Once Upon a Time at the Bureau of Labor Statistics
By
Mac McDowell
It has been said that the difference between a fairy tale and a government report is that a fairy tale begins with “Once upon a time…”
The history of federal agencies producing bogus reports ranges from fictional body counts during the Viet Nan War, to more recently, erroneous global warming data at the Environmental Protection Agency. In an effort to restore credibility to government reports and statistics, the Bush Administration, in 2001, wrote guidelines for a little known law called Data Quality Act (DQA). These guidelines were supposed to eliminate the ‘Bogus Factor.’ What is surprising is that the Obama Administration has not issued new guidelines or an Executive Order to change or nullify the DQA since they seem unable to comply with the spirit and intent of the law. For months now the Administration has seemingly been cooking the books on the unemployment numbers. The recently released unemployment rate of 7.8% is considered by many to be completely bogus. Last month when the Bureau of Labor Statistics (BLS) released the 8.2% figure, Investors Business Daily corrected the number to 11.2%. But why is there so much suspicion concerning the accuracy of these statistics?
The answer to this question is not a simple one. There are several statistically valid ways of calculating these unemployment numbers. So what are the accepted standards for calculating these numbers? There are none.
The science of statistics is based on making certain assumptions to arrive at a specified number. As an example, take the difference between mean and median calculations. The mean is the average of all the data points to be considered, and the median is simply the sum of highest value and the lowest value divided by two. So the same data set can result in widely different results between the median and the mean. For example, if the majority of the data points are clustered around the high end value, then the median will be lower than the mean. The opposite is true if the data is clustered at the low end. Is this type of manipulation of numbers going on at the BLS? Congressman Duncan Hunter thinks so.
In February of this year Hunter introduced legislation to set a standard for calculating unemployment called the Real Unemployment Calculation Act ( H.R.4128 ) The goal of the H.R. 4128 is to ensure that the treatment of unemployment statistics, issued by the BLS, is calculated off the data set known as U5, as the official and primary measure of unemployment in the United States.
Just as there are differences between median and mean there are different ways to treat unemployment numbers. Currently there are six different categories of labor statistics, numbered U1 though U6. U3 is what is being used as the official unemployment rate which takes in to account only those folks out of work who are actively looking for work; that is to say, folks collecting Unemployment Insurance (UI) who must file the weekly job search reports.
If you look at the unemployment numbers over the past year you will see that the September number of jobless folks is nearly the same as the number of folks without a job in May. Yet the unemployment rate in May of this year was 8.1%. How then can the September unemployment rate be 7.8%? The answer is that you stop counting the folks that have fallen off the UI rolls so you end up with a smaller available workforce. In other words pretend they don’t exist.
This is the reasoning behind H.R. 4128 so that anyone who can work is counted as part of the available workforce. At present, folks who have exhausted their UI benefits don’t have to report their job searches so they simply disappear from the statistical calculations in the U3 numbers. However the U5 number includes a segment of the available workforce known as "marginally attached workers." These are the folks who may be unemployed with no UI benefits, the underemployed, in a part time job, or the college grad who has never held a job and is looking. If this number were used for the recent jobless numbers, the unemployment rate for September would be 9.3%. In fact if you look at the U5 numbers for all of 2012, the unemployment rate never drops below 9%.
But is H.R. 4128 a duplication of the Data Quality Act? The short answer is no. The DQA has no teeth, and if an agency were to cook the books and produce bogus numbers there are no penalties. The law, as written, does not give standing to any branch of government, nor to the public at large, to file suite to demand a correction of the bogus data or institute any penalty whatsoever.
It was Benjamin Disraeli, the famed 19th century British Prime Minster, that said:
“There are three types of lies - lies, damn lies, and statistics."
And they lived happily ever after.
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