OBJECTIVE OF THE STUDY
The broad objective of the stuffy is to understand poverty
its causes, effects and protect strategies that may be employed to reduce the incidence
in Abakaliki Local Government Area of Ebonyi State.
The specific objective is to
determine the effect of the socio-economic characteristics of the respondents
on their level of acceptance in the study area.
Hypothesis
Null hypothesis were has;
The
socio-economic characteristics of the moral people have no significant effect
on their level of acceptance in the study area.
Data
analysis
Multiple regression analysis were
used to analyzed the objective selected for the study.
The model specifications were as
follows:
Y = F(x1,
x2, x3, x4, x5, x6)
Implicit function.
Y = b0
+ b1, + b2 x2 + b3 x3 +
b4 + b4 x4
b5 x5
+ b6 x6 + et explicit form
Where:
Y = level
of participation in poverty alleviation programmers
X1 = Age
(years)
X2 = Sex
=
X3 = Marital
status
X4 = Level
of Education (years)
X5 = From
size (La)
X6 = Faming
experience (years)
|
Variable
|
Variable
name
|
Regression
coefficient
|
Std
error
|
T-value
|
Size
|
|
Constant
|
-
|
1.75
|
0.727
|
2.416
|
0.021
|
|
X1
|
Age
|
0.112
|
0.074
|
-1.505
|
0.001
|
|
X2
|
Sex
|
0.007
|
0.229
|
0.030
|
0.976
|
|
X3
|
Mantel
status
|
0.056
|
0.76
|
0.736
|
0.467
|
|
X4
|
Educational
status
|
0.373
|
0.184
|
0.000
|
0.051
|
|
X5
|
Annual
income
|
|
0.056
|
0.401
|
0.007
|
|
X6
|
Family
size
|
|
0.114
|
2.747
|
0.010
|
R2(square) = 0.727 x 100 = 72.7%
Adjusted
R2 = 0.713
Std.
Error of the estimates = 0.73636
Durbin
– Waston = 1.949
Source:
Data analysis, 2013
The
result of analysis showed that a coefficient of multiple determinations R2
of 0.727. This shows that about 72.7% change in the dependent variable (level
of participation in poverty alleviation programmes) was caused by changes in
the independent variable (socio-economic characteristics of the respondents).
This is quite high in dictating that the socio-economic characteristics of the
respondents had significant influence on their level of participation in
poverty reduction strategies in the study area.
The coefficient of age (x1)
had a positive coefficient indicating positive relationship with the dependent variable,
but statistically significant. This shows that the higher the age of the forms,
the make they participate in poverty reduction programme in the study area
Sex (x2) was negatively signed
but not statistically significant, this reveals that negative relationship
exist between the respondents level of participation in poverty reduction programmes
and their socio-economic characteristics. It could be that male farmers
participated in poverty reduction programmes than female farmers or vice versa.
The coefficient of marital status (x3)
was positively signed and highly insignificant. This implies that positive
relationship exists between the respondents marital status and their level of
participation in poverty reduction programmes which level of participation in
poverty reduction programmes which means that married farmers participated in
poverty reduction programmes in the study area.
The respondents level of education (x4)
was highly statistically significant at 10% level of significant, and
positively signed, slowing that positive relationship is existing between the
respondent level of reduction and their level of participation in poverty reduction
strategies in the study area. This means that the higher the level of education
the higher than level of participation in poverty reduction programmes.
Also, family size (xg)
which was highly statistically significant at 10% level of significance and
indicated a positive coefficient meaning that positive relationship is existing
between family size of the respondents and their level of participation in
poverty reduction programmes. This implies that farmers with high family size
participated more in poverty reduction programmes than those with lower family size.
This is because the farmers with large family size have more months to feed and
to take part seriously in poverty reduction programmes in order to increase
productivity and have sufficient food to feed to their dependents.
Moreover, the respondent annual income
(x6), which was positively signed and highly statistically
significant at 5% level of significance was equally indicting that positive relationship
exists with the dependent variable (level of participation in poverty programmes
in the study area).
Hypothesis Testing
Decision Rule
If
F – cal is greater than F – tab, reject null hypothesis otherwise accept the
alternative hypothesis
F – cal
= R2 (N – K)
1 – R2
(K – I)
Where;
R2 = Multiple
coefficient determination
K = Number
of variable
N = Sample
size
F - cal 0.727 (40 – 6)
1
– 0.727 (b-1)
F – cal 31.988
1.365
F – cal 23.434
F – tab at 0.5 level of
significance
F – tab = 2.80
Mean
which, the f – cal was greater than the f – tab the null hypothesis was
rejected and alternative hypothesis accepted. Therefore, it implies that the
socio-economic characteristics of the rural people/farmers have significant
difference on the their level of participation in poverty reduction programmes in
the study area.