Advanced Econometrics

• Credit value: 15 credits at Level 7
• Tutor: Walter Beckert
• Assessment: a two-hour examination in June (100%). The dissertation route is not available on this option, since it is unlikely that students would be able to write a dissertation in theoretical econometrics or empirical industrial organisation within the available timeframe

This option covers a range of modern micro-econometric approaches not covered in the main Econometrics module. With a focus both on underlying theory and applications (using R and Stata) it showcases and critically evaluates these techniques in applications in demand analysis and empirical industrial organisation. Examples are drawn from both academic research and real-world antitrust consultancy projects.

Advanced Econometrics was possibly the most useful module that I took as part of my MSc at Birkbeck. I would encourage anyone who has an interest in empirical work to take it. (Ivan Olszak, Competition and Markets Authority)

This course is the perfect course for any microeconomist serious about growing their econometric toolbox. (James Forster, CompassLexecon)

By the end of this module, you will be able to demonstrate that you can:

• understand the principles, properties and numerical methods for non-linear estimation using Maximum Likelihood (ML), Generalized Method of Moments (GMM) and panel estimators
• derive properties of estimators based on asymptotic arguments as well as the bootstrap
• understand the implications of unobserved or latent variables for the observed data and use this understanding in econometric modeling
• apply such models in the context of applied demand analysis and empirical industrial organisation
• implement estimators in R and Stata
• review and critically evaluate the application of such models in the context of academic research and real-world competition and antitrust cases (e.g. considered by the Competition and Markets Authority or the Directorate General Competition at the European Commission).