Exploring a New ExpAce: The Complementarities between Experimental Economics and Agent-based Computational Economics
AbstractWhat is the relationship, if any, between Experimental Economics and Agent-based Computational Economics? Experimental Economics (EXP) investigates individual behaviour (and the emergence of aggregate regularities) by means of human subject experiments. Agent-based Computational Economics (ACE), on the other hand, studies the relationships between the micro and the macro level with the aid of artificial experiments. Note that the way ACE makes use of experiments to formulate theories is indeed similar to the way EXP does. The question we want to address is whether they can complement and integrate with each other. What can Agent-based computational Economics give to, and take from, Experimental Economics? Can they help and sustain each other, and ultimately gain space out of their restricted respective niches of practitioners? We believe that the answer to all these questions is yes: there can be and there should be profitable “contaminations” in both directions, of which we provide a first comprehensive discussion.
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 InfoPaper provided by LABORatorio R. Revelli, Centre for Employment Studies in its series LABORatorio R. Revelli Working Papers Series with number 45.
Length: 9 pages
Date of creation: 2006
Date of revision:
Experimental Economics; Agent-based Computational Economics; Agent-Based Models; Simulation.;
Find related papers by JEL classification:
- B4 - Schools of Economic Thought and Methodology - - Economic Methodology
- C9 - Mathematical and Quantitative Methods - - Design of Experiments
- C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
This paper has been announced in the following NEP Reports:
- NEP-ALL-2007-04-28 (All new papers)
- NEP-CBE-2007-04-28 (Cognitive & Behavioural Economics)
- NEP-CMP-2007-04-28 (Computational Economics)
- NEP-EXP-2007-04-28 (Experimental Economics)
- NEP-HPE-2007-04-28 (History & Philosophy of Economics)
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
- repec:fee:wpaper:1103 is not listed on IDEAS
- Jason Shachat & J. Todd Swarthout, 2002.
"Learning about Learning in Games through Experimental Control of Strategic Interdependence,"
Experimental Economics Center Working Paper Series
2006-17, Experimental Economics Center, Andrew Young School of Policy Studies, Georgia State University, revised Aug 2008.
- Shachat, Jason & Swarthout, J. Todd, 2012. "Learning about learning in games through experimental control of strategic interdependence," Journal of Economic Dynamics and Control, Elsevier, vol. 36(3), pages 383-402.
- Jason Shachat & J. Todd Swarthout, 2003. "Learning about Learning in Games through Experimental Control of Strategic Interdependence," Experimental 0310003, EconWPA.
- Grazzini, J., 2011. "Experimental Based, Agent Based Stock Market," CeNDEF Working Papers 11-07, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Giovanni Bert).
If references are entirely missing, you can add them using this form.