The Empirical Revolution in Economics: Taking Stock and Looking Ahead*

The last 40 years have witnessed tremendous developments in empirical work in economics. In a recent paper, Josh Angrist and his coauthors show that the proportion of empirical work published in top journals in economics has moved from around 30% in 1980 to over 50% today. This is a very important and welcome trend. In this article, I want to take stock of what I see as the main progress in empirical research and look ahead at the remaining challenges.

Academics

Incentives in an online Q&A community

Imagine some student from around the world contacts you to get information about TSE programs. She is looking to apply for a Master in Economics, but the website is not fully informative (they have clearly no incentives to provide the cons). Are you going to reply? If so, how long will your message be? Would your choice be affected if you shared the same nationality and language?

Academics

Banking on Technology: How Changes in Technology and Consumer Tastes Are Impacting the Consumer Banking Industry

Between classes, you decide that you need an injection of caffeine to help you remain awake in your afternoon Game Theory lecture. You walk briskly to the café and order your noisette. When it comes time to pay, you take out your iPhone and hold it to the point-of-sale system, quickly and conveniently purchasing your beverage via Apple Pay, without the direct usage of any cash or card. As you sip your stimulant, you remember that it’s the first of the month and your propriétaire is expecting his monthly rent. Not wanting to further damage your already strained relationship with him, you open up the Hello bank! app on your aforementioned iPhone and transfer the payment seamlessly by simply entering his mobile number. With a few minutes more to kill before class, you check in on the performance of the savings you sensibly set aside from your last internship by similarly accessing the app of Marie Quantier, an up-and-coming robo-advisor.

Academics

Interview with Marianne Fay

Marianne Fay is the Chief Economist for Sustainable Development Vice Presidency at the World Bank. She holds a PhD in Economics from Columbia University. Previously, she served as the Chief Economist for Climate Change. She has contributed to many papers and books on topics like infrastructure, climate change, urbanization, and decarbonisation. The TSEconomist team met with her during her visit to TSE in November 2017 where she presented a talk on Green growth and decarbonisation.

Academics

Interview with Ariel Pakes

Biography

Ariel Pakes is the Thomas Professor of Economics at Harvard, where he teaches courses in Industrial Organization and Econometrics. His research has focused on developing methods for empirically analyzing market responses to environmental and policy changes, and has done work for a number of consultancies, government agencies, and large firms. Much of his methodological work has been incorporated into the way government agencies evaluate the likely impact of policy changes. Ariel has mentored over fifty doctoral students, many of whom are now leading researchers at prestigious institutions. He received the Frisch Medal of the Econometric Society in 1986, was elected the Distinguished Fellow of the Industrial Organization in 2007 and in 2017 received the Jean-Jacques Laffont prize, after which he was kind enough to spare the time for this interview. 

Academics

Intelligent Infrastructure: The Future of AI

“It is not enough to build an AI [Artificial Intelligence] system that makes a robot work across the screen, do computer vision problem or beat someone in chess contest. We have to work on these things like good engineers do, to solve problems,”  Michael I. Jordan (Professor in Electrical Engineering and Computer Sciences at University of California Berkeley) said this in a recent lecture on perspectives on AI. Building a creative problem- solving AI brain has fascinated and frightened people for several decades now. The invention of the programmable digital computer in the 1940s–a machine based on mathematical reasoning–inspired a few scientists to begin thinking of building an electronic brain. While scientists would subsequently create robots, these machines would rarely have any sort of intelligence.

Academics