Econometrics
Read more about our research in econometrics.
Research
Our research in econometrics covers causal inference, partial identification, moment-based methods, time-series econometrics, structural breaks, and specification testing. We also work on Bayesian econometrics, nonparametric methods and machine learning, networks, and financial and high-frequency econometrics. Our theoretical research thrives from having strong links with the macroeconomics and environmental research areas, as well as with researchers outside of the department in Statistics and Alliance Manchester Business School.
Staff
- Ralf Becker - econometric theory and financial econometrics.
- Chad Brown - nonparametric estimation, deep neural networks.
- Karim Chalak - econometric theory, applied econometrics, causal inference.
- Alastair Hall - theoretical econometrics and statistical inference.
- Yizhou Kuang - Bayesian econometrics, partial identification, information economics.
- Riddhi Kalsi - labour economics, applied microeconometrics.
- Kieran Marray - applied econometrics, networks, machine learning.
- Simon Peters - applied microeconometrics, specification testing, inequality, data problems.
- Arthur Sinko - econometrics and financial econometrics, methods for high-frequency data.
- Xiaolin Sun - econometric theory, applied econometrics.
Econometrics seminar
Our regular seminar series brings researchers from the UK and internationally to Manchester to present their latest work.
Annual econometrics workshop
In the spring, the group hosts a one-day workshop consisting of invited talks on a particular theme in econometrics. Past programmes are available via the links below.