3 Results
3.1 Sample characteristics
On average, the household heads were 44 years old, with AFS farmers
being the youngest (Table 2). In terms of education, 15% of household
heads were illiterate. The average family size was 7 which is above the
national average i.e. 4.9 (CBS, 2012). The majority of households (57%)
were male-headed. AFS adopting households were more male-headed (65%)
compared to the other two farming systems (55% for both ACS and CAS).
Farmers had both off-farm and on-farm income sources. Of total
respondents, 46% of households had both off-farm and on-farm sources of
income while the rest were dependent only on on-farm income for their
livelihoods. Overall, 44% of the sample households had a private source
of irrigation. Specifically, 62% of AFS farmers had access to the
irrigation facility while only 46% and 35% of farmers from ACS and CAS
respectively possessed this facility. The study area consisted of both
native and migrated farmers. More farmers (56%) were migrated in the
study area. 58% of farmers were native in the AFS category while there
were only 40% and 41% native farmers in ACS and CAS respectively.
Out of eleven variables (continuous) tested, five variables i.e.
education, landholding size, livestock herd size, extension service, and
availability of transport means are significantly different in their
mean values (Table 2). The mean values of three variables i.e. household
head’s age, household size (economically active) and crop diversity were
significantly different for CAS and ACS. The statistics suggest that the
households with large holdings and bigger livestock herd size that are
headed by a young and educated male family member receiving more
extension services tend to adopt the tree-based farming (Table 2).
3.2 Association, relative risk and significance of explanatory variables
with regards to the choice of farming systems:
The parameter estimates (association) and relative risk ratios (RRR) of
the MNL model for AFS and ACS with CAS as a reference group are reported
in Table 3. The coefficients show the direction of explanatory
variables, while the RRR shows the likelihood of adoption/dis-adoption
of AFS and ACS by farmers with respect to CAS. The model was significant
at the 1% level. The log-likelihood ratio (LR) test shows that the
estimated model, including the constant and the set of explanatory
variables, fits the data better compared with those containing the
constant only. In other words, there is a significant relationship
between the likelihood of adoption/dis-adoption of agroforestry systems
and the explanatory variables included in the model. The result suggests
that these variables contribute significantly as a group to the
explanation of the agroforestry adoption behaviour of the sample
farmers, although several coefficients and RRR were not significant
individually.
Except for the variables ‘irrigation facility’ and ‘origin’ (types of
household), all other variables had expected signs. ‘Irrigation
facility’ was found to be positively associated with the adoption of AFS
and ACS but not significant for ACS. ‘Origin’ was found to be negatively
associated with the adoption of ACS only, which means a migrated farmer
is more likely to prefer ACS to CAS. Out of fifteen variables tested,
twelve variables were significant in the case of AFS while there were
only five variables significantly affecting the adoption of ACS. Our
result suggests that the likelihood of adopting AFS would increase by a
unit of 1.323 if the household head were a male. Similarly, the AFS was
2.9 times more likely to be adopted by households having off-farm income
sources. Having a private source of irrigation would increase the
likelihood of AFS adoption by 1.73.
There are some variables with negative signs indicating that these
variables decreased the likelihood of adopting AFS and ACS with respect
to CAS. If a farmer were risk-averse, the likelihood of adopting AFS
would decrease by 89%. In other words, a risk-averse farmer is less
likely to adopt an agroforestry system. Similarly, having own source of
transport would decrease the likelihood of AFS and ACS adoption by 50%
and 16% respectively compared to CAS.