Course information

Instructor: Eric Swanson (University of California, Irvine)
Dates:  24-28 August 2026
Hours: 15:00 to 18:30 CEST 
Format: In person

Intended for

Academic researchers and policy analysts who are interested in using high-frequency financial market data to study the effects of conventional and unconventional monetary policies on domestic and foreign financial markets and their economies.

Prerequisites

A basic familiarity with macroeconomics, econometrics, probability, and statistics at the advanced undergraduate level.

Overview

Estimating causal effects in macroeconomics is often very difficult, because issues of omitted variables or reverse causality are often very plausible. High-frequency changes in financial markets around significant events (e.g., FOMC or OPEC announcements) represent one of the most appealing methods of causal identification. By focusing on narrow windows of time around these significant events, the problems of omitted variables and reverse causality are essentially eliminated, because they are dominated by the importance of the significant event itself within that narrow time window. These financial market changes can then be used in high-frequency OLS regressions to measure causal effects in financial markets, or as an instrumental variable for lower-frequency (e.g., monthly or quarterly) changes to measure causal effects in macroeconomic VARs or local projections regressions.

The goal of this course is to familiarize students with all the main tools using high-frequency event studies for causal identification in macroeconomic applications. We will place a heavy emphasis on examples from highly-cited research papers throughout the course. 

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