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Susan Athey
Susan Athey
Professor, Economics
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+1 (650) 725-1813
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SusanAthey
The Economics of Technology Professor
Professor of Economics (by courtesy), School of Humanities and Sciences
Senior Fellow, Stanford Institute for Economic Policy Research
Academic Area: 
Economics

Additional Administrative Titles

Director, Golub Capital Social Impact Lab
Associate Director, Stanford Institute for Human-Centered Artificial Intelligence

Research Statement

Susan Athey’s research is in the areas of industrial organization, microeconomic theory, and applied econometrics. Her current research focuses on the design of auction-based marketplaces and the economics of the internet, primarily on online advertising and the economics of the news media. She has also studied dynamic mechanisms and games with incomplete information, comparative statics under uncertainty, and econometric methods for analyzing auction models.

Research Interests

  • Economics of the internet
  • Economics of the news media
  • Platform markets
  • Online advertising
  • Internet search
  • Econometrics and machine learning
  • Big data
  • Math-based currency
  • Industrial organization

Teaching Statement

Professor Athey teaches classes about the economics of the internet and digital markets, platform markets, and internet search.

Bio

Susan Athey is the Economics of Technology Professor at Stanford Graduate School of Business. She received her bachelor’s degree from Duke University and her PhD from Stanford, and she holds an honorary doctorate from Duke University. She previously taught at the economics departments at MIT, Stanford and Harvard. Her current research focuses on the economics of digitization, marketplace design, and the intersection of econometrics and machine learning.  She has worked on several application areas, including timber auctions, internet search, online advertising, the news media, and the application of digital technology to social impact applications. As one of the first “tech economists,” she served as consulting chief economist for Microsoft Corporation for six years, and now serves on the boards of Expedia, Lending Club, Rover, Turo, and Ripple, as well as non-profit Innovations for Poverty Action.  She also serves as a long-term advisor to the British Columbia Ministry of Forests, helping architect and implement their auction-based pricing system. She is the founding director of the Golub Capital Social Impact Lab at Stanford GSB, and associate director of the Stanford Institute for Human-Centered Artificial Intelligence.

Academic Degrees

  • PhD, Economics, Stanford Graduate School of Business, 1995
  • BA, Economics, Computer Science, and Mathematics, Duke University, 1991

Academic Appointments

  • Professor, Stanford University Graduate School of Business , 2013-present
  • Professor of Economics, Harvard, 2006-2012
  • Holbrook Working Professor of Economics, Stanford, 2004-2006
  • Associate Professor of Economics, Stanford, 2001-2003
  • Castle Krob Career Development Associate Professor of Economics, MIT, 1998-2001
  • Assistant Professor of Economics, MIT, 1995-1997

Awards and Honors

  • Von Neumann Prize, Rajk László College for Advanced Studies, 2019
  • Fellow, International Association of Applied Econometrics, elected 2019
  • Fellow, Game Theory Society, elected 2017
  • Jean-Jacques Laffont Prize, 2016
  • Codirector, Digital Business: Data, Decisions & Platform Strategy Initiative, Stanford GSB, 2015
  • Spence Faculty Fellow, Stanford GSB, 2013-2014
  • Fellow, Society for the Advancement of Economic Theory, 2013
  • Member, National Academy of Science, elected 2012
  • Honorary degree, Duke University, 2009
  • Fellow, American Academy of Arts and Sciences, elected 2008
  • John Bates Clark Medal, 2007
  • Fellow, Econometric Society, elected 2004
  • Guggenheim Faculty Scholar, Stanford University, 2004-2006
  • Elaine Bennett Research Award, 2001
  • Sloan Foundation Research Fellow, 2000
  • Undergraduate Economics Association Teaching Award, 1995-1996
  • Review of Economic Studies Tour, 1995
  • Stanford University Lieberman Fellow, 1994-1995
  • State Farm Dissertation Award in Business, 1994
  • National Science Foundation Graduate Fellowship, 1991-1994
  • Jaedicke Scholar, Stanford Graduate School of Business, 1992-1993
  • Mary Love Collins Scholarship, Chi Omega Foundation, 1991-1992
  • Duke University Alice Baldwin Memorial Scholarship, 1990-1991

