Diane Coyle. Diane is founder of Enlightenment Economics , and Bennett Professor of Public Policy at the University of Cambridge. She was recently appointed Commander of the Order of the British Empire (CBE) for "services to Economics and the Public Understanding of Economics". She is also the author of the 2014 book -- GDP A Brief but Affectionate History.
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Click to display or to hide the script from Episode 58. John Bailer: While cholesterol levels may lead to concern about your physical health, how do we measure the health of a nation's economy? Our focus today on Stats and Stories is the measurement and assessment of national economy's health. Stats and Stories is a partnership between Miami University's Departments of Statistics and Media, Journalism and Film as well as the American Statistical Association. I'm John Bailer from the Department of Statistics, and I'm joined on the panel today by Richard Campbell, chair of the department of Media, Journalism and Film. Our guest today is Diane Coyle. Diane is the founder of Enlightenment Economics and Bennett Professor of Public Policy at the University of Cambridge. She was recently appointed Commander of the Order of the British Empire C.B.E. for services to economics and the public understanding of economics. She is also the author of the 2014 book G.D.P. a brief but affectionate history. Diane, welcome.
Diane Coyle : Hello.
Bailer : Hello! Diane, I love the title of your book. Can you give a brief definition of G.D.P. and describe why you have an affection for it?
Coyle : G.D.P. stands for gross domestic product and it is really just what we would say it's the sum of all the production in the domestic economy. So it's the sum of all the transactions that take place in the economy. It's a measure of economic activity and if you look at it over long periods of time it tells you, really the story about progress in the market economy, the almost imperceptible increase through the Middle Ages and the Renaissance in the sixteenth, seventeenth and eighteenth centuries and then that acceleration, that takeoff, that saw the dawn of capitalism and the kind of exponential growth that we've grown used to in modern economies. So G.D.P. in that sense, is telling us the story of our economic history.
Bailer : So when was it first used?
Coyle : Well as we use it now, and understand it now, it was a creature of the Great Depression and the Second World War. Simon Kuznets whom a lot of people would have heard of and some people Colin Clark here in the United Kingdom, were working in the 1930s on trying to measure the whole economy. The Great Depression meant that was the first time when any governments, democratically elected governments felt the need to understand what was happening in the economy as a whole rather than in individual industries or to the banking sector for instance. So that was when it started but it crystallized into today's G.D.P. during the Second World War when the allies, the U.S. and the U.K. John Maynard Keynes and the British side very famous economist, devised the concept of G.D.P. and its components and the way that you can add it up either as all the incomes in the economy or the spending in the economy or the production in the economy and it's thought to have been one of the contributing factors to helping the allies win the Second World War because they had a better handle than their opponents on just how much capacity there was available to produce the war effort and what sacrifices consumers are going to have to make as a result.
Richard Campbell : Very interesting. You make an argument that G.D.P. was a good measure of prosperity in the twentieth century but is not such a good measure in the twenty first century. Can you talk a little bit about what's happened and why we need to think about other components to G.D.P.?
Coyle : Well the name gives a clue - it is gross domestic product. But most of our economies now don't consist of material products or goods. They consist of services. When a lot of, so much more of production consisted of the kinds of items that rolled off the mass production lines, automobiles or washing machines and so on, then it made sense to think about adding up products in that way. But when you're talking about services, they become much more varied, the quality is much harder to get a handle on. It's even quite hard to work out prices for services because of that issue of quality adjustment and so the whole issue, the whole issue of defining the economy as a whole becomes very much more complicated. We have a much greater variety in the economy, we have more intangible goods and services and that makes it just harder to define an aggregate and measure it in the way we have been doing, because it's not just you are adding up apples and pears, you are adding up apples and pears and cars and refrigerators and accountancy and law and there are multiple varieties of all of these and the information that you get from how we still define and measure G.D.P. is just becoming increasingly less useful I think as the economy changes.
Campbell : So you talk about, in one of your writings, you talk about how household work is not measured in G.D.P. and how would you go about doing that? Accounting for all this work that gets done that doesn't fall under the old definition of G.D.P.?
