Relationship between Inflation and employment rates and GDP
Gross Domestic Product as an indicator of wealth and therefore quality of life has long been criticized (Mederly, P. and et al. 2003). Gross Domestic Product (GDP) is the value of total production of goods and services in a country over a specified period, typically a year. The gross domestic product (GDP) or gross domestic income (GDI) is a measure of a country's overall economic output GDP can be determined in three ways, all of which should in principle give the same result. The most direct of the three is the product approach, which sums the outputs of every class of enterprise to arrive at the total. The expenditure approach works on the principle that all of the product must be bought by somebody, therefore the value of the total product must be equal to people's total expenditures in buying things. The income approach works on the principle that the incomes of the productive factor must be equal to the value of their product, and determines GDP by finding the sum of all producers' incomes (Bureau of Economic Analysis, U.S Department of Commerce, 2007). The most common approach to measure GDP is the expenditure method:
GDP= private consumption + gross investment + government spending + (exports −
GDP = C + I + G + (X-M)
An event in 1975 that remind us the current GDP in our country where the Malaysian economy slumped into its great recession, with a GDP growth rate of only 0.8 percent, compared to 8.3 percent in 1974. This is one of the effects of increase in oil prices and then substantial price increase in 1973 were bought about mainly shortage of food and raw materials arising from bad weather and increased aggregate demand (Cheng, M.Y. and Tan,.H.B. 2002).
According to the above circumstances occurred in 1975, the researcher has choosing one of variables that may relate with fluctuation of GDP which is inflation rate. Inflation means either an increase in the money supply or an increase in price levels. Generally, when we hear about inflation, we are hearing about a rise in prices compared to some benchmark.
The study of the effects of inflation on economic growth continues to be an important and complex topic in economics. If inflation has real economic effects, then governments can influence economic performance through monetary policy (Risso, W.A and Carrera, E.J.S, 2009). Therefore, investigating how inflation affects economic growth pertains directly to the optimal design of monetary policy. Results from such studies are particularly important for economies.
Besides the inflation, the researcher has considered total employment as one of the variable in the model since economic growth and employment are correlated between each others. The relationship between unemployment and GDP is called Okun's law. It is the association of a higher national economic output with the decrease in national unemployment. This is because in order to increase the economic output of a country, people will need to go back to work, thus lowering unemployment.
In order to support the relationship exist between GDP and employment, the researcher has found out the issue supporting the theory that GDP and employment has a positive relationship between each others. According to Hassan, M.K.H. and et al. (2010), in the period of 1996 -1997, the manufacturing sector experienced a rapid growth producing the employment rate in the sector to grow at 7.7 percent per annum but later declining to negative 3.6 percent in 1998 due to the economic recession. In addition, in year 2000, the Malaysian manufacturing sector contributed 33.4% to gross domestic product (GDP), 85.2% to total export and 27.6% to total employment.
1.2 PROBLEM STATEMENT
Inflation is a major source of economic instability because it weakens incentives for work and production, distorts the allocate efficiency of the market mechanism, erodes international competitiveness of the domestic industry, and reduces growth potential. According to study by Fischer and Modigliani (1980) suggested a negative and nonlinear relationship between the rate of inflation and economic growth through the new growth theory mechanism.
Furthermore, inflation also damages economic growth by lowering domestic and foreign savings, reducing efficiency of resource allocation, and deteriorating the balance-of payments (Risso, W.A. and Carrera, E.J.S., 2009). According to Cheng, M.Y. and Tan, H.B. (2002), the economy has experienced episode of high (1973-1974, 1980-1981) and low (1985-1987) regimes of inflation, and was able to contain low and stable inflation during the high economy growth period of 1988-1996.
The second problem statement that should be concerns since the employment can affect the economic growth and it is important variable to determine the quality of production for national output and next will influence the GDP of our country. For example, in the early 1990s, the unemployment rate increased for about a year following the end of the previous recession. Coming out of a recession, companies are thought to be reluctant to hire many more workers until they are convinced about the sustainability of a new economic recovery while people who had left the labor force during the recession return to seek to find jobs (Seyfried, W.).
