Net interest margin, bank risks and business cycle, evidence from vietnam

706 | ICUEH2017 NET INTEREST MARGIN, BANK RISKS AND BUSINESS CYCLE: EVIDENCE FROM VIETNAM TRAN PHUONG THAO University of Economics HCMC – tranthao@ueh.edu.vn THAN THI THU THUY University of Economics HCMC – thuynh@ueh.edu.vn LE VAN LAM University of Economics HCMC – levanlamtcnh@ueh.edu.vn Abstract The purpose of the study is to explore the relationships between net interest margin, bank risks, and business cycle as well as examine the role of business cycle on the relationship between bank risks and net interest margin in Vietnam By investigating the behavior of bank net interest margins over business cycle in the period 2007-2016, the results show that net interest margins are countercyclical, i.e they significantly increase in recessions In addition, business cycle also significantly affects the association between credit risk and net interest margins Banks with higher credit risk have higher net interest margins and the positive effects of credit risk on net interest margins are greater in booms than in recessions The empirical findings of the study also show that bank-specific and industry indicators are closely contributed to the bank net interest margin Keywords: net interst margins; business cycle; bank risk; Vietnamese banking system Tran Phuong Thao et al | 707 Introduction The relation between price-cost margins and aggregate shocks has been attracted voluminous theoretical and empirical studies In financial markets, the seminal papers contributed by Bernanke and Gertler (1989) and Bernanke, Gertler, and Gilchrist (1999) document that external finance premium, measured by the difference between the cost of external funds and internal funds, can act as a “financial accelerator” which exacerbates the aggregates shocks over business cycle Bank net interest margins, usually calculated by the difference between interest income and interest expense divided by total asset, is one of the important metrics of bank profitability (Angbazo, 1997) Furthermore, it is also considered as an indicator to evaluate the efficiency of banks’ intermediation role in financial markets High interest margins not only signal a hardship in investment due to high borrowing costs but they also discourage depositers to save when the deposit rates are low In the recessions, the phenomenon of high net interest margins (i.e countercyclical net interest margins) can amplify the adverse effects of economic shocks since they diminish opportunity to access sources of cheap funds which in turn reduces investment and production at marco level, resulting in a deeper recession period Bank operation faces inevitable sources of risks in which credit risk and liquidity risk are shown to link to the probability of default In the period of the recent global financial recession, the occourence of these risks partially leads to the failure of the majority of banks (Imbierowicz & Rauch, 2014) Credit and liquidity risks are also documented to be bank-specific determinants of bank net interest margins (Demirgỹỗ-Kunt & Huizinga, 1999; Saunders & Schumacher, 2000) However, very few studies examine the effects of these risks on net interest margins over business cycle Thus, the cyclical behavior of net interest margins as well as the effects of bank risks on bank net interest margin over business cycle should be investigated to understand the efficiency of banks’ intermediation role The Vietnamese banking system has experienced a rapid development since 1990 in terms of growth and profitability Despite not seriously affected by the recent global financial crisis, the credit growth rate in Vietnam significantly dropped in 2008 and 2009, revealing the effects of business fluctuation on the operation of Vietnamese banking industry When it comes to the issue, an analysis of the relation between net interest margins and business cycle in Vietnam is critical to provide implications for policy makers These observations motivate us to explore the impacts of cyclical behavior on the relationship between bank net interest margins and bank risks in Vietnam 708 | ICUEH2017 The results show that bank net interest margins in Vietnam are countercyclical Another interesting finding is that business cycle also significantly affects the relation between credit risk and net interest margins Credit risk is found to have a positive