It would be good for everyone if the BLS figures were trusted.
Even "not professional economists" might lose trust in figures which are regularly revised downwards ... months after being published.
A few notes from an interview on the Odd Lots podcast, interviewing Bill Beach, former head of the BLS:
* Response rates among surveyed employees are roughly:
Month 1 68%
Month 2 83%
Month 3 93-94%
* Large employers tend to respond sooner, and are staffed to handle these requests better.
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April 2025 interview: https://podcasts.apple.com/us/podcast/some-of-americas-most-...
August 2025 interview (after BLS head statistician was fired): https://podcasts.apple.com/us/podcast/bill-beach-on-how-trum...
Some notes and a transcript: https://www.crisesnotes.com/bloomberg-odd-lots-podcast-trans...
However, it's extremely common in forecasting to revise the forecast once actuals come in. In the case of the BLS, it's the documented approach for a very long time.
Every month the numbers are adjusted and annually. All of the notes as to why, the method, etc are in the actual reports*.
*I don't recommend reading them or the footnotes unless you have insomnia. :)
** Also, if the source data is inaccurate, corrupted, etc; if the models are non-transparently adjusted, that would be horrible and cause for alarm. At the moment, we don't know if that is the case. Yet.
Though honestly, I wish the terminology were changed to "forecasted" and "actual" to be clearer.
Because these numbers are so important- to journalists, to the Fed, to financial markets, etc. they wanted a few million dollars extra, over a few year period, to run the new methodology and the old methodology side-by-side for a significant portion of a business cycle, to understand the differences before they switched, and to gain confidence in the system. Because an important part of this particular data set is what it signals to those others, it is important not to move quickly with this data set, but to give time for everyone to understand all the nuances. It's things like, how the market views the meaning of corrections would be different under a different system, and so they want time so that they themselves and all those other people whose jobs depend on understanding it to be fully aware.
Basically, they wanted to run a blue-green deployment strategy for their updates, but couldn't get the budget for it- and their budget has instead been cut so far. So they have prioritized continuing the system that everyone understands rather than experimenting with new things that no one understands. Because these are smart, well educated people who spend their entire lives thinking about these problems, and understand how the data is used, this is something they have thought about a lot and want to do the best job they can.