Therefore, the researcher conducts this research in order to examine the correlation exists between inflation rate and employment with GDP so that we can help the country to mitigate the problem occurs by supporting the government’s policies to increase the country’s GDP. In addition, this research also useful since the results of the studies can be used in policy’s decision for resource allocation in order to accelerate economic growth.
The objectives of the study are to:
1.3.1 Analyze the relationship between Inflation Rate and Gross Domestic Product in terms of magnitude and direction.
1.3.2 Analyze the relationship between Total Employment and Gross Domestic Product in terms of magnitude and direction.
1.4 SIGNIFICANCE OF THE STUDY
The significances of this study are as follow:
This study will help the researcher to complete their course requirement and will be as guidelines for their field of work in the future. The researcher can gain many experiences in order to complete this research. There are lot of weaknesses may be obtained and this will encourage the researcher to provide the better research in the future. Future researcher will know and more understanding about gross domestic product when conduct this research. It will give the knowledge to the researcher to identify the correlation exist between inflation rate and employment and it always make the researcher briefing to know deeply and applied the study.
This study might help the organization in analyzing the country’s economic condition in order to prevent and reduce the risk during the inflation and know the effects of the crisis occurs to them. This study also may give some guidance to them to protect their company and industry itself.
This study can inform and gives some knowledge to the public the relationship between economic growth, inflation rate and employment. They also can make preparation to face the increasing in inflation rate and able to survive in that situation.
1.5 SCOPE OF THE STUDY
The researcher chooses to conduct the research about GDP in Malaysia from 2000 until 2010 In this study, the researcher wants to determine the correlation exist between inflation rate and employment with GDP in Malaysia. It is important because as economic planners and forecasters used the GDP per capita in monitoring economic growth trend for time series. The collection of data of GDP, inflation rate and total employment were collected from Department Of Statistics Malaysia in quarterly basis.
1.6 THEORETICAL FRAMEWORK
Figure 1.1: Theoretical Framework
Independent variables Dependent Variable
Figure 1.1 represents the dependent variable and independent variables in this study. The function of theoretical framework has been clarified by Sekaran, U. (2003) which is a conceptual model of how one theorizes or makes logical sense of the relationship among the several factors that have been identified as important to the problem. Figure above clearly discuss the correlation between Gross Domestic Product which is variable primary to the researcher while Inflation Rate and Employment act as independent variable which is influences the dependent variable.
In classical test of significant, two kind of hypothesis are used. They are Null Hypothesis and Alternate Hypothesis. Hypothesis is a conjectural statement that describes the relationship among variable even negative or positive. Null hypothesis which is represent by H0 symbol to show that the relationship between independent and dependent variable is not exist. However alternate hypothesis is representing by H1 symbol to show that the relationship is existing between both dependent and independent variable.
According to Sakaran (2004), a hypothesis defines as a logically conjectured relationship between two or more variables expressed in the form of testable statement. Relationship a conjectured on the basis on the network of associations established in the theoretical framework formulated for the research study.
There are two hypotheses that can describes the correlation exists between dependent variable and independent variables. Therefore the hypothesis that can be tested as follows:
Inflation and GDP
H0: there is no significant relationship between inflation and GDP.
H1: there is a significant relationship between inflation and GDP.
Employment and GDP
H0: there is no significant relationship between employment and GDP.
H1: there is a significant relationship between employment and GDP.
1.8 LIMITATION / CONSTRAINTS
The limitations / constraints are:
1.8.1 Time constraint
The length of time is limited since the researcher does not have much time to make detailed research. The time provided only three months and the researcher need to divide time properly to complete the research because the process of collecting data is quite difficult.
1.8.2 Cost constraint
The cost involves is quite high since as a student, the researcher only depend on the loan applied. Examples of cost involve in order completing this research such as cost of printing, cost of maintaining the laptop, cost of surfing the internet and etc.
1.8.3 Data constraint
Since the researcher use the secondary data, the collection of data that have been publish are so limited and the related material are not very supporting the topic of research.
