Dutch-American econometrician

Guido Wilhelmus Imbens (born 3 September 1963) is a Dutch-American economist whose research concerns econometrics and statistics. He holds the Applied Econometrics Professorship in Economics at the Stanford Graduate School of Business at Stanford University, where he has taught since 2012.

In 2021 Imbens was awarded half of the Nobel Memorial Prize in Economic Sciences jointly with Joshua Angrist "for their methodological contributions to the *ysis of causal relationships." The work of the two economists demonstrated the potentials for inferring causation from natural experiments which can offer empirical data in contexts where controlled experimentation may be expensive, time-consuming, or unethical. In 1994 Imbens and Angrist published an influential mathematical methodology for reliably inferring causation from natural experiments that accounted for and defined the limitations of such inferences. Imbens' work with Angrist, together with the work of co-recipient David Card, is credited with catalyzing the "credibility revolution" in empirical microeconomics.

Contents

• 1 Early life and education
• 2 Career
  • 2.1 Econometrics and work on causal relationships
  • 2.2 Nobel Memorial Prize in Economics
• 3 Personal life
• 4 Honors and awards
• 5 Bibliography
• 6 References
• 7 External links

Early life and education

Guido Wilhelmus Imbens was born on 3 September 1963 in Geldrop, the Netherlands. In 1975 his family moved to Deurne, where he attended Peellandcollege:. As a child, Imbens was an avid chess player. In a 2021 interview, Imbens connected his p*ion for econometrics to his childhood interest in the game.

In high school Imbens was introduced to the work of Dutch economist Jan Tinbergen. Influenced by Tinbergen's work, Imbens chose to study economics at Erasmus University Rotterdam, where Tinbergen had taught and established a program in economics. Imbens graduated with a Candidate's degree in Econometrics from Erasmus University Rotterdam in 1983. He subsequently obtained an M.Sc. degree with distinction in Economics and Econometrics from the University of Hull in Kingston upon Hull, UK in 1986.

In 1986 one of Imbens' mentors at the University of Hull, Anthony Lancaster, moved to Brown University in Providence, Rhode Island. Imbens followed Lancaster to Brown to pursue further graduate and doctoral studies. Imbens received an A.M. and a Ph.D. degree, both in Economics, from Brown in 1989 and 1991, respectively.

The Department of Economics at Brown University

Career

Imbens has taught at Harvard University (1990–97, 2006–12), Tilburg University (1989-1990), the University of California, Los Angeles (1997–2001), and the University of California, Berkeley (2002–06). He specializes in econometrics, which are particular methods for drawing causal inference. He became the editor of Econometrica in 2019 and will serve in that capacity until 2023. As of 2021, he is a professor of applied econometrics and economics at Stanford Graduate School of Business. He is also a senior fellow at the Stanford Ins*ute for Economic Policy Research (SIEPR) and a professor of economics at the ins*ute's School of Humanities and Sciences.

The Stanford Graduate School of Business, where Imbens has taught since 2012

Imbens is a fellow of the Econometric Society (2001) and the American Academy of Arts and Sciences (2009). Imbens was elected to the Royal Netherlands Academy of Arts and Sciences as a foreign member in 2017. He was elected as a Fellow of the American Statistical *ociation in 2020.

Econometrics and work on causal relationships

Working with fellow economists including Joshua Angrist and Alan Krueger, Imbens focused on developing methodologies and frameworks that help economists use real-life situations, known as natural experiments, to test real life theories. Specifically, through his study he helped *yze causal relationships. Some of the problem statements *yzed through his study included the impact of college education or additional years of education on earnings. His frameworks for causal relationships study found use in multiple other fields including social and biomedical sciences. His work has provided researchers across disciplines with tools to understand the limitation of real-world experiments improving their ability to better understand the effects of field and experimental data based interventions. These methodologies have been used by researchers in the *ysis of a variety of research questions in economics, the social sciences, and medicine.

In one of his earliest collaborations with Angrist, Imbens introduced a model called Local Average Treatment Effect (LATE) that helped researches to draw causal inference from observational data. Elaborating on the model in a Econometrica paper in 1994 *led "Identification and Estimation of Local Average Treatment Effects", the pair employed the idea of natural experiments, which were real world events and situations as against controlled conditions to study the effects of key changes. In doing so, the pair took advantage of the role chance and randomization that naturally occurred in the real world rather than controlled simulations, which could be expensive, time-consuming, or even unethical. The paper and the model had significant impact on other research efforts across econometrics, statistics and other fields.

