The ex‐post impact of agricultural technology adoption on poverty: Evidence from north Shewa zone of Amhara region, Ethiopia

Abstract

This study investigates the impact of agricultural technology adoption on poverty reduction in north Shewa zone of Amhara region of Ethiopia in 2020. Using the selection model, this study finds that farm household's decision to adopt agricultural technologies are mainly influenced by sex of the household head, credit access, saving, extension visit, farm cooperatives and distance from market. Using an endogenous switching regression model, this study finds that adopters of agricultural technologies have higher food consumption expenditure per adult. Moreover, the significant difference in food consumption expenditure per adult equivalent between the actual and counterfactual scenario is very high. The result of the study confirmed that adoption of agricultural technology has a direct and significant impact on increasing household's consumption expenditure while also reducing household poverty. The findings of the study suggest that increasing the access and adoptions of agricultural technologies significantly improves the welfare of farm households.

Determinants of Farmers’ Awareness and Adoption of Extension Recommended Wheat Varieties in the Rainfed Areas of Pakistan

“…Our results on poverty and the adoption of new technology are supported by the previous literature. For instance, poverty creates barriers to the adoption of agricultural technology [58,59]. Studies have reported that poverty negatively affects agricultural technology adoption; however, promoting awareness through extension and policy interventions can create improved technology, such as novel crop varieties that are available to farmers, and can facilitate their adoption, which, in turn, can reduce poverty.…”

Determinants of Rural Household Food Security Status in North Shewa Zone, Amhara Region, Ethiopia

“…In addition, even if agriculture is the mainstay of the economy, its contribution is declining over time, and its productivity is very low as well due to its heavy reliance on rain-fed farming, traditional farming, adverse climatic conditions, and minimal applications of farm technologies. The lower food production and productivity limits the national food availability and consumption requirements, which result in food insecurity problem in the country [ 4 ]. As a result, the daily calorie consumption in Ethiopia is below the recommended daily allowance of 2100 kcal/person/day [ 3 ].…”

Measuring the poverty reduction effects of adopting agricultural technologies in rural Ethiopia: findings from an endogenous switching regression approach

“…Past empirical studies have demonstrated that agricultural growth through improved and new agricultural technologies adoption is the most effective way to increase agricultural productivity, sustain food security and decrease poverty. The technology adoption in the sector of agriculture has greatly contributed to increased yields and improved household food security, thereby reducing household poverty ( De Janvry et al., 2000 , 2017 ; Kassie et al., 2018 ; Habtewold, 2021 ; Belay and Mengiste, 2021 ). Hence, various studies conducted around the world and in Ethiopia have suggested that agricultural technologies have the capability of reducing poverty in large scale.…”

“…Hence, various studies conducted around the world and in Ethiopia have suggested that agricultural technologies have the capability of reducing poverty in large scale. For example, the adoption of alternative farming technologies has been found to significantly increase yields, increase farm income, increase household consumption, improve nutrition, and generally improves household welfare ( Sebsibie et al., 2015 ; Hagos, 2016 ; Tesfaye et al., 2016 ; Alwang et al., 2017; Belete and Melak, 2018 ; Akinrinola and Adeyemo, 2018 ; Adebayo et al., 2018 ; Ahmed and Anang., 2019 ; Verkaart et al., 2019 ; Natnael, 2019 ; Legesse et al., 2019 ; Tesfay, 2020 ; Biru et al., 2020 ; Teka and Lee, 2020 ; Abewa et al., 2020 ; Ayenew et al., 2020 ; Shita et al., 2020 ; Belay and Mengiste, 2021 ; Habtewold, 2021 ; Wordofa et al., 2021 ).…”

“…But these approaches do not create enough counterfactuals and thus are not capable of providing adoption's actual impact. Also, here estimating the effect of technology adoption is difficult mostly due to selection bias owing to observables and unobservables factor ( Belay and Mengiste, 2021 ). Hence, we implement a novel method to address these impact assessment pitfalls.…”