Guy Aridor

News: We're organizing a workshop through the Social Science Research Council on The Economics of Social Media, see here for more details. Please send your work!

About Me

I am an Assistant Professor of Marketing and Donald P. Jacobs Scholar at Northwestern Kellogg School of Management. I am mainly interested in understanding competition and regulatory issues in the digital economy as well as more broadly the societal impacts of digital technologies. My research uses tools from empirical industrial organization, experimental methodologies, and applied microeconomic theory in order to shed light on these questions. I am also affiliated with the CESifo Research Network and the SSRC Digital Platforms Initiative.

Previously, I got my PhD in Economics at Columbia and a B.A. in computer science, pure/applied mathematics, and economics from Boston University. Before my PhD I spent a couple of years as a software engineer at HubSpot where I worked on a bunch of fun stuff, including product experimentation tools and scaling products.

Links: CV, Google Scholar, Github
Working Papers
  1. Drivers of Digital Attention: Evidence from a Social Media Experiment.
    • Short Abstract: I study demand for social media applications by conducting an experiment where I comprehensively monitor how participants spend their time and randomize access to applications. I characterize substitution patterns and estimate a demand model with inertia. I relate the findings to antitrust issues in these markets and argue that relevant markets are broader than those considered by regulatory authorities for social media applications.
    • Full Paper: PDF, SSRN, Last Updated: December 2022
  2. The Economics of Recommender Systems: Evidence from a Field Experiment on MovieLens. Joint work with Duarte Goncalves, Ruoyan Kong, Daniel Kluver, Joseph Konstan.
    • Short Abstract: We conduct a longitudinal field experiment on the movie recommendation platform MovieLens where we randomize the set of recommended movies and elicit beliefs about unseen movies. We use the data to decompose the influence that recommender systems have on consumption choices in terms of their informational and product discovery value.
    • Full Paper: PDF, arXiv, CESifo, Last Updated: November 2022
  3. Competing Bandits: The Perils of Exploration under Competition. Joint work with Yishay Mansour, Alex Slivkins, Steven Wu.
    • Extended Abstract at EC'19
    • Short Abstract: We study the tension between exploration and competition and ask whether competition incentivizes the adoption of better exploration algorithms.
    • Full Paper: PDF, arXiv, Last Updated: December 2022
  4. Adaptive Efficient Coding: A Variational Auto-Encoder Approach. Joint work with Francesco Grechi, Michael Woodford. (Under Major Revision)
    • Short Abstract: We study a model of neural coding that is based on the structure of a variational auto-encoder. We use the model to characterize how perception adapts as the underlying environment changes.
    • Full paper: PDF, biorXiv, Last Updated: May 2020
  1. Deconstructing the Filter Bubble: User Decision-Making and Recommender Systems. Joint work with Duarte Goncalves, Shan Sikdar.
    • Proceedings of the 14th ACM Conference on Recommender Systems (RecSys '20)
    • Full Paper: Publisher Version
  2. Recommenders' Originals: The Welfare Effects of the Dual Role of Platforms as Producers and Recommender Systems. Joint work with Duarte Goncalves.
  3. The Effect of Privacy Regulation on the Data Industry: Empirical Evidence from GDPR. Joint work with Yeon-Koo Che, Tobias Salz.
    • RAND Journal of Economics (Forthcoming); Extended Abstract at EC'21
    • Full Paper: PDF, NBER
Work in Progress
  1. Shopping Alone: The Impact of The Decline of the American Mall. Joint work with Louise Guillouet, Howard Zhang.
Recorded Presentations
Press, Blogs, and Other Mentions