Rising suppression cost and severity of wildfires in the US has prompted debate over federal wildfire management policy. The empirical economic literature on wildfire has sought to identify the factors that contribute to wildfire growth and cost without directly modeling the role of resource allocation over the course of the fire. Without a model of suppression resource allocation, it is difficult to understand how policy will impact wildfire outcomes. We fill this gap in the literature by estimating an econometric model of suppression resource allocation, wildfire expenditures, growth, and home damage using a dynamic panel dataset on over 500 wildfires in the Western U.S. Our econometric model is grounded in a theory of resource allocation that shows how individual fire managers communicate their need for resources to a regional command unit through the resource's shadow price. This model allows us to parse the complex incentives of wildfire managers, and disentangle direct from indirect impacts of threatened assets, environmental conditions, and resource scarcity on wildfire expenditure, growth, and damage. Among other results, we find that the use of aircraft increases daily wildfire expenditures by 35% while highly trained ground crews mitigate the daily damage to threatened homes.