- Consulting Editors
- Vars, Cointegration, and Common Cycle Restrictions
- Dynamic Factor Models
- Forecasting With Nonlinear Time Series Models
- Forecasting With DSGE Models
- Forecasting Economic Time Series Using Unobserved Components Time Series Models
- Improving the Role of Judgment in Economic Forecasting
- Forecasting with Mixed-Frequency Data
- Forecasting with Real-Time Data Vintages
- Forecasting from misspecified Models in the Presence of Unanticipated Location Shifts
- Forecasting Breaks and Forecasting During Breaks
- Forecast Combinations
- Multiple Forecast Model Evaluation
- Testing for Unconditional Predictive Ability
- Testing Conditional Predictive Ability
- Interpreting and Combining Heterogeneous Survey Forecasts
- Analyzing Three-Dimensional Panel Data of Forecasts
- Forecasting Financial Time Series
- Forecasting Volatility Using High-Frequency Data
- Economic Value of Weather and Climate Forecasts
- Long-Horizon Growth Forecasting and Demography
- Forecasting the Energy Markets
- Models for Health Care
- Election Forecasting
- Marketing and Sales
Abstract and Keywords
This article reviews and illustrates the methodology of forecasting with dynamic stochastic general equilibrium (DSGE) models using Bayesian methods. It discusses an algorithm for estimating the predictive distribution of the observed variables based on draws from the posterior distribution of the DSGE model parameters and simulation of future paths for the variables with the model. The article is organized as follows. Section 2 sketches the new area-wide model (NAWM) and briefly reports on its empirical implementation. Section 3 discusses how the predictive distribution of a DSGE model can be estimated and then presents the alternative forecasting models that are used in the empirical analysis. Section 4 covers the forecast evaluation of the NAWM, focusing first on point forecasts and then on density forecasts. Section 5 summarizes the main findings and concludes.
Kai Christoffel is Senioreconomist at the Econometric Modeling Division in the Directorate General Research of the European Central Bank. His research interests include quantitative macroeconomics and monetary economics. His recent research has focused on the specification and estimation of dynamic stochastic general equilibrium (DSGE) models, including the modeling of labor market issues and the development of models suitable for quantitative policy analysis and forecasting.
Günter Coenen is head of the Econometric Modeling Division in the Directorate General Research of the European Central Bank. His research interests include macroeconomics, monetary economics, as well as applied time-series econometrics. His recent research has focused on the development of large-scale dynamic stochastic general equilibrium (DSGE) models suitable for quantitative policy analysis and forecasting at policymaking institutions. Previously he worked on competing structural models of the inflation process and studied the performance and robustness of monetary policy rules, notably in the presence of the zero lower bound on nominal interest rates.
Anders Warne is a senior economist at the Econometric Modeling Division in the Directorate General Research of the European Central Bank. His main research interests are time series analysis for applied macroeconomics and Bayesian econometrics.
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