Transcript
Speaker: Welcome back to the Policy Biz Podcast. I'm your host, John Schwabisch. Hope you are well. Hope you are enjoying the beginning of September. Now, I had a plan for this week's episode.
Speaker: I had done my interview. I had created the audio file, the video file. Everything was edited, published, produced, ready to roll. And then I had the opportunity to... interview today's guest, Erica Groshen, one of the former commissioners of the Bureau of Labor Statistics under President Obama.
Speaker: And because I interviewed Erica on Friday, September 5th, a couple of hours after the September jobs report was released, I thought I would make this episode the first official episode of the season. So why is that?
Speaker: Well, you probably know that in early August, President Trump fired the now former commissioner of the Bureau of Labor Statistics, Erica McIntarfer, specifically because, as the president claimed, the job numbers were falsified, they were rigged.
Speaker: And so I reached out to Erica Groshen, former commissioner, to join me on the show to talk about the numbers, talk about that process, talk about what it is to be the BLS commissioner.
Speaker: And the timing just worked out. I didn't even really think about it, that the job numbers were going to come out a few hours before we talked. And so we get to talk about a lot of things in this episode. We talk about the current release and what it means for the US economy, which of course is going to impact the world economy.
Speaker: We talk about what it means for the BLS to produce these numbers. what the process is, why numbers are revised and what that process looks like. We talk about the commissioner's role in this entire process and the role of leading the BLS.
Speaker: And then we talk about what Erica is, thinks is important for the next commissioner. What questions she would ask in a Senate confirmation hearing. We talk about the importance of the federal statistical agency ecosystem and what we as individuals working with data, visualizing data should be looking out for when it comes to using these data going forward.
Speaker: So as I mentioned in the season 12 premiere last week, one of the goals, one of the themes of I think this season will be a focus on federal statistical data agencies, perhaps also state and localities. I hope so.
Speaker: And so this is sort of that first episode. We're going to focus on what I would sort of consider threats to the federal statistical agency ecosystem. And those data are, of course, important for lots of things, not just the work that we do to visualize and communicate data, but also importantly for decision making that policymakers, business leaders, organizations, nonprofits, transit agencies, lots of different groups,
Speaker: are doing and making relying on these data on a month to month or a week to week basis. So I think you're going to learn a lot from this week's episode of the show. I'm going to turn it over to my interview now with former BLS Commissioner Erica Groshen and myself only this week on the Policy Biz Podcast.
Speaker: Hi, Erica. Great to see you again. how are things? Things are good, John. How are we? How are things with you? Well, um it's early September in DC. You'd think it'd be a million degrees, but actually the weather has been actually delightful.
Speaker: It's been delightful for like three weeks. It's it's amazing. Like 70 degrees. Yeah. I don't know what's happening, but we're enjoying the weather. How's the Northwest? Great. And the summer here is amazing. It is 70 degrees and beautiful almost every day.
Speaker: Wow. I don't know if anyone's ever said that about Seattle before. So so Summer is a closely guarded secret. Okay, now you're going to let people you're to have too many tourists wandering around.
Speaker: Well, thanks for coming on the show. we ended up recording on sort of an interesting day. So it's it's Friday, September 5th. The BLS job numbers were just released for August of 25.
Speaker: And so what we saw was... fairly, I'd say, anemic growth in August of 22,000 jobs added. ah We had an upward revision in July up to 79,000. And then ah maybe the biggest part of that puzzle is the downward revision in June to 13,000 jobs lost nationwide. So my first question for you is just a reaction to kind of all these pieces, including these revisions, which of course is a big part of why the BLS is such an ah important part of the story these days.
Speaker: um But what's your reaction to the, to the job numbers? Well, it continues the impression that, um, that that we got last time. So that was August 1st, right? um And there we we got a clear, very strong indication that job creation had stalled.
Speaker: um And this month reinforces that. And so, yes, the estimate just...
Speaker: is just um You know job creation of 22,000 jobs. And that's zero. I mean, that's zero. yeah um And the three month moving average, which I like to look at because it includes the benefits of the past revisions and smooths out some of the randomness that you can get in this.
Speaker: ah gives us a three-month moving average ah job creation of 29,000. So about what we got this month. right And so that says that we're in a new phase of this expansion, um which is pretty close to stalled, basically.
Speaker: And that happens sometimes, but often that's the pathway to the beginning of a recession. So I'd say we're flashing yellow now. That's what I see.
