Evaluating changes in credit rating quality of U.S. farmer cooperatives

Abstract

The default of a cooperative has significant implications on cooperative members and the agricultural supply chain. Therefore, monitoring and even predicting future changes in creditworthiness is of value to cooperative managers and their lenders. However, we know little about farmer cooperatives' credit profiles and behavior because their financial statements are seldom shared. Using a Moody’s credit rating model and a unique data set, this article estimates Markov chains to evaluate changes in farmer cooperatives’ credit quality. The unconditional (one-size-fits-all) probability matrix, as is typically estimated, is shown to not be appropriate in describing credit rating transitions. Results also show cooperatives do not exhibit rating change momentum since a downgrade is not likely to be followed by another downgrade in the next period. Credit ratings of farmer cooperatives with less than $20 million in net sales follow a first-order Markov chain with stationary probabilities and the cooperatives with net sales of more than $250 million follow a zero-order Markov chain. This article adds to the limited research available on the credit rating behavior of farmer cooperatives. Cooperative managers, directors, and lenders can utilize these findings to make more informed decisions to impact future credit ratings.