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ARS Home » Midwest Area » West Lafayette, Indiana » Livestock Behavior Research » Research » Publications at this Location » Publication #245075
Title: Stochastic Simulation Using @ Risk for Dairy Business Investment Decisions

Author
item BEWLEY, J. - University Of Kentucky
item BOEHLJE, M. - Purdue University
item GRAY, A. - Purdue University
item HOGEVEEN, H. - Utrecht University
item KENYON, S. - Purdue University
item Eicher, Susan
item SCHUTZ, M. - Purdue University

Submitted to: Agricultural Finance Reviews
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 12/30/2009
Publication Date: 1/15/2010
Citation: Bewley, J.M., Boehlje, M.D., Gray, A.W., Hogeveen, H., Kenyon, S.J., Eicher, S.D., Schutz, M.M. 2010. Stochastic Simulation using @Risk for Dairy Business Investment Decisions. Agricultural Finance Review. 70(1):97-125.

Interpretive Summary: A dynamic, stochastic, mechanistic simulation model of a dairy business was developed to evaluate the cost and benefit streams coinciding with technology investments. The model was constructed to embody the biological and economical complexities of a dairy farm system within a partial budgeting framework. A primary objective was to establish a flexible, user-friendly, farm-specific, decision-making tool for dairy producers or their advisers and technology manufacturers. The model was composed of a series of modules, which synergistically provide the necessary inputs for profitability analysis. Estimates of biological relationships within the model were obtained from the literature in an attempt to represent an average or typical U.S. dairy. Technology benefits were appraised from the resulting impact on disease incidence, disease impact, and reproductive performance. Examples of the utility of examining the influence of stochastic input and output prices on the costs of culling, days open, and disease were examined. Each of these parameters was highly sensitive to stochastic prices and deterministic inputs. Decision support tools, such as this one, that are designed to investigate dairy business decisions may benefit dairy producers.

Technical Abstract: A dynamic, stochastic, mechanistic simulation model of a dairy business was developed to evaluate the cost and benefit streams coinciding with technology investments. The model was constructed to embody the biological and economical complexities of a dairy farm system within a partial budgeting framework. A primary objective was to establish a flexible, user-friendly, farm-specific, decision-making tool for dairy producers or their advisers and technology manufacturers. The basic deterministic model was created in Microsoft Excel (Microsoft, Seattle, WA). The @Risk add-in (Palisade Corporation, Ithaca, NY) for Excel was employed to account for the stochastic nature of key variables within a Monte Carlo simulation. Net present value was the primary metric used to assess the economic profitability of investments. The model was composed of a series of modules, which synergistically provide the necessary inputs for profitability analysis. Estimates of biological relationships within the model were obtained from the literature in an attempt to represent an average or typical U.S. dairy. Technology benefits were appraised from the resulting impact on disease incidence, disease impact, and reproductive performance. In this paper, the model structure and methodology were described in detail. Examples of the utility of examining the influence of stochastic input and output prices on the costs of culling, days open, and disease were examined. Each of these parameters was highly sensitive to stochastic prices and deterministic inputs. Decision support tools, such as this one, that are designed to investigate dairy business decisions may benefit dairy producers.