Print Email Download

Paid Writing Services

More Free Content

Get Your Own Essay

Order Now

Instant Price

Search for an Essay


Descriptive statistics

CHAPTER 4

RESULTS AND DISCUSSIONS

This chapter will present and illustrate the findings that the study revealed from the results. The data will be tested by using the Statistical Package for the Social Sciences (SPSS) software in order to develop the descriptive statistics for the pre- and post- mergers and acquisitions. Besides, this chapter also will discuss the results. Comparison between the two periods for the variables performance is presented using the paired-samples T-test. Next, the results of the regression are computed using the multiple regression analysis to find the coefficients correlation between the independent variables and dependent variable and to examine the strength and directions (either positive or negative) of the relationship.

Descriptive Statistics

Analysis is conducted on two periods which are the pre- and post- M&As. Both periods are computed for two years before and two years after the mergers and acquisitions. The descriptive statistics show the range, minimum, and maximum values, sum and mean values as well as the standard deviations for all the variables used. The entire sample consists of eight domestic banking institutions in Malaysia covering the two periods.

Table 4.1 provides the descriptive statistics for the Return on Common Equity (ROE), Capital Buffer Ratio (CBR), Loan Growth (LG), Loan Loss Reserve Ratio (LLRR), Cost Efficiency (CE), and Interest Earnings Ratio (IER) for the banks in Malaysia during the pre- merger and acquisition periods.

Table 4.2 provides the descriptive statistics for the Return on Common Equity (ROE), Capital Buffer Ratio (CBR), Loan Growth (LG), Loan Loss Reserve Ratio (LLRR), Cost Efficiency (CE), and Interest Earning Ratio (IER) for the banks in Malaysia during the post- merger and acquisition periods.

Table 4.3 shows the results of the t-test that were used to examine the mean differences for all the variables whether there are significant differences in the average values of each variable between the pre- and post- merger and acquisition periods.

Table 4.3 reports the mean values for the variables before and after M&As. According to the data above, the mean for the capital buffer ratio is lower (0.1614) after the M&A as compared to pre-merger period. In addition, loan growth, and interest earnings ratio, as the proxy for the banks' earnings are higher with means values equal to 0.2019 and 0.3929 respectively. However, loan loss reserve ratio which is also one of the proxies for the banks' earnings is lower (0.1144) during the post-merger period. For the cost efficiency which measures the efficiency of the banks' management team has increased from 0.2169 to 0.2670. Furthermore, the result implies that ROE has decreased after the mergers and acquisitions.

Details of the results show that the average cost efficiency (CE) for banks after the merger is higher than before the merger and the mean difference between the two periods is significant at the 5 percent level. The increase in cost efficiency indicates that the banks are less efficient after the merger and acquisition. As for the loan growth variable (LG), the mean figures before and after the mergers are statistically different at 10 percent level. The insignificant t-statistic for the mean differences of the loan loss reserve ratio (LLRR) suggests that banks maintained similar loan loss provisioning policy during the pre- and post- merger periods. The remaining variables in Table 2 indicate that the merging of banks does not have an important impact on the profitability, capitalisation, and interest earnings ratio. This is supported by insignificant t-statistics for the mean difference between the two periods of the capital buffer ratio, return on common equity and interest earnings ratio.

Regression Analysis

In this study, multiple linear regression analysis was used to test the hypotheses. The independent variables (capital buffer ratio, loan growth, loan loss reserve ratio, cost efficiency, and interest earnings ratio) were regressed on "profitability" as the dependent variable. Table 4.4 provides the results for the relationship between banks' performance and the independent variables before and after mergers and acquisitions periods.

The regression results during the pre-mergers and acquisitions period shown in Model 1 of Table 4.4 indicate that there are significantly negative relationship between four independent variables (CBR, LG, LLRR and IER) and dependent variable (ROE). In contrast, cost efficiency (CE) is a weak predictor with the significant value more than 0.05 and this indicates that there is no significant association between cost efficiency and banks' performance during the pre-mergers and acquisitions period. It is highlighted CBR, LG, LLRR, and IER are significant variables. But there are different levels of the significance. For instance, the CBR and IER are more significant than LG and LLRR. It is because the probability of these two variables is less than the significant level 0.05. Hence, these two variables movement will strongly affect the ROE performance. LG and LLRR are also significant to affect the ROE performance. But it is not as significant as CBR and IER because the probability is more than 0.05. From the table, the coefficient of determination (R square) of the model is 0.987, which indicates that 98.7 percent of the variation in the dependent variable is explained by the independent variables in the model. Also, the F value of 29.735 signifies that there is significant (p&0.01) relation between the variables.

