Shownotes
What if our most trusted economic statistic is pointing us in the wrong direction? Diane Coyle joins Kevin Coldiron to explore why GDP - long treated as a proxy for progress - now obscures more than it reveals. As economies shift toward services, intangibles, and unpaid digital labor, much of today’s value creation falls outside the frame. Drawing on her new book, The Measure of Progress, Coyle makes the case for a new way of seeing - one that captures time, trust, and the real foundations of growth. The question isn’t how fast we’re moving. It’s whether we’re measuring the right road.
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Episode TimeStamps:
02:19 - Introduction to Diane Coyle
03:55 - How did the current systems of national accounts came to be?
06:55 - Why the national statistics doesn't add up
11:22 - The underlying problems of GDP
18:42 - How software pose a problem for measuring GDP and economic activity
23:25 - The challenges of cloud computing
26:39 - What is disintermediation and why is it a problem for economic statistics?
33:35 - The importance of considering time as a variable in economic statistics
38:38 - How technological innovations can mess up our ability to measure GDP
40:45 - Coyle's framework for improving how we measure GDP
46:34 - We are thinking about measuring national capital in the wrong way
48:48 - How human capital is measured
53:13 - What kind of statistics does Coyle value when trying to gauge the economy
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Transcripts
We're in an interesting time because the system of national accounts gets revised every 10 years or so. We've just had a revision earlier this year, but almost immediately the Secretary General of the UN announced a new commission to look at how to do better economic statistics because there is, I think, a deep sense of among many populations that the GDP growth figures don't reflect their experience. GDP growth has been going up. A lot of people feel their lives have not been getting better.
So, the popular demand, if you like, for a different approach to measurement is definitely there.
Intro:Imagine spending an hour with the world's greatest traders. Imagine learning from their experiences, their successes and their failures. Imagine no more.
Welcome to Top Traders Unplugged, the place where you can learn from the best hedge fund managers in the world so you can take your manager due diligence or investment career to the next level.
Before we begin today's conversation, remember to keep two things in mind, all the discussion we'll have about investment performance is about the past, and past performance does not guarantee or even infer anything about future performance. Also, understand that there's a significant risk of financial loss with all investment strategies and you need to request and understand the specific risks from the investment manager about their products before you make investments decisions. Here's your host, veteran hedge fund manager Niels Kaastrup-Larsen.
Niels:For me, the best part of my podcasting journey has been the opportunity to speak to a huge range of extraordinary people from all around the world. In this series, I have invited one of them, namely Kevin Coldiron, to host a series of in-depth conversations to help uncover and explain new ideas to make you a better investor.
In the series, Kevin will be speaking to authors of new books and research papers to better understand the global economy and the dynamics that shape it so that we can all successfully navigate the challenges within it. And with that, please welcome Kevin Coldiron.
Kevin: welcome everyone to the July:Well, today we're going to delve into why this is the case. Why someone who has spent her career studying economic statistics, and has even written a book called GDP, A Brief but Affectionate History, is now warning us that the system of accounts we use to produce GDP and to track economic progress is no longer working for us.
ury. She was awarded a CBE in:And she's here today to talk about her latest book, one of many that she's written, and it's called The Measure of Progress: Counting what Really Matters. So, Diane, thanks for joining us today and welcome to the show.
Diane:Thank you for the invitation. I'm always really excited when somebody gets interested in economic measurement questions because I think it's so important.
Kevin:Well, it is important and it's fundamental to so much of our lives. And I think it's even more important right now with everything that's going on. So, I'm really excited to dig into this.
Now, your book is split into three parts. There's the first part that kind of documents all the ways in which the modern economy is kind of invisible or partially invisible in economic statistics. The second part of the book talks about why that matters to us, and then the third suggests a new framework that's designed with a modern economy in mind. And I’d kind of like to have the conversation mirror that, but I thought we could start by setting the stage.
Can you explain to us how the current system of national accounts, which is what we use to calculate GDP and all its components, how it came into being, and the nature of the economy that it was originally designed to measure?
Diane:Of course. So, about a decade ago I wrote a book called GDP: A Brief but Affectionate History, as you said. And one of the insights I got from that was that we've thought about the economy in very different ways over time. So, GDP is an idea. It isn't a natural object of any kind.
emerged starting in the late:And it was cemented into place, in the immediate post war years, through a process involving the United Nations built for economies that were, to a much greater extent than now, manufacturing economies or still, in lower income cases, agricultural economies. So, very material sets of ideas.
