Moody's Talks - Inside Economics - Data Deep Dive: Gross Domestic Product

Episode Date: March 22, 2022

Mark, Ryan, and Cris do a deep dive into GDP. What is it? How is it measured and what are it's shortcomings?Full episode transcript.Kennedy notably outlined why he thought the gross national product��was an insufficient measure of success.[Note 1] He emphasized the negative values it accounted for and the positive ones it ignored:[6]Even if we act to erase material poverty, there is another greater task, it is to confront the poverty of satisfaction - purpose and dignity - that afflicts us all.Too much and for too long, we seemed to have surrendered personal excellence and community values in the mere accumulation of material things. Our Gross National Product, now, is over $800 billion dollars a year, but that Gross National Product - if we judge the United States of America by that - that Gross National Product counts air pollution and cigarette advertising, and ambulances to clear our highways of carnage. It counts special locks for our doors and the jails for the people who break them. It counts the destruction of the redwood and the loss of our natural wonder in chaotic sprawl. It counts napalm and counts nuclear warheads and armored cars for the police to fight the riots in our cities. It counts Whitman's rifle and Speck's knife, and the television programs which glorify violence in order to sell toys to our children.Yet the gross national product does not allow for the health of our children, the quality of their education or the joy of their play. It does not include the beauty of our poetry or the strength of our marriages, the intelligence of our public debate or the integrity of our public officials. It measures neither our wit nor our courage, neither our wisdom nor our learning, neither our compassion nor our devotion to our country, it measures everything in short, except that which makes life worthwhile. And it can tell us everything about America except why we are proud that we are Americans.If this is true here at home, so it is true elsewhere in world. Follow Mark Zandi @MarkZandi, Ryan Sweet @RealTime_Econ and Cris deRitis on LinkedIn for additional insight.  Questions or Comments, please email us at [e-mail]. We would love to hear from you.  To stay informed and follow the insights of Moody's Analytics economists, visit Economic View. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Welcome to Inside Economics. I'm Mark Sandy, chief economist of Moody's Analytics, and this is a deep dive podcast. We've started this deep dive into different statistics back now a couple months ago with the consumer price index where we take a really hard look at the DNA of that particular series and data and try to give the listener some real context around what we're measuring. And today's deep dive will be around GDP gross domestic product. And, of course, to help me do this forensic look at GDP, I'm joined by Chris DREDIES. Chris, hello. Chris is the deputy chief economist. How are you? How are you, Mark? I'm good.

I'm good. And it's safely ensconced in your office in Westchester, I see. Yes, yes. Are you back north here? I am. I made my way back from Florida last week. You know, did it in one day, 16 hours. Nice. Five pit stops, you know, my wife and two dogs.

And it would have been flawless, but we got trapped in traffic around D.C., which cost us. But, you know, I might have said this before. I could be a truck driver. I'll just give me my Wawa coffee. Although it's getting a little expensive to be a truck driver these days, but I can do that. But I'm back. Yep. And also Ryan, Ryan Sweet. Ryan is the director of real-time economics and obviously in deep with all this data into the bowels of the data. So a good person to have talk about GDP.

So Ryan, why don't I turn the conversation over to you? Why don't you give us a summary of GDP, gross domestic product? Sounds good. So GDP grows domestic product. This data comes from the Bureau of Economic Analysis. It's a frequency is quarterly. But, taking a step back, the definition of GDP is the value of all goods and services that we produce within a nation's border in a given year. So it sounds like an easy definition, but there's a lot of key important aspects to that. First, we're only measuring final goods and services, so intermediate goods aren't counted in GDP. It's got to be produced within our country's borders, and it has to be within a given year. So when we think about GDP, you know, the equation that we kind of hammer

home is C plus I plus G plus NX. So GDP is a function of or is a sum of consumption. So what you and I spend on goods, services, non-durable, so that's consumer spending. Business investment, and business investment can include non-residential structures investment. So think manufacturing plan a new office building in downtown Westchester. So it includes non-residential structures. It includes residential structures. And that includes new homes, brokers commissions, multi-family apartments. And then the final part of investment includes inventories.

