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
Firm Productivity and Learning in the Digital Economy: Evidence from Cloud Computing
with James Brand, Connor Finucane and Avner Kreps, 2024
Data, Privacy Laws and Firm Production: Evidence from GDPR
with Diego Jimenez Hernandez, Dean Li and Sida Peng, 2024
Do Mergers and Acquisitions Improve Efficiency: Evidence from Power Plants
with Omer Karaduman, 2024
(R&R, Journal of Political Economy)
with Kevin Cui, Sonia Jaffe, Leon Musolff, Sida Peng and Tobias Salz, 2024
Production Function Estimation with Factor-Augmenting Technology: An Application to Markups, 2022
(R&R, Econometrica)
Production Function Estimation with Imperfect Proxies, 2019
Published and Accepted Papers
Generic Machine Learning Inference on Heterogenous Treatment Effects in Randomized Experiments
with Victor Chernozhukov, Esther Duflo, Iván Fernández-Val, 2024
Econometrica, Accepted
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, February 2018
Estimating Global Bank Network Connectedness
with Francis X. Diebold, Laura Liu and Kamil Yilmaz
Journal of Applied Econometrics, July 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, May 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
Welfare Effects of Buyer and Seller Power
with Antonio Martner and Michael Rubens
Federated Learning and Privacy Protection
with Dirk Bergemann, Alessandro Bonatti and Vod Vilfort