US created 111,000 fewer jobs in April and May than previously estimated
reuters.com
reuters.com
[0] https://www.nbcnews.com/politics/meet-the-press/half-million...
https://en.macromicro.me/charts/99068/nonfarm-payrolls-month...
Its not a huge indicator and I didn't imply anything should be read into it, but it is an interesting change in the long-term pattern worth looking into.
FYI, this sentence -- "It seems like every jobs report is lowered after the news cycle picks up the inflates numbers and they're free to adjust to the real data" -- gave me the sense that you meant the numbers were manipulated to put out good news. I think that's what the other poster was picking up on.
*Astronaut raises gun* "Always has been."
TL;DR:
In 2024, all but one of the months had downward revisions.
In 2023, 10 of 12 months had downward revisions.
In 2022, 7 of 12 months had upward revisions, but the mean revision was slightly down.
In 2021, 11 of 12 months had upward revisions.
https://en.macromicro.me/charts/99068/nonfarm-payrolls-month...
BLS explains why the revisions occur: "The initial estimate of job change for a month is based on the growth or loss of jobs at the businesses that have reported their data. Generally, BLS assumes that the employment situation at businesses that had reported is representative of the situation at those that had not yet reported. BLS continues to collect outstanding reports from the businesses in the sample as it prepares a second and then a third estimate for the month. With each subsequent estimate, more businesses have provided their information. In 2012, the average collection rate at the time of the third estimate for a month was 94.6 percent. (See chart 1.)"
https://www.bls.gov/opub/btn/volume-2/revisions-to-jobs-numb...
There may be a conspiracy to manipulate the numbers or a bias in the collection process or some dependence on the state of the economy. I didn't look closely at those theories. Some of which are compatible with the BLS revision process and some of which challenge it.
Historically it sure looks like they regularly under estimated jobs and revised upwards. A statistical analysis would be interesting, but just eyeballing the chart it looks like a meaningful difference.
The US government is so eager to hide these numbers that it… publishes them on the web site of the Bureau of Labor Statistics: https://www.bls.gov/web/empsit/cesnaicsrev.htm
The reason these revisions get made is that the statistics are based on a survey of some 130K employers, and not all report in a timely manner. Additionally, newly founded and newly defunct companies are generally not known immediately. Therefore, every monthly number gets revised twice over the next two months, and there is an annual adjustment in addition: https://www.bls.gov/opub/hom/ces/presentation.htm#revisions
The pattern of revisions can be an indicator of the direction of the economy. In early phases of a recovery, initial surveys tend to undershoot the actual statistics (e.g. in 2021, there were upward revisions, many of them massive, in 11 of 12 months). In slowdowns, there tend to be more downward than upward revisions.
If you believe that the current administration is deliberately reporting exaggerated initial numbers (How? Presumably by strong-arming 130,000 employers?), you also have to explain why they deliberately reported underestimates in 2021, or why revisions in 2022 were nearly balanced.
> In the survey sample, businesses report the total number of people who worked or received pay during the pay period that includes the 12th of the month. Although BLS uses a variety of methods to gather these reports as quickly as possible, many businesses do not have their payroll data ready to report by the scheduled date that BLS initially releases the data. In 2012, for example, the average collection rate at the time of the initial release was 73.1 percent.
Most of the time, the initial estimates are sufficient for analyzing labor market trends. Later revisions offer greater accuracy of the period. Most of the time, though, the revisions don't significantly alter our understanding of the period. Sometimes, however, they do:
> So why doesn’t BLS wait until it has all the reports to make the estimate and avoid revisions? Users of the data are intensely interested in the earliest possible read on labor market developments, and experience suggests that the initial estimate is generally very good. For example, in 2012, the average monthly employment change using the first estimate would have been +142,000, compared with a monthly average change of +165,000 using the third estimate. (See table 1.) Nevertheless, it is true that in some months, revisions are large enough that they change the users’ perspectives on the current state of the economy. In November 2012, for example, the initial estimate of over-the-month change was +146,000, while the third estimate was +247,000.
As for manipulating the data, it's pretty unlikely. BLS goes to extraordinary lengths to maintain data integrity[1][2] because they're quite aware of the consequences to global markets if they tried to fudge data. Hell, simply leaking the report a few hours early would cause problems.
For that matter, it's not the sort of data you're going to get away with manipulating for very long. There's lots of other data economists monitor that broadly track with unemployment data (not to mention the alternative labor underutilization rates[3] reported by BLS). Trying to manipulate the official U-6 rate means having to fiddle with the alternatives as well, only for some analyst or economist to come along and go "huh, that's weird."
Maybe that "huh?" moment amounts to nothing at all. Or maybe it opens the door to what might end up being a career-shaping paper for the economist. Or serious gains or losses for the analysts' firm. The kind of data incongruities you'd inevitably get are basically catnip for both analysts and economists alike.
Plus, they're monthly numbers. You'd have to continue the deception for months on end to avoid creating a weird spike that will definitely garner attention, all while somehow figuring out a way to massage the numbers back to reality when you're done doing whatever it was you were doing. You can't just go back to reality for the next report, and the longer it continues, the more likely it is you'll get caught. It's a hell of a task, and you're going to somehow have to manage it in an incredibly short amount of time, issue the expected revisions without giving it away, and then do it all over again the next month. With each falsified report, your task gets harder.
0. https://www.bls.gov/opub/btn/volume-2/revisions-to-jobs-numb...
1. https://www.bls.gov/bls/data_integrity.htm
2. https://www.nytimes.com/2020/06/08/business/economy/jobs-rep...