Determinants of liquidity in nationalised banks of india

Determinants of liquidity in nationalised banks of India Shyam Bhati 1and Anura De Zoysa School of Accounting, Economics and Finance University of Wollongong Wollongong, NSW2522 Australia and Wissuttorn Jitaree School of Accounting, Faculty of Business Chiang Mai University Chiang Mai, Thailand 50300 Abstract The purpose of this paper is to identify the determinants of liquidity among government owned nationalised banks in India Nationalised banks in India are the biggest group of banks and any issue with nationalised banks can have the potential of affecting liquidity of entire banking system in India The data covers a period from 1996 to 2012 Results of OLS regression show that the most significant factors influencing liquidity in nationalised banks of India are: call rate, cash reserve ratio and statutory liquidity ratio, gross domestic products, among the macroeconomic factors and capital to total assets and log of total assets for bank specific factors Others factors have very little influence on liquidity of banks in India Cash reserve ratio has a positive and expected relationship with liquidity ratios As such statutory liquidity ratio are not very effective instruments of managing liquidity in nationalised banks of India Supervision of each bank may become necessary for proper implementation of regulatory measures in India E-mail: sbhati@uow.edu.au, Phone: 61 42215383 Determinants of liquidity in nationalised banks of India Introduction In recent years, many banks around the world have faced liquidity problems mainly due to mismanagement of liquidity The liquidity position of banks as a major issue became apparent aftermath of the global financial crisis, which resulted a number of major commercial banks with serious liquidity issues went bankrupt According to Reserve Bank of India guidelines (2012) “liquidity is a bank’s capacity to fund increase in assets and meet both expected and unexpected cash and collateral obligations as they become due.” Liquidity risk, according to RBI guidelines is the inability of banks to meet such obligations as they become due without adversely affecting the bank’s financial conditions.” According to Mohan (2006), conduct of monetary policy and liquidity management has proved to be very difficult task for India after the financial liberalisation in 1991 Prior to this period, monetary policy was not a major issue in India as exchange rate was controlled and most interest rates were fixed administratively, portfolio flows were not permitted and foreign direct investment was negligible in India However, after the start of financial liberalisation in 1991, economy was opened, interest rates were deregulated and foreign exchange rates were allowed to be market driven With these changes, liquidity management in Indian banks has become critical due to significant fluctuations in exchange rates and volatility in interest rates Although banks in India have been able to manage their liquidity profile based on asset management guidelines of Reserve Bank of India, issues relating to liquidity management in Indian banks are largely unknown as there has been no prior study on the liquidity management of Indian banks Therefore, the purpose of this paper is to examine the determinants of liquidity in Indian commercial banks for the period from 1996 to 2012 Literature Review A number of authors have studied different aspects of liquidity management in banks across countries A paper by Bank for International Settlement (BIS, 2010) lays down the framework for liquidity risk management by banks and presents the reforms undertaken by BIS to strengthen the global capital and liquidity regulations The purpose of this framework is to improve the banking sector’s ability to absorb shocks arising from financial and economic stress BIS has set two standards for funding liquidity through this framework The first is the development of liquidity coverage ratios for improving short term resilience of bank’s liquidity risk by ensuring that a bank has high liquid assets to meet its liabilities in short term The second standard is about developing Net Stable Funding Ratio (NSFR) which will help in promoting resilience of a bank over a longer time period (time horizon of one year and above) and provide a sustainable maturity structure of assets and liabilities Following BIS regulation, Reserve Bank of India (2012) has laid down theoretical principles for management of liquidity for Indian banks The RBI framework provides