Speaker: um Not definitely, but but it's flashing yellow. And this is this could be yeah the sign that we are turning the corner into a recession. And there have been a lot of policy changes that might turn out to be the ah explanations for this.
Speaker: Right now, when you both today and in your in your previous roles as commissioner and and and at the Fed, when you dive deeper into the data, what do you look for in these sort of signposting either into expansion into recession? Like what are the what are the things that you're digging into?
Speaker: So, well, one of the things I look at first actually is what's happened to temporary help jobs. Because companies that are in a hiring mode will often be adding temp workers as well, either before they turn into permanent jobs or to try out the workers or whatever. So when you see temp jobs increasing, that's often goes along with permanent job creation or as a leading indicator, permanent job creation. And it's the same thing on the downside companies that are seeing a decline in demand for their goods and services are going to be getting rid of temp workers.
Speaker: not adding them on. Right. Right. And they're going to do that before they lay off workers, their own workers. Right. Right. And so Temp Help Jobs has been a ah pretty reliable leading economic indicator. That said, it's been acting weird since the end of the pandemic. So, you know.
Speaker: Right. Right. And the other question is, when you look at this, there are, you know, for folks who are not fully immersed in these data, and we'll talk more about them in a bit. There's the household survey and there's the establishment survey.
Speaker: and And how do you balance the two? How do you think about the two in terms of the trends? Because they don't always line up at a very micro level, you know, when you get sort of into states and cities.
Speaker: So how do you think about them as you're sort of wading through all the data? Well, one thing that I definitely do when I look at the payroll survey, then I'm mostly looking at actual numbers, numbers of jobs, whatever.
Speaker: And I know that the the precision is maybe... on the change, it's not terribly high. I mean, it's still standard error of like 100,000 jobs. So, right.
Speaker: Yeah. um But, but for the total number of jobs, the position is amazing. Yeah, yeah, yeah, yeah. And so it's okay to look at numbers, ah actual numbers of jobs in the payroll survey.
Speaker: When you get to the household survey, you only want to be looking at percentages and rates. Because is a survey of 60,000 households, and the only acceptable precision really is in the rates, the unemployment rate, the labor force participation rate, EPOP, that those kinds of things.
Speaker: Right. Numbers are those standard errors are so large that, you know, in the long run, they're going to look kind of like the payroll numbers, but only after you adjust a lot of different ways and the payroll numbers are fully.
Speaker: Anyway, so. Yeah. I want to come to the adjustments because I think that's a big part of, again, this kind of national conversation about the BLS. Before we get there, I want to ask you about the revisions because I think the revisions and and last month was one of the big reasons the president just decided to fire the commissioner, the BLS commissioner.
Speaker: um I haven't seen statement from the White House yet today. I'm sure it's it there'll be something. um But can you explain to people why these revisions exist and why, in this case at least, we've now had two revisions, right? The month of June revised both in the August release and now in the September release. And so what should people know or think about to help them understand why these numbers keep getting revised?
Speaker: When people want a measure of what's going on in the labor market, the They want two things. they They want the numbers to be accurate. Right? Don't bother telling me something.
Speaker: that does it be data yeah that's it And they want it to be timely. So don't wait for three years to tell me what's going on right now. yeah Right? So they want both things.
Speaker: And the statistical agencies try to give them both things. But you reach a limit when you try to get something that's both really timely and really accurate, where there's a trade-off between the two of them.
Speaker: right And so the the the payroll survey, officially it's called the Current Employment Statistics Program, payroll survey says, well,
Speaker: We want to know, we're the way we're going to count to jobs is how many people were on the payrolls for each employer during the pay period that contains the 12th of the month. That's that's the question, right?
Speaker: And so it asks that question at the end of the month, like the last week of the month. said It says to all the companies that have agreed to participate in the survey, says, okay, you choose your mode for reporting that, and you send that us that information during this window at the end of the month.
Speaker: Okay. And some of these employers can't answer that question because they haven't finished their pay period for the 12th of month. Right. Yeah. Monthly or the pay periods don't align.
Speaker: Right. And some of them are in some kind of turmoil or Sally is sick whatever. Right. Right. And they can't get it. But two thirds of them do.
Speaker: And BLS over time is determined that that is actually a useful, it's it's a useful preliminary number. It's not the final number because a third of them haven't reported yet, but a third of them have.
