What you need to know about the jobs report revisions

Summary

Podcast Summary: The Indicator from Planet Money Episode: What You Need to Know About the Jobs Report Revisions
Release Date: August 6, 2025
Host: Jerryne Woods
Co-Host: Waylon Wong
Produced by: Corey Bridges

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1. Introduction: The Fallout from Leadership Changes at the BLS

The episode opens with the hosts addressing the recent dismissal of Erica McIntarfer, the Commissioner of the Bureau of Labor Statistics (BLS), by President Trump. This event has stirred significant discussion, especially regarding the integrity of the jobs report—a critical economic indicator produced by the BLS.

Waylon Wong remarks on the impact of this leadership change:

“[Trump] claimed, without evidence, that downward revisions showing jobs numbers were lower than initially reported means the numbers are rigged... [But] there are too many layers of civil servants involved for rigging to take place without that becoming public knowledge.” (00:34)

2. Understanding Job Report Revisions

Jerryne Woods emphasizes that job report revisions are a routine part of economic reporting:

“Revisions ... happen all the time. ... every single month, the previous couple of months gets revised, and then there's a big adjustment annually too.” (03:04)

The hosts explain that the initial jobs numbers are estimates based on surveys of approximately 600,000 out of 12 million firms in the U.S., with about a 68% response rate in the first month. Revisions occur as more responses are received, refining the accuracy of the data.

3. Causes Behind Significant Recent Revisions

The discussion delves into why recent revisions were notably large. Bill Beach, former Commissioner of Labor Statistics, provides insights:

“A lot of times, the smaller businesses are the late returns. ... additional information is important to include because small businesses really do employ a lot of people.” (04:32)

Several factors may have contributed to the large revisions:

• Economic Pressures on Small Businesses: Tariffs, bad weather, and immigration crackdowns have disproportionately affected smaller companies, leading to delayed responses.

• Government Financial Constraints: State and local governments reported late, possibly due to exhausting COVID-era funding used for hiring.

• Potential Business Closures: Some late responses may indicate businesses going out of operation.

Jerryne Woods adds context:

“… if the companies that aren't responding are actually going out of business.” (05:41)

4. The Reliability and Confidence of Initial Estimates

The hosts highlight the statistical confidence in the initial job reports. Jerryne Woods explains:

“For the first release, ... that ballpark is roughly plus or minus 136,000 jobs. Anything less than that number means you can't even be sure any jobs are added.” (06:34)

By the third month, as more data becomes available, the estimates gain precision, reducing the confidence interval and enhancing reliability.

5. The Debate: Publish Early Imperfect Data or Wait for Accuracy?

A central question addressed is whether the BLS should continue publishing preliminary data or delay releases until more accurate information is available.

Bill Beach asserts the importance of timely data:

“... it is this punctuality of the data. ... It gives you ability to work in this crazy world.” (07:11)

Mike Puglisi, a senior economist at Wells Fargo, underscores the necessity of early data despite its imperfections:

“... what you want to do is get the data early, ... and just be cognizant and aware that you might end up with larger revisions.” (08:47)

6. Industry Perspectives: The Critical Role of Jobs Numbers

Mike Puglisi elaborates on how jobs numbers influence financial decisions:

“When you think about the US Economy at a very high level, it is predominantly driven by consumer spending. ... it comes from their job.” (08:28)

He emphasizes that the jobs report is central to predicting economic trends, interest rates, consumer behavior, and business investments, all of which are pivotal for financial institutions like Wells Fargo.

7. Potential Improvements: Automating the Jobs Report

The conversation shifts to possible enhancements in the data collection and reporting process. Bill Beach addresses the idea of automating the jobs report:

“... the budgets of the statistical system, BLS in particular, have not really changed at all for years. ... modernization costs little money, and that's what Congress is not supporting us on right now.” (09:22)

He points out that despite the need for modernization, budget constraints have hindered the implementation of more automated and efficient data collection methods.

8. Challenges Faced by the BLS

A significant barrier to improving the jobs reporting system is the persistent budget cuts faced by the BLS. Jerryne Woods references past budget reductions:

“... the BLS had faced about a 10% budget cut since 2009. ... reminding them to hand in their homework on time.” (09:41)

These financial limitations impact the BLS's ability to maintain and enhance its data collection efforts, ultimately affecting the accuracy and timeliness of the jobs report.

