Abstract:
In Ethiopia, the agricultural sector contributes the largest employment opportunities (70%) and is the major source of export earnings (90% of export value). Despite efforts made to modernize, mechanize, commercialize, and transform the Ethiopian agricultural sector from subsistence to production of diversified and high value crops, the sector’s performance has been lower. In light of the problems and the research gaps identified, this study seeks to address and generate information on the level of farm mechanization, factors affecting the level of farm mechanization, commercialization, and crop diversification, and impacts of farm mechanization on input utilization, economic efficiency (EE), and household income in the central and southern parts of Oromia region, Ethiopia. A total of 390 sample farm households were randomly drawn from 8 Kebeles in four districts, through a multi-stage sampling technique. Descriptive statistics and econometric models including Tobit, Stochastic Frontier Analysis (SFA), Augmented Inverse Probability Weight (AIPW) model, Heckman’s two-stage, Ordered Logit, and Seemingly Unrelated Regressions (SUR) models were employed to analyze the data. Results of this study show that the mean farm mechanization index was 35.14%. The Tobit model result pointed out that farm experience, education, off/non-farm activities, cultivated landholding, market participation and access to road were positively and significantly affect the level of farm mechanization. However, sex, zonal location, livestock possession, land fragmentation, distance to mechanization centers, and social capital were negatively and significantly affecting the level of farm mechanization. The stochastic frontier analysis results also indicated that the mean technical and economic efficiency of wheat farmers were 94 and 72% respectively whereas the barley producers’ mean technical and economic efficiency were 73 and 91% respectively. The relatively higher technical efficiency (TE) and EE scores could be due to enterprise specialization and government attention to such crops in the area. The result of the AIPW model revealed that higher level of farm mechanization has positive effect on the economic efficiency of wheat and barley producers, amount of chemical fertilizer applied, household income, and wheat farm productivity. On the other hand, farm mechanization has a significant negative effect on the xix xix amount of farm labor employed and agrochemical applied. The Heckman’s two-stages selection model result showed that the decision to participate in crop marketing was significantly and negatively affected by age, market distance, and instrumental variable for the level of farm mechanization. Contrary to this, it was affected significantly and positively by livestock size, agroecological zone, ownership of equines, annual income, and access to market information. Second tier result of the model also showed that intensity of commercialization was positively and significantly affected by annual income, access to market information, and number of oxen; while it was negatively and significantly affected by cultivated land, crop diversification level, and market distance. The ordered Logit model result indicated that the crop diversification was positively and significantly affected by variables like family size, farmland, level of farm mechanization, and land fragmentation but negatively affected by agro-ecological location. The SUR model results revealed that there is a positive and significant causation between farm mechanization and crop output commercialization with coefficient of 12.45% while there was also positive and significant causation between farm mechanization level and crop diversification index (SDI). However, crop commercialization and diversification had negative causation with a coefficient of 11%. Hence, commercialization and crop diversification were negatively affecting each other. In general land consolidation, availing infrastructural facilities and facilitating adult education and short-term trainings are important to enhance the level of farm mechanization level in the study area. Improving the resource endowment, and minimizing transaction costs by improving access to market centers, market information, and means of transportation can further enhance commercialization. Improving access to farm mechanization and enhancing productivity in highland areas are also issues that shall get policy and development practitioners’ focus. Furthermore, increasing the level of farm mechanization by availing the technologies can maximize the households’ welfare through reducing inputs cost and increasing efficiency and household income. Finally, from the result of the inter-linkage among farm mechanization, crop commercialization and diversification it can be recommended that improved level of farm mechanization can promote level of crop commercialization and crop diversification.