Dynamic Stochastic General Equilibrium Models as a Tool for Policy Analysis

Abstract

This article discusses the evolution of dynamic macroeconomic models from calibrated Real Business Cycle models to estimated dynamic stochastic general equilibrium models. The purpose is to suggest the usefulness of these models as a tool for policy analysis, with a particular emphasis on aspects of monetary policy. (JEL classification: D58, E50) This article gives an overview of the literature that has led to the emergence of dynamic stochastic general equilibrium (DSGE) models. This approach to macroeconomic modelling has gained widespread support among researchers and has recently started to be taken seriously by policy-making institutions as a modelling framework which is useful for policy analysis and the conceptual support of decision making. Modern macroeconomics is the result of an intense, and at times passionate, scientific debate that has taken place over the last decades. In the early 1980s, a new approach to the business cycle analysis was introduced by Kydland and Prescott (1982). The main tenet of their approach was that a small model of a frictionless and perfectly competitive market economy, inhabited by utility-maximising rational agents which operate subject to budget constraints and technological restrictions, could replicate a number of stylised business cycle facts when hit by random productivity shocks. This so-called real business cycle (RBC) approach to macroeconomic modelling was early on criticised on various aspects. Nevertheless, as it is now widely acknowledged, the RBC agenda has made a lasting methodological contribution. Most of today’s DSGE models