And then G is government. And I think the government is a big consumer. They buy hammers. They buy, they also buy planes, boats, trucks. So they're a big gigantic consumer. And then the final part is NX. And NX is exports minus imports. And that's how we get GDP, C plus I plus G plus NX.

And we can riff on this later, but there's all different ways of how you can measure GDP. You can look at the expenditure approach, the production approach, and the income approach. And we'll probably tackle each of those a little bit separately. but I'll turn it back over to you and Mark and see what I missed. Well, you just described the expenditure approach, right? So you added up spending by consumers, by businesses, and by government, and added that up to a GDP. The difference between, though, consumption spending and output is inventories, right? So that's the swing in inventories.

You didn't mention that, but that's a pretty, important swing factor, particularly quarter to quarter, it can make a big difference. And that's been the case certainly during the pandemic. In the last couple quarters, inventories have been a key source of growth in the economy and driving a lot of the GDP, the output. So inventories closes the gap between the expenditures, the spending, and the output. Maybe you can take a minute while we're at it. just talk a little bit about the other two ways of adding up to GDP, the income side of the

accounts, the GDP accounts and the production side of the accounts. And these all things, these all should add up in theory. Obviously, they don't add up in practice because there's so many moving parts here in data issues that, you know, there are so-called statistical discrepancies, you know, between these different ways of measuring things, but at least in theory they add up. So what are the other two approaches to adding up to GDP? We were always taught that in, you know, intro to macroeconomics that, you know, GDP equals GDI, which is gross domestic income.

So one person's spending is another person's income. But, you know, when I became a professional economist, I realized they don't add up. I was duped, you know, in my principles of macroeconomics class. But GDI is just adding up the income side of the economy. So we sound like a conspiracy theorist. Yeah. I was duped. I was just cogitating around that first.

I teach this to my students, and I tell them. I was like, your textbook is going to say that, you know, one person's spending equals another person's income. And it doesn't when you're looking at GDP versus GDI. Because of the measurement issues. Measurement issues. There's also methodology. They're just different ways. Like, of course, they're not going to be identical.

But theoretically, I mean, it's a construct, right? So, yes. In theory, yes. In theory, sure. Anyway, I interrupted you. So what goes into gross domestic income, GDI? This is the income side. So some of the things, not all of them, are going to be wages, corporate profits, dividends, interests, rents.

These are all things that will factor into the GDI part of the equation. Have you noticed that the corporate profits, which is a component of GDI, so as you mentioned, wages and salaries and compensation of labor plus what businesses earn in terms of corporate profitability, are the, And there's a lot of other smaller components that go up to adding up to overall gross domestic income. That corporate profits as a share of national income is at a record high. Did you notice that? That's just incredible. You know, I'm given the rise in labor costs that we've seen, given the rise in material costs that we've seen, you know, energy costs and materials related to the pandemic and the supply chain disruptions, despite all of that, businesses have been able to obviously raise prices enough to compensate

for their higher costs and their share of the economic pie. I think, I don't have this exactly right, but I think it's almost 15% of the national income now goes to businesses, corporations through corporate income, through profits. And that is high as it's ever been in the data. Is that just, did you guys know that? Or was that news to you? You knew that. I knew it was high.

I didn't know the exact number, but I knew it was large and growing. It could be 14.7. I don't remember. But it rounds to 15. Yeah. And, you know, typical is more like, you know, 12. I'm again, I'm making this up because I didn't really look, but 12, 13 percent, you know, something like that. But that doesn't sound like a big difference.

But that's a pretty big difference, you know, in terms of, you know, share of national income. Yeah. So. Yeah. And maybe that's why the stock market's hanging in. Have you noticed the stock market, no matter what's being thrown at it, you know, it's Russian invasion, Fed going on a war path and now talking about raising rates very aggressively. Stock market is kind of hanging in there.

