An unsuccessful adaptation of a classic
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A startling chart about income inequality, with interpretative difficulties

Reader Robbi B. submitted the following chart posted to Twitter by Branko Milanovic:

Brano_img

The chart took a little time to figure out. This isn't a bad chart. Robbi wondered if there are alternative ways to plot this information.

The U.S. population is divided into percentiles across the horizontal axis, presumably based on the income distribution in some year (I'm guessing 2007, the start of the recession). For each percentile of people, the real per capita growth (decline) in disposable income is computed for two periods: the blue line shows the decline during the recession (2007-2010) and the orange shows the growth (in some cases further decline) during the recovery (2010-2013).

This chart draws attention to the two tails of the distibution, namely, the bottom 10 percent, and the top 5 percent. At one level, these two groups (excepting the bottom 2%) experienced the best of the recovery. But then, they also suffered the worst declines during the recession.

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Here is one possible view of the same data, in a format with which I have been experimenting recently. You might call this a Bumps panel or a slopegraph panel.

Redo_branko

The slopes draw attention to the relative magnitude of the declines and the subsequent recoveries. (I thinned the middle 80% substantially because there isn't much going on in that part of the dataset.) If I have more time, I'd have chosen a different color instead of grayscale for those lines.

I ignored any questions I have about the underlying data. How is disposable income defined and measured? Does it carry the same meaning across the entire spectrum of income distribution? etc. (Milanovic points to the Survey of Consumer Fiannces as the source.)

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One reason for the reading difficulty is the absence of a reference point. It's unclear how to judge the orange line. Two answers are suggestive (but problematic). One is the zero line: which segments of the population experienced a recovery and which didn't? Another is the mirror image of the blue line: how much of what one lost during the recession did one recover by 2013 (roughly speaking)?

Both of these easy interpretations worry me because they carry an assumption of equal guilt (blue line) and/or equal spoils (orange line). It is very possible that the unwarranted risk-taking or fraud was not evenly spread out amongst the percentiles, and if so, it is impossible to judge whether the distribution exhibited in the blue line was "fair". It is then also impossible to know if the distribution contained in the orange line was "fair". Indeed, if the orange line mirrored the blue line, then all segments recovered similarly what they lost--this would only make sense if all segments are equally culpable in the recession.

Comments

jlbriggs

I am not always on board with your bumps/slope charts, but I think this one works really well.

I also like the progression that you are making as you do more of these panel style versions.

Nice work.

I do think a reference line at 0 is appropriate, even if it doesn't tell the full story. It's still about before and after, even if the reasons for the before and after are varied across the percentiles.

Dror Atariah

Aren't the bumps/slope a special case of parallel coordinates?

Dror Atariah

I would also add a horizontal reference line at `0` to distinguish between increase and decrease.

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