Farm-Level Analysis of Risk Management Proposals, March 2000

This paper presents a detailed report of the representative farm analysis (summarized in FAPRI Policy Working Paper #01-00). At the request of several members of the Committee on Agriculture, Nutrition, and Forestry of the U.S. Senate, we have continued to analyze the impacts of the Farmers’ Risk Management Act of 1999 (S. 1666) and the Risk Management for the 21st Century Act (S. 1580). Earlier analysis reported in FAPRI Policy Working Paper #04-99 concentrated on the aggregate net farm income and government outlay impacts. The representative farm analysis is conducted for several types of farms, including both irrigated and non-irrigated cotton farms in Tom Green County, Texas; dryland wheat farms in Morton County, North Dakota and Sumner County, Kansas; and a corn farm in Webster County, Iowa. We consider additional factors that may shed light on the differential impacts of the two plans. 1. Farm-level income impacts under alternative weather scenarios. 2. Additional indirect impacts, such as a change in ability to obtain financing. 3. Implications of within-year price shocks. Our results indicate that farmers who buy crop insurance will increase their coverage levels under S. 1580. Farmers with high yield risk find that the 65 percent coverage level maximizes expected returns, but some who feel that they obtain other benefits from higher coverage will find that the S. 1580 subsidy schedule significantly lowers the cost of obtaining the additional coverage. Farmers with lower yield risk find that the increased indemnities from additional coverage will more than offset the increase in producer premium. In addition, because S. 1580 extends its increased premium subsidy percentages to revenue insurance products, farmers will have an increased incentive to buy revenue insurance. Differences in the ancillary benefits from crop insurance under the baseline and S. 1580 would be driven by the increase in insurance participation and buy-up. Given the same levels of insurance participation and buy-up, the ancillary benefits under the two scenarios would be the same.

Health Information and the Choice of Fish Species: An Experiment Measuring the Impact of Risk and Benefit Information, April 2006

An experiment was conducted in France to evaluate the impact of health information on consumers’ choice between two different types of fish. Successive messages revealing risks (methylmercury) and benefits (omega-3s) of consuming the fish, along with consumption recommendations, were delivered. Results show a significant difference of reaction according to the order and type of information. The information about risks had a larger marginal impact on change in willingness to pay (WTP) than did the information about benefits. While the results show that detailed messages on risks/benefits, including recommendations for nutrition behavior, matter in the modification of WTP, 40% of respondents did not change their initial choices after the revelation of health information.

Native Grassland Conversion: the Roles of Risk Intervention and Switching Costs

We develop a real option model of the irreversible native grassland conversion decision. Upon plowing, native grassland can be followed by either a permanent cropping system or a system in which land is put under cropping (respectively, grazing) whenever crop prices are high (respectively, low). Switching costs are incurred upon alternating between cropping and grazing. The effects of risk intervention in the form of crop insurance subsidies are studied, as are the effects of cropping innovations that reduce switching costs. We calibrate the model by using cropping return data for South Central North Dakota from 1989 to 2012. Simulations show that a risk intervention that offsets 20% of a cropping return shortfall increases the sod-busting cost threshold, below which native sod will be busted, by 41% (or $43.7/acre). Omitting cropping return risk across time underestimates this sod-busting cost threshold by 23% (or $24.35/acre), and hence underestimates the native sod conversion caused by crop production.