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Conclusion

The episode provides an in-depth exploration of the complexities surrounding job report revisions. It underscores the delicate balance between timely data dissemination and the accuracy that comes with comprehensive reporting. The discussion highlights the multifaceted challenges faced by the BLS, including budget constraints and external economic factors influencing small businesses. Industry perspectives, such as those from Wells Fargo, reinforce the pivotal role that accurate and timely jobs data plays in shaping economic forecasts and financial strategies.

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Transcript

[Unknown Speaker]

NPR.

[Jerryne Woods]

This is the indicator from Planet Money. I'm Jerryne Woods.

[Waylon Wong]

And I'm Waylon Wong. We are still processing the shockwave of President Trump firing the Commissioner of Labor Statistics Erica McIntarfer last week. The jobs report that her agency puts out is packed with some of our favorite indicators.

[Jerryne Woods]

It's the only report we have an air horn for.

[Waylon Wong]

It's true, and Trump claimed, without evidence, that downward revisions showing jobs numbers were lower than initially reported means the numbers are rigged, as we showed yesterday. That's not true. There are too many layers of civil servants involved for rigging to take place without that becoming public knowledge.

[Jerryne Woods]

But it is true that the downward revisions were large. So today on the show, how revisions to the jobs numbers happen, what the process is and what law? What did last week's revisions say about the economy?

[Unknown Speaker]

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[Jerryne Woods]

The indicator, we have announced the jobs numbers right from the show's beginning. We knew it had to be.

[Waylon Wong]

Jobs, right? Once a month we put aside the stock market. Who cares?

[Jerryne Woods]

254,000 jobs. 187,000 jobs.

[Waylon Wong]

Man, we love a jobs number around here. And whether you're a cleaner or a carpenter or even if you're looking for work, the jobs report is like a mirror up for most people's personal finances.

[Jerryne Woods]

We do need to caution though, the jobs report is just the first pass. The numbers can change a lot. Like we saw on Friday is that the BLS made a big downward revision to its previously reported job numbers.

[Waylon Wong]

The air horn turned into a sad trombone yeah.

[Jerryne Woods]

And, you know, revisions are a big part of the jobs report. They happen all the time. Yes, it was larger than normal, but every single month, the previous couple of months gets revised, and then there's a big adjustment annually, too.

[Waylon Wong]

That got us asking, why exactly do revisions happen? Bill beach was the Commissioner of Labor Statistics right before Erica McIntarfer. He served under both the first Trump administration and the Biden administration.

[Unknown Speaker]

The basic reason is that we get additional information. So where does that information come from? Well, the jobs numbers are derived from a survey. So there's like, I don't know, 12 million firms in the United States, and we're doing a survey of about 600,000 at most. And about 68% turn their surveys in the first month. It's not a bad response rate, but you want more than that.

[Waylon Wong]

So this kerfuffle basically started from business owners and HR managers handing in their homework late.

[Jerryne Woods]

When late homework meets a conspiratorially minded president, heads will roll.

[Waylon Wong]

Stepping back, you know, part of the whole magic of statistics is that you can approximate based on just a small sample. You can extrapolate. So I'm curious about why the latecomers might change the numbers in one direction. Like, shouldn't the overestimates be canceled out by the underestimates?

[Jerryne Woods]

Yeah, Bill says there might be underlying issues that particularly affect the stragglers, the companies that don't respond to the survey in the first month.

[Unknown Speaker]

A lot of times, the smaller businesses are the late returns. And if you have a thing affecting small businesses rather than large businesses, for example, the tariffs might be affecting small businesses, or bad weather might be affecting small businesses. Who knows? I mean, there are many factors then that additional information is important to include because small businesses really do employ a lot of people.

[Waylon Wong]

And about why the specific month's revisions were so high. Bill says it's the kind of thing that is a little foggy in the moment.

[Unknown Speaker]

Now, honestly, most revisions are not this big, but these are not unprecedentedly large revisions. When I was commissioner, we had much larger revisions, and it was because we were coming into or going out of COVID Okay, that's a pretty good, obvious reason why you would have revisions. And people didn't complain about the size of the revisions. Obvious. What's lacking here is the reason. And once the reason becomes apparent, I think people will begin to say, oh, yeah, that makes sense.

