Econometrics with Data Science

Background

As we enter the big data era, there is a boom in the development of modern techniques, such as high-dimensional econometrics, approaches for non-Euclidean data structures, and machine learning methods. The research cluster of Econometrics with Data Science (EwDS) embraces this trend and brings together researchers with expertise in theoretical econometrics, applied econometrics, forecasting, and various data science techniques, including text analysis, indicator saturation, functional data analysis, and vine copula.

The cluster members have published their research in the world-leading academic journals: Annals of Statistics, Journal of Econometrics, Journal of Business and Economic Statistics, European Journal of Operational Research, Journal of Applied Econometrics, Journal of Financial Econometrics, Econometric Review, and International Journal of Forecasting, among others.

Our Members

Academics at Reading:

Doctoral Researchers:

  • Hamed Alaidarous
  • Omar Alarfaj
  • Baker Audeh
  • Albert Chongo
  • Wei Hu
  • Minko Markovski
  • Lillian Mookodi
  • Winnie Muangi
  • Okiemua Okoror
  • Stephen Opata
  • Jingqi Pan
  • Philip Ramirez
  • Hafsa Shoukat
  • Simeon Simeonov
  • Yi Sun
  • Elly Twineyo

Visiting Member:

  • Michael Kunkler

We are a newly established cluster (est. March 2023) and welcome new members (from any department at the University of Reading) whose research involves econometrics and/or data science. If you are interested in joining us, please contact the cluster coordinator, Shixuan Wang (shixuan.wang@reading.ac.uk).

Publications

Econometrics

Forecasting

Text Analysis

Indicator Saturation

Functional Data Analysis

Funded Projects

Improving Staff Retention at the RBFT: Econometric Data Analytics, Probabilistic Forecasting and Management Intelligence

(Team: Pete Sandham, People Directorate, RBFT; Shixuan Wang, Department of Economics, UoR; Rita Fontinha, Henley Business School; Eghosa Bazuaye, RBFT; Arran Rogers, RBFT; and Cindy Kouris, RBFT)

The team seeks to reform the Trust’s approach to staff retention at the Royal Berkshire NHS Foundation Trust (RBFT). They will research, test and deliver a solution that enables them to model and predict the likelihood of colleagues leaving the Trust in the future. Through the project, the team aims to create interventions to support workforce retention. This project is funded by Collaborative Innovation Fund.

Events

    • [In-person Conference] We are excited to announce the 1st Conference “Econometrics with Data Science” is going to take place at London Road Campus, University of Reading on 16th September 2024, in an in-person format. See the details on the conference webpage.

  • [Online Workshop] How to use ChatGPT to facilitate academic research? – Yuhao Mu (Renmin University of China), April 19, 12 noon via Teams. Yuhao’s slides are here.

If you would like to receive information about our future events, please contact the cluster coordinator, Shixuan Wang (shixuan.wang@reading.ac.uk).

Research Led Teaching