CHAPTER
FOUR
PRESENTATION AND ANALYSIS OF RESULTS
In the estimated the model,
variables considered are Poverty Level (Dependent variable) and the explanatory
variables; Agricultural Credit Guarantee Scheme Fund (ACGSF) and Government
Expenditure on Agriculture (GEA). It covers the period of years 1980-2010.
4.1 Presentation of Results
This research work employed the use of multiple
regression model based on Ordinary Least Square (OLS) method.
Modelling LPL by OLS
LPL = +4.063 -0.072 LACGSF +0.110 LGEA
T* = (14.929) (-2.329) (5.083)
S.E =
(0.272) (0.031) (0.022)
t0.025 =
2.048
F (2, 28) = 21.95
F0.05 = 3.34
R2 = 0.610540
DW = 0.455
4.2 Analysis
of Results
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
LACGSF and LGEA are -2.329 and 5.083
respectively. Considering the absolute values of the coefficients of LACGSF and
LGEA, their values are greater than the tabulated t- value which is 2.048 at 5%
level of significance. Thus, we conclude that their regression coefficients are
statistically significant.
Standard
Error test:
It is used to test for statistical reliability of the coefficient estimates.
S(b1) = 0.031 S(b2) = 0.022
b11/2 =
0.036 b21/2 =
0.055
Since S(b1) < b11/2
and S(b2) < b21/2, we conclude
that the coefficient estimates of S(b1) and S(b2) are statistically significant.
F-Test: This is used to test for the joint influence of the
explanatory variables on the dependent variable. The F-calculated value is 21.95 while the F-tabulated
value is 3.34 at 5% level of significance. Since the F-calculated value is greater than the F-tabulated value, we
conclude that the entire regression plane is statistical significant. This
means that the joint influence of the explanatory variables (LACGSF and LGEA)
on the dependent variable (PL) is statistically significant.
Coefficient of Multiple Determination (R2) It is used to measure the proportion
of variations in the dependent variable which is explained by the explanatory
variable. The computed coefficient of determination (R2 =
0.6105)shows that 61.05% of the total variations in the dependent
variable(LPL) is influenced by the explanatory variables namely ; Agricultural
Credit Guarantee Scheme Fund (AGCSF) and Government Expenditure on Agriculture (GEA)
while 38.95% of the total variation in the dependent variable is attributable
to the influence of other factors not
included in the regression model.
Durbin Watson statistics: It is used to test for the presence of positive
first order serial correlation. The computed DW is 0.46. At 5% level of
significance with two explanatory variables and 31 observations, the tabulated
DW for dL and du are 1.297 and 1.570 respectively. The
value of DW is less than the lower limit. Therefore, we conclude that there is
evidence of positive first order serial correlation.
4.3 Test of Hypothesis
The
researcher examines the impact of agricultural financing on poverty reduction
in Nigeria. With respect to this, the null hypothesis is stated as follows;
H0: Agricultural financing does not have
significant impact on Poverty reduction in Nigeria.
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. If F-cal > F-tab, reject the null hypothesis, otherwise accept
the null hypothesis. Using 5% level of significance at 2 and 28 degrees of
freedom, the tabulated F- value is 3.34 while calculated F-value is 21.95.
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 agricultural
financing has significant impact on Poverty reduction in Nigeria.
4.4
Implication of the Result
The regression result above shows agricultural
financing has significant impact on Poverty reduction in Nigeria. It is
estimated from the result that 1% increase in Agricultural Credit Guarantee
Scheme Fund (AGCSF) will, on the average lead to decrease by 0.07% in Poverty
Level. The sign borne by the parameter estimates is in conformity with the
economic a priori expectation. The result is in conformity with the assertion
of Ravallion, (2002) which states that “agricultural financing contributes to
poverty reduction which is sometimes thought to be small, because its relative
economic importance usually falls when low-income countries successfully
develop”.
However, the sign borne by the
parameter estimate of GEA does not conform to the a priori expectation. There
existed a positive relationship between Poverty level and GEA. Government
Expenditure on Agriculture increases while poverty is on the increase. This can
be attributed to the inability of farmers to benefit directly from the
opportunities surrounding government expenditure on agriculture.
CHAPTER
FIVE
SUMMARY,
CONCLUSION AND RECOMMENDATION
5.1 SUMMARY OF FINDINGS
This
research work sought to examine agricultural financing as a means of Poverty
Reduction in Nigeria from 1980 to 2010. Agricultural financing on poverty reduction
was captured using Agricultural Credit Guarantee Scheme Fund (AGCSF) and
Government Expenditure on Agriculture (GEA).
On the application of advanced statistical techniques
employed, the following information surfaced;
i.
The entire regression plane is statistical
significant. This means that the joint influence of the explanatory variables
(ACGSF and GEA) on the dependent variable (PL) is statistically significant.
ii. Agricultural
financing has significant impact on Poverty reduction in Nigeria.
iii. The
computed coefficient of multiple determination shows that 61.05% of the total
variations in the dependent variable (LPL) is accounted for, by the variation
in the explanatory variables namely; Agricultural Credit Guarantee Scheme Fund
(AGCSF) and Government Expenditure on Agriculture (GEA).
iv. The
total variation of 38.95% in the dependent variable is attributable to the
influence of other factors not included in the regression model.
v.
There is
evidence of first-order serial correlation (autocorrelation). It implies that
there are other variables which are not captured in the model.
5.2 Conclusion
There can be no meaningful Poverty Reduction without
adequate spending by the government. In government expenditure, there is need
to fund the agricultural sector. Such people in the sector are;
·
Predominance
of small scale producers with little asset base and working capital.
·
Need
to cultivate a new set of agricultural entrepreneurs to drive technological
change in agricultural production.
·
Long
gestation periods for agricultural production.
·
Public
subsidies for critical agricultural infrastructure with spill-over effects on
the economy.
·
Risks and
Uncertainties from natural causes.
Agriculture is fundamental
to the sustenance of life and is the bedrock of economic development,
especially in the provision of adequate and nutritious food so vital for human
development and industrial raw materials for industry.
The importance of poverty reduction is reminiscent in
the roles played by the poverty alleviation programme as a means of
understanding, controlling, altering and redesigning of economic growth (Olufemi, 2001). Agricultural financing has a link
with poverty reduction. As once remarked by Roseboom (1994), “In a developing
economy, poverty reduction cannot be dealt without agricultural financing”.
Thus, this research work examines agricultural funding as a means of poverty
reduction in Nigeria.
5.3 Recommendations
In the light of the
research findings, the following recommendations are presented;
·
In the bid to achieve poverty
reduction through agricultural financing, the annual budget by the federal
government should be considered with utmost care so as to enhance the adequate
funding of the agricultural sector.
·
Government funding on agriculture should be channelled to farm
mechanization. This will help to create employment and boost food production,
thereby reducing poverty.
·
Effort should be made by the Government to see that rural farmers
benefit the opportunities surrounding her expenditures as this will also
contribute to Poverty Reduction in Nigeria.
·
The CBN can as well advise commercial banks to allocate a reasonable
percent of their lending to agriculture so as to reduce poverty in the society.
·
There is need to understand the endemic problems of the agricultural
sector. This will help to ascertain the allocation of funds by government and
private individuals for better financing.
·
Increase on Salaries/wages most at times makes work attractive. This
should be the case in the agricultural sectors. As the income or wages of
farmers increase, this will cause an inducement on unemployed youths in
engaging themselves in the agricultural activities thereby contributing to
poverty in the society.