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This study describes the applications and extensions of an existing random-utility-based multiregional input-output (RUBMRIO) model, applied to Texas trade patterns. The new model simulates labor and commodity trade patterns among zones (counties), as motivated by foreign and domestic export demands. The trade impedance, represented by travel cost on a two-mode transportation network, can be iteratively updated to capture congestion impacts on the highway network. To achieve this, the extended model estimates truck, work and shopping trips, all of which are predicted to remain largely intercounty. Modeling results suggest that Chemical and Allied Products, Mining, Manufacturing and Agriculture sectors generate most of the State’s truck trips, consistent with information from the Vehicle Inventory and Use Survey. The new version can limit production levels and housing–and thus zonal development–according to local land availability. Incorporation of domestic demands, in addition to foreign demands for Texas goods, resulted in relatively close approximation of production found by the US Commodity Flow Survey. Simulation of different demand and production-technology scenarios highlighted the importance of Agriculture, Machinery and Equipment, and Fabricated Metal Products sectors for the State’s economy, as well as the State’s relative dependence on demands by New England and Middle Atlantic States. Improved production technologies reduce the need for intermediate trading but have a larger positive impact if applied in appropriate sectors and counties.