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Lee Harding“This is the best number I’ve ever seen in my life!” Jim Cramer told CNBC.

The U.S. Bureau of Labor Statistics had just reported a 3.5 percent unemployment figure in the United States. The November 2019 percentage was the lowest in 50 years.

Others would say that might not be the case and that such figures misrepresent reality.

Economists and other informed observers have more than a little evidence to back their claim.

The stakes are high, so what’s the truth?

That’s a question John Williams has tried to answer. The economic consultant graduated with his MBA in 1972 and has had a career that spans decades.

One of his early clients was a large airplane manufacturer that found its econometric model to predict revenue passenger miles had lost its relevance. The model relied on the gross national product (GNP).

Williams could only solve the problem when he discovered flaws in the government’s calculation of GNP. He made adjustments that worked for a while – until the government changed its GNP calculations yet again.

Williams began to question not just GNP calculations, but all of the government’s economic statistics. He asked business economists to assess their quality and most agreed it wasn’t very good. He interviewed key people involved in government reporting, past and present. In time, he had joint meetings with representatives of the statistical agencies and even testified to U.S. Congress. 

By now, Williams has made more than 1,000 presentations to government, business, the press, academia, banks and investors. His conclusion is that the quality of government reporting has deteriorated “out of the realm of real-world or common experience.”

Stephen D. Simpson agrees. His 2019 article 5 Government Statistics You Can’t Trust puts unemployment, inflation, gross domestic product and deficit accounting on that list.

“The accuracy of reported economic data is a problem in virtually every country,” he says. Sometimes this is intentional, as “countries engage in blatant manipulation to influence their obligations, manipulate markets (equity, bond and exchange) or influence capital flows.”

If You Want To Know The Real Rate Of Inflation, Don’t Bother With The CPI, Perianne Boring told Forbes readers in a 2014 article. The raw data the Bureau of Labor Statistics uses is unavailable. When she asked them why, she was told, “so companies can’t compare prices.” She refused to believe it, since such prices were available by a simple Internet search.

Boring says the CPI didn’t jive with other government statistics either.

The money supply rose 4.9 percent in 2012, yet the bureau said the cost of goods only went up 1.5 percent.

The U.S. Department of Agriculture noted that beef prices rose 26 percent over the previous five years, but the bureau said beef and veal only rose 20 percent.

When she asked a statistician at the bureau about the discrepancy, he could only reply, “I would expect those numbers to be a little closer together.”

Between 1979 and 1999, the bureau made more than 20 changes to the way it calculated inflation. Williams says the consumer price index hasn’t reflected actual out-of-pocket costs since the early 1980s.

The premise, as Simpson explains, is that, “at least some of the price difference between a good bought today and a good bought yesterday can be ascribed to significant quality improvements. Unfortunately, this is a highly subjective determination and one that does not always sync with reality.”

Another major change came in the 1990s when the government stopped measuring the price changes of a fixed basket of goods, and replaced it with a substitution-based basket of goods. The idea is that when times get tough, a person might stop eating steak and have hamburger instead.

Why would the government use these concepts to erode inflation calculations?

Quite possibly because tax brackets, social programs and some pension programs are indexed for inflation.

Williams laments, “Without the changes made to CPI calculations of the last several decades, social security payments would be more than double what they are today. Indeed, with the use of a substitution-based index the resulting cost of living adjustments promise only a declining standard of living.”

Lower inflation figures also mean that real (versus nominal) gross domestic product (GDP) figures will be skewed upwards. Every government wants to tell the public that the economy is burgeoning under their direction and warped stats help them when reality can’t.

Williams found the post 9-11 GDP stats to be impossibly optimistic. He concluded, “the GDP is heavily modeled, imputed, theorized and gimmicked.”

So is the 3.5 percent unemployment figure that Cramer was raving about accurate? And is today’s the best since 1969?

Starting in the 1960s, bureau unemployment figures began to exclude “discouraged workers.” These are defined as people who want a job but don’t have one and haven’t looked for one lately. (Canada has a similar methodology.)

To the common person, if a person is unemployed, they’re unemployed. But in the government stats, if someone hasn’t looked for a job, they don’t even exist.

If the unemployment figure is not 3.5 percent, then what is it? 

That number 6.9 percent is closer to the truth, but still ignores those people who are available to work but haven’t looked for a job in more than 12 months.

Williams’ shadow stats claim if those people are included, real unemployment stands at 20.9 percent, the best in 10 years but not 50.

Is Williams correct?

In a 2015 article, Ed Dolan examined Williams’ figures and found them less believable than the government’s.

Williams believes the data collection was changed to hide job losses due to the North American Free Trade Agreement, but that’s far from clear.

Sir Charles Dilke once wrote, “There are three kinds of lies: lies, damned lies, and statistics.”

Keeping accurate statistics for an entire nation is extraordinarily difficult.

Given the billions of dollars and political agendas at stake, and ease with which hidden methodologies can obscure the truth, citizens should always take government stats with a measure of reserve.

Lee Harding writes for the Frontier Centre for Public Policy.

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