Aggregation Bias in Multi-Industry Economic Contribution Analysis: The Case of Kentucky Forest Sector

Closely related industries are often aggregated in US forest sector economic contribution analysis, yet the choice of aggregation scheme can influence results. The Impact Analysis for Planning (IMPLAN) system is the most widely applied input–output model for forest economic contribution analysis in the US. In IMPLAN, the level of industry aggregation determines which inter-industry transactions are restricted, thereby influencing the magnitude of estimated indirect and induced effects. Although IMPLAN practitioners can model individual industries to avoid aggregation bias, they must still decide whether to analyze forest industries as a single group, as traditional subsectors, or individually. This decision can alter estimated economic contributions and the conclusions drawn from them. This study evaluates how three aggregation approaches affect economic contribution estimates for the Kentucky forest sector: analyzing all forest industries as a single group, as six traditional subsectors, and individually. Direct contributions were identical across all approaches. However, indirect and induced effects differed significantly between the single-group approach and both the subsector and individual-industry approaches. These differences indicate that aggregation is not simply a reporting choice but has measurable, systematic effects on contribution estimates. Clear specification and justification of aggregation choices are therefore essential in forest economic contribution analysis.