LABOUR COST ANALYSIS AND TRANSMISSION EFFECT OF CASSAVA PROCESSING

Objective of the Study
            The broad objective of this study is to determine labour cost analysis and transmission effect of cassava processing in Ebonyi state.
            The specific objective is to determine the relationship between the socioeconomic characteristics of cassava processors and their level of utilization of cassava in the study area.
Hypothesis

            The null hypothesis was used Ho: The socio economic characteristics of cassava processor do not have significant difference on their level of cassava utilization in the study area.
Data Analysis
Model specification
Multiple regression analysis were used to determine the socioeconomic characteristics of cassava processors on their level cassava utilization in the study area.
The model are stated as;
Y         =          (FX1, X2, X3, X4, X4, X5, X6+
Implicit form
Y         =          a0+ a1 + a1 + a2 + a2 + a3 + a3 + a4 + a4 + a5 + a5
                        Explicit function
Where;
Y         =          Level of cassava utilization
X1        =          Age (years)
X2          =          Marital status
X3          =          Educational level (yrs)       
X4          =          Annual Income (N)
X5          =          Labour cost.
X6          =          Faming experience 9yrs)
qt         =          Error term
F          =          Function
ao         =          constant
a1           =              Multiple regression coefficient



Variable
Variable name
Regression coefficient
Std error
T-value
Sign
Consistent 
-
1.757
0.727
2.146
0.021
X1
Age
-0.112
0.074
-1.505
0.142
X2
Marital status
0.007
0.229
0.030
0.976
X3
Educational level
0.056
0.076
0.736
0.467
X4
Annual income
0.373
0.184
2.028
0.051
X5
Labour cost
-0.023
0.56
-0.401
0.691
X6
Farming experience
0.313
0.114
-2.747
0.010
R2 (square)                            =          0.867
Adjusted R2               =          0.841
Standard Error of the estimates     = 106.73636
Durbin-Watson         =          1.924
Source: Computed data, 2013
After critical examination of the regression coefficient result the coefficient of determination(R2) value was 0.867(86.7%) indicating that about 86.7% variation in the dependent variable (level of cassava utilization) used in the regression model was caused by combined effect of charges in the explanatory variables (Socioeconomic characteristics adopted). The R2 value is high-enough to justify the good fit of regression model, since explanatory variables exert effects on the explained variable. Also, adjusted value R2 square 0.841(84.1%) which is very close in numerical value of R2 square. This closeness in the numerical implies that the explanatory power of regression mode adopted was not exaggerated.
            The regression coefficient of Age(X1) was negatively signed and was statistically insignificant. This means there is inverse relationship between age (X1) and level of cassava utilization among the selected farmers in the study area. The apriori expectation was not met. This is true because increase in age will increase level of cassava utilization among the farmers in study area.
            Marital status (X2) coefficient had a positive coefficient and statistically insignificant beyond the 15% level of significance.
            This implies that there is a positive relationship between the martial status (X2) and cassava utilization in the study area. This could be that there is no gender difference among the cassava processing in the study area. This conforms with the apriori expectation of the study.
            The coefficient of educational level (X3) and annual income (X4) has a positive relationship with the utilization of cassava product by the selected cassava processors in the study area. The regression model also showed that educational level was statistically insignificant while the annual income was statistically significant at 10% level of significance. This implies that the educational status and annual income has a significant role to play in utilization of cassava product. The apriori expectation was met because increase in educational level and annual income will positively influence the extensively utilization of cassava. Education helps in terms of well utilization of available resources and adoption of new innovation.
            Furthermore, the coefficient of labour cost bore negative coefficient and statistically in significant beyond 10% level of significance in regression model. This means that inverse relationship exists between the labour cost (X5) and level of cassava utilization among the selected cassava processors. The apriori expectation was met because increase in labour cost will negatively influence the price in market which the poor one can afford and leads to hunger in the study area.
            Farming experience (X6) had a positive relationship relented to the apriori expectation of the study. It was also statistically significant at 10% level of significance in the regression model of the study. This is true the more the farmer gets knowledge the higher the adoption of new technology and good management of the whole farm (wise in utilization of available resources) by the farmer.
Y         =          1.757  +  0.112          +  0.007          +  0.056          +  0.373
                        (0.727)   (0.074)          (0.229)          (0.076)            (0.184)
                        -0.023  +  0.313  + et
                        (0.056)  (0.114)
Testing of hypothesis
Decision Rule
If the f-cal is greater than f-tab, null hypothesis will be reject otherwise accept the alternative hypothesis.
F-cal               =          R2(N-k)
                                    1-R2(k-1)
where;
R2        =          coefficient of determination
N         =          Sample size
K         =          Number of variables
F-cal   =          0.867(40-6)
                        1.0867(6-1)
F-cal               =          38.148
                                    0.665
F-cal               =          57.36
F-tab at 0.05 level of significance
f-tab                =          2.76
            However, since the f-cal is greater than the f-tab, the null hypothesis was alternative hypothesis.
            And this implies that the socio-economic characteristics of cassava processors have significant difference on their level of cassava utilization in the study area.

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