1.8.4 Lack of experience
The researcher is less of experience in conducting the research therefore needs to refer the researcher’s advisor to process the data and learning the skill that needed as a good researcher.
2.1 DEPENDENT VARIABLE
2.1.1 GROSS DOMESTIC PRODUCT (GDP)
Generally, according to Chan, W.W. and Lam, J.C. (2000), gross domestic product is a common measure of the economic well-being of a society. When government officials plan for the future, they consider the various economics sectors contributed to the gross domestic products. In the other study by Ivanov, S. and Webster, C. (2007), they use the growth of real GDP per capita gr as a measure of economic growth in line with other publications in the field (see Ivanov and Webster, 2007; Lopes et al., 2002; Plosser, 1992). The function of GDP also has been explained by Kosmidou, K. (2008) where gross domestic product (GDP) is among the most commonly used macroeconomic indicators, as it is a measure of total economic activity within an economy. The gross domestic product growth (GDPGR), calculated as the annual change of the GDP, is used as a measure of the macroeconomic conditions.
The significance between GDP, foreign trade and foreign direct investment has been discussed by Liu Ying and Cui Riming (2008) where the economy is highlighted by the significant performance of both its economic growth and its foreign trade and foreign direct investment. Under this background, the correlation of foreign trade, foreign direct investments and economic growth in has become an important issue for academic research. Previous studies support that foreign trade and foreign direct investment have positive impacts on gross domestic product (GDP). In the study by Malul, M. and et al. (2008), the GDPpc is used mainly to compare the standard of living in different countries. It means that the higher of cost of living in a country, the higher earning of gross domestic product of the country. According to Wong, K.Y.(2008),economic growth of an economy refers to the expansion of its production possibility set, as a result of accumulation of primary factors such as labor and capital (physical and human), or improvement of production technologies. However, because the production possibility frontier (PPF) of an economy is not observable, economic growth is usually measured in terms of the growth rate of some observable variables such as real GDP or real per capita GDP.
Besides that GDP also one of the result of the country’s economic activities based on the statement of Daly and Cobb (1989), GDP expresses the content of physical flows of “capital, industrial production, services, resources and agricultural product”. The scientific research has been conducted by Ligon and Sadoulet (2007) using a sample of 42 countries show that GDP growth, which comes from agriculture is at least twice as effective in reducing poverty compared to GDP growth coming from nonagricultural areas. In order to know the correlation between inflation and growth, Gokal, V. and Hanif, S. (2004), stated that the tests revealed that a weak negative correlation exists between inflation and growth, while the change in output gap bears significant bearing. The causality between the two variables ran one-way from GDP growth to inflation. While, according to some consensus exists, suggesting that macroeconomic stability, specifically defined as low inflation, is positively related to economic growth.
2.2 INDEPENDENT VARIABLES
2.2.1 INFLATION RATE (INF)
Inflation on economic growth continues to be an important and complex topic in economics. If inflation has real economic effects, then governments can influence economic performance through monetary policy. Therefore, investigating how inflation affects economic growth pertains directly to the optimal design of monetary policy. According to Andres and Hernando (1999), for example, reducing inflation by one percentage point when the rate is 20 percent which results in an increase in the growth rate of 0.5 percent, compared to reducing inflation by one percentage point when the inflation rate is around 5 percent, which results in a decrease in the growth rate by 1 percent. Furthermore, a study by Mallik and Chowdhury (2001), the structuralisms argue that inflation is necessary for economic growth, whereas the monetarists argue the opposite, that is, inflation is detrimental to economic growth such debate started in the 1950s, focused on developing countries, which had long suffered from low-growth rates with high rates of inflation and larger deficits in the balance of payments.
In order of inflation, the monetarists argue that price stability promotes economic growth and protects the balance of payments. They argue that inflation is major sources of economic instability because it weakens incentives for work and production, distorts the allocative efficiency of the market mechanism, erodes international competitiveness of the domestic industry, and reduces growth potential. They also argued that inflation damages economic growth by lowering domestic and foreign savings, reducing efficiency of resource allocation, and deteriorating the balance-of-payments. To monetarists, stable prices are the starting point in the process of economic development. The policy choice of a country would be stabilization with growth, or stabilization without growth. Several papers are typical of the monetarist tradition.
