The IIF Summer School is a two-day course which provides in-depth analysis on a cutting edge topic in forecasting offered by an invited speaker at the International Symposium on Forecasting (ISF). The Summer School shares the same venue as the ISF. If you have questions, contact Laurent Ferrara or  Pilar Poncela, IIF Directors.

6th Forecasting Summer School

Modeling and Forecasting the International Dimensions: Business cycles, exchange rates, and cross-border capital and trade flows
Instructor: Prof. Menzie David Chinn, Professor of Public Affairs and Economics, University of Wisconsin
Location: University of Virginia Darden School of Business
Dates: June 24-25, 2023

About the Instructor

Menzie David Chinn is a professor of public affairs and economics at the University of Wisconsin–Madison, co-editor of the Journal of International Money and Finance, and a Research Associate of the National Bureau of Economic Research (International Finance and Macroeconomics Program).

Course details

Practitioners have long attempted to understand movements in macroeconomic variables in an open economy context, and use that knowledge to help forecast key variables. In some areas, theory has moved forward more than practical empirics, and in others empirical techniques have moved beyond theory. The course starts with a review of key cross border relationships in the context of continuing globalization, and then moves to sections on examining key variables: Business cycles, macro-financial linkages, current account balances, exchange and interest rates.

Course Syllabus

Saturday – Sunday, June 24 – 25, 2023
The course will take place in-person only.

Registration rates (USD)

Type Rate
IIF member $195
Non-member $295
Students $25

Notes on Registration

  • To become a member of the IIF, join here
  • Cancellation policy: No refunds after June 1st; in case of summer school cancellation, the IIF liability will be limited to a refund of the registration fee only

Past Programs

2022 Machine learning techniques for forecasting: perspectives and limitations Gianluca Bontempi (virtual)
2022 Machine learning techniques for forecasting Tim Januschowski and Nikolaos Kourentzes (in-person)
2021 Nowcasting & Models for Mixed Frequency Data Massimiliano Marcellino, Bocconi University
2020 Renewable Energy Forecasting Henrik Madsen, Technical University of Denmark
2019 Probabilistic Forecasting Tilmann Gneiting, Heidelberg Institute for Theoretical Studies
2018 Economic Forecasting David Hendry, University of Oxford