[deepGem]

What I really fail to understand - how can departments like BLS screw up to this extent. Either they are grossly incompetent or they are intentionally corrupt.

The data covers the period from March 2024 to March 2025 and trims the average monthly jobs gains seen during this period (roughly the last 10 months of Joe Biden's presidency and the first two months of Trump's) from a monthly average of 147,000 to about 71,000.

50% error. This is more or less consistent. How can a department have this error % and still have their job. I understand the data collection mechanism is not the most sophisticated, but even accounting for that, this consistent error % is not to be overlooked.

I wonder why there is such lack of accountability from firms whose data pretty much feeds the world's economy.

[mlyle]

There's a little bit of a philosophical thing here -- do you adjust the earlier measurement by some function because it's usually been high and revised downwards? If you do, you need to let every user know that you're doing something different, etc.

The worst case is that both the statistics orgs and the users are adjusting the numbers for a bias and overshooting.

This means there's a certain inertia: it can be better to handle the interim reports the same, even if they've been biased one way for several years, than to introduce a change that makes the numbers not comparable to history.

> 50% error.

It's not a 50% error; it's a 50% error in the magnitude of the change.

That's like saying that my room increased from 71.4 to 71.6 degrees, but my thermometer only saw an increase from 71.4 to 71.5; therefore, my thermostat has a 50% error.

[deepGem]

This means there's a certain inertia: it can be better to handle the interim reports the same, even if they've been biased one way for several years, than to introduce a change that makes the numbers not comparable to history.

This is a very interesting point. So if BLS suddenly became more accurate, all the agencies have to re-tune their own biases and corrections => Could lead to short term discrepancies.

What one sees as inefficiency is actually efficient from a totally different lens.

[mlyle]

Yup. Obviously you want to fix the bias in the early version of the numbers eventually.

But you don't want to change what you're doing all the time, so you stay an easy product for everyone else to use.

(Interesting that this "overreport jobs in the preliminary numbers" bias has showed up; in older data using similar methodology it didn't exist, but now it seems to...)

[lokar]

It’s a survey, there are a lot of non-responses (getting worse) and late responses. They try to correct for this, and that normally works, but when “weird” things are going on the corrections can be pretty wrong. The people who use these numbers understand all of this and it’s fine. It’s just the popular media that freaks out.

The quarterly numbers come from better data sources (tax withholding, unemployment insurance payments, etc)

[lokar]

For example, if a small business goes out of business and fires everyone, they probably won’t respond to the survey. If the rate of small business failures is not what we normally see (more of less is absolute of relative numbers) it can create a bias that throws the models off.

[fluorinerocket]

Let me guess, they are calling landlines. And no one picks up unknown numbers on cell phones. They are hopelessly behind the times

[lokar]

It’s a survey of business, so they have a list, I think the businesses are enrolled to take part. It’s not a random phone survey. I bet it’s email.

[rurp]

You might want to read up on the process a little more before forming such strong opinions. The BLS is extremely transparent, at least for now. The earlier reports are intentionally more noisy because there is value is being fast and then revising later, and everyone who uses this data is aware of that.

Calling this a 50% error rate is simply wrong. If an earlier report said a single job had been created and that was later revised to two jobs, that would be super humanly accurate and yet you would be calling for everyone to be fired over the 100% error rate.

[deepGem]

The earlier reports are intentionally more noisy because there is value is being fast and then revising later, and everyone who uses this data is aware of that.

I get it and yeah my tone is very exaggerated. I don't think anyone in BLS should be fired and whoever is suggesting that does not understand how public institutions work.

I am just curious why there is so much of a discrepancy. This has been pretty much the status quo in BLS for a long time. They issue numbers and then they revise them later. However, you'd expect the revision to be moderately within an error %age.

Also how will this retroactive change help everyone involved. Ok, the new job numbers reflect a gloomier past (or a more vibrant past) how is that even helping everyone who is so focused on 'what's going to happen tomorrow'.

I retract my stance about BLS being intentionally corrupt - that's uncalled for.

[k3vinw]

I disagree. The BLS head was either incompetent or corrupt. The two are not mutually exclusive so they easily could have been both. Firing the BLS head was the obvious choice and it sends the right message to all involved that we will not accept this margin of inaccuracy when it impacts our economy. We need a BLS head with the balls to raise hell when the numbers are not reflecting reality.

[Isamu]

They rely on reporting from employers, and employers don’t report that data quickly enough, so there’s an amount of estimation.

Over time they get better numbers relating to previous quarters and they revise their numbers.

Also employers can report revised numbers for a quarter, to make corrections.

[webdood90]

There are ~160 million working adults in the US. Jobs numbers being off by 100k in either direction doesn't seem that bad when you consider that.

[nabla9]

They are neither.

Revisions and surprises are routine. Data comes in gradually, but estimates are useful even before all data has arrived. Early data is based on business reporting and businesses that report on-time aren't necessarily representative of all businesses. Those people who use this data know this, and prepare for revisions.

I hope this helps and you understand better. Anyone here who still thinks this is still incompetence or corruption because surveys come late?

>I wonder why there is such lack of accountability from firms whose data pretty much feeds the world's economy.

Create punishment system? Unless compaies report data back to BLS very fast, they pay big fee or are taxed higher. Small shops would hate it.

[deepGem]

Create punishment system? Unless compaies report data back to BLS very fast, they pay big fee or are taxed higher. Small shops would hate it.

Or incentivize companies to report accurate data pretty fast. Payroll management systems can be plugged in real time, but that costs money and yeah small businesses are not going to be happy. So incentivization works better than punishment I think.

[lotsofpulp]

I feel like the IRS has near real time employment data simply based on tax withholding payments they receive every 2 to 4 weeks.

[lokar]

That comes out quarterly

[junar]

Yes, and to add, it would count anyone who had any wages in that quarter, not necessarily those who are still employed.

https://www.irs.gov/pub/irs-pdf/f941.pdf

[mempko]

People who don't do statistics and don't understand how the BLS gets their data think there must be corruption when they correct previous reports. Think of it this way, if they correct their previous estimates with new data, isn't that a sign they are NOT corrupt? Why would a corrupt organization correct their previous reports?

I advise you to do a little reading on how these reports are corrected. People relying on them understand how they work. People freaking out about them don't.

[amaranth]

One factor is that a part of their measurement is tracking how many new companies are founded and estimating how many employees a new company is likely to have. These numbers have been trending down and rapidly fell due to a lot of new companies being one person LLCs for gig economy work. It appears they haven't kept up with this trend so they overestimate how many jobs these companies will have.

[logifail]

> how can departments like BLS screw up to this extent

My null hypothesis might be that the BLS works for the government, so how can they not be under (implicit) pressure to goal-seek their figures.

Once the figure has been published, and widely reported, it can be revised downwards months later, few will care. The system may be broken by design.

[jeffbee]

This is the furthest thing from a null hypothesis. This is dressing your conscious biases in sciensism.

[logifail]

> This is the furthest thing from a null hypothesis

"It is difficult to get a man to understand something, when his salary depends on his not understanding it"

Q: Why would one trust initial BLS jobs figures under this - or indeed any other - administration?

> This is dressing your conscious biases in sciensism

BLS figures being revised downward month after month after month is data, not bias.

[wredcoll]

No, thats anecdotes.

Actual data would be measuring predictions vs accuracy over several decades.

[ipv6ipv4]

Maybe you don’t understand the role of the BLS or what it does. Maybe you’ve been sold a bill of goods that it is supposed to be an infallible oracle, when it is, in fact, a useful measurement device with limitations that have been well known for decades.