May 30, 2025 • 9 mins
It's been a year since we launched Here's Why. In that time we've brought you stories from the around the world about the global economy and how it's changing. To mark the occasion, we wanted to look back at one of our favourite episodes.
CPI, PCE, GDP, PMIs and JOLTS are all data points closely monitored by markets. They help us understand where the economy is, can give us hints on where it's going. But are all of these numbers equally important? Our global economy reporter Enda Curran joins Stephen Carroll to discuss how to separate the signal from the noise.
See omnystudio.com/listener for privacy information.
Mark as Played
Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Speaker 1 (00:02):
Bloomberg Audio Studios, Podcasts, radio News. Hello Stephen here, it's
been a year since we launched Here's Why, and in
that time we've brought you stories from around the world
about the global economy and how it's changing. To mark
our first birthday, we wanted to bring you one of
our favorite episodes with our global economics reporter, end a Current.
I'll be back next week with a brand new episode.
(00:24):
In the meantime, enjoy, I'm Stephen Carol and this is
Here's Why, where we take one news story and explain
it in just a few minutes with our experts here
at Bloomberg. It's the lifeblood of the finance world, the
numbers that tell us about the state of the economy.
Speaker 2 (00:44):
The August data was at least what in manufacturing PMI,
it was disappointing Flash PMI survey data for JINE signals
a slowing pace of economic growth.
Speaker 1 (00:51):
The latest payrolls report coming in below estimates us JUB'SDSA.
Speaker 2 (00:56):
New data data data, data, data data.
Speaker 1 (01:00):
There's a deluge of data available for major economies. But
to misquote George Orwell, some data is more equal than others.
Think about them many different ways that we measure inflation
or the labor market, job openings, job creation, unemployment all
tell you something different, and everything from economic growth to
purchasing manager index surveys can get significantly revised between the
(01:22):
first and last versions. So here's why some economic data
matters more than others. We'll also tell you how to
separate the signal from the noise. Joining me now is
our global economy reporter and a current and a great
to have you with us. You're a man who knows
your numbers. There's always this question of when we get data,
whether it's telling us what was happening in the past
(01:44):
or what's happening right now, or giving us a hint
as to what's going to potentially happen in the future,
how do we attach different levels of importance to those timeframes.
Speaker 2 (01:53):
Yeah, so some of the numbers we get are very
backward looking, like, for example, when you hear people talking
about GDP data on the news headlines, that's typically telling
you where the economy was maybe a quarter ago, So
in economic terms, that's kind of ancient history. Conditions can
change quickly. Economists like to talk about what they call
high frequency indicators, data points that are given more timely
(02:16):
read and what's happening and there. For example, you might
look at retail sales, retail spending on Main Street. That's
a good indicator of consumer confidence. You might keep an
eye also on what's going on with boring financing at
from banks. If banks are lending lots of money, that
suggests that there is animal spirits and a willingness to
invest out there by cuparts and maybe for would be
(02:37):
homeowners buy a home, that's a good signal. If you're
not lending money, then it suggests that perhaps things are
more subdued them you might have expected. So some of
the numbers, as you say, it can be quite backward looking.
It's better just to treat them as such. If you
want to timely read, keep an eye on the more
high frequency indicators.
Speaker 1 (02:52):
Yeah, I mean animal spirits. Depending on what kind of
animal you're thinking about, I suppose tells you different things
about it. How do we explain the contradictions that we
sometimes see in the numbers? Sometimes they don't make so
much sense lining up one against another. If we think
about an example of maybe inflation so.
Speaker 2 (03:09):
Over the past few years. If you want to talk
about the advanced economy world there's been the worst outbreak
of inflation in decades that impacted everyone's living standards, So
interest rates go up, and the cost of a mortgage
and alone go through the roof as a result. Now
we're in a phase whereby this inflation is well entrenched,
so the pace of inflation has slowed dramatically in many economies,
(03:31):
coming back to the area where central banks like to be.
