For this research in this chapter, we will observe the determinants that may affect the Inflation in Malaysia. One of the major statistical techniques used to examine the relationship between the independent

variables and the dependent variable is Regression Analysis technique. This regression can be used to explain and

describe the movement of one variable to another variable. The objective of

this analysis is to figure a regression model and to predict the variables

based on the coefficient resulted from the regression. Sekaran & Bougie (2009) stated

that, this analysis provides a means of objectively measuring the degree and the character of the relationship.

Accordingly, a Multiple Linear Regression analysis is carried out to

predict the value of a dependent variable, Inflation. Sources of data based on secondary data and there are no primary data

involve in this study. In addition, data stream is the main sources to get the

quantitative data. Data searched are Gross Domestic Product, Money Supply, Interest Rate, Import

Goods and Services and Government Expenditure.

The data that is to be analysed using the time

series data that have been obtained from the journal of Inflation in Malaysia derived from the Management Faculty of Multimedia University and Bank Negara Malaysia (BNM) ranging from year 2004 to year 2016. This research

consists of the

econometric model that is used to identify the relationship between the dependent variable and the independent variable. There are two models

that are used in this model which

are the mathematical model and the econometric

model. As per the equation below, inflation is the dependent

variable whereas the independent variables are Gross Domestic

Product, Government

Expenditure, Imported Goods and Services, Interest Rate and Money Supply.

Regression equation is an equation which expresses the linear relationship between the variables that are shown in the regression above. All the

computed values that are obtained from the SPSS show the function of inflation on these independent variables in this

econometrics model.

Based on the regression analysis above, it shows that the numerical values in brackets are

known as standard error. The econometric model shows the relationship between

the independent variable and the dependent variable. According to Phillips

curve theory, the

model proved the negative and positive relationship between the inflation and independent variable. Import goods and services also have a negative relationship

with inflation as well. If the interest rate increases, so the inflation also will increase.

The value of R² is 0.455 indicates that 45.5% of the

variation is the dependent variable which is the inflation; explained by the

variability of the independent variable which are gross domestic

products, government expenditure, imported goods and services,

interest rate and money supply.

From the Multiple Regression Analysis, it was found that gross domestic products, government expenditure, imported goods and

services, and money

supply are negatively related to inflation while interest rate

is positively related with inflation.

As this chapter covers about inflation as a major problem and it will not only affect a country’s economic

growth, but the findings also show that the independent variables has negative

impact on inflation except for the interest

rate. The government should cut

the expenses on non-development activities to overcome the problem of high inflation in

Malaysia. Besides, this chapter also explains about from where the data has been obtained and how we have analysed the data along with

clarifying the equation that have been

obtained from SPSS

data in chapter 4.