The past several years has marked one of the most heightened periods of fed cattle basis volatility since the installment of live cattle futures contracts. Understanding basis, the difference between local cash price and the futures contract price, is imperative when making marketing and procurement decisions. In the face of increased volatility, the ability to produce accurate basis expectations is no simple task. The purpose of these analyses was to develop econometric models to determine the greatest influencers of fed cattle basis, to test the presence of structural changes in the determinants of fed cattle basis, and to compare out-of-sample forecasting performance. This study analyzed in-sample econometric models using monthly data from January 2003 through September 2016, then compared the results of the competing models. Using the same time period, we then identified the presence of structural breaks in the data. Furthermore, this study analyzed the out-of-sample forecasting performance for January 2012 through September 2016. The out-of-sample results were then compared to in-sample estimations and historical average basis models. The in-sample estimations indicated the important factors that influence fed cattle basis. The results indicate that there are multiple structural breaks present in the determinants of fed cattle basis examined during this study. We can robustly conclude that there was a market structural break present in the fourth quarter of 2013 and within the 2005-2006 time period. The results indicate that the out-of-sample regression estimations were outperformed by historical average models and did not improve our ability to accurately forecast basis. Overall, a 3 or 4 year historical average model should be preferred over econometric estimations when forecasting fed cattle basis.

Live cattle basis witnessed incredible volatility in recent years leading to questions of structural change and the possibility of decreased hedging effectiveness. If fundamental drivers of live cattle cash and futures prices have changed, cattle feeders and beef packers alike may need to re-evaluate their business, marketing, and hedging plans. Structural breaks can be identified and confirmed using statistical methods while the drivers of those structural breaks can be evaluated using forecast models. This research finds evidence that both live cattle basis and live cattle basis variability witnessed structural change near the beginning of 2014. Furthermore, results suggest that changes to the live cattle supply chain including regional cash market thinness and a trend towards higher quality beef are among the most important factors driving structural change.