A Markov chain model of crop conditions and intrayear crop yield forecasting

Abstract

Crop condition reports are an important source of information for producers, grain traders, businesses, and policymakers to assess and manage the price and yield risk inherent in a given crop. A Markov chain model is proposed for describing the weekly dynamic behavior of reported crop conditions. Empirical transition probabilities are estimated for corn grown in Nebraska, and forecasted crop conditions from the Markov chain are used as inputs to forecast final crop yields prior to harvest time. The results suggest that the modeling and forecasting approach has value for estimating crop yields as intrayear information about crop conditions materializes.