Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/204779
Authors: 
Thompson, Erica L.
Smith, Leonard A.
Year of Publication: 
2019
Citation: 
[Journal:] Economics: The Open-Access, Open-Assessment E-Journal [ISSN:] 1864-6042 [Volume:] 13 [Year:] 2019 [Issue:] 2019-40 [Pages:] 1-17
Abstract: 
Both mathematical modelling and simulation methods in general have contributed greatly to understanding, insight and forecasting in many fields including macroeconomics. Nevertheless, we must remain careful to distinguish model-land and model-land quantities from the real world. Decisions taken in the real world are more robust when informed by estimation of real-world quantities with transparent uncertainty quantification, than when based on 'optimal' model-land quantities obtained from simulations of imperfect models optimized, perhaps optimal, in model-land. The authors present a short guide to some of the temptations and pitfalls of model-land, some directions towards the exit, and two ways to escape. Their aim is to improve decision support by providing relevant, adequate information regarding the real-world target of interest, or making it clear why today's model models are not up to that task for the particular target of interest.
Subjects: 
uncertainty
Modelling and simulation
decision-making
model evaluation
uncertainty
structural model error
dynamical systems
radical
JEL: 
C52
C53
C6
D8
D81
Persistent Identifier of the first edition: 
Creative Commons License: 
https://creativecommons.org/licenses/by/4.0/
Document Type: 
Article

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