I am an Assistant Professor at the MIT Sloan Applied Economics Group and a Faculty Research Fellow at the National Bureau of Economic Research. Prior to joining MIT Sloan, I was a Postdoctoral Researcher at Microsoft Research. I received my PhD in economics from MIT in 2020.
I work in the field of empirical industrial organization. My research focuses on firm productivity, use of digital technologies by firms, antitrust, and productivity effects of generative AI.
Email: mdemirer at mit.edu
Working Papers
Writing Code vs. Shipping Code: Productivity Effects Across Generations of AI Coding Tools
with Leon Mussolff and Liyuan Yang, 2026
Welfare Effects of Buyer and Seller Power
with Michael Rubens, 2025
Firm Productivity and Learning with Digital Technologies: Evidence from Cloud Computing
with James Brand, Connor Finucane and Avner Kreps, 2025
Chaining Tasks, Redefining Work: A Theory of AI Automation
with John J. Horton, Nicole Immorlica, Brendan Lucier, and Peyman Shahidi, 2025
Data, Privacy Laws and Firm Production: Evidence from GDPR
with Diego Jimenez Hernandez, Dean Li and Sida Peng, 2024
(Conditionally Accepted, Journal of Political Economy)
Published and Accepted Papers
The Emerging Market for Intelligence: Pricing, Supply and Demand for LLMs
with Andrey Fradkin, Nadav Tadelis and Sida Peng, 2026
Journal of Economic Perspectives, Forthcoming
Production Function Estimation with Factor-Augmenting Technology: An Application to Markups, 2026
Econometrica, Forthcoming
Do Mergers and Acquisitions Improve Efficiency: Evidence from Power Plants
with Omer Karaduman, 2025
Journal of Political Economy, Forthcoming
with Kevin Cui, Sonia Jaffe, Leon Musolff, Sida Peng and Tobias Salz
Management Science, 2026
Generic Machine Learning Inference on Heterogenous Treatment Effects in Randomized Experiments
with Victor Chernozhukov, Esther Duflo, Iván Fernández-Val
Econometrica, 2025
Drug Rebates and Formulary Design: Evidence from Statins on Medicare Part D
with Alex Olssen, 2023
Journal of Political Economy: Microeconomics, Conditionally Accepted
Semi-Parametric Efficient Policy Learning with Continuous Actions
with Vasilis Srygkanis, Greg Lewis, Victor Chernozhukov
NeurIPS, 2019
Double/Debiased Machine Learning for Treatment and Structural Parameters
with Victor Chernozhukov, Denis Chetverikov, Esther Duflo, Christian Hansen, Whitney Newey, and James Robins
The Econometrics Journal, 2018
Estimating Global Bank Network Connectedness
with Francis X. Diebold, Laura Liu and Kamil Yilmaz
Journal of Applied Econometrics, 2017
Double/Debiased/Neyman Machine Learning of Treatment Effects
with Victor Chernozhukov, Denis Chetverikov, Esther Duflo, Christian Hansen and Whitney Newey
American Economic Review P&P, 2017
Work in Progress
How On-Demand Inputs Change Firm Production and Business Dynamism: The Case of Cloud Computing
with James Brand and Rebekah Dix
Datacenter Entry and Congestion in the US Electricity Markets
with El Hadi Caoui, Andrew Stack and Sophie Calder-Wang
Federated Learning and Privacy Protection
with Dirk Bergemann, Alessandro Bonatti and Vod Vilfort