Estimating Implied Volatility Directly from "Nearest-to-the-Money" Commodity Option Premiums

Risk and Uncertainty,

Reduction of Yield and Income Risk Under Alternative Crop Insurance and Disaster Assistance Plans

This study compares the effectiveness of five crop insurance/disaster assistance plans: an individual farm yield insurance plan similar to the current FCIC multi-peril program ; two area yield insurance plans; a farm yield disaster assistance plan; and an area yield disaster assistance plan. These methods are examined for reduction in yield and gross income variability with and without participation in the government deficiency payment programs using farm-level yield data from 98 dryland wheat farms and 38 dryland corn farms in Kansas . Although individual farm yield insurance is complex, suffers from moral hazard and adverse selection problems, and is likely to be the most expensive to administer , it provides more yield and gross income risk reduction than any of the alternative insurance/disaster assistance plans.Crop Insurance, Crop Disaster Assistance, Risk, Wheat, Corn, Risk and Uncertainty,

June versus March Calving for the Nebraska Sandhills: Economic Comparisons

Costs and returns of June and March calving systems were compared at four production phases. Financial costs of the June system were lowest, due primarily to lower costs of producing a weaned calf. Post-weaning financial and economic costs at each phase were nearly identical. Selling June-born steer calves at January weaning would double net returns compared to selling March-born steer calves at October weaning due to lower costs and higher market prices. Net returns for June-born steer calves retained beyond weaning are highest if calves are retained as yearlings and finished. Calves finished as calf-feds provided the highest net returns for the March calving system

Factor Input Demand Subject to Economic and Environmental Risk: The Case of Nitrogen Fertilizer in Corn Production

Nitrogen (N) fertilizer demand in relation to economic and environmental risks associated with N-fertilizer management are examined. Both nominal and environmental damage-adjusted net returns distributions are evaluated using stochastic dominance analysis. Results suggest that, in the absence of environmental risk, N demand becomes more elastic as farmers become more risk averse. When environmental risk is introduced to the decision-making process, N demand becomes even more elastic

Factor Input Demand Subject to Economic and Environmental Risk: The Case of Nitrogen Fertilizer in Corn Production

Nitrogen (N) fertilizer demand in relation to economic and environmental risks associated with N-fertilizer management are examined. Both nominal and environmental damage-adjusted net returns distributions are evaluated using stochastic dominance analysis. Results suggest that, in the absence of environmental risk, N demand becomes more elastic as farmers become more risk averse. When environmental risk is introduced to the decision-making process, N demand becomes even more elastic.environmental damage, factor input demand, nitrogen fertilizer management, risk, stochastic dominance, Crop Production/Industries, Environmental Economics and Policy,

June Versus March Calving for the Nebraska Sandhills: Economic Risk Analysis

Price risk analysis of economic and financial net returns from June and March calving systems was used to rank and identify preferred production/sale strategies according to risk preferences of producers. Analysis of economic net returns identified selling a June-born steer at weaning from the breeding on meadow (meadow-bred) treatment as preferred strategy regardless of risk preferences. Post-weaning, selling a June-born finished yearling steer from the meadow-bred treatment was ranked highest. Analysis of financial net returns identified selling a June-born yearling steer from the meadow-bred treatment prior to summer grazing as preferred for all but those strongly risk averse; selling a June-born steer from the meadow-bred treatment at weaning ranked second

A Cross Sectional Analysis of Agricultural land Prices in Nebraska 1978-1982

Land Value expectations are important to land owners, agricultural producers, lenders, governmental agencies, and other parties. Greater understanding of land values and the factors involved in their determination is therefore beneficial to the decision-making process. The analysis of farmland values has been a major focus on the agricultural economics profession for several decades. Early research focused primarily on the measurement of the relationship of income levels to land values. In more recent years, econometric models have attempted to uncover additional economic factors which influence the value of farmland. Econometric models have used many quantification techniques ranging from single-equation ordinary least squares regression to systems-of-equations simulation. Data bases utilized in these studies have also been diverse, ranging from private survey information to Census of Agriculture data, the latter being the most common. Many of the models have received criticism for being too broad geographically or insensitive to value changes over time. In particular, models of the U.S. farmland market have needed to assume homogeneity of land its use throughout the nation. also, the utilization of nationally-aggregated time-series data perceivably smooths-out any short-term fluctuations in farmland values caused by varying expectations on the part of the market participants. The very nature of the farmland market necessitates a more regionalized time-specific study. the analysis should allow for spacially-sensitive factors to merge into the value estimation process which are otherwise forgone when more general, aggregated data are used. The primary focus of this study is to gain a clearer understanding of the Nebraska farmland market and the components which influence land values. While identification of the relevant factors that influence agricultural land values has been the focus of several recent studies, the specific nature of this study\u27s data source provides a unique opportunity to analyze the agricultural real estate market by sub-state regions