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Agent-based computational models– a formal heuristic for institutionalist pattern modelling?

Published online by Cambridge University Press:  15 June 2015

CLAUDIUS GRÄBNER
CLAUDIUS GRÄBNER*
Affiliation:
Institute for Institutional and Innovation Economics (iino), University of Bremen, Bremen, Germany
*
*Email: graebnerc@uni-bremen.de
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Abstract

I investigate the consistency of agent-based computational models with the institutionalist research program as outlined by Myrdal, Wilber and Harrison, Hodgson and others. In particular, I discuss whether such models can be a useful heuristic for ‘pattern modelling’: Can they provide a holistic, systemic and evolutionary perspective on the economy? How can agency be conceptualised within ABMs? Building on these issues, I discuss potentials and challenges of the application of ABM in institutionalist research. This discussion also relates to recent methodological advances in neo-Schumpeterian economics. I explain how institutionalists can benefit from these and suggest areas for joint research under the methodological umbrella of ABM.

Type
Research Article
Information
Journal of Institutional Economics , Volume 12 , Issue 1 , March 2016 , pp. 241 - 261
Copyright
Copyright © Millennium Economics Ltd 2015 

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References

Albin, P. and Foley, D. (1992), ‘Decentralized, Dispersed Exchange without an Auctioneer: A Simulation Study’, Journal of Economic Behavior & Organization, 18 (1): 27–51.Google Scholar
Arthur, B. (2006), ‘Out-of-Equilibrium Economics and Agent-based Modeling’, in Tesfatsion, L. and Judd, K. (eds.), Handbook of Computational Economics. Agent-Based Computational Economics, Amsterdam and Oxford: Elsevier/North-Holland, pp. 1551–1564.Google Scholar
Axelrod, R. and Tesfatsion, L. (2006), ‘A Guide for Newcomers to Agent-Based Modeling in the Social Sciences’, in Tesfatsion, L. and Judd, K. (eds.), Handbook of Computational Economics. Agent-Based Computational Economics, Amsterdam and Oxford: Elsevier/North-Holland, pp. 1645–1659.Google Scholar
Blume, L. and Durlauf, S. (2006), ‘Introduction’, in Blume, L. and Durlauf, S. (eds.), The Economy As an Evolving Complex System III: Current Perspectives and Future Directions, Oxford and New York: Oxford University Press, pp. 1–4.Google Scholar
Bunge, M. (2000), ‘Systemism: The Alternative to Individualism and Holism’, Journal of Socio-Economics, 29 (2): 147–157.Google Scholar
Bunge, M. (2004), ‘How does it work? The Search for Explanatory Mechanisms’, Philosophy of the Social Sciences, 34 (2): 182–210.CrossRefGoogle Scholar
Chen, S. (2012), ‘Varieties of Agents in Agent-Based Computational Economics: A Historical and an Interdisciplinary Perspective’, Journal of Economic Dynamics and Control, 36 (1): 1–25.Google Scholar
Cordes, C. (2006), ‘Darwinism in Economics: From Analogy to Continuity’, Journal of Evolutionary Economics, 16 (5): 529–541.CrossRefGoogle Scholar
Diesing, P. (1971), Patterns of Discovery in the Social Sciences, Chicago: Aldine Transaction.Google Scholar
Dopfer, K. and Potts, J. (2004), ‘Evolutionary Realism: A New Ontology for Economics’, Journal of Economic Methodology, 11 (2): 195–212.Google Scholar
Dopfer, K., Foster, J. and Potts, J. (2004), ‘Micro-meso-macro’, Journal of Evolutionary Economics, 14 (3): 263–279.Google Scholar
Durlauf, S. (2005), ‘Complexity and Empirical Economics’, The Economic Journal, 115 (504): F225–F243.Google Scholar
Edmonds, B. (1999), ‘Capturing Social Embeddedness: A Constructivist Approach’, Adaptive Behavior, 7 (3–4): 323–347.Google Scholar
Edmonds, B. and Meyer, R. (eds.) (2013), Simulating Social Complexity. A Handbook, Berlin and Heidelberg: Springer.CrossRefGoogle Scholar
Elsner, W. (2012), ‘The Theory of Institutional Change Revisited: The Institutional Dichotomy, its Dynamic, and its Policy Implications in a more Formal Analysis’, Journal of Economic Issues, 46 (1): 1–43.Google Scholar
