Enhancing feed optimization in Kenya’s poultry subsector: Commodity pricing dynamics and forecasting

Abstract

The poultry subsector has the potential to transform Kenya’s economic and social welfare. This study seeks to understand pricing dynamics of feed raw material based on available local price data with comparison to historical global data. Historical data of at least two years on the prices of various raw materials used in formulating poultry feed as well as climatic, geographical, demographical, and socio-economic data on Kenya and its counties were collected from various repositories. This was supplemented by key informant interviews. The Box-Jenkins Auto Regressive Integrated Moving-Average models predict an increasing trend in maize price at a rate of Kshs. 3.3 per day with a variance of 14.45% over a rolling 90-day cycle. For wheat, there is a decline over the same period of Kshs. 1.2 per day with a variance of −2.90%. The price forecast for finger millet shows a variation of 5.30%, with fluctuation in the trend. Energy prices and exchange rates have no influence on pricing of the three agricultural commodities. There is no confluence between Kenyan pricing movements and global price fluctuations for maize and wheat. Moving forward, participatory creation of platforms to complement the National Farmers Information Service website is key.

Keywords

• agricultural commodity price dynamics
• poultry feed
• auto-regressive integrated moving-average models
• poultry subsector
• kenya