MICROECONOMETRICS CLASS OF 2024 CONFERENCE

MICROECONOMETRICS CLASS OF 2024 CONFERENCE

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Center Title

September 27-28, 2024
Department of Economics
Northwestern University
Kellogg Global Hub, Room 1410

Conference Organizer
Eric Auerbach, Northwestern University
Matt Masten, Duke University


CONFERENCE PROGRAM


SPEAKERS


SESSION 1
Nonparametric Identification in Generalized Separable Models
Wan Zhang, Nankai University

An Identification-and Dimensionality-Robust Test for Instrumental Variables Models
Manu Navjeevan, Texas A&M University

SESSION 2
Treatment Effects of Multi-Valued Treatments in Hyper-Rectangle Model
Xunkang Tian, ERUNI Open Research Prague

Estimating Social Network Models with MissLinear Estimation of Global Average Treatment Effects (with Paul Niehaus)
Stefan Faridani, Georgia Institute of Technology

SESSION 3
Testing Sign Agreement

Deborah Kim, University of Warwick

Inference on Union Bounds
Xinyue Bei, University of Texas – Austin

SESSION 4
Identification and Estimation of Market Size in Discrete Choice Demand Models

Linqi Zhang, Chinese University of Hong Kong

Estimating the Effect of Education on Health via a Binary Model with Endogeneity in the Absence of Exclusion Restrictions
Nan Zhi, University of Florida

SESSION 5
Quasi-Bayes in Latent Variable Models

Sid Kankanala, University of Chicago, Booth School of Business

Empirical Bayes When Estimation Precision Predicts Parameters
Kevin (Jiafeng) Chen, Stanford University

SESSION 6
Mediation Analysis in Difference-in-Differences Designs

Timo Schenk, Aarhus University and Erasmus University Rotterdam

Estimating the Moments and the Distribution of Heterogeneous Marginal Effects Using Panel Data
Vladislav Morozov, University of Bonn

Moment Restrictions in Nonlinear Panel Data Models with Feedback (with Stéphane Bonhomme and Bryan Graham)
Kevin Dano, Princeton University

SESSION 7
Dynamic Treatment Effect Estimation with Interactive Fixed Effects and Short Panels (with Nicholas Brown)

Kyle Butts, University of Arkansas

A Linear Regression Model for Non-Oriented Dyadic Data with Interactive Individual Effects
Yassine Sbai Sassi, New York University