. 1111/acfi.12244 Hellmann, T. F., Murdock, K. C., & Stiglitz, J. E. (2000). Liberalization, moral hazard in banking, and prudential regulation: Are capital requirements enough? The American Economic Review, 90(1), 147–165. Herring, R. J., & Vankudre, P. (1987). Growth opportunities and risk-taking by financial intermediaries. The Journal of Finance, 42(3), 583–599. Ho, T. H., Le, T. D., & Nguyen, D. T. (2021). Abnormal loan growth and bank risk-taking in Vietnam: A quantile regression approach. Cogent Business & Management, 8(1), 1–21. https:// doi.org/10.1080/23311975.2021.1908004 Hoang, K. T., Faff, R., & Haq, M. (2014). Market discipline and bank risk taking. Australian Journal of Management, 39(3), 327–350. Hovakimian, A., & Kane, E. J. (2000). Effectiveness of capital regulation at US commercial banks, 1985 to 1994. The Journal of Finance, 55(1), 451–468. https://doi.org/10.1111/0022-1082.00212 IMF. (2019). Financial soundness indicators. Washington, DC. Intriligator, M. (1978). Econometric Models: Techniques and Applications. New Jersey: Prentice Hall. Jones, J. S., Miller, S. A., & Yeager, T. J. (2011). Charter value, Tobin’s Q and bank risk during the subprime financial crisis. Journal of Economics and Business, 63(5), 372–391. https://doi.org/10. 1016/j.jeconbus.2010.10.003 Keeley, M. C. (1990). Deposit insurance, risk, and market power in banking. The American Economic Review, 80(5), 1183–1200. https://www.jstor.org/stable/2006769 Kwan, S., & Eisenbeis, R. A. (1997). Bank risk, capitalization, and operating Efficiency [journal article]. Journal of Financial Services Research, 12(2), 117–131. https://doi.org/10.1023/ A:1007970618648 Le, T. D. (2018). Bank risk, capitalisation and technical efficiency in the Vietnamese banking system. Australasian Accounting Business & Finance Journal, 12(3), 42–61. http://dx.doi.org/10. 14453/aabfj.v12i3.4 Le, T. D. (2019). The interrelationship between liquidity creation and bank capital in Vietnamese banking. Managerial Finance, 45(2), 331–347. Le, T. D. (2021). Can foreign ownership reduce bank risk? Evidence from Vietnam. Review of Economic Analysis, 13(2), 1–24. https://doi.org/10.15353/rea.v13i3.1726 JOURNAL OF APPLIED ECONOMICS 1197 Le, T. D. (2022). A shift towards household lending during Fintech era: The role of financial literacy and credit information sharing. Asia-Pacific Journal of Business Administration. https:// doi.org/10.1108/APJBA-07-2021-0325 Le, T. D., Ho, T. H., Nguyen, D. T., & Ngo, T. (2021). Fintech credit and bank efficiency: International evidence. International Journal of Financial Studies, 9(3), 1–16. Le, T. D., Ho, T. H., Nguyen, D. T., & Ngo, T. (2022). A cross-country analysis on diversification, Sukuk investment, and the performance of Islamic banking systems under the COVID-19 pandemic. Heliyon, 8(3), e09106. Le, T. D., & Ngo, T. (2020). The determinants of bank profitability: A cross-country analysis. Central Bank Review, 20(2), 65–73. Le, T. D., & Nguyen, D. T. (2021). Bank stability, credit information sharing and a shift toward households’ lending: International evidence. International Journal of Managerial Finance. https://doi.org/10.1108/IJMF-07-2021-0311 Le, T. D., Nguyen, V. T., & Tran, S. H. (2020). Geographic loan diversification and bank risk: A cross-country analysis. Cogent Economics & Finance, 8(1), 1–20. https://doi.org/10.1080/ 23322039.2020.1809120 Le, T. D., & Pham, X. T. T. (2021). The inter-relationships among liquidity creation, bank capital and credit risk: Evidence from emerging Asia–Pacific economies. Managerial Finance, 47(8), 1149–1167. Lepetit, L., & Strobel, F. (2013). Bank insolvency risk and time-varying Z-score measures. Journal of International Financial Markets, Institutions and Money, 25, 73–87. Marcus, A. J. (1984). Deregulation and bank financial policy. Journal of Banking & Finance, 8(4), 557–565. Martinez-Miera, D., & Repullo, R. (2010). Does competition reduce the risk of bank failure? The Review of Financial Studies, 23(10), 3638–3664. Martynova, N., Ratnovski, L., & Vlahu, R. (2014). Franchise value and risk-taking in modern banks. DNB Working paper No. 430, De Nederlandsche Bank, Amsterdam. Mercieca, S., Schaeck, K., & Wolfe, S. (2007). Small European banks: Benefits from diversification? Journal of Banking & Finance, 31(7), 1975–1998. http://dx.doi.org/10.1016/j.jbankfin.2007.01. 