The broad objective of this study is to analyze the rice production and socio-economic factors affecting rice production in Ezza North L.G.A of Ebonyi State. The specific objective is to analysis the effect of socio-economic characteristics of respondents and output in rice production in the study area.
Hypothesis
H0: farmers do not have significant effect on the output in rice production in the study area.
Data analysis
Model specification is shown as, the multiple regression was used to determine the effect of the independent on the yield of rice production.
Y = F(X1 X2, X3 , X4 X5 + X5 X6) implicit function.
Y = ao + a1 x1+ a2x2 + a3 x3 + a4x4 + a5x5 + et
Where;
Y = Output of rice production (kg).
X1 = Age of farmers
X2 = Sex
X3 = Educational status
X4 = Farm size
X5 = farm Experience
X6 = Household size
Et = Error term
Regression analysis on the effect of socio-economic characteristics on output of rice production in the study area.
A multiple regression analysis was used to analysis the effect of socio-economic characteristics of rice producers on their output.
|
Variable |
Variable name |
Regression coefficient |
Std error |
T-value |
Sign |
|
Consistent |
– |
2.174 |
0.756 |
2.875 |
0.007 |
|
X1 |
Age |
-0.136 |
0.068 |
-1.995 |
0.054 |
|
X2 |
Sex |
0.005 |
0.230 |
0.020 |
0.984 |
|
X3 |
Educational status |
-0.201 |
0.159 |
-1.264 |
0.215 |
|
X4 |
Farm size |
0.255 |
0.134 |
1.904 |
0.066 |
|
X5 |
Farming experience |
-0.065 |
0.115 |
-0.567 |
0.575 |
|
X6 |
House hold size |
-0.153 |
0.109 |
-1.406 |
0.169 |
R2 (square) = 0.757
Adjusted R2 = 0.714
Standard Error of the estimates = 0.65589
Durbin-Watson = 1.946
Source: computed data, 2013
The result of multiple regression analysis as shown in table above showed that a coefficient of 0.757 was obtained. This implies that about 75.7% change in explained variable was caused by changes in the explanatory variables.
However, the coefficient of Age (X1) had a negative sign and was statistically significant at 10% level of significance in regression model in the study. This implies that there is a inverse relationship existing between the age(X1) and output of rice production in the study area. The a priori expectation was met because increase in the age increases the output.
The coefficient of sex(X2) bore a positive sign and was statistically insignificant beyond any level of significance in the study.
This implies that there is no gender dichotomy. The apriori expectation was met because when there is gender equality, there will be increase in output of rice production.
Furthermore, Educational status hard a negative sign and was not statistically significant at any level of significance.
This means that there is inverse relationship existing between the Educational status X3 and the output in the study area. The apriori expectation was not met. This is because educations play a
significant role in effective and efficiency of every farmers which help the farmers to enhance and extensively utilization available resources and increase his/her output.
Moreso, coefficient of farm size(X4) had a positive sign and was statistically significant at 10% level of significance in regression model. The apriori expectation was met. This is true because increase in form size of a rice farmer will lead increase in output.
Finally the coefficient of farming experience (X5) and house hold size(x6) had a negative sign and was statistically insignificant in regression model of the study.
It shown that farming experience and household size had a negative relationship with output in the study area.
Y = 2.174 – 0.136 + 0.005 – 0.201 + 0.255
(0.756) (0.068) (0.230) (0.159) (0.134)
-0.065 – 0.153 – et
(0.115) (0.109)
Testing of hypothesis
Decision Rule
If F-cal is greater than F-tab regret null hypothesis otherwise accept alternative hypothesis.
F-cal = R2(N-k)
1-R2(K-1)
where
R2 = multiple determination
N = Sample size
K = Number of variables
F-cal = 9.757(40-6)
1-0.757(6-1)
F-cal = 33.308
1.215
F-cal = 27.414
F – Tab at 0.05 level of significance
F- tab = 2.73
Since, f-cal is greater than the F-tab, the null hypothesis was rejected and alternative hypothesis was accepted.
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