April 30, 2025 • 47 mins
Gathering official economic data is a huge process in the best of times. But a bunch of different things have now combined to make that process even harder. People aren't responding to surveys like they used to. Survey responses have also become a lot more divided along political lines. And at the same time, the Trump administration wants to cut back on government spending, and the worry is that fewer official resources will make tracking the US economy even harder for statistical departments that were already stretched. Bill Beach was commissioner of labor statistics and head of the US Bureau of Labor Statistics during Trump's first presidency and also during President Biden's. On this episode, we talk to him about the importance of official data and why the rails for economic data are deteriorating so quickly.
Read more:
Houston, We Have a Data Problem
The US Economy Is Fracturing Too
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Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Speaker 1 (00:02):
Bloomberg Audio Studios, Podcasts, Radio News.
Speaker 2 (00:18):
Hello and welcome to another episode of the Odd Lots Podcast.
Speaker 3 (00:21):
I'm Joe Wisenthal and I'm Tracy Alloway.
Speaker 2 (00:24):
Tracy, I've said this a bunch of times, and we've
sort of danced around this issue on the podcast before,
but I've said this a bunch of times. I'm sort
of fascinated by the degree to which we sort of
take numbers on the screen. For granted, Like you know,
we look at a price of a stock and it
exists on the screen, it's like, where did that come from?
Speaker 4 (00:41):
How did that get there?
Speaker 2 (00:42):
Or like the first Friday of the month, the job's
data flashes on the screen and we just start talking
about what the data said, what the unemployment rate was,
et cetera. But we don't really talk enough about like
what had to happen behind the scenes to get that
number to the screen, right.
Speaker 3 (00:58):
I find this really interesting as well, because obviously there's
the data collection portion of this, Like, yeah, you have
to go out and talk to people for certain surveys,
certain data points, but also there are so many qualitative
and subjective adjustments that you can make to that data. So,
for instance, with CPI I didn't know that CPI waitings
(01:19):
are like different depending on what city you're in. So,
for instance, like food at home could matter a lot
more in I don't know, Minneapolis compared to Chicago. It's
really interesting. And there's also qualitative adjustments. Yeah, so if
your fridge gets Wi Fi connected, then that gets incorporated
into the price as well. So it's really interesting.
Speaker 2 (01:41):
It's super interesting, and like I have a you know,
this is the issue. We don't talk about data collection,
but it's obviously some of the most interesting stuff there
is because of course, you know, things like food at
home and one city should be different than another city
if you really want to collect a basket, and so
means that you have is some of the most interesting
economics work being done anywhere in a realm that virtually
(02:05):
gets no attention. And when we talk about data collection,
you know, you hear it a lot in politics, right,
surveys have gotten you know, no one answers the phone.
It's you know, it's harder and harder to do high
quality surveys. I think you've written about this, like response
rates and just the actual cost of collection of all
this data is on the rise.
Speaker 3 (02:23):
Yeah, so I have a bunch of thoughts on this.
I'll just say talking about the economic data might be
timely as well, because we know that Trump doesn't really
respect I guess a lot of official economic data. And
he's also trying to cut back on costs or funding
of a bunch of different government programs. So it's clear
that you know, entities like the Bureau of Labor Statistics
(02:46):
could potentially be in the crosshairs here. But you're right,
response rates lower, response rates have been happening for a
long time, and it's really easy to look up like
just how bad things have gotten. If you look at
the BLS website, for instance, look at response rates on
the housing portion of CPI that's gone from about seventy
(03:07):
percent back in twenty fifteen to just fifty seven percent. Now, wow,
response rates on jolts have gone from I think sixty
seven percent to just thirty percent, So that's pretty amazing.
And the other interesting thing here is it's not just
a US problem, right, Like there's no US exceptionalism here.
(03:27):
You see the same pattern in other economies like the
UK and New Zealand, and actually in the UK just
last month, the Office of National Statistics said it wasn't
going to publish PPI because of a data quality issue.
And also trade data had a problem because of errors
in the data provided by HM Revenue and Customs. And
now there's a task force to look at all of
(03:49):
these mistakes and data problems at the ONS. So something
that goes beyond the US here.
Speaker 2 (03:55):
This is a really big deal, especially when you just
consider how much economic activity is based on being able
to look at high quality data and make decisions from it,
obviously in the market, but also in just sort of
the quote real economy, et cetera. Anyway, without further ado,
we really do have the perfect guest, someone who knows
a lot about how the sausage is made and why
(04:18):
making the sausage is getting more expensive. We are going
to be speaking to Bill Beach. He was most recently
the commissioner of the BLS, and he knows all about this.
He was the fifteenth commissioner at the BLS, does research
affiliated with the Economic Policy Innovation Center, and he's going
to talk to us about all of these issues.
Speaker 4 (04:37):
Bill, thank you so much for coming on odd Lats.
Speaker 5 (04:40):
Oh Man, it's just it's great to be with you
and Tracy. Thank you very much. It's a great topic.
Speaker 4 (04:44):
It's a great topic.
Speaker 2 (04:46):
I don't know like when the process begins, but it's like,
I get this number. It says what the jobs report,
it says how many jobs were created that month? How
did that number get onto my screen or ontobls dot gov?
Speaker 5 (05:00):
And it gets there every month, Yeah.
Speaker 2 (05:01):
Every month, every month. It's never missed except maybe once
send like a hurricane or so. Anyway, So to get.
Speaker 5 (05:07):
That first, yeah, the first Friday report, the Jobs Report,
which comes out at eight thirty Eastern time on the
first Friday. It consists of two surveys. So let me
talk about the first one, which is the one you
just mentioned that the number of jobs. That is a
survey of about four hundred thousand firms out of eleven
(05:28):
point three million firms in the United States, about four
hundred thousand of them have agreed voluntarily to send in
a pretty complex survey response. Every month, they send that
survey to electronic collection centers. There's one in Chicago, there's
one in Atlanta. And that survey has to contain the
(05:51):
twelfth day of the month, if it is a work day,
or the closest workday to that twelfth of November, or whatever,
and the reason for that is we want to get
at least one pay period in the report. Okay, So
they submit that. That data continues to be collected through
(06:11):
almost the end of the month, not quite, but almost
the end of the month. It goes from regional offices,
these regional collection centers to the national headquarters in Washington,
where about forty people sometimes less, out of the two
thousand people that work there massage the data, which means
(06:32):
that they take the data which is in the survey.
It's a sample, it's just a fragment of the total population,
and they multiply the responses by what are called weights,
and that gives us the national number. So that number
is all done pretty much by Tuesday night, preceding the Friday,
(06:54):
and on Wednesday, the Commissioner gets to hear the data.
The Commissioner, by the way, plays no role whatsoever in
massaging the data or multiplying the survey results times the weights.
Then I would brief the White House. The White House
would then brief the Federal Reserve Ward chairman, the Secretary
(07:17):
of the Treasury on Thursday. That Thursday night, usually they're
sworn to secrecy, and then at eight o'clock in the morning.
I would walk over to the Department of Labor, because
blas's headquarters is about a twenty minute walk from the
Department of Labor. I would brief the Secretary of Labor
and for an hour from eight thirty to nine thirty,
(07:40):
the Secretary of Labor and his staff had to remain quiet,
and then at nine thirty they could answer questions of
the press. So that basically is the process for the
jobs report. There's another survey there. It interrupt me any time,
but that's where we get the unemployment raise, called the
Household Survey, and that's a survey of sixty thousand households
(08:02):
selected out of a sampling frame. We can talk about
that term to be representative of the entire United States
by demographic segments. You know how many people are in
the certain age group, male, female, the racial and ethnic compositions,
and geographic locations. So it's a complex sample. That sample
is done usually by Monday of the week prior to
(08:27):
the release on Friday, and then again I get to
see the results, so the commissioner gets to see the
results on Wednesday. So that's kind of the calendar. Both
the household Survey and the Employment survey cover the same
two week period in the month. Now there may be
a day or two switch there. Sometimes the household survey
(08:50):
has a few more days in it than the establishment survey,
but they all have that twelfth of the month because
we're trying to get the middle of the month. By
the way, that's really important because if you have a
natural disaster that happens prior to the twelfth or after
the surveys are closed, that does not affect the results,
even though you would think since it happened in the
month prior that you know, the hurricane might have affected
(09:13):
implument results.
Speaker 3 (09:29):
So one thing you mentioned is companies, you know, voluntarily
responding to these surveys. And one thing I always wondered
about is how how I guess onerous or resource intensive
is responding to these surveys. So do I have to
have like a person who's dedicated to doing this every month?
(09:50):
Does it consume resources? How long is this going to
take me? And then also does the BLS ever try
to fact check some of these self reported data points?