Coyle : That's right, there was quite a debate at the dawn of G.D.P. in the nineteen fifties, about whether or not work done in the home should be included in the aggregate measure or not. And the conclusion was, not. In theory, if you produce goods at home, if you produce or grow fruit in your garden and take it to market, then that ought to be included, although of course it's harder to measure and the reason for that is that G.D.P. is an international standard definition that was meant to apply to much poorer countries as well, where there's a lot more that kind of informal production, people selling things they make at home in the marketplace. So the goods got included but the services, the housework and childcare and doing your own garden and so on, did not and that debate has always been one of the criticisms that people, feminist scholars obviously levied against G.D.P. obviously over the decade in between. And I think it's coming into play again because what seems to be a sharp boundary between work in the market and work at home is becoming blurred. You know, actually it was never as clear as it seemed because through the years and the second half of the twentieth century, a lot more women went out to work. And that meant that they were instead of sewing their own clothes and making all the food from scratch, buying readymade clothes readymade meals. So there was already a shift towards the market that in a sense flattered our G.D.P. figures over that period.
Campbell : Um hmm.
Coyle : But what's happening now with new technologies is that things that people used to buy in the market are increasingly being done at home. One example is all those intermediary activities like going to travel agent or doing your banking, where people don't go to the high street stores anymore, they do that on their home computer. There's still an intermediary, an online company, but the prices are lower, you're putting in a bit of time yourself but saving a lot of time, you get more choice and many more people are providing their own services now in that way. The famous or infamous sharing economy is blurring it as well because people are using some of their household assets like a spare room to make some money and earn some money and although in principle that ought to be captured at one of the measures of G.D.P. it's actually much harder to collect the statistics and then finally people are producing lots of free digital goods so they make available online, and some of those are pretty obvious it's an entertainment through free YouTube videos or podcasts that people put online that people can freely enjoy, Wikipedia contributions, lots of online education and there are some very nice examples. One is that children who need prosthetic limbs grow out of them very quickly and they're really expensive or they were really expensive but people have now put free designs online so that you can then download a design in the right size for the child and 3D print it at much lower cost than older prosthetics and that's a free idea that people designed free and made available and so although they are not in a measure the market economy they're clearly contributing things that we can value. So the question is, how could you measure all of this? And I think the answer is probably the same way we measure lots of economic statistics anyway which is using surveys and a lot of the conventional statistics are captured by sending surveys out to companies or individuals. We could do the same thing to capture what work people are doing in their home.
Bailer : You're listening to stats and stories and today we're discussing how to measure a national economy in a world where we enjoy free internet resources, globally produced goods and are concerned about the lifecycle benefits and cost of products. Our guest on today's episode is Diane Coyle Bennett Professor of Public Policy at the University of Cambridge. Diane, how difficult is it to modify an existing measure of economic performance when it's familiar and has been used for so many years?
Coyle : The definition G.D.P. has been modified from time to time over the course of the decades since the Second World War when it was invented. There are a number of big reforms that take fifteen or twenty years of discussions among economists and statisticians and a committee that sits under the auspices of the United Nations ultimately and it's quite a big deal but it has happened. The thing about those changes is that they tend to be incremental changes. The fundamental concepts haven't changed that much. The biggest development really has been the development of what national accountants call "satellite accounts" and that includes, for example, household satellite where they measure some of the domestic activities that we were talking about a little while ago. They have an environmental satellite where they try to capture a lot of the environmental externalities such as pollution or changes in asset values as resources get depleted, for instance and they go into the environmental satellite. The trouble I think is that the processes put all the interesting things into the satellite camps and then what people pay attention to, the only thing that gets the attention is really that headline number of G.D.P. growth. And it's not even that we look at G.D.P. growth per capita, which is a better indicator if you're trying to get at economic progress or economic wellbeing in some sense. It is simply that change in the aggregate G.D.P. figure through quarter to quarter that tends to get all the attention.
