This paper suggests that we need an alternative approach to economic modeling in general, and macroeconomic modeling in particular, if we are to capture salient characteristics of recent economic developments. Rather than focusing on models built on the basis of isolated, rational, optimizing agents, we should recognize that much simpler individuals following basic rules can collectively generate complex behavior. We have lessons to learn from studying the behavior of social insects for example. Noisy systems of interactive agents can generate aggregate phenomena such as sudden changes in the state of an economy or market, with no external shock. I give two examples of simple models of financial markets to illustrate this but would argue more generally that such models are indispensible if we are to understand aggregate economic phenomena.

We consider a model in which foreign and domestic traders buy the assets of both of two countries. Speculators in both countries use chartist or fundamentalist rules for forecasting the exchange rate. Demand for the assets of each country is determined by these forecasts. Perceptions of the fundamentals in each country are not necessarily the same. Rules are used with a certain probability depending on an agent's previous experience with them. The demands of the fundamentalist and chartist agents in the two countries determine the temporary equilibrium exchange rate at each point in time. This is unique under certain assumptions. With traders of both nationalities there is no need, as in other models, for an exogenous supply of foreign exchange. The model produces realistic features of the equilibrium exchange rate series. Periods in which the exchange rate tracks the fundamentals of one of the countries alternate with others in which bubbles appear.

This issue contributes to the discussion of the relation between individual and aggregate behavior. The basic feature of all the models presented is that they allow for direct interaction between the individuals. This, it is shown, leads to a number of interesting phenomena that are difficult to account for in standard models. The basic message is that the inclusion of heterogeneous interacting agents allows us to escape from the pitfalls associated with the reduction to a representative individual and furthermore to show that aggregates will, in general, have behavior that is different from that of the component individuals. Lastly, complex aggregate behavior is not necessarily the result of complicated individual reasoning, it can emerge from very simple rule following by individuals.