Speaker 5 (10:02):
Those are great questions. So the survey is not just
one or two questions. It takes about thirty minutes to
fill it out completely. We do get responses that are incomplete,
and we accept those incomplete responses. The survey is usually
filled out by someone who can access the company's data
(10:23):
on wages, on total employment, on employment by supervisory or
non supervisory job functions. In other words, it's a person
usually in the operations office of a company. Now we
ask companies that are very large, you know, like the
big box retailers, all the way down to really small
corporations or small firms, and it becomes more and more
(10:47):
of a difficulty for the smaller firms, and we're very
cognizant of that. So BLS has reduced the scope of
the survey to get it as small as possible and
as free of burdens and compliance as possible. It's also
an electronics survey so that they can fill it out
on their computer screens and hit a submit button, which
(11:09):
greatly greatly improved our response rate, by the way, so
that survey is not so hard now to fill out,
though I think it still takes about thirty minutes, maybe
more if you have to dig out the data if
you're not in possession of it. The household survey is
a totally different beast. It is a long survey. It
consists of over one hundred and twenty questions. It really
(11:31):
is hard to fill out if you kind of don't
know the terminology. Let me just give you one. We
asked the question on employment. Are you working or have
you looked for work in the past four weeks? That's
the key question. We've been asking that question for since
nineteen I think nineteen forty three. If they answer I'm working,
then they are considered employed. We'll have follow up questions
(11:54):
about that, about their industry, about their tasks and so forth.
If they say no, I'm not working, then we say,
well did you look for work in the past four weeks?
And they'll say, well, you know, maybe I thought about it.
Well thinking about it. It's not enough you can look
for one day in the past four weeks and be
(12:15):
considered in the labor force but unemployed. So that sometimes
we have to have a verbal follow up rather than
they're just you know, just filling out a form. There
has to be a conversation. That's why we don't do
more than sixty thousand households because it is it's burdensome
for the person who's the questioner.
Speaker 2 (12:35):
This leads right into I think what I was about
to ask you, which is, you know we're having this
conversation April twenty twenty five. Your term of office at
the BLS ended March twenty twenty three, so you're actually
under both the two recent presidents, under the first Trump
administration then Biden. But let's say, okay, so let's say
it's March twenty twenty three. How much costlier is that
(12:58):
process of commune unicating with the households than it was,
say in twenty thirteen or two thousand and three.
Speaker 5 (13:07):
It was more and more costly, certainly, and that's because
of inflation and how inflation affected the wage bill for
the survey. Okay, the survey is taken by the Census
Bureau under a contract by BLS, So we pay the
Census Bureau to take this to go out in the
field and conduct the survey. Here's an idea of how
(13:29):
much more expensive it was. In twenty nineteen, which is
the first year of my term, I didn't have to
find any additional funding for the household survey. It might
have been just a small amount, but nothing significant. By
twenty twenty three, we were having to find almost four
million five million dollars. More so, the costs of the
(13:50):
survey is that ye per month, that would be for
the entire year. The cost of the survey went up significantly.
Now your listeners will be thinking about the federal budget,
which is in the trillions of dollars. You'd say, oh,
that's not very much money. But the Bureau's budget had
has not really changed for almost a decade, and our
(14:12):
costs have gone up, you know, progressively, especially during the
period of significant inflation which we had starting in twenty
twenty one, so that you know, finding additional money is
really hard. During the pandemic, I found millions of dollars
of couch money, unused conference fees, unused travel fees, so
I could apply that couch money if it were, you know,
(14:36):
to p purposes like buoying up the CPS or building
a data We built a brand new data center out
in the suburb of Washington. But once we were back
in business and fully using our entire budget, it was
very difficult to find those dollars to fill the hole.
(14:57):
And I think you could safely say I've been arguing
this now for over two years. Our surveys, but especially
the current population survey, the one that gives us the
unemployment rate, the labor force data are dying, They're decaying.
They're in very serious trouble and we will have if
unless we modernize that survey, we will see a time
when we will be like the British right, unable to
(15:20):
publish portions of it that just don't have sufficient sample
for statistical release.
Speaker 3 (15:27):
Okay, I'm going to ask the obvious question here, but
why have costs of conducting these surveys gathering this data
actually gone up? And I understand, you know, building data
centers is probably an expensive process. But on the other hand,
you know, going electronic instead of mailing out thousands and
thousands of surveys in theory, I would imagine maybe that
(15:49):
saves you some money. So what exactly is causing the
increase in expenses here?
Speaker 5 (15:56):
The problem is not with the electronic surveys. They will
eventually be very costly and they're there. We're suffering from
a different problem, which is just public support for the
electronic surveys. So the jobs report, that is that portion
of it that's electronically captured by these collection centers in
Chicago and Atlanta. I think those are going along all right,
(16:18):
for the time being, Our real problem is in the surveys,
the data of which is collected by people survey survey,
field survey people. They go out and they talk to
the households and they're The cost is the obvious one.
It is the wage bill. These people are highly skilled interviewers.
(16:42):
They are not high school graduates, and I have nothing
against high school graduates, but they are educated, very trained,
oftentimes economists, who will go out and speak to people
and to follow up interviews, oh my gosh, and they'll
spend hours and hours do it this. Well, okay, fine,
that's great, but it costs a lot to keep those
(17:05):
people employed. They have other opportunities, so we have to
have competitive wages. The wage bill is driving that. Collection
costs are a little bit higher, that is the processing costs,
but the big part of that is the wage build
and the wage bill is not going to go away.
That's just going to continue to go up. So we
need to do with the household survey what we have
(17:28):
done with the establishment survey, the firm survey, and that
is modernize it so it is more electronically collected. And
then we also need to integrate data which can be
obtained through the Internet on households. Households maybe go on
to a platform and with a tablet or something and
supply Maybe we go to a million households and they
(17:51):
supply five or six questions and we combine that or
blended with a person to person collected data. That's that's
what we call modernization. I mean, I mean that sounds
so innovative to your listeners, but it is very innovative
for the statistical system. Unless we do that, the cost
(18:11):
will continue to rise. The response rates, by the way,
are continuing to decline. So that's public support and we
will be we just won't have these surveys in the future.
There is too expensive.
Speaker 2 (18:22):
I want to get to the modernization in a second,
but just talk to us about I mean, I think
you said these the surveys dying, which is pretty dramatic.
Given the centrality of this between the response rates, the
increased wage bill, et cetera. How severe is this crisis?
How much time are we talking about because I imagine
(18:43):
it gets harder and harder to find that couch change
to keep it going.
Speaker 5 (18:48):
Yeah, Actually, we're out of time. We have to cut
down on the sample and I'll give you I'll give
you the evidence, my successor, the current Commissioner of Labor Statistics,
at the end of last year that we would have
to reduce the sample in the CPS, that's the household
survey by five thousand households in order to just publish
(19:11):
the rest of the sample. Okay, by cutting back on
the sample, you cut back on publishing details in the
current report. You may not have enough to publish on
teenagers anymore. On certain demographic groups, you may not be
(19:32):
able to publish details on certain age intervals, like everyone
between the ages of fifty five and sixty or sixty
five and seventy five. Every time you reduce the sample
or your response rate falls and it kind of reduces
it for you. We can talk about that next. What
(19:52):
suffers are the details. Let's go to the CPI, which
BLS also does. The CPI is a very big survey,
important survey, but it is oftentimes the case that we
don't have details for certain parts of the basket of goods,
and so we will average across some months and published
for another month based on averages of prior months. But
(20:15):
then we run out of the integrity of that average
and we can't publish the bread price or something like that.
That happens more and more because we're getting less and
less cooperation by retailers to allow our surveyors into their
stores and to go around grabbing the potato chip bag
(20:36):
and counting the number of potatoes in the back. So
we've had to innovate on the CPI, on the producer
price Index, on the import export price indexes. I hope
you haven't noticed the innovations because you're not supposed to,
but those innovations have saved, absolutely saved the import and
(20:57):
export price. We had response rates down in the twenty centiles,
completely unpublishable detail. During the time I was commissioner. We
went to using data from the Commerce Department that is
collected by the customs officials and it's working out just great,
so we completely left the surveys there. The PPI has
(21:17):
problems just like the British are having. Now not as bad,
and we're using more and more data from private companies
who will give us their data from the Internet, where
we collect that data and we combine that with the
survey data to keep the things alive on the CPI.
It's very interesting. We get all of our retail gas
(21:40):
prices now from a private company that aggregates gas prices
for the retail gasoline industry, and it's a very good source.
A lot of our housing prices now you mentioned housing,
We're going to more and more to aggregators, private aggregators.
So there are strategies for saving the survey by blending
in private data with the survey data. That is not
(22:03):
the case with the household survey of the labor force.
Nobody really collects that data except BLS. And that's why
these demographic surveys, Census has a bunch of them. Health
the health department, the Department of Health has a lot
very in very serious trouble.
Speaker 3 (22:23):
So I take the point about innovations. But one of
the things that's been happening recently is we have been
seeing bigger and bigger revisions in a lot of the data.
Is that because of the response issues, So more late
responses mean that you know you're going to get revisions
later on as those responses are incorporated. And the reason
(22:45):
I ask is I remember speaking to someone at the BLS,
and here shout out to the people working at the BLS,
because you can actually just call them and ask questions.
They're really really responsive, amazingly, like the only government department
that I really know where they'll just pick up the
phone and talk to you about methodology. Anyway, I was
asking about revisions to PPI for mayonnaise, of all things,
(23:09):
and the data there had been revised from like five
percent to ten percent, which is a pretty big change
in the space of a couple months. And he was
talking about how the PPI is subject to revision up
to four months after it's published, and it gets updated
as new replies come in. So I imagine if response
rates are going lower, then maybe that's contributing to some
(23:32):
of the revision issue.
Speaker 5 (23:33):
By and large, our issues have to do with response rate.
