Transcript
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Welcome to another episode of Conversations with Coleman. If you're hearing this, then you're on the public feed, which means you'll get episodes a week after they come out and you'll hear advertisements. You can gain access to the subscriber feed by going to ColemanHughes.org and becoming a supporter. This means you'll have access to episodes a week early, you'll never hear ads, and you'll get access to bonus Q and A episodes. You can also support me by liking and subscribing on YouTube and sharing the show with friends and family. As always, thank you so much for your support. Welcome to another episode of Conversations with Coleman. My guest today is Professor Abhijeet Banerjee. Professor Banerjee is a Nobel Prize winning economist, an Econ professor at mit, and a co founder of the Abdul Latif Jameel Poverty Action Lab. Banerjee and I discuss the difference between empirical work and theoretical work in economics. We talk about Banerjee's Nobel Prize winning research on alleviating global poverty. We talk about whether immigrants drive down wages for native workers. We talk about the role of financial incentives in driving human behavior. We talk about welfare. We talk about the effect of globalism on American industries like manufacturing and the social consequences of having whole industries die out and much more. So without further ado, Abhijeet Banerjee Professor Banerjee, thanks so much for coming on my show.
A (2:01)
Thank you for having me.
B (2:03)
So before we get into all of the topics of your expertise, can you give my listeners who, if they haven't heard of you from your Nobel Prize or your several books, for a wide audience, a sense of who you are and how you came to be interested in theoretical and experimental economics?
A (2:24)
I'm an economist. I'm a professor at MIT and I've been a professor here for 30 years. I guess my general interest is using economics to navigate the world to understand how to make the world a better place. And that means, unfortunately, a lot of economics makes that look like a stretch. It looks like statements about how things are perfect as they are and how in any case if you try to do something, something else will go wrong. I've sort of always been interested in how things could go right. And in fact what is nice about being an experimental economist, somebody who actually is involved in running large scale field experiments with policies, is that you actually see that in the world. Lots of things that you try do work, you do find that there's lots of good news to be had once we try. I Think there's a sense in which as a field we are a little bit given to the bad news. Things could go wrong, this could go wrong, that could go wrong. I have always been, I guess, more a glass half full guy. And I look for the full glasses. And to be honest, when you try things out, rather than speculate about it, a lot of those things do work. So I think a lot of the. My inspiration comes from looking for things that work, trying to identify, find rigorous evidence for them, and then to try to actually take it to policymakers, try to persuade them that they should also do it. So that's been my work. We 20, almost 20 years ago, we set up an organization called the Abdul Latif Jameel Poverty Action Lab. And what we do in the Poverty Action Lab, we have about a thousand odd professors associated with it. We do randomized control trials of policies that are of relevance to people's lives and usually having to do with poverty, where we're mostly interested in policies in some way or the other which help poor people. So that's, that's. And that there's now over a thousand randomized control trials which we have finished, and they are in 80 odd countries and including the US, including Europe, including many developing, most major developing countries. And our goal is to try to put the science of policymaking on a firmer ground, to rather move it away from guesswork and intuition. And my hunch is this, and I think people behave this way or that way to actually show when you try it, does it work or not. That's the ultimate test.
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