So, one of the points I make in the new book is that's become less and less suitable, over time, as the economic value that's being created is more and more intangible rather than material. We still use materials, of course, more than ever. But the value that's captured by the GDP metrics is intangible value.
So, the three word statistics is derived from the same root as state. So, the framework that we used is how states understand the societies that they are governing. And that's what makes them important, that's what they're used for policy. And they’re used to understand how we think things are going in our society in an aggregate sense.
Kevin:You make a very important point that the current system “adds up” and that users of economic statistics, like myself, can rely on that. But you also say that it doesn't add up when we take inflation into account. And that's very important.
Can you just explain the kind of adding up concept of national statistics? And then why, when we sort of adjust for changes in prices, that doesn't hold?
Diane:I'm really glad you raised that. I think it's a very important point that not even many economists think about enough. If you are trying to measure the economy in terms of dollars, you can do that by adding up all of the money people spend (the expenditure), adding up all the money they earn (the incomes), or adding up everything that gets produced. And there's a lot of kind of detailed adjustment needed, but in principle those are the same. So, we've got this, in effect, quadruple entry bookkeeping that goes on.
But what economists do is then divide price indices or deflators into each of those components to put them into, what we would call, real terms, which is a misnomer because these are not real things at all. They're even more conceptual than the dollar figures that we measure.
And once you apply the right price index to each component, then the things that you get out are not going to add up at all. In fact, very often it's not even obvious what kind of number you've created by using a price index to turn into this concept of real value.
The reason for doing it is that we want to understand, in some quite fundamental sense, what economic value is being created and who's getting it. But the idea of the price index comes from trying to understand what level of prices will keep a consumer's utility constant.
We've Seen that recently from:And yet in thinking about economic growth and productivity or market structures, we're using these slightly odd constructs that are often just index numbers rather than units of cars or washing machines or anything. And not enough thought is given to what on earth it is we're trying to do with these price indices.
And if you really want to understand, in some normative sense, how people's lives are going, is this the right way to go about it with this obscure technical set of index numbers that nobody really understands?
Kevin:Yeah, well, thanks for that. And I do want to talk about inflation a little bit later, but I have to say, when I read your section on that, the more I read, the more I thought, do we even really… Is there even really a concept of inflation? I mean, there are so many different ways that you can measure it.
And you make the case that different people are going to have different inflation rates depending on their income or their age because they buy different stuff and the prices of that stuff changes. And even they buy… You and I might even have the same “consumption basket”. We might, at a high level, buy the same things, but one of us might buy a lower quality product and one of us might buy a higher quality product. And so, as you said, it is almost inherently a political decision, when we choose a particular inflation index to measure across the entire economy.
Diane:There are really deep problems. So, there's an assumption, in constructing the price index, that all of the goods that you put in the price index substitute for each other. So, if the price of your food goes up, but you're getting TikTok for free, and they might cancel out in some way, but of course, you can't eat your TikTok videos.
Kevin:Although I’m sure some people will have tried. So, let's, okay, going back to the issue of GDP and some of the problems with it. I mean, you said that it was developed in a world where physical capital dominated a material world of industrial production and agriculture. And one of the sections of the book is literally called dematerialization. I know this is an area that you've written a lot about.
So, I thought maybe we could start with that in terms of some of the problems with GDP in the kind of economy that we're operating in now. And I thought we could use one of the examples in your book of Rolls-Royce, since I think that's a salient example and I know you've spent some time with them.
So, you know, Rolls-Royce is a company that makes sophisticated turbines, but you say that actually most of their profit, two thirds of their profit, comes after the sale of the turbine has been made. And I was wondering if you could just explain to the listeners how that works and then why that's an issue for the statistics and for GDP.
Diane:I've been to visit their factory in Derby in the Midlands, here in England, and it's a fantastic site. It's huge. They have all these impressive wind tunnels and the things that you would expect you need to construct turbine engines. And in one corner of the site, there's a hut with rows of people inside sitting at their screens, just like any other office in the world. And that is the driver of Rolls-Royce's revenues and profits, because they sell services around the engines.
If you operate an aircraft, you might buy a plane with Rolls-Royce engines. And you'll buy the services to monitor them in real time so you can be tracked, and problems can be spotted immediately and sorted out really quickly.
And so, there's a service relationship whereby the airlines can rely on the engine maker, who knows, in much greater detail, how to maintain and operate the engine safely, and it takes away the hassle of having to have your own maintenance for engines if you run the airline. So, it's a positive sum deal.
