Master of Science / Department of Agricultural Economics / Kevin C. Dhuyvetter / A Microsoft Excel based budget was developed to find the cost of becoming
National Animal Identification Systems (NAIS) compliant in the U.S for beef cow-calf
producers. This budget was turned into a stochastic budget by using different distributions
for five key variables. From these distributions 10,000 observations were simulated using
Latin Hypercube sampling.
From the comprehensive budget, a second, more simple budget was constructed for
obtaining NAIS cost. This Microsoft Excel based model gives beef cow-calf producers an
estimate and a prediction interval associated with the estimated cost of adopting a cattle ID
system that is compliant with the National Animal Identification Systems quickly and
conveniently, requiring only six inputs. Both the comprehensive and the quick budget are
available online. An Ordinary Least Squares regression was estimated using the simulated
observations to find marginal effects associated with key variables.
The driving factor of total cost per head was eID tag price for operations that tag
and eID tag price and chute costs for non-tagging operations. For producers with five or
less animals, it was cheaper to hire third parties to tag animals. From the sample data
generated, smaller operations pay significantly more than larger operations on a per head
basis, as the minimum cost was $2.08 for the larger operations and the maximum cost to
small operations was $17.56. The estimated overall average cost per head for the cow/calf
industry was $6.26, with a standard deviation of $4.12. Costs were on a per breeding
female basis. The Excel spreadsheet budget and model can be downloaded at
http://www.agmanager.info/ for producers who wish to estimate NAIS costs specific to
their operations.
| Identifer | oai:union.ndltd.org:KSU/oai:krex.k-state.edu:2097/1389 |
| Date | January 1900 |
| Creators | Crosby, Chris |
| Publisher | Kansas State University |
| Source Sets | K-State Research Exchange |
| Language | en_US |
| Detected Language | English |
| Type | Thesis |
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