CONCLUSIONES Y RECOMENDACIONES

Similar to Navaretti et al. (2010), we estimate the following specification on the data during the period of the recent global financial crisis.

where the dependent variable, is the ratio of customer loans and depo- sits of foreign bank i in Malaysia at time t. Dummy_Crisis is a dummy variable taking the value of one in the period of 2007, 2008 and 2009. Dummy_Foreign_Bank is a dummy variable taking the value of one if bank i in Malaysia of country j at time t is a foreign bank subsidiary of a holding company located in country j (or region) in parentheses. With most of the home countries of the foreign banks in Malaysia being located in North America, Europe and Asia, when bank i is located from those regions, the region dummy takes the value of one. Bank_Specific_Char are characteristics of bank i of country j in Malaysia, at time t-1. The model not only tests the effect of foreign bank subsidiaries’ financial characteristics on their loan-to-deposit ratio, but it also tests whether the access to the internal capital market will affect their loan-to- deposit ratio.

In order to simplify the country factors, a region dummy is used in another equation to replace the country dummy as follows:

The model uses dummies to capture systemic differences among panel observation results in what is known as a fixed-effect model using pooled data. The data set runs from January 2000 to December 2009, amounting to 1440 monthly observations comprising 12 foreign banks in Malaysia.

The test of the effect of the global financial crisis on the internal capital market of cross-border banks is based on the sign and significance of each of

β2 coefficients with k = 1 and 2. A positive and significant value would imply

that foreign banks with access to the internal capital market would reduce their loan-to-deposit ratio less than the control group of banks6_{, and therefore would}

have a stabilising effect on a potential shock caused by the financial crisis. As for the factors of bank characteristics, we have considered the ratio of return on assets (ROA) as a measure of profitability. If β2 is positive and

significant, it may imply that banks with more profit would extend more credits. On the contrary, if β2 is negative and significant, it means that unprofitable banks

may assume more credit risks to gain greater profits. Therefore, the expected sign of the variable is indeterminate. We also considered leverage (total equity over total assets, LEVERAGE) as a measure of the bank’s risk aversion. A low leverage ratio could mean relatively risk-adverseness and the bank may extend credit more conservatively during crisis period, implying a negative relationship between bank’s leverage and loan growth. In contrast, a low leverage ratio could also represent liabilities constraints being less severe so that banks have the capability to expand lending. Therefore, the sign of leverage ratio is indeterminate. Finally, we examine the implication of the bank’s asset size (ASSETS) and growth (DLOG(ASSETS)) for loans. Table 3 summarises the definition and sources of all the variables included in the model.

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Table 3

Data Definition and Sources

Source: Bank Negara Malaysia

4.2 Empirical Results

Table 4 shows the estimation results of the models using the country and region dummy. None of the interaction coefficients between the crisis dummy and country dummy (or region dummy) is significant. The results suggest that the effect of the global financial crisis on the internal capital market of cross-

border banks may not exist in all of the foreign banks’ parent home countries and the region of North America, Europe and Asia. These findings are inconclusive in determining whether all foreign bank subsidiaries with access to the internal capital market provided stabilising effects on Malaysia in response to the shock caused by the global financial crisis. The findings could also suggest that the foreign banks in Malaysia may not be reliant on the support of internal capital of their parents.

The coefficient of D(ROA_LAG) is negative and statistically significant in both models. Given with the negative signs, less profitable banks may assume more credit risks to garner bigger profits. In addition, the positive and statistically significance of the coefficient of DLOG(ASSETS_LAG) implies that foreign banks with bigger assets would extend more credits. However, we found that D(LEVERAGE_LAG) has a negative but negligible effect.

The adjusted-R squared of both models was 1.5% and 1.8% of variance loan-to-deposit ratio of foreign banks respectively. A low adjusted-R squared could be a result of the small sample size. Nonetheless, we have identified which determinant does affect the loan-to-deposit ratio of the foreign banks during the crisis period. The value of Durbin-Watson statistics of close to 2 in both models suggests that autocorrelation correction is not needed.

Table 4: Panel Least Square Test - Fixed Effects

(Dependent variable is the difference of the logarithm of loans over deposits of bank)

Note: In the panel, t-statistics are reported in parenthesis. The symbol *** indicates a significance level of 1% or less, ** indicates 5% and * indicates 10%.