A model was developed to estimate the economic stock supply of primary wood products. Two hardwood products were recognized: logs and bolts. The supply model was used to evaluate the impacts of shifting primary product demands and increasing supply costs on delivered prices and quantities in southwest Virginia. Homogeneous supply response cells, identified from Forest Service forest survey data, were used to generate log and bolt supplies. Response cells define blocks of forest land with similar biologic, physiographic, and landowner characteristics. Yield equations estimate the volume of logs and bolts available. Harvesting and hauling costs depend on a response cell's physiographic characteristics. Stumpage owners set reservation price as a function of expected stumpage prices, future timber yields, and an alternative rate of return. Recovery cost per unit in a response cell equals the sum of harvesting and hauling costs and reservation price. The quantities of logs and bolts supplied are determined by comparing harvest revenues to recovery costs. If revenues are greater than or equal to costs in a particular response cell, then timber is harvested The demands for logs and bolts are derived from the demand for manufactured products. Log and bolt demand equations in the model were statistically estimated. For each time period, the model determines the delivered log and bolt prices which equate the quantities of logs and bolts supplied to the quantities demanded. The solution technique is iterative. The quantities demanded and supplied of logs and bolts are determined for the given delivered prices. If quantities supplied do not equal the quantities demanded, then delivered prices are adjusted, and the quantities are recalculated. Primary product supplies in southwest Virginia are price elastic because of extensive hardwood resources and relatively constant recovery costs. Expansions in primary product demands expected over the next 15 years should have little direct impact on delivered prices. Delivered prices, however, will be sensitive to production costs. These costs will rise if factor input prices, such as fuel prices, wage rates, or machinery costs, increase. / Ph. D.