The Relationship Between Inflation Rate And Gdp

Published Date: 02 Nov 2017

This first chapter consists of an introduction and background to the study towards the factors that influenced Gross Domestic Product (GDP). This chapter also includes the problem statement, objectives of the study, theoretical framework, scope and hypotheses of the study. Besides that, it also briefly discusses the significance of the study and limitations during the process in completing this study.

1.2 BACKGROUND OF THE STUDY

This research is conducted to study on the factors that affect performance of the gross domestic products (GDP) in Malaysia. The determinants factors studied are inflation, government expenditure and export in Malaysia form the year 2003 to 2012. GDP is a common measure of economic well-being of a society. When government officials plan for the future, they consider the various economic sectors’ contribution to the GDP. GDP is the sum of value added produced within the country. The gross domestic product (GDP) or gross domestic income (GDI) is the market value of all final goods and services produced within a country in a given period of time. It is often positively correlated with the standard of living, alternative measures to GDP for that purpose. Countries seek to increase their GDP in order to increase their standard of living. Note that growth in GDP does not result in increased purchasing power if the growth is due to inflation or population increase.

One way to calculate a nation’s GDP is to sum all expenditures in the country. The expenditure approach calculates GDP by summing the four possible types of expenditures as follows:

GDP = Consumption + Investment + Government Purchases + Net Exports.

1.3 PROBLEM STATEMENT

The Gross Domestic Product (GDP) in Malaysia expanded 6.40 percent in the fourth quarter of 2012 over the same quarter of the previous year. GDP Annual Growth Rate in Malaysia is reported by the Department of Statistics Malaysia. Historically, from 2003 until 2012, Malaysia GDP Annual Growth Rate averaged 4.63 Percent reaching an all time high of 10.10 Percent in March of 2010 and a record low of -6.20 Percent in March of 2009. Malaysia is a developing economy in Asia which, in recent years, has successfully transformed from an exporter of raw materials into a diversified economy. The largest sector of the economy is services, accounting for around 54 percent of GDP. Manufacturing sector has been growing in recent years and now accounts for 25 percent of GDP and more than 60 percent of total exports. Mining and quarrying constitutes 9 percent of GDP and agriculture 9 percent.

The GDP growth rate is the most important indicator of economic health. If GDP is growing, so will business, increase jobs and personal income. If GDP is slowing down, then businesses will hold off investing in new purchases and hiring new employees, waiting to see if the economy will improve. This, in turn, can easily further depress GDP and consumers have less money to spend on purchases. If the GDP growth rate actually turns negative, then the economy is heading towards a recession. This study sought to examine knowledge about Gross Domestic Product (GDP). So, this research is done to measure or know whether the factors such as inflation, government expenditure and export influenced the Gross Domestic Product in Malaysia.

1.4 RESEARCH OBJECTIVE

In this research, the main objective is to study the determination of GDP in Malaysia. However, there are many factors that can influence the GDP. Thus, researcher tries to find the strong factor and relationship that influence GDP in Malaysia. Therefore, our specific research objectives are:-

1.4.1 To determine the factors that influenced Gross Domestic Product

1.4.2 To examine the relationship between each of independent variables with dependent variable

1.4.3 To study which is the most significant variable that contributed to the performance of Gross Domestic Product

1.5 RESEARCH QUESTIONS

To strengthen the research objectives, there are several research questions that can be discussed. From the problem statement and objectives of the study, the researcher came out with three research questions:

1.6.1 How significant is the relationship between inflation affect gross domestic products (GDP)?

1.6.2 To what extent the consumption expenditure impacts gross domestic products (GDP)?

1.6.3 Did export affect the gross domestic product (GDP)?

1.6 THEORITICAL FRAMEWORK

The conceptual framework in this research is the determination of GDP in Malaysia. This conceptual framework was needed in order to know the relationship among the variables. From the theoretical framework, researcher can see the flow and relation of variable towards GDP in Malaysia.

