Skip to main content Skip to navigation

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

Show all calendar items

Applied Economics, Econometrics & Public Policy (CAGE) Seminar - Nina Roussille (MIT)

- Export as iCalendar
Location: S2.79

Title: Bidding for Talent: A Test of Conduct on a High-Wage Labor Market

Abstract: We propose a novel procedure for adjudicating between models of firm wage-setting conduct. Using data on workers' choice sets and decisions over real jobs from a U.S. job search platform, we first estimate workers' rankings over firms' non-wage amenities. We document three key findings: 1) On average, workers are willing to accept 12.3% lower salaries for a 1-S.D. improvement in amenities. 2) Between-worker preference dispersion is equally large, indicating that preferences are not well-described by a single ranking. 3) Augmenting differentials prevail. Following the modern IO literature, we then use those estimates to formulate a test of conduct based on exclusion restrictions. Oligopsonistic models incorporating strategic interactions between firms and tailoring of wage offers to workers' outside options are rejected in favor of simpler monopsonistic models featuring near-uniform markdowns. Misspecification has meaningful consequences: while our preferred model predicts average markdowns of 18%, others predict average markdowns of 26% (about 50% larger).

Show all calendar items