Policy Advice Derived from Simulation Models

Thomas Brenner () and Claudia Werker ()
Additional contact information
Claudia Werker: http://www.tbm.tudelft.nl/live/pagina.jsp?id=aec3fc3c-4517-4251-9037-1a14f296e3c5&lang=nl

Journal of Artificial Societies and Social Simulation, 2009, vol. 12, issue 4, 2

Abstract: When 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.

Keywords: Policy Advice; Simulation Models; Uncertainty; Methodology (search for similar items in EconPapers)
Date: 2009-10-31
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
https://www.jasss.org/12/4/2/2.pdf (application/pdf)

Related works:
Working Paper: Policy Advice Derived From Simulation Models (2009)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:jas:jasssj:2009-72-1

Access Statistics for this article

More articles in Journal of Artificial Societies and Social Simulation from Journal of Artificial Societies and Social Simulation
Bibliographic data for series maintained by Francesco Renzini ().