This study demonstrates the use of an Excel program "Routechaser" to assess the effects of tract location, vehicle operating parameters, operating costs and other physical and economic inputs on the costs of transporting wood products from roadside to mill. The application chosen, a comparison of the effects of trucking costs from four tracts in Oktibbeha County, Mississippi, to eight markets, demonstrates that for forestry, as for any other real estate, value is a function of location. This is especially true if forest management is directed toward lower valued commodity products. Trucking costs were most restrictive on pulpwood, essentially eliminating many markets for several of the tracts. Trucking costs eliminated one market for all quadrants, another market for three, and three markets for one quadrant each.

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In recent years, the capital investment amounts flowing into the forest products industry in the southeastern United States have been unequal from state to state. Reasons for this have been informally hypothesized, but the topic has not been researched in depth. An economic model was tested that will aid relevant stakeholders in addressing this problem. The model utilizes a combination of county-level and state-level data related to lumber manufacturing and a linear programming solver to produce estimates of variable costs for a mill built in any Southeastern county. The variable costs considered by the program include raw materials, labor, electricity, and transportation costs (which are paid by the customer). Future versions of the model will consider non-financial metrics such as timber supply, socioeconomic statistics, and competition for timber-consuming facilities. This model could be exceptionally useful to those involved in industry recruitment efforts, as it provides them with an objective method for evaluating counties in both their state and competing states.

Effects of changes on industry sector data for the Mississippi logging industry were examined to determine importance to and economic impact in that state's economy. Quantification, evaluation, and improvements upon current methodology of data and data collection for use in the Impact Analysis for Planning (IMPLAN) software model to more accurately reflect and support IMPLAN inputs and outputs were also determined. Economic impact estimates derived from model default data were compared with estimates derived from survey-based expenditure data collected within the state. The top 20 output sectors in the state economy resulting from logging expenditures were determined. In turn, new data were acquired to replace 4 of the top 20 sectors and new economic impact estimates derived. Economic impact assessment results on the model default data showed total economic impacts of $2.309 billion and $2.489 billion in industry output in 2006 and 2009 dollars, respectively. Total economic impacts generated using survey-based data from a sample of 33 loggers were $129.310 million and $131.747 million in 2006 and 2009 dollars, respectively. Total economic impacts generated by replacing 4 of the top 20 sectors from 33 loggers were $109.979 million in 2009 dollars. While this study was limited by a small sample size in regard to making statewide estimates, results indicated that limitations within the IMPLAN model further manifest themselves when implementing economic impact assessments. Rather than just relying on the default model data, more localized data should be collected when doing studies of this type.

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