Workshop announcement

Bringing together theory, empirics, and methodology for an economic analysis of knowledge production

Science is a collective process of knowledge production. As such, science is often characterized by conflicting interests, inequalities, externalities, agency problems, and misaligned incentives. The consequences range from p-hacking and publication bias to scientific fraught, from insider clubs to hype cycles. How can the tools of economics shed light on these issues? And what recommendations can we derive for empirical methodology and for the institutions of science and science funding? We will discuss these questions from the perspectives of econometrics, microeconomic theory, and empirical microeconomics.

Workshop format

The goal of this workshop is to provide a venue for extended in-depth interaction, and the development of research agendas, formulating “big open questions,” with collaboration across field boundaries. In doing so, this workshop builds on last year’s workshop on Social foundations for statistics and machine learning.

This workshop will involve speakers from econometrics, economic theory, and empirical economics. The workshop will start with a series of tutorial lectures. The goal of these lectures is to bring all participants on the same page, especially with regards to the relevant state of research in other sub-fields. These will be followed by talks on frontier work. In these talks, the speakers will give an overview of their own work, and other related frontier work. The schedule will allow for extended discussions after each talk.

Registration (for attendees)

Speakers at this workshop have been personally invited. Attendance at the tutorial lectures and frontier talks is open to all, both in person (subject to space constraints) and online (via Zoom). To register for either in-person attendance or Zoom participation, please fill out the following form: Workshop registration

Talks will also be live-streamed and recordings will be made available, on this Youtube channel.

Logistics (for speakers)

  • Date: May 20-22, 2024.
  • Location: Skills Lab, Department of Economics, University of Oxford.
    Manor Road Building, Manor Road, Oxford, OX1 3UQ, UK
  • Accommodation: Bath Place Hotel.
  • Pub evening: The Chequers, 6:15pm, May 20 (open to all conference attendants).
  • Conference Dinner: Nuffield College, 7pm, May 21 (speakers only).
  • Contact: For logistical questions, please contact carlos.gonzalezperez@economics.ox.ac.uk.
  • Papers and Slides: Please also email these to carlos.gonzalezperez@economics.ox.ac.uk, and we will post them on this website before the conference.
  • Videos of talks will be recorded and posted online; please let us know if you don’t want to be recorded.

Confirmed speakers

  • Marco Ottaviani (micro theory) Website
  • Alessio Mitra (policy) Website
  • Carolyn Stein (applied micro) Website
  • Séverine Toussaert (behavioral) Website
  • Davide Viviano (econometrics) Website
  • Fabian Waldinger (economic history) Website [CANCELED]

Tentative Schedule

Tutorial lectures

Monday, May 20

11:45 Maximilian Kasy
Opening remarks
Slides

12:00 Marco Ottaviani
Designing Scientific Grants
Slides, Recording

14:15 Carolyn Stein
Incentives in Science
Slides, Recording

16:00 Alessio Mitra
R&I Policy Evaluation at the European Commission
Slides, Recording

Tuesday, May 21

10:30 Davide Viviano
Hypothesis Testing in Economic Research
Slides, Recording

12:45 Séverine Toussaert
Predicting social science results
Slides, Recording

[Canceled] Fabian Waldinger
Citations and Their Use in Social Science Research

Frontier talks

Tuesday, May 21

14:30 Maximilian Kasy
Optimal Pre-Analysis Plans: Statistical Decisions Subject to Implementability
Slides, Recording

16:15 Carolyn Stein
Race to the Bottom: Competition and Quality in Science
Recording

Wednesday, May 22

[Canceled] Fabian Waldinger
Measuring Science: Performance Metrics and the Allocation of Talent

12:45 Marco Ottaviani
Economics of Clinical Trials
Slides, Recording

14:30 Davide Viviano
(When) Should you adjust inference for multiple hypothesis testing?
Slides, Recording