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...

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....

In this paper, we analyze the importance of the frequency of decision making for macroeconomic dynamics. We explain how the frequency of decision making (period length) and the unit of time measurement (calibration frequency) differ and study the implications of this difference for macroeconomic...