Edited by J. Stanley Metcalfe and John Foster
Chapter 2: On the Methodology of Assessing Agent-Based Evolutionary Models in the Social Sciences
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...
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