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
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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.
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.
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.
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.
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