That's a good news story. But if you walk into
the shop having heard it on the news, headlinds, you're
still paying much higher prices than you wore only a
couple of years ago. So I think, say in the US,
for example, basket of groceries maybe twenty odd percent higher
than what they wore before the inflation crisis struck out.
(03:53):
And that's where you get into the difference between the
rate of inflation, which is what the economists measure every month,
versus the actual price level that you're paying in the store.
And I think there is a disconnected and confusion there.
People hear inflation's coming off, that doesn't mean prices are
coming down now. To be clear, for prices to come down,
that would need deflation, And when an economy is in deflation,
(04:13):
it typically suggests that it has some real problems going on.
So it's a tricky one at the moment. It's a
tough pill for households to swallow. But we're at a
point where inflation is slow, but for prices to start
falling that would require something of a deeper shock to
the economy.
Speaker 1 (04:28):
Yeah, and indeed, most of the conversations that you'll have
with people will be about how expensive things are consistently
rather necessarily how much they've gone up by. Another quirk
that we follow very closely here at Bloomberg is data revisions.
So we get sometimes several iterations of the same number.
Why do we see sometimes very big revisions in the data.
Speaker 2 (04:50):
It's mostly because, as I say, a lot of these
readings are snapshots in time. They are incomplete. It might
be on a monthly basis, or maybe a quarterly basis,
and as the months of the year ago goes by,
and maybe after another year or so, the kind of
agencies who utilitates the statistic agencies and the government economic
agencies put all the numbers together when they have a
(05:10):
more complete picture, and that's when they are able to say, oh,
we overstated something there, or we underestimated something there and
they make changes to what we're previously now. And so,
for example, the US employment data, and this is true
of employment data anywhere, can be subject to material revisions,
which has had recent revisions to US jobs at it
which suggest there were eight hundred thousand less jobs than
(05:32):
originally counted in the system. That speaks to a weekly
labor market than was broadly expected. Now the jobs market
still low kind in the US, but it goes to
show you that revisions can have a material impact.
Speaker 1 (05:43):
Yeah, and look, it also speaks to the idea of
getting the right data and data that is accurate, and revisions,
I suppose get us closer to what is a better
picture of what's going on in something like the jobs
market as well. There's an old joke about you put
ten economists in a room and you get eleven opinions.
How much can numbers be open to interpretation?
Speaker 2 (06:02):
There is a degree of interpretation because it could suit
someone's investment thesis. They will want to read numbers whatever
way it is to back the argument they're making. Numbers
can be interpreted to meet somebody's political bias or political outlook.
For example, so when we had the recent interest rate
cut in the US, for example, you had one side
of politics here saying it shows that the inflation story
(06:24):
is under control and the FED is at a point
that work can bring down interest rates. That's good for
costs of living. But of course you had the other
side of the political a ide here making the point
that interest rates coming down because the economy is losing
jobs and the jobs market is weakning. So everything can
be interpreted in different ways, but ultimately, one of the
good things with economics is the numbers and the data
(06:45):
and the statistics do not lie.
Speaker 1 (06:47):
So if you're looking for the most quality data or
the best things to look out for when you're trying
to assess numbers as they're being published, what are the
sort of things that you think about when you're trying
to parse what a certain number means to the economy.
Speaker 2 (07:01):
You have to look for the numbers that really speak
to what's happening in both people's lives and in companies' lives.
So that would be figures around corporate investment, business investment.
What's happening there with companies. Have they got the confidence
to go out and expand and hire new staff. Then
obviously you have to keep an eye on what's happening
with household credit. Are people taking out mortgages to buy
a house or those who have a mortgage taking out
(07:22):
a loan to renovate the house. That speaks to, of
course confidence in terms of consumer confidence that those all
around us. And then of course you have the very
timely monthly or even quarterly readings in terms of inflation,
what is going on with the price that we're paying
for goods and services? I mentioned the jobs at earlier,
that's obviously a very critical one. And then all of
(07:43):
that creates the jigsaw that is known as a GDPGIC.
So that's backward looking, but it's a health check and
it tells you worth economy.