Speaker: And so BLS doesn't want to sit on that. And it puts out the preliminary estimate using those numbers. Now, the companies then have another window that they can report for.
Speaker: So, you know, let's say we're talking about June, right? yeah so um So at the end of June, they were asked that. And then again at the end of July, they were asked the same question. And the companies who didn't report before have a chance to report again. And by then, but like around 90% of them report.
Speaker: And then they get one more chance, right you know, in August. So they have, they have in total three opportunities to report for each month of the year.
Speaker: Correct. That's right. i mean And so for like the July... form or questionnaire that they have to they have to fill out. There is a theres some section of that that says, do you have updates to the June numbers or you didn't fill it in? So is it, does every, I guess my question is, does every firm get the same questionnaire so that even if you did report your June numbers, you still have the opportunity to even change your own numbers as opposed to a firm that did not submit it at all because-
Speaker: you know, Sally wasn't in the office that week, um they can fill it in. So everybody has the opportunity to revise the numbers. Yes. And sometimes firms discover they've made a mistake and they'll correct it.
Speaker: okay yeah so So they each have these three opportunities. And the so the first revision ah the of the preliminary number is mostly driven by late reporting firms.
Speaker: Okay. So that's probably the the pay period Yeah. Yeah. Okay. Right. Yeah. The second revision that gets you to the third number, right?
Speaker: Right. That one will have the last stragglers. that So you go from around, you 60, 70% of
Speaker: ah for the first preliminary one, then you get up to pretty close to 90% for the second one. And for the third one, you're talking 94%, something like that.
Speaker: Okay. Yeah. Okay. Now, also between the second and the third one is when you're most likely to get a change in the seasonal adjustment factors.
Speaker: Mm-hmm. And the seasonal adjustment factors are what we all need to be able to detect trends because there's a lot of seasonality in employment.
Speaker: And if you don't take out the seasonal trend, you could be thinking that jobs are really growing like crazy in September. Right. When when they're, you know, when the teachers are coming back. yeah Teachers are coming back.
Speaker: Yeah, right. So, but those do move over time and you and BLS wants to keep up to date with seasonals. And so every month they recalculate the seasonals. And so most of the change from the the second to the third is usually seasonals.
Speaker: Right. Now, on the household side, and we don't need to get into into depth about it, but on the household side, it and I think just broader household individual surveys, response rates have been falling over time.
Speaker: Is that the same on the establishment side, or are those response rates fairly steady or steadier, I should say? I would have told you that they were steadier.
Speaker: okay When I was at BLS, they were fairly steady. And it turned out a reason an important reason for that was that BLS was really innovating on response modes and making it easier and easier for employers to respond.
Speaker: And that helped them to sustain those response rates for more or less the time that I was there. Since then, they have declined. They took a big dip during the pandemic and have not recovered very much since then. So now we're talking about employer response rates that are half of what they were when I was at BLO. Now that's just the ones that are agreeing to ah participate in the survey at all.
Speaker: and that's important. And that's going to affect the size of the benchmarking in particular. Right. right Right. Right. but But there's also been a decline in in companies getting in the survey for the first closing ah for the preliminaries. so So the two thirds that I talked about used to be more like three quarters.
Speaker: I see. okay And so that also, that feeds into, that would feed into bigger revisions. But there has been ah something else that the BLS has done to help keep those revisions and back to shrink those revisions.
Speaker: I think I can do this pretty succinctly. the The way that BLS treats most late reports is just there's a missing value in there. yeah Right.
Speaker: And so you're imputing the same growth rate to the ones who don't report as to the ones who did report. Mm hmm. There are some very large companies who sometimes report late.
Speaker: They don't act like small companies. Yeah. And they're important. They're big. Right. right And so BLS has some firm specific imputations that it uses for those very large companies. I got you. That has reduced revisions because you're you're you're extrapolating from their recent trends and their past behavior in other ways.
Speaker: Right. I want to ask you in a moment what you sort of see coming in the future and what people should be looking out for in the data. But I want to um just sort of put a bow on this part about quality of BLS data.
Speaker: And maybe you can tell folks, what the commissioner's role is in this. I mean, you know, the, one of the reasons that commissioner McIntyre for was, was fired by the president because, you know, he claimed the jobs were rigged and they were falsified and this sort of thing.
Speaker: And ah it's the other thing that i think is important for people to know is what does the commissioner do and what is the commissioner's role in these monthly numbers. I'm guessing that you are not working in whatever coding language BLS folks are doing, working on the birth-death model or the the you know seasonal adjustment model. So while you were there, what was your role in this monthly data collection and release?