[Jerryne Woods]

As Bill said, a possible reason for the big revisions could be that tariffs are affecting smaller businesses more than larger businesses.

[Waylon Wong]

You also have the immigration crackdown.

[Jerryne Woods]

Yeah, it could mean those smaller companies aren't hiring as much. It could also be that the companies that aren't responding are actually going out of business.

[Waylon Wong]

Bill also points to state and local government.

[Unknown Speaker]

State and local government reported late, and that caused a big change. I think the biggest reason is they were all running out of COVID era money. Strange that money would still be around. And they had used that for hiring purposes for years and years and years, and now it wasn't there, and so they weren't hiring as much.

[Waylon Wong]

So there are plenty of reasons why the revisions might have happened.

[Jerryne Woods]

A lot of reasons. But aren't there always reasons why this time is different? Like there's always something going on, maybe a hurricane or new tax cuts. If you look at the technical notes that the Bureau of Labor Statistics, the BLS puts out, the first round of jobs Numbers has a 90% confidence interval.

[Waylon Wong]

That means you can be 90% confident that the actual number is within a certain ballpark.

[Jerryne Woods]

And for the first release, when it comes to the jobs report, that ballpark is roughly plus or minus 136,000 jobs. Anything less than that number means you can't even be sure any jobs are added.

[Waylon Wong]

Okay, that's really big. That's a big number.

[Jerryne Woods]

True. That said, by the third month, when you get those revisions in, after more businesses have responded, the precision increases.

[Waylon Wong]

Now, this gets us to the question we've heard a lot recently, which is, why even publish the imperfect numbers?

[Jerryne Woods]

Would it be better just to hold the data until the numbers are more solid?

[Unknown Speaker]

The data needs to come out on a regular basis. It's this punctuality of the data. Every month we get the GDP report, the unemployment report, the jobs report, and we can see trend. The trend's really the thing that we're looking. Is the economy getting better? Is the economy getting worse? And then I can make my changes. I can say, well, I'm not going to change my jobs. Things look risky.

[Jerryne Woods]

Bill believes a lot of people who use the job's numbers would prefer imperfect over no data at all.

[Unknown Speaker]

People have built their businesses around them. Banks build decisions around them. You know, everyone wants these data, whether they're plus or minus at the same time. And it gives you ability to work in this crazy world.

[Waylon Wong]

One of these banks is Wells Fargo. We spoke to a senior economist there, Mike Puglisi.

[Mike Puglisi]

In my group and my team, right, we are riding on the US Economy and trying to figure out where it's going and what that means for interest rates and consumer spending and business investment and what the Fed is going to do, and a whole host of different questions that we and our clients have an interest in knowing.

[Jerryne Woods]

Mike's team's reports could influence how much money Wells Fargo lends out to people and businesses. And he says the jobs numbers are.

[Mike Puglisi]

Central because when you think about the US Economy at a very high level, it is predominantly driven by consumer spending. And for the average person, where does most of their spending power come from? It comes from their job.

[Waylon Wong]

We asked Mike, though, whether he would prefer the jobs numbers were withheld until they were more accurate.

[Mike Puglisi]

I think there would be pros and cons. I mean, I think if I had to come down on it, I would probably say what you want to do is get the data early, like we do now, and just be cognizant and aware that you might end up with larger revisions.

[Jerryne Woods]

The first estimates of jobs numbers have actually been getting more reliable over time, on average. That's through better statistical techniques. But could the system be improved further?

[Waylon Wong]

We asked Bill beach, why not automate the jobs report? You know, take information from other government departments or do things more digitally?

[Unknown Speaker]

Now you're getting into it. So the budgets of the statistical system, BLS in particular, have not really changed at all for years. Despite the big inflation that's occurred, despite all the changes in the world, modernization costs little money, and that's what Congress is not supporting us on right now.

[Jerryne Woods]

On yesterday's show, we Learned that the BLS had faced about a 10% budget cut since 2009. When you account for inflation, that's less money for those civil servants who painstakingly call up hundreds of businesses every month reminding them to hand in their homework on time. This episode was produced by Corey Bridges with engineering by Kwesi Lee. It was fact checked by Cierra Juarez Kick and Canon edits the show, and the indicator is a production of NPR.

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