Farm level technology assessment in Sub-Saharan Africa: a case study in Mali

Due to the character of the original source materials and the nature of batch digitization, quality control issues may be present in this document. Please report any quality issues you encounter to digital@library.tamu.edu, referencing the URI of the item.Includes bibliographical references (leaves 51-52).Issued also on microfiche from Lange Micrographics.The agricultural sector in Sub-Saharan Africa has been the beneficiary of significant expenditures for technology improvements. However, the implementation of the technologies that have been developed for the Sub-Sahara has met with limited success. As funding agencies reevaluate their role in the economic progress of the Sub-Sahara, the economic benefits of these new technologies need to be evaluated to determine their effectiveness. One of the key issues in the effort to evaluate new technology is the effect that risk has on the potential outcomes of proposed technology. The objective of this research was to evaluate the farm level impacts of implementing new technologies in Sub-Saharan Africa explicitly incorporating risk into the future outcomes of alternative technology assumptions. To achieve this objective the adoption of two improved varieties of sorghum (N'Tenimissa and Seguetana) in the Sub-Saharan nation of Mali was analyzed using a whole farm simulation model, the Technology Impact Evaluation System (TIES). The TIES model was used to estimate the empirical probability distributions of variables associated with economic well being under each technology assumption. Stochastic dominance with respect to a function was used to rank the technology alternatives for risk averse decision makers. Three case farms were analyzed to determine the effects that implementing new technologies has on small holder farms in different archeological regions in Mali. The results indicate that the most preferred technology on all of the case farms in the study is Seguetana sorghum. The results further show that early adoption of this technology yields the most economically beneficial situation on all farms. The evaluation of these results through stochastic dominance shows that the preference for Seguetana technology holds under the risky conditions facing each of the case farms in Mali