Publications

Journal Articles

Economists (and Economics) in Tech Companies
Susan Athey, Michael Luca. Journal of Economic Perspectives. December 2019, Vol. 33, Issue 1, Pages 209-230.
Ensemble Methods for Causal Effects in Panel Data Settings
Susan Athey, Mohsen Bayati, Guido W. Imbens, Zhaonan Qu. American Economic Review Papers and Proceedings. May 2019, Vol. 109, Pages 65-70.
Generalized Random Forests
Susan Athey, Stefan Wager, Julie Tibshirani. Annals of Statistics. 2019, Vol. 47, Issue 2, Pages 1148-1178.
Sampling-based vs. Design-based Uncertainty in Regression Analysis
Alberto Abadie, Susan Athey, Guido W. Imbens, Jeffrey M. Wooldridge. Econometrica (forthcoming). 2019.
SHOPPER: A Probabilistic Model of Consumer Choice with Substitutes and Complements
Susan Athey, Francisco J. R. Ruiz, David M. Blei. Annals of Applied Statistics (forthcoming). 2019.
Estimation and Inference of Heterogeneous Treatment Effects using Random Forests
Stefan Wager, Susan Athey. Journal of the American Statistical Association. June 6, 2018.
Estimating Heterogeneous Consumer Preferences for Restaurants and Travel Time Using Mobile Location Data
Susan Athey, David Blei, Robert Donnelly, Francisco Ruiz, Tobias Schmidt. American Economic Review Papers and Proceedings. May 2018, Vol. 108, Pages 64-67.
The Impact of Consumer Multi-homing on Advertising Markets and Media Competition
Susan Athey, Emilio Calvano, Joshua S. Gans. Management Science. April 2018, Vol. 64, Issue 4, Pages 1574-1590.
Approximate Residual Balancing: Debiased Inference of Average Treatment Effects in High Dimensions
Susan Athey, Guido W. Imbens, Stefan Wager. Journal of the Royal Statistical Society-Series B. February 18, 2018, Vol. 80, Issue 4, Pages 597-623.
Stable Predictions across Unknown Environments
Susan Athey, Kun Kuang. Knowledge Discovery and Data Mining. 2018.
Exact P-values for Network Interference
Susan Athey, Dean Eckles, Guido W. Imbens. Journal of the American Statistical Association. November 13, 2017, Vol. 113, Issue 521, Pages 230-240.
Estimating Average Treatment Effects: Supplementary Analyses and Remaining Challenges
Susan Athey, Guido W. Imbens, Thai Pham, Stefan Wager. American Economic Review. May 2017, Vol. 107, Issue 5, Pages 278-81.
The State of Applied Econometrics: Causality and Policy Evaluation
Susan Athey, Guido W. Imbens. Journal of Economic Perspectives. May 2017, Vol. 31, Issue 2, Pages 3-32.
Yuliy Sannikov: Winner of the 2016 Clark Medal
Susan Athey, Andrzej Skrzypacz. Journal of Economic Perspectives. May 2017, Vol. 31, Issue 2, Pages 237-256.
The Value of Information in Monotone Decision Problems
Susan Athey, Jonathan Levin. Research in Economics ( in press ). February 16, 2017.
Beyond Prediction: Using Big Data for Policy Problems
Susan Athey. Science. February 3, 2017, Vol. 335, Issue 6324, Pages 483-485.
A Measure of Robustness to Misspecification
Susan Athey, Guido W. Imbens. American Economic Review. May 1, 2015, Vol. 105, Issue 5, Pages 476–480.
Dynamics of Open Source Movements
Susan Athey, Glenn Ellison. Journal of Economics & Management Strategy. April 2014, Vol. 23, Issue 2, Pages 294–316.
An Efficient Dynamic Mechanism
Susan Athey, Ilya Segal. Econometrica. November 2013, Vol. 81, Issue 6, Pages 2463–2485.
Set-Asides and Subsidies in Auctions
Susan Athey, Dominic Coey, Jonathan Levin. American Economic Journal: Microeconomics. 2013, Vol. 5, Issue 1, Pages 1–27.
Comparing Open and Sealed Bid Auctions: Theory and Evidence from Timber Auctions
Susan Athey, Jonathan Levin, Enrique Seira. Quarterly Journal of Economics. 2011, Vol. 126, Issue 1, Pages 207–257.