It's called servitization, which is a rather unlovely word for this process. But there are quite a number of what you would think of as manufacturing companies, now, that are making a lot of their revenues from services of different kinds. And you see it in the everyday economy as well.
Often, you'll see people advertising solutions. Office furniture solutions means they'll sell you a chair and desk, but they'll also maintain it, and replace it when it gets broken. And so, these sorts of relationships between the manufacturer and the customer are occurring more and more.
So, it matters in a number of ways. One is that we think of the declined manufacturing as being a significant problem in economies like the US and the UK, and in some ways it certainly is because of a loss of engineering expertise that goes with having outsourced all of your manufacturing overseas.
But the figures probably overstate the extent to which manufacturing has declined because of things like these service activities taking up a larger share of revenues and profits. And, you know, there's been a lot of outsourcing in manufacturing.
There are other forms of regeoning of production patterns away from the conventional. The manufacturer designs and makes things, and then the wholesaler and retailer sells them, and then somebody else maintains them. So, contracting out has become a really familiar part now of the economic landscape. And that means that companies like Apple or Nike don't manufacture. So, we might think of them as manufacturers, but they're not.
Different countries would classify those in different ways in their statistical system. So, if you want to compare manufacturing sectors across countries, you would really need to go into the detail to understand, well, where did they put this company? Which sector did they put it in?
And then, of course, we might get on to the question of what does this imply about supply chains and important export figures? Because depending on whether or not the ownership of the components that go into a finished product changes or not, they get counted as imports and exports, or they just get counted as intra company transfers.
So, interpreting the production structures, because they shifted in ways that don't map onto the old categories that we have, it's become really difficult to get a really good handle on what actually is the production capacity of a national economy? Where are the profits and wages being generated from, and what actually is happening to the trade balance?
Kevin:So, is this an issue just with Rolls-Royce? How are they then classified? Are they classified as a manufacturer? Are they classified as a service company? Are their activities kind of somehow split between those sectors?
Diane:For that particular company, I don't know, because obviously company data is confidential. But the principle is usually that you ask a company to identify itself, to identify its major sector of activity, and so they might choose different categorizations for themselves.
Kevin:I see, yeah. So, is this a question, you know, of classification rather than scale? In other words, is this an issue, this particular issue (we'll talk about other ones), is this like, hey, we're still measuring the aggregate size of the economy correctly, but we're not measuring kind of where it's coming from? Or are there both issues happening here?
Diane:So, just as any accountant will tell you to look at a company's cash flow, I think if you look at the dollar amounts, we've got a pretty good handle on what that is. It's when you want to understand what's happening at the level of particular industries or particular companies and types of activity. There, I think, we really don't have a good handle on what's been going on. And part of it is about digitalization and the way that's changing where value is added and how activities get categorized.
One obvious example is all the free services that we have on our smartphones now, all those free search and email and so on. They’re incredibly valuable to people. There's clearly economic value being created by them. But because they have a zero price, it's not obvious how to put those into the quadruple entry bookkeeping system.
You can count the wages of people who work for those companies. Maybe you can trace the profits, although that's a bit complicated because of the way companies move their profits around. But how do you count that in the headline GDP figures when there's no price to add in?
Kevin:Yeah, now since you've brought it up, that's another section of your book. Kind of all the free services we get. And maybe we could, since you brought it up, we could talk about that a little bit more right now.
Things like Gmail that everyone uses or open-source software. How do those things pose a problem for our measurement of GDP and economic activity?
Diane:The problem at heart is that they're valuable things and we don't know how to count them because they've got a zero attached to them. And they're also substituting for things that people use to pay for. Open-source software, which many economists would now use to do our work.
R or Python replaces the paid for proprietary software that everybody used before. People will spend their dollars on something else.
So, the dollar figure for GDP might not be much affected, but there are obviously things that make it complicated to understand what's the productivity of the software producing sector? Is it going up or down? Do we want to count those free activities in it or not?
And it would be interesting just to know what is the value of all of the unpaid open-source effort that people are putting into the economy. And it's everything from software to both consumer software and the kind of software that underpins a lot of the Internet.
But also, all of the free entertainment we get now because people are creating fantastic content that they're putting online. A lot of what's called user innovation or things like creating new medical devices or sports devices, which might gain a commercial market eventually, but when they start, they're a niche thing and enthusiasts or people who need medical attention share them online freely. This is valuable stuff. We might want to know what's going on.
We might even want to shape policies to encourage some of these activities, but we've got no way of knowing how much or what exactly is being done.
