International Journal of Horticulture, 2018, Vol.8, No. 2, 8-15
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Table 2 Costs and returns to vegetable production using budgetary analysis
S/N
Item
Mean Amount
Vegetable Production
1
REVENUE
I
Quantity of vegetable harvested(kg)
716.03
II
Price per kg
83.82
A
Total Revenue (TR)
60,017.63
2
VARIABLE COSTS
I
Cost of Labour
14,236.76
II
Cost of Seed
8,367.84
III
IV
Cost of Chemicals
Miscellaneous
14,209.41
166.91
B
Total Variable Cost (TVC)
36,980.92
C
Gross Margin(GM)=(TR-TVC)
23,036.71
D
Total Fixed Cost (TFC)
18,207.16
E
Total Cost (TC)=(TFC+TVC)
55,188.08
F
Net Income (NI)=(GM-TFC)
4,829.55
G
Benefit Cost Ratio = TR/TC
1.09
H
Expense Structure Ratio= TFC/TVC
0.49
I
Rate of Return = NI/TC
0.09
J
Gross Margin Ratio = TC/TR
0.92
K
Efficiency level =π/
0.09
Note: Data analysis, 2016
Table 3 Marginal value product and unit cost of each resource
Resource
MPP
Unit price of input (₦) MVP
MFC (₦)
MVP/MFC
REMARK
Farm size
39,438.40
1,327.21
52343,038.86
1,327.21
39,438.40
Underutilization
Seed
7,127.94
535.15
3814,517.09
535.15
7,127.94
Underutilization
Labour
9,476.56
766.67
7265,394.26
766.67
9,476.56
Underutilization
Fertilizer
751.17
5,565.00
4180,261.05
5,565.00
751.17
Underutilization
Pesticides
18,605.12
1,056.00
19647,006.72
1,056.00
18,605.12
Underutilization
Note: Data analysis, 2016
2.4 Efficiency of resource use using stochastic frontier analysis
The sigma squared (σ
2
= 0.0026) and the gamma (ɣ = 0.99) were quite high and significant at 1.0% level of
probability (Table 4). This indicates the goodness of fit and the correctness of the specified assumption of the
composite error term distribution (Okoye and Onyenweaku, 2007). The gamma (γ = 0.99) shows that 99 percent
variation in the total production cost is due to differences in their technical efficiency among the production units
considered in the study. By implication, about 1% of the variation in output among producers is due to random
factors such as unfavorable weather, effect of pest and diseases, errors in data collection and aggregation etc.
The coefficients of all the variables have desired positive sign, which agrees with
a priori
expectations. Quantity
of seed, farm labour, fertilizer’s coefficients were highly significant at 99% confidence level while farm size and
pesticides’ coefficients were significant at 5% level of probability. This implies that increasing quantity of seed,
fertilizer and farm labour by 1.0% would increase the economic efficiency by 0.067, 0.035 and 0.114 respectively.
This is in line with the findings of other studies (Umoh, 2006; Okezie and Okoye, 2006; Udoh and Etim, 2008;
Okon et al.,
2010) which indicates the importance of labour, seed, fertilizer in vegetable production. Since, the
increase in the quantity of seed, fertilizer and farm labour is less than the proportionate increase in efficiency, the
output of vegetable is said to be inelastic to the inputs used in the area. Also, 5 per cent increase in farmland area
cultivated given the input; pesticide will correspond to an increase in economic efficiency of vegetable with 0.190
and 0.076 respectively.
