Adaptive Least Squares (ALS), i.e. recursive regression with asymptotically constant gain, as proposed by Ljung (1992), Sargent (1993, 1999), and Evans and Honkapohja (2001), is an increasingly widely-used method of estimating time-varying relationships and of proxying agents’...

Monitoring and forecasting price developments in the euro area is essential in light of the two-pillar framework of the ECB's monetary policy strategy. This study analyses whether the accuracy of forecasts of aggregate euro area inflation can be improved by aggregating forecasts of subindices of...

This paper introduces a form of boundedly-rational expectations into an otherwise standard New Keynesian Phillips curve. The representative agent's forecast rule is optimal, conditional on a perceived law of motion for inflation and observed moments of the inflation time series. The perceived...

The assumption of perfectly rational representative agents is now commonly questioned. This paper explores the equilibrium properties of boundedly rational heterogeneous agents. We combine an adaptive learning process in a modified cobweb model within a Stackleberg framework. We assume that...

We examine linear-quadratic (LQ) approximation of stochastic dynamic optimization problems in macroeconomics (and elsewhere), in particular in policy analysis using Dynamic Stochastic General Equilibrium (DSGE) models. We first define the problem that is solved by a social planner, given that...

Recently, there has been many applications of perturbation methods for solving stochastic dynamic general equilibrium models. However, in standard applications of the perturbation method, the Taylor expansion is always computed around the deterministic steady state. Because of nonlinearities,...