Instructors

Frank Schorfheide (University of Pennsylvania)

Dates

1-5 September 2025

Hours

9:30 to 13:00 CEST

Format

In person

Practical Classes

No

Intended for

Practitioners, researchers, and academics interested in methods to study the interaction of aggregate and cross-sectional data.

Prerequisites

A solid background in statistics and econometrics (masters level or first-year Ph.D. level) 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.

Overview

The course focuses on modeling the joint dynamics of macroeconomic aggregates and cross-sectional data. For instance, the macroeconomic aggregates could include a measure of productivity, gross domestic product, and the unemployment rate. The cross-sectional data could include administrative or survey data on labor earnings. Such models could be used, for instance, to examine the effects of an aggregate shock, such as a productivity shock, on the cross-sectional distribution of income. The course focuses on model specification and estimation using Bayesian techniques.

Topics

• Introduction to Bayesian inference and computation
• Empirical Bayes methods
• Functional autoregressive models
• Bayesian panel data analysis
• Modeling distributional versus unit-level dynamics
• Empirical applications: the effect of technology and monetary policy shocks on cross-sectional outcomes

Frank Schorfheide is the Christopher H. Browne Distinguished Professor of Economics at the University of Pennsylvania. He has as Chair of the Department of Economics from July 2018 to June 2021. He is also a Research Associate at the National Bureau of Economic Research (NBER) and a Research Fellow at the Centre for Economic Policy Research (CEPR). He has served on the editorial board (as co-editor) of the International Economic Review from 2005-2009 and as co-editor of Quantitative Economics from 2011-2018. He has been a Visiting Scholar at several central banks.

Schorfheide’s research areas are econometrics and empirical macroeconomics. Much of his work can be classified as macroeconometrics and is related to the Bayesian analysis of dynamic stochastic general equilibrium (DSGE) models. His research provides a set of tools that are useful for empirical work with modern macroeconomic models, including forecasting and policy analysis. He has applied these methods to analyze the sources of business cycle fluctuations and to study the effects of monetary policy. In recent years, he also has worked on forecasting with dynamic panel data models and on functional autoregressive models that capture the interaction of macroeconomic aggregates and cross-sectional distributions to inform heterogeneous agent modeling. He has published papers in the American Economic Review, Econometrica, the Journal of Political Economy, the Review of Economic Studies, and many leading field journals. He co-authored a Princeton University Press book with Ed Herbst on “Bayesian Estimation of DSGE Models.”