The Truth About Those Unemployment Numbers

The nation’s unemployment rate fell to 7.8 percent in September, the lowest level reported since January of 2009.  That is a 0.4 percent decline from the 8.1 percent reported for the previous month, yet represents a slight hiring slowdown after the Department of Labor revised the July and August numbers upwards by 86,000.  A total of 114,000 jobs were added in September.

Despite the good news, the fact remains that the American work force is now down six million individuals from its 2007 levels. After adding those six million to the total, the unemployment rate rises to 11 percent.  These individuals are also known as “underutilized workers”. Approximately one-third of that six million are actively looking for work; the rest have left the work force due to retirement, disability or another reason.  All told, 161.79 million American are currently employed.

Most people don’t realize that the jobs report actually collects data from two separate surveys.  In one, 140,000 employers report how many people are on their payrolls; in the second, 873,000 households report the number of members who have jobs.  While the employer-generated statistic reported in September was expected by economists, the household survey results were a surprise.  It reported the highest number of jobs filled since June of 1983.  It is not uncommon for the surveys to deviate from each other.   Here is how the household survey works is taken: an individual in the chosen household is asked if they own a business; do they work for pay; are they self-employed; do they work part time or full time.

Additionally, suggestions that the federal government had “cooked the books” are “nonsense”, according to New York Time s columnist and Nobel Price-winning economist Paul Krugman. “Job numbers are prepared by professional civil servants at an agency that currently has no political appointees,” Krugman wrote in a recent column.  “Furthermore, the methods the bureau uses are public – and anyone familiar with the data understands that they are ‘noisy,’ that especially good (or bad) months will be reported now and then as a simple consequence of statistical randomness.  And that, in turn, means that you shouldn’t put much weight on any one month’s report.”