for development of a sound liquidity system RBI stipulates that banks in India should develop strategy, policies and practices to manage liquidity risk based on risk tolerance of the bank A bank should identify, measure, monitor and control liquidity risk by projecting cash flows arising from assets, liabilities and off balance sheet items Banks are required to manage liquidity risk and funding needs across legal entities, business lines and currencies considering the fact that liquidity is not easily transferred across business units The study conducted by Aspachs et al (2005) to investigate how central bank’s Lender of Last Resort (LOLR) policy may affect banks’ liquidity provides an analysis of determinants of UK banks’ liquidity policy The study test for liquidity moral hazard which arises when banks hold lower liquidity buffers than they otherwise would when they expect to receive assistance from the LOLR and found strong evidence of the presence of liquidity moral hazard This study also found evidence to the effect that bank liquidity buffers are countercyclical Banks appear to build liquidity buffers in periods of weak economic growth and draw buffers in periods of strong economic growth The study revealed that that banks hold large buffers when short term rates are low and small buffers when short term rates are high In their opinion, banks hoard funds when current profits are high and future lending opportunities are good Banks have an incentive to increase their liquidity holdings in recession and decrease liquidity holdings in booms In addition, they found that foreign owned banks in UK manage their liquidity centrally and that UK branches and subsidiaries of foreign owned banks use group internal capital market to raise funding as and when needed The study by Valla et al (2007) presents an asset based measure of bank liquidity with the purpose of capturing and quantifying the dynamics of liquidity flows within French banking system between 1993 and 2005 They conclude that, on an average, positive flows of liquidity have been greater than negative flows of liquidity in French banking system resulting in net nominal liquidity flows growing by 1% every quarter between 1993 and 2005 Substantial liquidity expansion and contraction was observed to have taken place in the order of 6% to 5% per quarter implying an active market, trading beyond substantial growth in bank liquidity It observes that this trading intensity has occurred in all market segments involved in liquidity trading which includes money market and capital markets Large outflows occurred in 1996 and 2000 and increases in liquidity were noticed which later translated into negative liquidity adjustments Rauch et al (2009) examines the way in which macroeconomic factors and central bank’s monetary policy influence the creation of liquidity in the savings banks in German savings banks from the period 1997 to 2006 They measure the liquidity created and its determination using GMM framework focusing on bank specific factors as well as macroeconomic factors and found that over the period from 1997 to 2006 the total amount of liquidity created in German savings banks increased by 51% They also found that liquidity creation in these banks depend negatively on monetary policy indicators A tightening of monetary policy induces the decrease in liquidity creation However, this study did not find any bank specific factors to have any influence on liquidity creation Vodova (2011 & 2012) examined the determinants of liquidity of commercial banks in Slovakia and Czech Republic through four liquidity ratios and related them with bank specific and macroeconomic data over a period from 2001 to 2010 These two studies observed drop of banks’ liquidity as a result of the Gobal Financial Crisis The study reveals that the share of liquid assets in total assets and liquid liabilities in deposits and short term funding decreases with bank profitability, higher capital adequacy and bigger size of banks In their opinion big banks rely on the interbank market and on liquidity assistance of Lender of Last Resort (LOLR) Liquidity measured by share of loans in total assets and in deposits and short term borrowings increases with growth of domestic product They did not find any significant relationship between interest rates on loans, interest rate on interbank transactions or monetary policy interest rates, interest rate margins, the share of non-performing loans and the rate of inflation with liquidity of Slovak banks In another study