You're absolutely right, and I'm before I go further, I'm
very very happy you said that about BLS because BLS
prize itself and being responsive and transparent by the way,
so that's a good thing. So I think there are
two sources of this problem. The first is really hidden
(23:54):
and no one talks about it. So let me just
mention when we refresh survey, and you have to do
this because people are asked to give their survey responses
only for a few months, right, and then they drop
out and you have to find new people. The regional offices,
there are six of them in the United States for
the BLS, they have people who go out and do
(24:15):
what's called initiate a new survey respondent. It's getting more
and more difficult now to initiate that respondent. Well, people
are saying, we just don't have time, you know, Oh
my gosh, there's so many important things to do. We
don't want to give you our data because if we
give you our data, then the IRS is going to
be after us, or we're going to have some kind
of osha of you know, we don't. BLS's data is
(24:38):
completely protected from the law enforcement aspects of the federal government,
absolutely only for statistical purposes. That does not prevent help
or people saying, oh, it's going to happen, you know.
So if your initiations are dropping and it's harder and harder,
no wonder the response rates are dropping because people are
less enthusiastic. Even if they say yeah, I'd love to
(25:00):
be a part of it, they're not as enthusiastic as
they were a generation ago. So the real problem starts
at the initiation level, and we're seeing that not only
in the household survey and in the price area, but
we're also seeing that in another survey we haven't talked about,
the National Compensation Survey, which is a wonderful survey on
(25:22):
how much people are getting in union houses, union households
and non union households, and Northeast and the Southwest is
terrific about that. The Joelts report the job opening is
in labor turnover survey that you mentioned at the opening.
Its response rate has fallen dramatically, and it's largely because
(25:43):
people are less enthusiastic generally about participating in government surveys.
It's going to be hard to stem that tide, and
I think the only way we can do it is
by going to these platformed surveys, that is, surveys that
use the Internet as the main platform, integrating a lot
(26:03):
of private data, and being highly original in the way
we think about preparing a statistic for public use. We're
just not going to be facing a different world overnight
of really happy people wanting to give all their data
to the government.
Speaker 2 (26:18):
It's really a fallen world. Sometimes I'll say that, you know,
we won't let you in the store to you know,
look at the price of bread anyway? What would it
take to get there? Can this be done unilaterally within
the BLS, this sort of big upgrade. Would it need
to be something involved with Congress? Would it need a
budget allocation that would come from Congress? What would need
(26:38):
to happen to get the sort of modernized statistical collection
system that you would like actually in place?
Speaker 5 (26:44):
I think we have to approach this like we might
approach roads and bridges right. Once Congress becomes aware that
there's political liability and ignoring a problem, they generally focus
on it until it's fixed. And that was the case
with our national highway system still is a case with
our national highway system. We still have a lot of problems.
When I go to Congress and I talk about the
(27:06):
CPS and response rate, how we're going to lose the
unemployment rate, I get immediate response, and nobody, the Communists,
no one's ever said that to me, Oh, let's fix it.
So in the last Congressional Continuing Resolution, which is passed
a few weeks ago, BLS got six million more in
(27:26):
funding just to fill that hole that we've been talking
about on the wage bill. And that was an amazing
thing to get in a continuing resolution and increase in funding.
So I think Congress, presented with a plan, or the
administration of President Trump, is wide open to disruption and change.
(27:47):
I think if we develop an aggressive, bold, comprehensive plan
about how to rebuild the statistical system so that we're
using our resources much more efficiently, perhaps combining some agencies
together instead of having the twenty four separate statistical agencies,
maybe we ought to have just a handful, and then
going from there to a highly innovative different way of
(28:10):
collecting and disseminating data. Then our roads and bridges, statistically speaking,
won't be disintegrating or decaying. We will have new concrete,
will have new structures, and you can see a future
for the statistical system. I think right now, speaking as
a former director of an agency one of the most
important statistical agencies and not the most important statistical agency
(28:31):
in the world, that future looks grim to me, and
so change is required. It has to happen, and I
think that's what we have to do. Presented with the plan,
let Congress see what we're going to do and have
them fund modernization, not continuation of the current system.
Speaker 3 (28:47):
This is a little out there, but could you if
the problem is the response rates and incentivizing people to
actually answer these surveys, could you potentially pay them to
do it.
Speaker 5 (29:00):
We've tried that. It's been tried a lot. Good suggestion. Yeah,
you know, pay them dollars. Okay, tried that, didn't make
much of a difference. Then we thought, well, maybe they'd
like to have these cards you can take to retailers
and buy anything you want, right, gift cards. We tried, Yeah,
gift cards. So we tried that. Now that's not the issue.
(29:25):
I think you could pay people a lot of money,
say one thousand dollars a month, and they might participate
because that's a lot of money, But we can't afford that.
That's not out there for the statistical system. So inducements
may help with the margin, but they don't change the
trend line, which is going negative on the response rate.
(29:46):
I think we're going to live at that response rate
for a while. I do believe it's generational. I think
you can see in the really young kids now, not
the ones that are under five, but the ones that
are in their teams, kind of a return to doing
things together, having more social events. Maybe I would say
the bowling leagues are coming back, and maybe that's a
(30:08):
cultural change that leads to a more a greater sense
of participation and support of public institutions, one could hope.
Speaker 3 (30:15):
I like the idea of all the kids coming together
to answer surveys from the BLS. That's great.
Speaker 5 (30:22):
I think you get some really interesting answers there. But yes,
short of that, we have to be innovative. We have
to change, We have to think outside the box. Otherwise
this infrastructure which we all need, you know, it runs
our country. There's no economy without the Bureau of Economic
Analysis and the GDP numbers. They don't grow on trees.
(30:44):
That's going to be either going to go away or
become less reliable.
Speaker 2 (31:04):
You know something that strikes me while listening to you talk,
and like, oh, you found a way to allocate you know,
unused travel spending so that you could keep the surveys
going after the wage bilt went up, et cetera. I
keep rustling the couch change and I think about this
in you know, you mentioned Okay, well maybe the new
president is you know, theoretically open to shaking things up
(31:26):
and doing things a different way. Would you argue, pretty persuasively,
isn't necessary on the other hand, you have this sort
of dose kick which is sort of premised on this
idea that every agency in the government somehow is just
egregiously wasteful. That all of these agencies must be so
wasteful that you could cut aggressively and you almost certainly
(31:47):
aren't actually going to hit any bone. Seems to be
a sort of premise of some of the cutting. It
doesn't sound like to me when you described to be
a less in twenty nineteen through twenty twenty three, that
this is an agency that was just you know, larded up,
but had plenty of plenty of fat that can be
trimmed off.
Speaker 5 (32:07):
No fat, no pad at all. But you know, this
is the age old conflict right between the entrepreneur and
the accountant. The entrepreneur always looking for innovation and changed
and higher return on investment, and the accountant is always
looking for waste and abuse. Are we using our pencils
until they are only three inches long? I think that's
(32:28):
a fruitful thing. I think you have to have both
of those forces working all the time and overtime. Right now.
I don't doubt for one second that a lot of
the federal government could use a thorough scrubbing on the
things that Doge is looking at. The statistical system has unfortunately,
in my opinion, but fortunately now been through that scrubbing
(32:50):
over the past fifteen years, no real budgets, and yet
an increase in responsibility. So efficiencies have been gained there
just from the brutality of living year after year after
year with the same dollar amount while your costs are
going up while inflation is changing. Don't mind that because
efficiencies can occur, we can do more with fewer dollars.
(33:13):
That's okay. Innovation, on the other hand, has to be
kind of funded by your retained earnings, and we don't
have that in The statistical Congress has that, So we're
not getting the dollars necessary to innovate and secure the future.
That's the problem I want everybody kind of focus on.
Speaker 3 (33:31):
So you mentioned earlier that you had used internet data
to try to make up for the lack of a
certain data point or a certain response from the surveys,
and I'm curious, there is the sense nowadays that everything
we do is tracked and recorded somewhere. Could you potentially
use some of that type of data instead of voluntarily
(33:53):
reported responses.
Speaker 5 (33:57):
So to an extent you can use that. If you
have an unambiguous signal, and you can capture that unambiguous
signal month after month, why not capture it? Why not capture,
for example, certain pay bands or other things that are
happening in the labor force, or with wages, or with
working conditions. The restraint there is that not everything we
(34:20):
want to know about the world is unambiguously signaled every month.
And I go back to this seemingly easy question, are
you working or looking for work? You would be surprised
at the number of people who say I'm working, But
then we make that query, did you work for pay? No? No, okay,
I did the dishes? Okay, fine, Well that doesn't see
(34:44):
in the mind of the respondent, work is defined differently
than it needs to be defined in the statistics. Are
you looking for work, Well, yeah, I'm looking for work.
When did you look for work last year? Okay? See,
that doesn't count as the key determinant of whether or
not you're in the labor force. You're in the labor
(35:04):
force if you're working or looking for work in the
past four weeks. So that seemingly simple question is not
going to be unambiguously signaled by somebody answering an Internet question.
Because of the many different ways we think about our
lives and about what work is. We find this particularly
true as our country becomes I think it's a good thing.
