Mutyasira, Vine, authorHoag, Dana L. K., advisorPendell, Dustin, advisorManning, Dale, committee memberGalvin, Kathleen, committee member2017-09-142017-09-142017https://hdl.handle.net/10217/183901This dissertation examines the prospects of sustainable agricultural intensification by rural farming households in Ethiopia. Although widely accepted as the new paradigm for agricultural development in sub-Saharan Africa, several research and empirical questions still surround the concept of sustainable intensification, particularly its operationalization. Efforts to promote, measure and monitor progress towards sustainable intensification are hampered by the lack of quantifiable indicators at the farm level, as well as the uncertainty over the relationship between intensification and sustainability. This dissertation contributes to this knowledge gap by examining the relationship between agricultural intensification and sustainability, with a view to determine if sustainable paths of agricultural intensification are possible within the smallholder farming systems of Ethiopian highlands. To help better execute the research inquiry, and achieve the main goal of this study, the themes of this dissertation are addressed through three separate but interrelated essays, on top of the introductory and conclusion chapters. The first essay, presented in chapter two, examines the drivers and processes shaping agricultural intensification by smallholder farmers. This chapter contributes to the literature by providing evidence of how agricultural intensification depends on a wide range of factors, whose complex interactions give rise to different intensification pathways. The implication is that, even in a region that is undergoing the process of agricultural intensification, households are likely to respond differently to intensification incentives and production constraints, and thus pursue different paths of agricultural intensification. The second essay, chapter three, develops a methodological framework for defining elements of sustainability based on observed, context-specific priorities and technologies. Farm-level indicators of agricultural sustainability are developed using insights drawn from literature, and adapted to the Ethiopian context through consultations with agricultural experts and key stakeholders in the agricultural sector. A Data Envelopment Analysis (DEA) framework is applied to synthesize the selected indicators into a relative farm sustainability index, thus reducing subjectivity in the sustainability index. A generalized linear regression model applied on the computed sustainability scores shows that farm size, market access, access to off farm income, agricultural loans, access to agricultural extension and demonstration plots are key drivers of agricultural sustainability at the farm level. Despite being applied to the Ethiopian context; the methodology has broader policy implications and can be applied in many contexts. The third essay, chapter four, examines the relationship between agricultural intensification and relative farm sustainability, and identifies four clusters of farmers depending on their relative levels of intensification and sustainability. The main thrust of this essay is to examine whether farmers who are highly productive are also sustainable, and whether systems that are relatively more sustainable are mostly on the highly productive farms. The results show that of the farms that are relatively most intensive, in terms of the gross value of crop output per hectare, only 27 percent are relatively more sustainable. Of the farms that are relatively most sustainable, about 60 percent are more intensive. Overall, only 10 percent of the farms were both highly intensive and relatively more sustainable. In order to understand the typology of farmers that are likely to embark on sustainable paths of agricultural intensification, multivariate methods of Principal Components Analysis (PCA) and Cluster Analysis (CA) were used to cluster farmers according to their common characteristics. Multinomial Logit (MNL) regression models were used to model the probability of cluster membership as well as the likelihood of farmers embarking on different intensification trajectories. is used to analyze the odds of embarking on a sustainable intensification path. The results suggest that increasing farmers' access to technical information through demonstration plots and government extension services, addressing farm liquidity constraints, improving market access, as well fostering crop-livestock interactions, significantly increases the likelihood of sustainable intensification.born digitaldoctoral dissertationsengCopyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright.Ethiopiaintensification pathwayssustainable intensificationfractional response modeldata envelopment analysissmallholder farmers AfricaText