Kevin:Like this podcast, right. It increases everyone's wellbeing. But it's free.
Diane:Absolutely.
Kevin:One thing I thought about in the “free section” was that we are of course paying for things like Gmail because we're handing over our data. And as you say, you know, the most valuable companies in the world are “giving away” products for free. So obviously, there's value and we're exchanging something. How does that exchange of data… Presumably that also doesn't get reflected in GDP.
Diane:No, that's right. I don't think there are any good figures on how much data is being used or what's going in and out of data centers over the telecommunications networks. It's obviously increasing a lot. So, it is creating value. What isn't clear to me is the extent to which that is the result of market power.
And so, if you've got an advertising funded service and there are two companies, Google and Meta in UK markets, they dominate online advertising and capture most of that revenue. That's what our data is enabling. They're selling Google app services around insights into what people are doing online.
But data is what an economist would naturally see as a public good. It's intangible, it can be freely shared without being depleted. And if there were not the kinds of legal and technical protections around data use, then it might not have a price at all. Once it's out there, it's out there. It might be free, so we'd still have privacy concerns and so on.
But thinking about it just in pure economic terms, it's not clear where that value comes from. To what extent is that market power? I think it's not wholly that because the services that they provide are useful.
If you think advertising products to people who are interested in them is a useful thing, then that's also got economic value. We consumers get our share of the value through the services that we really do rate highly.
So, there's a kind of complicated assessment there about if your aim is to understand progress and what's going to be good for people, over time, in the economy, that's just quite complicated to understand.
Kevin:Let's go back to when we were talking about the dematerialization. One thing I wanted to ask you about there was, we talked about Rolls-Royce, and there kind of making money from, you know, not just from selling engines but from servicing them over time. There's another issue that you brought up which seems to me going that's going to be extraordinarily important, which is cloud computing, which is literally a completely or almost completely dematerialized product.
I mean, what are the measurement issues that cloud computing presents in terms of, you know, not just the aggregate GDP, but also kind of the trade balance.
Diane:So, the services being sold are software and things like storage. So, a whole range of products offered by the cloud providers. There are not official statistics on the cloud sector.
The data centers are privately owned, some of them by the big tech companies, some of them by others. So, I would guess that national security agencies know where all those data centers are and where the cables are going into and out of them.
But they're not economic statistics. So, we don't know that. We don't know about volumes. A lot of countries have data localization laws that require all data generated in their boundaries to be stored within those boundaries. And I think the tech companies largely abide by that. But it's not possible to monitor, really, what's going on there.
It's really complicated to understand what prices are being charged, partly because the product range changes all the time and it's very complex, and partly because that data is not given to statistical agencies constructing price indices. So, on the one hand, we know that a lot of governments are switching to using cloud services.
They don't buy their own servers and hire their own people anymore. That in itself, at least for a while, is going to reduce GDP growth, because buying your servers gets counted as investment, which adds to GDP. Paying a cloud service gets counted as an intermediate expenditure, which deducts from GDP. So, there's a kind of funny statistical artifact going on there.
But also, I think, particularly at times like these, where there's growing concern about questions of geopolitics and market power, just a real lack of regular statistics on what's going on with the sector. There are some competition inquiries, there's one going on in the UK at the moment into the cloud sector. And that's a means for the authorities to get some insight into the kinds of statistics I've just been talking about. But that won't deliver us the kind of regular price index for cloud services.
So, I've constructed that with a colleague. We did it by web scraping Amazon Web Services, which is the market leader. And that's being used by central banks in the UK and European Central Bank. But that's not the same as the kind of experts at the official statistics agencies being able to do that.
Kevin:Let's talk a little bit about another area which you call disintermediation. And this seems, again, this really resonated with me. So, I guess what you're saying is that economic statistics, they kind of envisioned an economy where there's this boundary between what you do for work and the activities you do for yourself.
And your point has been that there's this kind of transformation in these activities, so that this boundary is pretty blurred now or maybe even nonexistent in some cases. And that means that the measurement of the economy isn't accurate. So, could you kind of explain that idea to people in some detail?
Diane:Sure. So, we refer to this as the production boundary, and things that are transacted for money go on the GDP side of the boundary, and things that don't involve monetary transactions go on the household side of that boundary. And there has always been contention about not measuring some of the things on the household side of the boundary.
tally valuable. And since the:So, there's that background level of concern about what goes on what side of the boundary. Even on the monetary side of the boundary, we put some things that don't really have market prices.
