Climate‐Smart Innovations and Rural Poverty in Ethiopia: Exploring Impacts and Pathways

Abstract

Climate‐smart innovations have been receiving increasing attention in policy dialogues for their potential to transform agricultural systems and improve the well‐being and resilience of farm households. Using recent panel data from Ethiopia combined with novel historical weather data, we provide microeconomic evidence of the welfare effects of conservation agriculture (CA), a climate‐smart agricultural practice. We use a panel data endogenous switching regression model to deal with selection bias and farmer heterogeneity in CA choice. The study finds that the CA practices that play a pivotal role in addressing the exigencies of rural poverty are minimum tillage, cereal‐legume intercropping, and their combination. These practices reduce the incidence and depth of poverty in areas prone to rainfall stress, which is an indication of their risk mitigation role. In contrast, crop residue retention and its combination with minimum tillage appear not to be economically attractive CA options. The results show that CA portfolios that include minimum tillage and cereal‐legume associations can accelerate efforts to reduce rural poverty and improve climate risk management. We caution against exaggerated expectations of CA's economic benefits and a rigid recommendation of CA.

Sustainable Agricultural Practices, Farm Income and Food Security among Rural Households in Africa

“…Interestingly, the results also show that adopting all the practices (i.e., I 1 Z 1 R 1 A 1 ) signi cantly increased FI by 49% in East Africa, 82% in West Africa, 48% in Southern Africa and in 50% in the pooled sample, as well as SSF by 59% and 50% for East Africa and the pooled sample, respectively. This corroborates with previous studies which found that adoption of complete packages of SAPs improves households welfare in Africa (e.g., Abdallah et al, 2020;Sardar et al, 2020;Tesfaye et al, 2020). I 0 Z 0 R 1 A 1 0.07 (0.03) ** 0.99 (0.15) *** -0.07 (0.03) ** -0.32 (0.17) ** -0.07 (0.03) ** 0.12 (0.06) * -0.61 (0.13) *** -0.91 (0.45) ** I 1 Z 1 R 1 A 0 0.12 (0.05) *** -5.49 (0.87) *** 0.02 (0.03) -0.20 (0.12) * -0.02 (0.13) -0.38 (0.12) As stated earlier, the Multivalued Treatment Effect model (Cattaneo, 2010;Imbens& Wooldridge, 2009) was estimated to verify consistency of the results.…”

Sustainable agricultural practices, farm income and food security among rural households in Africa

“…Interestingly, the results also show that adopting all the practices (i.e., I 1 Z 1 R 1 A 1 ) signi cantly increased FI by 49% in East Africa, 82% in West Africa, 48% in Southern Africa and in 50% in the pooled sample, as well as SSF by 59% and 50% for East Africa and the pooled sample, respectively. This corroborates with previous studies which found that adoption of complete packages of SAPs improves households welfare in Africa (e.g., Abdallah et al, 2020;Sardar et al, 2020;Tesfaye et al, 2020). (Cattaneo, 2010;Imbens& Wooldridge, 2009) was estimated to verify consistency of the results.…”

Effects of the Adoption of Technology Combinations Beyond Standardized Systems on the Income of Chinese Tobacco Farmers

“…Michler, Tjernström, Verkaart, and Mausch (2019) argued that relative to yield targets, farmers focus more on economic return indicators when making decisions. Based on Khonje et al (2018) and Tesfaye et al (2020), this study used a random utility framework to analyse the adoption of multiple additional agricultural technologies, including IPM, BF, and SI, in a total of seven possible combinations:…”

“…In the process of agricultural production, farmers often face a series of technical choices that can be adopted individually or jointly (Feder, Just, & Zilberman, 1985;Mutale, Kalinda, & Kuntashula, 2017;Tesfaye, Blalock, & Tirivayi, 2020). Since Feder (1982) first developed a model to deal with interrelations in the adoption of multiple agricultural technologies (MATs), an increasing number of researchers have studied a variety of technology combination schemes (Cafer & Rikoon, 2018;Khanna, 2001;Kimbi et al, 2021;Wu & Babcock, 1998).…”