Elsner, W. and Heinrich, T. (2009), ‘A Simple Theory of ‘Meso’. On the Co-Evolution of Institutions and Platform Size - With an Application to Varieties of Capitalism and ‘Medium-Sized’ Countries’, Journal of Socio-Economics, 38 (5): 843–858.Google Scholar
Epstein, J. and Axtell, R. (1996), Growing Artificial Societies: Social Science from the Bottom Up, Cambridge, USA: The MIT Press.CrossRefGoogle Scholar
Farmer, D. (2012), ‘Economics Needs to Treat the Economy as A Complex System’, Paper for the INET Conference ‘Rethinking Economics and Politics’, 14 April 2012.Google Scholar
Foster, J. (2000), ‘Competitive Selection, Self-Organisation and Joseph A. Schumpeter’, Journal of Evolutionary Economics, 10 (3): 311–328.Google Scholar
Gilboa, I., Postlewaite, A., Samuelson, L. and Schmeidler, D. (2014), ‘Economic Models as Analogies’, The Economic Journal 124: F513–F533.Google Scholar
Gräbner, C. and Kapeller, J. (2015), ‘New Perspectives on Institutionalist Pattern Modelling: Systemism, Complexity and Agent-Based Modelling’, Journal of Economic Issues, 49 (2).Google Scholar
Granovetter, M. (1985), ‘Economic Action and Social Structure: The Problem of Embeddedness’, American Journal of Sociology, 91 (3): 481–510.Google Scholar
Harper, D. and Lewis, P. (2012), ‘New Perspectives on Emergence in Economics’, Journal of Economic Behavior & Organization, 82 (2): 329–337.Google Scholar
Hayden, G. (1982), ‘Social Fabric Matrix: From Perspective to Analytical Tool’, Journal of Economic Issues, 16 (3): 637–662.Google Scholar
Heap, S. H. and Varoufakis, Y. (2004), Game Theory: A Critical Text, London and New York: Routledge.CrossRefGoogle Scholar
Heinrich, T. (2014), ‘Standard Wars, Tied Standards, and Network Externality Induced Path Dependence in the ICT Sector’, Technological Forecasting and Social Change, 81: 309–320.Google Scholar
Hodgson, G. (1988), Economics and Institutions: A Manifesto for a Modern Institutional Economics, Cambridge, UK: Polity Press.Google Scholar
Hodgson, G. (2002), ‘Reconstitutive Downward Causation’, in Fullbrook, E. (ed.), Intersubjectivity in Economics. Agents and Structures, London and New York: Routledge, pp. 159–180.Google Scholar
Hodgson, G. (2004), The Evolution of Institutional Economics. Agency, Structure and Darwinism in American Institutionalism, London, UK: Routledge.Google Scholar
Hodgson, G. (2006), ‘What are Institutions?’, Journal of Economic Issues, 40 (1): 1–25.CrossRefGoogle Scholar
Hodgson, G. M. (2011), Downward Causation - some Second Thoughts. Website, March 2011. http://www.geoffrey-hodgson.info/downward-causation.htm; Accessed: May 21st, 2013.Google Scholar
Hodgson, G. M. and Knudsen, T. (2004), ‘The Complex Evolution of a Simple Traffic Convention: The Functions and Implications of Habit’, Journal of Economic Behavior & Organization, 54 (1): 19–47.Google Scholar
Hodgson, G. M. and Knudsen, T. (2010), Darwin's Conjecture. The Search for General Principles of Social and Economic Evolution, Chicago and London: University of Chicago Press.Google Scholar
Hodgson, G. M. and Stoelhorst, J. W. (2014), ‘Introduction to the Special Issue on the Future of Institutional and Evolutionary Economics’, Journal of Institutional Economics, 10 (4): 513–540.CrossRefGoogle Scholar
Kapeller, J. (2011), Modell-Platonismus in der Ökonomie: Zur Aktualität einer Klassischen Epistemologischen Kritik, Frankfurt: Peter Lang.Google Scholar
Kapeller, J. (2015, forthcoming), ‘Beyond foundations: Systemism in Economic Thinking’, in Jo, T. and Todorovka, Z. (eds.), Frontiers in Heterodox Economics: Essays in Honor of Frederic S. Lee, London and New York: Routledge.Google Scholar
Kim, J. (2006), ‘Emergence: Core Ideas and Issues’, Synthese, 151 (3): 547–559.CrossRefGoogle Scholar
Malerba, F., Nelson, R., Orsenigo, L. and Winter, S. (2001), ‘History-friendly Models: An Overview of the Case of the Computer Industry’, Journal of Artificial Societies and Social Simulation, 4 (3).Google Scholar
