The Purposes and Major Findings

Generally, liquidity risk measures can be calculated from balance sheet positions. In the past, better practices for liquidity risk measures focused on the use of liquidity ratios. However, Poorman and Blake (2005) indicated that it was not enough to measure liquidity just using liquidity ratios and it was not the solution. Beyond mere liquidity ratios, banks must develop a new view of liquidity measurement.

Recently, there are many methods provided to assess bank liquidity risk besides traditional liquidity ratios.

Therefore, the purpose of this study is to employ alternative liquidity risk measures besides liquidity ratio. In our study, we use financing gap measures provided by Saunders and Cornett (2006) to assess bank liquidity risk. In normal

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condition, banks seldom face the liquidity crisis, and liquidity risk may vary with overall economic environment. Besides, previous studies seldom focused on the causes of liquidity risk. Thus, another purpose of this study is to investigate the causes of liquidity risk (causes of liquidity risk model), using an unbalanced panel dataset of 12 advanced economies commercial banks over the period 1994-2006. Besides, we estimate the causes of liquidity risk model through the fixed effects regression. In this model, we use each bank’s financing gap ratio (FGAPR) as the dependent variable, and divide the causes of liquidity risk into internal and external factors as independent variable.

The empirical results 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 more 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. 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.

In addition, we further investigate the determinants of bank performance in terms of the perspective of the bank liquidity risk (bank liquidity risk and

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performance model). Previous studies regarded liquidity risk as exogenous determinant of bank performance. However, from the causes of liquidity risk model, we can find that bank liquidity risk may affected by another factors. In our study, we thus regard liquidity risk as an endogenous determinant of bank performance. Besides, we apply panel data instrumental variables regression, using two stage least squares (2SLS) estimators to estimate the determinants of bank performance model. In this model, we use return on average assets (ROAA), return on average equities (ROAE) and net interest margins (NIM) as the dependent variable. Besides, we divide the determinants of bank performance into internal and external factors as independent variable.

The empirical results 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 their cost of funding. It consequently decreases their performance. However, liquidity risk will increase bank’s net interest margins. 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 profitability is non-linear. The results also indicated that capital strength of banks has a positive 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-

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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 bank’s performance. About macroeconomic environment, the results indicated that economic boom has significantly positive effect on bank performance. The relationship between inflation annual percent change of last year and bank performance is significantly positive.

There are large differences in financial systems across countries.

Demirgüç-Kunt and Levine (1999) constructed conglomerate index of financial structure and produces two categories of countries: bank-based and market-based system. Besides, 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

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performance. Besides, we further investigate the determinants of bank performance in different financial systems. We find that liquidity risk is negatively related to bank performance in market-based financial system; however, it has no effect on bank performance in bank-based financial system.

Specifically, we explore how to measure bank liquidity risk, what are the causes of liquidity risk, what is the relationship between liquidity risk and bank performance.

Although liquidity risk is not the major risk in banks, it may cause banks to go into bankruptcy, thus we can’t ignore it as before.

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.