| Abstract: | Micro irrigation is one of the most useful irrigation systems designed to increase production and productivity; and reduces risk, related with rainfall variability and increases income of rural farm households too. Not surprisingly, planners, researchers, development practitioners, and donors emphasize the importance of micro irrigation in their policy recommendations and actual measures. So, this study examines the adoption and impact of micro irrigation on farm households’ income in Bambasi Woreda. The main objective of this paper is to investigate the factors that determine the adoption and impact of micro irrigation on the income of rural households. This paper is used a cross-sectional household level survey data. Multistage sampling was employed to select the four kebeles from Bambasi woreda. The information is obtained from a total sample of 383 randomly selected households. Of these total sample households, 169 households are micro irrigation users, and 214 households are none users. Secondary data were collected from different sources. The data collected were analyzed through logit model and propensity score matching. As the result of the logit model reveals that gender, age, education, family size, non-farm participation, access to irrigation water, extension service, frequency of DAs(Department of Agriculture ), total livestock unit, and market distance in kilometers are statistically significant and economically meaningful variables which significantly affect the probability of adoption of micro-irrigation of the households. Similarly, the estimates of the propensity score matching exhibits that gender, age, education, family size of the household heads, non-farm participation, social participation land size in hectare, access to irrigation water, extension service, frequency of DAs contact, total livestock unit and market distance in kilometer are the statistically significant variables which significantly affects income of micro-irrigation. Furthermore, the nearest neighbor, radius, kernel and stratification matching methods show a statistically significant result with bootstrapped standard errors and the average treatment effect for treatments of the radius and kernel matching is 14,431.78 birr where as the ATT of the nearest neighbor and stratification matching is 14,451.68 birr and 14,392.00 birr respectively as compared to the control groups. The result of ATT shows a significant income difference. |