It's only down, what, six, seven, eight percent from its all-time high, you know, back at the beginning of the year. So pretty amazing. And I guess fundamentally, the stock prices are, you know, tied to. corporate profitability, and that remains very, very good. Business are able to pass through their cost to consumers. And that shouldn't change any time soon. You don't see that changing anytime soon.

Yeah. We'll grow into these valuations, right? What's that, Chris? So we'll grow into these stock market valuations is the idea, right? Profits will continue to grow. Yeah. You know, so what if the PE ratios are extremely high? Yeah, I mean.

Yeah, profitability will continue. The earnings will continue. Unless the Fed really does go on the warpath, and then that's another way you can bring valuations down quickly. Right. Well, if you see mind-bending thing, if the stock market doesn't go down, then the Fed's going to have to step on the brakes, right? Because it's counting on, you know, tightening in the so-called financial conditions, weaker stock prices to do some of the work for them, to slow growth. but if that doesn't happen, then Fred's going to have to do even more, right? Yeah, I agree.

Yeah. Okay. Okay. Very good. Okay. So that we got the expenditure side of the accounts. We got the income side of the accounts. And then, okay, now the output side of the accounts.

What's that? Ryan. I can like Chris do that one. Okay. I'm maybe hogging the other two. You see the way he said that? Because that's an easy one to explain. So we'll let Chris do it.

Well, Chris is a difficult one. He kind of already did it. So it says the production approach of the, value-added approach. So it's just the gross value of output minus the intermediate, the value of the intermediates. So it's easy to explain, but it's probably the most difficult to actually implement. That's why the BA favors the expenditure approach. They view that as the most reliable of the three. Yeah, to measure it. It's hard, hard to measure it, I guess. Yeah. Yeah. I guess it's easy to, well, easier, nothing's easy, but easier to measure, you know, output of a factory or

mine or maybe even agriculture. But when you get to the service side of the economy, like, who can measure what Ryan actually does? You know, like, what's his output? I mean, you know, just think about that for a second. It's priceless. It's price. Oh, it's price. Of course. It's priceless, right? And it's lag, too, right? The output side of the, the, the, the expenditure side of the accounts and the income side, well, the expenditures comes out most, and I think this is why we really focus on it. It's very timely. Well, it's more timely. More time. Yeah, income side is lagged about a month because corporate profits, they can't, they can't be a Bureau of Economic Analysis, can't get that together as quickly. And then on the output side,

that takes time, you know, for them to be a A to measure all that and get. So the timeliness also plays a role in what we are focused on, I think, you know, here. Yeah. Yeah. when we look at this data yeah okay um so Ryan you uh have a tracking so called tracking estimate of GDP we've talked about this on the podcast before you want to explain that and in in what you're doing uh because you know that uh forces you to get into really into the bowels of the GDP accounts to be able to do the tracking so you want to explain the tracking yeah i didn't know how deep we wanted to get into this but we'll go this will be like a deep dive We'll go deeper.

Okay. So we have a U.S. high-frequency GDP model. You know, GDP coming from the BEA is reported quarterly, but throughout, you know, the quarter and, you know, over several months, source data, so data that we know that feeds into the BEA's methodology for certain components of the GDP are released. So we can kind of create a bean counting approach. So we can kind of take in the new data on construction spending or personal real consumer spending, retail sales, you know, industrial production or things that we know in the, you know, the where they feed into GDP. And then each day, each business day, we run the model and it tells us, you know, the new data on. So, for example, we got retail sales recently.

What does that do to current quarter GDP? and we report that on a daily basis. We have a good idea of, you know, roughly a very good idea of what GDP is going to do as the quarter evolves. Right. And right now for the first quarter of 2022, you're tracking. You know, here we are in kind of mid-late March. So almost the end of the quarter, of course, the data, the monthly data that comes in that you're using for the tracking estimate are lag. So we won't get full data from March until April or May in many cases.

but what's the tracking estimate now for Q1, 2020. What's GDP going to do in the first quarter? Just a hair above 1% out of the annualized rate. We're below, we're closer to half a point recently, but some of the data has come in a little bit better. Now,

the tracking estimate will be volatile because there's inherently in the monthly statistical data, there's a lot of volatility in it, particularly early in the year when you have potential seasonal adjustment issues. our current high-frequency GDP model, that estimate that one, a little bit above 1%, doesn't factor in any impact of Russia's invasion of the Ukraine. So that data will start to show up, that impact in late March, April data.

