Time Series Forecast Analysis in Wholesale Broiler Markets

In 2016 the chicken industry provided nearly 1.2 million jobs, 68 billion dollars in wages, 313 billion dollars in economic activity and 24 billion dollars in government revenue (John Dunham & Associates, Inc., 2016). Broiler production has changed dramatically from the early 90’s to the turn of the 21st century. Technological advancements, continuous improvements, production efficiencies and industry changes have made the industry the global market it is today. The poultry industry is an extremely volatile market with prices constantly fluctuating in response to input price volatility and demand and supply changes. These changes are often driven by world economic conditions which impacts the roughly 20% of U.S. production that is exported. Due to these variations, accurate forecasting of poultry prices is difficult. Economic modeling is complex at best; this paper examines a comparison between vector autoregression (VAR) and autoregressive (AR) techniques. Urner Barry average monthly northeast wholesale poultry parts price data was used for this research. Parts analyzed are; drumstick (DRUM), jumbo boneless skinless breast tender out (BSBTO), leg quarter (LQ), thigh (THIGH), small wing (SMWING), jumbo wing (JMWING), tender (TENDER) and whole bird without giblets weighing 2 ¼ lbs. (WOG). This modeling will focus on the technical aspects of modeling to initiate a strong foundation for further research. Key fundamental aspects are discussed to give economical understanding of the challenges the broiler industry faces. This research concludes that AR modeling is superior to VAR modeling techniques. It is important for the broiler industry to understand pricing strategies for contracts with food retail operators. Price forecasting has the potential to help poultry companies increase their returns on revenue. Wholesale broiler parts today are extensively further processed and value added today than in previous years. This causes the wholesale price to have little influence in processors determined price within contracts. Knowing price interaction will allow processors to determine alternate cuts of meat that can be substituted for products during times of high prices