Susan Athey | |
|---|---|
.jpg) Professor Susan Athey in 2020 | |
| Born | November 29, 1970 |
| Nationality | American |
| Spouse | Guido Imbens |
| Academic career | |
| Institution | Stanford University |
| Field | Microeconomics Econometrics Machine Learning |
| Alma mater | Stanford Graduate School of Business Duke University |
| Doctoral advisor | Paul Milgrom Donald John Roberts Edward Lazear |
| Awards | John Bates Clark Medal (2007) |
| Information at IDEAS / RePEc | |
Susan Carleton Athey (born November 1970 (age 53)[1]) is an American economist. She is the Economics of Technology Professor in the School of Humanities and Sciences at the Stanford Graduate School of Business.[2] Prior to joining Stanford, she has been a professor at Harvard University and the Massachusetts Institute of Technology. She is the first female winner of the John Bates Clark Medal.[3] She served as the consulting chief economist for Microsoft for six years[4] and was a consulting researcher to Microsoft Research. She is currently on the boards of Expedia, Lending Club, Rover, Turo, Ripple, and non-profit Innovations for Poverty Action.[4] She also serves as the senior fellow at Stanford Institute for Economic Policy Research. She is an associate director for the Stanford Institute for Human-Centered Artificial Intelligence and the director of Golub Capital Social Impact Lab.[4]
Athey was born in Boston, Massachusetts and grew up in Rockville, Maryland. Her parents are Elizabeth Johansen, an English teacher and freelance editor, and Whit Athey, a physics scholar.
Athey attended Duke University for her undergraduate coursework. There, she completed three majors (economics, mathematics, and computer science) and graduated in 1991.[4] Athey's interest in economics research can be attributed to a summer job where she prepared bids for a company that was selling personal computers to the government through procurement auctions. Working on problems related to auctions with Bob Marshall, a professor at Duke University who worked on defense procurement, she became his research assistant and subsequently inherited his passion for auction research. She was additionally involved in a number of leadership roles at Duke, including serving as treasurer of Chi Omega sorority and as president of the field hockey club.
Athey graduated with a Ph.D. in economics from the Stanford Graduate School of Business in 1995.[5][4] Her dissertation was supervised by Paul Milgrom and Donald John Roberts.[3] Athey also received an honorary doctorate from Duke University.
Athey has been married to economist Guido Imbens since 2002.[6]
Athey's first position was as an assistant professor at the Massachusetts Institute of Technology, where she taught for six years, before returning to Stanford's Department of Economics as professor, where she held the Holbrook Working Chair for another five years. Then, she served as a professor of economics at Harvard University until 2012, before finally returning to the Stanford Graduate School of Business, her alma mater and current employer.[7]
Because of Athey's completion of triple majors—economics, mathematics and computer science—in Duke University during her undergraduate period, she always utilized programming and statistics as tools to solve problems in the field of economics. Based on this background, Athey is interested in economics of the Internet, economics of the news media, internet search, econometrics, machine learning, big data, and math-based currency. Other related fields, such as platform markets, online advertising, and industrial organization, are proxy interests of hers. Currently, she focuses on the economics of digitization, marketplace design, and the intersection of econometrics and machine learning.[citation needed]
Auctions were the reason Athey went into economics. She has contributed on all dimensions to research on auctions. Athey's theoretical work on collusion in repeated games has been applied to auctions. She has performed significant empirical work in econometrics of auctions. In fact, her existence theorem for sets with private information has done an innovative job on the econometrics of auctions.