Position Auctions with Consumer Search
Susan Athey, Glenn Ellison. Quarterly Journal of Economics. 2011, Vol. 126, Issue 3, Pages 1213–1270.
The Impact of Targeting Technology on Advertising Markets and Media Competition
Susan Athey, Joshua S. Gans. American Economic Review. May 2010, Vol. 100, Issue 2, Pages 608–613.
Skewed Bidding in Per Per Auction Models of Online Advertising
Nikhil Agarwal, Susan Athey, David Yang. American Economic Review. 2009, Vol. 99, Issue 2, Pages 441–447.
Collusion with Persistent Cost Shocks
Susan Athey, Kyle Bagwell. Econometrica. May 2008, Vol. 76, Issue 3, Pages 493–540.
Discrete Choice Models with Multiple Unobserved Choice Characteristics
Susan Athey, Guido W. Imbens. International Economic Review. December 2007, Vol. 48, Issue 4, Pages 1159–1192.
Efficiency in Repeated Trade with Hidden Valuations
Susan Athey, David A. Miller. Theoretical Economics. September 2007, Vol. 2, Issue 3, Pages 299–354.
Designing Efficient Mechanisms for Dynamic Bilateral Trading Games
Susan Athey, Ilya Segal. American Economic Review. May 2007, Vol. 97, Issue 2, Pages 131–136.
What Does Performance in Graduate School Predict? Graduate Economics Education and Student Outcomes
Susan Athey, Larry Katz, Alan Krueger, Steve Levitt, James Poterba. American Economic Review. May 2007, Vol. 97, Issue 2, Pages 512–520.
Nonparametric Approaches to Auctions
Susan Athey, Philip A. Haile. Handbook of Econometrics. 2007, Vol. 6, Issue A, Pages 3847–3965.
Identification and Inference in Nonlinear Difference-In-Difference Models
Susan Athey, Guido Imbens. Econometrica . March 2006, Vol. 74, Issue 2, Pages 431–497.
The Optimal Degree of Discretion in Monetary Policy
Susan Athey, Andrew Atkeson, Patrick J. Kehoe. Econometrica . September 2005, Vol. 73, Issue 5, Pages 1431–1475.
Collusion and Price Rigidity
Susan Athey, Kyle Bagwell, Chris Sanchirico. Review of Economic Studies. April 2004, Vol. 71, Issue 2, Pages 317-349.
The Impact of Information Technology on Emergency Health Care Outcomes
Susan Athey, Scott Stern. RAND Journal of Economics. September 2002, Vol. 33, Issue 3, Pages 399-432.
Monotone Comparative Statics Under Uncertainty
Susan Athey. Quarterly Journal of Economics. February 2002, Vol. 117, Issue 1, Pages 187-223.
Identification of Standard Auction Models
Susan Athey, Philip Haile. Econometrica. 2002, Vol. 70, Issue 6, Pages 2107 - 2140.
Optimal Collusion with Private Information
Susan Athey, Kyle Bagwell. RAND Journal of Economics. September 2001, Vol. 32, Issue 3, Pages 428-465.
Single Crossing Properties and the Existence of Pure Strategy Equilibria in Games of Incomplete Information
Susan Athey. Econometrica. July 2001, Vol. 69, Issue 4, Pages 861-889.
Organizational Design: Decision Rights and Incentive Contracts
Susan Athey, John Roberts. American Economic Review. May 2001, Vol. 91, Issue 2, Pages 200-205.
Information and Competition in U.S. Forest Service Timber Auctions
Susan Athey, Jonathan Levin. Journal of Political Economy. April 2001, Vol. 109, Issue 2, Pages 375-417.
Investment and Market Dominance
Susan Athey, Armin Schmutzler. RAND Journal of Economics. March 2001, Vol. 32, Issue 1, Pages 1-26.
Mentoring and Diversity
Susan Athey, Chris Avery, Peter Zemsky. American Economic Review. September 2000, Vol. 90, Issue 4, Pages 765-786.
Information Technology and Training in Emergency Call Centers
Susan Athey, Scott Stern. Industrial Relations Research Association. January 3, 1999, Pages 53-60.
Product and Process Flexibility in an Innovative Environment
Susan Athey, Armin Schmutzler. RAND Journal of Economics. December 1995, Vol. 26, Issue 4, Pages 557-574.

