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Future Computing Environments for Microsimulation Modeling
Paul Cotton and George Sadowsky
INTRODUCTION
Microanalytic simulation models have been used worldwide in a variety of contexts for the past 25 years to assess the impact of alternative economic and social programs. In particular, the analysis of tax and transfer systems applied to families and individuals now depends critically on the construction and evolution of such models, and their use is routine and expected in public agencies and research organizations that address these issues.
Microanalytic simulation models of nontrivial size or complexity have relied for solution on the use of digital computers. The ability to use these models in a practical manner has depended on rapid technical progress in the computing industry. This progress has allowed the complexity of microanalytic models to increase and the costs associated with a specific simulation experiment to decrease substantially over time.1
Paul Cotton is senior technical advisor at Fulcrum Technologies, Inc., in Ottawa, Canada; George Sadowsky is director of the Academic Computing Facility at New York University. The authors gratefully acknowledge the assistance of a number of colleagues in contributing to the improvement of the first draft of the chapter.
The authors note that most of the analysis for this chapter was done during 1989. Since then, some of the microsimulation models we describe have been revised, and some of the computing developments that we forecast have begun to happen.
