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 - Juliana Cunha Carneiro Pinto
Title: Transitory health shocks, human capital and crime: Evidence from Linked Administrative Data in Brazil.
Abstract: This paper provides the first causal evidence on the effects of dengue fever on educational and
behavioural outcomes. Using matched administrative data linking official dengue notifications,
school census records, and police reports for the universe of public secondary school students in
Minas Gerais, Brazil, we estimate the impact of individual health shocks on grade progression,
dropout, and subsequent involvement in crime. Identification exploits within-school and within-
neighbourhood variation in dengue exposure over an eleven-year period, with rich student and
classroom controls and detailed temperature measures. We find that dengue infections during
the school year increase grade retention by about 5 percent and school dropout by roughly
4 percent relative to baseline means. Linking the same students to police records, we show that
dengue infections also raise criminal involvement by 9–12 percent in the following years, driven
primarily by property and violent offenses. The results reveal that even short-lived illnesses can
have lasting consequences for human capital formation and youth behaviour, underscoring the
broader social costs of infectious diseases and the potential gains from targeted vaccination and
vector-control policies.