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VARIANCE ESTIMATION OF MICROSIMULATION MODELS THROUGH SAMPLE REUSE 237 6 Variance Estimation of Microsimulation Models Through Sample Reuse Michael L.Cohen Microsimulation models play an important role in informing policy makers by providing timely information about the likely changes in allocations resulting from modifications to family assistance programs, tax regulations, etc., and also by identifying the characteristics of the people who are affected and in what ways they will be affected by those modifications. Currently, the results of microsimulation models are presented without any estimate of variability, aside from the variability that results from use of different policy scenarios. This lack of information about the variability in the models limits the utility of the output. For example, it is reasonable to expect a policy maker to act differently if informed that a change in program regulations for Aid to Families with Dependent Children (AFDC) would cost between $1.1 and $1.2 billion than if informed that the change would cost between â$2 and +$4 billion. The likely immediate result of the second range would be either the search for alternative estimates with less variability, if they were available, or the increased importance of policy objectives other than total cost. A possible long-range result might be the allocation of more resources to reduce the variability of future cost estimates. The crucial point is that an estimate without an accompanying assessment of its precision is difficult to use when it is one of several ingredients in a decision. The lack of a variance estimate for microsimulation models is not surprising Michael L.Cohen is assistant professor in the School of Public Affairs at the University of Maryland; he served as a consultant to the Panel to Evaluate Microsimulation Models for Social Welfare Programs.