Technological Change, Learning and Macro-Economic Coordination: an Evolutionary Model
AbstractThe purpose of the paper is to model the process of rule generation by firms that must allocate their resources between physical assets, training, and R&D, and to study the microeconomic performances as well as the aggregate outcomes. The framework is a complete micro-macroeconomic Leontieff-Keynesian model initialised with Swedish firms, and provides one of the first applications of the " artificial world " methodology to a complete economic system. The model also displays detailed features of technological change and firms' human capital. In this complex and evolving Schumpeterian environment, firms are "boundedly rational" and use rules. They learn better rules to survive, and we model this process with the use of classifiers. We are able to show that the diversity of rules is sustained over time, as well as the heterogeneity of firms' performances. Simple rules appear to secure larger market shares than complex rules. The learning process improves macroeconomic performance to a large extent whereas barriers to entry are also detrimental for macroeconomic performance.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoArticle provided by Journal of Artificial Societies and Social Simulation in its journal Journal of Artificial Societies and Social Simulation.
Volume (Year): 2 (1999)
Issue (Month): 2 ()
Contact details of provider:
Technological Change; Human Capital; Endogenous Growth; Artificial Intelligence; Artificial Worlds; Classifier Systems; Microsimulation; Evolutionary Theory;
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
- Vanessa Oltra & Murat Yildizoglu, 1999. "Non Expectations and Adaptive Behaviours: the Missing Trade-off in Models of Innovation," Working Papers of BETA 9915, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
- Murat Yildizoglu, 2001.
"Connecting adaptive behaviour and expectations in models of innovation: The Potential Role of Artificial Neural Networks,"
2001-2, Equipe Industries Innovation Institutions, Université Bordeaux IV, France.
- Murat Yildizoglu, 2002. "Connecting adaptive behaviour and expectations in models of innovation: The Potential Role of Artificial Neural Networks," Computing in Economics and Finance 2002 200, Society for Computational Economics.
- Grazzini, Jakob & Richiardi, Matteo, 2013.
"Consistent Estimation of Agent-Based Models by Simulated Minimum Distance,"
Department of Economics and Statistics Cognetti de Martiis. Working Papers
201335, University of Turin.
- Jakob Grazzini & Matteo G. Richiardi, 2013. "Consistent Estimation of Agent-Based Models by Simulated Minimum Distance," LABORatorio R. Revelli Working Papers Series 130, LABORatorio R. Revelli, Centre for Employment Studies.
- Nigel Gilbert & Pietro Terna, 2000. "How to build and use agent-based models in social science," Mind and Society: Cognitive Studies in Economics and Social Sciences, Fondazione Rosselli, vol. 1(1), pages 57-72, March.
- Ballot, Gerard, 2002. "Modeling the labor market as an evolving institution: model ARTEMIS," Journal of Economic Behavior & Organization, Elsevier, vol. 49(1), pages 51-77, September.
- Murat Yildizoglu, 1999.
"Competing R&D Strategies in an Evolutionary Industry Model,"
Computing in Economics and Finance 1999
343, Society for Computational Economics.
- Yildizoglu, Murat, 2002. "Competing R&D Strategies in an Evolutionary Industry Model," Computational Economics, Society for Computational Economics, vol. 19(1), pages 51-65, February.
- Murat Yildizoglu, 1999. "Competing R&D Strategies in an Evolutionary Industry Model," Working Papers of BETA 9914, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Nigel Gilbert).
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.