August 3, 2010
Unethical Statistics Lead Us Astray
By Ron Robins, Founder & Analyst -
Investing for the Soul
How did the developed world economies come to be in
such a mess? It seems that revisions to key U.S.
statistics over the past three decades may have played a
significant role in fashioning an illusion of unbounded
prosperity. Inflation and unemployment rates were
lowered and a brighter spin on the gross domestic
product (GDP) fashioned. Unaware of the subtleties of
many statistical changes, the media, investors, and the
general public believed in a new golden era of an ever
increasing GDP.
This golden economic era even had a name: the
‘Cinderella economy.’ Believing in the illusory
Cinderella economy, people made financial and economic
decisions that many subsequently regretted as they saw
their homes and stocks plunge in value. They were
uneducated about, and duped by statistics that helped
lead them astray. These statistics are thus, ‘unethical
statistics.’
Chief among these revisionist statistics is the Consumer
Price Index (CPI). Most people believe it is the measure
of inflation. But the way it is now constructed makes it
a ‘cost-of-living-index.’ The two are very different
from each other. Inflation, technically, usually means
inflation of the money supply and might be evidenced by
rising prices. And rising prices are observed by
monitoring the same products and services from period to
period to period!
On the other hand, a cost-of-living index like the CPI
refers to price changes in what people buy, and this
basket of goods and services changes frequently—as does
the way in which the numbers are massaged.
The changes made by the U.S. Bureau of Labor Statistics
(BLS) to the U.S. CPI over the past three decades have
been staggering. As John Williams, an
economist-statistician who has made it his life’s work
to study U.S. government statistics, states, “Inflation,
as reported by the Consumer Price Index (CPI) is
understated by roughly 7% per year [compared to that of
the pre Clinton Administration]. This is due to recent
redefinitions of the series as well as to flawed
methodologies, particularly adjustments to price
measures for quality changes.” For June 2010, the CPI
(CPI-U) showed an annual gain of 1.1 per cent compared
to 8.4 per cent had the 1990 methodology been used,
according to John Williams’ website, http://www.shadowstats.com/.
One simple example of these changes refers to
substitution. Mr. Williams says the “cost of living was
being replaced by the cost of survival. The old system
told you how much you had to increase your income in
order to keep buying steak. The new system promised you
hamburger, and then dog food, perhaps, after that.” So,
as the price of beef goes up, the statisticians
producing the CPI believed the consumer would substitute
another cheaper meat, say chicken, for the beef.
Furthermore, the weighting of beef in the index could be
lowered too. Hence the CPI component related to meat
costs might not change even though the cost of beef had
risen markedly.
Other complex and controversial issues with the CPI
series include: (1) adjustments for quality
improvements, such as when a washing machine comes with
improved technology but sells for a similar price to the
old one, the CPI component registering washing machine
costs might show a price fall; (2) ‘intervention
analysis’ which relates to spreading out price changes
over extended periods of time so that sudden price
changes are smoothed out and do not shock people; (3) an
outdated focus on a ‘core-CPI’ which excludes energy and
food as if they do not matter because statistically they
are too volatile; and, (4) a housing cost component that
for many people is irrelevant.
The problems surrounding the employment/unemployment
statistics are similarly disturbing. One huge concern
here is the uncounted millions of individuals who have
given up looking for work for more than a year. If they
were included, June’s U.S. unemployment rate of 9.5 per
cent (BLS data) would be 21.6 per cent according to Mr.
Williams.
In a recent column I explained why the gross domestic
product (GDP) statistic had to be replaced. That was
primarily because it does not measure our well-being. My
criticism here concerns how the numbers within the GDP
are constructed. As Mr. Williams states, the “upward
growth biases built into GDP modeling since the early
1980s… have rendered this important series nearly
worthless as an indicator of economic activity.”
One of the upward biases in GDP referred to by Mr
Williams is the downplaying of inflation in calculating
the real GDP. This reduction of inflation results in a
higher GDP. The raw or nominal GDP data has to be
inflation adjusted by a ‘deflator’ to arrive at the real
GDP number. For simplicity’s sake, say the nominal GDP
is $1 million. If you have high inflation of 10 per
cent, then your GDP is ‘deflated’ by 10 per cent for a
real GDP of $900,000. But if you manage to keep down the
inflation rate to 5 per cent, then the deflator is only
$50,000 and your real GDP is now $950,000. Hence, the
potential bias to create a lower inflation (deflator)
number.
In its latest estimate of first quarter 2010 GDP the
U.S. Bureau of Economic Analysis (BEA) said the economy
grew at a year over year rate (not annualized) of 2.4
per cent. Mr. Williams’ believes it was actually closer
-1.5 per cent!
Unbeknownst to the investing and general public, the
changes in methodologies made to the principal
statistics—the CPI, unemployment and GDP numbers—over
the past thirty years helped them believe in a
Cinderella economy and an ever expanding GDP. Believing
that, they made ill-informed financial and economic
decisions and suffered the consequences as the golden
age evaporated before their eyes.
Had there been greater transparency, questioning and
education concerning these statistics, we may have
averted some of the economic excesses of recent times.
But, unfortunately, that did not happen. Clearly,
‘unethical statistics’ may have played a large part in
leading us astray.
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