This article presents an applied framework for selective precision in the insertion of superior data into hybrid regional models where regional purchasing coefficients are absent or unattainable. Due to the lack of regional-level data, crude top-down methods are the most frequently applied methods in Canadian regional studies. However, they may lead to inaccurate policy analysis where significant variation exists between the technical coefficients and trade flows of two economies. This article discusses an alternative, hybrid approach that involves the collection of region-specific information and therefore promises greater accuracy and validity of impact analysis. The robustness of the hybrid model is tested against the results derived from a synthetically regionalized model. The Foothills Model Forest (FMF) in west-central Alberta is used as a case study for the development of a sub-provincial economic database for the purpose of regional impact modeling.