Whole Farm Income Insurance in a Canadian Context

This paper employs mean-variance and mean-skewness optimization to investigate farmers’ crop choices under Gross Revenue Insurance (GRIP), Whole Farm Income Insurance, the Canadian Agricultural Income Stabilization program, and its modified 2008 program AgrInvest. To our knowledge this paper is the first to fully consider the endogenous optimization of whole farm insurance in a farm optimization model. The results indicate that farmers will alter farm plans significantly in response to the type of insurance offered and the level of subsidy. Farmers will take on production risks that they would not otherwise take and this risk taking behavior is exacerbated by subsidy.Agricultural Insurance, Skewness Maximization, Mean-Variance, Farm Income Insurance, GRIP, CAIS, AgrInvest, Agricultural Finance,

CAN HYSTERESIS AND REAL OPTIONS EXPLAIN THE FARMLAND VALUATION PUZZLE?

This paper proposes that the common finding that land prices are systematically higher than their fundamental value as measured by the present value of future cash might be due to real options arising from uncertainty in cash flows. The paper posits a model in which the seller has a real option to postpone the sale of land. Because the value of land is measured as a present value, the buyer does not hold a similar option to postpone the purchase. It is argued that the seller's option offers a plausible explanation for the wedge between observed farmland prices and the present value model. The paper uses a Dixit and Pindyck (1996) real options framework. Using historical cash flow and land price information for Ontario, it is shown how real options can lead to a land price greater than that predicted by the present value model. The findings also suggest the existence of land price bubbles and shows how a real options framework can be used to detect bubbles.Land Economics/Use,

WEATHER DERIVATIVES AND SPECIFIC EVENT RISK

This paper investigates the relationship between weather events and agricultural risks. Specific event risks are defined by outcomes related to a specific event such as low temperature and rainfall. Using Ontario data this paper describes specific events and shows how these specific events can be insured using weather derivatives and insurance.Heat insurance, rainfall insurance, weather derivatives, weather options, crop insurance, agricultural risk, Risk and Uncertainty,

Fear, Trust and Agroterrorism

This paper presents results from a consumer survey on risk perceptions about agroterrorism and the safety of the US food supply. The survey conducted in the United States during the fall of 2004, provides insights into what consumers are thinking about terrorism against the food system, their knowledge base on food safety, the vulnerabilities of the food supply chain and food categories to terrorist contamination, and their trust in government and groceries to protect the food supply.Food Consumption/Nutrition/Food Safety, Institutional and Behavioral Economics,

WEATHER INSURANCE, CROP PRODUCTION AND SPECIFIC EVENT RISK

Crop Production/Industries, Risk and Uncertainty,

INSURING HEAT RELATED RISKS IN AGRICULTURE WITH DEGREE-DAY WEATHER DERIVATIVES

This paper presents a model and framework for pricing degree-day weather derivatives when the weather variable is a non-traded asset. The paper compares the options prices from the recommended model and compares it to a typical insurance-type model.Risk and Uncertainty,

RANDOM WALKS AND FRACTAL STRUCTURES IN AGRICULTURAL COMMODITY FUTURES PRICES

This paper investigates whether the assumption of Brownian motion often used to describe commodity price movements is satisfied. Using historical data from 17 commodity futures contracts specific tests of fractional and ordinary Brownian motion are conducted. The analyses are conducted under the null hypothesis of ordinary Brownian motion against the alternative of persistent or ergodic fractional Brownian motion. Tests for fractional Brownian motion are based on a variance ratio test and compared with conventional R-S analyses. However, standard errors based on Monte Carlo simulations are quite high, meaning that the acceptance region for the null hypothesis is large. The results indicate that for the most part, the null hypothesis of ordinary Brownian motion cannot be rejected for 14 of 17 series. The three series that did not satisfy the tests were rejected because they violated the stationarity property of the random walk hypothesis.Demand and Price Analysis, Marketing,

PARAMETRIC AND NON-PARAMETRIC CROP YIELD DISTRIBUTIONS AND THEIR EFFECTS ON ALL-RISK CROP INSURANCE PREMIUMS

Normal, gamma and beta distributions are applied to 609 crop yield histories of Ontario farmers to determine which, if any, best describe crop yields. In addition, a distribution free non-parametric kernel estimator was applied to the same data to determine its efficiency in premium estimation relative to the three parametric forms. Results showed that crop yields are most likely to be described by a beta distribution but only for 50% of those tested. In terms of efficiency in premium estimation, minimum error criteria supports use of a kernel estimator for premium setting. However, this gain in efficiency comes at the expense of added complexity.crop insurance, crop yield distributions, kernel, Crop Production/Industries, Risk and Uncertainty,