This study investigates the causes of liquidity risk and the relationship between bank liquidity risk and performance for 12 advanced economies over the period 1994-2006. In the causes of liquidity risk model, we divide the causes of liquidity risk into bank-specific, supervisory and macroeconomic factors. Besides, the model is estimated through fixed effects regression. In the bank liquidity risk and performance model, we regard liquidity risk as an endogenous determinant of bank performance, and apply panel data instrumental variables regression to estimate this model. We also consider another factors affect bank performance besides liquidity risk. Besides, we divide these factors into bank-specific factors, market structure factors, supervisory factors, and macroeconomic conditions.
We find that liquidity risk is the endogenous determinant of bank performance.
Besides, the causes of liquidity risk include components of liquid assets and dependence on external funding, supervisory and regulatory factors and macroeconomic factors. Besides, we also find that liquidity risk may lower bank profitability (ROAA and ROAE), but increase bank’s net interest margins (NIM).
The empirical results of causes of liquidity risk model indicate that large banks have incentive to hold more loans thus have larger financing gap ratio. However, over the limit point the effect of size becomes negative. Thus, the effect of size on liquidity risk is non-linear. Banks with much less risky liquid assets and risky liquid assets can reduce their liquidity risk. Besides, banks depend heavily on the external funding face much severe liquidity problem. Thus banks should diversify their funding sources to reduce liquidity risk. In regulation and supervision, we can find that countries with greater official power, higher restrictiveness make their banks suffer less liquidity risk.
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However, we find no evidence that regulatory empowerment of private monitoring of banks has significantly impact on liquidity risk. Thus, we can find that direct government supervision and regulation of bank activities could reduce bank liquidity risk. About macroeconomic environment, the results indicated that banks run down their liquidity buffer in boom because they increase their loans but attract less customer deposits in this period.
The empirical results of bank liquidity risk and performance show that liquidity risk may lower bank profitability (ROAA and ROAE). Banks with larger gap lack stable and cheap fund, and thus they have to use liquid assets or much external funding to meet the demand of fund, increase bank’s cost of funding. It consequently decreases bank’s profitability. However, liquidity risk will increase bank’s net interest margins. (NIM) It indicated that banks with high levels of illiquid assets in loans may receive higher interest income. The effect of size provides evidence of economies of scale in banking. However, over the optimum point the effect of size becomes negative due to bureaucratic. Thus, the effect of size on bank performance is non-linear. The results also indicated that capital strength of banks has a positive and dominant impact on their performance. We can find that increase exposure to credit risk will lower their profitability (ROAA and ROAE). However, credit risk has the positive effect on bank’s net interest margins. It provides that credit risk requires banks to apply a risk premium implicitly in the interest rates charge.
About market structure, the effect of concentration is positive using ROAA and ROAE as the dependent variable, which provides evidence to support the structure-conduct-performance (SCP) hypothesis. Turning to supervision and regulation, the results support that greater official power, greater regulatory empowerment of private monitoring of banks, higher restrictiveness can increase
52
bank’s performance.
About macroeconomic environment, the results indicated that economic boom has significantly positive effect on bank performance. Inflation is anticipated by the inflation change of last year, thus give banks the opportunity to adjust interest rates accordingly, and consequently increase their performance.
The financing behavior is very different between bank-based and market-based financial system. In our study, we classify countries as bank-based or market-based system, and investigate the difference of causes of liquidity risk in different financial systems. The empirical results indicated that the bank-specific variable has the same effect on bank liquidity risk in two financial systems. About supervision and regulation, it provides that greater official power, higher activity restrictiveness will diminish bank liquidity risk in market-based financial system. However, we find that greater regulatory empowerment of private monitoring of banks will increase bank liquidity risk in market-based financial system. Regarding macroeconomic environment, the results indicates that economic boom make banks in market-based financial system run down their liquidity buffer, but macroeconomic has no effect on bank liquidity risk in bank-based financial system.
We also investigate the effect of financial system on bank performance. The empirical results show that market-based system has the positive effect on bank performance. This indicated that stock market development may improve bank performance. The probably reason is that it allows firms to be better-capitalized, thus reducing risks of loan default, consequently increasing bank’s performance. Besides, we further investigate bank liquidity risk and performance in different financial systems. We find that liquidity risk has different effects on bank performance in different financial systems. Liquidity risk is negatively related to bank performance in
53
market-based financial system; however, it has no effect on bank performance in bank-based financial system.
Finally, we check the robustness of our results using alternative liquidity risk measures, net loans to customer and short term funding. We find that the results are almost same as the model using financing gap to total assets ratio (FGAPR).
The contribution of this study is to use another liquidity risk measures besides to liquidity ratio, and we are the first study to investigate the causes of liquidity risk.
Besides, we find that liquidity risk is an endogenous determinant of bank performance.
In subsample analysis, we further classify countries as bank-based or market-based system, and investigate the difference of causes of liquidity risk in different financial systems. Besides, we further investigate the effect of liquidity risk on bank performance in different financial systems.
However, the limitation of this study is that we just use the banks which are available from Bankscope database as our sample. Besides, banks in United States occupy most of our sample.
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Table 1 Empirical Results of the Relationship between Bank Liquidity Risk and Performance
Previous Studies Liquidity Risk Measures Empirical Results
Bourke (1989) The ratio of liquid assets to total assets The liquidity ratio is positively related to return on assets (ROA).
Molyneux and Thornton (1992) The ratio of liquid assets to total assets The liquidity ratio is negatively related to return on assets (ROA).
Demirgüç-Kunt and Huizinga (1999) The ratio of loans to total assets The ratio of loans to total assets is negatively related to return on assets (ROA) and positively related to net interest margins (NIM).
