In previous chapter, data collection, sample types

and sizes, settings and models are being done. While this chapter will carries

on with the interpretation and analysis on the results generated through the

test that have been mention on previous chapter. This chapter will start with

the normality test followed by descriptive and trend analysis. The overall

significance of the model and the individual significance of the independent

variables are to be discussed in detail in the correlation and regression

analysis in order to figure out the effect of the independent variable towards

the dependent variable in immediate effect and in the short-run.

The above table shows the Shapiro-Wilk

tests that are often used to determine whether that data is normally

distributed or not. The Shapiro-Wilk was used because this study has a sample

that is less than 50. The table shows that the TD and TF have concluded to the

value of significance that is less than 0.05. Suggesting that both TD and TF

data is not normally distributed. However, the test result on GDP suggest that

GDP is normally distributed as (sig. 0.890>0.05).

The table above summarizes all

the dependent variable (GDP) and independent variables (TF and TD) descriptive

statistics for Islamic Banks. On average the mean value of GDP for 10 years is

935366134670 with the minimum of 664914799200 and maximum of 1226096454800. The

standard deviation for GDP value is 192908681576.7. The mean of TF is lesser

than TD where it derives the value of 1265752772.3 and 1367793101.3

respectively. The maximum value of total deposit is 1861492879 which are lesser

than TF at 2056815201. The result also shows that the minimum value of TF is

higher than TF with the value resulted at 910512754 and 142864599. However, the

TF standard deviation is higher compare to total deposit standard deviation

where the difference is quite far apart. This indicates that TF is more

fluctuated if compared to TD.

Trend analysis

evaluates an organization’s financial information over a period of time.

Periods may be measured in months, quarters, or years, depending on the

circumstances. The goal is to calculate and analyze the amount change and

percent change from one period to the next.

Beginning in

the year 2007, we see the total financing for fully fledge Islamic Banks,

Foreign Islamic Banks, and banks that offered Islamic Banking windows started

to growing rapidly, capping the total amount of RM140610375 in that year alone.

The bank that contributed the largest amount of financing is the Asian Finance

Bank with the accumulate amount of RM90789188. The bank also continue to inject

their total financing with consistently increase across the period. Standard

Chartered

Saadiq contributes the lowest amount of

total financing during this period, with an accumulate amount of RM37,886,656.

A small decline of total financing can be seen in 2015 from RM2,056,815,201 to

RM1,839,695,581. As suggested by (Global Islamic Getaway, 2017), the Islamic

banks assets is on the decline starting 2014, thus explaining the total

financing of Islamic Banks is in a downtrend during that period. In 2016

however, the total financing recovered, placing them in a RM1, 882,715,962

valuations.

The graph above shows the trend or the

movement of the total deposits acquired from all of the Islamic banks in

Malaysia which include the full-fledge Islamic banks, foreign Islamic banks and

Islamic bank windows and are within the range of 10 years from the year 2007 to

2016. The trend shows a stable increase of the deposits especially after the

year of 2008 which was the year that the global financial crisis had occurred.

This might be because of the increase in Islamic banks customers

due

to the stable characteristics of Islamic banking system which prohibits the use

of Riba’ (interest) in it system.

The

graph also shows a sharp increase in the total deposits in the year 2012 with

the total of RM 1,840,537,988, 000 while the previous year, 2011 has stated the

total of RM 1,305,424,432,000. This means that it has increase by 29.07% and

the largest contribution was from the Asian Finance Bank with the increase in

RM 492,812,257,000 during the year 2012. The trend however shows a downward

movement from the year 2013 till the 2016.

The GDP value

of Malaysia represents 0.48 percent of the world economy. In 2009, the Gross

Domestic Product (GDP) for Malaysia falls from previous year performance,

standing at RM712,575,159,800 mainly due to the Asian Financial Crisis

happening in the year 2008. After the crisis, the growth of the Malaysian

economy improves throughout the period, eventually breaking an all time in 2010

valuing at RM820,517,197,500 in that year. Further uptrend can be seen in 2014 with

the implementation of Goods and

Services Tax (GST) which inject funds towards the economy. GDP in Malaysia was

worth RM1156,718,460,300 in 2015. Malaysia’s 6.2 per cent growth in Gross

Domestic Product (GDP) in the third quarter of 2017 makes it among the fastest

growing economies in Asia, a minister said today. The (World Bank, 2017) recent

prediction suggest that Malaysia’s economic will project itself to 5.2% by the

end of 2017.

After the

analysis for both of the independent variable has been done, the comparison

graph between those two were created to see the differences in the movement of

both of the graphs. The trends of both of the graphs shows a steady increase

from the year 2007 to 2011. The graph also shows a sharp increase during the

year 2012 which was the same for both of the variables. When the total deposits

shows a downward trend in the year 2013, the total financing however has shown

a further

increase until it reach the year 20014

before going back downwards afterward. It then increase back in the year 2015

and this shows that the total financing of the Islamic banking system in

Malaysia are quite volatile in the past few years. This might be affected by

the total deposits collected by the banks since the volatility started when the

total deposits shows a sharp decrease after the year 2012 to 2016.

