Abstract
This paper provides a survey of the development and contributions of agent-based modeling to economic analysis, without any claim to be exhaustive. Our perspective is particularly shaped by the papers presented at the 17th Wehia conference, a selection of which are published in this special issue. The paper shows how agent-based models have developed, and how they have improved our understanding not only of macroeconomic disequilibria but also of the possibilities of the emergence of equilibrium in such realistic systems. It also reviews the progress made in our understanding of real markets, and lists some of the improvements needed to establish these models as alternative tools to the present orthodox models.
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Notes
Similar definitions are proposed by Gallegati and Richiardi (2009).
The program is available at http://ermes.u-paris2.fr/Wehia_2012/pdf/Program_WEHIA.
Ballot (1987) offers a typology of the microsimulation models in 9 classes and the view that ABMs correspond to the best theoretically grounded classes of microsimulation models.
Orcutt’ autobiography (Orcutt 1990a) makes this extremely clear.
Baroni and Richiardi (2007) provide a recent and compact survey of Orcutt’s methodology and diverse types of microsimulation models, but do not investigate the relations with ABMs.
Although some models simulate cohorts that do not interact, in order to avoid the modeling complexities and the computational load induced by interactions.
See Baroni and Richiardi (2007, p. 27), for the specifications.
This may not pay tribute to some other pioneers who did a less comprehensive research over time. See Orcutt (1990). Moreover we leave aside some ABMs of markets built in the 70s. They will be mentioned below.
The full description of the model is given by Bennett and Bergmann (1986), on which we rely here.
The model has given birth to over 50 publications and extended versions are still being developed. The model is fully documented in a series of books, notably the version for PC by Taymaz (1991).
If perfect rationality is unique, each orthodox researcher makes a huge number of assumptions on the environment which are his own choice and arbitrary.
There exists a huge literature on the theory of search but, as far as we know, individual strategies are given exogenously and what is considered is not the emergence of different search strategies but the influence of a priori strategies on the outcomes.
Fagiolo et al. (2007) review the many problems involved.
The Krieging method is a method of interpolation which predicts unknown values from data observed at known locations. This method uses variogram to express the spatial variation , and it minimizes the error of predicted values which are estimated by spatial distribution of the predicted values.
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Acknowledgments
The authors gratefully acknowledge the contribution of all the participants to the 17th WEHIA conference who have provided the inspiration and the material for this special issue and helpful comments from the referee. A. Mandel acknowledges the support of Institute for New Economic Thinking grant INO1200022 and from the EU-FP7 projects SIMPOL and IMPRESSION. A. Vignes acknowledges the support of the ANR-CNRS project DyXI. The authors thank the Universities of Paris 1 and Paris 2 for their support. The usual disclaimer applies.
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Ballot, G., Mandel, A. & Vignes, A. Agent-based modeling and economic theory: where do we stand?. J Econ Interact Coord 10, 199–220 (2015). https://doi.org/10.1007/s11403-014-0132-6
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DOI: https://doi.org/10.1007/s11403-014-0132-6