Farmers’ Willingness to Grow Switchgrass as a Cellulosic Bioenergy Crop: A Stated Choice Approach
Creators: name: Fewell, Jason E.
name: Bergtold, Jason S.
name: Williams, Jeffery R.
name: Fewell, Jason E.
name: Bergtold, Jason S.
name: Williams, Jeffery R.
Publisher: name: Unknown
Year: 2011
Subjects: subject: Crop Production/Industries
subject: Production Economics
subject: Resource /Energy Economics and Policy
subject: Biofuels
subject: Cellulosic
subject: Biomass
subject: Switchgrass
subject: Farmers
subject: Willingness to Pay

description: Farmers’ Willingness to Grow Switchgrass as a Cellulosic Bioenergy Crop: A Stated Choice Approach Agriculture’s role as a source of feedstocks in a potential lignocellulosic-based biofuel industry is a critical economic issue. Several studies have assessed the technical feasibility of producing bioenergy crops on agricultural lands. However, few of these studies have assessed farmers’ willingness to produce or supply bioenergy crops or crop residues. Biomass markets for bioenergy crops do not exist, and developing these markets may take several years. Therefore, an important, yet unaddressed question is under what contractual or pricing arrangements farmers will grow biomass for bioenergy in these nascent markets. The purpose of this paper is to examine farmers’ willingness to produce switchgrass under alternative contractual, pricing, and harvesting arrangements. Contracts are likely to be the preferred method to bring together producers and processors of biomass for bioenergy. Contract design may vary across farmers and crop type, and may include attributes specific to annual crops, contract length, quantity or acreage requirements, quality specifications, payment dates, and other important features. A stated choice survey was administered in three, six-county areas of Kansas by Kansas State University and the USDA, National Agricultural Statistics Service from November 2010 to January 2011 to assess farmers’ willingness to produce cellulosic biomass under different contractual arrangements. This paper focuses on the switchgrass stated choice experiment from the survey. The stated choice experiment asked farmers to rank their preferred contractual arrangement from two contract options and one “do not adopt” option. Contractual attributes included percentage net returns above the next best alternative (e.g. CRP or hay production), contract length, a custom harvest option, insurance availability, and a seed-cost share option. Respondents then ranked their preferred contract option. The survey also collected data on farm characteristics, bioenergy crop preferences, socio-economic demographics, risk preferences, and marketing behavior. The survey used a stratified sample of farmers who farm more than 260 acres and grow corn. A total of 460 surveys were administered with a 65 percent completion rate. The underlying theoretical model uses the random utility model (RUM) approach to assess farmers’ willingness to grow switchgrass for bioenergy and determine the contractual attributes most likely to increase the likelihood of adoption. This framework allows us to define the “price,” or farmers’ mean willingness to accept, for harvested biomass sold to an intermediate processor. The estimated choice models follow the approach of Boxall and Adamowicz (2002) to capture heterogeneity across farmers and geographic regions due to management differences, conservation practices, and risk preferences. Using the percentage net return above CRP or hay production allows prices to float to levels that will entice farmers to adopt switchgrass. This will help determine a market price for bioenergy crops based on current market and production conditions without specifying an exact monetary value for the biomass. In addition, the survey results will facilitate contract designs between biorefineries and farmers while informing policymakers and the biofuel industry about farmers’ willingness to supply biomass for bioenergy production. Reference: Boxall, P.C. and W.L. Adamowicz, “Understanding Heterogeneous Preferences in Random Utility Models: A Latent Class Approach,” Environmental and Resource Economics 23(2002): 421 – 446.