Climate Resilient Agriculture: Impact Assessment of Adopting Enhanced Farm Input Technologies for Improvement of Farmers Livelihood in Ethiopia

概要

Agriculture in Ethiopia is characterized as mixed agriculture constituting crop and livestock production in the highlands and pastoralism in the lowlands. In this study we tried to assess the status of mixed agricultural production system. It is a backward agricultural production system with low production and productivity attributable, but not limited to inefficient input technologies and climate change. Most of the Ethiopian farmers are still using animal power for plowing, threshing, and transporting. Land preparation takes longer period stretched from March to July. As a result, the productivity of land and labor is too low to meet the current demand of farm products in the country. Further, inefficient agricultural input technologies coupled with the climate change makes the situation worse and forced part of the rural farm households (HH) to depend on food support. Drought is one of the major effects of climate change that adversely affecting agricultural production in Ethiopia and severely leads to soil erosion and environmental degradation due to lack of alternative water source. These are challenging the agricultural production system enough to meet the current farm products demand and maintain for the future needs. Therefore, promoting climate resilient sustainable agriculture requires due attention that copes the adverse effect of climate change and meet the current demand of agricultural products without compromising the future needs by promoting efficient input technologies and irrigation systems.

The study was conducted to understand the impact of enhanced agricultural input technologies in promoting climate resilient agriculture. Specifically, it was planned to investigate farmers preferences for agricultural tractors. Second, a quasi-experiment was conducted to measure the impact of small-scale irrigation motor pumps (SSIMP) on farmers HH income in cases where small- scale canal irrigation system (SSCIS) is not applicable due to other constraints. Both primary and secondary data were used in the analysis. The primary data were collected using a structured questionnaire with two rounds in 2017 and 2019 comprising a sample of 79 and 92, respectively. The secondary data are survey reports and annual reports from concerned offices, including office of agriculture and national bank of Ethiopia.

Choice experiment was applied to understand the preferences of farm HH for agricultural tractors. Two designs of tractor buying and participating in the rental service were conducted. A fractional factorial design comprising 36 and 12 choice sets were used for the purchase and rent designs, respectively. Each respondent was presented with 12 choice sets from one of the designs and other additional socioeconomic and demographic questions. From the descriptive statistics, we found that 41.77% of the respondents preferred to adopt tractors through purchasing and 44.30% preferred to participate in tractor rental service, whereas 13.92% wanted to keep using oxen plow. The random parameter logit (RPL) estimation result revealed that, four-wheeled tractors having both plowing and transporting functions got the highest probability of selection followed by plowing only tractors. Regarding the rental service design, the rental price per ha was estimated to be Ethiopian Birr (ETB) 1,720 (1USD=22.8874ETB). The current rental price, ETB 2,000 was found far from the 95% confidence interval of the estimated price as 90% of high wheat producers were participated in the purchase design.

In the quasi-experimental method, covariates associated with the treatment assignment and the outcome variables were included. To estimate the propensity score (PS), weights for each sample were attached to balance the differences of sampling rates. The logit model was used to estimate the PS and the attached weights improved the significance level of the variables. Using the estimated PS, the nearest neighbor matching (NNM) with 0.1 caliper was found to provide better matches as the standardize mean differences are below 5% and the histograms of the two groups are similar. The average treatment effect estimation result showed that for all alternative matching algorisms, the p values found to be non-significant. Therefore, we do not have sufficient support for the alternative hypothesis that the mean income difference in the two groups is not zero. Thus, we cannot state that the difference between the mean income of SSIMP users and SSCIS users is different from zero. The value of the estimation results shows only the mean income difference between the two treatment groups, but not the actual scale between irrigation users and non-users. This means that the introduction of SSIMPs can have a positive impact by improving the income of farm HHs, similar to SSCISs.

Therefore, the introduction of agricultural tractors coupled with irrigation technologies, can contribute for promotion of climate resilient agriculture by improving farm HH income and minimizing soil degradation to maintain for the future need.