Application of modern statistical tools to solving contemporary economic problems: Evaluation of the regional agricultural campaign impact and the USDA forecasting efforts.

摘要

The research is comprised with three studies to implement statistical tools for examining two economic issues: the impact of a regional agricultural campaign on participating restaurants and efforts of U.S. Department of Agriculture (USDA) forecasting reports in agricultural commodity markets.;The first 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.;The second study evaluated the revision inefficiencies of all supply, demand, and price categories of World Agricultural Supply and Demand Estimates (WASDE) forecasts for U.S. corn, soybeans, wheat, and cotton. Significant correlations between consecutive forecast revisions were found in all crops, all categories except for the seed category in wheat forecasts. This study also developed a statistical procedure for correction of inefficiencies. The procedure took into account the issue of outliers, the impact of forecasts size and direction, and the stability of revision inefficiency. Findings suggested that the adjustment procedure has the highest potential for improving accuracy in corn, wheat, and cotton production forecasts.;The third study evaluated the impact of four public reports and one private report on the cotton market: Export Sales, Crop Processing, World Agricultural Supply and Demand Estimates (WASDE), Perspective Planting, and Cotton This Month. The "best fitting" GARCH-type models were selected separately for the daily cotton futures close-to-close, close-to-open, and open-to-close returns from January 1995 through January 2012. In measuring the report effects, we controlled for the day-of-week, seasonality, stock level, and weekend-holiday effects on cotton futures returns. We found statistically significant impacts of the WASDE and Perspective Planting reports on cotton returns. Furthermore, results indicated that the progression of market reaction varied across reports.