Instructor:
Frank Schorfheide (University of Pennsylvania)
Dates: 1-5 September 2025
Hours: 9:30 to 13:00 CEST
Format: In person
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
Dates: 1-5 September 2025
Hours: 9:30 to 13:00 CEST
Format: In person
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
- Professor: Frank Schorfheide