Inflation –consumer price index (CPI)

Government Expenditure (investment, services, manufacturing, transportation, telecommunication and education)

Export

GROSS DOMESTIC PRODUCT (GDP)

Independent variable Dependent variable

Figure 1.5: Theoretical Framework

1.7 VARIABLE MEASUREMENT

1.7.1 Dependent variable

Dependent variable is the variable of primary interest to the researcher. It also has been know as criterion variable. The dependent variable in this study is the Gross Domestic Product (GDP).

1.7.2 Independent variable

Independent variable is one that influences the dependent variable in either a positive or negative way. That is, when the independent variable is present, the dependent variable is also present, and with each unit of increase in the independent variable, there is an increase or decrease in the dependent variable also. The independent variables in this study are inflation, government expenditure and export.

1.8 RESEARCH HYPOTHESES

In this study, three hypotheses were built to examine the relationship between independent variable and dependent variable. According to Uma Sekaran, the hypothesis can be defined as a logically conjectured relationship between two or more variables expressed in the form of a testable statement. There are two types of hypotheses. The first type is null hypothesis (H0) and the other hypothesis is known as alternative hypothesis (H1). A null hypothesis is a proposition set up to be rejected, exact relationship between two variables. In general, the null statement is expressed as no (significant) relationship between two variables or no (significant) difference between two groups. The alternate hypothesis, which is the opposite of the null, is a statement expressing relationship between two variables or indicating differences between two groups. The hypothesis will come out such as follows:

Hypotheses 1

H0 = There is no relationship between inflation and GDP.

H1 = There is a relationship between inflation and GDP.

Hypotheses 2

H0 = Government expenditure does not have relationship with GDP.

H1 = Government expenditure have a relationship with GDP.

Hypotheses 3

H0 = GDP is not influences by export.

H1 = GDP is influences by export.

CHAPTER 2: LITERATURE REVIEW

2.1 INTRODUCTION

In this section, it will include the literature review from previous study. According to Uma Sekaran (1993) literature review is the documentation of a comprehensive view of the published and unpublished work from secondary sources of data in the area of special interest to the researcher. In this chapter, the focus studies on factors that influence GDP are discussed. Literature reviews are dividing into four parts. Firstly focus on study about determinations of GDP which is dependent variable. Second part focused on the study between GDP and inflation rate. Third part shows the relationship between GDP and government expenditure. The last part will respectively explain the relationship between GDP and export.

The detail of the discussion for all the factors will be well elaborated in the following sections as it will connect and integrate the information from various sources of researches which have been conducted in various timeframe, different countries and several perspectives. This information from various scenarios will become an important approach in explaining and exploring the determination of GDP. Thus, it will provide greater understanding with regards the factors that determinant of GDP in Malaysia.

2.2 GROSS DOMESTIC PRODUCT (GDP)

Ram (1986) studied the effect of the size of government expenditure on economic growth for 115 countries for the 1960-1980 periods. He found that although a higher rate of increase in government expense is associated with a higher growth rate a higher share of government expenditure in GDP dampens growth. Barro (1990), Barro and Salai-Martin (1992) in his studies consider government to be complimentary, not a substitute, for private investment, and examine the effect of government expenditures on growth in this light. He found that an increase in government expenditure would also forced GDP to be increased.

2.3 THE RELATIONSHIP BETWEEN INFLATION RATE AND GDP

Adriana (2009) studied in economics, inflation is a rise in the general level of prices of goods and services in an economy over a period of time. At the consumer level, inflation is perceived as a decline in the purchasing power of the money. The consumer price index (CPI) uses a fixed basket of goods (food, non-food and services) from some base year, meaning that the quantities of goods and services consumed remain the same from year to year in the CPI composition, while the price of goods and services changes. This type of index, where the basket of goods is fixed, is called a Laspeyres index.

