Expectations play a central role in modern macroeconomics. The econometric learning approach, in line with the cognitive consistency principle, models agents as forming expectations by estimating and updating subjective forecasting models in real time. This approach provides a stability test for...

We analyse some practical aspects of implementing adaptive learning in the context of forward-looking linear models. In particular, we focus on how to set initial conditions for three popular algorithms, namely recursive least squares, stochastic gradient and constant gain learning. We propose...

Out-of-sample forecasting tests of DSGE models against time-series benchmarks such as an unrestricted VAR are increasingly used to check a) the specification b) the forecasting capacity of these models. We carry out a Monte Carlo experiment on a widely-used DSGE model to investigate the power of...

Forward-looking RE models such as the popular New Keynesian (NK) model do not provide a unique prediction about how the model economy behaves. We need some mechanism that ensures determinacy. McCallum (2011) says it is not needed because models are learnable only with the determinate solution...

This paper uses a model of boundedly rational learning to account for the observations of recurrent hyperinflations in the last decade. We study a standard monetary model, where the full rational expectations assumption is replaced by a formal definition of quasi-rational learning. The model...

The theory of monotone comparative statics and supermodular games is presented as the appropriate tool to model complementarities. The approach, which has not yet been fully incorporated into the standard toolbox of researchers, makes the analysis intuitive and simple, helps in deriving new...

This paper proposes a new approach for modeling investor fear after rare disasters. The key element is to take into account that investors' information about fundamentals driving rare downward jumps in the dividend process is not perfect. Bayesian learning implies that beliefs about the...

We study the extent to which self-referential adaptive learning can explain stylized asset pricing facts in a general equilibrium framework. In particular, we analyze the effects of recursive least squares and constant gain algorithms in a production economy and a Lucas type endowment economy....

This Paper shows that price rigidity evolves in an economy populated by imperfectly rational agents who experiment with alternative rules of thumb. In the model, firms must set their prices in the face of aggregate shocks. The payoff depends on the level of aggregate demand, as well as on their...

Robust learning experiments confront participants with structurally different decision environments which they encounter, furthermore, repeatedly. Since the decision format does not depend on the rules (of game), forward looking deliberation (the shadow of the future) can be detected by...