Breeding Technology and the Valuation of Animal
Genetic Resources in the Senegalese Dairy Sector

with Karen Marshall and Aya Missohou, in Submission

We analyze the factors affecting willingness-to-pay (WTP) for artificial insemination (AI) breeding technology by smallholder dairy farmers in Senegal. AI is a critical tool for expanding access to new animal genetic resources and increasing livestock productivity in developing countries, but it faces significant barriers to adoption in Senegal despite government campaigns that provide new breeds with AI free of charge. Since AI is often the only delivery method for new dairy cow breeds, previous work has not been able to distinguish what factors affect adoption of AI independent of the new breeds it delivers. Our analysis disentangles these two factors by using a double-bound contingent valuation experiment to elicit WTP for both AI and NM of a chosen dairy breed. We find that while WTP did not differ between the two methods for any breed on average, those with higher education and experience using a private sector provider valued AI more. Specifically, those using a private provider value AI up to 25% more than those using a public campaign. Respondents indicate the disadvantages of AI as a low success rate and poor breed choice, two shortcomings of the public campaigns, which suggests that poor service in public campaigns affected opinions about the efficacy of AI. Since the same technicians were used for private and public AI service, the quality in service can be attributed to the differing incentives in the case of public campaigns, which aimed to breed as many cows as possible. Our analysis elucidates the unique challenges of improving livestock productivity via adoption of AI when mass provision by the government can affect service quality and undermine future adoption.