In one of the real-world applications of the model that would have implications for policymakers, Imbens partnered with statistician Donald Rubin and economist Bruce Sacerdote to study the impact of unearned earnings on labor supply. The group studied the implications of policy interventions such as Universal Basic Income or other federal and state wage *istance programs on citizens' willingness to participate in the labor force and the eventual impact on labor supply.

To devise a natural experiment, the group studied the winners of the M*achusetts state lottery where the winners were paid incrementally over many years as opposed to a lump-sum payment. In doing so, the group was able to study the causal effects of guaranteed income. They found that winning the lottery had only a small impact on how much people worked. Winners of $80,000 a year for 20 years reduced their working hours somewhat, but winners of $15,000 a year for 20 years did not. Among unemployed persons who played the lottery, winners worked more than non-winners in the six years after playing.

Some of Imbens' work was summarized in a book co-written with American statistician Donald B. Rubin, Causal Inference for Statistics, Social, and Biomedical Sciences.

More recently, he (along with Prof. Susan Athey) has been working on using machine learning methods, particularly modifications to random forests called causal forests to estimate heterogeneous treatment effects in causal inference models.

Nobel Memorial Prize in Economics

Imbens speaking at Brown University in March 2022

Imbens received the 2021 Nobel Memorial Prize in Economic Sciences along with fellow economists David Card and Joshua Angrist for their contributions toward methodologies for the *ysis of causal relationships. In its press release announcing the winners, the Royal Swedish Academy of Sciences stated "his year’s Laureates – David Card, Joshua Angrist and Guido Imbens have provided us with new insights about the labour market and shown what conclusions about cause and effect can be drawn from natural experiments. Their approach has spread to other fields and revolutionised empirical research."

Personal life

Imbens has been married to fellow economist Susan Athey since 2002. Athey likewise teaches at the Stanford Graduate School of Business where she holds the Economics of Technology Professorship. The best man at Imbens and Athey's wedding was Joshua Angrist, with whom Imbens would share the Nobel prize 19 years later.

He holds dual citizenship in the United States and the Netherlands.

Honors and awards

• Honorary Doctorate, University of St. Gallen, 2014
• Horace Mann Medal, Brown University Graduate School, 2017
• Nobel Memorial Prize in Economic Sciences, 2021
• Doctorate of Humane Letters, Brown University, 2022

Bibliography

• (with Lisa M. Lynch) Re-employment probabilities over the business cycle. Cambridge, MA: National Bureau of Economic Research, 1993.
• (with Richard H. Spady and Philip Johnson) Information Theoretic Approaches to Inference in Moment Condition Models. Cambridge, M*.: National Bureau of Economic Research, 1995.
• (with Gary Chamberlain) Nonparametric applications of Bayesian inference. Cambridge, MA: National Bureau of Economic Research, 1996.
• (with Donald B. Rubin and Bruce Sacerdote) Estimating the effect of unearned income on labor supply, earnings, savings, and consumption:: evidence from a survey of lottery players. Cambridge, MA: National Bureau of Economic Research, 1999.
• (with V. Joseph Hotz and Jacob Alex Klerman) The long-term gains from GAIN:: a re-*ysis of the impacts of the California GAIN Program. Cambridge, MA: National Bureau of Economic Research, 2000.
• (with Thomas Lemieux) Regression discontinuity designs: a guide to practice. Cambridge, M*.:: National Bureau of Economic Research, 2007.
• (with Jeffrey M. Wooldridge) Recent Developments in the Econometrics of Program Evaluation. Cambridge, M*.:: National Bureau of Economic Research, 2008.
• (with Karthik Kalyanaraman) Optimal bandwidth choice for the regression discontinuity estimator. Cambridge, M*.: National Bureau of Economic Research, 2009.
• (with Alberto Abadie) A martingale representation for matching estimators. Cambridge, M*.: National Bureau of Economic Research, 2009.
• Imbens, Guido W.; Rubin, Donald B. (6 April 2015). Causal Inference for Statistics, Social, and Biomedical Sciences: An Introduction. Cambridge University Press. ISBN:9780521885881.

References

External links

• Website at Stanford University
• Guido Imbens publications indexed by Google Scholar
• Guido Imbens on Nobelprize.org