Book Chapters

The Impact of Machine Learning on Economics
Susan Athey. The Economics of Artificial Intelligence: An Agenda (forthcoming). University of Chicago Press, January 2018.
The Nature and Incidence of Software Piracy: Evidence from Windows
Susan Athey, Scott Stern. Economic Analysis of the Digital Economy (National Bureau of Economic Research Conference Report). Chicago: University of Chicago Press, April 1, 2015, Pages 443–447.

Other Publications

Learning in Games with Lossy Feedback
Zhengyuan Zhou, Panayotis Mertikopoulos, Susan Athey, Nicholas Bambos, Peter Glynn, Yinyu Ye. 32nd Conference on Neural Information Processing Systems (NIPS 2018). Montéal, Canada: 2018.

Working Papers

The Allocation of Decision Authority to Human and Artificial Intelligence | PDF
Susan Athey, Kevin Bryan, Joshua S. Gans, January 102020
Optimal Experimental Design for Staggered Rollouts
Susan Athey, Guido W. Imbens, Mohsen Bayati, November 2019
Using Wasserstein Generative Adversarial Networks for the Design of Monte Carlo Simulations | PDF
Susan Athey, Guido W. Imbens, Jonas Metzger, Evan Munro, September 2019
Sufficient Representations for Categorical Variables | PDF
Jonathan Johannemann, Vitor Hadad, Susan Athey, Stefan Wager, August 2019
Counterfactual Inference for Consumer Choice Across Many Product Categories | PDF
Rob Donnelly, Francisco R, Ruiz, David Blei, Susan Athey, June 2019
Machine Learning Methods Economists Should Know About | PDF
Susan Athey, Guido W. Imbens, March 242019
Estimating Treatment Effects with Causal Forests: An Application | PDF
Susan Athey, Stefan Wager, February 202019
Synthetic Difference in Differences | PDF
Dmitry Arkhangelsky, Susan Athey, David A. Hirshberg, Guido W. Imbens, Stefan Wager, February 12019
Experienced Segregation | PDF
Susan Athey, Billy Ferguson, Mathew Gentzkow, Tobias Schmidt, February 2019
Estimation Considerations in Contextual Bandits | PDF
Maria Dimakopoulou, Susan Athey, Guido W. Imbens, December 2018
Offline Multi-Action Policy Learning: Generalization and Optimization | PDF
Susan Athey, Zhengyuan Zhou, Stefan Wager, October 102018
Design-based Analysis in Difference-In-Differences Settings with Staggered Adoption | PDF
Susan Athey, Guido W. Imbens, August 152018
When Should You Adjust Standard Errors for Clustering? | PDF
Alberto Abadie, Susan Athey, Guido W. Imbens, Jeffrey Wooldridge, October 92017
Structured Embedding Models for Grouped Data | PDF
Maja Rudolph, Francisco Ruiz, Susan Athey, David Blei, September 282017
Estimation and Inference of Heterogeneous Treatment Effects using Random Forests | PDF
Susan Athey, Stefan Wager, July 102017
The Digital Privacy Paradox: Small Money, Small Costs, Small Talk | PDF
Susan Athey, Christian Catalini, Catherine E. Tucker, June 2017
Efficient Policy Learning | PDF
Susan Athey, Stefan Wager, February 2017
The Impact of News Aggregators on Internet News Consumption: The Case of Localization | PDF
Susan Athey, Mark Mobius, January 112017
Solving Heterogeneous Estimating Equations with Gradient Forests | PDF
Susan Athey, Julie Tibshirani, Stefan Wager, January 2017
Matrix Completion Methods for Causal Panel Data Models
Susan Athey, Mohsen Bayati, Nick Doudchenko, Guido W. Imbens, Khashayar Khosravi2017
A Theory of Community Formation and Social Hierarchy | PDF
Susan Athey, Emilio Calvano, Saumitra Jha, August 62016
Bitcoin Pricing, Adoption, and Usage: Theory and Evidence | PDF
Susan Athey, Iva Parashkevov, Vishnu Sarukkai, Jing Xia, August 2016
Exact P-values for Network Interference | PDF
Susan Athey, Dean Eckles, Guido W. Imbens, June 2015
Machine Learning for Estimating Heretogeneous Casual Effects | PDF
Susan Athey, Guido W. Imbens, April 2015
Finite Population Causal Standard Errors
Alberto Abadie, Susan Athey, Guido W. Imbens, Jeffrey M. Wooldridge, July 2014
Peaches, Lemons, and Cookies: Designing Auction Markets with Dispersed Information | PDF
Ittai Abraham, Susan Athey, Moshe Babaiof, Michael D. Grubb, May 62014
Social Media and News Consumption | PDF
Susan Athey, Markus Mobius, Jeno Pal, January 142014
Exchange Rate Fluctuations, Consumer Demand, and Advertising: The Case of Internet Search | PDF
Susan Athey, Maya Cohen Meidan, November 172010
Mentoring, Discrimination and Diversity in Organizations | PDF
Susan Athey, Christopher Avery, Peter Zemsky1994
The Allocation of Decisions in Organizations | PDF
Susan Athey, Joshua Gans, Scott Schaefer, Scott Stern1994

