Introduction. Analyzing the effect of COVID-19 is an important issue in agricultural sectors. However, such analysis requires a complex hierarchical statistical model. Rapid spread of the COVID-19 pandemic has disrupted the world’s production and productivity in many sectors. Among those sectors, the agricultural sector is highly affected. The Bale zone in the larger extent and Sinana district, in particular, is one of the potential agricultural areas in the Oromia regional state, Ethiopia where agriculture is the major sector in supporting the livelihood of thousands of subsistence farmers in the area as well as the country at large. Research Methodology. This study involved primary data collected from the farmers in the Sinana district during the period 2020–2021. A total of 991 farmers were selected from the entire 22 kebeles in the district. The data were analyzed using multilevel binary logistic random intercept regression models with maximum-likelihood parameter estimation. Results. Of the 991 farmers, 549 (55.4%) responded that COVID-19 has brought only challenges in their agricultural production and 311 (31.4%) responded both challenges and opportunities. About 632 (63.8%) of the farmers said that there was wastage of products such as milk, dairy, fruits, and vegetables. Three hundred twenty-eight (33.1%) of the participants obtained modernization in their agricultural production system like use of tractors and irrigation systems. According to the model results, farmer’s sex, age, educational level, family size, farmland size, types of effect, aggravation in food insecurity, input delay, lack of workers, slowdown of service, falling in income, modernization in the system of production, wastage of product, and types of wasted products were identified as significant factors. About 8% of the total variability in the effect of COVID-19 is due to differences across kebeles (ICC = 0.08, value ≤0.05), and the remaining is due to individual differences. Conclusion. This study further demonstrated the potential of a hierarchical model for the study of COVID-19 effect variation within and between the kebeles. The majority, about 92% variation in the effect, is due to the disparity of individuals (farmers). The farmers with large family sizes and high capacity to produce and who were females were negatively related to the effect of COVID-19 in agricultural production.
The rapid spread of COVID-19 pandemic has disrupted the world’s production and productivity in many sectors and, as a consequence, slowed down the world’s economic growth to a larger extent. The agricultural sector is among the highly affected especially in the Third-World countries. Even during prepandemic times, agricultural production was subjected to high risk, as compared to other sectors, because of its dependence on environmental conditions, which are largely unpredictable nowadays. The pandemic halted the rate of economic growth in many countries during 2019 and is expected to result in severe recession in the upcoming years, especially in the Third-World countries where agriculture is a key sector . bib3
Ethiopia is among the highly affected countries and faced a dramatic decrease in agricultural production and productivity, hence a minimum economic growth (GDP) as compared to the last ten years. The pandemic and related partial social restrictions have posed a negative impact on the smallholder farmers such as market loss and cause significant income losses in specific sectors such as livestock and horticulture .
The main purpose of this study was to estimate the challenges and opportunities of COVID-19 on agricultural production among farmers in Sinana district, Bale zone, Ethiopia. The study revealed a huge negative impact on the agricultural production and productivity of the farmers and the country at large. Of the 991 farmers, 549 said COVID-19 had only challenges in their agricultural production, and 311 had both challenges and opportunities. About 632 (63.8%) of the farmers said that there was wastage of products such as milk, dairy, fruits, and vegetables. Three hundred twenty-eight (33.1%) of the participants obtained modernization in their agricultural production system like use of tractors and irrigation systems. This study further demonstrated the potential of a multilevel random intercept model for the study of COVID-19 effect variation within and between the kebeles. The majority, about 92% variation of the effect, is due to the disparity of individuals (farmers). Farmers with a large family size and high capacity to produce, and whose sex is female were negatively related to the effect of COVID-19 in agricultural production. The odds of farmers who did not face both challenges and opportunities due to the pandemic was 1.308 (adjusted OR = 1.308, 95% CI = (−1.232, 1.769)) times more likely than those farmers who did face only challenges. This study also contributes to the literature by statistically examining challenges and opportunities for agricultural producers in Sinana district in reflection to COVID-19 and its countermeasures based on the variation within individuals and between kebeles that have been explained, which can provide more targeted implications for policymakers.