Campbell : So if you were in charge of everything, what would you do, what would you replace…
(Voices overlap)
(Laughter)
Campbell : What would you replace G.D.P. with or what would you call it for the twenty first century? I know you also know that G.D.P. is…doesn't account for inequality, for example. So how could we measure, how could we measure this stuff better today?
Coyle : Well this is a big question and you know, as you just alluded to, there are some longstanding criticisms that it doesn't take into account inequalities. One that it doesn't take account of damage to the environment caused by growth is another, that it ignores all the work in the home as we've been discussing and so you could take the view that what we need to stick with the G.D.P. framework but just improve it to take account of these things, and carry on with this process of incremental improvement and that would be better, I think. You know, the figures that we have now would give us a lot more insight but it's a very top down measure and as the name suggests it's about what happens in a nation with a national borders in a world that's very globalized.
Campbell : Right.
Coyle : And it's extremely complicated to try and pick what's happening in terms of production when the supply chains cross many different country boundaries or even actually what the trade figures really are when you take account of all the components that are imported into China to assemble the iPhone there as it's re-exported for example. So that's very complicated and so I'm playing with the idea now of a completely different kind of framework which is bottom up and it says what economic assets did individuals or places have access to, and how can you measure economic progress that way. And that would include the physical and financial capital that they have access to, which we think about conventionally, it would include natural capital, the natural resources, it would include intangible capital, ideas and intellectual property and human capital, what skills and what's the quality of health of workers and if you think about it in those ways that kind of automatically gives you a distributional angle on it because you're asking people have certain wants, there are certain things they want to do economically in their lives. What capabilities do these assets get them to get on and do it.
Bailer : It seems like there's a real challenge that's embedded in doing that. I mean there are inputs to these types of calculations and it seems like the inputs will vary in terms of the uncertainty that are associated with them. When this was first proposed, I mean, as you mentioned, it goes back to the thirties and forties, most of the manufacturing, most of the production was being done, pretty much internal to a country you know and this, it seems like this is, you know, all bets are off right now in terms of the way the world works so I love the idea of expanding this. I mean you talk about you know the complexity in these systems and in trying to measure productivity inside with these complex systems and also then trying to quantify some of the sustainability. But when you think about some of these improved measures you're going to have an improved measure that reflects some inputs that are probably better known than other inputs. How…what's the role of uncertainty in thinking about framing a measure such as G.D.P.?
Coyle : We…there's a lot of uncertainty about it. It's an amalgam of tens of thousands of different statistics collected from different sources, there's something error in all of that anyway. There may just be as they are filling out the forms and then there are lots of processes that it goes through to combine into single indices and to adjust for seasonal variations that are predictable and then to adjust for general inflation so that you get a sense of what's happening in real terms as we call it in economics. So the uncertainty around the figures that we look at every quarter is already immense, and I don't think people have enough of a grasp of how uncertain that is. The Bank of England does a quarterly report on the economy called the Inflation report and they publish what we call fan charts and for the inflation you see a line for the inflation figures up to the present and then it fans out showing the uncertainty about the forecast. The G.D.P. chart, the uncertainty fans out at around the future but also around the present and the past just reflecting revisions in the general and uncertainty about the figures and so they're saying growth in the U.K. economy now could be anything between about zero percent and four percent which is a huge range. In terms of how quickly living standards are increasing so there's already tremendous uncertainty and I don't think uncertainty is a good argument against trying something new but it is a big task, it will involve collecting all kinds of different statistics and figuring out the methodologies for combining them again.
Campbell : So you talk about uncertainty. This is something that journalists don't understand, though report about, usually we see G.D.P. reported and it's just numbers and they're presented as if these are…this is just the way it is. They're often not explained to the general public in the same way they show the stock market going up and down without ever explaining what exactly does that mean? What are those numbers they are in for? So as someone who really understands this can you talk a little bit about what journalists can do better and maybe some mistakes they make that drive you crazy?
Coyle : Where to start!
(Laughter)
Coyle : One of the things that any journalism involving numbers, never gives you, almost never gives you, is some sense of, is this a big number or a small number.
Campbell : Yeah.
