The purpose of this article is to document and evaluate patterns of nontraditional credit use among Wisconsin dairy farmers. Using a survey-based case study approach, this article analyzes farmer and farm characteristics, farmers’ utilization of credit and farmers’ perceptions of nontraditional lenders. The findings are connected to ongoing structural change in the dairy sector and economic theories of trade credit.
Data were collected using an incentivized online survey of Wisconsin dairy farmers distributed through existing university and industry networks. A total of 16 farmers completed the survey. The sample is treated as a focus group case study, and participants’ responses are examined using summary statistics and correlational analyses to describe emergent patterns in the industry.
Among survey respondents who utilize agricultural credit, nearly 80% (11 of 14) borrow from at least one nontraditional lender, and nontraditional credit comprises 17% of their total borrowing, on average. Much of this borrowing occurs through the financial arm of a vendor and is used to finance equipment or machinery purchases. Despite widespread use of nontraditional credit, no surveyed farmers preferred nontraditional lenders over traditional lenders.
This is the first study to analyze the use of nontraditional credit specifically among Wisconsin dairy farmers. Dairy farming is a capital-intensive endeavor, and recent structural change in the sector has increased surviving dairy farmers' demand for credit.
The author wishes to thank Kevin Bernhardt, Stephanie Plaster, Jenny Vanderlin, Trisha Wagner and Katie Wantoch for their help in framing this research and developing the survey tool. The author appreciates Paul Mitchell, the University of Wisconsin–Madison Center for Integrated Agricultural Systems and the Wisconsin Dairy Business Association for their help disseminating the survey and is grateful to the Wisconsin dairy farmers who participated in this research. The author also wishes to thank the Guest Editor Dr. Jennifer Ifft and two anonymous referees for their helpful comments during the review process. Finally, the author thanks Qinan Lu for providing excellent research assistance.
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