So maybe some in Q1 will be affected by what's going on in Eastern Europe, but that effect on the U.S. economy will be more noticeable in the second quarter using the source data. You know, usually GDP, you know, is a pretty good barometer of how the economy is doing and how you kind of think about the economy is doing. Right now, my sense is the economy is booming, you know. I look at the job market, half million jobs, you know, every single month. But then I look at GDP of just a hair over 1%. That's pretty weak. And it just feels incongruous with the reality of what's going on.

But keep in mind that some degree that reflects a very well. weak conditions coming into the quarter when Amacron hit back in December in January. So you started from a very low level. And so that might be part of what's going on. But do you have that same kind of feeling that this GDP number just doesn't feel right, given what's going on in the economy? Yes, partly because if you look at what's dragging the economy down in the first quarter, it's one component.

It's inventories. So we had a big inventory build in the final three months of last year. and inventories are going, we're not going to be able to duplicate that. So, you know, inventories, for example, say they went up by $100 billion at an annual rate, we have to increase inventories in the first quarter of this year by at least $100 billion,

or inventories are going to be a drag on GDP because just the way the BEA does it is the change and the change in inventories that matters for GDP. We're setting up for a weak inventory bill in the first quarter, and that's going to pull GDP down by quite a lot. So a lot of the weakness is inventory. Well, that goes something more fundamental. It's the expenditure versus production.

So what you're saying is spending is going to be stronger than production, right? So again, GDP is production output. And we're spending more, and that's why it feels better, I think, sort of you look at retail sales and jobs and everything else. But the actual production is lower, and that goes to the, it's reflected in the reduction in inventory, or less inventory, accumulation, right? So it's a difference between output, it's between the difference between expenditure and production, the swing in. Exactly. Okay. But one thing you can do is you can, you know, adjust GDP. So you can look at something called real final sales. So you can take GDP and exclude inventories. And then you can look

at real final sales to the domestic purchaser. So you can look at GDP minus inventories minus net exports. So that's kind of a proxy for the domestic economy. And I think when you we look at that in the first quarter, that's going to be really booming. That's a good point. Yeah. You don't track that, though. It's not part of your tracking estimate. Real final sales to, yeah, I get, yes, we do.

Oh, so what is that? Do you think is, how strong is you're going to? You got to check, okay. Yep. No, but if you look at real GDP excluding inventories will be much stronger than just one percent. Got it. So real final sales is going to feel more like how I feel about the economy.

is going to be wrong. Correct. Yeah. Okay. Very good. Well, this gets to another issue and this gets to revisions. Chris, do you want to talk about the revisions today? This GDP numbers has a quarterly periodicity, but it's updated every single month.

And therefore, every month you get revisions to the day. And then you get some longer-term revisions. Do you want to describe those revisions, Chris? Yeah, high-level. I don't know where exactly you're going here, but certainly- Nowhere in particular. Just deep dive, Chris. Yeah, sure.

We could go deep as you want. But we're talking, I think what's clear from all these definitions is that they are estimates, right? We talked about measurement error. We even talk more fundamentally about how you define these different items. And so the economists at the BEA are doing their best to estimate each of these components based on the data they have. And it's from a wide variety of sources. I mean, if you really get into it, you recognize the complexity. of this problem. You're combining lots of different data, survey data, there's all sorts of

data that is getting updated and revised as time goes on, and that then causes their estimate for output within a given quarter to be revised and updated as well. So the process is to continuously update with data as it comes in, and before we arrive at a final GDP estimate. Well, that final estimate is years and years and years down the road. Fair enough. Fair enough. Because every year, well, they have an annual revision. Correct.