To argue that, according to Fischer and Modigliani (1980) suggested a negative and nonlinear relationship between the rate of inflation and economic growth through the new growth theory mechanism proposed a model where the agents decide the level of labor output, and an increase in inflation reduces labor supply, and producing a decrease in economic production. On the other hand, a study by Mundell and Tobin (1965), the structuralizes argue that inflation normally accompanies economic growth in developing countries because structural rigidities and bottlenecks in supply sectors prevent the elastic supply of some basic commodities such as food, housing, energy, and transportation. Increased income as a result of growth would expand demand for such basic commodities, and prices would rise. The structuralize position is that economic difficulties in developing countries have roots deeper than just the results of inflation. Thus, structuralizes thought that inflationary pressures and deterioration in the balance of payments inevitably are attendant matters of economic growth. In developing countries, there thus would be a trade-off relationship between economic growth and inflation and an attendant deterioration in balance of payments.
If a developing country wants stabilization of prices and balance of payments, it must reduce the speed of economic growth, including a sacrifice of employment. Among scholars who support the structuralize’ position on a positive relationship between inflation and economic performance, predict a positive relationship between the rate of inflation and the rate of capital accumulation, which in turn implies a positive relationship to the rate of economic growth. But, DeGregorio (1996) and Fischer (1926) pointed out, since money and capital are substitutable, an increase in the rate of inflation increases capital accumulation by shifts in portfolios from money to capital and thereby stimulate a higher rate of economic growth was the first to establish a negative correlation between inflation and unemployment.
According to Grier and Grier (2006), it presents evidence on the real effects of inflation and inflation uncertainty on output growth. Their main findings are as follows:
Inflation uncertainty has a negative and significant effect on growth
Once the effect of inflation uncertainty is accounted for, lagged inflation does not have a direct negative effect on output growth; and
As predicted higher average inflation raises inflation uncertainty, and the overall net effect of average inflation on output growth.
Differ with theory of Bortis, H. (2004), he argues that inflation is a macroeconomic phenomenon represented by a gap between global supply and global demand. Inflation affects the money-output relationship, as does deflation; both phenomena modify the purchasing power of money over domestic output. In this view, price indices cannot come to grips with the inflation phenomenon. While Cheng and Tan (2002) in their study inflation in Malaysia, suggested that main factors affecting Malaysian inflation were external (foreign trade, foreign direct investment and technology transfer). Malaysia has been comparatively successful in balancing strong economic growth with moderate levels of inflation in the periods preceding and following the Asian Financial crisis. Actually, empirical results related to low and medium inflation are of a mixed nature; some papers (mainly these analysing the developed economies) argues that moderate inflation negatively affects growth (e.g. Alexander, 1997, Gillman et al. 2002; Gillman and Harris 2009; Gillman et al. 2001; Fischer 1993; De Gregorio 1992 and 1993) while other argues that moderate inflation is actually stimulating growth.
On the theory side Friedman (1977) in his Nobel lecture argues that a positive relationship between the level of inflation and inflation uncertainty. Friedman points out higher inflation leading to greater uncertainty, which lowers welfare and efficiency of output growth. On the other hand, Ball (1992) formalizes Friedman’s hypothesis using an asymmetric information game where public faces uncertainty regarding the type of policymaker in the office. One of the policymaker is willing to tolerate a recession to reduce inflation and the other is not. During the low inflation time, both type of policymakers will attempt and try to keep it low. But, when inflation is high, only the tough type or anti-inflation policymaker will bear the economic costs of disinflation. The argument that central banks should emphasize holding down inflation comes from the beliefs that inflation has an adverse effect on macroeconomic variables, such as output and productivity growth.