Speaker 1 (07:49):
Has been And you've covered economies all over the world
for Bloomberg. I wonder do you have a favorite piece
of data? Is there one that still you get excited
about trying to read into the details.
Speaker 2 (07:58):
Of well, I used to get excited about. There was
a phase when satellite data on China was a big thing,
especially among hedge funds. Was popular that someone had the
latest satellite footage of some industrial expansion or development somewhere,
maybe some housing property site being developed, and they were
claiming that they were getting an early read and what's
happening in China's economy. But I think we've passed that
phase now. During the pandemic, there was a huge rush
(08:22):
on high frequency indicators, so people wanted to know what's
happening with cinema tickets, and what's happening with eating out,
and what's happening with.
Speaker 1 (08:29):
Samwiches from press.
Speaker 2 (08:31):
I remember that one all of this and usage of
the subways and truth, we're back to where we started.
We're looking at the official data that comes out of
the agencies, and people are keeping an eye on as
I mentioned earlier, spending data, keeping an eye lending data,
jobs data, inflation data. I think the satellites and SANDWIDG
indexes were all very interesting, but we've come back to
what we know and trust.
Speaker 1 (08:50):
Most returned to the classics and the current. Our Global
Economy Reporter, thanks very much for joining us for more
explanations like this from our team of twenty seven hundred
journalists and analysts around the world. World search for Quick
Take on the Bloomberg website or Bloomberg Business app. I'm
Stephen Carol. This is Here's why I'll be back next
week with more thanks for listening
Bloomberg Audio Studios, Podcasts, radio News. Hello Stephen here, it's
been a year since we launched Here's Why, and in
that time we've brought you stories from around the world
about the global economy and how it's changing. To mark
our first birthday, we wanted to bring you one of
our favorite episodes with our global economics reporter, end a Current.
I'll be back next week with a brand new episode.
(00:24):
In the meantime, enjoy, I'm Stephen Carol and this is
Here's Why, where we take one news story and explain
it in just a few minutes with our experts here
at Bloomberg. It's the lifeblood of the finance world, the
numbers that tell us about the state of the economy.
Speaker 2 (00:44):
The August data was at least what in manufacturing PMI,
it was disappointing Flash PMI survey data for JINE signals
a slowing pace of economic growth.
Speaker 1 (00:51):
The latest payrolls report coming in below estimates us JUB'SDSA.
Speaker 2 (00:56):
New data data data, data, data data.
Speaker 1 (01:00):
There's a deluge of data available for major economies. But
to misquote George Orwell, some data is more equal than others.
Think about them many different ways that we measure inflation
or the labor market, job openings, job creation, unemployment all
tell you something different, and everything from economic growth to
purchasing manager index surveys can get significantly revised between the
(01:22):
first and last versions. So here's why some economic data
matters more than others. We'll also tell you how to
separate the signal from the noise. Joining me now is
our global economy reporter and a current and a great
to have you with us. You're a man who knows
your numbers. There's always this question of when we get data,
whether it's telling us what was happening in the past
(01:44):
or what's happening right now, or giving us a hint
as to what's going to potentially happen in the future,
how do we attach different levels of importance to those timeframes.
Speaker 2 (01:53):
Yeah, so some of the numbers we get are very
backward looking, like, for example, when you hear people talking
about GDP data on the news headlines, that's typically telling
you where the economy was maybe a quarter ago, So
in economic terms, that's kind of ancient history. Conditions can
change quickly. Economists like to talk about what they call
high frequency indicators, data points that are given more timely
(02:16):
read and what's happening and there. For example, you might
look at retail sales, retail spending on Main Street. That's
a good indicator of consumer confidence. You might keep an
eye also on what's going on with boring financing at
from banks. If banks are lending lots of money, that
suggests that there is animal spirits and a willingness to
invest out there by cuparts and maybe for would be
(02:37):
homeowners buy a home, that's a good signal. If you're
not lending money, then it suggests that perhaps things are
more subdued them you might have expected. So some of
the numbers, as you say, it can be quite backward looking.
