As pattern-seeking creatures, statistics have a peculiar hold on our minds. Quite a large number of decisions are undertaken on the basis of what statistics tell us. That is certainly true when it comes to government economic data and the blizzard of stats that come out every month; billions of dollars worth of value appears or vanishes on the basis of what these numbers say about the health, growth and direction of the economy, and the implications for company profits, interest rates and so on. (Can butter production help you predict the market's next move? Find out here. Read World's Wackiest Stock Indicators.)

TUTORIAL: Economic Indicators

Unfortunately, some of that faith seems to be misplaced. While great reliance is placed on government economic numbers and the financial media reports on them at length, in-depth discussions of how the numbers are created - and where the weaknesses may lie - is relatively rare. Unfortunately, those gaps are significant.

Unemployment
There are two different surveys that examine employment - the household survey and the payroll survey. While many seem to think that the larger sample size of the payroll survey makes it more accurate and reliable, from a statistical standpoint the household survey's design is more sound and the margin of error is usually better.

That said, the unemployment numbers give a few examples of the problems of government statistics. Starting during the 1960s, the methodology was changed to exclude discouraged workers - people who are out of work and have met with so little success in finding a new job that they have quit trying. This had the instant effect of lowering the unemployment number.

Inflation One of the Worst Examples
If readers want to find a "messy" stat, they need go no further than the inflation measures reported by the U.S. government. Generally speaking, the most important inflation measure is the Consumer Price Index (the CPI); as manufacturing becomes an increasingly smaller part of the U.S. economy, the Producer Price Index (PPI) becomes somewhat less relevant.

Inflation reporting used to be based on a fixed basket of goods, but that has changed with time. Substitution effects have infiltrated the measurement of inflation such that it is now assumed that when certain goods get expensive, consumers will substitute cheaper goods. Clearly, then, that understates inflation. Likewise, the weighting has been shifted from an arithmetic basis to a geometric basis, another change that helps to minimize the appearance of higher prices.

Last and not least is the impact of hedonics. The idea of hedonic adjustment 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.

There is a great deal of controversy about the "real" rate of inflation, and that argument goes far beyond the dispute over whether it is right to exclude energy and food from "core inflation." While many economists support the changes to the CPI as being more theoretically or mathematically sound, others see it is a blatant attempt to under-report inflation. Fortunately, the government still provides a lot of information calculated by the older methodologies, so diligent observers can piece together an alternative view of inflation if they so choose.

GDP - Growth May Not Be What You Think It Is
It would not be difficult to write thousands of words about the process of calculating Gross Domestic Product (GDP) and its drawbacks, and many have done so. In some respects GDP depends upon economic theories about how things should work as opposed to surveys indicating how they do work. Here are some of the "highlights" of the problems with GDP:

GDP and Gross Domestic Income (GDI) should be equal, but they never are and the discrepancy is not insignificant; moreover, IRS data generally fails to corroborate GDI data.

  • GDP figures include imputed growth; free checking is treated as imputed interest income and homeowners are calculated to receive imputed rental income
  • GDP ignores household work, volunteerism and the underground economy. There is an old joke that if you marry your housekeeper or handyman, you'll cause GDP to drop.
  • The deflation of GDP. The GDP deflator is an inflation measurement that is designed to translate nominal GDP into "real" GDP. Unfortunately, the composition has changed over time and the move from fixed-weighted inflation measures to chain-weighted has increased the risk that GDP is being overstated (because inflation is being understated).
  • Negative things are positive; the costs of crime and natural disaster are excluded, so crime and disaster are actually "positive" - more locks and prisons are positive, as are rebuilding efforts.

On top of all this, readers should remember another detail - Gross National Product (GNP) used to be the preferred method of measuring national wealth. Unfortunately, GNP punishes debtor nations (like the U.S.), so the change was made to GDP in 1991. (Find out what reports to watch in order to anticipate and react to market movements. Check out 4 Key Indicators That Move The Markets.)

Retail Sales - Turning Off the Volume
For a widely-followed statistic, the retail sales figure has a problem. Though the survey is fairly thorough (including 5,000 firms in the advanced survey and 12,000 in the final), it only tracks the dollar value of sales, not the changes in unit volume. Once again, then, here is another number whose validity is tied significantly to whatever metrics are used to represent inflation. Assume an inflation number that is too low and the retail sales figure will look too good.

TUTORIAL: Economics Basics

Deficit Accounting
Much is made of the high, and growing, U.S. deficit. The numbers may actually be worse than they seem. The U.S. government uses a form of cash accounting that includes Social Security surpluses as revenue and does not factor in accruals. Consequently, while the cash-basis deficit for 2010 was about $1.3 trillion, the same number calculated by GAAP accounting would be more on the order of $2.1 trillion - and far, far higher if one were to include credible actuarial assumptions for unfunded Social Security and Medicare/Medicaid liabilities.

U.S. Is Not Alone
The accuracy of reported economic data is a problem in virtually every country. Sometimes the drawbacks are honest issues related to statistics, data collection and interpretation. In other cases, countries engage in blatant manipulation to influence their obligations, manipulate markets (equity, bond and exchange) or influence capital flows.

In the case of the U.S., many economists will argue that the above-mentioned changes have firm footings in economics and statistics (for instance, when the U.S. switched to GDP almost every other major country was already using GDP). So it is hardly a universal opinion that the numbers cannot be trusted. That said, with so few people in the country being well versed in statistics and such large incentives for reporting the "right" numbers, readers and investors should probably ask more questions about the data and how it is calculated instead of putting their trust in the final figures.

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