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Suggested Citation:"CONCLUSIONS." National Research Council. 1991. Improving Information for Social Policy Decisions -- The Uses of Microsimulation Modeling: Volume II, Technical Papers. Washington, DC: The National Academies Press. doi: 10.17226/1853.
Page 134
Suggested Citation:"CONCLUSIONS." National Research Council. 1991. Improving Information for Social Policy Decisions -- The Uses of Microsimulation Modeling: Volume II, Technical Papers. Washington, DC: The National Academies Press. doi: 10.17226/1853.
Page 135

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DYNASIM2 AND PRISM: EXAMPLES OF DYNAMIC MODELING 134 to simulate the effects of a wide range of policy options on retirement age and retirement income. Contributions to an IRA are simulated much like another pension plan, except that such contributions only started in 1975 for individuals without pension coverage and in 1982 for those with coverage. Participation and contribution rates are assigned probabilistically. PROGRAM SIMULATIONS As described briefly above, the social security routines of both DYNASIM2 and PRISM are highly parameterized, enabling the user to simulate changes in many different program features. In addition, both models contain simulations of the private retirement savings accounts, IRAs and Keoghs. Finally, both models simulate SSI eligibility and participation and federal taxes. DYNASIM2 simulates SSI benefits and federal taxes for the final simulation year, while PRISM simulates them in every year. To simulate SSI, both models create filing units, calculate aggregate filing unit income, and check the categorical eligibility criteria (age and disability). PRISM approximates an asset test by disqualifying a proportion of units defined by age, income, sex, and marital status, on a probabilistic basis. The proportion of units to be disqualified was determined by analyzing asset income information for elderly families on the March 1980 CPS. PRISM computes state-specific SSI benefits; DYNASIM2 computes region-specific benefits because the state of residence is not simulated across time. SSI participation in DYNASIM2 depends on benefit level (three categories); PRISM estimates SSI participation on the basis of marital status and benefit level. PRISM and DYNASIM2 calculate federal income taxes and social security payroll taxes. PRISM also simulates state income taxes. CONCLUSIONS Both DYNASIM2 and PRISM begin with a microdata file of individuals in households and put them through a series of demographic and economic modules that determine, for each year, whether the individual dies, marries, works, retires, or experiences some other event. In any year, this series of events gives the individual a set of characteristics that can be used to determine whether other events occur in the next year and whether the individual is eligible for government transfer programs, including social security, supplemental security income, and others. The models thus simulate the implications of policy changes, demographic changes, and economic trends. While the models share these basic features, some important differences exist, and these affect the types of questions each model can best analyze. DYNASIM2 simulates a fuller range of demographic events than does PRISM,

DYNASIM2 AND PRISM: EXAMPLES OF DYNAMIC MODELING 135 including education and migration. DYNASIM2 not only adds children to the file (born during simulations), but educates them and moves them into the labor force. As a result, a full range of demographic issues can be analyzed, including the policy implications of changing marital status patterns and teenage fertility. The full range of demographic simulations also enables the analyst to examine events over a longer time horizon and to focus on a broader range of cohorts than is possible with PRISM. In addition, DYNASIM2 includes more formal models of labor force and demographic events than does PRISM, and has been constructed so that the user can specify different models of behavior. PRISM, on the other hand, includes a model of long-term care that can address policy questions in this important area. Both dynamic models provide a great deal of flexibility. Parameters governing demographic and labor force events ma y be changed, allowing an analyst to create alternative population projections on the basis of different assumptions. For example, it is possible to change parameters specifying fertility rates, mortality rates, female labor force participation rates, and the real growth in wage rates. Similarly, alternative projections of retirement income can be made by altering the rules that guide social security and pension eligibility, accumulation, and distribution. This flexibility enables the models to project the distributional effects of a policy, a demographic change, or a labor force trend far into the future, given certain well-specified assumptions about the trend of other demographic events and labor force behavior. Building the projections from microdata allows an analyst to examine interactions between provisions of a policy or between demographic and labor force events and to obtain the distribution of effects across population subgroups. For questions about interactive effects and distributional effects, this is the best available framework. There are limits to the flexibility of these models, however. Under their current structure, policy changes do not generate either demographic or labor force behavioral responses. For example, in DYNASIM2, many events —including jobs, pension characteristics, social security benefit levels, and retirement—are simulated after the longitudinal demographic and economic histories are created. The model is structured in this way because creating longitudinal histories is very expensive on a mainframe. This split structure enables an analyst to create the longitudinal histories only once (or to create a few under different reasonable assumptions), and then have the capability to run a large number of different program simulations on that longitudinal file. However, this structure makes it impossible for policy changes to affect demographic or labor market events (except for the retirement decision, which is done in the second stage and overrides a retirement decision that may have been made when the longitudinal histories were created). This is unfortunate, since interest in the projections made by these models often arises because a policy change is being considered today that is expected to affect behavior

Improving Information for Social Policy Decisions -- The Uses of Microsimulation Modeling: Volume II, Technical Papers Get This Book
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This volume, second in the series, provides essential background material for policy analysts, researchers, statisticians, and others interested in the application of microsimulation techniques to develop estimates of the costs and population impacts of proposed changes in government policies ranging from welfare to retirement income to health care to taxes.

The material spans data inputs to models, design and computer implementation of models, validation of model outputs, and model documentation.

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