The following courses provide training in methods for those studying economics and related subjects.
Applied Health Econometrics
Gain an in-depth overview into the application of econometric techniques to health economics. The focus is on producing i) good descriptive analysis and ii) casual inference. The entire course is lab-based and mixes computer exercises with traditional lectures
Factor Models in Time Series with Applications in Macroeconomics and Finance
A graduate level course about “big data” analysis. It introduces methods and techniques for extracting meaningful and useful information from large panels of time series.
Intermediate Econometrics
This course aims to build a solid, comprehensive understanding of the use of the regression model when one progresses from the Classical Linear Regression Model, with its strong and unrealistic assumptions, and addresses the issues that researchers encounter in practice.
Real Analysis
A considerable part of economic theory is difficult to follow without a strong background in Real Analysis. This course will introduce students to concepts of modern analysis such as continuity, metric spaces, compactness, convexity and integration and will show the connections to economic theory. Note: this course has a week-long online component prior to the start of the two-week on-campus component.
Statistical Methods in Risk Management
A self-contained introduction to statistical methods in risk management. This course combines theory and implementation, and emphasises on hands-on experience working with real financial data.
Tools for Macroeconomists: The Essentials
A hands-on graduate-level course teaching key techniques to solve, analyse, and estimate macroeconomic models. It teaches the key building blocks of numerical analysis and shows how to use them to solve dynamic stocastic models.
Tools for Macroeconomists: Advanced Tools
Offering a higher level of understanding in the state-of-the-art techniques used to solve and analyse advanced macroeconomic models. In particular, models with heterogeneous agents and models with inequality constraints.