The need for forecasting the direct and indirect effects of land use and transport policies on society, the environment, and the local economy has led to the development of integrated land use and transport (LUTI) models. The land use and transport policy evaluation is based on point estimators of economic sustainability indicators, usually computed at an aggregate level (e.g., social welfare) despite the fact that the models and simulation are based on the individual. A methodology based on the strength of microsimulation in three dimensions (space, time, and agents) is presented. By multiple simulation runs of the LUTI model UrbanSim, the distributions of inequality and accessibility indicators in space and time were generated, and their variance was measured. The methodology was first applied in a base case scenario (in which the then current trend existed) of the Limmattal region including Zurich, Switzerland, and then on a public transport investment scenario. The results of the two scenarios were then compared on the basis of actual distributions rather than the mean point values of the indicators. The proposed methodology differed from the point-based policy evaluation frameworks in terms of details and insightfulness that could better support the process of informed decision making.