Policy Advice Derived from Simulation Models
AbstractWhen advising policy we face the fundamental problem that economic processes are uncertain. Consequently, policy can err. In this paper we show how the use of simulation models can reduce policy errors by inferring empirically reliable and meaningful statements about economic processes. We suggest that policy is best based on so-called abductive simulation models, which help to better understand how policy measures can influence economic processes. We show that abductive simulation models use a combination of theoretical and empirical analysis based on different data sets. By way of example we show what policy can learn with the help of abductive simulation models, namely how policy measures can influence the emergence of a regional cluster.
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Bibliographic InfoArticle provided by Journal of Artificial Societies and Social Simulation in its journal Journal of Artificial Societies and Social Simulation.
Volume (Year): 12 (2009)
Issue (Month): 4 ()
Contact details of provider:
Policy Advice; Simulation Models; Uncertainty; Methodology;
Other versions of this item:
- C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
- B52 - Schools of Economic Thought and Methodology - - Current Heterodox Approaches - - - Institutional; Evolutionary
- H89 - Public Economics - - Miscellaneous Issues - - - Other
- B41 - Schools of Economic Thought and Methodology - - Economic Methodology - - - Economic Methodology
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