She also oversaw work that has had significant effects on business and public policy. Athey and Jonathan Levin examined the U.S. Forest Service's oral ascending auctions for the rights to cut timber in the national forests. Typically, a given tract contains several different species of timber-yielding trees. The Forest Service publishes an estimate of the proportions of the various species based on an inspection. Potential bidders then can conduct their inspections. Bids are multidimensional: amounts to be paid per unit for each species. The winner is determined by aggregating each bidder's offer using the Forest Service's estimated proportions. The actual amount the winner pays, however, is computed by applying the bid vector to the exact amounts that are ultimately harvested (the winner has two years to complete the harvest). These rules create an incentive for a bidder whose estimate of the proportions differs from that of the Forest Service to skew its bidding, which raises the bid for species that the bidder believes are less common than does the Forest Service. Conversely, it lowers the bid for the species that the bidder believes are more common than does the Forest Service. For example, suppose there are two species and the Forest Service estimates that they are in equal proportions, but a bidder believes they are in dimensions 3:2. Then bids of ($100, $100) and ($50, $150) yield the same amount under the Forest Service proportions and so are equally likely to win, but the bidder's expected payments under the first and under the second differ.[8]
One of Athey's best-known works that deals with auctions is called “Comparing Open and Sealed Bid Auctions: Theory and Evidence from Timber Auctions." In this paper, Athey works with Johnathan Levin and Enrique Seira. She and her peers were interested in testing to see if the participation effects on auction were important. There are two types of auctions, open and sealed-bid auctions. Open auctions are where bidders are constantly outbidding one another until the last bidder gives up and the auction ends, and sealed-bid auctions are when individuals write down their bids and submit them, whoever has the highest bid wins. The data that they used came from the United States Forest Service auctions. Their results indicated that participation type matters. It even matters more than what is actually taking place during the auctioning process.[9]
With Athey's multidisciplinary education, it comes as no surprise that she would take interest in the digital marketplace. However, her ultimate goal in her contributions to technology and the digital marketplace is to improve the social impact of them. Pioneering the field alongside Google's Hal Varian, Athey was one of the first coined "tech economists." She cites this to be one of her proudest lifetime accomplishments.[10]
Athey is able to hone her skills from different fields to create an amalgamation of machine learning and market design which is leveraged to make sense of and improve the social impact of technology. In some of her more recent research, Athey applies these techniques to the COVID-19 pandemic. By analyzing the effectiveness of social media advertising in influencing the beliefs surrounding COVID-19 vaccine efficacy, Athey was able to conclude that the average cost of influencing a person in favor of the vaccine was $3.41. This, coupled with an estimated vaccine cost of $5.68, provided empirical evidence for the cost-effectiveness of using social media campaigns to influence the vaccination rate.[11]
Her passion for using machine learning to advance the alleviation of societal issues led her to become the faculty director of the Stanford Business School's Initiative for Shared Prosperity and Innovation (ISPI). This project utilizes technology to address social problems like poverty, inequality, and, as aforementioned, COVID-19. The Initiative's mechanism for doing this is to apply machine learning methods to technology companies with the eventual result of improving methods for measuring impact. As technology companies rapidly and incrementally improve using data collection methods, it is increasingly important that they do this more efficiently by being more accurate in their impact measurements. When companies implement these machine learning tactics, they become more efficient; this is particularly important because they are legitimized to potential investors, which helps secure funding. This is particularly important in the case of social impact projects, which oftentimes rely on volatile forms of investment like philanthropic or governmental funding.[10]
Athey's early contributions included a new way to model uncertainty (the subject of her doctoral dissertation) and understand investor behavior given uncertainty, along with insights into the behavior of auctions. Athey's research on decision-making under uncertainty focused on conditions under which optimal decision policies would be monotone in a given parameter. She applied her results to establish conditions under which Nash equilibria would exist in auctions and other Bayesian games.
Athey's work changed the way auctions are held. In the early 1990s Athey uncovered the weaknesses of an overly lenient dispute mechanism through experiences selling computers to the U.S. government at auctions, discovering that open auctions which resulted in frequent legal disputes followed by settlements were actually rife with collusion (e.g., auction winners shared a portion of their spoils with losers who had cooperated in bidding).[12] She also aided British Columbia in the design of their pricing system used for publicly owned timber.[3] In addition, Athey published articles about auctions for online advertising and advised Microsoft about the design of their search advertising auctions.[13]
Athey has served as an associate editor of several leading journals, including the American Economic Review, Review of Economic Studies, and the RAND Journal of Economics, as well as the National Science Foundation economics panel, and she also served as an associate editor for Econometrica, Theoretical Economics, and the Quarterly Journal of Economics. She is a past co-editor of the Journal of Economics and Management Strategy and American Economic Journal: Microeconomics. She was the chair of the program committee for the 2006 North American Winter Meetings, and has served on numerous committees for the Econometric Society, the American Economic Association, and the Committee for the Status of Women in the Economics Profession. She is a member of President Obama's Committee for the National Medal of Science.[14]
Furthermore, besides professional services in academic committees, Athey, as a "tech economist," also used to serve as consultant chief economist for Microsoft Corporation for a few years and now serves on the board of Expedia, Lending Club, Rover Turo, and Ripple. She also serves as a long-term advisor to the British Columbia Ministry of Forests, helping architect and implement their auction-based pricing system. Athey is the founding director of the Golub Capital Social Impact Lab at Stanford Graduate School of Business, and serves as the associate director of the Stanford Institute for Human-Centered Artificial Intelligence.[15]