from Pakistan, Malik and Rafique (2013) examines bank specific and macroeconomic determinants of commercial bank liquidity in Pakistan Their study period covers from 2007 to 2011 They have used two models of liquidity The first L1 is based on cash and cash equivalents to total assets The second model L2 is based on advances net of provisions to total assets Their results suggest that Non Performing Loan (NPL) and Return on Equity (ROE) have a negative and significant effect coefficient with L1 Capital (CAP) and inflation (INF) are negatively and significantly correlated and Total Assets (TOA) Return on Equity (ROE) are significantly and positively correlated with L2 Their results of model suggests that bank specific factors NPL and TOA and monetary policy interest rates positively determine the bank liquidity whereas the inflation has a negative effect Bank liquidity is also affected by financial crisis measured by L1 The results of model indicate that the bank size and monetary policy interest rate positively and significantly determine bank liquidity Additionally there is a significant and positive impact of financial crisis on the liquidity of commercial banks Their studies conclude that bank specific factors such as liquid assets such as liquid assets are required as bank size increases The central bank regulations greatly affect the liquidity of commercial banks which means tight monetary policy can regulate the undesirable effect of inflation on liquidity In a recent study on liquidity problems in Zimbabwean banks, Chagwiza (2014) found that there is a positive link between bank liquidity and capital adequacy, total assets, gross domestic product and bank rate Adoption of multi-currency, inflation rate and business cycle has negative impact on liquidity Bank size and their liquidity is positively correlated Liquidity management in Indian context has not received much attention as there is hardly any literature on liquidity management in Indian banks Mohan (2006) identified issues relevant to liquidity management in Indian financial system After the financial system reforms started in India in 1991, India was able to sustain capital inflows which helped Indian central bank to smooth out interest rates Introduction of Liquidity Adjustment Facility (LAF) helped India to manage liquidity and reduce volatility in the capital flows and short term interest rates India evolved Market Sterilisation Scheme (MSS) to sustain open market operations, which helped monetary authorities to manage liquidity cycles Indian monetary authorities also developed instruments such as Collateralised Borrowings and lending Obligations, market repo, interest rate swaps, Certificates of deposits and Commercial papers which helped the central bank meet liquidity needs The central bank has also undertaken has developed link between overnight interest rates and T-bills and liquid dated securities The lending and deposit rates have also helped in mopping up excess liquidity in Indian financial system The central bank through its monetary policy has been able to exercise control over short term interest rates and reduce their volatility In spite of many reforms, inflation rate in India remains a challenge for liquidity management Also due to central bank operations moral hazard is an issue because some market players may take excessive risk in managing their own liquidity when LAF is available from central bank Also Statutory Liquidity Ratio is being gradually reduced by Reserve Bank of India, some of the market players are not covered by SLR creating liquidity gaps in part of financial markets The central bank— Reserve Bank of India (RBI)—has used Cash Reserve ratio (CRR), Statutory Liquidity ratio (SLR) and bank discount rate (bank rate) as instruments of liquidity management for a long time Although these instruments have been used by central bank, their relationship with liquidity levels have not been studied in India Since there is no previous study on determinants of liquidity in commercial banks of India, it is worthwhile to study these issues in regard to Indian Banking system Our current study focuses on the determinants of liquidity in nationalised banks of India because these banks are government owned and have biggest branch network in India There are 2o nationalised banks in India with a branch network of 54478 branches constituting biggest banking groups in India Methodology We use balance sheet and profit and loss data for a panel of 20 Indian resident banks on a yearly basis over the period 1996 