Degree Type

Dissertation

Date of Award

1997

Degree Name

Doctor of Philosophy

Department

Economics

First Advisor

Marvin Hayenga

Abstract

A model is developed to analyze the nearby basis behavior of corn and soybeans in several markets across the U.S. Results suggest that basis behavior has a seasonal pattern, and that different variables affect nearby corn and soybean basis at various periods. The most important factors affecting basis are storage cost (opportunity cost), transportation cost (barge rates), and supply (regional production relative to regional storage capacity). Nine conventional (naive three-year-average forecasts, econometric, ARIMA and composite forecast models) and less conventional forecasting techniques (State Space and Neural Networks models) are utilized to forecast out-of-sample basis for one-month up to 12-month ahead. The performance of all methods in forecasting 1991-1995 basis is analyzed. The forecasting performance comparison shows that adding current market information to the three-year-average model and the seasonal ARIMA model can slightly improve basis forecasts compared to the benchmark simple three-year-average forecast model.

DOI

https://doi.org/10.31274/rtd-180813-13490

Publisher

Digital Repository @ Iowa State University, http://lib.dr.iastate.edu/

Copyright Owner

Bingrong Jiang

Language

en

Proquest ID

AAI9737727

File Format

application/pdf

File Size

149 pages

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