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.