Model 2 of Table 4.4 reports the findings during the post-mergers and acquisitions period. Different from Model 1, Model 2 shows that there are significantly negative relationship between all the independent variables and dependent variable (ROE). This gives an indication that cost efficiency has significant impact on the banks' profitability after the merger and acquisition compared to before the merger and acquisition. The negative relationship indicate that where increase in these five variables, it would have negative effect on the banks' performance in terms of profitability. The results show that the models fit with the data reasonably well as shown by the strongly significant F value of 1582.403 being significant at p&0.01. The R square value of 1.000 indicates that 100 percent of the variation in the dependent variable is explained by the independent variables in the model.

Hypotheses Test Result and Discussion

The strength of the proposed relationship was assessed using the respective multiple linear regressions summarized in Table 4.4.

H01: Capital buffer ratio has no effect on the performance of banks before and after merger and acquisition.

The regression analysis shows that coefficient of capital buffer ratio is negative and significant at the 5 percent level and 1 percent level for before and after merger, respectively. Therefore, the null hypothesis is rejected and this implies that the capital buffer ratio has significant impact on the ROE. The negative sign illustrates that as the capital buffer ratio of the banks increases, the ROE of the banks decreases. The higher capitalisation could be due to a higher equity base, higher loan loss reserve or a combination of both. The finding of an inverse relationship between capital buffer ratio and ROE implies that very likely the higher capitalisation of the banks is because of the higher loan loss reserve of the merged banks and not the equity base.

H02: Loan growth has no effect on the performance of banks before and after merger and acquisition.

From the results, the significant value of the pre- merger and acquisition is 0.100 which is significantly at 10 percent level whereas the post- merger and acquisition significant value of 0.003 is less than the 1 percent significance level. Thereby, the null hypothesis for both periods should be rejected as the results implied that loan growth has an effect on the performance of banks. However, the loan growth for pre- merger and acquisition period is not as significant as the loan growth during post- merger and acquisition period.

H03: Loan loss reserve ratio has no effect on the performance of banks before and after merger and acquisition.

The results from the regression analysis show that the loan loss reserve ratio is significant during the pre- and post- merger and acquisition periods. The coefficients of the pre- and post- loan loss reserve ratio are negative at the significant level of 10 percent and 1 percent, respectively. In other words, as the loan loss reserve ratio of the banks increase, the ROE decreases. This is because high loan loss reserves eat away a large portion of banks' profits. Thus, the null hypothesis should be rejected and this indicates that loan loss reserve has a significantly impact on the ROE. It is consistent with Rasidah et al.'s (2008) evidence that banks with the high level of loan loss reserves tend to have a low level of profitability.

H04: Cost efficiency has no effect on the performance of banks before and after merger and acquisition.

The analysis indicates that cost efficiency is not significant during the pre-merger and acquisition period. In contrast, it is inverse and statistically significant at 1 percent level at the post- merger and acquisition period. Hence, the hypothesis on the cost efficiency has no effect on the banks' performance before merger and acquisition is not rejected and for the hypothesis for post-period is rejected. This is because cost efficiency in this study is measure by expenses divided by revenues, so if the cost efficiency has increase after merger and acquisition, it implies that level of inefficiency of management increases, the ROE of banks decreases. Rasidah et al. (2008) suggested that high expenses incurred by the banks will cause negative impact on the overall profitability.

H05: Interest earning ratio has no effect on the performance of banks before and after merger and acquisition.

Interest earning ratio serves as the proxy to reflect the nature of the banks' business activities is found significantly negative at 5 percent level and 1 percent level of significance for pre- and post- merger, respectively. This means that as the interest earning ratio of the banks increases, their ROEs decrease.

CHAPTER 5

CONCLUSIONS AND RECOMMENDATIONS

Based on the results and findings obtained in the study, this chapter will further with the summary on the discussion and practical implication will be presented. There are some contributions of this study will be provided also. Limitations and recommendations for future research will be discussed in this chapter too. Lastly, conclusion will be presented to end of this thesis.

Summary of the study

Objective 1:

To analyse and determine the variables that influences the banks' performance before and after the merger and acquisition.

