To isolate the impact of the assumption of model-consistent expectations, this paper proposes a baseline case in which households are individually rational, have full information and learn using forecast rules specified as in the minimum state variable representation of the economy. Applying...

This paper considers the use of neural networks to model bounded rational behaviour. The underlying theory and use of neural networks is now a component of various forms of scientific enquiry, be it modelling artificial intelligence, developing better pattern recognition or solving complex...

This paper considers the ‘negotiation game’ (Busch and Wen [4]) which combines the features of two-person alternating offers and repeated games. Despite the forces of bargaining, the negotiation game in general admits a large number of equilibria, some of which involve delay in agreement and...

This paper uses the complexity of non-competitive behaviour to provide a new justification for competitive equilibrium in the context of extensive-form market games with a finite number of agents. This paper demonstrates that if rational agents have (at least at the margin) an aversion for...

This paper demonstrates that an asset pricing model with least-squares learning can lead to bubbles and crashes as endogenous responses to the fundamentals driving asset prices. When agents are risk-averse they need to make forecasts of the conditional variance of a stock¡¯s return....

I develop an equilibrium model with collateral constraints in which rational agents are uncertain and learn about the equilibrium mapping between fundamentals and collateral prices. Bayesian updating of beliefs by agents can endogenously generate booms and busts in collateral prices and largely...

Incorporating adaptive learning into macroeconomics requires assumptions about how agents incorporate their forecasts into their decision-making. We develop a theory of bounded rationality that we call finite-horizon learning. This approach generalizes the two existing benchmarks in the...