Policy Advice Derived From Simulation Models

Brenner, Thomas and Werker, Claudia (2009): Policy Advice Derived From Simulation Models.

Abstract

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.

• Item Type: MPRA Paper
• Language: English
• Keywords: Policy Advice, Simulation Models, Uncertainty, Methodology
• Subjects: C - Mathematical and Quantitative Methods > C6 - Mathematical Methods ; Programming Models ; Mathematical and Simulation Modeling > C63 - Computational Techniques ; Simulation Modeling; B - History of Economic Thought, Methodology, and Heterodox Approaches > B5 - Current Heterodox Approaches > B52 - Institutional ; Evolutionary; H - Public Economics > H8 - Miscellaneous Issues > H89 - Other; B - History of Economic Thought, Methodology, and Heterodox Approaches > B4 - Economic Methodology > B41 - Economic Methodology

References

Brenner, T. (2001). Simulating the Evolution of Localised Industrial Clusters -An Identification of the Basic Mechanisms, Journal of Artificial Societies and Social Simulation, 4 (3), 4.

Brenner, T. (2003). Policy Measures to Create Localised Industrial Clusters, in T. Brenner and D. Fornahl (eds.): Cooperation, Networks, and Institutions on Regional Innovation Systems, Cheltenham: Edward Elgar, 325-349.

Brenner, T. (2004). Local Industrial Clusters: Existence, Emergence, and Evolution. London: Routledge.

Brenner, T. and A. Mühlig (2007). Factors and Mechanisms Causing the Emergence of Local Industrial Clusters – A Meta-Study of 159 Cases, mimeo, Max Planck Institute of Economics, Jena.

Brenner, T. and C. Werker (2007). A Taxonomy of Inference in Simulation Models, in: Journal of Computational Economics, forthcoming.

Brown, A., Slater, G. and Spencer, D.A. (2002). Driven to abstraction? Critical realism and the search for the ‘inner connection’ of social phenomena. Cambridge Journal of Economics, 26, 773-788-

Cowan, R. and Foray, D. (2002). Evolutionary economics and the counterfactual threat: on the nature and role of counterfactual history as an empirical tool in economics. Journal of Evolutionary Economics, 12, 5, 539-562.

Downward, P.J., Finch, H. and Ramsay, J. (2002). Critical realism, empirical methods and inference: a critical discussion. Cambridge Journal of Economics, 26, 481-500.

Falk, R. (2007). Measuring the Effects of Public Support Schemes on Firms' Innovation Activities: Survey Evidence from Austria. Research Policy, 36, 665-679.

Lawson, T. (1997). Economics and Reality. London, New York: Routledge.

Machlup, F. (1978). Methodology of Economics and other Social Sciences. New York, San Francisco, London: Academic Press.

Malerba, F. (2004). Sectoral Systems of Innovation, Cambridge: Cambridge University Press.

Metcalfe, J.S. (1995). The Economic Foundations of Technology Policy: Equilibrium and Evolutionary Perspectives, in: Stoneman, P. (ed.) Handbook of the economics of innovation and technological change, Oxford, Cambridge MA (Blackwell), 409-512

Nielsen, P. (2002). Reflections on critical realism in political economy, in: Cambridge Journal of Economics, 26, 727-738.

Pavitt, K. (1984) Sectoral Patterns of Technical Change: Towards a Taxonomy and a Theory. Research Policy, 13, 343-373.

Peirce, C.S. (1867/1965). Collected papers of Charles Sanders Peirce. Edited by Hartshorne C and P Weiss, 1-6, Cambridge (MA) US: Harvard University Press.

Pinkstone, B. (1999). Underlabouring Postkeynesian Economics, in: The Journal of Postkeynesian Economics, 22 (1), 45-48.

Reiss, J. (2004) Roundtable: Tony Lawson’s Reorienting Economics. Journal of Economic Methodology, 11, 3, 321-327.

Schwerin J. and C. Werker (2003). Learning Innovation Policy Based on Historical Experience, in: Structural Change and Economic Dynamics, 14 (4), 385-404.

Sternberg, R. and Litzenberger, T. (2004). Regional Clusters in Germany: Their