Erika McEntarfer was Commissioner of the U.S. Bureau of Labor Statistics until August 1, 2025, when she was abruptly fired by President Trump. Neale Mahoney of the Stanford Institute for Economic Policy Research discusses the experience with her and what comes next for federal statistics in “The hidden backbone: The data behind the economy” (SIEPR, “Econ to Go,” March 26, 2026). Here are a few of the comments that caught my eyes:
On her earlier interaction with the Department of Government Efficiency, widely known as DOGE:
I actually had a whole basket of AI related projects when DOGE arrived early in the administration. The early word was they were gonna help us with AI. And I was like, “Great, we could use some more resources here.” So, you know, I had this whole list of projects for them and instead I wound up sitting across the table from a member of DOGE and they were like, “So we want to fire all of these statisticians and replace them with the AI.” And I was like, “I don’t think that’s actually possible, but if you can explain to me how it is possible, I am all ears.” And then they would just stare at me blankly and tell me that I was not cooperating with their vision. I was like, “No, I don’t actually understand how you replace a time series statistician with an AI model, but if you can explain it to me, I’m all ears.”
How the actual firing happened:
So it was jobs day for the July release. We had been you know, we’d spent the morning at the Labor Department briefing the Labor Secretary the day before. We had briefed the White House on the data and, you know, by afternoon on a jobs release, things are starting to wind down a bit. And we were having a social gathering in our office for the staff. And I looked down at my phone and I saw that I had missed an email from a reporter, who wanted to ask me about something Trump was tweeting, and I was like, “Oh, let me go check this in my office.” And so I walked down the hall and I opened up this email, and by then I had a few from, I think it was an NBC reporter, and he was like, “Do you wanna comment on this tweet that the president, that he is going to fire you for the jobs numbers?” And I have to say, my first thought was, I thought he was just threatening. I assumed I hadn’t actually been fired, so I started thinking together a calm strategy. I’m like, “Oh, it’s Friday afternoon.” I gotta assemble a team here to, like, deal with this, and I’m already, like, 10 minutes into this thought process. When I look and I realize, oh, I have missed some other emails during this gathering, and one of them was from the presidential personnel office, and it was a termination letter. And I was like, “Oh, I am actually fired.” Okay, that’s a whole different crisis than the one I thought we were entering. It was an unbelievably crazy moment because all, like, while what I just described to you was happening, my phone is completely blowing up, because this has hit the media, it’s on television, people are texting me, people are emailing me, my family is calling me, like everyone is just reaching out all at once and my phone is just, all my phones are just buzzing and buzzing and buzzing and buzzing. And it was just wild.
What’s next for federal statistics?
So the interesting thing about the US statistical system and particularly economic data is you have to keep two thoughts in your head simultaneously. And one is that US economic data is actually very, very good. … It is the envy of the world. The richness of the data, the timeliness of the data, it’s really hard to match. If you do international comparisons, you’ll discover very quickly how advantaged we are. The other thing that you have to keep in your head is that the system is in a certain amount of danger in terms of its sustainability. And those dangers are fiscal. So the costs of fielding surveys are increasing, but the budgets are not keeping up with those costs. The others declining response rates. It’s harder to reach respondents, that’s true for households and businesses. …
I worked in [data] modernization for at least 15 years, and there’s a lot of things that we can do to shore up the survey-based collection system that we have from the 20th century. The most promising avenue for modernizing statistics is, like, what we often refer to as a blended data approach, where you ask the respondents the things that are otherwise really hard to collect. So unemployment is probably a key one here. So unemployment, you really have to go to a household and find out what they were do, like were they working? If they weren’t working, were they seeking work? There’s no administrative solution to this problem because lots of people who are sitting at home not working are doing other things. They’re taking care of small children. They’re taking care of elderly relatives there in school. And so you don’t really know why people are out of the labor market unless you ask them, and if they’re trying to get in. On the other hand, there are domains where, like wage and salary income, where we have a lot of rich administrative data, and we know that this is something respondents really don’t like providing themselves. And so you can use, like, IRS data, unemployment insurance, wage record data to help fill in and take response burden away from individuals. So you just, you have to go sort of item by item in terms of the potential for this other, like, alternative data where it can fill in.
If you were designing a job search for an economist to lead the way in actually nuts-and-bolts job of updating the federal statistical apparatus, it would be hard to do better than McEntarfer. As she points out, firing the statisticians is actually a lasting blow to the credibility of government statistics:
Ishould explain one reason I assumed this was just a threat [to fire me] and not an actual execution of a firing is because firing your chief statisticians is a shock to trust in your economic data that has real economic consequences. So it’s not something you really want to do as a rule. So I assume somebody was gonna, you know, tell him actually you don’t want to do that. … [T]he economic community immediately realized the consequences. Many, many people spoke out in the aftermath of my firing, both defending my work, but also just saying, “You do not want to do this.” Like, this is countries where they have fired their chief statisticians, Argentina, Greece, it’s not, it’s just not a good list.