They bring in even more what they call source data, so underlying data. Every August. Every August. And then they have what they call a comprehensive revision, don't they? Or am I mixing things? That happens every... I think it's called a comprehensive benchmark revision. comprehensive benchmark revision.

Is that every three years, I believe? I think it's five. Is it five, three or five years? Chris, what do you're, Chris is? I thought it was five, that was my guess. Yeah, I think it's five years. Okay. That's when they can make methodological changes so they can make adjustments.

I mean, I remember this is going away back, but intellectual property had never been part of GDP until they added it, you know, years and years ago. So that's when they can make big changes to their approach to measuring GDP. Yeah. I remember the intellectual property. There was, you know, right now a big chunk of business investment is in so-called, well, there's, you mentioned structures, equipment, and there's now intellectual property. And in there, there's a popery of things, including R&D, software, I think even movies,

you know, the production of movies is in there as well, that kind of thing. And that never, that wasn't there. I think if you go back certainly 10, 15 years ago. And now that's a very large component of investment and a very fast-growing component of investment. It's a very important part of investment spending. So, yeah, they make big changes. So this is good segue to some of the criticisms, right? And one big criticism is that GDP doesn't capture all the activity in the economy, right?

So one reason why we have these methodological revisions is to try to improve it over time. So you mentioned some of the intellectual property issues, and hopefully we're getting better at capturing those. Black market activity is always a good point of debate, right? Whether you like it or not, there are activities in the economy going on. There is output or production of drugs or other activities, for example. Should you include those in GDP if you're trying to really get a comprehensive measure of all the activity in the economy, that that's going on? Probably yes, but then measuring that is even more difficult. So, lots of, lots of issues here. The other major issue is what unpaid household

activity or household production, right? That's not captured because it doesn't have a market value, right? So it's certainly output. Certainly output. Give that a shot for a while. That's pretty hard to do. Yeah, absolutely. Absolutely. I think by some necessary, estimates, right? It can maybe it's high, it might be as high as 50% or, is that right? Substantial, well, that's my, I'm thinking of my, my, yeah, exactly. Based on my experience last week, it's more than 75%. You had a lot of household, you, you missed the podcast last week, I think, because. Daddy daycare. There you go. Unpaid. Unpaid household output.

Yeah, right. It's probably not getting into the GDP accounts, that's for sure. Definitely under count. Well, I guess there's even broader conceptual issues like, for example, does GDP really reflect, you know, welfare? I mean, is that really a good measure of the, you know, how the economy is performing? You know, it's kind of, we're counting the widgets, yeah, but is that really the best way of measuring, you know, how much, how well our economy is actually doing for the population?

I think that's a pretty deep question. And there's some countries like France, I think, have tried to, with the Nobel laureate Joe Stiglitz, have come up with different measures of some variations on the theme of GDP to try to get a broader sense of how economies are doing. Yeah, as I recall, again, going to the Metering Banks, was Simon Kuznitz, right? Who was the father of GDP, the modern GDP back in the 30s?

I think he was the main critic, the first critic of GDP. So I've created this measure, but, you know, to your point, I'm counting the widgets here, but GDP is not everything. You shouldn't use this to determine whether your economy is operating efficiently or providing all the benefits that it could because it is missing a lot. It's also ignoring extraction or, you know, we talk about environmental degradation, right? That's not captured any. How you're actually producing all this output isn't captured.

It's not capturing people's health or the quality of their lives or political liberty. So there's a lot of missing parts here. It's a measure, but it's certainly shouldn't be the supreme measure. And unfortunately, I think that it often gets that place in people's minds, right? Take it for granted. Oh, that's how we're doing. You're right, right. That's the yardstick.

