About

Matthew Gentzkow is a Professor of Economics at Stanford University and holds the Landau Professor in Technology and the Economy position. His research focuses on applied microeconomics with a particular emphasis on media industries. Gentzkow has made significant contributions to economic thought and knowledge, recognized by the American Economic Association with the 2014 John Bates Clark Medal, awarded to the most influential economist under the age of forty. He is a fellow of the American Academy of Arts and Sciences and the Econometric Society, and serves as a senior fellow at the Stanford Institute for Economic Policy Research. Additionally, he has served as a co-editor of the American Economic Journal: Applied Economics. Gentzkow's academic background includes degrees from Harvard University, where he earned a bachelor's in 1997, a master's in 2002, and a PhD in 2004. His work has been recognized through various awards and grants, and he is involved in research examining topics such as digital addiction, social distancing policies during the pandemic, political polarization, and racial diversity exposure in U.S. metropolitan areas.

Research topics

• Political Science
• Sociology
• Computer Science
• Social psychology
• Economics
• Psychology
• Law
• Demography
• Internet privacy
• Development economics
• Medicine
• Business
• Computer Security
• Demographic economics
• Social Science
• Mathematics
• Advertising
• Market economy
• Communication
• World Wide Web
• Data science
• Virology
• Algorithm
• Chemistry

Selected publications

• Re-Examining Geographic Variation in Health and Health Care

  National Bureau of Economic Research · 2026-01-01

  reportOpen accessSenior author
  PublisherDOI

• Code for "The Effect of Deactivating Facebook and Instagram on Users’ Emotional State"

  ICPSR Data Holdings · 2026-03-31

  datasetOpen access

  We estimate the effect of social media deactivation on users’ emotional state in two large randomized experiments before the 2020 U.S. election. People who deactivated Facebook for the six weeks before the election reported a 0.060 standard deviation improvement in an index of happiness, depression, and anxiety, relative to controls who deactivated for just the first of those six weeks. People who deactivated Instagram for those six weeks reported a 0.041 standard deviation improvement relative to controls. Exploratory analysis suggests the Facebook effect is driven by people over 35, while the Instagram effect is driven by women under 25.<br>

  PublisherDOI

• Data and Code for: “What is newsworthy? Theory and evidence"

  ICPSR Data Holdings · 2026-03-27

  datasetOpen access

  We introduce a model in which a benevolent news outlet decides whether to report the realization of a state to a consumer, who pays a cost to receive it. A simple statistical rule, called a proper scoring rule, describes when the outlet should be more likely to report the realization. Using data from the US television news, we show that a particular scoring rule successfully predicts many salient features of news reporting. We show how to use this rule as a control variable to discipline tests of reporting bias, and we show that controlling for it matters in our applications.

  PublisherDOI

• How deceptive online networks reached millions in the US 2020 elections

  Nature Human Behaviour · 2026-04-06

  article
  PublisherDOI

• Data and Code for: “What is newsworthy? Theory and evidence"

  ICPSR Data Holdings · 2026-03-27

  datasetOpen access

  We introduce a model in which a benevolent news outlet decides whether to report the realization of a state to a consumer, who pays a cost to receive it. A simple statistical rule, called a proper scoring rule, describes when the outlet should be more likely to report the realization. Using data from the US television news, we show that a particular scoring rule successfully predicts many salient features of news reporting. We show how to use this rule as a control variable to discipline tests of reporting bias, and we show that controlling for it matters in our applications.

  PublisherDOI

• Code for "The Effect of Deactivating Facebook and Instagram on Users’ Emotional State"

  ICPSR Data Holdings · 2026-03-31

  datasetOpen access

  We estimate the effect of social media deactivation on users’ emotional state in two large randomized experiments before the 2020 U.S. election. People who deactivated Facebook for the six weeks before the election reported a 0.060 standard deviation improvement in an index of happiness, depression, and anxiety, relative to controls who deactivated for just the first of those six weeks. People who deactivated Instagram for those six weeks reported a 0.041 standard deviation improvement relative to controls. Exploratory analysis suggests the Facebook effect is driven by people over 35, while the Instagram effect is driven by women under 25.<br>

  PublisherDOI

• Reshares on social media amplify political news but do not detectably affect beliefs or opinions

  UNC Libraries · 2025-03-19

  articleOpen access

  We studied the effects of exposure to reshared content on Facebook during the 2020 US election by assigning a random set of consenting, US-based users to feeds that did not contain any reshares over a 3-month period. We find that removing reshared content substantially decreases the amount of political news, including content from untrustworthy sources, to which users are exposed; decreases overall clicks and reactions; and reduces partisan news clicks. Further, we observe that removing reshared content produces clear decreases in news knowledge within the sample, although there is some uncertainty about how this would generalize to all users. Contrary to expectations, the treatment does not significantly affect political polarization or any measure of individual-level political attitudes.

  PublisherDOI

• The Effect of Deactivating Facebook and Instagram on Users’ Emotional State

  National Bureau of Economic Research · 2025-04-01 · 5 citations

  reportOpen access

  We estimate the effect of social media deactivation on users' emotional state in two large randomized experiments before the 2020 U.S. election.People who deactivated Facebook for the six weeks before the election reported a 0.060 standard deviation improvement in an index of happiness, depression, and anxiety, relative to controls who deactivated for just the first of those six weeks.People who deactivated Instagram for those six weeks reported a 0.041 standard deviation improvement relative to controls.Exploratory analysis suggests the Facebook effect is driven by people over 35, while the Instagram effect is driven by women under 25.

  PublisherDOI

• Report of the Editor <i>American Economic Review: Insights</i>

  AEA Papers and Proceedings · 2025-05-01

  articleOpen access1st authorCorresponding
  PublisherOA PDFDOI

• How do social media feed algorithms affect attitudes and behavior in an election campaign?

  UNC Libraries · 2025-03-19 · 10 citations

  articleOpen access

  We investigated the effects of Facebook's and Instagram's feed algorithms during the 2020 US election. We assigned a sample of consenting users to reverse-chronologically-ordered feeds instead of the default algorithms. Moving users out of algorithmic feeds substantially decreased the time they spent on the platforms and their activity. The chronological feed also affected exposure to content: The amount of political and untrustworthy content they saw increased on both platforms, the amount of content classified as uncivil or containing slur words they saw decreased on Facebook, and the amount of content from moderate friends and sources with ideologically mixed audiences they saw increased on Facebook. Despite these substantial changes in users' on-platform experience, the chronological feed did not significantly alter levels of issue polarization, affective polarization, political knowledge, or other key attitudes during the 3-month study period.

  PublisherDOI

Recent grants

• Collaborative Research: Transparency and Misspecification in Structural Estimation

  NSF · $200k · 2020–2024

Frequent coauthors

• Jesse M. Shapiro

  Harvard University

  206 shared

• Hunt Allcott

  92 shared

• Luca Braghieri

  52 shared

• Sarah Eichmeyer

  51 shared

• Michael Sinkinson

  Yale University

  33 shared

• Isaiah Andrews

  Harvard University Press

  33 shared

• Amy Finkelstein

  National Bureau of Economic Research

  31 shared

• Stefano DellaVigna

  University of California, Berkeley

  28 shared

Education

• Ph.D., Economics

  University of California, Berkeley

  2008

• B.A., Economics

  University of Chicago

  2003

Awards & honors

• 2014 John Bates Clark Medal
• Fellow of the American Academy of Arts and Sciences
• Fellow of the Econometric Society
• 2016 Calvó-Armengol International Prize
• Alfred P. Sloan Research Fellowship