A Predictive Analytics Understanding of Cooperative Membership Heterogeneity and Sustainability

Recent advances in cooperative theory have focused on membership heterogeneity as being a significant challenge for cooperative sustainability. We use predictive analytics to forecast U.S. farmer cooperative sustainability at an aggregate level and include multiple dimensions of membership heterogeneity. We report the importance and shape of the effect of membership heterogeneity when predicting and forecasting cooperative sustainability in the near-term. We also report forecasts of cooperative sustainability given expected changes to membership heterogeneity. The data this study used are from the United States Department of Agriculture (USDA)-Economic Research Service (ERS) Agricultural Resource Management Survey (ARMS) joined with USDA-Rural Development cooperative financial data at the state level. Membership heterogeneity was found to be less relevant than other variables included in the model for predicting cooperative business volume and number of cooperatives headquartered per state, and an estimate of cooperative sustainability. Membership heterogeneity effects were mostly offsetting given expected changes to member heterogeneity, and/or were offset due to changes to other macro factors. Consequently, we conclude membership heterogeneity may affect the number of cooperatives and extent consistent with theoretical literature at a micro level; however, we also expect a similar level of sustainability of cooperatives at an aggregate level in the near-term despite changes to membership heterogeneity.