impact on net interest margins and its effect is greater in good time than in bad time These results provide an insight into Vietnamese banks’ intermediation role, suggesting important implications for interest rates policy in Vietnam to mitigate the adverse influence of net interest margins during crisis The remainder of the paper is structured as follows A brief review of literature is mentioned in section Section describes data and methodology Section provides empirical results while the conclusion is presented in section Literature review The theoretical model suggested by Ho and Saunders (1981) is considered as the starting point for empirical studies of net interest margins in banking sector In this seminal study, banks are viewed as risk-averse intermediaries between the supply side and the demand side of funds The existence of interest margins results from uncertainty faced by banks in transaction process Specifically, in a single period model, banks set the price of deposits and loans at the beginning of the period while facing asymmetric arrival time between deposits and loans demand In the purpose of maximising wealth at the end of the period, deposit and loan rates are set to minimise the asymmetry of arrival time between the two side of funds Ho and Saunders (1981) demonstrate four determinants of interest margins including (1) degree of managerial risk aversion, (2) size of transactions, (3) market structure of banking industry, (4) interest rates volatility Known as a measure of bank profitability, net interest margins significantly depend on bank risks Based on Ho and Saunder’s work, Angbazo (1997) incorporates not only interest rate risk but default risk into the model Employing the data for the US banks from 1989 to 1993, the study demonstrates that riskier loans result in higher net interest margins Another type of bank risks, credit risk, is found to have positive effects on net interest margins in various studies, with the data for European Union member countries in Maudos and De-Guevara (2004) and Kasman, Vardar, and Tunỗ (2011) or for many countries around the world (Demirgỹỗ-Kunt & Huizinga, 1999) Nassar, Martinez, and Pineda (2014) suggest a similar evidence in Honduras when examining quarterly data for the period 1998-2003 Exceptionally, Williams (2007) illustrates an opposite result to the conventional hypothesis when concluding that credit risk negatively affects net interest margins in the Australian banking system Net interest margins are also posited to have a positive relation with liquidity risk, i.e a negative relation with liquidity ratio This hypothesis is examined and confirmed in Angbazo (1997), Drakos (2003) and King (2013) Tran Phuong Thao et al | 709 Liquidity ratio is also found to inversely affect bank spreads in Turkey (Aydemir & Guloglu, 2017) However, the negative sign between liquidity ratio and net interest margins is not confirmed in other studies such as Afanasieff, Lhacer, and Nakane (2002) or Islam and Nishiyama (2016) The relation between liquidity ratio and net interest margins is also found insignificant for the case of Australia in Williams (2007) or Philippines and Indonesia in Doliente (2005) In terms of cyclical behavior, Bernanke and Gertler (1989) and Bernanke et al (1999) provide evidence that the adverse influence of aggregate shocks can be amplified by external finance premium Using a “pricipal – agent” model, they conclude that the agency cost and external finance premium negatively affect borrowers’ net worth Based on the argument that the net worth of borrowers is procyclical, external finance premium is posited to be countercyclical In the banking sector, the impact of business cycle on net interest margins is firstly explored by Aliaga-Díaz and Olivero (2011) Using quarterly data in the US banking industry for the period 1979-2005, the study concludes that net interest margins are countercyclical It offers some potential explanations that net interest margins are significantly affected by several factors over the business cycle including monetary policy, interest rates volatility, the degree of financial deepening, liquidity and capital holdings and the proportion of total assets owned by major banks in the system The countercyclical behavior of interest margins is also found in Turkish banking system by Turgutlu (2010) Aydemir and Guloglu (2017) conduct an investigation