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Econometrics Seminar

Two cogs fitting together on which public policy is written
(credits: AlexLMX/shutterstock)

This seminar, co-organised with the Centre de recherche en économie et statistique (CREST) and the Paris School of Economics (PSE), features research on theoretical and applied econometrics. The invited speakers are econometricians, with a particular focus on applied econometricians interested in methods for policy evaluations.

Half of the talks are on zoom, the other half in person (1/3 in Sciences Po, 1/3 in PSE, 1/3 in CREST). On weeks where there is no seminar, a reading group on zoom is organised with faculty and students from the three institutions to discuss recent econometrics papers.

Mondays, from 4 to 5.30 pm 

Scientific contact: Clément de Chaisemartin (Sciences Po), Elia Lapenta (CREST), Philipp Ketz (PSE) and Martin Mugnier (PSE). 
Administrative correspondent at Sciences Po: Stéphanie Berrebi

If you would like to register for the CREST-PSE econometrics seminar mailing list and receive all of the seminar announcements and links to zoom, sign up online

Upcoming seminar

Funded by the European Union (ERC, REALLYCREDIBLE, GA N°101043899). Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the European Research Council Executive Agency. Neither the European Union nor the granting authority can be held responsible for them.

FALL SEMESTER 2024

September 16th, via zoom - Kevin CHEN (Stanford)
Empirical Bayes When Estimation Precision Predicts Parameters

September 23rd, via zoom - Reading Group

September 30th, via zoom - David RITZWOLLER (Stanford)
Simultaneous Inference for Local Structural Parameters with Random Forests

October 7th, at *5 pm*, via zoom - Lihua LEI (Stanford)
Estimating Counterfactual Matrix Means with Short Panel Data
exceptional scheduling!

November 4th, via zoom - Reading Group

*November 18th, at Sciences Po* - Cristina GUALDANI (Queen Mary University London)
On the Identification of Models of Uncertainty, Learning, and Human Capital Acquisition with Sorting

December 9th (location tbd) - Marc HENRY (Penn State University)
TBA

December 16th (location tbd) - Stéphane BONHOMME (University of Chicago)
TBA

WINTER-SPRING SEMESTER 2025

The schedule will be published later this Fall.

Fall Semester 2023

*Sessions organised at Sciences Po*

September 11th - Aleksey TETENOV (University of Geneva)
Constrained Classification and Policy Learning

*September 18th* - Elie TAMER (Harvard)
Parallel Trends and Dynamic Choices

October 9th - Soonwoo KWON (Brown University)
Testing Mechanisms

October 16th - Denis CHETVERIKOV (University of California at Los Angeles)
Spectral and Post-Spectral Estimators for Grouped Panel Data Models

November 13th - Yinchu ZHU (Brandeis University)
New Possibilities in Identification of Binary Choice Models with Fixed Effects

December 4th - Jean-Jacques FORNERON (Boston University)
Occasionally Misspecified

December 11th - Guillaume POULLIOT (University of Chicago)
An Exact t-Test

Winter-Spring 2024

*Sessions organised at Sciences Po*

February 26th - Geert DHAENE (KU Leuven)
Iterated Corrections for Incidental Parameter Bias

*March 11th* - Konrad MENZEL (New York University)
Transfer Estimates for Causal Effects across Heterogeneous Sites

March 18th - Frank WINDMEIJER (Oxford)
The Falsification Adaptive Set in Linear Models with Instrumental Variables that Violate the Exclusion or Conditional Exogeneity Restriction

April 29th - Jiaying GU (University of Toronto)
Counterfactual Identification and Latent Space Enumeration in Discrete Outcome Models

May 13th - Senay SOKULLU (University of Bristol)
Counterfactual Identification and Latent Space Enumeration in Discrete Outcome Models

*TUESDAY, May 28th* - Francesca MOLINARI (Cornell)
Inference for an Algorithmic Fariness-Accuracy Frontier
(exceptional scheduling & joint with Departmental Seminar)

June 3rd - Junnan HE (Sciences Po)
Diversified Production and Market Power: Theory and Evidence from Renewables

*June 17th* - Ashesh RAMBACHAN (MIT)
From Predictive Algorithms to Automatic Generation of Anomalies