Coyle : If it is naught point two, is that big or small. When, another context we think a billion is a big number so does that kind of giving it context anyway. The sense of uncertainty that we were just talking about that there are frequent revisions and anyway standard errors around figures, if one calculate them, would be enormous and I'm not putting so much weight on tiny changes we even get in the headlines now that the quarterly figures for G.D.P. growth annualized was revised from 1.2 to 1.4 as if that's a headline story but that's just the same number really and I don't quite know how to get journalists away from too much obsessing about individual numbers when it's only a sequence of them pointing in the same direction. It will give you any information at all and just generally that seems to be a lack of I don't know what is critical thinking about numbers and it's quite widespread among journalists and I know that there are lots of courses that they can do that help them understand it and I wish more of them would take those kind of courses.
Campbell : Me too.
Bailer : You are listening to stats and stories where we discuss the statistics behind the stories and the stories behind the statistics. Today our focus is on measuring the health of national economies. I'm John Bailer from Miami University's Statistics department and I'm joined by Richard Campbell from the Media, Journalism and Film department. Our special guest today is Diana Coyle, Bennett Professor of Public Policy at the University of Cambridge. In your recent book you describe why Greece's chief statistician was charged with treason in 2013 for apparently doing nothing more than trying to accurately report the size of the country's economy. Can you give a brief summary of the situation?
Coyle : The case is still ongoing, he is still under threat of judicial action and this dates back to the Greek financial crisis and the condition that the International Monetary Fund and the Europeans put on the bail out of Greece was that the statistical agency was revamped because the figures clearly had been made up prior to that period, so the Greek government could borrow more money because these figures, these loans were always assessed against the size of the country's G.D.P.. And so Andreas Georgiou was brought in and did a really good job of sorting out the statistics and among the things that he did was sack the statistics board that had preceded him. And one of those started this set of legal proceedings against him so he is fundamentally being taken to court for producing accurate statistics, and the whole international economics community and statistics community is horrified by this. And I think it's a scandal that the Greek government and Greek legal system is pursuing him this way, somebody who's a dedicated public servant with a great international stature.
Bailer : It indeed is one that we've seen highlighted on you know, in Significance magazine we've seen the discussion still continuing and I've just recently seen some efforts to think about crowdsourcing some of the support for the defense for Georgiou.
Coyle : Yes and there's a petition of support that people can sign as well.
Bailer : It's very shocking, you know, are you familiar with other circumstances where you see this?
Coyle : I can't think of any that's parallel and it's certainly not something that you'd expect in an advanced economy that belongs to the European Union. The fundamental problem is that G.D.P. is increasingly being used for what would be called administrative purposes like measuring the ratio of debt to G.D.P. to decide how much a country's able to borrow or setting fiscal rules, you know, limiting government borrowing depending on their relation to G.D.P. And given how uncertain the concept is and the fact that those uncertainties are growing, these administrative uses are very dangerous because they do tend to distort people's behavior in ways that don't reflect an underlying economic or public policy analysis. So I would like to see some other way of anchoring what governments would be doing with fiscal policy laws rather than setting it in relation to G.D.P. and you can make the same point about monetary policy as well because many central banks set interest rates by looking at the gap between measured G.D.P. and what they think some potential output of the economy is and again those are two such fuzzy, uncertain numbers now that it does make me uneasy to think that interest rates, people's mortgage rates are being determined that way.
Campbell : So this is a much bigger sort of broader question that we ask some of our guests that are living in these times in which we have sort of very much a fact-based thinking, fact-based evidence up against what I call faith based you know where you have either faith in some spiritual realm or faith in somebody that told you something and you said because I heard it from somebody that I trust, I believe it. So this is been going on for a while now and I guess my question to you is and this is a hard one because I struggle with this one all the time, how do we do a better job of convincing people how important facts are, numbers are, evidence-based research is, in a culture that seems to want to move in a different direction, and this is such a problem in the States right now.