for the period 2002-2013 in Turkey and point out that business cycle affects not only bank spreads but also the relation between credit risk, liquidity risk and bank spreads Based on the aforementioned literature, not much research capturing the fluctuation of net interest margin with regard to business cycle and the moderating effect of business cycle on the relationships the bank risks and net interest margins in emerging countries Furthermore, the fluctuation of the banking sectors in emerging markets after the 2007 – 2008 global financial crisis is of interest of many researchers Thus, the study may fill this gap by investigating the cyclical behavior of bank net interest margin and the effects of bank risks on bank net interest margin during business cycle in the Vietnamese banking sector Methodology 3.1 Variables and models To examine the relationship between net interest margin, bank risks and business cycle, three empirical specifications are developed in this study The effect of business cycle and bank risks on bank net interest margin 710 | ICUEH2017 Model 1: NIMit = 𝛽 + 𝛽 1GDPit + 𝛽 2CRit + 𝛽 3LIQit + 𝛽 4INFit + 𝛽 5LARit + 𝛽 6CIit + 𝛽 7CAPit + 𝛽 8MKSit + 𝛽 9DRES +𝜀 it (1) The moderating effect of business cycle on the relationship between bank risks and bank net interest margin Model 2.1: NIMit = 𝛽 + 𝛽 1GDPit + 𝛽 2(LIQ*GDP)it + 𝛽 3CRit + 𝛽 4INFit + 𝛽 5LARit + 𝛽 6CIit + 𝛽 7CAPit + 𝛽 8MKSit + 𝛽 9DRES +𝜀 it (2) Model 2.2: NIMit = 𝛽 + 𝛽 1GDPit + 𝛽 2(CR*GDP)it + 𝛽 3LIQit + 𝛽 4INFit + 𝛽 5LARit + 𝛽 6CIit + 𝛽 7CAPit + 𝛽 8MKSit + 𝛽 9DRES +𝜀 it (3) where 𝜀 it denotes for error terms of bank i at time t In the first empirical specification, the dependent variable is net interest margins denoted by NIM, measured by banks’ net interest income to total assets ratio Our main concern is the impact of business cycle and bank risks on net interest margins Hence, following the study of Aydemir and Guloglu (2017), the first explanatory variable is the growth rates of real Gross Domestic Product (GDP) The sign of 𝛽 is expected to be negative to reflect the countercyclical behavior of net interest margins as the argument in our literature Controlling for bank risks, we respectively include credit risk (CR) and liquidity risk (LIQ) into the model as mentioned in the studies of Williams (2007) and Aydemir and Guloglu (2017) We employ the ratio of liquid assets to total assets as a proxy for liquidity risk Since the effects liquidity risk on net interest margins is found with mixed results in literature, we not expect the sign of this relation and consider it as an empirical issue To measure credit risk, we employ the ratio of preserves of risky loans to total loans Facing higher credit risk, banks are more likely to require higher risk premium on the loan rates, leading to higher net interest margins Therefore, the coefficient of CR in the model is expected to be positive Additionally, the interaction terms of LIQ with GDP in the second specification and CR with CDP in the third specification to respectively capture the relation between liquidity risk and credit risk with net interest margins over business cycle The study incorporates the inflation rates (INF) into the model since higher inflation rates motivate banks to increase their loan rates to offset an increase in costs In Demirgỹỗ-Kunt and Huizinga (1999) and Mendes and Abreu (2003), the inflation rates is found to positively impacts upon net interest margins The loan size (LAR), that is measured by the ratio of total loans to total asset, is documented to be positively related to net interest margins since a higher loan size signals a riskier degree of bank operation that requires higher net interest margins (Maudos & Solís, 2009; Maudos & De-Guevara, 2004) The operating cost to total income ratio (CI) is found to inversely affect net interest margins (Maudos & Solís, 2009) The higher this ratio is, the less efficiently banks operate, leading to lower net interest margins Captial structure (CAP) is shown Tran Phuong Thao et al | 711 to be one of the determinants of net interest margins (Saunders & Schumacher, 2000) Using the equity to total assets ratio as a proxy for capital structure, we expect a negative relation between CAP and NIM since a lower banks’ financial leverage ratio is likely to reduce banks’ risk-taking degree in lending activities and hence, reduce interest income In terms