According to Clark (1982), inflation causes misperception of the relative price levels and leads to inefficient investment plans and therefore affects productivity inversely. Furthermore, inflation erodes tax reductions for depreciation and raises the rental price of capital, which in turn causes a reduction in capital accumulation and therefore in labour productivity. In addition, according to Feldstein (1982) inflation disrupts investment plans by imposing a higher tax rate on corporate profits and through higher effective tax rates on corporate income and accordingly affects productivity (Gilson, 1984; Boskin et al., 1980). Finally, inflation distorts price signals and reduces the ability of economic agents to operate efficiently (Smyth, 1995). According to Chen and et al. (1991), it has documented a significant relationship between the US stock returns and real economic variables such as industrial production, real GNP, interest rates, inflation and money supply.
Besides that, there are also otherwise arguments that there is no relation between inflation rate and gross domestic product in the long run. For instance, Faria and Carneiro (2001) investigate the relationship between inflation and output in the context of an economy facing persistent high inflation and they find that inflation does not affect real output in the long run, but that in the short-run inflation negatively affects output. In addition, scholars such as Sidrauski (1967) suggest that there is no relationship between inflation and economic growth, supporting the hypothesis of super neutrality of money. On the other hand, Sarel (1995) asserts that there is a nonlinear relationship between inflation and economic growth. Using 87 countries, he finds the existence of an inflation threshold of 8 percent. Above the threshold there is a negative relationship between inflation and economic growth, whereas under the threshold there is a positive but not significant relationship.
The others studies in order to prove Sarel’s result, Judson and Orphanides (1996) divide Sarel’s sample of countries into three groups, and they find similar results to Sarel, finding a threshold of 10 percent. Ghosh and Phillips (1998a, b) study 145 countries in the period 1960-1990 again finding similar results. Paul et al. (1997) study 70 countries (of which 48 are developing economies) for the period 1960-1989. They find no causal relationship between inflation and economic growth in 40 percent of the countries, bidirectional causality among 20 percent of the countries, and unidirectional causality for the rest (either inflation to growth or vice versa). Lastly, Mendoza (1998) finds that inflation has had no effect on Mexico’s long-run economic growth since he conducted the study of inflation in Mexico.
Some of studies have been conducted to examine the relationship between gross domestic product and employment. For instance, according to Okun (1962) and Philips (1958), they found different relationship both of these. Okun found a negative correlation between unemployment and economic growth, then from both propositions it can be deduced a positive relationship between economic growth and inflation while Phillips proposed a positive relationship between inflation and unemployment implying the same type of relationship. In addition, Boltho and Glyn (1995) found elasticities of employment with respect to output growth in the order of 0.5 to 0.6 for a set of OECD countries. While according to Evangelista and Perani (1996) discovered evidence suggesting that restructuring of major economic sectors reduce the relationship between economic growth and employment.
A specific research conducted by Seyfried, W., among the G7 countries (Canada was excluded), a positive and significant relationship between growth in value added and employment was found only in Germany and the US. In addition, according to Verdoon (1949) and Kaldor (1966), an increase in output growth of 1 percent leads to an increase in productivity and employment growth of half a percentage point each. It should be noted that the higher the productivity effects of growth, the more difficult it will be to keep unemployment from rising. According to Okun's Law an increase of the economic growth rate by 3 percent (above the normal rate) was expected to reduce the unemployment rate by 161 percentage point. Or, to put it the other way round: The gain of real GDP associated with a reduction in unemployment of one percentage point was estimated to be 3 percent.
Several studies also have been conducted to examine the correlation exists between employment and inflation rate. One of the studies by Spithoven, A.H.G.M. (1995), by the end of the 1960s evidently there was no fixed relationship between unemployment and inflation. Empirical research revealed that the relationship was not consistent over time and varied sharply between countries. This was explained as follows: in the short run higher nominal wages attract more labour and engender a fall in the rates of unemployment. As soon as the workers recognize the wage rise to be purely nominal they abstain from work, and unemployment is restored to the pre-wage-rise level, but with a level of prices higher than before. Secondly, according to Brenner (1991), confronted with a combination of unemployment and inflation (stagflation), many governments abandoned efforts to regulate the economy by the Keynesian instruments. They declared fiscal policies ineffective and sought refuge in a mixture of monetary measures with supply-side economics.
