In recent years three important trends have become apparent among grain marketing and farm supply cooperatives. These farmer owned firms have been rapidly investing in infrastructure, reformulating profit distribution and equity strategies, and have pursued consolidation with other cooperatives. This manuscript explores the factors contributing to those trends, the implications for cooperatives leaders, and the impacts on farmer members. Abstract: In recent years three important trends have become apparent among grain marketing and farm supply cooperatives. These farmer owned firms have been rapidly investing in infrastructure, reformulating profit distribution and equity strategies, and have pursued consolidation with other cooperatives. This manuscript explores the factors contributing to those trends, the implications for cooperatives leaders, and the impacts on farmer members.

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Maize is one of the major staples and cash crops for many Tanzanians. Excessive volatility of maize prices destabilises farm income in maize-growing regions and is likely to jeopardise nutrition and investment in many poor rural communities. This study investigates whether market reform policies in Tanzania have increased the volatility of maize prices, and identifies regional characteristics that can be attributed to the spatial price volatility. To achieve the objectives, an autoregressive conditional heteroskedasticity in mean (ARCH-M) model is developed and estimated in this study. Results show that the reforms have increased farm-gate prices and overall price volatility. Maize prices are lower in surplus and less developed regions than those in deficit and developed regions. Results also show that the developed and maize-deficit regions, and regions bordering other countries have experienced less volatile prices than less developed, maize-surplus and non-bordering regions. Our findings indicate that investments in communication and transportation infrastructures from government and donor countries are likely to increase inter-regional and international trade, thereby reducing the spatial price volatility in Tanzanian maize prices in the long run. Copyright (c) 2008 The Authors. Journal compilation (c) 2008 The Agricultural Economics Society.

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This research forecasts peak call volume of a centralized after-hours call center for rural electric cooperatives to help the call center determine staffing levels. A Gaussian copula is used to capture the dependence among non-normal distributions. Using a centralized call center reduces costs by approximately 75% compared to having individual call centers at each cooperative. Adding cooperatives to the centralized call center is projected to further decrease costs per member. An out-of-sample forecasting exercise after the call center expanded validated the model's forecast that additional cooperatives could be added without a proportional increase in the peak number of calls.