Cost estimates for reducing energy-related CO2 emissions vary with modeling assumptions and methods. Much debate has centered on the tendency for top-down models to suggest high costs and for bottom-up models to suggest low costs. This study incorporates behavioral parameters, derived from end-use equipment acquisition surveys, in a bottom-up simulation model of the residential sector in order to probe the basis for differing cost estimates and to test various policy suggestions. Simulating the effect of carbon tares on a business as usual forecast, the results suggest that a CO2 tar will lead to significant net costs of adjustment if the factors leading to higher private discount rates reflect in part real costs and risk. The results also suggest that it may be in society＇s interest to pursue fuel switching policies with Equal or greater vigour than energy efficiency improvements for the goal of reducing CO2 emissions in the residential sector. As further research helps to distinguish the significance of these perceived costs and risks, and to refine projections of technology costs, the inputs to the model can be adjusted in order to refine the estimates for policy makers of CO2 reduction costs and of appropriate strategies for achieving reduction goals.