The Visual Display of Quantitative Information

by Henry Farrell on March 10, 2008

“Lane Kenworthy”: shows how it’s done.


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Largest Eph Income in 2007 » EphBlog
03.10.08 at 12:38 pm
The Ambrosini Critique » Blog Archive » Beautiful evidence
03.11.08 at 10:57 am



bigTom 03.10.08 at 5:16 am

It would be more useful to use a logarithmic verticle scale, then the poor poor people wouldn’t all be squished together at the bottom. (But maybe by using a linear scale that was what you wanted to show).


qb 03.10.08 at 5:31 am

i knew the numbers but that sort of brought it home for me. thanks for posting.


jlr 03.10.08 at 5:54 am

I’m not sure if this post is supposed to be interpreted ironically or not. I’m sure the figures are depressing, but this is really a poor and distorted way to display this data. It cries out for a log scale. Of course the absolute difference for the folks at the bottom is far less than for those at the top. The useful measure here is the multiplicative change relative to the original values, and that can be best displayed logarithmically. The numbers, displayed correctly, will no doubt speak for themselves; there is no need to game them, doing so will only lend credence to those who would impeach them.


shteve 03.10.08 at 10:53 am

I take it the only way out is wage inflation. Instead what we have is price inflation.


stuart 03.10.08 at 11:51 am

bigtom, most people don’t understand logarithimic scales, if you wanted to avoid the scaling issue but still make most of the point the original grapher was after it might be better to index them all to 100 at the beginning of the graph and see what that does.


DickHarmer 03.10.08 at 1:02 pm

bigtom, Your brain’s been marinated too long in standard practice. If you want to convey actual magnitudes – which is the point here – this is precisely the way to depict this data.


HH 03.10.08 at 1:16 pm

The chart shows the results of a successful effort in the USA to cap the living standards of the vast majority of the population and transfer the gains of two decades of increasing productivity to a plutocratic elite.

This was accomplished by the deployment of a mercenary cadre of opinion makers and propagandists using television and legalized political bribery via campaign donations.

Whether this remarkable transfer of wealth and power is sustainable will depend on the ability of citizens to use the public Internet to counter the plutocratic power of broadcast media.


Matthew 03.10.08 at 1:23 pm

Only if you believe its the proportional difference that counts, not the absolute difference. Normally we talk about the former, but I can see a case for the latter.


Barry 03.10.08 at 1:26 pm

Somebody posted a very tall, skinny graph, so that they could use a linear scale, and show all quartiles at the same time (with the top quartile broken down into pieces).

I wish that I had saved that graph.


wolfgang 03.10.08 at 1:42 pm

If one believes in log-utility a logarithmic scale should be used for the y-axis imho.


Andy 03.10.08 at 2:47 pm

I disagree, this graph is virtually unreadable. I see one line going up but cannot tell at all what is happening to the other two lines. It looks like the 40-60 group is going up, but who knows by how much. And who can tell about the bottom series. Just terrible presentation.

You don’t need a log-scale to fix this. Just graph it in %-changes year-to-year or scale all series to 100 in 1980 so you can see differential trends clearly. Another possibility is the ratios of these three series over time (which is a standard presentation in the inequality literature).


David Estlund 03.10.08 at 5:01 pm

It’s a telling graph. Could you just quickly cite the sources (possibly adding them right into the post?). Not that I doubt them. They’d just help when using the graph to argue with Republicans.


mpowell 03.10.08 at 6:18 pm

If one believes in log-utility a logarithmic scale should be used for the y-axis imho.

That would give you an idea of the utility growth. Then we could sum up the different parts by weight, and I’m sure we’d see a decrease in net utility over the time period. But the point is to show the vast difference in linear allocation, b/c if you could swap these amounts efficiently, they would swap linearly. The only problem is that we can’t see much regarding the relative changes in those other groups.

I looked into this issue quite a bit recently. It seemed to me that for each percentile in the US economy, you could talk about their growth (or loss) in their share of US income. This growth seems to have been a mostly monotonically increasing function of the percentile. It seems, depending on your time period of measure, the zero-crossing is somewhere in the 90-95 percentile range. This is pretty astonishing and also convenient. Since I fall approx in that range, I can be very bothered about this issue w/o having to feel guilty that I benefited from an unfair growth in my income share. Or in other words, there is perfectly good reason for me to advocate a tax increase on those making more than me. (though I am willing to pay more taxes as well, if it comes to that)


notsneaky 03.10.08 at 6:53 pm

Of course it depends on who your target audience is (just like writing say a Lit paper). If it’s “professionals” who are down with log scale, use log scale. If it’s the general public which has trouble with that sort of thing then use the absolute values and maybe state in words what’s going at the bottom. Or you can go completely nutzoid and have not one, but TWO, yes TWO, graphs.


notsneaky 03.10.08 at 6:57 pm

And he’s right that the Gini measure of inequality is pretty much useless when talking to non-inequality-studying folks. For one, there’s some problems with it that you always need to be aware of. Second, how much of a Gini in exactly “a lot”? If it changes from, say, .45 to .49 is inequality skyrocketing or could that just be due to measurement error or something?
On the other hand, using quintile shares and the like has its own problems.


smaug 03.10.08 at 7:19 pm

I think an index is better, largely on legibility grounds. The overall effect is the same, however, in terms of the gap.

The magnitude difference between incomes and between initial positions is just not high enough to make it more informative rather than misleading.


smaug 03.10.08 at 7:20 pm

Re my 17, the “it” is the log-scale.


John Emerson 03.10.08 at 10:34 pm

I disagree, this graph is virtually unreadable. I see one line going up but cannot tell at all what is happening to the other two lines.

Hint: they’re not going up much, if at all. The top line more than triples and almost quadruples. If the bottom two lines did that, you’d easily be able to tell. One goes from slightly under $50,000 to slightly over $50,000. One stays significantly below $25,000. Significant change in either number (more than about +/- 20%, which would be $45,000 to $54,000) would have been clearly visible. There was no such change. That’s what the graph was designed to show.

If you can’t read the graph you probably you should major in art history or aromatherapy.


Barry 03.11.08 at 2:10 am

19 comments, and note one jsutifying the situation, or denying it. A new record!


Sortition 03.11.08 at 3:30 am

I find this graph more informative. Everybody knows that some people are extremely rich, but it is surprising to find that 1% of the families control about a fifth of the total income and 10% control about half of it. Thus not only are some people very rich, they are so rich as to make the rest significantly poorer.


mq 03.11.08 at 11:20 pm

It’s a telling graph. Could you just quickly cite the sources (possibly adding them right into the post?).

I’ll bet it’s from here:

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