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 - Yang Zhong (Warwick)
Title: Working under Distractions
Abstract: Distractions are pervasive in today’s workplaces, from noisy open-plan offices to digital interruptions. Using an incentivized laboratory experiment, I study the effects of distractions on performance and well-being, elicit willingness to pay to avoid distractions, and validate questionnaire items on resilience in working under distractions. I then incorporate these validated items in a representative Dutch survey panel. I obtain four main results. First, despite having little impact on performance in the lab, distractions are detrimental to individuals' self-reported well-being while working. Second, many individuals are willing to pay to eliminate distractions, and this willingness to pay is negatively correlated with the change in well-being. Third, individual heterogeneity in the impact of distractions on well-being can be captured by questionnaire items. Fourth, resilience to distractions strongly predicts income and job satisfaction in the representative survey data, even conditional on education, sector, and other personality traits.