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The Dismal Economics of Utopia

Spreading the wealth around forces massive inequalities. Duh.

by
William M. Briggs

Bio

April 18, 2010 - 12:00 am
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Socialists and other utopians are usually content to let this definition float, and let its fuzziness work to their advantage. This sly trick puts realists on the defensive, who are ever nervous about making statements that might be judged hostile to equality.

So far we have had a hint of the large-scale corruption that occurs when incomes are reported by household. Let me show you how you can go from poor to rich by the flip of a switch.

In real life, most households have one or two bacon suppliers. Some have none, some have three or more. Suppose, judging it to be absurd to award infants a salary (and not every socialist would), equality is defined to mean that each household is only allowed to have one income.

Then the mean household income would indeed be $50K. And there would be no rich and no poor households because each household earns exactly the same.

But consider per capita income. Sixteen-percent of the population will make an average salary of $50K, 24% will make an average of just $25K. These people are rich compared to the roughly 1% who will average just $6,500, and the 1% bottom-of-the-barrel poor who will average about $4,000 or less.

Best of all, our new definition of equality ensures that those who used to be rich under the old definition are now poor! In the new definition, larger households are penalized, under the old they were rewarded.

This result also assumes that people of all ages go into the averages. But neither this nor the first analysis need that assumption. We can eliminate babies: the artificial creation of rich and poor happens even if you consider only “adults.”

Perhaps utopia can still be found by eschewing household statistics and considering wealth instead of income? It cannot. But that is a lesson for another time.

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William M. Briggs is a statistical consultant in New York and San Francisco. He is an American Meteorological Society member and serves on their Probability & Statistics Committee. His specialty is on the philosophy of evidence, forecast evaluation, and marketing.
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