Speaker: So the way you want to think about this is it's really a finely oiled machine, right? This is much more like a manufacturing process than anything else. It's not like consulting.
Speaker: Yeah. yeah ah um The numbers come in and they are processed and then the tables are spit out, right?
Speaker: And all of the work and the investment goes into the design of that system, not into the any ability to manipulate them on a monthly basis.
Speaker: It's just not in there. In fact, it's designed so that that if you tried to manipulate it, you'd break it. Yeah. right Yeah. Um, you have teams of experts doing quality control for specific industries just to make sure there's nothing crazy in there because some company put in a million workers when they met 10, you know?
Speaker: Um, and, uh, but they're just looking at that particular industry when they're, they're fine with that. Mm-hmm. Then they get added up in a small number of people.
Speaker: Just check those things to make sure there's nothing crazy going on there. Right. And then the numbers are final and that's it. And the commissioner gets them after their final.
Speaker: Mm-hmm. The only thing that the commissioner sees that's at all preliminary is the draft of the narrative. Those are the paragraphs. And the narrative I learned in my first a few months there when I tried to make them lively is they're not supposed to be lively.
Speaker: um There are no adjectives in there. Right. down, that's it, right? The BLS answer is the glass half empty or glass half full is, this is an eight ounce vessel with four ounces of liquid.
Speaker: You know, yeah and that' that's that that's it. Right. I mean, even the visual of the employment situation report is like plain text. It looks like it was published on a typewriter.
Speaker: I mean, it definitely has this as neutral look and feel as you could get something on the web in 2025. our There are words they use and words they don't use.
Speaker: And that's that. And so do all of these teams, well, I guess I'll ah make a little bit little bit more detailed. So for the jobs, and I'm sure differs by different data sources,
Speaker: collection, but, do but, but for jobs, are people assigned are they split into different roles? So there's the group that does large businesses, the group that does small businesses, are they distinguished by region of the country and and they kind of don't talk to each other? And then there is some other group that talks to each other to sort of pull it all together.
Speaker: Yeah. um So, of course, there are the people who work on data collection. They're mostly out on the field and they're convincing companies to participate. And they don't have much of a role in processing the numbers as they come in, although maybe someone from an industry group might reach out to them about some particular company's report that doesn't make any sense. Right. But that would be on the one off basis in the some certain circumstance.
Speaker: Right. Right. Okay. like So once once the data have all been collected, it and they the and the collection period is over, then you have the different industry groups in the main office looking at them separately from each other and only looking at their industry and not communicating with each other until they're added up together and only a few people have seen that.
Speaker: And those... Very tightly choreographed, very short turnaround. Right. Yeah. And yeah, because that the deadline for reporting the numbers is typically the Monday before the Friday when the numbers are reported.
Speaker: Yeah. So that was that's an interesting that's an interesting point. So what does the calendar look like? The firms are reporting in the last week of the month. So, so that's when it's being collected in that last week. And then it takes, I'm assuming those next it's two full weeks of the analysis and assembling.
Speaker: No, no, no, no. It's, uh, it's not, it's, it's three days to three days. Oh, wow. Yeah. Yeah. Um, yeah. So yeah, it's very, very fast, but there, there is time, you know, to look at it and, and the, the, um,
Speaker: That's why the the the programs are really important because they they flag the issues and then the people look at them and address them and most and it and it runs smoothly. but But, you know, sometimes I got it on Tuesday night and sometimes I got it Wednesday morning.
Speaker: Right, revenge right, right. To go out on Friday, right? It goes out on Friday at a very specific time, right? That's right. That's right. Okay, so with that is background and how and in your role as commissioner, um they're minute you didn't ask me, so then what does a commissioner do? Right, so what does a commissioner do? Right, yes.
Speaker: yeah Yeah, so far we've established you haven't really done anything. Right, yeah.
Speaker: So um on on the numbers day, I prepared to brief the Council of Economic Advisors and the Secretary of Labor, and also to answer questions from journalists or whatever yeah that might have come up afterwards on that release. So i was just educating myself on what the numbers said.
Speaker: Right. There are two changes that I made to the release, this boring release. Right. Yeah. oh If you look at the very last paragraph of the narrative every month, when it talks about the revisions, there is a clause there that says the second sentence actually with these revisions employment in June and July combined is at this point, 21,000 lower than previously reported.
