Behavioural Models in Economics and Finance

Economic Theory views consumers, firms, investors, etc, as abstract agents. Neoclassical Economics further assumes that these agents exhibit full rationality when facing even the most complex economic situation (e.g. a stock market). However, real economic agents often exhibit bounded rationality (a term coined by the Nobel prize laureate Herbert Simon): first, they may lack the relevant information; second, they may lack the capability (either computational or in terms of time) to process even the information they have; third, pure maximization of individual welfare neglects to take into account altruism, conformism, regret, sheer whim, and other well- documented traits of human behaviour. The accumulation of experimental (psychological) evidence over recent years shows that the full rationality assumption must be rejected. The development of an Economic Theory of individual behaviour under bounded rationality is currently a very active research field. There are two different approaches. The first is axiomatic. It attempts to relax standard assumptions on agent behaviour and enlarge the classical models provided by decision theory and game theory to accommodate bounded rationality. The second is behavioural. It views agents` actions and even the motivations behind them not as static and definitive, but rather as dynamic and tentative. Observed behaviour is hence the outcome of dynamical, evolutionary processes, which reflect how economic agents learn (e.g. through trial and error, imitation, etc). The network aims to bring together a numer of European economic theory specialists (based at Salamanca (Spain), Vienna (Austria), and Zurich (Switzerland)) with a common interest in this field. The starting point of the network is the recognition that the ultimate objectives of all involved researchers are the same: the modelling of (boundedly rational) agent behaviour in specific situations of economic nature, ranging from consumption decisions and oligopolistic markets to stock markets. Research synergies arise when behavioural theories are able to provide stability checks or selection procedures among different classical economic theory predictions.

One of the main goals of the present project (not the only one) was to study the implications of boundedly rational behavior in economic contexts, and to compare the results with those obtained by traditional economic theory (based on the assumption of full rationality). "Bounded Rationality" is modelled here as behavior based on imitation of more successful agents (one form of "learning"), plus occasional experimentation with new strategies. This gives rise to a dynamic stochastic process, whose long-run outcome, the so-called evolutionarily stable states (ESS) form the prediction of the theory. This is to be contrasted with the outcome of perfectly rational behavior, modelled as a game-theoretic equilibrium (Nash equilibrium). One important difference between the two concepts is that Nash equilibrium is based on the maximization of absolute payoffs, whereas ESS is based on relative payoffs (agents imitate others whose payoff is relatively higher than the own payoff). Central issues addressed have been, on the one hand, to identify economic problems where both notions of equilibrium give the same prediction and, on the other hand, to characterise the predictions made by evolutionary equilibrium in a broad class of economic problems where both concepts differ (in particular, problems which exhibit strategic complementarities resp. substitutes). A key result is that evolution selects behaviour which maximizes individual payoffs disregarding externalities on aggregate elements of the problem. This is a generalization of perfectly competitive behavior (where agents also disregard externalities). As an example, consider the problem of optimal extraction from a common pool where total extraction affects negatively the possibilities of further extraction. The result says that evolution selects for individuals whose extraction maximizes individual payoffs disregarding their effect on total extraction. This is a negative example of evolutionary forces leading to particularly inefficient outcomes. Applying these ideas to financial markets, however, we were able to show that prices in an asset market converge to the fundamental prices when wealth in a financial market flows more likely towards investment fonds that have displayed higher observed performance in the past. At the same time we illustrate how this "long-run efficiency" is compatible with bubbles and crashes in the short run.