According to Keynes (1946), the volume of employment is given by the point of intersection between the aggregate demand function and the aggregate supply function. This was naively interpreted and construed to imply that a rise in costs – and with this was meant a rise in costs owing to increasing government expenditure – will result in an upward shift of the supply curve and will cause greater unemployment and inflation.
RESEARCH METHODOLOGY AND DESIGN
3.1 MODEL SPECIFICATION
This study is to examine the correlation exists between inflation rate and total employment with gross domestic product. It uses secondary data which is based on time series data. The collection of time series data from 1982 to 2006 and the scope is in Malaysia. The researcher applied STATA software to process the data and log-log model in this study. The model applied a log transformation, since log transformations help, at least partially, to eliminate the strong asymmetry in the distribution of inflation (Sarel, 1995) and (Ghosh and Phillips, 1998a, b). The logarithm equation is written in the Equation 3.1.
GDP = α + β1In(INF) + β2ln(EMP) + ε
GDP = Gross Domestic Product
α = Constant
β1 = Inflation
β2 = Employment
ε = Error term
In above equation, it shows clearly dependent variable that has been applied in this study is gross domestic product, besides that, the researcher also used two independent variables which are quantitative variables, they are inflation rate and total employment.
3.1.1 DEPENDENT VARIABLE
The dependent variable is the variable of primary interest to the researcher. The researcher’s goal is to understand and describe the dependent variable, and to explain its variability, or predict it (Sekaran, 2006). Dependent variable of this study is factor contributed to the gross domestic product. According to Zikmund (2000), independent variable is a criterion that predicted or explained. It show that the component contributed to improving of gross domestic product depend on the listed independent variables.
3.1.2 INDEPENDENT VARIABLES
According to Zikmund (2000), independent variables that expected to influence the dependent variable. Refer to (Burn and Bush, 2000), independent variables are those variables over which the researcher has some control and wishes to manipulate. In this study, two independent variables will influence the dependent variables. They are inflation rate and employment.
3.2 DATA SET AND METHODOLOGY
The collections of data in this research only gain from secondary data and based on time series data which are from 2000 to 2010. The researcher has considered annual data of real GDP, inflation rate and employment. All the data on the growth rate of real GDP, Inflation and total employment were obtained from Department of Statistics Malaysia database. GDP is considered per capita. In addition, according to Aigenger (2005) per capita real GDP is also used as an alternative measure of productivity, as some theoretical models do. Moreover, according to OECD (2001), living standards as represented by per capita income reflects productivity since the former is determined, to a significant extent, by the latter. CPI consider in weight 100 while employment in number of labor. The variables were selected based on relevant economic theories that allow for the interaction among inflation rate and total employment in addition to response to GDP.
3.3 TECHNIQUE ANALYSIS DATA
In this research, the researcher has applied unit SPSS in order to determine time series data is stationary or non stationary about the correlation between inflation rate and employment with gross domestic product. The researcher examines the existence of a long-run relationship between inflation and employment with GDP using a vector error-correction model (VECM) after applying Johansen’s (1988, 1990, and 1995) cointegration technique. We conduct a test for weak exogeneity in order to do inference. Then, the researcher conduct stability test by using Jarque Bera test in order to test normality distribution between the variables selected. Finally, a modified version of the Granger causality test is applied in order to analyze causality between the variables.
22.214.171.124 Multiple Regression Analysis
Multiple Linear regression analysis is an analysis of the relationship between one variable (dependent variable) and set of variable (independent variables). It is used by the researcher to test the hypothesis. As in all hypothesis tests, the goal is to reject the null hypothesis and accept the alternative hypothesis.
This technique will identify how much of the variance in the dependent variables can be explained by independent variables. This analysis is used primarily for the purpose of prediction. The regression model can be used to predict the value of the proposed model in the study is:
GDP = f (INF, EMP)
GDP = α + β1 Inflation+ β2 Employment + ε
GDP = Gross Domestic Product
α = Constant
β1 = Inflation
β2 = Employment
ε = Error term
126.96.36.199 Coefficient of Determination (R2)
A goodness of fit measure for a Simple Regression Model, the square of the correlations show how well a regression model explains the changes in the values of the dependent variables. In this study, R2 determine the changes in the dependent variable (x) can be explained by the changes in independent variables. This regression can be expected if the forecasting of R2 is 50% and above.
