Olga Isengildina-Massa

The Impact of Situation and Outlook Information in Corn and Soybean Futures Markets: Evidence from WASDE Reports

The purpose of this study was to examine the impact of situation and outlook information from World Agricultural Supply and Demand Estimates (WASDE) in corn and soybean futures markets over the period 1985 to 2006. Results indicate that WASDE reports containing National Agricultural Statistics Service (NASS) crop production estimates and other domestic and international situation and outlook information have the largest impact; causing return variance on report sessions to be 7.38 times greater than normal return variance in corn futures and 6.87 times greater than normal return variance in soybean futures. WASDE reports limited to international situation information and domestic and international outlook information have a smaller impact. The results show that the impact of WASDE reports has increased over time.

Empirical confidence intervals for USDA commodity price forecasts

Conventional procedures for calculating confidence limits of forecasts generated by statistical models provide little guidance for forecasts based on a combination or a consensus process rather than formal models, as is the case with US Department of Agriculture (USDA) forecasts. This study applied and compared several procedures for calculating empirical confidence intervals for USDA forecasts of corn, soybean and wheat prices over the 1980/81 through 2006/07 marketing years. Alternative procedures were compared based on out-of-sample performance over 1995/96 through 2006/07. The results of this study demonstrate that kernel density, quantile distribution and best fitting parametric distribution (logistic) methods provided confidence intervals calibrated at the 80% level prior to harvest and 90% level after harvest. The kernel density-based method appears most accurate both before and after harvest with the final value falling inside the forecast interval 77% of the time before harvest and 92% after harvest, followed by quantile regression (73% and 91% before and after harvest, respectively) logistic distribution (73% and 90% before and after harvest, respectively) and histogram (66% and 84% before and after harvest, respectively). Overall, this study demonstrates that empirical approaches may be used to construct more accurate confidence intervals for USDA corn, soybean and wheat price forecasts.

The biggest bang for the buck: valuation of various components of a regional promotion campaign by participating restaurants.

This study examined how various components of the Certified South Carolina campaign are valued by participating restaurants. A choice experiment was conducted to estimate the average willingness to pay (WTP) for each campaign component using a mixed logit model. Three existing campaign components—Labeling, Multimedia Advertising, and the ‘‘Fresh on the Menu’’ program—were found to have a significant positive economic value. Results also revealed that the type of restaurant, the level of satisfaction with the campaign, and the factors motivating participation significantly affected restaurants’ WTP for the campaign components.

Do Markets Correct for Smoothing in USDA Crop Production Forecasts? Evidence from Private Analysts and Futures Prices

This study evaluates whether smoothing (positive correlation in subsequent revisions) in USDA corn, soybean, and wheat production forecasts is likely to result in misallocation of economic resources. Smoothing, like any other type of forecast inefficiency, implies that some of the information in these forecasts is predictable. Based on the evidence of smoothing, we decomposed market surprise and forecast revision into predictable and unpredictable components. Our results show that futures markets tended to react only to the unpredictable component, therefore indicating that market participants were aware of smoothing and adjusted for it in forming their price expectations.

The impact of public and semi-public information on cotton futures market

ABSTRACT This study estimated the impact of all major public and semi-public reports on the cotton futures market from 1995 through 2012. The estimation was based on the event study approach with the events measured by the release of five major reports: Export Sales, Crop Progress, World Agricultural Supply and Demand Estimates (WASDE) and Prospective Plantings (public reports from US Department of Agriculture) and Cotton This Month (semi-public report from International Cotton Advisory Committee). The best-fitting IGARCH(1,1)-t model that accounted for the day-of-week, seasonality and stock levels was used to measure the report effects on daily nearby cotton close-to-close futures returns. Prospective Plantings and WASDE reports appeared to be the most important sources of information in the cotton markets moving the conditional standard deviation of returns by an average of 14.4 and 9.6 percentage points, respectively. However, significant market reaction was not found for the other three reports. Our analysis revealed that, in the presence of clustering, ignoring the impact of other reports would have resulted in about 18% overestimation of WASDE impact.

Can Rationality of Usda’s Fixed-Event Crop Forecasts be Improved?

Abstract Weak-form rationality of fixed-event forecasts implies that forecast revisions should not be correlated. However, significant positive correlations between consecutive forecast revisions were found in most USDA forecasts for U.S. corn, soybeans, wheat, and cotton. This study developed a statistical procedure for correction of this inefficiency which takes into account the issue of outliers, the impact of forecast size and direction, and the stability of revision inefficiency. Findings suggest that the adjustment procedure has the highest potential for improving accuracy in corn, wheat, and cotton production forecasts.