Shen, Kuo and Chen ( 2001) The ratio of liquid assets to deposits Banks with high fraction of liquid assets have lower net interest margins (NIM).
Barth, Nolle, Phumiwasana and Yago (2003) The ratio of liquid assets to total assets The liquidity ratio is negatively related to return on assets (ROA).
Demirgüç-Kunt, Laeven and Levine ( 2003) The ratio of liquid assets to total assets Banks that hold a high fraction of liquid assets have lower net interest margins (NIM). And it is consistent with banks receiving lower returns on holding cash or securities, but facing a competitive market for deposits.
Kosmidou, Tanna and Pasiouras (2005) The ratio of liquid assets to customer and short term funding
The ratio of liquid assets to customer and short term funding has positive effect on return on average assets (ROAA). It has negative effect on net interest margins (NIM) but is only significant in the presence of external factors.
Athanasoglou, Delis, and Staikouras (2006) The ratio of loans to total assets The ratio of loans to total assets has no effect on return on assets (ROA) and return on equity (ROE).
Pasiouras and Kosmidou (2007) The ratio of net loans to customer and short term funding
The ratio of net loans to customer and short term funding is positively related to return on average assets (ROAA) of domestic banks operating in the 15 European Union countries. And it is negatively related to ROAA of foreign banks.
Kosmidou (2008) The ratio of net loans to customer and short term funding
The ratio of net loans to customer and short term funding is negatively related to return on average assets (ROAA).
Naceur and Kandil (2009) The ratio of net loans to customer and short term funding
The ratio of net loans to customer and short term funding is positively and significantly related to net interest margins (NIM) of domestic banks, indicating a negative relationship between net interest margins and the level of liquid assets held by the bank. However, banks’ liquidity risk does not determine returns on assets or equity (ROA or ROE) significantly.
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Table 2 Bank Observations in Each Country and Year
Year/Country Australia Canada France Germany Italy Japan Luxembourg Netherlands Switzerland Taiwan United Kingdom United States Total
1994 17 21 151 124 76 144 51 26 144 27 41 337 1159
1995 19 24 159 135 91 144 67 22 130 28 45 363 1227
1996 20 25 153 135 91 144 61 24 140 27 51 366 1237
1997 17 29 143 147 94 137 73 24 131 31 52 388 1266
1998 16 30 132 138 102 131 68 24 117 33 46 368 1205
1999 13 29 124 121 100 127 70 20 117 38 43 358 1160
2000 14 27 113 128 99 127 68 13 110 37 48 386 1170
2001 15 24 104 129 97 125 55 20 90 34 47 373 1113
2002 14 26 98 128 94 123 35 16 89 36 51 362 1072
2003 13 25 96 113 99 122 32 19 89 38 50 321 1017
2004 12 18 87 107 103 123 26 18 92 37 45 279 947
2005 12 24 78 98 98 122 32 14 78 37 46 265 904
2006 15 23 71 102 88 121 33 15 83 32 40 260 883
Total 197 325 1509 1605 1232 1690 671 255 1410 435 605 4426 14360
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Table 3 Variable Description
Category Variable Notation Description/Calculation
Liquidity Risk Financing Gap Ratio FGAPR The ratio of financing gap to total assets. Financing gap defined as the difference between a bank's loans and customer deposit.
Liquidity Ratio NLCS The ratio of net loans to customer and short term funding.
Profitability Return on Average Assets ROAA Net profit after tax divided by average total assets.
Return on Average Equity ROAE Net profit after tax divided by average total equities.
Net Interest Margin NIM Interest income minus interest expense over earning assets.
Bank-specific Size SIZE Natural logarithm of total assets Square of Size SIZE2 Natural logarithm of total assets
squared
Less Risky Liquid Assets LRLA The ratio of less risky liquid assets to total assets. Less risky liquid assets is sum of the cash, due from central banks, treasury bills, government securities.
Risky Liquid Assets RLA The ratio of risky liquid assets to total assets. Risky liquid assets is sum of the deposits with banks, due from other banks, due from other credit institutions, other bills and trading securities.
External Funding Dependence EFD The ratio of external funding to total liabilities. We add money market funding and other funding as external funding.
Capital ETA The ratio of equity to total assets.
Credit Risk LLPL The ratio of loan loss provision to loans.
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Category Variable Notation Description/Calculation
Market structure Three-Bank Concentration Ratio (CR3)
CON The ratio of total assets of the three largest commercial banks to total assets of all commercial banks in each country.
Supervisory and Regulatory
Official Supervisory Power OSP It is used to measure of legal power of the supervisory agency. The value is principal component indicator of fourteen variables. Besides, the survey questions used to construct the official supervisory power can be found in appendix A.
Private Monitoring Index PMI It is used to measures regulations that empower private monitoring of banks.
Principal component indicator of nine variables. Besides, the survey questions used to construct the private monitoring index can be found in appendix A.
Overall Bank Activities and Ownership Restrictiveness
BAR Indicator of bank's ability to engage in business of securities underwriting, insurance underwriting and selling, and in real estate investment, management, and development.
Besides, the survey questions used to construct overall bank activities and ownership restrictiveness can be found in appendix A.
Macroeconomic Business Cycle GDPC Annual percent change of GDP Lag of Business Cycle GDPCt-1 GDP annual percent change of last
year
Inflation INF Annual percent change of inflation Lag of Inflation INF t-1 Inflation annual percent change of last
year
Dummy variable Financial system MB Market-based countries =1, otherwise
=0
Source: Bank-specific data and market structure variables are available from BankScope database. And the data unit of each bank in a given year is million U.S dollars. Supervisory variables are available
Source: Bank-specific data and market structure variables are available from BankScope database. And the data unit of each bank in a given year is million U.S dollars. Supervisory variables are available