of industry indicators, this study employs the proportion of banks’ assets in total assets of Vietnamese banking system (MKS) to measure banks’ market power McShane and Sharpe (1985) and Maudos and De-Guevara (2004) suggest a positive relation between market power and net interest margins Suspecting that the restructuring process in the Vietnamese banking system can significantly affect banks’ operation, we include a dummy variable (DRES) that is equal to one for the period 2012-2016 and equal to zero for the remaining years Regarding empirical methodology, we firstly employ pooled OLS (Ordinary Least Square) estimators to estimate the coefficients of explanatory variables However, in panel data analysis, unobserved heterogenity can cause pooled OLS estimators become inefficient and inconsistent Therefore, we respectively use fixed effects model (FEM) and random effects model (REM) to control for this empirical issue We conduct F-test (pooled OLS versus FEM), Hausman test (FEM versus REM) and Breusch and Pagan Lagrangian test (pooled OLS versus REM) to select the most appropriate estimation method among them Furthermore, to achieve more robust results, we use Feasible General Least Square (FGLS) estimators to control for heteroskedasticity and autocorrelation 3.2 Data description The study uses data on bank specific variables from the annual financial reports of 24 commercial banks for the period 2007-2016 These 24 banks account for 65% of the total assets of Vietnamese commercial bank system in 2016 Due to some missing observations, our unbalanced panel dataset consists of 227 observations The data on macroeconomic variables including the inflation rates and the real Gross Domestic Product are collected from Asian Development Bank dataset Table below presents the descriptive statistics for our sample while the correlation matrix of variables is provided in Table 712 | ICUEH2017 Table Sample descriptive statistics Variables Number of observations Mean Standard deviation Minimum value Maximum value NIM CR LIQ GDP INF LAR CI CAP 227 227 227 227 227 227 227 227 0.026 0.013 0.204 6.163 9.575 0.527 0.497 0.110 0.011 0.006 0.117 0.935 6.296 0.129 0.150 0.058 0.004 0.001 0.052 5.200 2.500 0.194 0.162 0.043 0.067 0.037 0.607 8.500 23.000 0.852 0.927 0.371 MKS DRES 227 227 0.043 0.471 0.050 0.500 0.002 0.000 0.233 1.000 Table Correlation matrix of variables NIM GDP CR LIQ CR*GDP LIQ*GDP INF LAR CI NIM 1.000 GDP -0.175 1.000 CR 0.0845 -0.321 1.000 LIQ -0.245 0.288 -0.269 1.000 CR*GDP 0.0513 -0.086 0.958 -0.237 1.000 LIQ*GDP -0.274 0.537 -0.342 0.951 -0.259 1.000 INF 0.0872 0.018 -0.034 0.364 -0.023 0.303 1.000 LAR 0.3930 0.005 -0.076 -0.539 -0.058 -0.469 -0.132 1.000 CI -0.185 -0.396 0.087 -0.314 -0.012 -0.382 -0.123 -0.050 1.000 CAP 0.3220 0.080 -0.267 0.134 -0.274 0.157 0.234 CAP 0.125 -0.086 1.000 MKS DRES Tran Phuong Thao et al | 713 NIM GDP CR LIQ CR*GDP LIQ*GDP INF LAR CI CAP MKS DRES MKS -0.057 0.016 0.366 -0.200 0.419 -0.190 -0.037 0.243 -0.227 -0.470 1.000 DRES 0.0652 -0.429 0.234 -0.569 0.120 -0.588 -0.615 0.088 0.498 -0.218 0.042 1.000 Empirical results 4.1 Time series of net interest margins in Vietnam Average NIM and real GDP growth rates 12.0000 10.0000 8.0000 6.0000 Average NIM (%) 4.0000 2.0000 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 Figure NIM over business cycle To capture the time series of net interest margins in Vietnam, the study computes the average of banks’ net interest margins for each year Figure provides the information of the average net interest margins in Vietnam over business cycle It could be seen that the average net interest margins fluctuates over the examined time It is noted that the average net interest margin gradually increases from 2007 to 2009 whereas this period witnesses a decrease in the growth rates of real GDP On the contrary, during the post crisis period (2010-2012) with a drop in the real GDP growth rates, there is an upward trend of the average net interest margins in Vietnam The findings presented in Model are consistent with our hypothesis Specifically, GDP shows its significant and negative effects on NIM, revealing that net interest margins in Vietnam are countercyclical, i.e they increase in bad economic condition This leads to the difficulty to invest and produce at macro level while discouraging savers to deposit their funds because of the bigger gap between loan rates and