Teaching

Degree Courses

2019-20

MGTECON 634: Machine Learning and Causal Inference

This course will cover statistical methods based on the machine learning literature that can be used for causal inference. In economics and the social sciences more broadly, empirical analyses typically estimate the effects of counterfactual...

STRAMGT 529: Marketplaces for Goods and Services

In this class we will analyze the economics and strategy of marketplaces and platforms for goods and services. We will consider the forces that have led to the proliferation of these marketplaces, as well as the economics behind which ones are...

2018-19

GSBGEN 513: Using Technology and Market Interventions to Solve Social Problems

This course will focus on finding solutions to social problems enabled by technology, where market failures prevent the solutions from being provided by the private market, and where market-based interventions can be used to create the...

MGTECON 515: Cryptocurrency

This class will provide an overview of the rapidly evolving area of distributed ledger and blockchain technologies, with a focus on economic and strategic issues. We will cover key components of the architecture that affect the products derived...

MGTECON 634: Machine Learning and Causal Inference

This course will cover statistical methods based on the machine learning literature that can be used for causal inference. In economics and the social sciences more broadly, empirical analyses typically estimate the effects of counterfactual...

STRAMGT 529: Marketplaces for Goods and Services

In this class we will analyze the economics and strategy of marketplaces and platforms for goods and services. We will consider the forces that have led to the proliferation of these marketplaces, as well as the economics behind which ones are...

Executive Education & Other Non-Degree Programs

Other Teaching
  • ALP 301: Data-Driven Impact
    This is a team-based course where students will work on a project to improve a product using data and experimentation. We will cover key considerations for designing and executing high-quality research for product innovation to drive business outcomes and social impact. Students will have the opportunity to apply methods from machine learning and causal inference to a real-world scenario provided by a partner organization. Topics include designing research and experiments, data analysis, experimental and non-experimental methods for estimating the impact of product features, as well as management consideration for the delivery of actionable research. The course involves three weekly meetings: two lectures and one lab.

Conferences, Talks, and Speaking Engagements

  • Video: Jean-Jacques Laffont Prize 2016
    Susan Athey, Professor of Economics at Stanford Graduate School of Business, came to Toulouse to receive the Jean-Jacques Laffont Prize 2016. She tells us about her research "the internet and the news industry", and her relationship with TSE.
  • Video: Professor Susan Athey on the Dangers of Becoming Too Data-Driven
    Susan Athey, Professor of Economics at Stanford Graduate School of Business, discusses how data-driven organizations still need to exercise intuition and judgement to ensure that short-term results don't override long-term interests.
  • Video: Designing Online Advertising Markets
    Susan Athey, Professor of Economics at Stanford Graduate School of Business, discusses Designing Online Advertising Markets at the Algorithmic Game Theory and Practice talk held at the Simons Institute for the Theory Computing, UC Berkeley

Stanford University Affiliations

Stanford GSB

Greater Stanford University

  • Senior Fellow, Stanford Institute of Economic Policy Research
  • Member, Program on Computational Social Science

Service to the Profession

Current Activities

  • Member, President’s Committee for the National Medal of Science (Presidential Appointment), 2014-Present
  • Member, National Academies Board on Science, Technology and Economic Policy Innovation Policy Form, 2013-present
  • Member, National Academies Committee on Science, Engineering, and Public Policy, 2013-present

