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...

This paper presents a model of non-cooperative network formation in which the marginal benefit of new links eventually decreases. Agents link with each other to gain information and update their links according to better-reply dynamics. In the long run the system settles to a unique network...

We explore the stability of imitation in a 1200-period experimental Cournot game where subjects do not know the payoff function but see the output quantities and payoffs of each oligopolist after every period. In line with theoretical predictions and previous experimental findings, our...

Expectations play a central role in modern macroeconomic theories. The econometric learning approach models economic agents as forming expectations by estimating and updating forecasting models in real time. The learning approach provides a stability test for rational expectations and a...

Learning and adaptation play great role in emergent socio-economic phenomena. Complex dynamics has been previously found in the systems of multiple learning agents interacting via a simple game. Meanwhile, the single agent adaptation is considered trivially stable. We advocate the idea that...

The article presents a temporary equilibrium framework for macroeconomic analysis that allows for a wide range of possible specifications of expectations but reduces to a standard new Keynesian model in the limiting case of rational expectations. This common framework is then used to contrast...