After testing on the regression analysis, the results indicate that all of the control variables have an impact on the banks' performance before and after the merger and acquisition, except for the cost efficiency which is found to be insignificant during the pre- merger and acquisition period. This means that in the study, cost efficiency has no much influence on the banks' performance before the merger and acquisition event.

Objective 2:

To compare and evaluate the changes in the performance of Malaysian banks before and after mergers and acquisitions.

Based on the analysis on the paired samples T-test, it can be concluded that there is no change in the banks' performance after the merger and acquisition. Only one variable is found to be highly significant variable which is the cost efficiency. As stated before, the cost efficiency represents the banks' management efficiency level. Thus, the banks that tend to merge have to be carefully in analysing this variable after the merger and acquisition, since it is closely associated with the performance of the banks.

Objective 3:

To find out whether mergers and acquisitions benefit the banking groups in Malaysia.

From the findings, on average, the profitability in terms of the banks' return on common equity did not improve after the mergers and acquisitions exercise. This may be due to the analysis is based on the short-run period which is computed for two years post- merger and acquisition. However, the loan growth for the banks has improved tremendously after the M&As and eventually the increment in the loan growth will be expected to benefit the banks. During the post- merger and acquisition period, the merged banks do not experience cost savings. The cost inefficiency may be attributed to the fact that merging activity does not lead to branch disclosure and employees layoffs.

Managerial Implications

This study makes significant implications to the banks' shareholders, investors, and management. To shareholders and investors, the result of the independent variables that significantly affecting the banks' performance imply that changes of the banks' management and intermediation activities after the merger and acquisition will affect the profitability performance. In these findings, regardless of merger and acquisition activity, banks' management is important in a banks' success. The outcome of this study has several implications which may be useful for banks in order to improve their performance from the effect of the merger and acquisition activity.

Since the findings of this study stated merger and acquisition could not deliver positive gains in the banks' performance, thus this may be taken into consideration by the banks' decision making bodies to develop a coherent strategy for managing the problem faced in the bank management.

Limitations of the study

There are some limitations faced when carrying out this research. Firstly, the data used in this study was based on two years before and two years after the mergers and acquisitions from the annual reports of each individual bank. Due to the data limitation, the initial samples of the nine domestic commercial banks in Malaysia had been reduced to eight samples. The data availability is limited because it was difficult to get the annual reports as the data provided in Bursa Malaysia website as well as the Thomson Datastream will not be presented if the bank is not listed at the year requested. Besides, not all the annual reports can be found in the library of Bank Negara Malaysia.

In addition, the sample size in this study was small as compared to other studies. The reason for analysing eight banks only is because this research main focus is on Malaysian domestic commercial banks. Thus, foreign commercial banks in Malaysia are not included. Obviously, small sample size is the limitation in this study which might caused the accuracy of the results to be lower than others who using large sample size.

Furthermore, the sample period is limited to two years prior and two years after merger and acquisition. A shorter period was adopted considering reasonable to avoid any other factors that might influence the performance. But, if this study could be done in a longer period, the results and conclusion may be different.

Recommendations

For future research, there are some recommendations constructed. Based on the limitation, it is recommended to use a large sample size if compared to the small sample size. The reason is large sample size will give more accurate data and make the result more reliable. It would be interesting to take a longer sample period and compare with the shorter sample period. The results will be different as the longer the period, the banks' management might change.

Further, researchers may also focus on both domestic and foreign banks which have involved in merger and acquisition exercise in Malaysian banking institutions. Thus, researchers can make a comparison in analysis between domestic and foreign banks' performance after the merger and acquisition. Likewise, it is also recommended that further research can be extended to other countries involved in M&As in their banking industry. It is because different countries have different management strategies in their banking institutions. Through this comparison, further justification in various models can be obtained thus a better result could be made in determining which model has significantly influencing the actual performance of the banking institutions, regardless of merger.

Extension of theoretical framework should be done by future researchers. This study concentrates merely on the bank-specific variables. Thus, other variables that might affect the banks' performance were not mention in this study. So, it is suggested that future research can be done by identify both internal and external factors that can affect the banks' performance before and after the merger and acquisition such as macroeconomic factors, corporate governance factors, other financial and operating factors. In order to enhance the accuracy of this study, it is recommended to reduce variables that have closely related to each other. By this way, multicollinearity problem can be reduced. Also, the dependent variables can be extended by including other variables which investors and shareholders will be interested, for instance, the return on stock price performance.

Conclusions