Past Activities

  • Member, President’s Committee for the National Medal of Science (Presidential Appointment), 2011-2013
  • Member, Nominating Committee for American Academy of Arts and Sciences, 2011-2012
  • Cambridge Economics Economics and Computational Day, co-founder, 2011.
  • Council, Game Theory Society, 2009-2012. (elected position)
  • Associate Editor, Theoretical Economics, 2005-2011
  • Council, Econometric Society, 2007-2010. (elected position)
  • Executive Committee, American Economic Association, 2008-2010. (elected position)
  • Advisory Committee on Editorial Appointments, American Economics Association, 2011
  • Co-Editor, American Economic Journals: Microeconomics, 2007-2008
  • Associate Editor, Econometrica, 2006-2007
  • Associate Editor, Quarterly Journal of Economics, 2001-2007
  • Editorial Board, Not a Journal Economics, 2001-2008
  • Fellows Nominating Committee, Econometric Society, 2006
  • Elaine Bennett Research Prize Committee (AEA/CSWEP), 2002, 2004, 2006 (Chair)
  • Chair, Program Committee, Winter Meetings of the Econometric Society, 2006
  • National Science Foundation Economics Panel, 2004-2006
  • Co-director, Market Design Program, Stanford Institute for Economic Policy Research, 2004-2006
  • Mentor, CeMent Mentoring Workshop, AEA/CSWEP, 2006
  • Young Faculty Nominating Committee, Center for Advanced Study in the Behavioral Sciences
  • Associate Editor, American Economic Review, 2002-2005
  • Associate Editor, RAND Journal of Economics, 2002-2004
  • Foreign Editor, Review of Economic Studies, 2001-2004
  • American Economic Association Nominating Committee, 2003
  • Stanford University Fellow, 2002-2004
  • Co-editor, Journal of Economics and Management Strategy, 1997-2001
  • Program Committee, Summer Meetings of the Econometric Society, 1997 and 1998; 8th World Congress of the Econometric Society, 2000; Winter Meetings of the Econometric Society, 2001 and 2005

In the Media

Bringing an Economist's Perspecive to Data Science
Women in Data Science (WiDS), January 16, 2020
HAI 2019 Fall Conference: AI and the Economy, with Susan Athey and Erik Brynjolfsson
The Stanford Daily, October 28, 2019
Interview from SNS Tylösand Summit
SNS Tylösand Summit, October 14, 2019
Economist as Engineer
International Monetary Fund, June 2019
Tech: economists wanted
AEA Research Highlights, March 15, 2019
Machine Learning and Economics
TNIT News, February 2019
Fixing Big Data's Blind Spot
Forbes India, June 8, 2018
Bitcoin: The Past, Present and Future
Bloomberg, April 26, 2018
Pizza over privacy? Stanford economist examines a paradox of the digital age
Stanford News, August 3, 2017
Machine Learning for Policy Analysis
The Wonk, June 2017
Can business schools prepare students for a 70-year career?
Financial Times, September 8, 2016
Featured Economist
STEM Gem Book, June 6, 2016
Designing Online Marketplaces
AdExchanger, April 14, 2016
Why Do Technology Companies Hire Economists?
Forbes, January 27, 2016
What Will The Impact Of Machine Learning Be On Economics?
Forbes, January 27, 2016
Bitcoin Blockchain Technology In Financial Services: How The Disruption Will Play Out
Forbes, September 14, 2015
CMSA Big Data Interview
Harvard University, August 26, 2015
Prof. Susan Athey discusses her research and work on big data
Economists and the Real World
Federal Reserve Bank of Richmond, August 2015
The Economics of Bitcoin and Virtual Currency
Stanford GSB, June 18, 2015
Susan Athey explains how Bitcoin works, and why virtual digital currency might change the way consumers and financial institutions do business. Athey is the Economics of Technology professor at Stanford Graduate School of Business.
Why Managers Must Embrace Big Data or Be Left Behind
The Fast Track, June 1, 2015
Nasdaq Signals Confidence in Bitcoin, Not Just the Blockchain
American Banker, May 19, 2015
Stanford Professor Combines Machine Learning and Econometrics
The Harvard Crimson, April 29, 2015
E-Commerce Ad Rates Paying by Time, Not Clicks
Businessweek, April 26, 2015
Diverse Perspectives Needed To Provide Better Analysis Of Big Data
Becker Friedman Institute, April 10, 2015
University of Chicago undergraduates heard an array of views on the economic, moral, and political effects of so-called "big data" at a student-organized panel discussion held on April 10, 2015 at the Saieh Hall for Economics. Led by fourth-year students students in the College, the panel featured economists Susan Athey of Stanford University and Hal Varian of the University of California, Berkeley, as well as statistician and machine learning expert Larry Wasserman of Carnegie Mellon University.
Women in Business: Sara Clemens, Chief Strategy Officer, Pandora,
Huffingtonpost, March 31, 2015
Who Will Benefit From Digital Currency? Bitcoin Experiment Gives A Glimpse
Forbes.com, November 26, 2014
Could Digital Currency Make Our Money More Secure?
Forbes.com, November 25, 2014
Susan Athey On How Digital Currency Could Transform Our Lives
Forbes.com, November 24, 2014
Challenges for Women in Economics
Bloomberg, July 27, 2013

