13th Annual International Management Conference Proceeding

But,
Y � ax j
i
i
bi
xj
b
ui
je .......... .......... .......... .......... .......... .......... .......... .......... .......... .......... .......... ....( 6)
It follows that elasticity with respect to a particular input is equal to the exponent (b).
b b ui
axi
ix j je xi
E p � bi
* .......... .......... .......... .......... .......... .......... .......... .......... ( 7)
bi
b ui
x ax x je
� E
p
� b
i
i
i
j
.......... .......... .......... .......... .......... .......... .......... .......... .......... .......... .......... .......( 8)
Elasticity of production is used in deriving marginal products with respect to the various inputs.
3.0 Presentation, Interpretation And Discussion Of Findings
Introduction
This section presents, interprets and discusses the findings of the study. Findings were presented both
quantitavely and qualitatively. Findings were presented by use of tables for easy interpretation.
Demographic characteristics
Most of the respondents interviewed were men.69% of the respondents were males.
Most of the respondents had not attended school at all (42%). This means that agriculture has been left into
the hands of the uneducated. Participation in agriculture tends to reduce as the level of education increases.
This could mean that agriculture is left into the hands of the unskilled and old people. Most participants are
in the age group 31-40 and 41-50.
Most men and women below 30 years migrate to urban areas leaving agriculture in the hands of few
uneducated parents. This is because agriculture is traditionally viewed as a “dirty” business.
Regression Results of the major variables
This section first dealt with Land, Labour, Capital and manure. As noted earlier in methodology, a Poisson
regression (for use with regression based on count i.e. Number of bunches of bananas) was done to
determine the influence of these factors in determining Banana production in the area of study. Stata
software was used to carryout the analysis.
Test for normality was done and the independent variables, labour, land and capital were found to be
violating the normality principle. They were found to be positively skewed and in this case they were
transformed into logarithim form to simulate the normality component for regression.
Test for collinearly was done and all the independent variables were found to have a very weak relationship.
For instance, between land and labour variable the correlation coefficient was found to be –0.02556 while
between capital and land was found to be 0.1524. Between capital and labour was found to be 0.
Poisson Regression Number of Obs = 200
Prob > chi2 = 0.0000
Pseudo R 2 = 0.5892
Table 3.1: Regression results
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Output | IRR Std. Err. Z P>|z|
-------------+----------------------------------------------------------------------------
lnlbr | 1.470545 .0291346 19.46 0.000
lnland | 1.736113 .0222952 42.96 0.000
lncap | .7108875 .0102124 -23.75 0.000
Manure | 1.731499 .0357789 26.57 0.000
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