Ming-Yu Cheng (2002) studied that in the history of inflationary in Malaysia, 1973 and 1974 were exceptional years. Inflation rose significantly in both the international and domestic market in 1973.The sharp oil price increase in 1973 and 1974 was the principal reason for the escalation of world inflation in 1973-1974. However, the effect of an increase in oil price was actually felt in 1974. The substantial price increase in 1973 were bought about the mainly of the shortages of food and raw material arising from bad weather and increased an aggregate demand.

Consequently consumer price in Malaysia began to rise and had reach of high level of 10.62 percent by the end of the year 0f 1973. In 1974, the surge in the oil price by over 230 percent put strong fuel of inflation and the inflation rate in Malaysia was increased to its record high of 17.29 percent. A year later Malaysian economy slumped into its great recession with GDP growth rate of only 0.8 percent in 1975 compared to 8.3 percent in 1974.

2.4 THE RELATIONSHIP BETWEEN GOVERNMENT EXPENDITURE AND GDP

Abu Nurudeen*, Abdullahi Usman (2010) studied, following the results reported in the preceding section, the authors make the following recommendations. Firstly, government should ensure that capital expenditure and recurrent expenditure are properly managed in a manner that it will raise the nation’s production capacity and accelerate economic growth. Secondly, government should increase its investment in transport and communication sectors, since it would reduce the cost of doing business as well as raise the profitability of firms. Thirdly, government should encourage the education and health sectors through increased funding, as well as ensuring that the resources are properly managed and used for the development of education and health services. Second, expenditure on transport and communication, as just noted, crowds in investment for developing countries only.

Ahmed, Habib and Miller, Stephen M (1999), that finding may suggest that there may be an optimal level of government expenditure. Devarajan, Swaroop, and Zou (1996) rationalize their findings of either no or negative effects of the components of government expenditure on the growth of real per capita GDP by arguing that the level of expenditure in the categories of negative effects must have gone beyond the optimum level.

2.5 THE RELATIONSHIP BETWEEN EXPORT AND GDP

Yousif K. Al-Yousif (1999) studied, he examine the relationship between export and economic growth in the Malaysian context using a vector-error-correlation (VECM) in which labor, capital and the exchange rate are allowed to exert their potential influence on exports and economic growth. Our finding from Johansen test shows that the five variables are co-integrated and thus have a long-run relationship. this implies that most previous studies in the Malaysian context that ignore cointegratedness between export and real output are miss specified for they ignore this important long -run information.

The studied by Michaely (1997), Heelr and Porter (1978), Balassa (1978), Ram (1985) and Feder (1983) support the view that export growth promotes overall economic growth. A serious drawback of cross section studies, however, is that the issue of causality between export growth and GDP growth is not address directly. However, faster growing economics may give rise to a greater dynamic export. Many authors have doubted the validity conclusions based on cross country studies. Sheehey (1990), for example investigates whether there are other productive categories besides export whose growth has a similar relationship to GDP.

Studies have found that a number of other determinant factors contribute to economic growth.

CHAPTER 3: RESEARCH DESIGN AND METHODOLOGY

3.1 INTRODUCTION

In this section, research methodology will discuss clearly researcher research plan. All the method used to gain understanding and answers to the research objectives, research questions and the research hypotheses. Research is simply the process of finding solutions to a problem after a thorough study and analysis of the situational factors (Uma Sekaran: Research Methods for Business, 2005). This section discusses the methods that will be use in the study such as will be discuss including the research design, sampling and data collection, the instruments used for the research, measurement and scaling, and the procedure in data analysis.

3.2 RESEARCH DESIGN

Research design is a master plan specifying the methods and procedures for analyzing and collecting the needed information. According to William G Zikmund, it is a framework or blueprint that plans the action for the research project. It details the procedures necessary for obtaining the information needed to structure or solve the research problem. Causal research design was used in this research to identify cause and affect relationship among variables, where the research problem has already been narrowly defined. The researcher wants to identify whether the factors such as inflation, government expenditure and export are influenced performance of Gross Domestic Product (GDP) in Malaysia.