Insights by Stanford Business

writtenThe Future of Criminal Justice
March 16, 2020
A conference on prosecution reform through data discusses the challenges of culture change.
videoThe New Emerging Role in Big Tech? Economists
January 31, 2020
To maximize the potential of big data, firms are looking for employees with a new skill set.
videoMachine Learning and AI for Social Impact
January 16, 2020
Innovations developed at big tech firms could transform the nonprofit world, with a little help from academia.
written8 Most-Read Stories of 2019
December 6, 2019
Communication mistakes, job-stealing robots, and career-gap explanations captured reader attention this year.
writtenHow Markets Can Change to Ease Economic Inequality
November 14, 2019
Experts weigh in on economic, education, and financial gaps at a recent Stanford GSB conference.
writtenExploring the Human Side of Artificial Intelligence
November 7, 2019
At an AI forum, experts say the arrival of superhuman machine intelligence will be one of the biggest events in human history.
writtenOur Misplaced Fear of Job-Stealing Robots
March 7, 2019
At a Future of Work forum, experts say demographic shifts, not artificial intelligence, create the biggest challenges for today’s workplace.
writtenHere’s What You Should Read over the Holidays
December 3, 2018
Seven Stanford business professors recommend their favorite books.
writtenReshaping Markets to Solve Poverty and Inequality
October 10, 2018
Academics, investors, and nonprofit leaders on how to find innovative solutions for the world’s starkest problems.
writtenSusan Athey: Why Business Leaders Shouldn’t Have Blind Faith in AI
May 23, 2018
Telling cats from dogs is easy. It’s the what-ifs that get problematic.
writtenPizza Over Privacy? A Paradox of the Digital Age
August 3, 2017
Consumers choose convenience over protection.
writtenFixing Big Data’s Blind Spot
March 10, 2017
Susan Athey wants to help machine-learning applications look beyond correlation and into root causes.
writtenThe Promise and Peril of Bitcoin
February 25, 2014
Economist Susan Athey and venture capitalist Balaji Srinivasan discuss the digital currency.
writtenSusan Athey: How Big Data Changes Business Management
September 20, 2013
The Stanford economist explains how troves of digital data will reshape competition.

School News

writtenHow Professors Are Teaching in a Coronavirus World
March 18, 2020
Faculty members explore new technologies to bring classroom lessons to remote students.
writtenAction Learning Program Brings Experiential Learning to Forefront of Curriculum
October 30, 2019
Project-based courses pair students with external organizations to solve real-world business problems.
writtenGolub Capital Social Impact Lab Aims to Enhance Social Sector Effectiveness
October 28, 2019
The recently launched lab aims to support and guide innovation in the social sector.
writtenFixing Economics’ Gender Problem
May 14, 2019
Meet three graduates of an innovative Stanford GSB program designed to create a path for women and minorities in business academia.
writtenFor Women’s History, Look to the Future
March 27, 2019
These Stanford GSB women are changing their industries and their communities.
writtenFrom the Dean: Staying Ahead in the Digital Age
February 27, 2018
“Effective leaders in the digital age will need to be mindful of the social consequences of technology.”
writtenNew Faculty Enrich the Stanford GSB Experience
July 11, 2012
Award-winning economist Susan Athey, noted econometrician Guido Imbens, corporate finance expert Joshua Rauh, and others to join Stanford GSB faculty.
writtenJohn Roberts Altered the Study of Industrial Organization
November 1, 2010
John Roberts' groundbreaking work in industrial organization affected the course of economic research and inspired a new generation of economists.