Miller, J. H. and Page, S. E. (2007), Complex Adaptive Systems. An Introduction to Computational Models of Social Life, Princeton, USA: Princeton University Press.Google Scholar
Mitchell, M. (1999), An Introduction to Genetic Algorithms, Cambridge, Massachusetts and London, UK: The MIT Press.Google Scholar
Moss, S. (2002), ‘Policy Analysis from first Principles’, Proceedings of the US National Academy of Sciences, 99 (3): 7267–7274.Google Scholar
Murmann, J. P. and Homburg, E. (2001), ‘Comparing Evolutionary Dynamics Across Different National Settings: The Case of the Synthetic Dye Industry 1857–1914’, Journal of Evolutionary Economics, 11 (2): 177–205.Google Scholar
Myrdal, G. (1978), ‘Institutional Economics’, Journal of Economic Issues, 12 (4): 771–783.Google Scholar
Nelson, R. and Winter, S. (1982), An Evolutionary Theory of Economic Change, Cambridge, MA: Belknap Press of Harvard University Press.Google Scholar
Orsenigo, L. (2007), ‘History-Friendly Models of Industrial Evolution’, in Hanusch, H. and Pyka, A. (eds.), The Elgar Companion to Neo-Schumpeterian Economics, Cheltenham, UK, Northampton, MA: Edward Elgar, pp. 453–466.Google Scholar
Page, S. E. (2012), ‘Aggregation in Agent-Based Models of Economies’, The Knowledge Engineering Review, 27 (2): 151–162.Google Scholar
Potts, J. (2000), The New Evolutionary Microeconomics. Complexity, Competence and Adaptive Behavior, Cheltenham, UK, and Northampton, MA: Edward Elgar.Google Scholar
Pyka, A. and Fagiolo, G. (2007), ‘Agent-Based Modelling: A Methodology for Neo-Schumpeterian Economics’, in Hanusch, H. and Pyka, A. (eds.), The Elgar Companion to Neo-Schumpeterian Economics, Cheltenham, UK, Northampton, MA: Edward Elgar, pp. 467–487.Google Scholar
Radzicki, M. J. (1988), ‘Institutional Dynamics: An Extension of the Institutionalist Approach to Socioeconomic Analysis’, Journal of Economic Issues, 22 (3): 633–665.CrossRefGoogle Scholar
Reinhart, C. M. and Rogoff, K. S. (2010), ‘Growth in a Time of Debt’, American Economic Review, 100 (2): 573–78.Google Scholar
Rengs, B. and Wäckerle, M. (2014), ‘A Computational Agent-Based Simulation of an Artificial Monetary Union for Dynamic Comparative Institutional Analysis’, Proceedings of the 2014 IEEE Conference on Computational Intelligence for Financial Engineering & Economics (CIFEr), pp. 437–434.Google Scholar
Strogatz, S. H. (2001), ‘Exploring Complex Networks’, Nature, 410 (6825): 268–276.Google Scholar
van Steen, M. (2010), Graph Theory and Complex Networks: An Introduction, Maarten van Steen.Google Scholar
Veblen, T. (1898), ‘Why is Economics not An Evolutionary Science?’, The Quarterly Journal of Economics, 12 (4): 373–397.Google Scholar
Velupillai, K. V. and Zambelli, S. (2011), ‘Computing in Economics’, in Davis, J. B. and Hands, D. W. (eds.), The Elgar Companion to Recent Economic Methodology, Cheltenham, UK: Edward Elgar, pp. 259–295.Google Scholar
Vilena, M. C. and Vilena, M. (2004), ‘Evolutionary Game Theory and Thorstein Veblen's Evolutionary Economics: Is EGT Veblenian?’, Journal of Economic Issues, 38 (3): 585–610.Google Scholar
Wäckerle, M., Rengs, B. and Radax, W. (2014), ‘An Agent-Based Model of Institutional Life-Cycles, Games, 5 (3): 160–187.Google Scholar
Weaver, W. (1948), ‘Science and Complexity’, American Scientist, 36 (4): 536–544.Google Scholar
Wilber, C. K. and Harrison, R. S., (1978), ‘The Methodological Basis of Institutional Economics: Pattern Model, Storytelling, and Holism’, Journal of Economic Issues, 12 (1):61–89.Google Scholar
Witt, U. (1997), ‘Self-Organization and Economics - What is New?’, Structural Change and Economic Dynamics, 8 (4): 489–507.CrossRefGoogle Scholar
Witt, U. (2004), ‘On the Proper Interpretation of Evolution in Economics and its Implications for Production Theory’, Journal of Economic Methodology, 11 (2): 125–146.CrossRefGoogle Scholar