Links (with annotation)
October 23, 2014
I’ve been heads down writing this week but I wanted to share a bunch of great stuff coming out.
- Here’s a great interview with machine learning expert Michael Jordan on various things including the big data bubble (hat tip Alan Fekete). I had a similar opinion over a year ago on that topic. Update: here’s Michael Jordan ranting about the title for that interview (hat tip Akshay Mishra). I never read titles.
- Have you taken a look at Janet Yellen’s speech on inequality from last week? She was at a conference in Boston about inequality when she gave it. It’s a pretty amazing speech – she acknowledges the increasing inequality, for example, and points at four systems we can focus on as reasons: childhood poverty and public education, college costs, inheritances, and business creation. One thing she didn’t mention: quantitative easing, or anything else the Fed has actual control over. Plus she hid behind the language of economics in terms of how much to care about any of this or what she or anyone else could do. On the other hand, maybe it’s the most we could expect from her. The Fed has, in my opinion, already been overreaching with QE and we can’t expect it to do the job of Congress.
- There’s a cool event at the Columbia Journalism School tomorrow night called #Ferguson: Reporting a Viral News Story (hat tip Smitha Corona) which features sociologist and writer Zeynep Tufekci among others (see for example this article she wrote), with Emily Bell moderating. I’m going to try to go.
- Just in case you didn’t see this, Why Work Is More And More Debased (hat tip Ernest Davis).
- Also: Poor kids who do everything right don’t do better than rich kids who do everything wrong (hat tip Natasha Blakely).
- Jesse Eisenger visits the defense lawyers of the big banks and writes about his experience (hat tip Aryt Alasti).
After writing this list, with all the hat tips, I am once again astounded at how many awesome people send me interesting things to read. Thank you so much!!
Categories: data journalism, data science, economics, finance
mathbabe 
I’m actually kind of confused about point no. 5. I saw this earlier, and I feel that I must be misunderstanding something.
To me, the chart as presented actually looks somewhat more like a meritocracy than I would honestly expect: if you are poor and complete college, then 20% of you will be in the top quintile at age 40. Conversely, if you are rich and drop out, a smaller portion of you will be so. In fact, if you take the top two quintiles, it’s even more striking: 41% of poor people who have college degrees will be in the top 40% of income earners, while only 19% of rich people who are high school dropouts will be. Isn’t this a good thing?
It also seems misleading to have the arrow which links the bottom quintile of poor people with the top quintile of rich people. So those are about the same size. What exactly does that represent? It seems more reasonable to compare horizontally, in which case it appears that being poor and going to college is actually better for you, in the long run, than being rich and dropping out of high school.
Am I misunderstanding something?
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I agree it’s a confusing graphic, not to mention confusing data. I think it would have made more sense if we had also compared these two groups to “poor high school dropouts” and “rich college grads” and seen how very different those stats are.
In other words, we’re seeing two things that look pretty similar, but that’s only interesting if you know that other things are very different indeed from them.
We can get some sense of this from Figures 10 and 11 in the appendix of this paper, although those are not broken down into “black” and “white.” But we can get some idea of the black/ white statistics in Figures 8 and 9.
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Some of those figures clarify it a bit, but they also confuse me a little bit more too. In particular, figure 9 is a little surprising in that it looks (almost) like it’s evenly split up amongst the different quintiles: it’s pretty close to each quintile (at birth) yields an even split among all quintiles later in life. It is weighted towards the wealthier end, but it’s not far from that.
Then there’s (in figure 10) the seemingly odd fact that if you are born in the 4th quintile, that 77% of such people will end up in the bottom two quintiles and… wait, 6% are split among the top three quintiles? That doesn’t add up to 100. That’s probably the problem there.
The sad part is in figure 8 though, the complete lack of any people born into the top quintile…
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I think you want to consider what “true mobility” would look like, if it existed, namely equal size boxes everywhere, and then compare that ideal to those matrices.
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I agree with Charles on this. What the chart shows is that poor kids who graduate college have significantly higher income than rich kids who drop out of high school. E.g. 41% of the first category are in the top two quintiles, as opposed to only 19% of the second category. The inequality manifests itself in the fact that rich kids are a lot more likely to finish high school and college, which is not shown in this chart.
Incidentally, figure 11 in the original paper shows that, among college graduates, though people born in the bottom quintile of family income end up poorer than other college graduates, for people born in the other quintiles, their family income at birth has essentially no relation to their income at 40, in terms of quintile.
Click to access reeves-sawhill.pdf
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Ah, thanks! That’s one of the big things that I missed thinking of, the fact that more rich kids will finish high school and college than poor kids. That makes the picture make a lot more sense now, and is something that is rather important to bear in mind with these stats.
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From the bank article: “to the white-collar defense lawyers of Washington, the banks are the victims as they bow beneath the weight of regulators’ remarkably harsh punishments.”
Remarkably harsh punishments? You mean, like jail time? Where is our Pecora? Where is our Eccles? (We have Bill Black, but have not used him.)
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Re: achieving poor kids vs failing rich kids
As commented here and in the comments on the WP blog post itself, that blog entry is very weak. Beyond the problems with interpreting the graphic presented, the underlying paper suggests:
(a) the data is sparse for the high school drop-outs from top income quintile families (which itself isn’t surprising since, remember, top income quintile kids get a lot of help and are unlikely to become high school dropouts)
(b) choosing to compare those two cohorts is cherry picking. If you look at high school dropouts from families in any other income quintile, they do significantly worse than college grads from the lowest income quintile families. This is particularly true of those from the second highest quintile suggesting these “better-off” kids aren’t immune to the consequences of personal failure. Also, this suggests improving educational attainment is a key area for intervention.
However, the Fed paper is worth scanning directly. Two striking exhibits particularly struck me:
(1) Figure 8 shows a consistent pattern of downward mobility for black Americans. Even for those born in Q4, almost half fell to Q1 or Q2 by age 40.
(2) Figure 25 suggests that interventions only made a marginal difference in closing the black-white success gap.
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