Estimating the Effectiveness of Extension Information Systems Using Farm Trical and Subjective Probabilities

Wayne H. Howard, University of Guelph
Robert W. Blake, Cornell University
Thomas O. Knight, Department of Agricultural Economics USA
Richard C. Shumway, Department of Agricultural Economics USA
Michael A. Tomaszewski, Texas A & M University - College Station

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Copyright © 1992 Elsevier. The definitive version is available at http://dx.doi.org/10.1016/0169-5150(92)90023-R.

NOTE: At the time of publication, the author Wayne H. Howard was not yet affiliated with Cal Poly.

Abstract

A method of combining survey data and Dairy Herd Improvement Association (DHIA) records to achieve low cost farm trials is presented. Farm trials and surveys of current practices and production responses are useful to identify yield gaps between expectations predicted from experimental findings and actual field results. Different management schemes can be ranked using subjective probabilities and stochastic dominance to enhance successful implementation of research findings and to increase the feedback between researchers, extension workers, and producers. A survey of current masitis control practices and expected milk yield response is the example. Combining survey results with DHIA records allowed estimating the relationship between somatic cell counts (SCC) and milk yield. Eliciting beliefs about the relationship between SCC and milk yield showed that producers agreed with predictions from the statistical model. Subjective probabilities about SCC and mastitis control practices showed that our sample of experts and producers consistently ranked the different practices but extension agents had no consensus about the most or least effective ones.