Policy Advice Derived From Simulation Models
When advising policy we face the fundamental problem that economic processes are connected with uncertainty and thus policy can err. In this paper we show how the use of simulation models can reduce policy errors. 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. This helps inferring empirically reliable and meaningful statements about how policy measures influence economic processes. By way of example we show how research subsidies by the government influence the likelihood that a regional cluster emerges.
|Date of creation:||01 Jan 2009|
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- 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, Philipps University Marburg, Department of Geography.
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- 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.
- 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.
- 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.
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