Abstract
Stumpage price is one of the key economic inputs in developing sustainable forest-management plans and analyzing forest-management decisions and investments. A robust method to forecast stumpage prices and prediction intervals would help timberland owners and consultants bound uncertainty and improve the chance that future management actions agree with specified objectives. We evaluated three forecasting methods: simple moving average, linear weighted moving average, and exponential weighted moving average. Real annual stumpage prices for New York's six most common species were used to evaluate the robustness of the three forecasting methods. We concluded that, while being more complex computationally, the exponential weighted moving average was preferred to the simple and linear weighted moving average.