Guido W. Imbens slept through the first phone call, but awoke for the second. Caller ID told him the call was coming from Sweden.
On the other end, the prize committee for the Nobel Memorial Prize in Economic Sciences relayed some big news: Not only had the professor of economics at Stanford Graduate School of Business won the Nobel Prize, but he’d won it with the best man at his wedding.
“I was just shocked. Typically people winning these prizes are much further along in their careers. I did not expect this to come anytime soon,” Imbens said Monday (October 11) at a virtual news conference.
“My co-winners of the prize, I have known both of them for a long time and both of them are very close friends … Their work has always been a great source of inspiration.”
THREE U.S. ECONOMISTS SHARE PRIZE
This year’s Nobel prize in economics — awarded by the Royal Swedish Academy and officially called The Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel 2021 — is shared between three economists all hailing from American universities: One half of the award goes to David Card, professor of economics at the University of California-Berkeley, for his “empirical contributions to labor economics.” The other half is shared between Imbens and Joshua D. Angrist, professor of economics at MIT, for their “methodological contributions to the analysis of causal relationships.”
The 2021 Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel has been awarded with one half to David Card and the other half jointly to Joshua D. Angrist and Guido W. Imbens.#NobelPrize pic.twitter.com/nkMjWai4Gn
— The Nobel Prize (@NobelPrize) October 11, 2021
Unlike experiments in, say, medicine, researchers in the social sciences aren’t able to conduct double-blind experiments in highly controlled laboratories. You can’t cause a famine to compare its economic effects against a non-famine, for example.
So, economists and other social scientists rely on observational data. The work of Imbens and Angrist helped demonstrate how causal inferences could be derived from natural experiments and observational studies of real-world situations, leading to precise conclusions and answers to very large societal problems.
“All of us at Stanford are incredibly proud of Professor Imbens, and we are delighted that his accomplishments have been recognized by the Nobel Committee,” says Jonathan Levin, Stanford GSB dean.
“The real-world impact (of Imbens’ work) has been profound and far reaching. Professor Imbens has worked with policymakers to design and evaluate economic policy interventions in areas such as education and labor, and his methodology has been implemented beyond the field of economics … as we seek solutions to our society’s great challenges — from economic and educational inequality to the disparate impacts of climate change.”
FRIENDS, COLLEAGUES AND BEST MEN
Imbens, an applied econometrics professor and a senior fellow at the Stanford Institute for Economic Policy Research, has known Angrist since his first year teaching and living at Harvard University in the early 1990s. The two would talk over the big world questions on Saturday mornings in the university laundromat. Those discussions formed the foundation for the work that earned them the Nobel prize 30 years later.
The friends pioneered a research model that demonstrated how natural experiences can be used to show how cause and effect are related. In big, real-world situations in which chance and randomization naturally occur and cannot be controlled, this has major implications. The model is called the Local Average Treatment Effect (LATE) and was introduced in a 1994 Econometrica paper.
“I think it’s totally revolutionized the way we do empirical work,” Eva Mörk, member of the economic sciences committee, says of this year’s Nobel winners. “We can go out and answer these super interesting, relevant questions about so many different things. About how early interventions in a child’s life affect the major outcomes, how different tax and benefit systems affect a lot of things, so we can give so much better policy advice.”
One example Imbens cites is this: Does Universal Basic Income disincentivize people from seeking paid work? An experiment to answer such a question would be very expensive and take a long time to collect meaningful data. Instead, using their research tools, Imbens looked at the experience of lottery winners in Massachusetts who received $25,000 checks each year for 20 years. Measuring the hours worked of the lottery winners can provide causal inferences about guaranteed income on a wider scale.