3.3 DATA COLLECTION

According to Uma Sekaran (2005), data collection methods are an integral part of research design. Data collection is a way of gathering information for use in various studies or decision making situations. Depending on the required outcome or information needed methods of data collection can vary and even be combined to achieve needed results. Data can be obtained from primary or secondary sources.

3.3.1 Secondary data

The researcher firstly studies the entire journal from internet, newspaper, library and other related press to understand the Gross Domestic product (GDP). The previous research reports, books, library and articles are important sources to understand the issues. The data are being collected using the DataStream UiTM data. Secondary data helped the researcher to obtain the additional information about the study. It is based on the data that were collected for the purpose other than solving the problem at hand (Malhotra, 1999).

3.4 DATA PROCESSING

From all the data that been collected, it is then analyze to get result. To simplify the result so that the reader can understand it, the data then analyze using EViews program. The EViews program will make arrange the information and data into more simplified form to help the reader understand it. This program will explain the finding of the study which answer the objectives research questions. The method such as regression analysis, multicollinearity, heteroscedasticity and serial correlation can show the finding. Then it will transform in table, bar chart, pie chart and so on.

DATA ANALYSIS AND HYPOTHESIS TESTING

3.5.1 Multiple Regression Model

This tool is being use as the analysis to ensure the significant of the both data. It is used to analyze the expected relationship between the dependent variable and independent variable which are BFR, IR, and UER.

3.5.2 Coefficient of Determination (R²)

R² is to measure how many percent of change in the dependent variable that can be explained by the independent variable. The value of R² is from 0 – 1. If the result is 0 so there none changes in dependent variable will be explain independent variable. If the result is 1 so the changes in dependent variable can be explain by the independent variable.

3.5.3 F – STATISTIC

F – Statistic test is use to know the reliability the over all data. This method is to evaluate the significant of each data. The result significant show if less than 0.05. If the result is more than 0.05 it not significant.

3.5.4 T – STATISTIC

T – Statistic is used to examine the null hypothesis. It show where there is a significant relationship between dependent variable with each independent variable. If the T - value is higher it indicates there is significant relationship between the dependent variable and the independent variable.

3.5.5 BETA

Beta is used to determine which independent variables that most influence the NPAs of RHBIB. The highest beta the strongest contribution of predictor in explaining the dependent variable.

3.5.6 Multicollinearity

In the context of multiple regression, strong correlations among the explanatory variables, which often result in large estimated standard errors and insignificant estimated coefficients. This is essentially a property of the sample and not a problem with the method of estimation, although sometimes ridge regression is used as a remedy. Perfect multicollinearity occurs when some of the explanatory variables are perfectly correlated, i.e. linearly dependent; in this case the redundant variable(s) must be removed from the regression (Oxford references).

3.5.7 Heteroscedasticity

A set, or a vector, of observations is heteroscedastic if the variance is different for different observations. Heteroscedasticity observed in cross-sectional data is typically related to the scale effect: often, larger cross-sectional units are subject to larger erratic values of the disturbance. In time-series data it may take the form of serial correlation in the variance (autoregressive conditional heteroscedasticity) (Oxford references).

3.5.8 Serial correlation

The relationship between a given variable and itself over various time intervals. Serial correlations are often found in repeating patterns when the level of a variable effects its future level. In finance, serial correlation is used by technical analysts to determine how well the past price of a security predicts the future price. The term can also be referred to as "autocorrelation" or "lagged correlation" (Investopedia Dictionary). 

3.5.9 Regression analysis

Regression analysis is a statistical technique for studying linear relationship. It begins by supposing general form for the relationship, known as regression model.

Y = a + b1X1 + b2X2 + b3X3 + .........+ bkXk

Y = Dependent variable (GDP)

X1…Xk = Independent variables (inflation, government expenditure and export)

(northwestern.edu)

For regression analysis approach, "Ordinary Least Squares‟ (OLS) is the regression method that will be used in this study, specifically simple linear regression. OLS is a statistical technique that uses sample data to estimate the true population relationship between two variables so as to minimize the sum of the residuals squared.