And the big example is we put what's called an imputation for the rents that you would pay yourself if you didn't own your own home. So, if you're an owner occupier, you're not paying rent. The statisticians estimate how much rent you would pay, and they put that on GDP.
The idea being that shifts between owner occupation and rental shouldn't change GDP. But that kind of artifact of shifts across the boundary applies to other things as well.
the paid economy through the:Now the digital technologies are causing a lot of shifts across these boundaries. And you can think of examples like doing more of your banking online or your travel agency online. There are still obviously activities in the market, but some of that you're now doing for yourself.
We talked earlier about the example of rather than buying newspapers, you'll be looking at some of the free services online. So, a lot of these shifts have started to happen and it's probably, to some extent, reducing the productivity as measured in the monetary economy - in the monetary side of the economy.
Kevin:How does that work?
Diane: have prices attached. Back in:And so, people stopped going to the barber to get their shave, they bought a safety razor and shaved at home. Eventually barbers figured out how to offer other services instead.
But at least for that transition period, they would have had less revenues, less growth, less productivity, less measured productivity. And he hypothesized this was quite a big part of the productivity patterns.
Another example that I've been thinking about is the way that we shop for our groceries has changed. And back in the ‘50s or’ 60s you'd go to the greengrocer who would have all the goods behind the counter, and you'd say, could I have half a pound of butter please? And it'd be measured out for you and handed over. So, not much capital, a lot of labor involved in that.
Then we've got supermarkets, they used to have people who would bag your groceries for you, so you picked things off the shelves yourself, but all the rest of the work was done by paid labor. Now we have these automatic teller machines which have a lot of capital and software, but rather than a paid employee scanning and bagging the groceries, you're doing all that yourself. So, this is a shift of labor involved in shopping for groceries.
Going steadily from paid labor and no capital, to some paid labor and more capital, to a lot of capital and no paid labor, which you are doing for yourself. What's this going to do to the measured productivity of the retail sector over time?
I think at the moment it'll be increasing the productivity of the supermarkets because they've got roughly the same kind of sales, but they're paying fewer wages, but the same work is being done. So how should we be thinking about that?
Kevin:Yeah, no, I'm glad you brought that up because I think about that a lot and there's kind of a broader issue which is, I don't know, I always have to check myself, like how much of what I'm saying is insightful and how much is just being a grumpy old man. But there's this, you know, I feel like so much of the customer service activities of companies are essentially now outsourced to the customer.
And as you say, that's it's sort of like that job is still being done, but now it's being done by you and I trying to figure out how to fix something if it goes broke, as opposed to being able to call up the customer service and say, hey, you know, can you help me with this?
Diane:Well, it's not just you being grumpy. It's been labeled a time tax and engaging with a lot of public services and private services. You can spend a lot of time talking to a bot or trying to get through to a human being on the telephone to sort out your problem. And there are automatic menus.
So, you end up having to spend a lot of your time on this activity and not even necessarily to get a good outcome, but as you say, to fix a problem that's gone wrong because of all the automation that goes on. But this will get worse, I think, because companies are using bots more and more for customer service because of the advances in AI.
And so how are we going to think about it or measure it when my agent, my agentic bot is talking to the bank's agentic bot? Is that real economic activity at all? What value is that creating?
Kevin:Yeah, no, that's right. And I mean, I know this is quite an important concept for you, right? And what you would like to see happen going forward, I mean, you'd like to see time (I believe, if I'm right) as a kind of a base unit of measurement. Because that's sort of a resource that is finite and we all only have 24 hours in the day.
How would you like to see time incorporated in kind of a reformed set or an expanded set of economic statistics?
Diane:So, I've started to think about this both from the perspective of us as consumers and from the perspective of production and productivity. So, as we were just saying, we spend our 24 hours, you can't carry them over, you've got to allocate them to different activities.
You need to spend time to work, but you also need to spend time to consume, which isn't usually thought about. And you need to spend time as well as money to engage in leisure activities. So maybe we should think about how much well being do people get out of their activities over that 24 hours.
A lot of countries have time use statistics for consumer and household activities, mainly used to get an insight into things like what's the value of caring activities in the home. But you could think about doing it more regularly and in a more detailed way to understand these allocations and to think about how to make, you know, each of them more enjoyable or at least less unpleasant for people. And then that would bring the time tax right into the frame. And we might start thinking about, do we really want companies to be setting up their business models in this way?