Augmented

Dickey-Fuller was deployed for the reliability test to see whether the series

has stationary properties or not.

The Schwarz Info Criterion was used to

determine the optimal lag length for this test. From the table, the result for

the ADF test shows that TD and TF is non-stationary as the probability value is

>0.05 at both level and first difference, suggesting that both independent

variables to have a unit root. However, GDP shows to be non-stationary at level

with intercept test equation, with the p-value deriving at 0.9833.

To

measure the degree of association between variables, the Spearman Rank

Correlation was deployed for non-parametric measures

The result on the immediate

effect shows that both of the IVs namely the total deposit and the total

financing are not significant. However, the correlation coefficient shows that

the total deposit has a weak positive relationship while the total financing

has a strong positive relationship with the GDP. The table shows a weak

correlation with TD which is less than 0.05 as shown by the p-value of 0.873.

The spearman correlation also shows that GDP has a weak correlation with total

financing as indicated by the p-value of 0.188. This concludes that GDP has a

weak correlation in an immediate effect with both total deposit and total

financing. This insignificant result wouldn’t allow this study to continue to

do the Multiple Linear Regression on immediate effect.

On the other hand, Spearman

correlation shows a different result when running the test on the short run as both

IVs shows to have a significant result. Moreover, the correlation coefficient

shows a very strong positive relationship between both the total deposits and

total financing with the GDP. The spearman correlation coefficient value at

1.000 indicates it has a strong positive correlation for total deposit and GDP

(p-value 0.000). The result also shows that GDP has a strong positive

correlation with total financing where p-value derives 0.000. Based on the

regression test, the result for total deposit and total financing regression

with the GDP shows that both of them have explanatory power in the short-run.

MLR is an

extension of simple linear regression. It is used to predict the value of a

variable based on the value of two or more other variables

Based on the regression

observation on the short run, the result for TD and TF regression on GDP in the

short run shows that it has explanatory power. The explanatory power of the

adjusted R-square is at the satisfactory level of 0.980. Which means it indicates

that 98% in the dependent variable and independent variable while acknowledging

the degree of freedom. In fact, the

regression is significant when the value falls lesser than 0.05 levels as it

concludes on 0.020b. In order to see whether the overall regression model is a

good fit for the data, we have to observe the F-ratio in the ANOVA table. The

table shows that the independent variables statistically significant predict

the dependent variable where F(2,2) = 48.885. This finding supports the results

from the Spearman Correlation that have been tested earlier. The test indicates

that the H3 and H4 null hypothesis can be rejected.

The study had examined the

effects of the total financing and the total deposits of Islamic banks in

Malaysia toward the economic growth of the country. Both of the independent

variables have been studied by vary them into two periods, which are immediate,

1-year period and short-term, 5-year period. The finding of the studies has

shown that the total financing and the total deposits have played more

significant role in the short-term rather than the immediate effect. Both of

the independent variables obtained the value of the correlation coefficient of

1.000 which indicates a very strong positive correlation with the economic

growth.

There might be a few factors

which can influence these results. Some of them include the implementation of

the Goods and Service Tax (GST) effective in the year 2015. Since GST is an

overall implementation towards the people within the country without taking

into account the household income of the consumers, it can slowly but surely

affect the banking industries by reducing the purchasing power of the consumer

in Malaysia. When the GST was implemented, the cost of living has been

drastically increased for the people in order to improve the economic

well-being of the country. When this happened, people with need to pay more on

their expenses thus they might think twice before buying something which are

expensive. To relate it with the effect towards the banking industries, people

will tend to spend less thus will less likely to borrow from banks. Plus,

people will also have less money to save in the banks since they have to pay

more for their everyday expenses thus affecting the total deposits of the

banks.

The immediate effect however does

not obtain any significant relationship between the independent and the

dependent variables. This might be because of the effect of the total financing

and the total deposits do not contribute toward the economy in a 1-year period

or it might be because of the lending and saving activities managed by the

Islamic banks have little affects in the immediate term rather than the short

term.

Some suggestions that can be made

in order for the Islamic banks to improve their businesses are by investing

more in government link project provided by the government to help them get

better return rather than depending mainly on the total deposits such as when

the government spends more, the suppliers come to borrow from the bank or

deposit more money due to increased money supply thus the economy thrives

(Walid, 2015). Furthermore, the government can also include the Islamic banks

in their initiatives to improve the economy. For example, the government can help

the SMEs or start-up entrepreneurs by providing them with banking loans which

comes from the Islamic banks in Malaysia.

In conclusion, it is found that the dependent

variable is normally distributed and both independent variables are not normally

distributed. For the reliability test, the ADF test suggests that that the

independent variable is non-stationary and the dependent variable is stationary

and does not have a unit root. Furthermore, the hypothesis testing shows that

in there is no significance in the immediate effect. This concludes that H1

and H2 are rejected. However, the short run correlation on

both TD and TF suggested that there is significance with the GDP and was

further supported when carrying out the regression analysis. Thus, H3

and H4 is accepted.