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

Bureau of Statistics based on the 1999 population census (CBS 2001). Based on these figures,
Mtito Andei division had a population of 66,663 people in 13,354 households. These
households were clustered in 228 villages. Twelve villages were randomly selected. From
these villages 180 households were then randomly sampled, with probability proportional to
population size of village. The selected households were visited, and the household head
interviewed.
3.3 Data analysis
Descriptive statistics were used to describe the characteristics and activities of
CBAHWs and the farm and personal characteristics of the livestock keepers. The relationship
between the characteristics of the CBAHWs and their level of success was established using
correlation and regression analysis.
In assessing the success of the CBAHWs, the study tracked their performance through
activity analysis and used level of activity as a performance measure. Generally in such
estimations, relations are often modeled simply as structural relations between the traditional
factors perceived to be influencing activity levels and the variables representing output. Once
a decision about candidate variables is made, the specific relationship can then be modeled.
The quadratic model was selected in this case because of its computational ease, ease of
interpretation, interpolative and extrapolative robustness, and consistency with data.
The estimated model was of the form:
X = [ß][Z], (1)
where
X is the level of activity of CBAHWs, estimated as the number of cases handled in the
one-year period preceding the survey;
ß is a vector of estimated coefficients; and
Z is a vector of independent variables describing the characteristics of CBAHWs.
An ordinary least squares stepwise regression approach was used in estimation of the model.
Factors that are likely to keep CBAHWs in active practice were identified using a
logistic regression. The dependent variable in this case was observed as a binary indicator—
that is, whether or not a CBAHW is still providing services. Although it is possible to use
dummy variables as dependent variables to see such a dichotomous choice, ordinary least
squares regression is not appropriate in such circumstances for several econometric reasons.
Nonlinear estimation techniques have been developed to overcome some of the major
statistical problems. Two techniques most commonly used in this instance are probit and logit
analyses. The probit uses the cumulative normal function whereas the logistic function uses
the logit model. Although both use the maximum likelihood estimation method, the logistic
function 5 was thought to capture the distribution of the data better and thus used in this study
(Maddala 1983; Greene 1993).
5 Some of the outputs of the logistic procedure and their interpretation are given in the Appendix.