From the production perspective, you can look at this in two ways. A lot of productivity improvement over time has been about doing things faster. So, we focus on the shiny gadgets, but actually it's the fact that the steamship can cross the ocean much faster than the sailing ship, or that manufacturing a car since the introduction of Just-In-Time systems, has become much faster than it used to be in the ‘50s and ‘60s assembly line. So, those process innovations are how technology drives productivity forward. And they're often about time saving.
But there are also, in a service economy, lots of activities where you want a lot of time spent, but it's got to be high quality time. If you're thinking about, say, a medical setting having a routine test, you want it to be done quickly, you don't want to have to wait around for it, and you want your results as fast as possible. So, productivity gains there are speeding up all of those procedures.
But if you're really ill and you're in an intensive care unit, you want to have a lot of attention from highly skilled medical staff. And so, you can think about two kinds of productivity. There's a sort of time and speed productivity, and there's a quality productivity.
And if we thought about how to divide up the economy on that basis, we get a different kind of perspective from conventional ways of manufacturing versus services or industrial sectors.
Kevin:What would it require to produce those types of statistics? Are we talking about just expanded types of surveys, or are there other ways that you can capture?
And the reason I ask that is that, you know, we did have Julia Lane on the show in, in January, and I know that you quoted some of her research in your book… She does a, you know, very good job of explaining the challenges with the survey method of collecting data.
And then she was talking more about collecting data on, you know, other types of economic activities. But it does raise a sort of degree of skepticism in terms of, you know, the accuracy of surveys, at least as they're done now.
Diane:Her research is fantastic, and she's absolutely right about the way that surveys are collapsing at the moment. So, we have to think about new methods to do this. I think the technologies may offer some ways to think about it. You know, they might be considered to be surveillance technologies, but you can often map what people are doing through their outlook diaries online, for example.
We do have a pilot time use survey for public sector workers where they actually recorded how much time they thought they spent in useless meetings and how much of their activities were productive. So, it's an open question. I don't know the answer and I'm thinking at the moment about how to monitor that in the emerging AI economy.
If it's the case that generative AI is going to transform the economy and productivity, what should we be looking for? How should we looking about those kinds of processes at work to change?
Kevin:You talked about, I think in the introduction of the book, just how kind of new technologies and new innovations which clearly would improve people's standard of living but would have kind of a counterintuitive impact on GDP. The example you gave was new treatments for macular degeneration. Switching from a drug that costs $2,000 a month to one that costs $55 a month.
That reduces spending, so potentially reduces GDP, but at the same time clearly improves wellbeing. Can you just explain that idea in detail how these kind of technological innovations can, I guess, mess up or interfere with our ability to kind of measure GDP accurately?
Diane:It's about ideas, really. So, there are other medical examples. You might think about the realization that aspirin can be used to avert cardiovascular problems rather than just being a painkiller. So, there are plenty of medical examples of new ideas. Here are really everyday examples as well.
I don't know if you ever get sucked into the Instagram vortex of videos, but for some reason I get served quite a lot of videos about home hacks. And it's things like you can turn your milk carton into a trowel to use in the garden. Those are great ideas, but they're not adding anything to the economy. If anything, it's reducing a measure of GDP because I'm not buying the trowel to use in the garden.
So, it's really about what has driven human progress for at least a quarter of a millennium. And it's using ideas. So, productivity is all about that you've got a certain amount of resources. How effectively can you use them to deliver things that people value and make it feel like life is getting better. That's what it's fundamentally about.
Kevin:That's a good, I think, segue to what your new framework that you'd like to see. Because it really is, I guess, the base of it is getting a much broader understanding of what that resource base of the economy is. And so, you have this concept that you call ‘six capitals’, which I know you've done some… that's kind of your research framework.
Can you explain that to us, the six capitals? How you've chosen the categories and why they're important? And, I guess, maybe which of those capitals we're currently measuring and which ones were not.
Diane:So, a simple way to think about, well, at least the way I think about what we might measure. We've got the system of national accounts, GDP. You can think of that as being like a company profit and loss account, and that involves various manipulations. We talked about time. You can think of that as a kind of cash flow that monitors things day to day. And then the missing bit is a balance sheet.
And so, the idea of the six capitals, which in literature is called comprehensive wealth, sometimes inclusive wealth, is that you're looking at all of the assets that an economy needs to continue producing GDP growth in future. So, in that very broad sense, it's about can you continue to grow?
And so, think about what we need. And people would think about financial capital, I guess, but certainly productive capital - the buildings and machinery that are used to deliver goods and services. Also, the infrastructure of the economy, which isn't particularly well measured anywhere, but without it, there's no economy.