to 2012 These data relate to banks’ Indian resident activity The data was obtained from Reserve Bank of India (2012a) The data was adjusted for opening of new banks, bank mergers and bank consolidations A total of 330 observations were recorded for 20 banks Our measure of liquidity is similar to the one described by Aspach et al (2005) and Vodova (2011) and modified to the Indian context Liquid assets consists of cash, bank balance including balance with Reserve Bank of India, bills purchased and money at call and short notice Table summarises the set of variables used by us to test the relationship We have constructed four alternative liquidity ratios The liquidity ratio L1 gives us the information about banks’ ability to meet its liabilities in short term The higher is the proportion of liquid assets in total assets, the higher is the bank’s ability to meet its liquidity needs in short term The high value of liquid assets may also be taken as banks inefficiency of the bank as liquid assets provide less income for the bank The second ratio L2 uses the relation between liquid assets and deposits and short term borrowings This ratio gives us the banks sensitivity to sources of funding such as deposits short term borrowings including bills payable The bank is able to meet its liquidity obligations if this ratio is 100% or more Low value could indicate that the bank is sensitive to withdrawal of deposits The third ratio L3 measures the proportion of loans in total assets A high ratio indicates that bank’s liquidity is less The last ratio L4 indicates the proportion of illiquid assets (loans) with liquid liabilities such as deposits, short term borrowings and bills payable A high ratio indicates lack of liquidity with the bank The selection of variables was based on previous relevant studies However, it was important to know which variables made economic sense in Indian context For example, Aspach (2005) considered probability of obtaining support from lender of last resort, interest margin, bank profitability, loan growth, size of bank, gross domestic products and short term interests rates as relevant variables Rauch et al (2009) considered monetary policy interest rates, level of unemployment, saving quota, level of liquidity in previous periods, size of banks and bank profitability as relevant variables in their study Vodova (2012) defined their variable in terms of bank specific factors and macroeconomic factors For bank specific factors they used share of own capital on total assets, share of non-performing loans on total volume of loans, return on equity and logarithm of assets For macroeconomic variables they considered FIC as dummy variable for realisation of financial crisis, growth rate of gross domestic product, inflation rate, interest rate on loans, difference between interest rate on loans and interest rate on deposits, monetary policy interest rate and unemployment rate as relevant variables We have considered four bank specific variables and four macroeconomic variables in this study Our expectation on positive and negative impact of variables on liquidity is given in Table Lit= αi + β1 Callrateit+ β2 CRRit+ β3 SLRit+ β4 GDPit+ β5 CapitalTAit +β6 LogTAit +β7 ROEit+β8 NPAAdvit + μit The variables are defined in table αi are constant and βi are coefficients μit is an error term and Lit is one of the four liquidity ratios in time t The multicollinearity test was conducted to detect the correlation among financial performance indicators, liquidity ratios and the variables The multicollinearity is examined to discover that independent variables are not highly correlated and no multicollinearity among independent variables was found to exist This study tested for pooled OLS model The results are given in next section Results and discussions We use an econometric package Stata 12 The descriptive statistics for variables for banks are given in table We use estimates separately for each of four defined ratios for nationalised banks The aim is to find high adjusted coefficient of determination and simultaneously the variables are statistically significant As can be seen from table 3, results of analysis suggest that each liquidity ratio depends on different factors Table shows the results for nationalised banks The results of analysis suggest that the explanatory power of model is very high The liquidity ratio L1 has significant relationship with call rate, cash reserve ratio (CRR), capital to total assets, gross domestic product GDP, and total assets and non-performing assets (NPA/Advances) L1 has a positive relation with cash reserve ratio, and total assets only, and negative coefficients with call rate, capital to total assets, GDP and NPA/Advances Signs of coefficients for cash reserve ratio, statutory liquidity ratio, gross domestic product and NPA/Advances are as expected although the coefficients for call rate and capital to total assets are not as expected Further, small banks with less capital may have more liquidity The liquidity in nationalised banks may decrease with increase in call rate, and gross domestic product The ratio L2 has significant relationship with cash reserve ratio(CRR) gross domestic product (GDP) , capital to total assets and total assets but no relationship with call rate, SLR, NPA/Advance and ROE The reason could be that nationalised banks may not depend on short term money market for borrowings and could borrow from each other for short term needs The ratio L3 has significant relationship with call rates, CRR, SLR, gross domestic product, capital to total assets, total assets and NPA/Advances The relation with call rate, SLR, LogTA is as expected and the relation with gross domestic product is opposite to what was expected The last model L4 also has a high explanatory power The ratio L4 has significant relationship with call rate, SLR, GDP, capital/TA and total assets The relation with call rate, SLR, GDP and Log TA is positive but there is a negative relationship with capital to total assets Signs of coefficients for CRR, GDP and capital to total assets not correspond with the expected signs Summary and conclusions We have examined the determinants of liquidity in nationalised banks of India The explanatory power of models for nationalised banks is high The most significant factors influencing liquidity in nationalised banks are: call rate, CRR and gross domestic products, among the macroeconomic factors and capital to total assets and log of total assets for bank specific factors SLR has very little influence on liquidity of nationalised banks in India and ROE has no influence on liquidity Cash reserve ratio has a positive and expected relationship with liquidity ratios L1 and L2 but negative relationship with L3 and L4 This suggests that cash reserve policy of Reserve Bank of India is working to influence the liquidity of nationalised banks in India Statutory liquidity ratio, however does not have a clear relationship with liquidity ratios as it has relationship with L3 and L4 only In the absence of any clear relationship it is hard to suggest that statutory liquidity ratio as an instrument of liquidity is effective or not Increase in gross domestic product has a positive influence on liquidity ratios while increase consumer price index has a negative influence on liquidity ratio L1 but positive relationship with L3 and L4 of nationalised banks in India Among the bank specific factors capital to total assets has a negative effect on liquidity of nationalised banks while the relationship with Log of total assets is positive with all liquidity ratios This suggests that larger nationalised banks may have higher levels of liquidity Among the four liquidity ratios L1 and L3 seems to have more significant relationship with determinants of liquidity as compared to L2 and L4 Both L1 and L3 are ratios based on assets based liquidity while L2 and L4 are based on liability based liquidity It is clear that asset based liquidity is more prominent for nationalised banks as compared to liability based liquidity References Aspach, O., E.Nier and Muriel Tiesset (2005), “Liquidity, banking regulation and macroeconomy: Evidence on bank liquidity holdings from a panel of UK-resident banks.” Available at http://www.bis.org./bcbs/events/rtfo5AspachsNier Tiesset.pdf Bank for International Settlement, (2010), ‘Basel III: International framework for liquidity risk measurements, standards and monitoring” Basel Committee on banking Supervision, p 1-48 Bank for International Settlement (2011), “Global liquidity – concept, measurement and policy implications.” Committee on the Global Financial System, CGFS papers No 45, November 2011 Chagwiza, W (2014), “Zimbabrean commercial bank’s liquidity and its determinants” International Journal of Empirical Finance, Vol 2, no 2, p 52-64 Distinguin, I., C.Roulet and A.Tarazi (2011), “bank capital buffer and liquidity: Evidence from US and European publicly traded banks” Malik M.F and A Rafique (2013), “Commercial banks liquidity in Pakistan: Firm specific and Macroeconomic Factors” The Romanina Economic