R2 = Explained Variance
188.8.131.52 F- Stastistics
F-Stat is used to test the hypothesis that the variation in independent variable explained a significant portion of variation in the dependent variable.
F-Stat = Explained variation / (k-1)
Unexpected Variation / (n-k-1) F-stat can be calculated as follow:
K= Number of independent variable
n = Number of observation
184.108.40.206 T- Statistics
T-Stat is used to determine if there is any significant relationship between the dependent variables and each independent variable. Under this method, the hypotheses are as follows:
H0 : β = 0
H1 : β ≠ 0
t=n-k-1To accept the hypotheses, this T-Stat should be compared with critical value. T-value is the critical level of significance and it can be measured by using this formula :
k = Number of independent variables
n = Number of observation
When the data was analyzed, the result of T-stat should be:
Accept H0 and Reject H1, when T-Stat > T-value
Accept H1 and Reject H0, when T-Stat < T-value
220.127.116.11 Correlation Analysis
Pearson correlation analysis will be used to analyze the relationship between two variables or to measure the degree of association between variables (Parasuraman, 1986). In analyzing the result, the researcher want to investigate the relationship exists between two variables, dependent and independent variables. The analysis can be interpreted as high, moderate and low correlation based on the score computed.
3.4.2 THEORETICAL FRAMEWORK
There is a classical theory that explained the high correlation between the key factor of performance in terms of profitability and independent variable.
Dependent variable : Gross Domestic Product
Independent variable : Inflation and Employment
Gross Domestic Product
Independent variable Dependent variable
Diagram 1: Theoretical Framework
According to the schematic diagram above, it can be elaborated that the performance in terms of profitability, GDP are determine by the inflation and employment.
Hypothesis can be defined as a specific statement of prediction. It describes in concrete (rather than theoretical) the expectation in the study. Hypothesis can be defined as logically relationship between two or more variables expressed in the form of testable statement. Relationships are conjectured on the basis of the network association established in the theoretical framework formulated for research study. As in the study, two hypotheses can be made based on the independent and dependent variables. To test whether this is applicable to ROA, it is hypothesized that:
H0: There is no relationship between the ROA and LTD
H1: There is relationship between the ROA and LTD
H0: There is no relationship between the ROA and DER
H1: There is relationship between the ROA and DER
CHAPTER 4: FINDINGS
The data for this study can be analyzed through the software such as SPSS, Limdep, Minitab or any other programs. It is very user-friendly and interactive and has the capability to seamless interface with different database. It ensures that the data are reasonably good of assured quality for further analysis. This chapter represents the findings and analysis on the factors affecting profitability performance of ROA of Islamic banking and conventional banking.
4.1 ANALYSIS AND INTERPRETATION OF DATA
As for the data analysis, the statistical tools use in this study is the Statistical Package for Social Science (SPSS) version 15.0 to code the data gathered from the historical data in this study. The statistical Package for Social Science (SPSS) version 15.0 is software designed in making data analysis for the research to be more accurate. As the data has been keyed in the SPSS, there is little analysis that will be conducted by researcher.
4.2 CORRELATION ANALYSIS
In this section, researcher used Pearson Correlation Coefficient to study the relationship exists between dependent variables and independent variables, as seen in the correlation coefficient (r). The analysis can be interpreted as high, moderate and low correlation based on the score computed. The score computed could vary from +1.00 to -1.00 but for this study, the researcher decided to use the suggested interpretation for value or “r” in determining the strength of coefficient as proposed by ( Guilford 1956). The interpretation of “r” value is explained in the table below.
Less than .20
Slight, almost negligible relationship
Low correlation, definite but small relationship
Moderate correlation, substantial relationship
High correlation, marked relationship
Very high correlation, very dependable relationship
(Source: Guilford 1956)
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