*3.3. Determinants of Adoption of Climate Change Adaptation Strategies*

The estimation of the MNL model for the determinants of the choice of adaptation strategy mix to the variable but adverse impacts of climate was accomplished by normalizing the "Off-farm adaptation" category to become the reference category. This allowed analyses and comparisons of the different actual adaptation strategy mixes used by different households in Bobirwa sub-district. Table 9 presents the MNL model marginal errors together with their standard errors (in parentheses) and levels of significance.


Standard errors in parentheses; \* *p* < 0.05, \*\* *p* < 0.01, \*\*\* *p* < 0.001. Source: Household Survey Data, 2017. Key: 001 = Livestock-related Adaptations Only; 010 = Land, Soil and Water Conservation Adaptations Only; 011 = Land, Soil and Water + Livestock-related Adaptations; 100 = Crop Adaptations Only; 101 = Crop + Livestock-related Adaptations; 110 = Crop + Land, Soil and Water Conservation Adaptations; and 111 = Crop + Livestock + Land, Soil and Water Conservation Adaptations.

The results in Table 9 show a *p*-value of the F-statistic (Prob > Chi2) of 0.000 indicating that the variables used in the model, including the model itself, are very significant (*p* < 0.05). The null hypothesis which states that the social and economic attributes considered in this study do not explain the adaptation choices by households in Bobirwa sub-district is rejected since the model F-statistic has an R<sup>2</sup> greater than zero. Therefore, the attributes of households considered in this study significantly explain some of the variability in adaptation choices by households in the study area, i.e., with a pseudo R<sup>2</sup> of 0.2503, about 25% of the choice of adaptation strategy mix by households in Bobirwa sub-district was due to variations in the different social and economic attributes in Table 9. Table 9 shows that several variables had a significant influence (*p* < 0.05) on the type of adaptation measure chosen by households.

Table 10 above gives a summary of the different adaptation strategies whose likelihood of adoption was positively or negatively influenced the different socio-economic attributes of the surveyed households. Whether a variable has a positive (negative) or a significant (non-significant) influence on the adoption of any adaptation strategy does not imply a "cause-effect" relationship although, in some instances, causality does exist. Table 11 below shows how the factors considered in explaining household adaptation choices (Table 9) influenced the extent of the adoption of the different strategies. The same explanatory variables revealed a lower inference power on the extent of the adoption of adaptation strategies as shown by a pseudo R2 value of 0.1578, i.e., only 15.78% of the variation in the extent of adoption by the surveyed households can be explained by those factors which influenced the choice of adaptation strategies by households in Bobirwa sub-district.


**Table 10.** Summarized influence of determinants of adaptation in Bobirwa sub-district.

Key: 001 = Livestock-related Adaptations Only; 010 = Land, Soil and Water Conservation Adaptations Only; 011 = Land, Soil and Water + Livestock-related Adaptations; 100 = Crop Adaptations Only; 101 = Crop + Livestock-related Adaptations; 110 = Crop + Land, Soil and Water Conservation Adaptations; and 111 = Crop + Livestock + Land, Soil and Water Conservation Adaptations.

**Table 11.** Marginal effects of determinants of the extent of adaptation in Bobirwa sub-district.



**Table 11.** *Cont*.

Standard errors in parentheses; \* *p* < 0.05, \*\* *p* < 0.01, \*\*\* *p* < 0.001.

#### 3.3.1. Gender of Main Decision-maker

Table 9 shows that the gender of main decision-maker in the household (De jure household head) had no significant effect (*p* > 0.05) on the adoption of any strategy. Results show that households with females as the main decision-maker were less likely to adopt Land, Soil, and Water + Livestock-related Adaptations; Crop Adaptations Only; Crop + Livestock-related Adaptations; and Crop + Livestock + Land, Soil, and Water Conservation Adaptations and more likely to adopt off-farm adaptations. Conversely, households with male decision-makers were more likely to adopt the four adaptation strategies compared than they would off-farm adaptations. On the contrary, households with females as main decision-makers had higher chances of adopting Livestock-related Adaptations Only; Land, Soil, and Water Conservation Adaptations Only; and Crop + Land, Soil, and Water Conservation Adaptations than off-farm adaptations. Similarly, households with male decision-makers were less likely to adopt the three adaptation strategies than they would off-farm adaptations. Gender had no significant influence on the adoption of any of the strategies.
