DSGE and Time-Series Models for Macroeconomic and Policy Analysis


26-30 August 2024


9:30 to 13:00 CEST


In person

Intended for

Practitioners, researchers, and academics interested in time-series methods, business cycle analysis, and forecasting.


A good background in statistics and econometrics will be useful to follow the class, but no familiarity with the Bayesian approach is required, as the course will start with a brief introduction to Bayesian econometrics.


The course will offer an overview of modern tools in macroeconometrics, ranging from VARs, state-space models (such as time-varying coefficients models, factor models and models with stochastic volatility), dynamic stochastic general equilibrium (DSGE) and DSGE-VARs models, pools, and model averaging. The course will strive to offer enough theory to understand the tools' theoretical underpinnings, why they work, how and when they should be used, and what their limitations are. At the same time, it will emphasize their practical use in macro applications. The course will take a Bayesian perspective, both because this approach has shown itself to be useful in applied macroeconomics and because of its computational advantages relative to the frequentist approach. Monte Carlo methods, which lie behind the recent surge in popularity of the Bayesian approach, will be reviewed.


  • Basic notions of Bayesian econometrics and introduction into VARs
  • Time-series models
  • A Quick Overview of MCMC Methods
  • DSGE and DSGE-VARs
  • Model averaging/combination

Marco Del Negro is Economic Advisor at the Federal Reserve Bank of New York, and director of the Applied Macroeconomics & Econometrics Center (AMEC) there. His research focuses on the use of general equilibrium models in forecasting and policy analysis. He has published work in the American Economic Review, American Economic Journal: Macroeconomics, Journal of Econometrics, Journal of .Applied Econometrics, Journal of International Economics, Journal of Monetary Economics, International Economic Review, Journal of the European Economic Association, and the Review of Economic Studies. He is coauthor with Frank Schorfheide of a chapter on “Bayesian Macroeconometrics” in the Oxford Handbook of Bayesian Econometrics, and of a chapter on “DSGE Model-Based Forecasting”, in the Handbook of Economic Forecasting.