Show Less

Evolution and Economic Complexity

Edited by J. Stanley Metcalfe and John Foster

Dedicated to the goal of furthering evolutionary economic analysis, this book provides a coherent scientific approach to deal with the real world of continual change in the economic system. Expansive in its scope, this book ranges from abstract discussions of ontology, analysis and theory to more practical discussions on how we can operationalize notions such as ‘capabilities’ from what we understand as ‘knowledge’. Simulation techniques and empirical case studies are also used.
Buy Book in Print
Show Summary Details
You do not have access to this content

Chapter 2: On the Methodology of Assessing Agent-Based Evolutionary Models in the Social Sciences

Paul Ormerod and Bridget Rosewell


Paul Ormerod and Bridget Rosewell INTRODUCTION Agent-based evolutionary models appear strange to most economists. They offer solutions with apparently limited predictive power and where a range of outcomes is often possible. Individual agents are usually heterogeneous, defying simple, easily generalizable descriptions. Probabilistic behaviour of such agents is normally incorporated in the models. It is not surprising that there is suspicion of this modelling approach, since it looks, indeed is, so different from the deterministic models in which most economists are trained. But both conventional economic models and agent-based evolutionary ones face a fundamental problem of validation. Because we can rarely undertake fully controlled experiments, the result of any empirical testing in social and economic science is inevitably to a degree ambiguous. No theory in economics or sociology can be justified or tested simply by reference to the data. We have only to look at the enormous efforts spent in timeseries econometrics in specifying the consumption function, or at attempts to identify in cross-sectional data the elasticity of female labour supply with respect to the real wage, to realize that conventional econometric ‘testing’ has not taken us very far. Moreover, predictive power is necessarily limited in a world where practical experiments are few and far between. Indirect tests are the most that can be hoped for. This is analogous to much of the current situation in theoretical physics. While the discovery of quantum mechanical rules was capable of experimental testing and refinement at each stage, the...

You are not authenticated to view the full text of this chapter or article.

Elgaronline requires a subscription or purchase to access the full text of books or journals. Please login through your library system or with your personal username and password on the homepage.

Non-subscribers can freely search the site, view abstracts/ extracts and download selected front matter and introductory chapters for personal use.

Your library may not have purchased all subject areas. If you are authenticated and think you should have access to this title, please contact your librarian.

Further information

or login to access all content.