I like your paper very much. I want to write a paper with above pictures. Would you please give me ti permission?

Thank you for your consideration.

Best regards.

Chenguang Lu

Such a curve goes from the origin to the gross national annual earnings on the y-axis and the slope is proportional to the income of persons on the x-axis. If the lower half of the earners aggregated one quarter of the gross the x mid-point of the curve would pass through a point one quarter as high in the y direction as the top point, which is the gross national earnings.

In all countries the real curve is flat at the beginning, representing children and beggars living under bridges, and the last part is an almost vertical spike. These two very important regions are not detailed in most graphs. The census, for example, manages to ignore them by dealing only with quintiles.

First, Census table shows per capita income (comparing apples to apples now — comparing income to income) increased 100% from 1967 through 2007).
http://www.census.gov/hhes/www/income/histinc/p01AR.html

Census mean family income quintiles table show:
5th quintile mean grew 22.4% over that span;
4th grew 31.4%;
3rd mean (effectively median) grew 47.3%;
2nd grew 64.6%;
1st (w/o adjusting for top coding) grew 95.8%.

If you play my little top coding adjustment game using per capita income for your overall growth gauge (should be somewhere inside the ballpark):
1st quintile income grew 175.4%. (I mis-remembered above that my adjustment doubles top quintile income—rather it approaches doubling income growth.)
http://www.census.gov/hhes/www/income/histinc/f03AR.html
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Best inequality graph I’ve seen in a long time:
http://delong.typepad.com/delongslides/2008/08/income-gains-19.html

Absolutely right. John Kenneth Galbraith in his classic “The Great Crash, 1929″ listed high income disparity as the number one reason for the crash and resulting depression.

What doesn’t receive nearly enough discussion, in my opinion, is that extreme income inequality can also weaken and even endanger our democracy. How many more decades can middle and lower class families be expected to put more workers and hours into the workplace for little or no real gain in income before they snap? With the extraordinary financial pressures mounting on families due to excessive debt, mounting costs for health care and education, and historical destruction of asset values, I would expect the snap to come sooner rather than later.

a) Economists are unable to communicate meaningful aggregate income measures in an understandable fashion (at least understandable to sociologists)

b) Sociologists shouldn’t dabble in other fields

First, I would like to acknowledge an error on my part. At several points, I have suggested that the median family income data was deflated using the CPI (as in CPI-U). This is not correct, the median family income data is actually deflated using CPI-U-RS. Unfortunately, this creates yet another problem. The CPI-U-RS has risen substantially less than the standard CPI (CPI-U). This makes the trend line for median family incomes look better than it would if the CPI-U was used.

Why the Census uses the CPI-U-RS when the rest of the government utilizes the CPI-U isn’t clear. TIPS and Social Security are adjusted using the CPI-U. The BLS does appear to use the CPI-W. However, the CPI-W and CPI-U aren’t very different.

I agree that median family income is a useful of well being. However, it has the very serious problem that the number of earners has risen over time (as you state). I find that real median family income has risen just 6.7% since 1973 if you deflate the nominal value using the CPI-U. The increase using the CPI-U-RS is 22.3%. I don’t have the numbers at hand. However, I am reasonably sure that the number of earners per household has risen more than 6.7% and possibly more than 22.3%. This means that earnings per working family member may well have declined at the median.

To get a better understanding of the data, I checked Net National Income per-worker. NNI has risen 52.1% using the GDP deflator since 1973. Using CPI-U-RS the increase is 40.5%. Using CPI-U it is only 22.7%.

Over the same period mean (not median) wages for production workers (as defined by the BLS) have fallen 16.7% measured using CPI-W, 18.0% using CPI-U, and 6.1% using CPI-U-RS.

Clearly the data supports a very large divergence between output per-worker (or family) and actual wages. However, I don’t think the data is clearly understandable unless it is done on a apples to apples basis.

The points you make are good ones. I tried to keep this simple, but perhaps went too far in that direction. A more straightforward comparison is of the trends in productivity and median compensation. But I think family/household outcomes are of greater relevance, since earnings (and benefits) are typically pooled. For this, GDP per person (or family) is better than productivity.

Using net national (or domestic) product, deflating with the CPI-U-RS (instead of output deflator), and measuring per family rather than per person, the rise since 1973 is less than for GDP per capita. The median family income using this counterfactual would have been $83,000 in 2007, rather than $91,000. Lower, but still far above the actual level of $61,000. And there’s the additional fact of many more families now having two earners.

Lane

“Peter, what evidence do you have that the medians and means reported by the professor use different price deflaters?”

I downloaded the data from the BLS, Census, EROP, and BEA and reproduced the chart above. Just as I stated above, GDP was deflated using the GDP deflator and median family incomes were deflated using the CPI-U. I can send you a spreadsheet with all (lots and lots) of the data.

However, there are (at least) two more errors worth noting.

1. Per-Capita GDP is a poor measure of economic performance because it fails to take into account the worker / population ration. This ratio has risen dramatically since WWII. Stated differently, per-worker GDP has risen much less than people think, but this has been masked by a strongly rising worker / population ratio.

2. The number of workers per-family has risen strongly since WWII (female labor force entry). This should have caused a stronger rise in per-family incomes. In other words, the actual data understate how badly the median family is doing by not taking into account the rising number of workers per-family.

As you can see comparing per-capita GDP to median family incomes is a muddled mess.

1) From 1977 to now the percentage of Americans that have college degrees has gone from 10% to 25%. We should all be thankful for the work that these people have put in because our increasingly complex and technical world needs more educated people. Those with these degrees get more money, obviously. This also shows up in the income distribution ranked by education. In 1977 the average college person earned only 10% more than the average high school graduate. Now it is about 60%. So, the income disparity has come from a new education disparity. Its all pretty logical.

2) Since the 1990′s our current account has gotten massively in the red. Using China as an example they want to sell us goods but do not want to buy goods from us so the money they have gotten from us gets recycled into our capital markets. (They may buy Treasuries but it means that others in America don’t have to so their money now goes into stocks, real estate, etc.) These increased capital flows has had the normal effect: it raised valuations which has benefited people that have assets in the first place, ie those college graduates. So, they are getting richer.
But if China was buying our goods instead of hoarding capital we’d have jobs and income for ordinary workers and the income disparity would be a lot less.

You’re right that this would be a mistake if the professor did it, but without having the data in front of you how can you know he made this mistake?