Econometrics and Data Science
Econometrics and Data Science
The Econometrics and Data Science Research Group covers a wide number of topics within the areas of modern econometric theory and applications, as well as data science in economics. On the econometrics side, the group’s research interests include: the econometrics of networks, panel data econometrics, identification and semiparametric econometrics, macroeconometrics and financial econometrics. On the data science side, the group is interested in, among other topics, machine learning, artificial intelligence, high-dimensional econometrics and text analysis. Such research is often motivated and applied to problems in other fields, including those in industrial organisation, labour economics, political economy, macroeconomics and finance.
The group organises an Econometric seminar that takes place every two weeks on Mondays at 2pm. The group also participates in the CAGE seminar in applied economics, which runs every two weeks on Tuesdays at 2pm, and engages with other seminars in the Department. Students and faculty of the group present their work in progress in two brown bag seminars which run weekly on Tuesdays and Wednesdays at 1pm. The group also co-organises annual workshops, including the Econometrics Workshop, which is a one-day event coupled with an econometrics masterclass.
Our activities
Econometrics Seminar
Monday afternoons
For faculty and PhD students at Warwick and other top-level academic institutions across the world. For a detailed scheduled of speakers please see our upcoming events.
Organisers: Kenichi Nagasawa and Ao Wang
Work in Progress Seminars
Tuesdays and Wednesdays: 1.00-2.00pm
Students and Faculty of the group present their work in progress in two brown bag seminars. For a detailed scheduled of speakers see our upcoming events.
Organiser: Chris Roth
People
Academics
Academics associated with the Reseach Group Name research group are:
Events
CWIP Workshop - Anjali Adukia (Chicago)
Title: Separation of Church and State Curricula? Examining Public and Religious Private School Textbooks (with Emileigh Harrison)
Abstract: Curricular materials not only impart knowledge but also instill values and shape collective memory. Growth in U.S. school choice programs has increased public funds directed to religious schools, but little is known about what is taught. We examine textbooks from public schools in Texas and California and from religious private and home schools, applying and improving upon artificial intelligence tools to measure topics, values, representation, and portrayal over time. Political polarization suggests a narrative of divergence, but our analysis reveals meaningful parallels between the public school collections overall, while religious textbooks differ notably, featuring less female representation, characters with lighter skin, more famous White individuals, and differential portrayal of topics such as evolution and religion. Important similarities, however, also emerge: for example, each collection portrays females in contexts that are more positive but less active and powerful than males, and depicts the U.S. founding era and slavery in similar contexts.