Speaker: Right? Yes. That's there because I said, let's end it up for people. noticed that sentence this morning. was like, I don't think I've ever paid that much attention to it. But yes, I saw that this morning. are welcome. You are welcome.
Speaker: Okay, so we have you to thank for that, like that and and that now that one I could do just say, okay, let's put that in and I yeah yeah and I want that in going forward, right? So that that could be done.
Speaker: So that's in the narrative. Right. Other thing that I did was if you look at table B, there is a row there, a couple of rows there that says three month average change in thousands.
Speaker: I suggested that that be in there too. Again, anybody could do that but but My time in the Fed, we were often looking at the three-month average because that incorporated the recent revisions and helped to change our view of what we thought was going on before.
Speaker: And it smoothed out some of the randomness. And so we looked at it there and I said, well, I think it should be there because I think that people should be looking at that number. Therefore, let's put it in.
Speaker: How long, once you were like, we should put this in, how many conversations, meetings, how long was the process to get it through sort of like the, especially the career folks who had been there for a long time to say, yeah, this is a good idea. We should put this in.
Speaker: So the the ah probably one or two meetings for that. And then I saw a draft of it as they worked it through. And i I don't remember how many months, at least two months, maybe three months to get that change into.
Speaker: ah But both of these are, they are both taking data that are already produced and just disseminating them, basically additional dissemination.
Speaker: Right. it that I was not changing any methodology. This was all communication. right and yeah And I wasn't doing it just for this month because yeah i see i thought an ongoing basis, it would be helpful to the users.
Speaker: right and and i And the staff agreed with me. Right. Yeah. um And so there it is. and And it has lived on. So no one, no one just decided it was useless.
Speaker: so People are actually using it and now it's there. but that' well there you go. its um So there's that. And then, but then there's the big picture, right? And this was what really was, I consider the most important job, which was looking over the horizon.
Speaker: Where should we be going? What should we be prioritizing of all the things that BLS could be doing? What should we be but doing? And being the public face of the agency,
Speaker: fending off ah requests that were inappropriate for the agency, encouraging ones that were appropriate. that kind of thing. So, you know, CEO type thing. Right.
Speaker: Right. But the CEO isn't down there producing on the factory. They're not running machines. Right. I wasn't, I wasn't programming anything. you right Right.
Speaker: Probably in Fortran, if I know anything about, if I know anything about government work, but yeah. um hey what That wasn't, no, it wasn't Fortran. It wasn't Fortran, okay. um Okay, so with that in mind of of the commissioner's role, there've been a couple of names floated to replace the the commissioner, Commissioner McIntyre. For...
Speaker: If you were on the, ah I guess it'd be a senate ah Senate panel. If you're on the Senate panel, what are you looking for in a nominee or what questions are you asking a nominee for the position?
Speaker: Yeah, so some management leadership management experience if you're going to do this for 2500 people across the country and you're producing seven of the principal federal economic indicators for the entire country and therefore for the world really, you know, leadership management.
Speaker: is something you have to be ready for. yeah um Expertise in economic statistics, even if you're not running the calculator yourself, you understand what they mean and be able to brief people, answer questions.
Speaker: um ah you A ah good relationship with experts, you know, and knowing enough about the agencies and you're drinking from the fire hose anyway, but you've got to have some kind of grounding.
Speaker: but Right, right. right ah Ability to interact effectively with Congress, with the media, with senior Department of Labor staff.
Speaker: All of that's important. And then you get to something that sounds squishy, but is fundamental, which is that trust is mission critical for a statistical agency.
Speaker: You might as well not produce statistics if they're not trusted. Right. Because if they're not trusted, people won't use them to make their most important decisions. Mm hmm.
Speaker: In which case, why produce the data? That's only reason to produce them is so that they will be used and they're not going to be used if they're not trusted. right so And also, ah people, respondents,
Speaker: right ah aren't going to assume the burden and the risks of responding to your surveys if they don't think that they are going to create trustworthy statistics.
Speaker: Right. Right. So, i so and yeah. So in your mind, what does the commissioner what can a commissioner do to create that trust from the from the public?
Speaker: Not just the, I mean, the public receiving, as as you mentioned, the public receiving the information, but also the people who are being asked to contribute to the to the data. what what can can What can the commissioner do?