A lot of this comes up around natural disasters. So anytime you have a big hurricane, oh, it's going to be a net positive for the economy because, you know, basically you get a lot of destruction of property, but that destruction doesn't show up in GDP, but the rebuilding will. And so on net, when you say it's a net positive, people are, well, that sounds wrong. You know, Hurricane Katrina did a lot of super storm Sandy. They did a lot of damage. And people weren't better off after those storms. And I was like, there's a difference between economic welfare and GDP. Well, that's, that was a methodological change too, right? I mean, I remember back,

the day, BBEA did the accounting around natural disasters differently, I believe. And they did account, I think so. The, you know, the insurance losses were actually a deduction from GDP. You know, they tried to account for the loss. I believe, I believe that's because do you know, Ryan? Do you know that's the case or not? They have, I don't know about insurance losses, but I know they have an estimate of around natural disasters around the lost output. Yeah. Yeah. So the economic cost of the natural disaster.

We should actually get Adam Kamens on. He's our resident expert on natural disasters and all the economic accounting that goes around it. But you can see, the listener, you should hear this conversation. This gets really pretty complex, you know, exactly how you should measure these things and handle them. That's the other point, the other kind of missing ingredient is the distributional effects of GDP. So there has been some efforts to construct so-called distributional account. So, you know, what is the GDP for different parts of the income and wealth distributions? Because you get a better sense of, you know, who's benefiting from the output or the GDP.

And I think there's a, you know, some moves afoot in D.C. to try to – like the federal reserve has actually created so-called distributional financial accounts so they can take a look at, you know, assets and liabilities of households by different parts of the income and wealth distribution. So you can see, you know, who's getting wealthier and who's not getting as wealthy and what shares going to the top part of the income distribution, what shares going to the bottom part, that kind of thing, which is really important in a world where income and wealth inequality has become more pronounced. And so there's been an effort to try to do this with the GDP accounts, but, you know, pretty tough to do, but, you know, certainly more equitable.

Yeah, and you already highlighted the capital versus labor split, right? Yeah. That's one obvious way we can see how things have migrated over time. So, yeah, that's really important. That's the other thing to point out that given all these measurement issues, methodological issues, GDP in the United States, it could be very different from GDP in France or GDP in China or anywhere else on the planet because the statistical agencies, you know, they have different qualities of source data, timeliness of sort data, and they use the data in different ways conceptually and methodologically

to come up with their own estimate. So, you know, we all kind of compare, you know, GDP here with somewhere else, but you do that at your own peril, right? Particularly, you know, places that, you know, have pretty thin statistical, you know, kind of infrastructures for collecting information and data. And you also have to normalize it. So you can't compare the level of GDP in the U.S. to the level of GDP in China or the level of GDP in Eurozone. You're looking at GDP per capita.

Yeah. To make it closer to apples to apples compared. Apples to apples, yeah. I mean, there are some international standards, right, that broadly define all these should be OECD type of. But interpretation is up to the individual countries and what data they might have. available how they estimate. So yeah, lots of variation. And, you know, there's a lot of issues like, for example, price deflators, you know, that's measuring prices for things, right? Because we, we get nominal GDP, which is, you know,

just in dollars or euros or whatever pounds, whatever it is. Yeah. But then you try to account for inflation over time to get to kind of the real output, not the output related to price increases or declines. And so therefore, you've got to start measuring price movements. We talked about this when we did the deep die for CPI, but this gets even more complicated for GDP because now you're measuring prices for investment goods, for example. So, you know, you're trying to measure investment in information processing equipment, computer equipment. If you do that, you can count, you know, the nominal dollars that Apple sells or IBM sells or Dell sells, but then you've got to try to account for, you know, the price changes, which, by the way, you have to account for

the quality changes. So now you're into, this is really mind-numbing, you know, because you can get big increases in real output if you have very fast declining prices for investment goods related to fast technological change. And in fact, that was what was happening, you know, back when the internet was first getting going in the late 90s and early 2000s, we had very, very fast innovation technological change. that drove down prices, measure prices because of the quality improvement, which drove up real GDP. And we saw, oh, my gosh, we're booming.

You know, this was the boom times. And it was largely because of the way we were measuring, you know, quality changes in the price deflators. I mean, very, very difficult to do, very hard to do. It makes it very difficult. Okay. The other thing I wanted to mention is, Ryan, you also construct monthly GDP. So we do. GDP is, at least in the United States, in some countries like the UK and I believe Canada, they actually construct GDP on a monthly basis.