deposit rates The contraction period, hence, is likely to be lengthened In other words, net interest margins in Vietnam can be considered as an “amplifier” of aggregate 714 | ICUEH2017 shocks, which is similar to external finance premium in the seminal studies of Bernanke and Gertler (1989) and Bernanke et al (1999) Therefore, it could be argued that banks’ intermediation role is less efficient in the bad time There is no significant change in our results in terms of the signs of relations and p-values for the Model 2.1 and Model 2.2 when we respectively include the interaction terms of LIQ and GDP, CR and GDP into the model Interestingly, the business cycle affects not only net interest margins but also the association between credit risk and net interest margins In table 5, CR*GDP shows positive and significant effects on NIM, suggesting that higher credit risk raises more net interest margins in booms than in recessions This finding may be due to that banks with higher credit risk find it easier to charge more borrowing cost to offset the risk exposure in a good economic condition than in a bad economic condition Table Estimation results on the moderating effect of business cycle and liquidity risk on net interest margin Variables Model 2.1 Pooled OLS FEM REM FGLS Intercept 0.0244** 0.0245** 0.0250** 0.0244** GDP -0.0014** -0.0013* -0.0013* -0.0014* LIQ*GDP -0.0018* -0.0013 -0.0015 -0.0018 CR 0.2450** 0.3747** 0.3293** 0.2450** INF 0.0004 0.0004** 0.0004** 0.0004** LAR 0.0291** 0.0240** 0.0252** 0.0291** CI -0.0304** -0.0278** -0.0285** -0.0304** CAP 0.0390** 0.0212 0.0274** 0.0390** MKS -0.0467* -0.0318 -0.0463** -0.0467** DRES 0.0062** 0.0055** 0.0057** 0.0062** Adjusted R-squared 0.4098 0.4898 0.551 F-Statistic/Wald.Chi2 1382.17 9.64 108.63 157.58 Prob(F-statistic)/Prob.Chi2 0.000 0.000 0.000 0.000 **, * indicate significant levels of 5% and 10% respectively Tran Phuong Thao et al | 715 Table Estimation results on the moderating effect of business cycle and credit risk on net interest margin Variables Model 2.2 Pooled OLS FEM REM FGLS Intercept 0.0294** 0.0307** 0.0308** 0.0294** GDP -0.0022** -0.0022** -0.0022** -0.0022** CR*GDP 0.0430** 0.0602** 0.0546** 0.0430** LIQ -0.0109* -0.0086 -0.0096 -0.0109 INF 0.0004 0.0004** 0.0004** 0.0004** LAR 0.0292** 0.0237** 0.0251** 0.0292** CI -0.0304** -0.0281** -0.0287** -0.0304** CAP 0.0388** 0.0215 0.0274** 0.0388** MKS -0.0481* -0.035 -0.0478** -0.0481** DRES 0.0061** 0.0055** 0.0057** 0.0061** 0.412 0.5037 0.553 2147.17 9.72 109.79 159.04 0 0 Adjusted R-squared F-Statistic/Wald.Chi2 Prob(F-statistic)/Prob.Chi2 Note: **, * indicate significant levels of 5% and 10% respectively The signs of coefficients of control variables are the same with our expectation and with the results in most previous studies, except MKS, the proxy for banks’ market power and CAP, the ratio of equity to total assets In the case of Vietnamese banks, market power shows a negative effects on net interest margins A potential explanation is that the Vietnamese bank market is dominated by a few and highly efficient banks with very high proportions of market share whereas the majority of banks share insignificant market power resulting in an inefficiency in cost management Additionally, it is possible that the Vietnamese banks compete to achieve more market shares and hence, they are willing to reduce the loan rates while increasing the deposit rates to attract more customers, resulting in lower net interest margins Similarly, the negative relation between net interest margins and equity ratio is not supported It could be argued that equity capital in the Vietnamese banks shows its advantages over its costs In other words, higher proportions of equity capital to total capital motivate the interest of banks’ shareholders to control and monitor banks’ operation, leading to higher net interest incomes This finding is similar to the case of Egyptian banks (Naceur & Kandil, 2009) 716 | ICUEH2017 Our results also point out that net interest margins are significantly affected by most control variables although the argument that banks hold more liquid assets have lower net interest margins is not statistically supported This finding is not in line with Angbazo (1997) but similar to Williams (2007) and Doliente (2005) Credit risk, the inflation rates and banks’ loan size enter positively and significantly as our expectation The dummy