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The economics of radical uncertainty

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  • Ormerod, Paul

Abstract

In situations of what we now describe as radical uncertainty, the core model of agent behaviour, of rational autonomous agents with stable preferences, is not useful. Instead, a different principle, in which the decisions of an agent are based directly on the decisions and strategies of other agents, becomes the relevant core model. Preferences are not stable, but evolve. It is not a special case in such circumstances, but the general one. The author provides empirical evidence to suggest that as a description of behaviour in the modern world, economic rationality is applicable in a declining number of situations. He discusses models drawn from the modern literature on cultural evolution in which imitation of others is the basic strategy, and suggests a heuristic way of classifying situations in which the different models are relevant. The key point is that in situations where radical uncertainty is present, we require theoretical 'null' models of agent behaviour which are different from those of economic rationality. Under uncertainty, fundamentally different behavioural rules are 'rational'. The author gives an example of a very simple pure sentiment model of the business cycle, in which agents use very simple heuristic decision rules. It is nevertheless capable of approximating a number of deep features of output growth over the cycle.

Suggested Citation

  • Ormerod, Paul, 2015. "The economics of radical uncertainty," Economics Discussion Papers 2015-40, Kiel Institute for the World Economy (IfW).
  • Handle: RePEc:zbw:ifwedp:201540
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    References listed on IDEAS

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    1. Armen A. Alchian, 1950. "Uncertainty, Evolution, and Economic Theory," Journal of Political Economy, University of Chicago Press, vol. 58, pages 211-211.
    2. R. Bentley & Michael O’Brien & Paul Ormerod, 2011. "Quality versus mere popularity: a conceptual map for understanding human behavior," Mind & Society: Cognitive Studies in Economics and Social Sciences, Springer;Fondazione Rosselli, vol. 10(2), pages 181-191, December.
    3. Keen, Steve, 2013. "A monetary Minsky model of the Great Moderation and the Great Recession," Journal of Economic Behavior & Organization, Elsevier, vol. 86(C), pages 221-235.
    4. Ormerod, Paul, 2002. "The US business cycle: power law scaling for interacting units with complex internal structure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 314(1), pages 774-785.
    5. Xavier Gabaix, 2011. "The Granular Origins of Aggregate Fluctuations," Econometrica, Econometric Society, vol. 79(3), pages 733-772, May.
    6. Paulo Brito & Carlos Barros, 2005. "Learning-by-Consuming and the Dynamics of the Demand and Prices of Cultural Goods," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 29(2), pages 83-106, May.
    7. Valerie A. Ramey, 2011. "Can Government Purchases Stimulate the Economy?," Journal of Economic Literature, American Economic Association, vol. 49(3), pages 673-685, September.
    8. Guilmi, Corrado Di & Gallegati, Mauro & Ormerod, Paul, 2004. "Scaling invariant distributions of firms’ exit in OECD countries," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 334(1), pages 267-273.
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    More about this item

    Keywords

    uncertainty; imitation; evolution; agent-based model; sentiment; business cycle;

    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • E14 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Austrian; Evolutionary; Institutional
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles

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