multipurpose tree species research for small farms: strategies ... - part

The utility of this technique to MPTS is the ability
to analyze the adoption process in detail. In
designing an appropriate extension program it is
necessary to identify the target audience, and to
design the program to meet their needs. This
model allows the identification of individuals, using
a range of criteria, who are likely to be responsive
to the program.
The mathematical specification of the logit
model is presented below.
Let Y = 0 be the outcome of the dependent
variable to be explained by a number of other
variables Xi, i = 1 to n. Otherwise Y = 1.
Let P(Y = 0) be the probability that an event Y
will take the value. 0. Then P(Y = 1) = 1 -
P(Y =0).
The logit model assumes that the probability
P(Y =0) takes the form:
P(Y=0) = 1/{1 + exp(bo + biXi + b2X2
+ .The
Then the value of P(Y = 1) is
P(Y = 1) = exp(bo + biXi + b 2X 2
+ ...)/{I + exp(bo + blXI + ...)}.
The model then allows for easy estimation of the
parameters bi, since the odds, defined as the ratio
of P(Y = 1) to P(Y = 0), is a linear function:
P(Y = 1)/P(Y =0) = exp(bo + bIXI +
b 2X 2 + ... ).
This function can be estimated if the values
of P are known for each value of X. However, in
the case of individual observations, if the observed
data refer to Y and not to P, the simple method of
estimation cannot be used. The parameters of b
can be estimated using the method of maximum
likelihood instead.
The computation is made simple by using
available software packages which contain routines
to process the data using the model (Hall and
Lilien 1986).
A Hypethetical Example
Consider the case of a village involved in a
proposed woodlot project. The project design
team wants to find out if the villagers are interested
in taking part in planting for fuelwood. There are
many factors involved, as previously described.
They theorize that interest in participating will
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depend on factors such as land ownership, the
extent of land holding, the time spent collecting
fuelwood, the distance traveled, etc. To
establish the importance of the various factors
in assessing the response, they take a sample
survey of the villagers, noting the response and
the various characteristics ol the respondents.
The model would look like this:
INTER = f (LAND,TIME,CROPIN,DIST,
FUELAQ) where
INTER = 0 if the farmer is not interested
in tree planting
= 1 if he/she is interested
LAND = extent of land holding by farmer
TIME = time spent to collect fuelwood
CROPIN = income from cropping by the
farmer
DIST = the distance traveled to collect
fuelwood
FUELAQ = method of acquiring fuelwood,
whether by self or by purchase
results are presented in Table 1.
The rt;.-elt indicates that farmers are more
likely to be iierestcd in participating in the
project if they have to go a Iong way to collect
fuelwood, if they spend a lot oftime on the task,
or if they earn high incomes from cash crops
(coefficients for DIST, TIME and CROPIN are
positive). However, they are less likely to agree
to the project if their land holding is large, or if
they purchase fuclwood from others (the
coefficients for LAND and FUELAQ are
negative).
This result certainly suggests the role of cost
factors in influencing the farmers' preference
for the project, yet at the same time the effect of
land holding might be unexpected if it were
be!ieved that farmers wit h large holdin s would
be favorably inclined to participate in the
project.
In any case, the model identifies the relevant
factors influencing the outcome of a pro posed
project and assesses the weight of each factor
on the attitude of the farmer. This knowledge
would greatly enhance the design process for
creating projects to meet the needs and the
wishes of the villagers.