EVALUATING THE USE OF FUTURES PRICES TO FORECAST THE FARM LEVEL U.S. CORN PRICE

A model is developed using bases, marketing weights, and a composite of monthly futures and cash prices to forecast a season-average U.S. farm price for corn. Forecast accuracy measures include the mean absolute percentage error and Theil's U-statistic. Futures forecasts are compared with a naïve forecast and WASDE projections. Futures price forecasts are timely and reliable.Marketing,

Price Determination for Corn and Wheat: The Role of Market Factors and Government Programs

Annual models for U.S. farm prices for corn and wheat are developed based on market factors as well as government agricultural commodity programs. The pricing relationships utilize a stocks-to-use modeling framework to capture the effects of market supply and demand factors on price determination. This formulation is augmented by factors that represent the changing role of agricultural policies, particularly government price support and stockholding programs. For wheat, international market effects as well as wheat feed use and related crosscommodity pricing considerations also are included. Model properties and model performance measures are presented. Additionally, recent price-forecasting applications of the models are discussed. The relatively simple structure of the estimated price models and their small data requirements lend themselves to use in price-forecasting applications in conjunction with market analysis of supply and demand conditions. In particular, the models have been implemented into USDAís short-term market analysis and long-term baseline projections. In these applications, the models provide an analytical framework to forecast prices and a vehicle for making consistency checks among the Departmentís supply, demand, and price forecasts.corn, wheat, farm price, price determination, stocks-to-use ratio, price supports, commodity programs, forecasts, Crop Production/Industries, Demand and Price Analysis,

Measuring the Influence of Commodity Fund Trading on Soybean Price Discovery

The increase in commodity fund trading in the agricultural commodity futures markets has raised concern that this trading is degrading the price discovery performance of these markets. We used the Beveridge-Nelson Decomposition procedure to estimate the price discovery performance of the soybean futures and spot markets. We found that the price discovery performance of the soybean futures market has improved along with the increased commodity fund trading. Our results indicated that a portion of the price discovered in the soybean futures market is passed to the spot market.price discovery, commodity funds, cointegration, Beveridge-Nelson decomposition,

U.S. Peanut Markets Adjust to Policy Reform

With the recent (2002) elimination of the longstanding "marketing quota" system that supported domestic peanut prices at well above world levels, the U.S. peanut sector is in the initial stages of adjusting to a more uncertain, market-oriented environment. At the aggregate level, some early indications are that the adjustment process for U.S. peanut farmers has been difficult, resulting in deep losses of revenue and a rapid exit from peanut production by some producers. In 2003, the value of U.S. peanut production was down 30 percent and prices fell by nearly 25 percent compared with 2001. U.S. peanut planted acreage is at its lowest since 1915, and planted acreage has declined sharply in several important peanut producing States-55 percent in Virginia and nearly 40 percent in Texas since 2001. Peanut production is concentrated geographically, with a relatively small subset of counties in just 7 States accounting for the bulk of output. As a result, changes to the peanut program have potentially important economic implications not just for the individual farm households that produce peanuts, but perhaps for some rural communities as well. At the same time, it appears that adjustment difficulties for many current (and historical) producers may be mitigated by a number of factors, including: (1) an already diversified farm enterprise structure, with peanut (harvested) acreage accounting for an average of only 20 percent of peanut farmers' overall cropland, and a substantial share-72 percent of total household income already coming from off farm sources; (2) lower production costs for some producers stemming from policy-induced reductions in factor or input costs (e.g. land rental rates, seed prices); and (3) government revenue support and asset-loss compensation for current and historical peanut producers. It appears that one of the main difficulties faced by U.S. peanut producers following the elimination of the marketing quota system has been the loss of price stability, and a lack of price transparency and price discovery mechanisms under the new peanut program. Sources of price information and risk management tools -such as futures markets - are not available to peanut producers. Marketing alternatives may also be limited by a concentrated market structure at the buyer/processor level. Beyond detailing the more aggregate-level indicators of market adjustment, examining the adjustment experience and strategies of peanut producers at the household/farm enterprise level represents an opportunity to identify policy and market factors that facilitated or hindered adjustment, and to inform producers and policy-makers contemplating reform in other commodity programs. In particular, other U.S. commodities that are geographically concentrated or have a similar program history of production/import controls (tobacco, sugar, dairy) could draw lessons from the experience of peanut producers. Variations by region, demographic and household financial characteristics, and other factors such as institutional setting "market structure, trading/price discovery institutions, macroeconomic context or market orientation of the economy" are relevant to the analysis of policy reform both in the United States and other countries.peanuts, policy, adjustment, marketing quotas, Agricultural and Food Policy, Crop Production/Industries,