(35:27):
More and more culturally diverse. People come in with very
different views of what is work of, what is pay of,
what is a family of, what is a household? And
we have to work harder and harder and harder to
make sure that their responses fit this continuous since nineteen
(35:47):
forty three, continuous stream of data that allows us to
do these wonderful time series analyzes. That's the issue tracy
with using Internet data. Some of it can be used
and blended in, some of it from the private sector
can be used and blended in, but some cannot. You
still have to have that survey instrument out there, asking
(36:09):
the hard questions, doing the follow ups.
Speaker 2 (36:12):
You know, there are some people who simply do not
believe these statistical agencies are honest, or they believe they
you know, they do not trust when academic economists explain
why data gets revised a year later or something like that,
and they assume that there is political influence of some sort,
or they believe it and you know, it goes back
(36:32):
years and I remember two thousand and twelve years ago,
Jack Welch, the Chicago guys will do anything, can't believe
these jobs numbers, et cetera. You were appointed in twenty
nineteen by President Trump and you crossed over to Biden.
What do you say to people who do not believe
that they can trust these numbers?
Speaker 5 (36:52):
Well, I can't dislaunch their suspicions without going to some
factual basis. So I take them through the simplest revision process,
which is the jobs revision that you know. We had
an eight hundred and eighteen thousand preliminary estimate of a
decrease in employment that was announced last August, and everybody
President Trump was running for at the time, and he
(37:14):
just said, look at this, it is totally dishonest. Bls okay.
So this happens every year. We compare our numbers to
a sampling frame with all the people who work in
the entire country, and we say, is our estimate of
total employment based on a much smaller sample than all
the firms. Is it accurate? And when we go up
(37:36):
there and we compare it every March to this total universe,
we sometimes find we're spot on, you know, less than
one tenth of a percent off, and sometimes we find
we're as much as two percent or three percent off.
That we're off more often when the economy is either
diving into recession or growing rapidly out of a recession,
(37:57):
or has a period of really bad time happening. So
when I take them through the revision process, they usually
come out and say, you know, I never knew that,
And so the next time they think about, oh, the
BLS is lying, they'll have that in their mind that really,
we did this every year it is the same way,
and we're pretty good with those numbers.
Speaker 3 (38:17):
So I want to ask you about qualitative adjustments because
I find these so interesting. And the example I used
was fridges that now have I don't know, new and
interesting features. And my understanding is that if a company
is selling a basic refrigerator for like one thousand dollars,
and then the next year it sells this new advanced
(38:39):
refrigerator for one thousand, one hundred and fifty, and then
it's also spending additional money, so like an extra hundred
or whatever to make the more advanced fridge. In cases
like that, the BLS would use a qualitative adjustment and
then the year on year PPI would be something like,
I don't know, it would be five percent instead of
(39:01):
the fifteen percent change in the actual price. How do
you actually go about making those qualitative adjustments? And I
imagine they must have been getting harder as things become
more technologically complex.
Speaker 5 (39:14):
Well, you're absolutely right, it is very difficult to do that,
but we do a lot of training. A lot of
people don't know that. At the National Headquarters there is
a training suite. I think it's on the second second floor,
at least be before we moved out of that building.
And so people from the regions who are the CPI
and PPI field teams that go out and do the surveying,
(39:38):
they come to the bl AS for training. And in
these training rooms our kitchens, there are grocery store aisles.
We've recreated kind of the inventory you might find in
a grocery store or a warehouse, and we will train
people from time to time on the changes in the
items in the CPI, the two hundred plus items the
(40:00):
CPI or the items that we're surveying at the producer
price level. So if there is a change all the
way from the number of potato chips in a bag,
which is a very important thing. And when we do
the we will look at fast foods and potato chips
and so forth, all the way to the technology involved
(40:20):
in diamond cutting. We will be training people to observe
the change and work that into their evaluation of the
product when they're in the store, when they're in the warehouse.
So the field person will literally pick up a jar
of if I could say pringles, right, and they'll say, well,
(40:40):
last month I had thirty six springles in here, and
it's this month it's the same price, but we only
have thirty two pringles here.
Speaker 3 (40:49):
Wow. True regularity.
Speaker 5 (40:52):
Yeah, so that that fits into.
Speaker 4 (40:55):
Now price perles keep going exactly.
Speaker 5 (40:59):
But it has to be that way because what happened
is the retailer will keep the or the producer will
keep the price at the same level, but decrease the
item count in the in the product bag, and that
means that the product has actually gone up in price,
not have the same price. Let me just say one
more thing, great question for Tracy. We have. That's the
(41:21):
reason why we can't go to the internet and get
all of our prices because when you go to the internet,
you can't sometimes see the quality adjustments that are there.
You can't see that the fact that the hot dogs
are just a little shorter than they used to be,
or the apples a little smaller than they used to be.
I don't know about the apple thing, but the shorter
(41:43):
hot dogs is definite the case. So you have to
we train these people. They're highly trained. That's they're also
very expensive because they're highly trained people and they can
see and know when to look and when to check
for quality improvements. Electronics definitely, you know, but a lot
of times the producers of the electronics will heavily advertise
(42:04):
the changes, make it known to everybody, because that's what
you're selling new and improved. It's all of these other
items that it's more subtle. And you know, housing, Housing
is a big deal because the house is more valuable
if it has improvements in it, and some of those
improvements are completely invisible. So we're we're very conscious of
(42:25):
the fact that quality governs the price structure.
Speaker 2 (42:30):
Bill Beach, that was a fascinating conversation. I feel like
some of these areas like even just like I'm talking
about the art of actually conducting an interview you see
if someone's in the labor force, really fascinating stuff.
Speaker 4 (42:42):
Really appreciate you coming on. There's something we want.
Speaker 2 (42:45):
We wanted to talk to you, to talk to someone
long time as so appreciate you joining outlines.
Speaker 5 (42:50):
It's been it's been a pleasure. Thank you very much.
Speaker 3 (42:53):
Thank you so much.
Speaker 4 (42:53):
That was great, Tracy. I thought that was great.
Speaker 3 (43:10):
I'm so glad we finally did that one. Yeah, a
couple points. So, first of all, I did not know
that hot dogs have been getting shorter.
Speaker 4 (43:16):
Me neither.
Speaker 3 (43:17):
And it's being incorporated into the inflation data, So all
the people complaining about shrink flation, I guess you know
it is mitigated. Yeah, exactly. And then the other thing
I would say is I thought the point Bill was
making about the loss of granularity in the data was
really important. So the idea of getting to like the
(43:37):
tails of the distribution or certain minorities. And the reason
I say that is because we've been seeing a lot
of regional and social variation in a lot of these
consumer surveys. Right, So obviously people who are poorer have
been feeling terrible during the days of high inflation, and
(43:57):
people who are rich feel, you know, pretty good, good
but also inflation in Florida has been higher than elsewhere
in the country. So I think it does become more
important to get really really specific with some of these
statistics as we see those differences increase.
Speaker 2 (44:13):
It's really interesting to me to think about government high
quality government data as like this public good and try
to imagine infrastructure, right infrastructure, and try to imagine the
amount of economic activity that exists because this thing is
offered for free that we don't that people don't have
(44:34):
to pay for. And obviously in the investing world there's
a tremendous amount of interest in all this, but it's
obviously not just you know, the investing world, and so
all of these questions, whether you're starting a business or
whatever it is, you know, on some level you can
do because there is consistent, trustworthy data. And the thought
of like that going away, and what I imagine what happened is, yeah,
(44:56):
sure you'd have like private versions of varying quality that
try to replace it, and that exists today. You know,
there's private measures of inflation, et cetera. But like that
would like start to deteriorate the idea of like there
being a gold standard, and so then you hear it's like, oh,
here's like a oh, we needed to find a few
more million dollars to pay the budgets of the survey collectors.
(45:17):
Like how many billions are riding on that few extra millions?
Oh yeah, right, like how many hundreds of billions in activity?
So it's just really interesting. And then his thing explanation
at the end, why like survey collection for something like
this is it makes sense to do as a trained job, right,
and even like the subjectivity of like are you working
and what does that mean and et cetera. It's really
(45:39):
interesting to think about why it's not trivial to just
send out a survey or send out a high school
or send out a volunteer or something like that.
Speaker 3 (45:47):
Absolutely. Also, I just love the idea of someone at
the BLS counting how many potato chips are in a bag?
Speaker 2 (45:53):
I know, you know what I'm imagining, like I don't know,
like someone with like a monocle, yeah, or something like.
Speaker 3 (45:59):
The magnifying class examining shifts seeing how big they are.
Speaker 2 (46:04):
We have we're having the same image in our minds,
that's sure right now?
Speaker 3 (46:08):
Yeah, all right, shall we leave it there?
Speaker 4 (46:09):
Yeah, let's leave it there.
Speaker 3 (46:10):
This has been another episode of the Authoughts podcast. I'm
Tracy Alloway. You can follow me at Tracy.
Speaker 2 (46:15):
Alloway and I'm Jill Wisenthal. You can follow me at
the Stalwart. Follow our producers Kerman Rodriguez at Kerman armand
Dashill Bennett at Dashbot and kil Brooks at Kale Brooks.
For more odd Laws content, go to Bloomberg dot com
slash odd Lots, where we have all of our episodes
in the daily newsletter and you can chat about all
of these topics twenty four to seven in our discord
(46:36):
Discord dot gg slash od.