Natural capital, we get a lot of services, from pollination on farms, to cooling by trees in cities, to clean air that stops people getting asthma because the pollution is so bad. Human capital, which is the term for people. And what skills do they have, but also what health do they have that affects their ability to work productively and be satisfied with their lives?
And then sort of more the fuzzier bits. It's the ideas, it's the knowledge capital. What's that knowledge, that base that we have that allows us to carry on doing things? That does seem to be able to erode. And I think we're seeing some examples of that at the moment. And then how do we organize that all collectively – so, social or institutional capital?
Daron Acemoglu and his colleagues won the economics Nobel Prize for focusing on the importance of institutions for economic growth. So, we know that they matter. Can you think about how to measure what constitutes a good set of institutions for transactions to take place and contracts to be observed and people to trust each other? So that's the sort of balance sheet. Waterfront. What do we measure?
Well, the bit we measured best, I suppose, is physical capital, but even then it's pretty complicated because you're thinking about combining the equipment a hairdresser has in their salon with the machine tools in a standard manufacturing plant, with the really advanced stuff needed to make silicon chips. But that's probably the one that we measure best.
A lot of progress has been made in measuring the natural resources that we use. And the US started collecting those statistics a couple of years ago. We've done it in the UK for 10 years or so, and there's a set of standards for doing so across countries.
Human capital people typically measure as either what skills have people gained or what wages they earn that reflect the assumptions about their skills. It doesn't usually measure health. I think, because of aging societies, it's becoming more important to understand the health component of human capital. And then the others, we don't measure all that well at all.
And infrastructure, as I said, seems pretty basic, but we don't measure it in terms that understand how well maintained it's been. And of course, bridges can collapse overnight, as they sometimes do.
Kevin:I want to ask a question about natural capital. As I was thinking about your expanded framework, that one, I guess, seemed the easiest for me to think about because I think it's fairly straightforward to think about - a natural asset producing services that's input to economic growth.
So, is what you're imagining a system whereby you would have a kind of a balance sheet of natural capital, I don't know, today, and then you would kind of adjust that as the natural capital gets used or depleted? I mean, I guess I was thinking about something like a mineral deposit, copper or lithium, something like that, that we would need for renewable energy.
Are you imagining that if that's extracted, that depletes natural capital? And then also there’s got to be an interaction with technology, right? Because maybe the value of that deposit is a function of our ability to extract it, but the extracting, you know, technique might then have environmental consequences, presumably, which also affects the balance. So, am I conceptualizing that correctly?
Diane:Yes, well, you're pointing to some of the challenges and trying to think about how would you measure the whole of the economy's natural capital?
And if you come at this from a national accounting background, you think, well, I'd need to know the quantity and I need to know what price to apply to that. And that gives me my balance sheet figure. So, I will estimate the amount of reserves of whatever, lithium, or whatever it is. And what the national accountants do is they then apply a market price or something close to a market price to that.
If you're thinking about it from the point of view of broader societal needs, you might want to think about the kinds of technological substitutions that can occur. You're going to think about it more as an asset in a portfolio of things available to the economy. So, there are two different ways of thinking about it. The literature is on the simple, we'll just look at the quantities and find some kind of price.
To understand what does this imply for future capabilities to produce and grow? You need to think about it in a different way. And that's not happened yet. That's work in progress, I would say.
I do think it's becoming important because in the geopolitical environment now, or given the shocks of the past 10, 20 years in the economy, and the impact of bottlenecks in supply chains (thinking more about as a nation), what are your capabilities? What are the assets that you have to continue to produce? This becomes much more important than it has been. So, I think that's a really interesting agenda. There's not a lot of research around thinking about it like that, but fundamentally important.
The farming sector in the Midwest depends critically on the ecosystems that deliver the bugs that keep the soil healthy. And nobody's looking, well, environmentalists are looking at it. Nobody in economics or national statistics is looking at that. But if that reached a tipping point, it would destroy the productivity of the sector really quickly.
Kevin:With human capital, you quote, I guess the World Bank has said that something like 60% of total wealth is human capital, I think if I got that right. And then you say, well, that's not in the national statistics at all.
And you also talk about, you know, how spending on education is considered consumption as opposed to investment. So, it's not building capital. Can you talk a little bit about, you know, if we wanted to value human capital, how we would go about doing that?
