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The US Business Cycle: An Agent-based Model of Firms Operating under Uncertainty

This paper offers an agent-based model of the US business cycle which is solved computationally. The business cycle, along with long-term growth, is one of the two features which distinguishes capitalism from all previously existing societies. The source of cycles is posited in general in economic theory to be a series of random shocks which are external to the system. In this model, the cycle is an internal feature of the system, arising from the level of industrial concentration of the agents and the interactions between them in the face of uncertainty. The agents are myopic and follow behavioural rules which can be thought of as Keynesian rules of thumb. The model in contrast to most existing economic theories of the cycle accounts for the key time-series features of output growth in the US business cycle in the twentieth century. On average over a large number of simulations, the output growth series in the model is similar to that of the actual data both in terms of the autocorrelation function and its Fourier transform pair the power spectrum. Further, the model exhibits positive co-movement of output of the agents over the course of the cycle. The model also replicates the power law distribution of the duration of recessions.