Speaker 3 (46:37):
Lots And if you enjoy odd Lots, if you like
it when we talk about how these statistics sausage actually
gets made, then please leave us a positive review on
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(47:00):
Thanks for listening.
Bloomberg Audio Studios, Podcasts, Radio News.
Speaker 2 (00:18):
Hello and welcome to another episode of the Odd Lots Podcast.
Speaker 3 (00:21):
I'm Joe Wisenthal and I'm Tracy Alloway.
Speaker 2 (00:24):
Tracy, I've said this a bunch of times, and we've
sort of danced around this issue on the podcast before,
but I've said this a bunch of times. I'm sort
of fascinated by the degree to which we sort of
take numbers on the screen. For granted, Like you know,
we look at a price of a stock and it
exists on the screen, it's like, where did that come from?
Speaker 4 (00:41):
How did that get there?
Speaker 2 (00:42):
Or like the first Friday of the month, the job's
data flashes on the screen and we just start talking
about what the data said, what the unemployment rate was,
et cetera. But we don't really talk enough about like
what had to happen behind the scenes to get that
number to the screen, right.
Speaker 3 (00:58):
I find this really interesting as well, because obviously there's
the data collection portion of this, Like, yeah, you have
to go out and talk to people for certain surveys,
certain data points, but also there are so many qualitative
and subjective adjustments that you can make to that data. So,
for instance, with CPI I didn't know that CPI waitings
(01:19):
are like different depending on what city you're in. So,
for instance, like food at home could matter a lot
more in I don't know, Minneapolis compared to Chicago. It's
really interesting. And there's also qualitative adjustments. Yeah, so if
your fridge gets Wi Fi connected, then that gets incorporated
into the price as well. So it's really interesting.
Speaker 2 (01:41):
It's super interesting, and like I have a you know,
this is the issue. We don't talk about data collection,
but it's obviously some of the most interesting stuff there
is because of course, you know, things like food at
home and one city should be different than another city
if you really want to collect a basket, and so
means that you have is some of the most interesting
economics work being done anywhere in a realm that virtually
(02:05):
gets no attention. And when we talk about data collection,
you know, you hear it a lot in politics, right,
surveys have gotten you know, no one answers the phone.
It's you know, it's harder and harder to do high
quality surveys. I think you've written about this, like response
rates and just the actual cost of collection of all
this data is on the rise.
Speaker 3 (02:23):
Yeah, so I have a bunch of thoughts on this.
I'll just say talking about the economic data might be
timely as well, because we know that Trump doesn't really
respect I guess a lot of official economic data. And
he's also trying to cut back on costs or funding
of a bunch of different government programs. So it's clear
that you know, entities like the Bureau of Labor Statistics
(02:46):
could potentially be in the crosshairs here. But you're right,
response rates lower, response rates have been happening for a
long time, and it's really easy to look up like
just how bad things have gotten. If you look at
the BLS website, for instance, look at response rates on
the housing portion of CPI that's gone from about seventy
(03:07):
percent back in twenty fifteen to just fifty seven percent. Now, wow,
response rates on jolts have gone from I think sixty
seven percent to just thirty percent, So that's pretty amazing.
And the other interesting thing here is it's not just
a US problem, right, Like there's no US exceptionalism here.
(03:27):
You see the same pattern in other economies like the
UK and New Zealand, and actually in the UK just
last month, the Office of National Statistics said it wasn't
going to publish PPI because of a data quality issue.
And also trade data had a problem because of errors
in the data provided by HM Revenue and Customs. And
now there's a task force to look at all of
(03:49):
these mistakes and data problems at the ONS. So something
that goes beyond the US here.
Speaker 2 (03:55):
This is a really big deal, especially when you just
consider how much economic activity is based on being able
to look at high quality data and make decisions from it,
obviously in the market, but also in just sort of
the quote real economy, et cetera. Anyway, without further ado,
we really do have the perfect guest, someone who knows
a lot about how the sausage is made and why
(04:18):
making the sausage is getting more expensive. We are going
to be speaking to Bill Beach. He was most recently
the commissioner of the BLS, and he knows all about this.
He was the fifteenth commissioner at the BLS, does research
affiliated with the Economic Policy Innovation Center, and he's going
to talk to us about all of these issues.
Speaker 4 (04:37):
Bill, thank you so much for coming on odd Lats.
Speaker 5 (04:40):
Oh Man, it's just it's great to be with you
and Tracy. Thank you very much. It's a great topic.
Speaker 4 (04:44):
It's a great topic.
Speaker 2 (04:46):
I don't know like when the process begins, but it's like,
I get this number. It says what the jobs report,
it says how many jobs were created that month? How
did that number get onto my screen or ontobls dot gov?
Speaker 5 (05:00):
And it gets there every month, Yeah.
Speaker 2 (05:01):
Every month, every month. It's never missed except maybe once
send like a hurricane or so. Anyway, So to get.
Speaker 5 (05:07):
That first, yeah, the first Friday report, the Jobs Report,
which comes out at eight thirty Eastern time on the
first Friday. It consists of two surveys. So let me
talk about the first one, which is the one you
just mentioned that the number of jobs. That is a
survey of about four hundred thousand firms out of eleven
(05:28):
point three million firms in the United States, about four
hundred thousand of them have agreed voluntarily to send in
a pretty complex survey response. Every month, they send that
survey to electronic collection centers. There's one in Chicago, there's
one in Atlanta. And that survey has to contain the
(05:51):
twelfth day of the month, if it is a work day,
or the closest workday to that twelfth of November, or whatever,
and the reason for that is we want to get
at least one pay period in the report. Okay, So
they submit that. That data continues to be collected through
(06:11):
almost the end of the month, not quite, but almost
the end of the month. It goes from regional offices,
these regional collection centers to the national headquarters in Washington,
where about forty people sometimes less, out of the two
thousand people that work there massage the data, which means
(06:32):
that they take the data which is in the survey.
It's a sample, it's just a fragment of the total population,
and they multiply the responses by what are called weights,
and that gives us the national number. So that number
is all done pretty much by Tuesday night, preceding the Friday,
(06:54):
and on Wednesday, the Commissioner gets to hear the data.
The Commissioner, by the way, plays no role whatsoever in
massaging the data or multiplying the survey results times the weights.
Then I would brief the White House. The White House
would then brief the Federal Reserve Ward chairman, the Secretary
(07:17):
of the Treasury on Thursday. That Thursday night, usually they're
sworn to secrecy, and then at eight o'clock in the morning.
I would walk over to the Department of Labor, because
blas's headquarters is about a twenty minute walk from the
Department of Labor. I would brief the Secretary of Labor
and for an hour from eight thirty to nine thirty,
(07:40):
the Secretary of Labor and his staff had to remain quiet,
and then at nine thirty they could answer questions of
the press. So that basically is the process for the
jobs report. There's another survey there. It interrupt me any time,
but that's where we get the unemployment raise, called the
Household Survey, and that's a survey of sixty thousand households
(08:02):
selected out of a sampling frame. We can talk about
that term to be representative of the entire United States
by demographic segments. You know how many people are in
the certain age group, male, female, the racial and ethnic compositions,
and geographic locations. So it's a complex sample. That sample
is done usually by Monday of the week prior to
(08:27):
the release on Friday, and then again I get to
see the results, so the commissioner gets to see the
results on Wednesday. So that's kind of the calendar. Both
the household Survey and the Employment survey cover the same
two week period in the month. Now there may be
a day or two switch there. Sometimes the household survey
(08:50):
has a few more days in it than the establishment survey,
but they all have that twelfth of the month because
we're trying to get the middle of the month. By
the way, that's really important because if you have a
natural disaster that happens prior to the twelfth or after
the surveys are closed, that does not affect the results,
even though you would think since it happened in the
month prior that you know, the hurricane might have affected
(09:13):
implument results.
Speaker 3 (09:29):
So one thing you mentioned is companies, you know, voluntarily
responding to these surveys. And one thing I always wondered
about is how how I guess onerous or resource intensive
is responding to these surveys. So do I have to
have like a person who's dedicated to doing this every month?
(09:50):
Does it consume resources? How long is this going to
take me? And then also does the BLS ever try
to fact check some of these self reported data points?
Speaker 5 (10:02):
Those are great questions. So the survey is not just
one or two questions. It takes about thirty minutes to
fill it out completely. We do get responses that are incomplete,
and we accept those incomplete responses. The survey is usually
filled out by someone who can access the company's data
(10:23):
on wages, on total employment, on employment by supervisory or
non supervisory job functions. In other words, it's a person
usually in the operations office of a company. Now we
ask companies that are very large, you know, like the
big box retailers, all the way down to really small
corporations or small firms, and it becomes more and more
(10:47):
of a difficulty for the smaller firms, and we're very
cognizant of that. So BLS has reduced the scope of
the survey to get it as small as possible and
as free of burdens and compliance as possible. It's also
an electronics survey so that they can fill it out
on their computer screens and hit a submit button, which
(11:09):
greatly greatly improved our response rate, by the way, so
that survey is not so hard now to fill out,
though I think it still takes about thirty minutes, maybe
more if you have to dig out the data if
you're not in possession of it. The household survey is
a totally different beast. It is a long survey. It
consists of over one hundred and twenty questions. It really
(11:31):
is hard to fill out if you kind of don't
know the terminology. Let me just give you one. We
asked the question on employment. Are you working or have
you looked for work in the past four weeks? That's
the key question. We've been asking that question for since
nineteen I think nineteen forty three. If they answer I'm working,
then they are considered employed. We'll have follow up questions
(11:54):
about that, about their industry, about their tasks and so forth.