It's better just to treat them as such. If you
want to timely read, keep an eye on the more
high frequency indicators.
Speaker 1 (02:52):
Yeah, I mean animal spirits. Depending on what kind of
animal you're thinking about, I suppose tells you different things
about it. How do we explain the contradictions that we
sometimes see in the numbers? Sometimes they don't make so
much sense lining up one against another. If we think
about an example of maybe inflation so.
Speaker 2 (03:09):
Over the past few years. If you want to talk
about the advanced economy world there's been the worst outbreak
of inflation in decades that impacted everyone's living standards, So
interest rates go up, and the cost of a mortgage
and alone go through the roof as a result. Now
we're in a phase whereby this inflation is well entrenched,
so the pace of inflation has slowed dramatically in many economies,
(03:31):
coming back to the area where central banks like to be.
That's a good news story. But if you walk into
the shop having heard it on the news, headlinds, you're
still paying much higher prices than you wore only a
couple of years ago. So I think, say in the US,
for example, basket of groceries maybe twenty odd percent higher
than what they wore before the inflation crisis struck out.
(03:53):
And that's where you get into the difference between the
rate of inflation, which is what the economists measure every month,
versus the actual price level that you're paying in the store.
And I think there is a disconnected and confusion there.
People hear inflation's coming off, that doesn't mean prices are
coming down now. To be clear, for prices to come down,
that would need deflation, And when an economy is in deflation,
(04:13):
it typically suggests that it has some real problems going on.
So it's a tricky one at the moment. It's a
tough pill for households to swallow. But we're at a
point where inflation is slow, but for prices to start
falling that would require something of a deeper shock to
the economy.
Speaker 1 (04:28):
Yeah, and indeed, most of the conversations that you'll have
with people will be about how expensive things are consistently
rather necessarily how much they've gone up by. Another quirk
that we follow very closely here at Bloomberg is data revisions.
So we get sometimes several iterations of the same number.
Why do we see sometimes very big revisions in the data.
Speaker 2 (04:50):
It's mostly because, as I say, a lot of these
readings are snapshots in time. They are incomplete. It might
be on a monthly basis, or maybe a quarterly basis,
and as the months of the year ago goes by,
and maybe after another year or so, the kind of
agencies who utilitates the statistic agencies and the government economic
agencies put all the numbers together when they have a
(05:10):
more complete picture, and that's when they are able to say, oh,
we overstated something there, or we underestimated something there and
they make changes to what we're previously now. And so,
for example, the US employment data, and this is true
of employment data anywhere, can be subject to material revisions,
which has had recent revisions to US jobs at it
which suggest there were eight hundred thousand less jobs than
(05:32):
originally counted in the system. That speaks to a weekly
labor market than was broadly expected. Now the jobs market
still low kind in the US, but it goes to
show you that revisions can have a material impact.
Speaker 1 (05:43):
Yeah, and look, it also speaks to the idea of
getting the right data and data that is accurate, and revisions,
I suppose get us closer to what is a better
picture of what's going on in something like the jobs
market as well. There's an old joke about you put
ten economists in a room and you get eleven opinions.
How much can numbers be open to interpretation?
Speaker 2 (06:02):
There is a degree of interpretation because it could suit
someone's investment thesis. They will want to read numbers whatever
way it is to back the argument they're making. Numbers
can be interpreted to meet somebody's political bias or political outlook.
For example, so when we had the recent interest rate
cut in the US, for example, you had one side
of politics here saying it shows that the inflation story
(06:24):
is under control and the FED is at a point
that work can bring down interest rates. That's good for
costs of living. But of course you had the other
side of the political a ide here making the point
that interest rates coming down because the economy is losing
jobs and the jobs market is weakning. So everything can
be interpreted in different ways, but ultimately, one of the
good things with economics is the numbers and the data
(06:45):
and the statistics do not lie.
Speaker 1 (06:47):
So if you're looking for the most quality data or
the best things to look out for when you're trying
to assess numbers as they're being published, what are the
sort of things that you think about when you're trying
to parse what a certain number means to the economy.