We don't, the BEA does not do that here, but you take, you've taken it upon yourself to construct an estimate of monthly GDP. Do you want to describe that? We Maverick. Yeah, right. It's not like I'm sitting in my basement doing this. So very similar, like our high frequency GDP model trying to track current. current quarter GDP. We also have simultaneously an estimate of real monthly GDP.

So GDP comes out quarterly, but we know the source data that is available at a monthly frequency. So we add them all up and we create an estimate of real monthly GDP in the U.S. Yeah. And I think the last data point is for January, right? Correct. Okay. And that showed a pretty big decline if memory servers. Yeah, we got off to a really conversation.

Omicron, weather, yeah, the economy got off to a really slow start to the first quarter. Right. And even though it feels like it's picking up here in February and particularly March, Amacron has faded. And despite Ukraine, Russia, Ukraine's invasion, feels like things are strong. It's going to depress that quarterly estimate. That's the one, a little over 1% growth that we're getting. Yeah, we dug yourself a hole, getting this quarter start.

And also on top of that, we have inventories that are going to be an enormous drag. Trades are going to be a weight. So really the domestic economy can be booming, but you get these offsets and other parts of the GDP accounts that will temper growth in the first quarter. I don't know if we want to go down this rabbit hole, but there's still some signs of residual seasonality in GDP. So GDP is seasonally adjusted, meaning we try to take away. We know that the economy doesn't do really well in the winter. We adjust for that, but there are still within some of the details, signs of residual seasonality, meaning that they're still not capturing all the seasonality that is occurring in the economy.

Oh, that's interesting. Yeah, I knew it was a problem in the employment data, or at least it felt like it was a problem in the employment data, but it's also bled into the GDP data as well, you're saying. Yeah, this is a much bigger issue five or six years ago. when we were starting to really launch and do the high frequency GDP model, so we had to put in adjustments, so-called dummy variables, to account for these residual seasonality. So each quarter had a dummy variable, whether or not seasonality was a problem.

Then when they did the comprehensive revision, the benchmark revision, the most recent one, they tried to fix a lot of it. And they did fix most of it, but some is still there. right right uh and on on the monthly GDP why why do you suppose the BEA does not construct that it's just a matter of resource that they don't construct the an estimate of GDP every month because they know that that that's my baby and if they do and no one no one else is going to yeah look at it do any better why would they I bet that's coming I haven't heard but I beg I mean neither Canada is doing it the UK is doing it yeah they could probably do it a lot better than I'm doing it so yeah

I've been confused by that. Okay. Any other, did I miss anything on GDP? Any other issues around GDP that we should alert the listener to when we talk about this? No? I mean, you can grill down into GDP. You have industry level GDP, which comes from the BEA as well. So there's a lots of...

Wasn't that goes back to the production side of the accounts, doesn't it? Correct. It does. Yeah. Okay. Oh, I guess I should also, we should also mention that there is, B.A also provides GDP estimates regionally, right? For states and I believe metropolitan areas, you can get GDP now?

I believe you can. Am I wrong? I guess something else we should check. Yeah. We'll have to check that one. I know for states, you're 100% right on states. Yeah. I know about metric areas.

And that's relatively new, too. That wasn't the case back when I first started as an economist. So that's new as well. Okay. So I think we covered it, right? Any other things you want to alert the listener to on the GDP accounts? The so-called national income and product accounts. We shorthand GDP, but it's really the national income and product accounts from the Bureau of Economic Analysis.

Oh, I did, oh, one other thing I did want to mention or just get the sense of, given all of the changes in private source information, you know, we get data, companies are getting pretty good at collecting data, you know. We work with ADP, for example, the human resource company, and we get. information on, I think, 25 or 6 million employees every single month. We have a relationship with Equifax, credit bureaus, we get a lot of credit file data that provides a lot of information. You know, every, you know, all the big tech companies are capturing a lot of information and data. Do you have any sense of that getting incorporated into the GDP accounts or is the BEA working to do that? I'm sure that's a pretty, there's a lot of thorny issues around privacy and intellectual property, that kind of thing.