If they say no, I'm not working, then we say,
well did you look for work in the past four weeks?
And they'll say, well, you know, maybe I thought about it.
Well thinking about it. It's not enough you can look
for one day in the past four weeks and be
(12:15):
considered in the labor force but unemployed. So that sometimes
we have to have a verbal follow up rather than
they're just you know, just filling out a form. There
has to be a conversation. That's why we don't do
more than sixty thousand households because it is it's burdensome
for the person who's the questioner.
Speaker 2 (12:35):
This leads right into I think what I was about
to ask you, which is, you know we're having this
conversation April twenty twenty five. Your term of office at
the BLS ended March twenty twenty three, so you're actually
under both the two recent presidents, under the first Trump
administration then Biden. But let's say, okay, so let's say
it's March twenty twenty three. How much costlier is that
(12:58):
process of commune unicating with the households than it was,
say in twenty thirteen or two thousand and three.
Speaker 5 (13:07):
It was more and more costly, certainly, and that's because
of inflation and how inflation affected the wage bill for
the survey. Okay, the survey is taken by the Census
Bureau under a contract by BLS, So we pay the
Census Bureau to take this to go out in the
field and conduct the survey. Here's an idea of how
(13:29):
much more expensive it was. In twenty nineteen, which is
the first year of my term, I didn't have to
find any additional funding for the household survey. It might
have been just a small amount, but nothing significant. By
twenty twenty three, we were having to find almost four
million five million dollars. More so, the costs of the
(13:50):
survey is that ye per month, that would be for
the entire year. The cost of the survey went up significantly.
Now your listeners will be thinking about the federal budget,
which is in the trillions of dollars. You'd say, oh,
that's not very much money. But the Bureau's budget had
has not really changed for almost a decade, and our
(14:12):
costs have gone up, you know, progressively, especially during the
period of significant inflation which we had starting in twenty
twenty one, so that you know, finding additional money is
really hard. During the pandemic, I found millions of dollars
of couch money, unused conference fees, unused travel fees, so
I could apply that couch money if it were, you know,
(14:36):
to p purposes like buoying up the CPS or building
a data We built a brand new data center out
in the suburb of Washington. But once we were back
in business and fully using our entire budget, it was
very difficult to find those dollars to fill the hole.
(14:57):
And I think you could safely say I've been arguing
this now for over two years. Our surveys, but especially
the current population survey, the one that gives us the
unemployment rate, the labor force data are dying, They're decaying.
They're in very serious trouble and we will have if
unless we modernize that survey, we will see a time
when we will be like the British right, unable to
(15:20):
publish portions of it that just don't have sufficient sample
for statistical release.
Speaker 3 (15:27):
Okay, I'm going to ask the obvious question here, but
why have costs of conducting these surveys gathering this data
actually gone up? And I understand, you know, building data
centers is probably an expensive process. But on the other hand,
you know, going electronic instead of mailing out thousands and
thousands of surveys in theory, I would imagine maybe that
(15:49):
saves you some money. So what exactly is causing the
increase in expenses here?
Speaker 5 (15:56):
The problem is not with the electronic surveys. They will
eventually be very costly and they're there. We're suffering from
a different problem, which is just public support for the
electronic surveys. So the jobs report, that is that portion
of it that's electronically captured by these collection centers in
Chicago and Atlanta. I think those are going along all right,
(16:18):
for the time being, Our real problem is in the surveys,
the data of which is collected by people survey survey,
field survey people. They go out and they talk to
the households and they're The cost is the obvious one.
It is the wage bill. These people are highly skilled interviewers.
(16:42):
They are not high school graduates, and I have nothing
against high school graduates, but they are educated, very trained,
oftentimes economists, who will go out and speak to people
and to follow up interviews, oh my gosh, and they'll
spend hours and hours do it this. Well, okay, fine,
that's great, but it costs a lot to keep those
(17:05):
people employed. They have other opportunities, so we have to
have competitive wages. The wage bill is driving that. Collection
costs are a little bit higher, that is the processing costs,
but the big part of that is the wage build
and the wage bill is not going to go away.
That's just going to continue to go up. So we
need to do with the household survey what we have
(17:28):
done with the establishment survey, the firm survey, and that
is modernize it so it is more electronically collected. And
then we also need to integrate data which can be
obtained through the Internet on households. Households maybe go on
to a platform and with a tablet or something and
supply Maybe we go to a million households and they
(17:51):
supply five or six questions and we combine that or
blended with a person to person collected data. That's that's
what we call modernization. I mean, I mean that sounds
so innovative to your listeners, but it is very innovative
for the statistical system. Unless we do that, the cost
(18:11):
will continue to rise. The response rates, by the way,
are continuing to decline. So that's public support and we
will be we just won't have these surveys in the future.
There is too expensive.
Speaker 2 (18:22):
I want to get to the modernization in a second,
but just talk to us about I mean, I think
you said these the surveys dying, which is pretty dramatic.
Given the centrality of this between the response rates, the
increased wage bill, et cetera. How severe is this crisis?
How much time are we talking about because I imagine
(18:43):
it gets harder and harder to find that couch change
to keep it going.
Speaker 5 (18:48):
Yeah, Actually, we're out of time. We have to cut
down on the sample and I'll give you I'll give
you the evidence, my successor, the current Commissioner of Labor Statistics,
at the end of last year that we would have
to reduce the sample in the CPS, that's the household
survey by five thousand households in order to just publish
(19:11):
the rest of the sample. Okay, by cutting back on
the sample, you cut back on publishing details in the
current report. You may not have enough to publish on
teenagers anymore. On certain demographic groups, you may not be
(19:32):
able to publish details on certain age intervals, like everyone
between the ages of fifty five and sixty or sixty
five and seventy five. Every time you reduce the sample
or your response rate falls and it kind of reduces
it for you. We can talk about that next. What
(19:52):
suffers are the details. Let's go to the CPI, which
BLS also does. The CPI is a very big survey,
important survey, but it is oftentimes the case that we
don't have details for certain parts of the basket of goods,
and so we will average across some months and published
for another month based on averages of prior months. But
(20:15):
then we run out of the integrity of that average
and we can't publish the bread price or something like that.
That happens more and more because we're getting less and
less cooperation by retailers to allow our surveyors into their
stores and to go around grabbing the potato chip bag
(20:36):
and counting the number of potatoes in the back. So
we've had to innovate on the CPI, on the producer
price Index, on the import export price indexes. I hope
you haven't noticed the innovations because you're not supposed to,
but those innovations have saved, absolutely saved the import and
(20:57):
export price. We had response rates down in the twenty centiles,
completely unpublishable detail. During the time I was commissioner. We
went to using data from the Commerce Department that is
collected by the customs officials and it's working out just great,
so we completely left the surveys there. The PPI has
(21:17):
problems just like the British are having. Now not as bad,
and we're using more and more data from private companies
who will give us their data from the Internet, where
we collect that data and we combine that with the
survey data to keep the things alive on the CPI.
It's very interesting. We get all of our retail gas
(21:40):
prices now from a private company that aggregates gas prices
for the retail gasoline industry, and it's a very good source.
A lot of our housing prices now you mentioned housing,
We're going to more and more to aggregators, private aggregators.
So there are strategies for saving the survey by blending
in private data with the survey data. That is not
(22:03):
the case with the household survey of the labor force.
Nobody really collects that data except BLS. And that's why
these demographic surveys, Census has a bunch of them. Health
the health department, the Department of Health has a lot
very in very serious trouble.
Speaker 3 (22:23):
So I take the point about innovations. But one of
the things that's been happening recently is we have been
seeing bigger and bigger revisions in a lot of the data.
Is that because of the response issues, So more late
responses mean that you know you're going to get revisions
later on as those responses are incorporated. And the reason
(22:45):
I ask is I remember speaking to someone at the BLS,
and here shout out to the people working at the BLS,
because you can actually just call them and ask questions.
They're really really responsive, amazingly, like the only government department
that I really know where they'll just pick up the
phone and talk to you about methodology. Anyway, I was
asking about revisions to PPI for mayonnaise, of all things,
(23:09):
and the data there had been revised from like five
percent to ten percent, which is a pretty big change
in the space of a couple months. And he was
talking about how the PPI is subject to revision up
to four months after it's published, and it gets updated
as new replies come in. So I imagine if response
rates are going lower, then maybe that's contributing to some
(23:32):
of the revision issue.
Speaker 5 (23:33):
By and large, our issues have to do with response rate.
