Abstract
Although quantitative system models are only one of many tools of a policy analyst, they are an important tool. For the policy analyst, the purpose of building and using models is to estimate things that cannot be observed or measured directly. The prime example is impact assessment—estimating the outcomes of a policy that a decisionmaker may consider adopting. Other uses are diagnosis (estimating what factors have the greatest leverage to change a specified outcome or what is the primary source of a given outcome) and forecasting (estimating how a variable is likely to evolve in the future, usually assuming “present trends”). They also may be used as learning tools (to gain an understanding of how the system works, or may work in the future).
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Notes
- 1.
Merriam-Webster’s Collegiate Dictionary, 10th edition, 1998, includes the following among its many definitions of model: A description or analogy used to help visualize something (as an atom) that cannot be directly observed.
- 2.
Of course, engineering design models are built for similar purposes.
- 3.
Note that we label the inputs to a model diagram as variables instead of factors to emphasize the distinction between a model diagram and a system diagram.
- 4.
This can be a point of contention between the policy analyst and the academic researcher. The purpose of an academic study, after all, is to find the truth of the matter. Extrapolation is mere speculation, and is generally frowned upon. The purpose of a policy study is to decide what to do next, and the analyst does not have the luxury of waiting until the truth is known with reasonable certainty. Extrapolation is necessary.
- 5.
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Walker, W.E., van Daalen, C.E. (2013). System Models for Policy Analysis. In: Thissen, W., Walker, W. (eds) Public Policy Analysis. International Series in Operations Research & Management Science, vol 179. Springer, Boston, MA. https://doi.org/10.1007/978-1-4614-4602-6_7
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