Improving Information for Social Policy Decisions -- The Uses of Microsimulation Modeling Volume I, Review and Recommendations (1991) / Chapter Skim
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7 Computing Technology and Microsimulation
7 Computing Technology and Microsimulation
Pages 182-193
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From page 182... ...
require significant computing power because they process large microlevel databases, mimic the features of complex government programs, and apply probabilistic techniques to simulate the behavior of individual decision units. The historical development of microsimulation models as a policy analysis tool is closely intertwined with the expansion of computing technology over the past 30 years.
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From page 183... ...
We recommend a strategy that we hope will minimize the risks and maximize the payoffs from investment by policy analysis agencies in new computing platforms for microsimulation modeling. THE EVOLUTION OF MICROSIMULATION COMPUTING PLATFORMS DYNASIM2 In the late 1960s, Guy Orcutt and his colleagues obtained funding to begin work on a full-scale dynamic microsimulation model at the Urban Institute, building on his pioneering work to develop dynamic microsimulation techniques for research and policy analysis in the late 1950s.~ The first version of DYNASIM, completed in 1975, represented an ambitious effort to simulate all major demographic and economic life events, including birth, death, marriage, remarriage, unemployment, and migration.
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The Urban Institute attempted to build a more useful system by modifying RIM, but had to abandon the effort Instead, the Institute built an entirely new system called TRIM.3 TRIM was programmed in FORTRAN, with some use of assembly language, for running on an IBM mainframe computer. The software system was designed to enable TRIM to · run with large microlevel databases that could support reporting simulation results for very disaggregated groups; simulate a wide variety of tax and income support programs through a modular stn~cture; simulate programs that use different filing units in the same model run; model alternative versions of a single program or different program interactions in a single model non; support flexible specification of program characteristics to be simulated; Me discussion in this section draws heavily on Cotton and Sadowsky (in Volume 1I)
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From page 185... ...
The new TRIM2 software, also written in FORTRAN for an IBM mainframe computer, then takes over to complete the processing of the input data and to run program simulations.4 NEW DEVELOPMENTS IN COMPUTING TECHNOLOGY Both DYNASIM2 and TRIM2 as well as other major microsimulation models that are widely used today such as MATH are optimized for batch processing with mainframe technology (or, as for DYNASIM2, a large minicomputer)
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From page 186... ...
, while the Urban Institute has developed a PC-based benefit-calculator model of the AFDC program for use by ASPE. Statistics Canada several years ago instituted a major microsimulation modeling effort that led to the Social Policy Simulation Database/Model (SPSD/M - a static model of Canadian household tax and transfer programs, written in C for an MS-DOS microcomputer, that is available to the general public (Statistics Canada, 1989~.
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From page 187... ...
offer important benefits to the policy process, we fear that they will not be competitive with special-purpose ad hoc models for many policy needs so long as they remain relatively inaccessible to the analyst. For the same reason, we fear that microsimulation models will remain less well utilized and studied by academic researchers and, hence, Hat there will be less useful feedback for the improvement of policy models (see Chapter 11)
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with minimal assistance from Statistics Canada. TRIM2, in contrast, is currently used almost exclusively by the technical programming staff at the Urban Institute, and no outside researchers are attempting to enhance the model by modifying the internal FORTRAN source code.
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The history of electronic computing has been characterized by hardware developments leading software developments. However, the workstation software environment in 1995 is likely to feature several elements of importance to microsimulation modeling activities.
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Chief among these benefits is the ability for users, as well as programmers, to interact directly with models and data in a manner that encourages experimentation and use. Arguments against moving to microcomputer technology because of the limited storage capacity of microcomputers (both immediate access and secondary storages and slow processing times are rapidly losing relevance with the pace of change in the microcomputer world.
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From page 191... ...
To achieve these goals, we believe, requires soon leaving behind the current computing environment for microsimulation modeling and moving toward new technology. FUTURE DIRECTIONS FOR COMPUTING IN MICROSIMULATION We are excited about the prospect that powerful new hardware and software technology will make possible a new generation of microsimulation models that support increased modeling capabilities and flexibility for analysts and Hereby attract a new, broader user community.
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From page 192... ...
We recommend that policy analysis agencies invest resources in developing prototypes of static and dynamic microsimulation models that use new computer technologies to 9We understand that ASPE recently investigated the ability of TRIM2 to run in a personal computer version of FORTRAN and was pleased with the results. However, we still believe that what is called for is not simply moving a model such as TRIM2 in its entirety to a microcomputer but, rather, designing a new version of TRIM2 or component modules to take maximum advantage of hardware and software features for increasing flexibility and accessibility to users.
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From page 193... ...
We recommend that policy analysis agencies, after experience with prototypes and reviews of developments in computer hardware and software technologies, make plans to invest in a new generation of microsimulation models that facilitate such design criteria as user accessibility and adequate documentation and evaluation of model components, as well as computational efficiency. ASPE participated in a recent conference of this group.
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