You're absolutely right, and I'm before I go further, I'm
very very happy you said that about BLS because BLS
prize itself and being responsive and transparent by the way,
so that's a good thing. So I think there are
two sources of this problem. The first is really hidden
(23:54):
and no one talks about it. So let me just
mention when we refresh survey, and you have to do
this because people are asked to give their survey responses
only for a few months, right, and then they drop
out and you have to find new people. The regional offices,
there are six of them in the United States for
the BLS, they have people who go out and do
(24:15):
what's called initiate a new survey respondent. It's getting more
and more difficult now to initiate that respondent. Well, people
are saying, we just don't have time, you know, Oh
my gosh, there's so many important things to do. We
don't want to give you our data because if we
give you our data, then the IRS is going to
be after us, or we're going to have some kind
of osha of you know, we don't. BLS's data is
(24:38):
completely protected from the law enforcement aspects of the federal government,
absolutely only for statistical purposes. That does not prevent help
or people saying, oh, it's going to happen, you know.
So if your initiations are dropping and it's harder and harder,
no wonder the response rates are dropping because people are
less enthusiastic. Even if they say yeah, I'd love to
(25:00):
be a part of it, they're not as enthusiastic as
they were a generation ago. So the real problem starts
at the initiation level, and we're seeing that not only
in the household survey and in the price area, but
we're also seeing that in another survey we haven't talked about,
the National Compensation Survey, which is a wonderful survey on
(25:22):
how much people are getting in union houses, union households
and non union households, and Northeast and the Southwest is
terrific about that. The Joelts report the job opening is
in labor turnover survey that you mentioned at the opening.
Its response rate has fallen dramatically, and it's largely because
(25:43):
people are less enthusiastic generally about participating in government surveys.
It's going to be hard to stem that tide, and
I think the only way we can do it is
by going to these platformed surveys, that is, surveys that
use the Internet as the main platform, integrating a lot
(26:03):
of private data, and being highly original in the way
we think about preparing a statistic for public use. We're
just not going to be facing a different world overnight
of really happy people wanting to give all their data
to the government.
Speaker 2 (26:18):
It's really a fallen world. Sometimes I'll say that, you know,
we won't let you in the store to you know,
look at the price of bread anyway? What would it
take to get there? Can this be done unilaterally within
the BLS, this sort of big upgrade. Would it need
to be something involved with Congress? Would it need a
budget allocation that would come from Congress? What would need
(26:38):
to happen to get the sort of modernized statistical collection
system that you would like actually in place?
Speaker 5 (26:44):
I think we have to approach this like we might
approach roads and bridges right. Once Congress becomes aware that
there's political liability and ignoring a problem, they generally focus
on it until it's fixed. And that was the case
with our national highway system still is a case with
our national highway system. We still have a lot of problems.
When I go to Congress and I talk about the
(27:06):
CPS and response rate, how we're going to lose the
unemployment rate, I get immediate response, and nobody, the Communists,
no one's ever said that to me, Oh, let's fix it.
So in the last Congressional Continuing Resolution, which is passed
a few weeks ago, BLS got six million more in
(27:26):
funding just to fill that hole that we've been talking
about on the wage bill. And that was an amazing
thing to get in a continuing resolution and increase in funding.
So I think Congress, presented with a plan, or the
administration of President Trump, is wide open to disruption and change.
(27:47):
I think if we develop an aggressive, bold, comprehensive plan
about how to rebuild the statistical system so that we're
using our resources much more efficiently, perhaps combining some agencies
together instead of having the twenty four separate statistical agencies,
maybe we ought to have just a handful, and then
going from there to a highly innovative different way of
(28:10):
collecting and disseminating data. Then our roads and bridges, statistically speaking,
won't be disintegrating or decaying. We will have new concrete,
will have new structures, and you can see a future
for the statistical system. I think right now, speaking as
a former director of an agency one of the most
important statistical agencies and not the most important statistical agency
(28:31):
in the world, that future looks grim to me, and
so change is required. It has to happen, and I
think that's what we have to do. Presented with the plan,
let Congress see what we're going to do and have
them fund modernization, not continuation of the current system.
Speaker 3 (28:47):
This is a little out there, but could you if
the problem is the response rates and incentivizing people to
actually answer these surveys, could you potentially pay them to
do it.
Speaker 5 (29:00):
We've tried that. It's been tried a lot. Good suggestion. Yeah,
you know, pay them dollars. Okay, tried that, didn't make
much of a difference. Then we thought, well, maybe they'd
like to have these cards you can take to retailers
and buy anything you want, right, gift cards. We tried, Yeah,
gift cards. So we tried that. Now that's not the issue.
(29:25):
I think you could pay people a lot of money,
say one thousand dollars a month, and they might participate
because that's a lot of money, But we can't afford that.
That's not out there for the statistical system. So inducements
may help with the margin, but they don't change the
trend line, which is going negative on the response rate.
(29:46):
I think we're going to live at that response rate
for a while. I do believe it's generational. I think
you can see in the really young kids now, not
the ones that are under five, but the ones that
are in their teams, kind of a return to doing
things together, having more social events. Maybe I would say
the bowling leagues are coming back, and maybe that's a
(30:08):
cultural change that leads to a more a greater sense
of participation and support of public institutions, one could hope.
Speaker 3 (30:15):
I like the idea of all the kids coming together
to answer surveys from the BLS. That's great.
Speaker 5 (30:22):
I think you get some really interesting answers there. But yes,
short of that, we have to be innovative. We have
to change, We have to think outside the box. Otherwise
this infrastructure which we all need, you know, it runs
our country. There's no economy without the Bureau of Economic
Analysis and the GDP numbers. They don't grow on trees.
(30:44):
That's going to be either going to go away or
become less reliable.
Speaker 2 (31:04):
You know something that strikes me while listening to you talk,
and like, oh, you found a way to allocate you know,
unused travel spending so that you could keep the surveys
going after the wage bilt went up, et cetera. I
keep rustling the couch change and I think about this
in you know, you mentioned Okay, well maybe the new
president is you know, theoretically open to shaking things up
(31:26):
and doing things a different way. Would you argue, pretty persuasively,
isn't necessary on the other hand, you have this sort
of dose kick which is sort of premised on this
idea that every agency in the government somehow is just
egregiously wasteful. That all of these agencies must be so
wasteful that you could cut aggressively and you almost certainly
(31:47):
aren't actually going to hit any bone. Seems to be
a sort of premise of some of the cutting. It
doesn't sound like to me when you described to be
a less in twenty nineteen through twenty twenty three, that
this is an agency that was just you know, larded up,
but had plenty of plenty of fat that can be
trimmed off.
Speaker 5 (32:07):
No fat, no pad at all. But you know, this
is the age old conflict right between the entrepreneur and
the accountant. The entrepreneur always looking for innovation and changed
and higher return on investment, and the accountant is always
looking for waste and abuse. Are we using our pencils
until they are only three inches long? I think that's
(32:28):
a fruitful thing. I think you have to have both
of those forces working all the time and overtime. Right now.
I don't doubt for one second that a lot of
the federal government could use a thorough scrubbing on the
things that Doge is looking at. The statistical system has unfortunately,
in my opinion, but fortunately now been through that scrubbing
(32:50):
over the past fifteen years, no real budgets, and yet
an increase in responsibility. So efficiencies have been gained there
just from the brutality of living year after year after
year with the same dollar amount while your costs are
going up while inflation is changing. Don't mind that because
efficiencies can occur, we can do more with fewer dollars.
(33:13):
That's okay. Innovation, on the other hand, has to be
kind of funded by your retained earnings, and we don't
have that in The statistical Congress has that, So we're
not getting the dollars necessary to innovate and secure the future.
That's the problem I want everybody kind of focus on.
Speaker 3 (33:31):
So you mentioned earlier that you had used internet data
to try to make up for the lack of a
certain data point or a certain response from the surveys,
and I'm curious, there is the sense nowadays that everything
we do is tracked and recorded somewhere. Could you potentially
use some of that type of data instead of voluntarily
(33:53):
reported responses.
Speaker 5 (33:57):
So to an extent you can use that. If you
have an unambiguous signal, and you can capture that unambiguous
signal month after month, why not capture it? Why not capture,
for example, certain pay bands or other things that are
happening in the labor force, or with wages, or with
working conditions. The restraint there is that not everything we
(34:20):
want to know about the world is unambiguously signaled every month.
And I go back to this seemingly easy question, are
you working or looking for work? You would be surprised
at the number of people who say I'm working, But
then we make that query, did you work for pay? No? No, okay,
I did the dishes? Okay, fine, Well that doesn't see
(34:44):
in the mind of the respondent, work is defined differently
than it needs to be defined in the statistics. Are
you looking for work, Well, yeah, I'm looking for work.
When did you look for work last year? Okay? See,
that doesn't count as the key determinant of whether or
not you're in the labor force. You're in the labor
(35:04):
force if you're working or looking for work in the
past four weeks. So that seemingly simple question is not
going to be unambiguously signaled by somebody answering an Internet question.
Because of the many different ways we think about our
lives and about what work is. We find this particularly
true as our country becomes I think it's a good thing.
(35:27):
More and more culturally diverse. People come in with very
different views of what is work of, what is pay of,
what is a family of, what is a household? And
we have to work harder and harder and harder to
make sure that their responses fit this continuous since nineteen
(35:47):
forty three, continuous stream of data that allows us to
do these wonderful time series analyzes. That's the issue tracy
with using Internet data. Some of it can be used
and blended in, some of it from the private sector
can be used and blended in, but some cannot. You
still have to have that survey instrument out there, asking
(36:09):
the hard questions, doing the follow ups.