004 Ngo, T., & Le, T. (2019). Capital market development and bank efficiency: A cross-country analysis. International Journal of Managerial Finance, 15(4), 478–491. Nguyen, J. (2012). The relationship between net interest margin and noninterest income using a system estimation approach. Journal of Banking & Finance, 36(9), 2429–2437. http://dx.doi. org/10.1016/j.jbankfin.2012.04.017 Nguyen, D. T., & Le, T. (2022). The interrelationships between bank risk and market discipline in Southeast Asia. Studies in Economics and Finance, Ahead of print(Ahead of print https://doi.org/ 10.1108/SEF-02-2022-0122 Nguyen, D. T., Le, T. D., & Ho, T. H. (2021). Intellectual capital and bank risk in Vietnam: A quantile regression approach. Journal of Risk and Financial Management, 14(1), 1–15. https:// doi.org/10.3390/jrfm14010027 Nguyen, T. P. T., & Nghiem, S. H. (2015). The interrelationships among default risk, capital ratio and efficiency: Evidence from Indian banks. Managerial Finance, 41(5), 507–525. Nguyen, T. P. T., Roca, E., & Sharma, P. (2014). How efficient is the banking system of Asia’s next economic dragon? Evidence from rolling DEA windows. Applied Economics, 46(22), 2665–2684. Noman, A. H. M., & Isa, C. R. (2021). Financial soundness and macroprudential regulation of banks in ASEAN-5 countries. In W. L. Filho, A. M. Azul, L. Brandli, A. L. Salvia, P. G. Özuyar, & T. Wall, Eds., Reduced Inequalities, pp. 241–253. Cham: Springer International Publishing. https://doi.org/10.1007/978-3-319-95882-8_8 Nosier, S., & El-Karamani, A. (2018). The indirect effect of democracy on economic growth in the MENA region (1990–2015). Economies, 6(4), 61. Park, S. (1997). Risk-taking behavior of banks under regulation. Journal of Banking & Finance, 21 (4), 491–507. 1198 D. T. NGUYEN AND T. D. LE Repullo, R. (2004). Capital requirements, market power, and risk-taking in banking. Journal of Financial Intermediation, 13(2), 156–182. Saif-Alyousfi, A. Y. H., Saha, A., & Md-Rus, R. (2020). The impact of bank competition and concentration on bank risk-taking behavior and stability: Evidence from GCC countries. The North American Journal of Economics and Finance, 51, 100867. Shim, J. (2013). Bank capital buffer and portfolio risk: The influence of business cycle and revenue diversification. Journal of Banking & Finance, 37(3), 761–772. Stewart, C., Matousek, R., & Nguyen, T. N. (2016). Efficiency in the Vietnamese banking system: A DEA double bootstrap approach. Research in International Business and Finance, 36, 96–111. Thakor, A. V. (2015). The financial crisis of 2007–2009: Why did it happen and what did we learn? The Review of Corporate Finance Studies, 4(2), 155–205. Thampanya, N., Wu, J., Nasir, M. A., & Liu, J. (2020). Fundamental and behavioural determinants of stock return volatility in ASEAN-5 countries. Journal of International Financial Markets, Institutions and Money, 65, 101193. Vithessonthi, C. (2014). The effect of financial market development on bank risk: Evidence from Southeast Asian countries. International Review of Financial Analysis, 35, 249–260. https://doi. org/10.1016/j.irfa.2014.10.005 WB. (2019). World development indicators: GDP Growth (annual %). Washington, DC:World Bank. Wooldridge, J. M. (2001). Econometric analysis of cross section and panel data. Massachusetts: The MIT Press. Zhang, J., & Jiang, H. (2018). Capital regulatory pressure, charter value and bank risk-taking: Empirical evidence for China. Journal of Financial Regulation and Compliance, 26(1), 170–186. JOURNAL OF APPLIED ECONOMICS 1199