The study deals with an empirical analysis on the
relationship between inflation rate and government expenditure in Nigeria
1980-2009. It is purely a survey of inflationary trend along side with the
level of government expenditure over the years to maintain stability in the
Nigeria economy.
Model Specification
By theoretical definition, ‘it is
given that a country inflation rate is negatively related government
expenditure. Therefore, the analytical model for this study can be stated to
reflect that the rate of inflation (Ø) is a function of government expenditure
(G).
That
is Ø = F (G)
For the purpose of this study. I
assume the following linear model. A regression model is linear when the
parameter of the model occurs linearly. Therefore from the functional
relationship we can write an equation
Ø
= b0 +bi G + U
Where
Ø
= dependent variable – inflation rate
G
= independent variable – Government expenditure
B0,
b1 = coefficient of the parameter estimates of the regression line.
U
= Error term
Sources of Data
In carrying out this study, the
research made use of secondary method of data collection. The data were
gathered from public sources of some government agency and parastatals. They
were data collected over the year and statistical bulletin and statistical
abstract of federal office of statistic, the central bank of Nigeria (CBN).
Data obtain cover the period 1980-2009 and mainly an index of government
expenditure and inflation rate.
Procedure for Data Analysis
In the regression analysis, tables
and ordinary least squares were used in determining the relationship between
the variables. The variable span through inflation rate and total government
expenditure, which is employed in the model specified above.
Ø
= b0 + bi G +U
Where
Ø
= inflation rate
B0
= the intercept
B1
= parameter estimate
G
= Government expenditure
U
= Error term
Tested above, the calculated
variable of the parameter (b0 and bi) are used to divide the parameters in the
regression model. This gives the t* - the computed values which is thus
compared with the critical table values (t0.025)
(Cap)
= computed value
t0.025
= critical table value
n
= number of years
k
= number of parameters,
Decision Rules
Which
is thus compared with the critical table values (t 0.025)
(Cap)
= computed value
t0.025
= critical table vaule
n
= number of years
k
= number of parameters,
Decision Rules
The study will reject H0 if the computed value (t* -
values) greater than the critical table value (t0.025) and alternatively
accept.
H1. that is, if t* > t0.025 accept H1 and reject
H0. if otherwise the researcher reject H1 and accepts H0. That is, if t* <
t0.25.