Speaker 2 (36:12):
You know, there are some people who simply do not
believe these statistical agencies are honest, or they believe they
you know, they do not trust when academic economists explain
why data gets revised a year later or something like that,
and they assume that there is political influence of some sort,
or they believe it and you know, it goes back
(36:32):
years and I remember two thousand and twelve years ago,
Jack Welch, the Chicago guys will do anything, can't believe
these jobs numbers, et cetera. You were appointed in twenty
nineteen by President Trump and you crossed over to Biden.
What do you say to people who do not believe
that they can trust these numbers?
Speaker 5 (36:52):
Well, I can't dislaunch their suspicions without going to some
factual basis. So I take them through the simplest revision process,
which is the jobs revision that you know. We had
an eight hundred and eighteen thousand preliminary estimate of a
decrease in employment that was announced last August, and everybody
President Trump was running for at the time, and he
(37:14):
just said, look at this, it is totally dishonest. Bls okay.
So this happens every year. We compare our numbers to
a sampling frame with all the people who work in
the entire country, and we say, is our estimate of
total employment based on a much smaller sample than all
the firms. Is it accurate? And when we go up
(37:36):
there and we compare it every March to this total universe,
we sometimes find we're spot on, you know, less than
one tenth of a percent off, and sometimes we find
we're as much as two percent or three percent off.
That we're off more often when the economy is either
diving into recession or growing rapidly out of a recession,
(37:57):
or has a period of really bad time happening. So
when I take them through the revision process, they usually
come out and say, you know, I never knew that,
And so the next time they think about, oh, the
BLS is lying, they'll have that in their mind that really,
we did this every year it is the same way,
and we're pretty good with those numbers.
Speaker 3 (38:17):
So I want to ask you about qualitative adjustments because
I find these so interesting. And the example I used
was fridges that now have I don't know, new and
interesting features. And my understanding is that if a company
is selling a basic refrigerator for like one thousand dollars,
and then the next year it sells this new advanced
(38:39):
refrigerator for one thousand, one hundred and fifty, and then
it's also spending additional money, so like an extra hundred
or whatever to make the more advanced fridge. In cases
like that, the BLS would use a qualitative adjustment and
then the year on year PPI would be something like,
I don't know, it would be five percent instead of
(39:01):
the fifteen percent change in the actual price. How do
you actually go about making those qualitative adjustments? And I
imagine they must have been getting harder as things become
more technologically complex.
Speaker 5 (39:14):
Well, you're absolutely right, it is very difficult to do that,
but we do a lot of training. A lot of
people don't know that. At the National Headquarters there is
a training suite. I think it's on the second second floor,
at least be before we moved out of that building.
And so people from the regions who are the CPI
and PPI field teams that go out and do the surveying,
(39:38):
they come to the bl AS for training. And in
these training rooms our kitchens, there are grocery store aisles.
We've recreated kind of the inventory you might find in
a grocery store or a warehouse, and we will train
people from time to time on the changes in the
items in the CPI, the two hundred plus items the
(40:00):
CPI or the items that we're surveying at the producer
price level. So if there is a change all the
way from the number of potato chips in a bag,
which is a very important thing. And when we do
the we will look at fast foods and potato chips
and so forth, all the way to the technology involved
(40:20):
in diamond cutting. We will be training people to observe
the change and work that into their evaluation of the
product when they're in the store, when they're in the warehouse.
So the field person will literally pick up a jar
of if I could say pringles, right, and they'll say, well,
(40:40):
last month I had thirty six springles in here, and
it's this month it's the same price, but we only
have thirty two pringles here.
Speaker 3 (40:49):
Wow. True regularity.
Speaker 5 (40:52):
Yeah, so that that fits into.
Speaker 4 (40:55):
Now price perles keep going exactly.
Speaker 5 (40:59):
But it has to be that way because what happened
is the retailer will keep the or the producer will
keep the price at the same level, but decrease the
item count in the in the product bag, and that
means that the product has actually gone up in price,
not have the same price. Let me just say one
more thing, great question for Tracy. We have. That's the
(41:21):
reason why we can't go to the internet and get
all of our prices because when you go to the internet,
you can't sometimes see the quality adjustments that are there.
You can't see that the fact that the hot dogs
are just a little shorter than they used to be,
or the apples a little smaller than they used to be.
I don't know about the apple thing, but the shorter
(41:43):
hot dogs is definite the case. So you have to
we train these people. They're highly trained. That's they're also
very expensive because they're highly trained people and they can
see and know when to look and when to check
for quality improvements. Electronics definitely, you know, but a lot
of times the producers of the electronics will heavily advertise
(42:04):
the changes, make it known to everybody, because that's what
you're selling new and improved. It's all of these other
items that it's more subtle. And you know, housing, Housing
is a big deal because the house is more valuable
if it has improvements in it, and some of those
improvements are completely invisible. So we're we're very conscious of
(42:25):
the fact that quality governs the price structure.
Speaker 2 (42:30):
Bill Beach, that was a fascinating conversation. I feel like
some of these areas like even just like I'm talking
about the art of actually conducting an interview you see
if someone's in the labor force, really fascinating stuff.
Speaker 4 (42:42):
Really appreciate you coming on. There's something we want.
Speaker 2 (42:45):
We wanted to talk to you, to talk to someone
long time as so appreciate you joining outlines.
Speaker 5 (42:50):
It's been it's been a pleasure. Thank you very much.
Speaker 3 (42:53):
Thank you so much.
Speaker 4 (42:53):
That was great, Tracy. I thought that was great.
Speaker 3 (43:10):
I'm so glad we finally did that one. Yeah, a
couple points. So, first of all, I did not know
that hot dogs have been getting shorter.
Speaker 4 (43:16):
Me neither.
Speaker 3 (43:17):
And it's being incorporated into the inflation data, So all
the people complaining about shrink flation, I guess you know
it is mitigated. Yeah, exactly. And then the other thing
I would say is I thought the point Bill was
making about the loss of granularity in the data was
really important. So the idea of getting to like the
(43:37):
tails of the distribution or certain minorities. And the reason
I say that is because we've been seeing a lot
of regional and social variation in a lot of these
consumer surveys. Right, So obviously people who are poorer have
been feeling terrible during the days of high inflation, and
(43:57):
people who are rich feel, you know, pretty good, good
but also inflation in Florida has been higher than elsewhere
in the country. So I think it does become more
important to get really really specific with some of these
statistics as we see those differences increase.
Speaker 2 (44:13):
It's really interesting to me to think about government high
quality government data as like this public good and try
to imagine infrastructure, right infrastructure, and try to imagine the
amount of economic activity that exists because this thing is
offered for free that we don't that people don't have
(44:34):
to pay for. And obviously in the investing world there's
a tremendous amount of interest in all this, but it's
obviously not just you know, the investing world, and so
all of these questions, whether you're starting a business or
whatever it is, you know, on some level you can
do because there is consistent, trustworthy data. And the thought
of like that going away, and what I imagine what happened is, yeah,
(44:56):
sure you'd have like private versions of varying quality that
try to replace it, and that exists today. You know,
there's private measures of inflation, et cetera. But like that
would like start to deteriorate the idea of like there
being a gold standard, and so then you hear it's like, oh,
here's like a oh, we needed to find a few
more million dollars to pay the budgets of the survey collectors.
(45:17):
Like how many billions are riding on that few extra millions?
Oh yeah, right, like how many hundreds of billions in activity?
So it's just really interesting. And then his thing explanation
at the end, why like survey collection for something like
this is it makes sense to do as a trained job, right,
and even like the subjectivity of like are you working
and what does that mean and et cetera. It's really
(45:39):
interesting to think about why it's not trivial to just
send out a survey or send out a high school
or send out a volunteer or something like that.
Speaker 3 (45:47):
Absolutely. Also, I just love the idea of someone at
the BLS counting how many potato chips are in a bag?
Speaker 2 (45:53):
I know, you know what I'm imagining, like I don't know,
like someone with like a monocle, yeah, or something like.
Speaker 3 (45:59):
The magnifying class examining shifts seeing how big they are.
Speaker 2 (46:04):
We have we're having the same image in our minds,
that's sure right now?
Speaker 3 (46:08):
Yeah, all right, shall we leave it there?
Speaker 4 (46:09):
Yeah, let's leave it there.
Speaker 3 (46:10):
This has been another episode of the Authoughts podcast. I'm
Tracy Alloway. You can follow me at Tracy.
Speaker 2 (46:15):
Alloway and I'm Jill Wisenthal. You can follow me at
the Stalwart. Follow our producers Kerman Rodriguez at Kerman armand
Dashill Bennett at Dashbot and kil Brooks at Kale Brooks.
For more odd Laws content, go to Bloomberg dot com
slash odd Lots, where we have all of our episodes
in the daily newsletter and you can chat about all
of these topics twenty four to seven in our discord
(46:36):
Discord dot gg slash od.
Speaker 3 (46:37):
Lots And if you enjoy odd Lots, if you like
it when we talk about how these statistics sausage actually
gets made, then please leave us a positive review on
your favorite podcast platform. And remember, if you are a
Bloomberg subscriber, you can listen to all of our episodes
absolutely ad free. All you need to do is find
the Bloomberg channel on Apple Podcasts and follow the instructions there.
(47:00):
Thanks for listening.
Hosts And Creators
Joe Weisenthal
Tracy Alloway
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