Economic valuation of phenotypic cattle trait preferences in trypanosomosis prevalent production systems of Eastern Africa: Implications for sustainable cattle breeding programs.
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Ouma, E. A. 2007. Economic valuation of phenotypic cattle trait preferences in trypanosomosis prevalent production systems of Eastern Africa: Implications for sustainable cattle breeding programs. PhD thesis, University of Kiel.
Permanent link to cite or share this item: http://hdl.handle.net/10568/79627
External link to download this item: http://macau.uni-kiel.de/receive/dissertation_diss_00002057?lang=en
The livestock sector plays crucial multifunctional roles in the rural livelihoods and economies of many sub-Saharan African countries; yet productivity remains relatively low in the region. Breed improvement programs that utilize advanced animal breeding technologies provide key entry points for improving livestock productivity. However, there are tendencies for genetic breed improvement programs to focus on single traits associated with production outputs such as meat or milk production with an assumption of a profit maximizing objective function when calculating economic values of traits and important non-income and socio-cultural roles of livestock from the breeding objective since such functions are often embedded in traits that lack market values or prices. This may result in breeds that are not well adapted to the environment and not capable of performing the multiple objectives of the livestock enterprise environment and not capable of performing the multiple objectives of the livestock enterprise in developing countries. In order to design sustainable breed improvement programs aimed at improving productivity, livestock keepers' preferred traits need to be integrated into the breeding objectives. The study examines cattle keeping households' preferences for phenotypic cattle traits in trypanosomosis prevalent production systems if Kenya and Ethiopia, using cross-sectional choice experiment survey data of 5006 cattle keeping households collected between September 2004 and May 2005. Further, it investigates potentially sustainable pathways by which the cattle keeping households can access improved genetic materials based on their cattle traits of preference. Mixed logit and latent class models are employed to model preference behavior for cattle traits from the choice experiment data with a focus on heterogeneity among cattle keeping households. Specifically, mixed logit model is employed to investigate existence of preference heterogeneity, while a latent class model is used to investigate the existence of endogenous preference segmentation for cattle traits among the cattle keeping households. The results reveal significant preference heterogeneity among cattle keeping households. Good traction potential, fertility, trypanotolerance and reproduction performance are found to be the most preferred cattle traits. Traits related to beef and milk yield are ranked below these traits. The findings are particularly interesting because traditional economic analyses on livestock and cattle breeding programs often focus on raising milk and meat productivity, with little emphasis on the non-income traits such as traction potential and disease resistance programs besides beef and milk yield. The results of the latent class model indicate that the households' preferences are clustered around the production systems under which cattle production takes place. Three distinct classes of cattle keeping households in the sample population emerge, each displaying differing preferences for the same set of cattle traits. This indicates the importance of considering heterogeneity within population segments as it provides a useful framework for adapting breeding policy interventions to specific producer segments. Additional results indicate that communal breeding initiatives provide important pathways through which resources-poor cattle keepers can access genetically improved livestock. Factors that influence a households' willingness to participate in such a collective action decision are analyzed using a binary logit model. The results indicate that the probability of participating in a collective action decision is influenced by several socio-economics and location characteristics. High human population density indicates the probability of taking up collective action decision. Similarly, the presence of adult females in the household as well as higher level of formal education and age of the head of the household increases the likelihood of