But has there been any moves there? I have not been following that. Just curious, if you know of any. It doesn't have to be with just a BEA. It could be some of the source data that feeds into GDP. And, you know, I know for a fact that some agencies are incorporating, you know, alternative measures of consumer spending, particularly on the services side, which is, it's easy to count the number of vehicles that, you know, are, you know, get bought off a lot.

But it's difficult to count, you know, how much. many hamburgers were purchased in Westchester. So I think they are already starting to use some alternative data on the services side. Right. Chris, anything that I would suggest say there's a lot of nuances when it comes to GDP measures and what the definitions mean. And especially for people who aren't deep into the topic, right, even the terminology we use, investment, right? A lot of people think that when they buy stocks in the stock market, right, oh, that's investment, it's not. So it's not in the sense of what GDP is trying to capture a measure. So I just would advise if you are going to use this measure and use it in models or to make predictions, you really need

to get into the bowels here and really understand what all the different components actually mean. Yeah, do we mention that financial securities aren't counted in GDP? So like stocks, bonds, they're not counted. I don't know if we did. Right. I don't think we did. that. Why would they be counted in GDP? No, but, so I do this exercise with my students. I'm like, where is GDP counted? And I give them different scenarios.

I'm like, you, you buy, you know, 100 shares of GM stock. And they're like, oh, that's investment. Because they need investment. I was like, you pay, you know, tuition to Westchester University. Where is that investment? And so it's a fun exercise for them to learn. Yeah. The way you think where things should show up isn't necessarily where they are going to

actually show up to the GCP counts. think that they go. Or you buy a used car or an existing home versus a new car, right? So there are all these. Yeah, those both are on there. That's a great point. If you, you know, people buy six, seven million existing homes a year, but the only way that shows up in GDP is the output of the realtors that are, right?

The broker's commission. Yeah. It's because you're not, you're not building anything. There's no new output. You're just transacting an existing home for, you know, another. new homes, the construction of that, that is output. That cuts into GDP, but the existing homes does not. Use cars to say.

Yeah, we have to avoid double counting. Exactly. So the first home we bought was, you know, it was built in 1963. You know, I got counted in GDP in 1963. When we bought it in 2010, it shouldn't be counted in GDP again. Yeah, shifting ownership doesn't matter, right? Exactly. And from a macroeconomic standpoint.

Right. Right. Well, great. One last call. Anything else? I was thinking to end with this, and maybe you know this, Mark. There was a Kennedy quote around GDP where I can't remember who, which Kennedy, but something along the lines of GDP measures everything except what really matters in life. Do you remember this?

Yeah, I do remember that. Was that a Kennedy quote? I don't remember that. I'm pretty sure. Okay. It's like one of those things. Computers are everywhere, but in the GDP accounts. Right. That was out there for a while.

Oh, yeah. Who said that? Is that Greenspan? I don't think it was green. No, it was an MIT professor. How can I forget his name? Really good Econ professor, MIT or Harvard. And that went back to...

Was it cats? No, no, no, no. You would know. I just... Arthur? No. No. Okay, no.

You would know. Anyway, so that's an old quip that, you know, we could see computers taking over business, every aspect of business, but didn't seem to show up in GDP. But all of a sudden it did. You know, we got to some kind of, I guess, critical mass of computers and people, businesses really figured out how to use them effectively and got to, you know, some kind of tipping point. And that really then showed up in the data in a very significant way.

But nonetheless, it kind of highlights the difficulty in measuring anything like that. this. So, okay, I think that's a pretty deep dive. I think we went pretty deep. And if listeners have any other additional questions, fire away. Or if, you know, you want us to do a deep dive on any other particular statistic, let us know. That would be very helpful and we'll do it. So with that, we'll call this a podcast. Thank you.