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EconTalk

Susan Athey on Machine Learning, Big Data, and Causation

EconTalk

Library of Economics and Liberty

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4.74.4K Ratings

🗓️ 12 September 2016

⏱️ 62 minutes

🧾️ Download transcript

Summary

Can machine learning improve the use of data and evidence for understanding economics and public policy? Susan Athey of Stanford University talks with EconTalk host Russ Roberts about how machine learning can be used in conjunction with traditional econometric techniques to measure the impact of say, the minimum wage or the effectiveness of a new drug. The last part of the conversation looks at the experimental techniques being used by firms like Google and Amazon.

Transcript

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0:00.0

Welcome to Econ Talk, part of the Library of Economics and Liberty.

0:09.2

I'm your host, Russ Roberts, of Stanford University's Hoover Institution.

0:13.8

Our website is econtalk.org where you can subscribe, comment on this podcast, and find

0:18.8

links and other information related to today's conversation.

0:21.7

You'll also find our archives where you can listen to every episode we've ever done going

0:26.1

back to 2006.

0:28.3

Our email address is mailadycontalk.org.

0:30.8

We'd love to hear from you.

0:32.3

Today is June 18th, 2016, and my guest is Susan Athe, the Economics of Technology Professor.

0:41.5

At the Graduate School of Business here at Stanford University.

0:44.8

She won the John Bates Clark Medal in 2007, and she is a member of the National Academy

0:49.4

of Sciences.

0:50.4

Susan, welcome to Econ Talk.

0:52.1

Hello.

0:53.3

So we're going to start with a recent paper you wrote, co-authored on the state of applied

0:58.2

econometrics.

0:59.2

It's an overview paper, and it gets at a lot of issues I think that are current in the

1:03.4

field.

1:04.4

I want to start with an example you use in there, which is a pretty important policy issue,

1:08.7

which is the minimum wage.

1:10.0

It's in the news these days, people are talking about increasing the minimum wage, you've

1:14.6

talked about it in passing on the program many times.

...

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