The Fake Unemployment Rate

The current US unemployment rate of 4.7% is at best a flawed calculation and at worst a deliberate deception. The Bureau of Labor Statistics uses unemployment insurance reporting from the states along with a complicated and potentially biased sampling to come up with the rate. The sampling method used relies on an insufficient number of survey participants. The methodology used to calculate the rate uses race and sex in their formula to exacerbate the disinformation. New data capturing tools are needed to provide a realistic picture of the nation’s unemployment rate.

According to the Bureau of Labor Statistics (BLS), the unemployment rate is 4.7% of the population or roughly 15 million people. The calculations are based on a number of variables. Even though the assumption that the BLS only uses statistics based on those collecting unemployment insurance is incorrect, the other factors that are used in calculating the unemployment rate is inaccurate and erroneous.

First, the BLS does use unemployment insurance information reported by the states for part of their calculation of the unemployment rate. Unfortunately, this figure does not include: unemployed workers who have exhausted their benefits, unemployed workers who have not yet earned benefit rights (such as new entrants or reentrants to the labor force), disqualified workers whose unemployment is considered to have resulted from their own actions rather than from economic conditions (i.e. a worker fired for misconduct on the job), and otherwise eligible unemployed persons who do not file for benefits. So, how does the BLS deal with those that fell off the unemployment insurance radar?

The BLS uses a sampling or survey of US households to help in their calculation of the unemployment rate. Indeed, it would be impossible to contact every US household every month to inquire about their employment status. Instead, the BLS contacts 60,000 “eligible” households, or roughly 110,000 people. Even if the BLS defined how a household is considered “eligible”, they are only contacting about .00035 percent of the population. By sampling so few in order to provide a picture of the nations’ unemployed, it is easy to see how the BLS sampling cannot be reflective of the entire US population. Even surveys for the recent US elections have proven to be incorrect and distorted.

The BLS uses a complex methodology to determine an eligible household that, of course, is to expansive and complicated to go into great detail here. However, I will provide a snapshot of their calculation logic. They start by grouping all of the counties and independent cities in the US into approximately 2,000 geographic areas called sampling units. The Census Bureau designs and selects a sample of about 800 of  those 2000 geographic areas to represent each state and the District of Columbia. They offer no explanation as to how they “design and select” their 800 geographic areas to represent the entire US.

Let’s looks at their next step. The BLS states, “Every month, one-fourth of the households in the sample are changed, so that no household is interviewed for more than 4 consecutive months. After a household is interviewed for 4 consecutive months, it leaves the sample for 8 months, and then is again interviewed for the same 4 calendar months a year later, before leaving the sample for good.” Again, this using a sampling of 60,000 households that only the BLS selects.

The BLS states, “Each month, highly trained and experienced Census Bureau employees contact the 60,000 “eligible” sample households and ask about the labor force activities (jobholding and job seeking) or non-labor force status of the members of these households during the survey reference week (usually the week that includes the 12th of the month). These are live interviews conducted either in person or over the phone. To deepen the error in their ways, the BLS fails to explain how the phone numbers are obtained and how they are connected to a household. Is it based on landlines or cell phones? Are the households being truthful in the number of occupants? What time do they come to the households? How many interviewers fail to speak with someone at the residents? How is it reported when they fail to personally talk to someone in the household? How many fail to answer their phones and how are those reported and factored into the statistic? As we know, some Americans do not answer a phone call received from a number they do not recognize.

Looking deeper into the unemployment statistic I found the BLS classifies each person according to their activities during the reference week. Survey responses are then “weighted,” or adjusted to independent population estimates from the Census Bureau. The BLS states, “The weighting takes into account the age, sex, race, Hispanic ethnicity, and state of residence of the person, so that these characteristics are reflected in the ‘proper proportions’ in the final estimates.” They fail to give a formula and example of how these individuals are weighted. They also fail to mention the necessity or rationale for doing so. These unexplained variables are very concerning and show additional areas where the logic may be flawed and further the inaccuracies of the unemployment rate. Also, the BLS admits that the survey respondents are never asked specifically if they are unemployed!

As we move further into the 21st century, it is essential to have a complete picture of our nation’s unemployed. The sampling method currently used must be replaced in order to provide a more comprehensive analysis to solve the unemployment problem. If the US is using methods that do not provide an accurate accounting of those without work, then our laws will not be effective and allow for needed changes to occur in our economy.

 

References:

https://www.bls.gov/cps/cps_htgm.htm

https://www.census.gov/popclock/

Picture by John E. Allen

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