Speaker: ah There are some really important guidelines that are put out. OMB statistical policy directive number one is full of all of the things that an agency should be doing and the commissioner should be ensuring that the agency does.
Speaker: Right. And statistical policy directive three is all about the principal federal economic indicators in particular and what should be done with how you put them together, how you disseminate them, all of that.
Speaker: So saying that you are going to prioritize all of those things. And then there's a publication called the principles and practices for a federal statistical agency that's put out by the national academies goes through all of these practices.
Speaker: so um, uh,
Speaker: pledging that these are going to be the standards for your behavior and those of the agency is critical. in And then saying that if anybody superior to you tells you that you should violate them, that you are going to refuse to do that.
Speaker: Right. Now, well, to that point, Should people be worried? And given your what we've talked about with what the commissioner can and can't do when it comes to some of these monthly numbers, should people be concerned about a new commissioner being able to modify, manipulate, change the numbers in any way?
Speaker: Or is it this sort of bigger picture, broader... perspective to that is that is important, um but should people be maybe a little less worried about someone coming in and being able to change the the numbers on a month-to-month basis?
Speaker: So if the commissioner comes in alone, right right, then they're not going to be able to do something very quickly, right? and They don't have access to the underlying data.
Speaker: They don't have access to the programs. Right. Right. It's not like they can just go and change that unless they want to retype the tables themselves. Right.
Speaker: Right. On a typewriter. yeah and And there are thousands of the tables that are all put out at the same time in the same processes that have to add up. Right. This is a finely oiled machine.
Speaker: Everybody knows what they're doing. And the commissioner is not running it on a moment to moment basis. and They're the only appointee in the whole agency. Right. Right. ah So.
Speaker: What would then be the signs that they tried to do this? Right? but Well, they might bring in a posse, you know? Yeah, their own, their own people.
Speaker: But even they, they would have to figure out what to do and how to do it. Yeah. Right. And how to do it on the fly. Right. right And very complicated stuff on the fly. like just just that Just so people understand, like this isn't like you know changing a tab in an Excel file. like this is This is complicated stuff with lots of programs and lots of math going on. It's not like you just toggle some switch. Yeah.
Speaker: Right. That has been tested to make sure it all adds up. Right. yeah Right. um Okay. so So what would you see? Well, you'd probably see some delays in releases if they're trying to do it.
Speaker: You know, it would they'd have to be superhuman to not screw it up in some way. Yeah. Right. um You you'd see some unannounced or unexplained changes in methodology that and that would violate principles of transparency that the agencies are supposed to follow.
Speaker: Right. And you'd you just see mistakes. Right. you know, in them that aren't typical, right? right um You'd see injection of policy spin into the release narrative. So all a sudden you'd get adjectives.
Speaker: Yeah, right. So just the language itself. That's right. Interesting. Yeah. Yeah. Um, and, and then you'd have the signs of staff resistance because remember the culture of the BLS is definitely a political data nerds, totally dedicated, a political data nerds and you would get whistleblowers, resignations, leaks, uh, trans crazy transfers, things like that.
Speaker: So I think it would be visible. Okay. All right. So that that's the things to look for. So then what do you think Congress or...
Speaker: you know, other policy leaders, policymakers can or should be doing in this, we could almost call it a transition period from one commissioner to the next and then and then going forward.
Speaker: I'm going to assume funding is part of that. um we can We can put that to the, maybe to the side if you want, but what should policymakers role be in in this entire process?
Speaker: So a rapid and thorough vetting of any candidate. Right. The kinds of things that we talked about. So make sure that that that this candidate is worthy.
Speaker: Right. yeah And will uphold the trust. um Then there's some other important things. ah There is a ah policy that the administration is pushing forward called schedule policy career to convert, reclassify civil servants who deal in policy influencing jobs ah so that they they'll be reclassified so that they can be fired at the pleasure of the president, essentially.
Speaker: Right. Right. That converts these civil service jobs into much more like political appointments that should not be applied to anybody in the statistical agencies because the numbers influence policy.
Speaker: but the but But the statistical processes are not about influencing policy. and That distinction is not clear in anything written so far about these positions.
Speaker: We talked about investing in improving and modernizing BLS methods. Every statistical agency needs to be modernizing all the time. BLS has not been able to because it's been so strapped for funds.
Speaker: here um Congress should also clarify the um the distinction between a Presidential appointee in a term limited position like the head of the BLS and appointees that serve at the pleasure of the president.
