Title page for ETD etd-07242010-112837

Type of Document Master's Thesis
Author Khanal, Aditya Raj
Author's Email Address akkhanal@gmail.com
URN etd-07242010-112837
Title Adoption of Breeding Technologies in the U.S. Dairy Industry and Their Influences on Farm Profitability
Degree Master of Science (M.S.)
Department Agricultural Economics & Agribusiness
Advisory Committee
Advisor Name Title
Gillespie, Jeffrey M. Committee Chair
Mishra, Ashok Committee Member
Salassi, Michael Committee Member
  • breeding technologies
  • adoption
  • bivariate probit
  • dairy
  • self-selection
  • endogeneity
Date of Defense 2010-06-28
Availability unrestricted
Current trends in the U. S. dairy industry show an increase in milk cows per farm and milk production per cow, though the total number of milk cows in the industry is declining. This increase in productivity is attributed to advancements and adoption of modern dairy technologies. Breeding technologies are one of the important components of this structural change. This study analyzed the factors affecting the adoption of modern breeding technologies such as artificial insemination, embryo transplants, and sexed semen, and the impact of these technologies on farm productivity and profitability.

Results of a bivariate probit model with selection showed that the adoption decision is affected by different farm and farmer attributes such as age, education, off-farm work, farm size, and specialization. The embryo transplants and/or sexed semen technology adoption decision was also influenced by the farmerís planning horizon. Farm impact was assessed by estimating net returns and cost measures using ordinary least squares methods. Endogeneity and self-selection bias issues were also tested and corrected for in the impact models. Both artificial insemination (AI) and embryo transplants and/or sexed semen (ETSS) technologies are found to have significant and positive influences on net returns over total and net returns over operating costs per hundredweight of milk produced. Results also suggest that a higher allocated cost is associated with ETSS adoption. Relatively younger, more highly educated farmers and larger and more specialized farms received higher net returns. Since some part of the costs involved in ETSS may be for conducting artificial insemination, larger farms that had already adopted AI may consider ETSS adoption. Adoption decisions on a farm, however, would be based on the added advantages of ETSS adoption versus the additional costs of adopting these.

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