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Policy Advice Derived from Simulation Models

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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.

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File URL: http://jasss.soc.surrey.ac.uk/12/4/2/2.pdf
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Bibliographic Info

Article 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 ()
Pages: 2

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Handle: RePEc:jas:jasssj:2009-72-1

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Keywords: Policy Advice; Simulation Models; Uncertainty; Methodology;

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  1. Schwerin, Joachim & Werker, Claudia, 2003. "Learning innovation policy based on historical experience," Structural Change and Economic Dynamics, Elsevier, vol. 14(4), pages 385-404, December.
  2. Thomas Brenner & André Mühlig, 2007. "Factors and Mechanisms Causing the Emergence of Local Industrial Clusters - A Meta-Study of 159 Cases," Papers on Economics and Evolution 2007-23, Max Planck Institute of Economics, Evolutionary Economics Group.
  3. Thomas Brenner, 2001. "Simulating the Evolution of Localised Industrial Clusters - an Identification of the Basic Mechanisms," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 4(3), pages 4.
  4. Falk, Rahel, 2007. "Measuring the effects of public support schemes on firms' innovation activities: Survey evidence from Austria," Research Policy, Elsevier, vol. 36(5), pages 665-679, June.
  5. Andrew Brown & Gary Slater & David A. Spencer, 2002. "Driven to abstraction? Critical realism and the search for the 'inner connection' of social phenomena," Cambridge Journal of Economics, Oxford University Press, vol. 26(6), pages 773-788, November.
  6. Pavitt, Keith, 1984. "Sectoral patterns of technical change: Towards a taxonomy and a theory," Research Policy, Elsevier, vol. 13(6), pages 343-373, December.
  7. Thomas Brenner & Claudia Werker, 2007. "A Taxonomy of Inference in Simulation Models," Computational Economics, Society for Computational Economics, vol. 30(3), pages 227-244, October.
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