Coyle : This is a really difficult one as you say and there is a saying that there is so much demand among politicians and others for simple answers to complex questions that they'll get those supplied to them. Suddenly it's ever been terribly easy. And I guess I come down to thinking that essentially there are two things: one is about the conversation and carrying on the conversation. Each year I organize a festival of Economics here in the U.K. We get several thousand people buy tickets to come and hear panels, so there's an appetite for it and having experts like economists and statisticians go out and talk to people I think is really healthy. That doesn't scale up so well in person, it would be great to have a primetime television series about statistics. But you know we have to do what we can in terms of that conversation. But the other thing I think is being really honest about the limitations of the statistics, because I think many people feel that you know as I was just saying about the administrative uses of G.D.P. That the numbers can distort decisions. And take environmental example, there are lots of environmentalists who feel that it is morally wrong to put numbers on the environment in any way, and economists feel that if you don't put numbers on environment, then people don't value it. But we ought to be really honest about the limitations of the numbers that we try, you know we can try to value a particular natural resource but there are elements of it that are truly invaluable and that's got to be part of the conversation as well so I think you can build more trust in the numbers if you acknowledge the limitations honestly.
Campbell : Thank you.
Bailer : I am intrigued about the challenge of trying to monetize some of these resources and some of the values. I mean I'm thinking about you know you talked about natural resources and trying you know how do you how do we put value on this for decision. So what are some of the strategies that you see used for putting value on things like natural resources?
Coyle : This is an area where I think economists need to do some more thinking about it. One of the conventional methods is to do what's called a "willingness-to-pay survey" or willingness to accept you ask people how much would you have to be paid if you lost access to this particular area, park land? So for some natural resources you could do it that way you couldn't do that with clean air of course because. That question of it being invaluable really quickly comes into play and that's a kind of adding up problem as well. You might be able to value the loss of one particular piece of woodland but there comes a point, a tipping point, when you lose so much of the wood land area that part of the diversity is damaged and that the ability of the woodland to absorb carbon is damaged and those things hang together and you get an acceleration processes too. We don't have a very good techniques for incorporating those kinds of nonlinear changes and option values in how we approach this work. So I think we've got some work to do there.
Bailer : Well I mean, the importance of economic and official statistics, I think, is there. I mean I don't know that many people appreciate that as much as they probably should. How does someone prepare for a career such as yours?
Coyle : I did a degree as an undergrad in politics, philosophy and economics which I think has stood me in good stead over the years, and I did a Ph D. In economics and that's become, has been for a while now, a very quantitative subject we do lots of statistics in the form of econometrics statistics, applied to economics, and many economists now do a lot of applied work getting down into all the detail of different data sets, huge interest now in big data and those kinds of techniques to a new sources of data so that's a very thriving area of economics. But there are other routes and here we have a growing number of apprenticeships you can be apprenticed to the Office of National Statistics and take that route and get your training that way but I guess any quantitative undergraduate degree and graduate degree will help you get into this kind of area. Economics is a...I think it's a science that is enriched by having people from lots of different backgrounds and there's a great variety among people who engaged in the kind of work that I'm doing here.
Bailer : Just my last question for you is what do you like best about what you do?
Coyle : Oh that's the hardest question of all.
(Laughter)
Coyle : I love everything about what I do.
Bailer : How wonderful!
Coyle : I really love understanding what different sets, what different data series tell you. I love plotting the data and visualizing it and picking out the stories from it, but I also like going to talk to businesses to understand how they think about strategies and what kinds of variables they look at as they make decisions and does that mesh at all with our economic models. So I like I like the whole gamut there's a lot of variety!
Bailer : How outstanding! Well Diane, that's all the time we have for our conversation today, thank you so much for joining us.
Coyle : It's been a real pleasure talking to you, thank you.
Bailer : Indeed! Stats and stories is a partnership between Miami University's departments of statistics and media journalism and film and the American Statistical Association. Stay tuned and keep following us on Twitter or Apple podcasts. If you'd like to share your thoughts on our program, send your e-mail to statsandstories@MiamiOH.edu and be sure to listen for future editions of stats and stories when we discuss the statistics behind the stories and the stories behind the statistics.