Transcript from an interview with Jean Tirole
Interview with Jean Tirole on 6 December 2014, during the Nobel Week in Stockholm, Sweden.
Could you please explain your Nobel Prize awarded work in simple terms?
Jean Tirole: My work, which has been awarded the prize, is on the regulation of industries. The regulations of industries include what we call anti-trust which mean that churches and courts and anti-trust authorities check on behaviour of large firms, to check there is no abuse of a dominant position so that the large firms don’t abuse their power. It also includes regulation, regulation of what’s called network industries, so the telecom industry, electricity industry, railroad, post offices and also a little bit of regulation of banks which of course has been a very typical issue lately.
At what point did you realize your work was a breakthrough?
Jean Tirole: I am not sure that my work is a breakthrough. I have done a lot of different pieces of work because this field actually is very diverse and very rich. Two industries are not the same, all industries are different. For example, the payment card industry when you use your Visa or American Express card doesn’t work at all like Google or doesn’t work at all like the cement industry or the telecoms industry – they are all different so we have to build a number of series and /---/
work so as to understand those industries better. So it is more like a accumulation of work, not only by me but also by my colleagues and the entire profession which has made it easier for regulators and competition policy, for central banks, for regulators to deal with those large firms, but I don’t think there is really a breakthrough, it is more like an accumulation of different contributions by me and many other people.
What brought you to science?
Jean Tirole: What attracted me about economic sciences, well, when I was a student, I didn’t study economics to start with. When I was in high school, I liked mathematics because it is very challenging and intrigued and then I liked social sciences, but I didn’t know anything about economics, I liked history, I liked psychology. And then when I was 21, I was studying engineering and mathematics, I discovered economics and I loved economics because it basically combined the rigour of mathematics and this human aspect of social sciences so then I decided to do some economics and I went for PhD at MIT in the US, but it was very late actually, I discovered economics.
Who is your role model, and why?
Jean Tirole: I have a lot of role models. My adviser of course, Eric Maskin, who got the Nobel Prize in 2007, he is a fantastic researcher but also a wonderful person, human being. And Jean-Jacques Laffont actually was my mentor. He started the old school in Toulouse, he was a great scientist, but instead of being at a top university in the US, he decided to be in Toulouse in France and to build something. He was a very dear friend. He passed away in 2004, he was a very dear friend. I learned a lot from him, both in terms of work but also, just like with Eric Maskin, as a human being. And of course, there are lots of other mentors, Paul Samuelson, Ken Arrow – you know, all the great economists and many others as well, you know, standing on the shoulders of science as Newton used to say.
What were you doing when you heard you had been awarded the Nobel Prize?
Jean Tirole: It was strange, I was working with a collaborator with a grand proposal for the European Research Council and I was not expecting the prize, so I didn’t hear the phone. It was on the vibrating mode. So, the committee actually tried to call, and I understand they tried to call my secretary as well and so on and so forth. And at the end I heard the phone, it was vibrating on my desk and I took the phone. The number was +46, so I said: “Uh-oh”. I was very surprised and that was wonderful news.
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Nobel Prizes and laureates
Six prizes were awarded for achievements that have conferred the greatest benefit to humankind. The 12 laureates' work and discoveries range from proteins' structures and machine learning to fighting for a world free of nuclear weapons.
See them all presented here.