The Impact of Agricultural Technologies on Poverty and Vulnerability of Smallholders in Ethiopia: A Panel Data Analysis

Abstract

Many studies evaluating the impact of adoption on welfare focused on adoption of a single technology giving little attention on the complementarity/substitutability among agricultural technologies. Yet, smallholders commonly adopt several complementary technologies at a time and their adoption decision is best characterized by multivariate models. This paper, therefore, examines the impact of multiple complementary technologies adoption on consumption, poverty and vulnerability of smallholders in Ethiopia. The study used a balanced panel data obtained from a survey of 390 farm households collected in 2012, 2014 and 2016. A two stage multinomial endogenous switching regression model combined with the Mundlak approach and balanced panel data is employed to account for unobserved heterogeneity for the adoption decision and differences in household and farm characteristics. An ordered probit model is used to analyze the impact on poverty and vulnerability. We find that the adoption of improved technologies increases consumption expenditure significantly and the greatest impact is attained when farmers combine multiple complementary technologies. Similarly, the likelihood of households to remain poor or vulnerable decreased with the adoption of different complementary technologies. We therefore conclude that the adoption of multiple complementary technologies has substantial dynamic benefits that improve the welfare of smallholders in the study area, and given the observed low level of adoption rates, we suggest that much more intervention is warranted, with a special focus on poorer and vulnerable households, to ensure smallholders get support to improve their input use.

Adoption of improved agricultural technology and its impact on household income: a propensity score matching estimation in eastern Ethiopia

“…It is considered as a center-stage of economic development and a platform to win the battle to food security and poverty reduction in the country [2]. The agricultural sector contributes 43% of Gross Domestic Product (GDP), 90% of export earnings, and 96% of rural employment [3]. It also provides raw materials for industries in the country.…”

“…Finally, adoption of multiple and/or complementary agricultural technologies-improved seeds, chemical fertilizers, pesticides and soil and water conservation practices-in the country is shown to enhance consumption expenditure and improve poverty status [3]. However, there is limited empirical study in eastern Ethiopia regarding the causal effect of multiple agricultural technology adoption on household welfare.…”

Determinants of Farmers’ Level of Interaction with Agricultural Extension Agencies in Northwest Ethiopia

“…Although ordered probit and logit models yield similar inferences, they assume standard normal and logistic distributions of the error terms, respectively. An ordered probit model was used in this research as it is a commonly used tool in other related research such as [37][38][39][40][41][42].…”

Integrated Multi-criteria Land Suitability Evaluation and Mapping for Scaling Malt Barley Varieties in Rain-Fed Production Areas of Ethiopia

“…Moderately suitable land areas may need additional interventions on top of the recommended production packages of malt barley production. According to the recent report on the results of nationwide soil and water conservation measures which have been going on for decades in the rugged highlands resulted in significant improvements in the agronomic and economic efficiency of productivity enhancing technologies (Biru, Zeller, & Loos, 2020).…”