The Future of Smallholder Farming in Eastern Africa - Uganda ...

was corrected using the White-Huber sandwich estimator as implemented by Stata version 7.0
that uses standard errors that are robust to hetero-skedasticity.
Since the regressions had many explanatory variables, multi-collinearity could not be ruled out.
This was investigated using the variance inflation factor method (Chatterjee and Price 1991).
Since the maximum VIF was less than 3, we found that multi-collinearity was not a serious
problem.
We tested for normality of the error term using the Jargue Bera Langrage multiplier test of
skewness and kurtosis, as well as using the Shapiro Wilk and Shapiro Francia tests of normality.
The tests revealed that the variables of crop value, acreage, and off-farm income were not
normally distributed. Using the Box Cox power of transformation, the log transformation was
identified as the most appropriate transformation of the variables to normality.
We examined the appropriate mathematical functional forms (non-linearity and interaction terms
in the data) of the variables in the regressions. Using the exploratory band regression method
(Linear spine method), the variables of fishv (value of wetland fishing), buildv (value of wetland
building material collection), fuelv (value of wetland fuel collection) and totlvsin (total livestock
income), showed a non-linear relationship with the dependant variables, hence their quadratic
functional form was included in the models, which greatly improved model specification. The
Ramsey regression error specification test (REST) for omitted variable bias could not be
performed, as it is invalid for ordered probit models, however the Hosmer-Lemeshow goodness
fit test showed that the models are generally good fits. We did not suspect Endogenity bias
problems in all these regressions hence we did not perform the Hausman-Wu specification tests.
All these tests were performed using Stata version 7.0.
5.2.2 Determinants Of Wetland Diversity And Food Security
The results of the econometric analysis for Wetland Diversity and Food Security are presented in
the following table.