journal, Vol XVI, no 48, 139-154 Mohan, Rakesh (2006), “Coping with liquidity management I India: A practioner’s view.” Eights Annual Conference on Money and banking in India Economy, Indira Gandhi Instritute of Development Research, May 27, 2006 Rauch C., S Stephen, A Hackethal and M.Tyrell (2009), “Saving banks, liquidity creation and monetary policy.”, Available at http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1343595 Reserve bank of India (2012), “Draft guidelines on liquidity risk management and Basel.III Framework on liquidity standards.” Department of banking operations and development, Reserve bank of India, Mumbai Reserve Bank of India (2012a), “Database on Indian economy, Banking Statistics” Department of Statistics and Information management, http;//dbie.rbi.org.in/DBIE Valla, Natacha, Beatrice Saes-Escorbiac and Muriel Tiesset (2007), “bank liquidity and financial stability” IFC Bulletin no 28, p 40-47 Vodova, P (2011), “Liquidity of Czech commercial banks and its determinants” International Journal of mathematical models and Methods in Applied Sciences, p 1060-1067 Vodova, P (2012), “Determinants of commercial bank’s liquidity in Slovakia” Czech Scientific Foundation project GACR P403/11/P243: Liquidity risk of commercial banks in Visegrad countries Vodova, P (2013), ‘Determinants of commercial bank’s liquidity in Hungary” Financial Internet Quarterly e-Finance Vol 9, No 3, P.64-71 Table Variable Definition Variables Definitions L1 L2 L3 L4 𝐿1 = L2 𝐿𝐿𝐿𝐿𝐿𝐿 𝐴𝐴𝐴𝐴𝐴𝐴 𝑇𝑇𝑇𝑇𝑇 𝐴𝐴𝐴𝐴𝐴𝐴 Liquid Assets = Deposits + Short term borrowings + Bills Payable L3 = L4 Loans Total Assets Loans = Deposits + Short term borrowings + Bills Payable Source Estimated Effect Bank Annual Reports Bank Annual Reports Bank Annual Reports Bank Annual Reports Bank specific Variables Capital TA Capital/Total Assets Bank Annual Reports + ROE Return on Equity (Net Profit/Total Equity) Bank Annual Reports - NPA/Adv Non-Performing Loans/Total Loans Bank Annual Reports - LogTA Logarithm of Total Assets + Macroeconomic Variables Call rate Lending rate for money at call and short notice RBI + CRR Cash Reserve Ratio of RBI RBI + SLR Statutory Liquidity Ratio of RBI RBI + GDP Gross Domestic Product of India RBI - NPA Advances Non- performing loans to total advances RBI - Table Descriptive Statistics for variables - Nationalised Banks Standard Variable Mean Maximum Deviation Number of Observations Minimum L1 0.13 0.33 0.06 0.05 330 L2 0.15 0.44 0.01 0.05 330 L3 0.49 0.68 0.22 0.11 330 L4 0.55 4.40 0.11 0.24 330 Callrate 8.54 28.75 3.51 5.84 330 CRR 7.06 14.00 4.50 2.63 330 SLR 25.57 31.50 24.00 2.18 330 GDP 30957.10 52435.82 17377.40 10701.52 330 CapitalTA 0.06 0.38 0.01 0.03 330 LogTA 6.68 7.66 5.84 0.41 330 ROE 0.13 1.15 1.26 0.16 330 NPAAdvances 4.50 26.01 0.00 4.71 330 10 Table 3: Results of Pooled OLS Regression Analysis Independent Variables L1 L2 L3 L4 Callrate -0.00104*** (-2.956) -0.000710 (-1.465) 0.00266*** (5.573) 0.00668** (2.213) CRR 0.0124*** (10.76) 0.0133*** (9.998) -0.00352** (-2.118) -0.00523 (-1.347) SLR 0.000873 (0.838) 0.00147 (1.170) 0.00433*** (2.777) 0.00902** (2.181) GDP -2.96e-06*** (-11.62) -3.09e-06*** (-8.177) 5.38e-06*** (14.35) 8.48e-06*** (2.712) CapitalTA -0.185** (-2.088) -0.188*** (-3.366) -0.401** (-2.132) -0.976*** (-2.591) LogTA 0.0325*** (4.455) 0.0454*** (4.832) 0.0734*** (8.395) 0.163*** (2.829) ROE 0.000450 (0.0365) 0.0664 (1.347) -0.00504 (-0.200) 0.658 (1.187) NPAAdvances -0.00297*** (-5.266) -0.00123 (-0.890) -0.00462*** (-4.017) 0.0137 (0.950) Constant -0.0678 (-1.310) -0.175** (-2.073) -0.230*** (-3.383) -1.142* (-1.660) 330 330 330 330 0.658 0.614 0.851 0.425 70.59 74.83 285.70 57.13 0.0000 0.0000 0.0000 0.0000 Observations R-Squared F-Statistic P-Value Robust t-statistics are reported in parentheses * Indicate statistically significant at the 10% level ** Indicate statistically significant at the 5% level *** Indicate statistically significant at the 1% level 11 .. .Determinants of liquidity in nationalised banks of India Introduction In recent years, many banks around the world have faced liquidity problems mainly due to mismanagement of liquidity The liquidity. .. on determinants of liquidity in commercial banks of India, it is worthwhile to study these issues in regard to Indian Banking system Our current study focuses on the determinants of liquidity in. .. on liquidity management in Indian banks Mohan (2006) identified issues relevant to liquidity management in Indian financial system After the financial system reforms started in India in 1991, India