Forecast Performance of Futures Price Models for Corn, Soybeans, and Wheat

Replaced with revised version of paper 06/15/07.Marketing,

Economic Analysis of Base Acre and Payment Yield Designations Under the 2002 U.S. Farm Act

The 2002 Farm Act provided farmland owners the opportunity to update commodity program base acres and payment yields used for calculating selected program benefits. Findings in this report suggest that farmland owners responded to economic incentives in these decisions, selecting those options for designating base acres that resulted in the greatest expected flow of program payments. Decisions of farmland owners in South Dakota, in upland cotton area, and in the Heartland region support the payment-maximization argument. In general, landowners favored maximizing payments over aligning base acres to current or recent plantings. Farmland owners with high-payment base acres, such as rice and cotton, held on to these base acres and, whenever possible, expanded them. Analogously, landowners with low-payment commodity base acres, such as oats and barley, switched to higher payment commodities whenever possible.base, 2002 Farm Act, direct payments, counter-cyclical payments, production flexibility contract payments, base acres, program yields, Agricultural and Food Policy, Farm Management,

Domestic Support for the U.S. Rice Sector and the WTO: Implications of the 2002 Farm Act

The U.S. rice sector is expected to receive some of the largest relative support under the 2002 Farm Act. USDA's rice baseline model is used to compute marketing loan benefits, while direct payments and counter-cyclical payments are estimated from endogenous prices and exogenous policy parameters. Alternative scenarios of reduced marketing loan benefits suggest that projected annual average sector revenue could decline by 4 to 27 percent.Agricultural and Food Policy,

Volatility Spillover and Time-Varying Conditional Correlation Between DDGS, Corn, and Soybean Meal Markets

We find distiller\u27s dried grains with solubles (DDGS) prices to be positively correlated with both corn and soybean meal prices in the long run. However, neither corn nor soybean meal prices respond to deviations from this long-run relationship. We also identify strong time-varying dynamic conditional correlations between the markets, with the correlation between DDGS and corn strengthened after the expansion of ethanol production. There also appear to exist significant volatility spillovers from both the corn and soybean meal markets to the DDGS market, with the impact from corn shocks much larger compared to soybean meal shocks

SPATIAL PRICING EFFICIENCY: THE CASE OF U.S. LONG GRAIN RICE

The spatial rice price relationships for U.S. long grain rough rice are affected by many factors besides the transportation cost between markets, such as milling, processing, cooking and nutritional value as well as physical characteristics. This study applies a time series framework to analyze long run price relationships for Arkansas, Mississippi, Louisiana, Texas and California long grain rice. Johansen's test results showed that at least there are two cointegrating price vectors. However, such a finding is not supported by the ECM model in any of the price series.Demand and Price Analysis,

FARMERS' VEG RISK PERCEPTIONS AND ADOPTION OF VEG CROP INSURANCE

Producer survey results are analyzed to determine factors influencing value-enhanced grain (VEG) risk perceptions and VEG crop insurance adoption. VEG production is perceived to be riskier than commodity production. VEG types, input costs, and production problems affect risk perceptions. Factors including previous insurance use impact VEG crop insurance adoption.Risk and Uncertainty,