An analysis of economic factors affecting corn basis in Southwest Kansas

Abstract

The region of Southwest Kansas will be experiencing growth in both beef and dairy production in the coming years. Additionally, there are also concerns with ground water availability for corn production in the area for the long run. Southwest Kansas most years is already a corn deficit area and with growing demand of corn and corn silage for feed, corn basis in the region is expected to strengthen. Familiarity with local corn basis is crucial for producers, grain merchants, and end-users to optimize their business decisions. This study examines potential outcomes for corn basis impacts based on the anticipated structural changes in the region. To examine these changes, OLS Models were developed to specifically observe changes in total cattle inventory, corn acres, and corn silage acres, to measure impacts on corn basis as a dependent variable. First however, grain elevators in the region were analyzed to determine which ones to model for, and which modeled elevators would be the most valuable. The relationships of 30 grain elevators’ corn basis values in the region were observed, and it was concluded that they were mostly highly correlated, suggesting a highly related market in the area and that similar factors were all explaining basis in the region. Other background information for the region and insights from the data were also explored throughout the paper. Lastly, data transformations and some proxies and assumptions had to be implemented for the data since not all variables were always complete and clean. The results of the study indicated that the selected variables to explain corn basis, which included nearby corn futures, cattle inventory, planted corn acres, corn silage acres, diesel prices, and monthly time fixed effects, explained 76% of the variation in corn basis on average for the southwest Kansas regional models that were implemented. The RMSE’s were slightly higher than ideal ranging from 0.249 to 0.268, however, prior literature has noted that in recent years, it may be more difficult to forecast basis with lower error terms in general. Also, previously as noted, the data isn’t perfect, with some proxies in place, which may contribute to the higher RMSE’s as well. Nevertheless, with these results potential impacts on basis can be forecasted. A median forecast for changes in silage acres, and the anticipated future change in total cattle inventory is an impact of corn basis strengthening by $0.29/bu. The potential impacts discussed in this study are valuable for all parties involved in the corn supply chain in Southwest Kansas. Econometric models have some drawbacks, and complete accuracy is never ensured with any forecasting methods. However, the results in this paper provide a data driven method, and potential impacts to anticipate in the future.