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.

Executive Order Number Twenty Nine, December 1977

States' option on federal flood insurance.

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.

Network externalities across financial institutions

We propose and estimate a financial distress model that explicitly accounts for the interactions or spill-over effects between financial institutions, through the use of a spatial continuity matrix that is build from financial network data of inter bank transactions. Such setup of the financial distress model allows for the empirical validation of the importance of network externalities in determining financial distress, in addition to institution specific and macroeconomic covariates. The relevance of such specification is that it incorporates simultaneously micro-prudential factors (Basel 2) as well as macro-prudential and systemic factors (Basel 3) as determinants of financial distress. Results indicate network externalities are an important determinant of financial health of a financial institutions. The parameter that measures the effect of network externalities is both economically and statistical significant and its inclusion as a risk factor reduces the importance of the firm specific variables such as the size or degree of leverage of the financial institution. In addition we analyze the policy implications of the network factor model for capital requirements and deposit insurance pricing.

Analysis of Hail and Temperature Series for Peninsular Spain

Hail is a serious concern for agriculture on the Iberian Peninsula. Hailstorms affect crop yield and/or quality to a degree that depends on the crop species and the phenological time. In Europe, Spain is one of the countries that experience relatively high agricultural losses related to hailstorms. It is of high interest to study models that can support calculations of the probabilities of economic losses due to hail damage and of the tendency over time for such losses. Some studies developed in France and the Netherdlands show that the summer mean temperature was highly correlated with a yearly hail severity index developed from hailrelated parameters obtained for insurance purposes. Meanwhile, other studies in the USA point out that a highly significant correlation between both is not possible to find due to high climatic variability. The aim of this work is to test the correlation between average minimum temperatures and hail damage intensity over the Spanish Iberian Peninsula. With this purpose, correlation analyses on both variables were performed for the 47 Spanish provinces (as individuals and single set) and for all crops and four individual crops: grapes, wheat, barley and winter grains. Suitable crop insurance data are available from 1981 until 2007 and based on this period, temperature data were obtained. This study does not confirm the results previously obtained for France and the Netherlands that relate observed hail damage to the average minimum temperature. The reason for this difference and the nature of the cases observed are discussed.

Oats in Minnesota, acreage, yield, production by counties, 1921-1959.

Mode of access: Internet.

Report.

Report year irregular.

Review of the effects of disaster conditions on wheat, soybeans, and feed grains production : hearings before the Subcommittee on Wheat, Soybeans, and Feed Grains of the Committee on Agriculture, House of Representatives, One Hundred First Congress, first session, March 23 and April 6, 1989; May 19, 1989, Amarillo, TX, and May 20, 1989, Great Bend, KS.

"Serial no. 101-7."

Technological and financial approaches to risk management in agriculture: an integrated approach

In the present paper, risk-management problems where farmers manage risk both through production decisions and through the use of market-based and informal risk-management mechanisms are considered. It is shown that many of these problems share a common structure, and that a unified and informative treatment of a broad spectrum of risk-management tools is possible within a cost-minimisation framework, under minimal conditions on their objective functions. Fundamental results are derived that apply regardless of the producer's preference towards risks, using only the no-arbitrage condition that agricultural producers never forego any opportunity to lower costs without lowering returns.

Drought policy: a graphical analysis

The standard approach to modelling production under uncertainty has relied on the concept of the stochastic production function. In the present paper, it is argued that a state-contingent production model is more flexible and realistic. The model is applied to the problem of drought policy.

Supplemental Coverage Option Expanding as Part of the Farm Safety Net

The 2014 Farm Bill created Supplemental Coverage Option (SCO), a new add-on crop insurance option which provides supplemental coverage on a producer’s underlying crop insurance policy. SCO operates by mimicking a producer’s individual crop insurance coverage and covering a portion of the deductible based on county-level yield or revenue. SCO is available in select Maryland counties for apples, barley, corn, grain sorghum, green peas, oats, peaches, processing beans, soybeans, sweet corn, and winter wheat, as of the 2017 crop year. USDA’s Risk Management Agency (RMA) continues to expand covered counties and crops covered, and begin distinguishing by practices (such as irrigated compared to non-irrigated).