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 - Peter Lambert (Warwick)
Title: The Aggregate Consequences of Default Risk: Evidence from Firm-level Data
Authors: Tim Besley, Peter John Lambert, Isabelle Roland, John Van Reenen
Abstract: We examine the impact of firm-level default risk on aggregate economic performance. First, we develop a micro-to-macro model, and show that firms' perceived default risk serves as a sufficient statistic for credit frictions. We next use this model to quantify the impact of credit frictions, leveraging administrative data on the population of UK employer firms, augmented with a measure of default risk from S&Ps widely used algorithm. Between 2004-2019, credit frictions reduce aggregate output by up to 27%. This output gap due to frictions grew post-financial crisis and again after the Brexit vote. We compare partial and general equilibrium impacts, showing that approaches that abstract equilibrium wage rises significantly over-estimate output gains. Finally, reduced frictions and higher wages create both winners and losers across industries and firm-size groups, highlighting the redistributive role of the uneven access to credit.