Improving Information for Social Policy Decisions -- The Uses of Microsimulation Modeling: Volume II, Technical Papers (1991)
Chapter: Layered Structure
Here the term microsimulation model describes some universe of elements solved under a variety of conditions by using computer-based microsimulation techniques. In the context of social and demographic analysis, the microanalytic units of such models are individuals and groupings of individuals, such as families or households.
This chapter addresses the impact that computing technology has had and will have, in the medium term, on the conceptualization, design, implementation, and use of microanalytic simulation modeling. Two areas are studied in detail: (1) the current state of computer systems that support static microsimulation models, with specific reference to the TRIM2 (Lewis and Michel, 1990) and SPSD/M (Statistics Canada, 1989a) models and (2) advances in computing technology anticipated in the medium term (1990–1995) and their implications for additional investment in microanalytic simulation models, with special attention given to static models and the computer systems that support them.
This chapter also provides an introduction to microanalytic simulation models in terms of their characteristics and the history of their development. The TRIM2 and SPSD/M models, their histories, and model support systems are described and their characteristics are compared. An assessment is made of current computer hardware trends, with emphasis on desktop computing environments that are likely to be available to support such modeling activity in the medium term. Factors affecting the demand for and availability of microanalytic models also are assessed, with special emphasis on shifts in the production function through software advances and the ability to exploit future desktop computing environment characteristics. Finally, an overall assessment is presented of alternatives for investing in the evolution of TRIM2, as well as recommendations for investment planning for future microanalytic simulation model developments in general.
Because the focus of this chapter is on examining and comparing a U.S. microsimulation model and a Canadian one, much of the development of microanalytic simulation models outside North America is not covered here. Readers are referred to Orcutt, Merz, and Quinke (1986) for information on the state of activity in Europe.
Characteristics of Microanalytic Simulation Models
Layered Structure
It is useful to think of microanalytic simulation models as being composed of
|
|
simulation exercise, executing it, and analyzing its results. Although the actual computer-based simulation portion has decreased substantially in cost in the past 30 years, the cost and turnaround time of this step are central in that they determine the feasibility and scope of studies that can be attempted. Overall costs of microsimulation activities are increasingly dominated by the cost of research, programming, support, and operations related to microsimulation, not by computing costs. |
a number of related but distinct components that to some extent can be organized into layers. The component approach is useful in separating underlying knowledge, procedural modeling, and computer-based implementation aspects of a model.2 Our suggested components and their structure are as follows:
-
Knowledge regarding the world and how it works, from either a theoretical or an empirical basis, having two distinct parts:
-
the substantive social science and related knowledge in demography, economics, and other disciplines underlying the content of the socioeconomic model, and
-
a representation of the population of microanalytic units that will be used as a basis for simulation exercises.
-
-
The process of defining, organizing, and shaping this knowledge into a procedural and computer-executable form, including:
-
defining procedures, or operating characteristics,3 for each component of the model, that describe how the knowledge is to be applied to microanalytic simulation units to derive their behavior under alternative assumptions;4
-
coding each operating characteristic into a computer-executable module that applies that procedure to a specific micropopulation unit used as the basis for the simulation exercise; and
-
preparing the population microdata for simulation, including precise definition through a data dictionary (or equivalent) and possibly including physical medium transformation, record and file reformatting, subset extraction, value remapping, demographic and economic aging of the data, and similar operations.
-
-
The application computer system that provides a framework for integrating the operating characteristics into a single module that will execute complete simulation exercises, including:
-
the interface(s) seen and used for model construction and execution;
-
the supervisor program that invokes and sequences the collection of operating characteristics;
-