Speaker 2 (07:01):
You have to look for the numbers that really speak
to what's happening in both people's lives and in companies' lives.
So that would be figures around corporate investment, business investment.
What's happening there with companies. Have they got the confidence
to go out and expand and hire new staff. Then
obviously you have to keep an eye on what's happening
with household credit. Are people taking out mortgages to buy
a house or those who have a mortgage taking out
(07:22):
a loan to renovate the house. That speaks to, of
course confidence in terms of consumer confidence that those all
around us. And then of course you have the very
timely monthly or even quarterly readings in terms of inflation,
what is going on with the price that we're paying
for goods and services? I mentioned the jobs at earlier,
that's obviously a very critical one. And then all of
(07:43):
that creates the jigsaw that is known as a GDPGIC.
So that's backward looking, but it's a health check and
it tells you worth economy.
Speaker 1 (07:49):
Has been And you've covered economies all over the world
for Bloomberg. I wonder do you have a favorite piece
of data? Is there one that still you get excited
about trying to read into the details.
Speaker 2 (07:58):
Of well, I used to get excited about. There was
a phase when satellite data on China was a big thing,
especially among hedge funds. Was popular that someone had the
latest satellite footage of some industrial expansion or development somewhere,
maybe some housing property site being developed, and they were
claiming that they were getting an early read and what's
happening in China's economy. But I think we've passed that
phase now. During the pandemic, there was a huge rush
(08:22):
on high frequency indicators, so people wanted to know what's
happening with cinema tickets, and what's happening with eating out,
and what's happening with.
Speaker 1 (08:29):
Samwiches from press.
Speaker 2 (08:31):
I remember that one all of this and usage of
the subways and truth, we're back to where we started.
We're looking at the official data that comes out of
the agencies, and people are keeping an eye on as
I mentioned earlier, spending data, keeping an eye lending data,
jobs data, inflation data. I think the satellites and SANDWIDG
indexes were all very interesting, but we've come back to
what we know and trust.
Speaker 1 (08:50):
Most returned to the classics and the current. Our Global
Economy Reporter, thanks very much for joining us for more
explanations like this from our team of twenty seven hundred
journalists and analysts around the world. World search for Quick
Take on the Bloomberg website or Bloomberg Business app. I'm
Stephen Carol. This is Here's why I'll be back next
week with more thanks for listening
Popular Podcasts
On Purpose with Jay Shetty
I’m Jay Shetty host of On Purpose the worlds #1 Mental Health podcast and I’m so grateful you found us. I started this podcast 5 years ago to invite you into conversations and workshops that are designed to help make you happier, healthier and more healed. I believe that when you (yes you) feel seen, heard and understood you’re able to deal with relationship struggles, work challenges and life’s ups and downs with more ease and grace. I interview experts, celebrities, thought leaders and athletes so that we can grow our mindset, build better habits and uncover a side of them we’ve never seen before. New episodes every Monday and Friday. Your support means the world to me and I don’t take it for granted — click the follow button and leave a review to help us spread the love with On Purpose. I can’t wait for you to listen to your first or 500th episode!
Crime Junkie
Does hearing about a true crime case always leave you scouring the internet for the truth behind the story? Dive into your next mystery with Crime Junkie. Every Monday, join your host Ashley Flowers as she unravels all the details of infamous and underreported true crime cases with her best friend Brit Prawat. From cold cases to missing persons and heroes in our community who seek justice, Crime Junkie is your destination for theories and stories you won’t hear anywhere else. Whether you're a seasoned true crime enthusiast or new to the genre, you'll find yourself on the edge of your seat awaiting a new episode every Monday. If you can never get enough true crime... Congratulations, you’ve found your people. Follow to join a community of Crime Junkies! Crime Junkie is presented by audiochuck Media Company.
Ridiculous History
History is beautiful, brutal and, often, ridiculous. Join Ben Bowlin and Noel Brown as they dive into some of the weirdest stories from across the span of human civilization in Ridiculous History, a podcast by iHeartRadio.