Considering
the estimated model, variables used are Gross Domestic Product (dependent
variable) and the explanatory variables: Export rate, Import rate and Exchange
rate. The data obtained from the period
of 1979-2007 were used for the empirical result of the estimated equation
bearing in mind the objectives and hypothesis of the study.
It is noted that the researcher used
statistical software package called Pc-Give in running the regression. It is a
computer application which gives output of
regression results in an equation
format. This research work employed the use of multiple regression model based
on Ordinary Least Square (OLS) method.
Modeling
GDP by OLS
LGDP = + 10.8707 + 0.05736LEXP
+ 0.0595LIMP +0.3808EXD
T*
= (16.0626) (0.38296) (0.79907) (5.91266)
S.E = (0.67677) (0.14979) (0.13259) (0.06441)
t0.025 = 2.060
F (3,
25) = 11.667
F0.05 = 2.99
R2 = 0.7778
DW = 0.6982
Where
t* is the t-calculated, t0.025 is the t-tabulated at 5% level of
significance, F* is the calculated F-statistics, F0.05 is the F-tabulated
statistics, R2 is the coefficient of determination and DW is the
Durbin Watson statistics
ANALYSIS OF RESULTS
(a) T-test:
It is used to test for the statistical significance of the individual estimated
parameters. The calculated t-value for the regression coefficients of LEXP, LIMP and LEXD
are 0.38296, 0.79907 and 5.91266 respectively.
The tabulated t- value is 2.060. Since the calculated t-value of LEXD
is greater than the tabulated t-value at 5% level of significance; we conclude
that the regression coefficient is statistically significant. However, the
calculated t-value of LEXP and LIMP are less than the tabulated t-value.
Therefore, its estimated parameters are statistically insignificant.
(b) Standard
Error test: It is used to test
for statistical reliability of the coefficient estimates.
S(b1)
= 0.14979 S(b2)
= 0.13259 S(b3) = 0.06441
b1/2 =
0.02868 b2/2
= 0.02975 b3/2 = 0.1904
Since
S(b3)
< b3/2, we conclude that the coefficient estimate of b3
is statistically significant. However, S(b1) > b1/2
and S(b2)
> b2/2,
hence its coefficient estimate are not
statistically significant.
(c)
F-Test:
This is used to test for the joint influence of the explanatory variables on
the dependent variable. The F-calculated
value is 11.667 while the F-tabulated value is 2.99 at 5% level of significance. Since
the F-calculated 11.667 value is greater than the F-tabulated value of 2.99,
we conclude that the entire regression plane is statistically significant. This
means that the joint influence of the explanatory variables (LEXP, LIMP and LEXD)
on the dependent variable (LGDP) is statistically significant.
(d)
Coefficient
of Determination (R2):
It is used to measure the proportion of variations in the dependent variable,
which is explained by the explanatory variables. The computed coefficient of
determination (R2= 0.7778)
which shows that 77.78% of the total variations in the dependent variable (LGDP)
is influenced by the variation in the explanatory variables namely Export rate,
Import rate and Exchange rate while 22.22% of the total variation in the
dependent variable is attributable to the influence of other factors not
included in the regression model.
(e)
Durbin
Watson statistics: It is used to test for the presence of positive first
order serial correlation. The computed DW is 0.6982. At 5% level of significance with three explanatory
variables and 29 observations, the tabulated DW for dL and du are 1.20 and 1.65
respectively. The value of DW is less than the lower limit. Therefore, we
conclude that there is evidence of positive first order serial correlation (i.e
autocorrelation) which shows that there is omission of other important
variables which explains export promotion that are included in the regression model;
errors in the mathematical form of the equation; errors in the macro-variables
i.e smoothing processes of seasonal variation and misspecification of the
behaviour of error terms, which results in under-estimation of variances of the
parameter estimates and error term (u). Thus leading to accepting as significant
variables which in reality are not significant explanatory variables.
TEST OF HYPOTHESIS
The
researcher examines the impact of export promotion on Nigeria’s economic growth.
With respect to this, the null and alternative hypotheses are stated as
follows;
H0: b1 = 0 Export promotion has no significant
effect on Nigeria’s economic growth.
H1: b1 ≠ 0 Export promotion has significant
effect on Nigeria’s economic growth.
F-test
is employed in testing the hypothesis. This test will help to capture the
joint influence of the explanatory
variables on the dependent variable.
Decision Rule
If F-cal > F-tab, reject the null
hypothesis otherwise accept the null hypothesis. Using 5% level of significance
at 3 and 25 degrees of freedom, the tabulated F- value is 2.99 while calculated F-value is 11.667. Since the calculated F-value is greater than the tabulated
F-value at 5% level of significance; we reject the null hypothesis and conclude
that Export Promotion has significant effect on economic growth of Nigeria.
IMPLICATION OF THE RESULT
The regression result above shows that Export
promotion has a significant impact on Nigeria’s economic growth. It is
estimated from the result that 1% increase in Export, Import and Exchange rate will
on the average lead to an increase by 0.06unit, 0.10unit and 0.3unit in Gross
Domestic Product (GDP) respectively. The sign borne by the parameter estimates
is in conformity with the economic a priori expectation. In a nutshell, a
substantial export promotion will lead to expansion of export which will ploughed
back to increase the economy’s capacity.