Economics(PhD)

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Browsing Economics(PhD) by Author "Dr. Wassie, Berhanu"

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    Impacts of Improved Agricultural Technologies Adoption on Multidimensional Welfare Indicators in Rural Ethiopia
    (A.A.U, 2020-06) Tsegaye, Mulugeta; Profess Edilegnaw, Wale; Dr. Wassie, Berhanu; Professor Almas, Heshmati; Dr. Zerayehu, Sime
    This thesis consists of an introduction, one Co-authored paper and three independent single-author papers. This thesis discusses the importance of improved agricultural technologies and improved practices on multidimensional welfare in Rural Ethiopia. The introduction gives a brief summary of the four papers which form the thesis. In the first stage, a meta-analysis was done to identify the gaps in literature and learn more about the linkages between improved agricultural technologies and welfare. The papers are held together by concepts and theories associated with farm households’ adoption of modern agricultural technologies, linkages between the indicators of multidimensional welfare and technology through an impact analysis in a program evaluation setting and unobservable behavior of the factors in the adoption-welfare context. Chapter 2 (Paper 1) does a meta-analysis of improved agricultural technologies and their impact on welfare in Africa. The meta-analysis considers the results of a study of a sample of 52 empirical estimates that investigated the impact of improved agricultural technologies in Africa with a focus on three key outcomes: output or expenditure, food security, and poverty. The results show that differences in the reported impact of technologies can be attributed to several factors such as data type, model specification, theories, sample size, study area, and journal type. The study also used a test for publication bias and observed no publication bias in general. The next two chapters (Papers 2 and 3) focus on linking multidimensional poverty, food security and child nutrition with improved agricultural technologies. Paper 2 examines the impact of adopting improved agricultural technologies on multidimensional poverty through two powerful impact evaluation techniques--propensity score matching and endogenous switching regression methods--for measuring the causal inference and the Alkire and Foster counting approach for measuring the multidimensional poverty index. The results of the empirical analysis show that adoption of technology reduced overall and living standards’ deprivation scores while there were regional variations in the impact of the technology; a high reduction in deprivation was observed in Amhara region followed by the Oromiya region. Across deprivation groups the impact was higher in the severely deprived households. Paper 3 discusses the impact of improved agricultural technologies on food security and child nutrition using a panel data through a two-ways fixed effect combined with the propensity score matching and endogenous treatment effect techniques. This paper links adoption-nutrition which has been partly neglected by most existing studies. It uses four different outcomes: consumption expenditure, child nutrition, food shortages, and household worries about food availability. The results of the first two outcome variables show that adoption had a significant positive impact while the impact of the remaining two outcomes shows that improved agricultural technologies did not affect welfare. 2 The last paper links improved agricultural technologies to women’s empowerment in the context of impact evaluation relying on a panel data analysis and employing differences-in-differences and propensity score matching techniques in a program evaluation setting. This is a new setting in the agriculture sector. It applies the Abbreviated Women’s Empowerment in Agriculture Index and its two components--five domains of the Empowerment and Gender Parity Index for measuring empowerment. The findings show that technology improved women’s empowerment through five domains of empowerment, but not through the gender parity index, which implies that empowerment is derived more from its five domains.