Diane:The typical way of doing it is to look at the different levels of educational skills and attainment in groups of the workforce and to (using a somewhat complicated formula) basically apply the wage that people get for those different types of skilled activities and add it up that way. That's obviously quite a narrow way of thinking about human capital. As I mentioned, it doesn't include health, it doesn't include particularly people's well being and how motivated they feel.
So, you could think about it in a much more expansive way. So, what's there is quite a narrow measure, but that 60% is also 60% of quite an incomplete measure of this broad sense of national wealth. So, I think that we're slightly at sea in the fog with those kinds of figures.
But if ideas (and this is one of the questions about AI), if you think ideas drive productivity and progress over the long term, which has been the case since the Industrial revolution. Ideas are attached to people, and well educated people tend to have the kind of ideas that produce new technologies that continue driving economic growth.
Now maybe AI for science will change all that and the machines will start doing all that innovation and so the people can stop thinking, and the human capital will get substituted by agentic AI capital. I'm not sure I believe that.
Kevin:So, if you do say, and I think we get the sense (we're just listening to it) that it's a challenging agenda that you're putting forward. I mean, what is the current state of play on some of these things? And if people listening are interested in kind of following up, what are some of the places where they can kind of take a look at, I don't know, say, where we are with natural resource accounting or human capital accounting? I mean, is there public data that you think at least useful in some sense?
Diane:Yes. So, all the industrialized economies have their own national statistics agencies that put out lots of data and interpretation. The international agencies like the World Bank or the OECD are good places to go for information. We're in an interesting time because the system of national accounts gets revised every 10 years or so. And we've just had a revision earlier this year approved by the United Nations. So, it's become the official set of standards.
But almost immediately, the Secretary General of the UN announced a new commission to look at how to do better economic statistics. Because there is, I think, a deep sense among many populations that the GDP growth figures don't reflect their experience. GDP growth has been going up. A lot of people feel their lives have not been getting better. So, the popular demand, if you like, for a different approach to measurement is definitely there.
But it's a bit like a technical standard. You know, if you've got two pin plugs and you want to switch people away from two pin to something else, you've got to know what the something else is. And it's got to happen at the same time. So, you need a consensus.
And I don't think we're anywhere near having a consensus among economists and statisticians on what is the right way to do this? The things I talk about in my book have pretty solid economic theory underpinning them. So, my hope is that the economists will go, that might be a good way to go. Let's explore that and let's think about developing standards around that.
But I might be wrong and somebody else might come up with something better.
Kevin:When you personally try to gauge where the economy is strong, weak, growing or not, what statistics and data sources do you still value given the fact that as you said that so much of the economy is invisible?
Diane:Well, you have to use a mix. The official statistics are suffering, as you mentioned, because survey response rates are going down. There's a lot of turmoil in the US statistical system at the moment because of cuts and proposals to merge the agencies. But there have been budget cuts everywhere and we're going to have to think about new ways of doing it.
So, my team used a lot of techniques like web scraping, or trying to think about accessing mobile phone data, or online trends data, and so on. So, a lot of experimentation is going on with different ways of doing things. And I think we're just in quite a confused phase.
ve a facsimile edition of the:I think we're in one of those periods driven by big technological transformations in our economy and really big social and political changes as well. So, it'll keep me busy for the rest of my career.
Kevin:Well, that's good. You'll be productive.
But it does mean that, you know, for a lot of people, especially those in the markets, but just in general that we're kind of operating in a fog and the fog isn't going to clear anytime soon. But it also means that we should take a lot of interest in this sort of research because it will hopefully, eventually, give us a much better system for understanding where we're at.
So, I think that's a good place to leave it today. Diane, I just wanted to say thanks for writing the book and in particular thanks for taking your time. I hope it wasn't too taxing. I hope it wasn't a big time tax to share your ideas with us. We really appreciate it.
Diane:On the contrary, it was a real pleasure. Thanks so much.
Kevin:Okay. Well, the book is called The Measure of Progress.
Please make sure to go and get a copy and to follow Diane's work, because I think you can tell not only are these very important ideas, but they're also not being discussed enough on mainstream media. So, for all of us here at Top Traders Unplugged, thanks for listening and we'll see you next time.
Ending:Thanks for listening to Top Traders Unplugged. If you feel you learned something of value from today's episode, the best way to stay updated is to go on over to iTunes and subscribe to the show so that you'll be sure to get all the new episodes as they're released. We have some amazing guests lined up for you, and to ensure our show continues to grow, please leave us an honest rating and review in iTunes. It only takes a minute, and it's the best way to show us you love the podcast. We'll see you next time on Top Traders Unplugged.
