Seminars , Courses and Events Quantitative Economics
MLSE Seminars
MLSE is a (mostly) bi-weekly seminar to foster cooperation between the Department of Microeconomics and Public Economics and the Department of Quantitative Economics. It aims to give researchers the opportunity to present their ongoing work and to facilitate cooperation
Website of MLSE : https://www.maastrichtuniversity.nl/mlse-seminar
In case you want to follow the seminar online, please let us know. Also let us know whenever you know people that would like to receive these emails.
If you would like to present in this seminar series, please send an email to either @Gonzalez Fernandez, Pedro (ALGEC) or @Triêu, Anh (KE)
On the 1st of July, Pedro will present his work at the MLSE Seminar: Regulating Information
Date and time: July 1st, 14:00-15:00
Authors: Pedro Gonzalez-Fernandez, Stefan Terstiege, and Elias Tsakas
Title: Regulating Information
Abstract: Economic agents often seek to acquire information before taking an important action, but in many domains, gathering this information requires approval from a regulator. This paper develops a model in which an agent designs an experiment to inform his decision, but can only implement it if a regulator authorizes it ex ante. We characterize the agent’s optimal experiment under this approval constraint and show that, whenever the regulator rejects full revelation, the agent strategically reduces informativeness in the states where their disagreement is strongest. We then extend the model to settings with multiple regulators, comparing sequential and collective approval mechanisms. The analysis yields predictions for how institutional structure shapes access to information, with applications to clinical trials, data privacy, and ethics boards.
Econometric Seminars Programme 2025
Author: Sofia Borodich Suarez (University of Luxembourg and UM)
Wednesday 14 May 1500 PM -16:00 PM
Title: Robust Priors in Non-linear Panel Data Models - Estimating Average Marginal Effects.
Abstract: In a seminal paper, Arellano and Bonhomme (“Robust priors in nonlinear panel data models,” Econometrica, 2009) propose priors to simultaneously reduce the bias for estimating the common parameters (theta_0) and the average marginal effects (M) in non-linear panel data models with fixed effects. However, we show that the Arellano-Bonhomme (AB) priors are not simultaneously bias reducing by proving mathematically that although the AB priors always reduce the bias for estimating theta_0, they do not always reduce the bias for estimating M. E.g., in the static panel probit model or, generally, for dynamic panel data models, the AB priors only reduce the bias for estimating theta_0 but not for estimating M, whereas in the static panel logit and Poisson models the AB priors simultaneously reduce the bias for estimating theta_0 and M. Furthermore, we construct priors that we prove are simultaneously bias reducing for general non-linear panel data models including panel probit, and show numerically in a simulation study that the AB priors for a panel probit model do not reduce the bias for estimating M — the bias of the estimator of M based on the AB priors remains comparable to the bias of the maximum likelihood estimator of M even when the panel is long — whereas the priors that we construct do.
This is joint work with her supervisors, Martin Schumann and Gautam Tripathi. It appears in part in print in the forthcoming (Arellano, M., Bonhomme, S., Borodich Suarez, S., Schumann, M., Shi, X., and Tripathi, G. (2025): "Erratum to “Robust Priors in Nonlinear Panel Data Models”," Econometrica, 93, 3 , doi: 10.3982/ECTA23441, in production).
For previous seminars, please see our archive
EPICENTER Summer Course on Epistemic Game Theory
In 2025, our EPICENTER will organize the tenth
EPICENTER Summer Course on Epistemic Game Theory
Reasoning in Static and Dynamic Games
Maastricht University, June 30 – July 11, 2025
Website: Detailed information about the course, and how to register, can be found on the course website https://www.epicenter.name/summercourse/ .
About the course: Are you interested in game theory, and its relation to human reasoning and decision making? Then this is the perfect course for you.
In this course we explore game theoretic situations from an epistemic perspective, by zooming in on the reasoning of a player before he makes a decision in the game. This reasoning does not only concern the possible choices of his opponents, but also the beliefs that his opponents may have before they make a choice.
The course consists of three parts: standard reasoning in static games, cautious reasoning in static games, and reasoning in dynamic games.
In static games, the players only make one choice, and choose in complete ignorance of the other players' choices. For standard reasoning we focus on the central reasoning concept of common belief in rationality, and investigate what happens if we add a correct beliefs assumption.
Cautious reasoning means thar a player, before he makes a choice himself, does not completely discard any opponent's choice from consideration. For this part we will investigate different variants of common belief in rationality.
In dynamic games, a player may have to make more than one choice, and may fully or partially observe what other players have done before he makes a choice himself. We explore backward and forward induction reasoning, embodied by the reasoning concepts of common belief in future rationality and common strong belief in rationality.
The course is open to advanced bachelor students, master students, PhD students and researchers all over the world.
Book: This course is based on the textbook Epistemic Game Theory: Reasoning and Choice by Andrés Perea, which was published by Cambridge University Press in 2012.
Difference with previous edition: In 2024 we provided a course on incomplete information, unawareness and psychological games. To follow this year’s course, it is not necessary to have followed the previous edition. In fact, you should be able to follow this year’s course without having any prior knowledge about game theory. The course is completely self-contained.
Forward: Please forward this message to all people whom you think might be interested.
Questions? Please send an E-mail to Andrés Perea at: course@epicenter.name