Speaker: If they are the same, then why is there a difference? And if they're not the same, then exactly what can you fire someone in a term limited position?
Speaker: The understanding used to be, and when I took the job, my understanding was that I could only be fired for cause, for not doing my job or malfeasance or something like that. not because I produced unwelcome news to the president.
Speaker: right i And so if Congress wants there to be a distinction, they're going to have to step up to the plate for that. which Which I'm sure, by the way, which I'm sure you did on occasion in four years there. I'm sure there was news that the administration that you that you worked under was not particularly happy with.
Speaker: I was told at one point that revisions were causing presidential heartburn to President Obama.
Speaker: But that's as far as it went. Well, you could just send him a bottle of Tums, I guess. and and so they yeah Anyway, sorry, Okay, so go ahead.
Speaker: That's okay. So those are um those are really the main things. um I don't know if Congress can tell the um administration to lift the hiring freeze for the statistical agencies, but they should. Yeah, right. Because BLS is down over 20% of its staff, a third of its top leadership ah positions are empty.
Speaker: This is a problem for just maintaining operation. Yeah, right. ah One more thing Congress can do is that there are some restrictions, legal restrictions on sharing data between federal agencies and and federal and state agencies that really hamper the ability of the statistical agencies to produce modern statistics.
Speaker: Those can be lifted because statistical agencies do not endanger the privacy and the confidentiality. of any of these respondents. or i mean there's There's no logical reason for the statistical agencies not to have access to these data to produce better statistics for us all to use.
Speaker: Right, right. To talk with each other. To talk with each other. to talk Right. Right. um Okay. So before i let you go, where are you right now? How are you feeling about um the BLS and and these various attacks? I know you're part of, if not leading the the friends of the BLS group, like where are you feeling about where the agency stands now? And and we've talked a little bit about this, but where it stands now and then where things are headed with the um you know we can We can leave names of potential commissioners off, but like how are you sort of viewing the world these days from from ah from your perspective?
Speaker: I have two conflicting emotions. yeah One is i am I'm very worried about the continued collateral damage and intentional damage to the statistical agency for all the things we talked about.
Speaker: And i I understand that things could get much worse. And I think that would be really bad for our country as a whole in in so many ways.
Speaker: ah Countries who that don't have reliable statistics ah lose stature quickly. All right. And we would inhibit the ability of our businesses to make good decisions and inhibit the ability by policymakers to make good decisions.
Speaker: Chaos, all of those things. So I'm very worried about that. At the same time, I think that the uproar that we have seen since August 1st has been very, it's been very heartening to me. All the sectors, bipartisan, public, it's been vigorous, it's been sustained.
Speaker: And this signals an appreciation um ah for this long neglected public good, right? I don't know what you got till it's gone or about to be gone.
Speaker: So is this going to be a turning point for federal statistics, at least in the next years? So ah this recognition could ah lead to support from Congress and administrations that that has been lacking in the past few decades.
Speaker: um and And here's some real irony. If some of the reason that we haven't had improvement to our statistical system has been fear of disruption or people say, well, it's not necessary to disrupt things.
Speaker: Well, this administration is not worried about disruption. So maybe either by this administration or in the aftermath, of the disruption caused by this administration, there'll be an opportunity, a moment for really modernizing the statistical system the way it should be.
Speaker: And then that calls on all of us to help decide what that plan should look like and get it in place so that this administration or the next one has something good to work from, not just cobbled together by some congressmen at the last minute.
Speaker: Right. right, well, on that note, um we shall see what happens. Erica, thanks so much for coming on. Enjoy getting to see you again, getting to chat. And i appreciate you taking the time out of your day to talk with me.
Speaker: Oh, you're welcome, John. And thank you for inviting me and giving me a chance to talk to you and to your audience. This was fun. Thanks for listening to the show, everybody. Hope you learned a lot about that. I hope you will support the BLS in its efforts to produce high quality and consistent data over time.
Speaker: I hope you will check out some of the links that I posted in the show notes. And of course, I hope you will rate and review the show wherever you get it, be it on iTunes, be it on Spotify, be it on Zencastr, or be it on my website at policybiz.com.
Speaker: And of course, as always, if you're watching on YouTube, be sure to subscribe. And if you are listening, be sure to rate or review the show. Helps me bring in more listeners, more guests, and more great content for you to learn about how to be a better data professional. So until next time, this has been the PolicyViz podcast.
Speaker: Thanks so much for listening.
