Announcing MLESC '24!

We are excited to welcome this year's presenter's for the Machine Learning in Economics Summer Conference, which will be held in Chicago, August 6-7, 2024. Submit your paper for the 2024 Conference here.

Program Description:

Sanjog Misra of the University of Chicago Booth School of Business, Sendhil Mullainathan of the University of Chicago Booth School of Business, Annie Liang of Northwestern University, Jann Spiess of Stanford University, and Ashesh Rambachan of Massachusetts Institute of Technology are organizing the first Machine Learning in Economics Summer Conference (MLESC). 

The MLESC conference brings together researchers working at the intersection of machine learning and economics. It will focus on research studying how machine learning methods (e.g., supervised and unsupervised learning algorithms, machine vision, text analysis) may be used to tackle existing questions and open new directions in fields like behavioral economics, applied microeconomics, development, and macroeconomics. Both empirical and theoretical papers are welcome. 

Application:

The MLESC conference will be held at the University of Chicago on August 6–7, 2024. 


Please submit papers here. Submission of full drafts is encouraged, but extended abstracts of manuscripts that will be available by the time of the conference are possible. The submission deadline is April 12th, 2024. Please contact Lauren Doan if you have any questions. 


The conference will take place after this year’s Machine Learning in Economics Summer Institute, which will be held on August 1–5 and consist of workshops and tutorials for graduate students.

Graduate students admitted to MLESI will be in attendance at the conference.
Graduate students interested in applying for MLESI can find application materials here.


Schedule

Tuesday

 08:00am-09:00am  Breakfast
 09:00am-09:45am   Jacob Conway | Journalist Ideology and the Production of News: Evidence from Movers 
 09:45am-10:30am  Hadar Avivi | Are Patent Examiners Gender Neutral?
 10:30am-11:00am  Break
 11:00am-11:45am  Roshni Sahoo | Learning Targeted Transfers
 11:45am-12:30pm  Lindsey Raymond | The Market Effects of Algorithms
 12:30pm-01:30pm  Lunch
 01:30pm-02:15pm  Szymon Sacher | Inference for Regression with Variables Generated from Unstructured Data
 02:15pm-03:00pm  Jose Montiel Olea | On the Testability of the Anchor-Words Assumption in Topic Models
 03:00pm-03:30pm  Break
 03:30pm-04:15pm  Daniel Martin | AI Oversight and Human Mistakes: Evidence from Centre Court
 04:15pm-05:00pm  Keaton Ellis | The Productivity of Theories of Choice Under Uncertainty

 

Wednesday

 08:00am-09:00am  Breakfast
 09:00am-09:45am   Joseph Leland Bybee | The Ghost in the Machine: Generating Beliefs with Large Language Models 
 09:45am-10:30am  Carlos Cinelli | Long Story Short: Omitted Variable Bias in Casual Machine Learning
 10:30am-11:00am  Break
 11:00am-11:45am  Christopher Mills | The Impact of Algorithmic Tools on Child Protection: Evidence from a Randomized Controlled Trial
 11:45am-12:30pm  Max Tabord-Meehan | Testing Fairness-Improvability of Algorithms
 12:30pm-01:30pm  Lunch

Conference Organizers

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Annie Liang

Assistant Professor of Economics, Northwestern University

Annie Liang
Jann Spiess Placeholder

Jann Spiess

Assistant Professor of Operations, Information, and Technology, Stanford Graduate School of Business

Jann Spiess
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Ashesh Rambachan

Assistant Professor of Economics, Massachusetts Institute of Technology

Ashesh Rambachan

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