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United States Guido Imbens is a Nobel laureate economist known for his foundational contributions to econometrics and statistics, specifically in the analysis of causal relationships within observational studies.
A conversation with economics Nobelists including Amazon Scholar David Card and Amazon academic research consultant Guido Imbens on the past and future of empirical economics.
Guido Imbens discusses how the future of data science belongs to causal methods, addressing industry bottlenecks created by the data science revolution.
Featured in 'Finance & Development' in an article titled 'Guido Imbens: A Causal Pioneer,' highlighting his shared Nobel Prize with Angrist and Card.
Guido Wilhelmus Imbens was born on September 3, 1963, in Geldrop, the Netherlands. His early interest in complex systems, stemming from a childhood passion for chess, led him to econometrics. He pursued his education at Erasmus University Rotterdam, where he earned a Candidate’s degree in Econometrics in 1983. He then obtained an M.Sc. with distinction in Economics and Econometrics from the University of Hull in 1986. Following his mentor, Anthony Lancaster, Imbens moved to Brown University, securing an A.M. in 1989 and a Ph.D. in economics in 1991 with his thesis “Two essays in econometrics.”
Imbens’ career involved teaching roles at Tilburg University (1989–1990), Harvard University (1990–97, 2007–12), the University of California, Los Angeles (1997–2001), and the University of California, Berkeley (2001–07). Since 2012, he has been a Professor of Applied Econometrics in Economics at the Stanford Graduate School of Business. He is also a senior fellow at the Stanford Institute for Economic Policy Research (SIEPR) and a professor of economics at Stanford’s School of Humanities and Sciences. Imbens’ work primarily focuses on developing methods for drawing causal inferences from observational data, utilizing techniques such as matching, instrumental variables, and regression discontinuity designs.
A significant milestone in his career came in 1994 when, with Joshua Angrist, he introduced the Local Average Treatment Effect (LATE) framework, a mathematical methodology for inferring causation from natural experiments. This work, along with contributions from David Card, catalyzed a “credibility revolution” in empirical microeconomics. In 2001, Imbens collaborated with Donald Rubin and Bruce Sacerdote to study the impact of unearned income on labor supply, using Massachusetts state lottery winners as a natural experiment. In 2021, Imbens, alongside Joshua Angrist and David Card, was awarded half of the Nobel Memorial Prize in Economic Sciences for their methodological contributions to the analysis of causal relationships.
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