Impulse response identification in DSGE models

Dynamic stochastic general equilibrium (DSGE) models have become a widely used tool for policymakers. This paper modifies the global identification theory used for structural vector autoregressions, and applies it to DSGE models. We use this theory to check whether a DSGE model structure allows for unique estimates of structural shocks and their dynamic effects. The potential cost of a lack of identification for policy oriented models along that specific dimension is huge, as the same model can generate a number of contrasting yet theoretically and empirically justifiable recommendations. The problem and methodology are illustrated using a simple New Keynesian business cycle model.

Structural Macro-Econometric Modelling in a Policy Environment

The paper looks at the development of macroeconometric models over the past sixty years. In particular those that have been used for analysing policy options. We argue that there have been four generations of these. Each generation has evolved new features that have been partly drawn from the developing academic literature and partly from the perceived weaknesses in the previous generation. Overall the evolution has been governed by a desire to answer a set of basic questions and sometimes by what can be achieved using new computational methods. Our account of each generation considers their design, the way in which parameters were quantified and how they were evaluated.DSGE models;Phillips Curve;Macroeconometric Models;Bayesian Estimation

Structural macro-econometric modelling in a policy environment

In this paper we review the evolution of macroeconomic modelling in a policy environment that took place over the past sixty years. We identify and characterise four generations of macro models. Particular attention is paid to the fourth generation -- dynamic stochastic general equilibrium models. We discuss some of the problems in how these models are implemented and quantified.

Note on the role of natural condition of control in the estimation of DSGE models

This paper is written by authors from technical and economic fields, motivated to find a common language and views on the problem of the optimal use of information in model estimation. The center of our interest is the natural condition of control -- a common assumption in the Bayesian estimation in technical sciences, which may be violated in economic applications. In estimating dynamic stochatic general equilibrium (DSGE) models, typically only a subset of endogenous variables are treated as measured even if additional data sets are available. The natural condition of control dictates the exploitation of all available information, which improves model adaptability and estimates efficiency. We illustrate our points on a basic RBC model.

Limited Information Estimation and Evaluation of DSGE Models. Working paper #6

We advance the proposal that DSGE models should not just be estimated and evaluated with reference to full information methods. These make strong assumptions and therefore there is uncertainty about their impact upon results. Some limited information analysis which can be used in a complementary way seems important. Because it is sometimes difficult to implement limited information methods when there are unobservable non-stationary variables in the system we present a simple method of overcoming this that involves normalizing the non-stationary variables with their permanent components and then estimating the estimating the resulting Euler equations. We illustrate the interaction between full and limited information methods in the context of a well-known open economy model of Lubik and Schorfheide. The transformation was effective in revealing possible mis-specifications in the equations of LS\'s system and the limited information analysis highlighted the role of priors in having a major influence upon the estimates.

Issues in Adopting DSGE Models for Use in the Policy Process

Our discussion is structured by three concerns - model design, matching the data and operational requirements. The paper begins with a general discussion of the structure of dynamic stochastic general equilibrium (DSGE) models where we investigate issues like (i) the type of restrictions being imposed by DSGE models upon system dynamics, (ii) the implication these models would have for 'location parameters', viz. growth rates, and (iii) whether these models can track the long-run movements in variables as well as matching dynamic adjustment. The paper further looks at the types of models that have been constructed in central banks for macro policy analysis. We distinguish four generations of these and detail how the emerging current generation, which are often referred to as DSGE models, differs from the previous generations. The last part of the paper is devoted to a variety of topics involving estimation and evaluation of DSGE models.DSGE model, Bayesian estimation, model evaluation.

Commentary on "An estimated DSGE model for the United Kingdom"

Equilibrium (Economics) - Mathematical models ; Economic policy - Great Britain

New Keynesian Model Dynamics under Heterogeneous Expectations and Adaptive Learning

We analyze the economic dynamics in a basic New Keynesian model adjusted for imperfect, heterogeneous knowledge and adaptive learning. The policy, represented by a forward-looking Taylor rule, is driven by the central bank's own internal forecasts, whereas the core economic dynamics are driven by private agents' expectations. We study the implications of disagreement between those two. We find that if there is expectations heterogeneity, monetary policy should be less active in its actions in order to be short-run stability improving, and to affect positively the speed of convergence towards the first best equilibrium in the long run. This is in contrast to the homogeneous incomplete knowledge literature, which predicts the opposite. We also find that the homogeneous expectations economy is easier to operate in for monetary policy, and that policy can be more effective than in the heterogeneous expectations economy. From the perspective of incomplete, heterogeneous knowledge and adaptive learning methodology, we can thus see the importance of good communication policy and monetary policy credibility.. Imperfect and heterogeneous knowledge, adaptive learning, monetary policy.

Managing and communicating risk and uncertainty in macroeconomic policymaking

In policymaking, as in life, we often must make decisions without knowing how the future will play out. Taking uncertainty into account when making macroeconomic policy allows policymakers to help improve economic outcomes. This article considers three aspects of improving outcomes for fiscal and monetary policymaking: considering risk and uncertainty in decision-making; communicating risk and uncertainty; and designing better tools to communicate risk