This course covers a selection of methods that are widely used in modern econometric theory and practice. It aims to provide students with a grounding in statistical and probability theory, econometric theory and methods, such that students are able to do research using econometric techniques, as well as have the basis for undertaking research in econometric theory.
Most students will take this course in Year 2 after already having passed Core Econometrics in Year 1. Some students, who have enough background in economics (and only with the permission of GSC) can take the course in Year 1 instead of the Core course. This course thus assumes more previous knowledge than the Core course and advances faster.
The course will cover a range of topics that are important for applying, understanding and developing econometric tools, likely including:
- Principles of Statistical Inference
- Asymptotic Theory
- Model Selection, Shrinkage and Machine Learning
- Non-parametric and Semi-parametric Methods
- Simulation-based Methods
- Advanced Topics in Time Series
- Advanced Topics in Panel Data
- Advance Topics in Causal Inference