Improving Information for Social Policy Decisions -- The Uses of Microsimulation Modeling Volume I, Review and Recommendations (1991) / Chapter Skim
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The kinds of formal models that are used for policy analysis, defined as the production of estimates of the budgetary and population impacts of proposed program changes, vary 1
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. ASPE, ENS, and other agencies have used microsimulation models for many years to estimate the impacts of proposed changes in social welfare programs, including programs for income support for the poor, retirement income support, and provision of health care, as well as in tax laws.
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program helped kill this provision in the debate over the Family Support Act of 1988. The estimates produced by the tax policy microsimulation model operated by the Joint Committee on Taxation and the Office of Tax Analysis in the U.S.
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Recognizing the difficulty of changing the behavior of decision makers, we urge the heads of policy analysis agencies to take the lead in working to ensure that information on uncertainty becomes available as a matter of course for the estimates their agencies produce. Agency heads should set and enforce standards that validation be part of the policy analysis work of their staffs; allocate staff and budget resources to the validation task; support efforts by their staffs to educate the staffs of decision makers about the need for information on the
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The effort that we believe is required for systematic, ongoing validation of policy analysis estimates requires attention to ancillary activities as well. Specifically, policy analysis agencies need to allocate sufficient resources for complete and understandable documentation of policy analysis tools and of the methodology and procedures employed in major policy analyses.
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Significant cutbacks in budgets and staff resources for the major federal statistical agencies (amounting to a 13 percent overall budget reduction in real dollar terms from 1980 to 1988) , although encouraging the demise of some outmoded programs, in most cases had debilitating effects.
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A major factor has been the increased emphasis placed by statistical agencies on restricting date access in order to gourd against possible breeches of confidentiality. For example, the Census Bureau no longer prepares exact-match files for public release from household surveys such as the March Current Population Survey (CPS)
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(For example, the Census Bureau adjusts household surveys for nonresponse by people in the sample but does not perform other adjustments, such as correcting income amounts for misreporting, that would involve the use of outside sources such as administrative records.) Currently, policy analysis agencies and other end users must perform many additional adjustments to survey data to make them suitable for modeling and analysis.
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A typical response in the past to the problems posed by the complexity of microsimulation modeling was to pare back model capabilities or focus new development on the accounting functions that mimic program rules and to leave aside other, more difficult aspects, such as modeling behavioral response to program changes. However, these kinds of design choices limit the usefulness of the models for the policy debate.
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We also note that the underlying base of research knowledge that is needed to support modeling behavioral responses to government program changes and in other ways expand the capabilities of current models has important limitations. Finally, we are troubled by some aspects of the current structure of the microsimulation modeling community is, the interrelationships among the agencies that use the models, the statistical agencies that produce needed input data, the contractors that generally operate the models, and the academic research community.
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In particular, future models need to be designed to facilitate the conduct of validation studies that involve altering model components and data inputs. In considering strategic directions for future microsimulation model development, we identified three components that are problematic or not well developed in many current models: techniques to project (or age)
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Adding to our earlier recommendation that the Census Bureau and other federal statistical agencies play a more active role in preparing usable databases for modeling and policy research uses, we recommend that policy analysis agencies undertake cooperative activities and encourage relevant academic research to further microsimulation model development. Given the particularly fragmented nature of health care
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In turn, a larger role for microsimulation modeling as a basic research tool, which we encourage agencies to help foster and seek to benefit from, should make possible advances in the usefulness of microsimulation techniques for policy research and analysis and thereby contribute to better information for public policy decision making. RECOMMENDATIONS FOR IMPROVING POLICY ANALYSIS Data 3-1 We recommend that the federal government increase its investment in the production of relevant, high-quality, statistical data for social welfare policy analysis and other purposes.
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3-9 We recommend that the heads of policy analysis agencies assume responsibility for ensuring, to the extent feasible, that their staffs regularly prepare information about the level and sources of uncertainty in their worm Agency heads should also support efforts of their staffs to accustom decision makers to request and use such information in the policy process. 3-10 We recommend that policy analysis agencies earmark a portion of the funds for all major analytical efforts for evaluation of the quality of the results.
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The results of each evaluation should be brought together in a quality profile that is published for users and updated periodically as further evaluations are conducted and new findings obtained. 5-3 We recommend that the Census Bureau, in conjunction with policy analysis agencies, immediately evaluate alternative options for short-term improvements to the data used for microsimulation modeling, and policy analysis generally, of income support and related social welfare programs.
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Steps necessary to achieve this goal include evaluating income reporting errors in the SIPP and March CPS, on the basis of administrative records and other information sources, and using data from multiple sources to develop improved estimates. Model Design and Development 6-1 We recommend that policy analysis agencies set standards for the design of future microsimulation models that include: · setting clear goals and priorities for the model; · using self-contained modules that can be readily added to (or deleted from)
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6-4 We recommend that policy analysis agencies require that future static microsimulation models build in an aging capability in a manner that facilitates evaluation and use of alternative aging assumptions and procedures. 6-5 We recommend that policy analysis agencies devote resources to studies of the relationship between behavioral research and microsimulation modeling, including studies of ways in which research and modeling can complement one another, as well as ways in which the two are alternative modes of deriving answers to policy questions.
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However, except perhaps for health care issues, we do not recommend investment at this time in building second-round effects capabilities into microsimulation models. Computing Technology 7-1 We recommend that policy analysis agencies invest resources in developing prototypes of static and dynamic microsimulation models that use new computer technologies to provide enhanced capabilities, such as the ability for a wider group of analysts to apply the models; conduct timely and cost-effective validation studies, including variance estimation and sensitivity analyses; and alter major components, such as the aging routines, without requiring programmer intervention.
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The kinds of documentation that agencies should require to be developed for analysts and programmers who use, or expect to use, the models include general informational materials; tutorials; and detailed reference documents for model components that describe their theoretical basis, assumptions, operation, inputs, and outputs. 1~2 In order to facilitate model validation, we recommend that policy analysis agencies require archiving of microsimulation model databases on a regular
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The archived materials should include the model itself, the documentation of the model, the database and other inputs, the analyst's specifications, and the outputs. Structure of the Microsimulation Modeling Community 11-1 We recommend that executive and legislative branch policy analysis agencies expand their communications and undertake cooperative efforts to improve the quality of microsimulation models and associated databases through such means as cosponsoring research on model validation methods and other initiatives.
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