variable for the period of bank market restructuring in Vietnam (DRES) shows a significant and positive impact upon bank net interest margins, revealing that the policies to restructure banking system in Vietnam after the crisis increase banks’ interest income and reduce banks’ interest costs Conclusion This paper mainly addresses the questions on the relationships between bank risks, net interest margin and business cycle in Vietnam The analysis on 24 commercial banks for the period 2007-2016 suggests that net interest margins are countercyclical in the Vietnamese banking context The margins significantly increase during recessions On the one hand, higher net interest margins can offset the risks banks face during a bad economic condition On the other hand, at macro level, they can exacerbate the adverse influence of aggregate shocks Our results also suggest that business cycle significantly impacts upon the relation of credit risk and net interest margins The positive effects of credit risk on net interest margins are greater in booms than in recessions In the banking system with high intervention from central bank as Vietnam, these findings provide important implications for interest rate policies In recessions, higher net interest margins make banks’ intermediation role become less efficient Therefore, interest rate polices should be made and implemented to balance the interests of borrowers and depositors, increasing banks’ contribution to the economy as efficient intermediaries in financial system Our study can not avoid some limitations Firstly, our sample accounts for 65% of the total assets of the Vietnamese banking system for the period 2007-2012 One should extend the time series and cross-sectional dimensions of the data to fully capture the cyclical behavior of net interest margins in Vietnam Secondly, we suspect there is a persistence of net interest margins over the time, i.e the relation between net interest margins and their lagged values However, the limitation in our data, especially in terms of time series dimension, prevents us from including the lagged value of net interest margins as an explanatory variable More profound studies in the future should consider these issues to shed the light on the effects of business cycle on net interest margins in Vietnam Tran Phuong Thao et al | 717 References Afanasieff, T S., Lhacer, P M., & Nakane, M I (2002) The determinants of bank interest spread in brazil Money Affairs, 15(2), 183-207 Aliaga-Díaz, R., & Olivero, M P (2011) The cyclicality of price-cost margins in banking: An empirical analysis of its determinants Economic Inquiry, 49(1), 26-46 Angbazo, L (1997) Commercial bank net interest margins, default risk, interest-rate risk, and off-balance sheet banking Journal of Banking & Finance, 21(1), 55-87 Aydemir, R., & Guloglu, B (2017) How banks determine their spreads under credit and liquidity risks 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Paper presented at the EcoMod2003-International Conference on Policy Modeling Naceur, S B., & Kandil, M (2009) The impact of capital requirements on banks’ cost of intermediation and performance: The case of egypt Journal of Economics and Business, 61(1), 70-89 Nassar, K B., Martinez, E., & Pineda, A (2014) Determinants of banks' net interest margins in honduras: International Monetary Fund Saunders, A., & Schumacher, L (2000) The determinants of bank interest rate margins: An international study Journal of International Money and Finance, 19(6), 813-832 Turgutlu, E (2010) Cyclical behavior of price–cost margins in the turkish banking industry Economic Modelling, 27(1), 368-374 Williams, B (2007) Factors determining net interest margins in australia: Domestic and foreign banks Financial Markets, Institutions & Instruments, 16(3), 145-165  ... between bank net interest margins and bank risks in Vietnam 708 | ICUEH2017 The results show that bank net interest margins in Vietnam are countercyclical Another interesting finding is that business. .. of these risks on net interest margins over business cycle Thus, the cyclical behavior of net interest margins as well as the effects of bank risks on bank net interest margin over business cycle... margin during business cycle in the Vietnamese banking sector Methodology 3.1 Variables and models To examine the relationship between net interest margin, bank risks and business cycle, three