For from the journal of Inflation in Malaysia derived

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.

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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.