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发帖数: 29853 | 1 http://m.townhall.com/columnists/thomassowell/2016/09/06/misleading-statistics-n2214085
Misleading Statistics
Thomas Sowell| September 06, 2016
Mark Twain famously said that there were three kinds of lies -- "lies,
damned lies, and statistics." Since this is an election year, we can expect
to hear plenty of all three kinds.
Even if the statistics themselves are absolutely accurate, the words that
describe what they are measuring can be grossly misleading.
Household income statistics are an obvious example. When we hear about how
much more income the top 20 percent of households make, compared to the
bottom 20 percent of households, one key fact is usually left out. There are
millions more people in the top 20 percent of households than in the bottom
20 percent of households.
The number of households is the same but the number of people in those
households is very different. In 2002, there were 40 million people in the
bottom 20 percent of households and 69 million people in the top 20 percent.
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A little over half of the households in the bottom 20 percent have nobody
working. You don't usually get a lot of income for doing nothing. In 2010,
there were more people working full-time in the top 5 percent of households
than in the bottom 20 percent.
Household income statistics can be very misleading in other ways. The number
of people per household is different among different racial or ethnic
groups, as well as from one income level to another, and it is different
from one time period to another.
The number of people per American household has declined over the years.
When you compare household incomes from a year when there were 6 people per
household with a later year when there were 4 people per household, you are
comparing apples and oranges.
Even if income per person increased 25 percent between those two years,
average household income statistics will nevertheless show a decline. When
the income of 4 people rises 25 percent, this means that 4 people are now
making the same income as 5 people made in an earlier time. But not as much
as 6 people made before.
So household income statistics can show an economic decline, even when per
capita income has risen.
Why do so many people in the media, in academia and in politics use
household income statistics, when the number of people per household can
vary so much, while individual income statistics always mean the average
income of one person?
Although individual income statistics can give a truer picture, not everyone
makes truth their highest priority. Alarming news that household incomes
have failed to rise, or have actually fallen, is more exciting news for the
media, or for alarmists in academia or in politics.
Such alarming news can attract a larger audience for the media, and can
justify an expansion of government programs dear to the heart of academics
on the left, or to politicians who just want more power to hand out goodies
and collect more votes from the beneficiaries.
Even individual income statistics have pitfalls when they lump together very
different kinds of income, as is usually the case. Incomes from salaries
are very different from incomes from capital gains.
A salary is usually earned and paid in the same year. Capital gains received
in a given year can be paid for value accrued over a number of years. If
you paid $100,000 for a home or a business in the past, and then sold it 20
years later for $300,000, have you made $200,000 per year when you sold it
or $10,000 a year for 20 years?
In the income statistics, your income will be recorded the same as that of
someone on a salary of $200,000 a year.
What difference does that make? It makes a big difference when most low and
moderate incomes are from salaries, while incomes in the highest brackets
are more likely to be primarily capital gains -- whether from the sale of
homes or businesses, or receiving an inheritance, cashing in stock options,
or some other forms of capital gains.
This means that statistics on income inequalities are often comparing high
multi-year earnings with lower single-year earnings -- that is, comparing
apples and oranges.
Such statistical distortions are discussed more fully in my book "Wealth,
Poverty and Politics." In an election year, it might be worth taking a look.
http://m.townhall.com/columnists/thomassowell/2016/09/06/misleading-statistics-n2214085 | g********2
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