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🗓️ 7 November 2011
⏱️ 66 minutes
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0:00.0 | Welcome to Econ Talk, part of the Library of Economics and Liberty. I'm your host Russ Roberts |
0:13.9 | of George Mason University and Stanford University's Hoover Institution. Our website is econtalk.org |
0:21.2 | where you can subscribe, find other episodes, comment on this podcast, and find links to |
0:26.5 | another information related to today's conversation. Our email address is mailadicontalk.org. We'd |
0:33.6 | love to hear from you. Today is November 1st, 2011, and my guest is Stephen Kaplan, the new |
0:43.4 | power family distinguished service professor of entrepreneurship and finance at the University |
0:49.0 | of Chicago's Booth School of Business. Steve, welcome to Econ Talk. Thank you. Good to be here. |
0:55.5 | Our topic for today is what might be called the super rich, what gets called sometimes the top |
1:01.0 | one percent. Sometimes we're going to look at the top one tenth of one percent, and we're going |
1:06.2 | to organize our conversation around a paper that we will link to that you've written with Joshua |
1:11.1 | Rao called Wall Street and Main Street. What contributes to the rise in the highest incomes? |
1:16.9 | It's published in the Review of Financial Studies in 2009. There's a lot of evidence that |
1:22.2 | the richest Americans are richer than the richest Americans of the past. I phrase it that way |
1:28.0 | because it is important to remember that in most of the recent discussions of inequality and |
1:33.4 | it's a very hot topic right now, we are typically not talking about the same people. So when people |
1:39.3 | say the top one percent have gotten richer, that does not mean that somebody in say 1980 necessarily |
1:45.7 | has learned who was in the top one percent is now making a lot more or has a bigger share than they |
1:51.8 | had in today than in 1980 because they're taking a snapshot, a slice in time of a segment of the |
1:59.6 | income distribution in 1980 versus today or today versus 1995. So that's a really important |
2:06.6 | distinction. I'm sure we'll blur it because of the nature of the English language, but I want |
2:10.6 | everybody who's listening to remember that that's what the data are literally measuring when we |
2:16.9 | usually are talking about the top one percent. There are data that look at the same people over time |
... |
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