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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

Events

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CWIP (CAGE Work in Progress) Workshop - Ludovica Gazze

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Location: S2.79

Title: People, places or houses? A decomposition of households' carbon emissions in the UK (with Lucie Gadenne, Peter Levell, Davide Sansone)

Abstract: Understanding the determinants of households' greenhouse gases (GHG) emissions is key to designing successful decarbonization policies. We examine the role of household, house, and place in explaining household GHG emissions from transport and energy in the UK. Using detailed household panel data on housing characteristics enables us to speak to the determinants of both household and place effects and investigate the effects of different policy scenarios (e.g., revenue recycling from carbon taxes). We exploit the panel dimension of our data using a "mover design" approach to disentangle contextual factors, such as place-based drivers of emissions and house characteristics, from household-level determinants.

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