Scope for pair-wise factor substitution strategies in US rural transit operations when factor prices change

Rural transit providers face unique challenges beyond those of their urban counterparts, including worse road conditions, access to trained labor, tighter budget constraints, and higher miles per rider. To date, transportation economics and policy research is scarce for this essential service in rural geographies due to data paucity. Employing the Generalized Translog Cost-minimization model, the core innovation in this paper is presenting the first illustration of the cost-minimization strategies available to transit providers when faced with the constraints of sparsely populated geographic settings. Using a rich dataset of 42 U.S. rural transportation providers across 17 years, we estimate the operational factor (fuel, labor, materials and maintenance) substitution capabilities for the typical provider. The estimated production factor input elasticities of substitution (own, cross-price, Morishima, and Shadow) differ substantially across price changes for the three input factors. Following, this study sheds new operational cost-minimization policy insights for rural public transportation operations.