For longer than a year, many of us have been watching the monthly reports and jobs numbers and noticing certain anomalies. The math was simply not adding up. There are two different surveys, one of households and one of payrolls, and they were becoming increasingly divergent. The total employed did not match the news reports of white-collar job losses and neither did the figures match on other indicators such as labor participation and unemployment.
My economist colleagues also noted the way that data revisions in the past several years have gone in only one direction: down. Based on what they were seeing, they fully expected that the next round of revisions would be dramatically down. Ever since March, there have been hints in the air. One clue was even dropped by Fed Chairman Jerome Powell, who essentially said the official numbers were not reliable.
Once we add this figure to previous revisions, the total number of vanishing jobs comes to 1.2 million, which, again, seriously revises the economic history of the past several years. The only reason a recession was not declared already in 2022 was that the labor market seemed rather healthy. Looking at the data, many of us never believed that, but that’s how it is with official data: It’s all we have to go on, so it became true in the absence of alternatives.
As it turns out, much of these phantom jobs were created by phantom companies too. The business formation data are also being revised downward. It appears that many stimulus payments in 2021 went to companies that were suddenly founded only to receive the payments. This is clearly an act of fraud, and many of the perpetrators have been caught. But still, the data collectors retained the companies on the books as if they existed, along with the jobs, too.
For several years, we’ve puzzled about the why of all this crazy, mixed-up data. It’s easy to place the blame on political spin and manipulation, and we cannot rule that out. But it actually makes more sense to examine the role of the trillions in stimulus payments that manufactured epically large data distortions in all sectors. This is why the economic data from 2020 and following has been such a mess.
These data problems pertain not only to jobs numbers but also to output data because the collection and reporting of gross domestic product (GDP) skews up because of government spending. Current debt-to-GDP ratios compare with World War II, so we can reasonably assume that much of the mild growth we’ve seen over several years is likely negative.
Once you adjust that GDP data with a real revision of inflation numbers that include housing, insurance, and interest and make adjustments for actual prices instead of “hedonically adjusted” ones, the numbers look even worse. When you subtract out ghost jobs and companies, labor markets look exactly like what we would expect in a deep recession.
Current labor participation rates compare with levels all the way back in 1977, and it is hard to know if these numbers are even correct. Again, once you lose trust in such a major piece of data as jobs numbers, everything else starts to crumble. And strangely, the secretary of commerce was asked about the new numbers in an interview, and she claimed to not know anything about them.
Let there be no mystery concerning the loss of trust in official institutions these days. One can understand mistakes and oversights, and we’ve come to expect revisions. But when officials in power go on record to claim to not know anything about them at all, we seem to have a problem.
Another issue: If we could not trust the old numbers, which turn out to be rooted in complete fiction, what reason do we have to trust the new numbers? If the agencies are willing to spend the better part of two years propagating data that turn out to be false, is there any reason to embrace the new numbers as if the bean counters are certain to have it correct this time?
When I talk to friends about these issues, they are quick to say that the whole economy is a fake right now and that nothing can be trusted. We could be in the midst of a Greater Depression and not know it. Or we do know it but cannot do anything about it, so why bother?
A lesson I’ve taken from this mess is to trust your eyes and the stories of your friends and family more than any reporting from government statistical agencies. We were long taught to doubt mere anecdotes on grounds that they are not scientific. As it turns out, stories and first-hand reports have proven more reliable than the official science. This is true in infectious disease but also in economics.
