Both in incipient and later phases of developing a model, unexpected behavior is frequently encountered—that is, behavior which is at odds with the initial expectations of the model builder or client. The appearance of such surprise behavior immediately raises two possibilities: either the behavior is implausible, and the model therefore must be revised; or the behavior withstands scrutiny and reveals previously unappreciated aspects of the system. In either instance, the process of diagnosing and interpreting surprise behavior gives a powerful basis for model for model evolution and generating policy insights. But frequently, it is quite difficult in practice to discern whether the incidence of surprise model behavior reveals errors or suggests insights. The paper is designed to contribute to the literature on model formulation, testing, and policy analysis, by discussing the criteria for diagnosing surprise model behavior. Several case examples are presented in which appropriate resolution of surprise model behavior led to significant model improvements and/or behavior insights. Moreover, operational guidelines are presented to increase the likelihood of uncovering and successfully treating surprise behavior.

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Date created

• 1981

Type

• Document

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• Processing documentation available at: https://wiki.albany.edu/display/SCA/Processing+Ingested+Digital+Files

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• Creative Commons BY-NC-ND Attribution-NonCommercial-NoDerivs 4.0 International

  
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ITEM CONTEXT

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e8eac154b3129692f26c222dbc2c9466

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Part of

4a97153f59047c298f3bcd6b15c284f5

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23d738ba88f8333bc39725f9cb5bd0b8

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Collection

System Dynamic Society Records

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Collecting area

• This collection is part of the University Archives