The National Accounts is the comprehensive data set on a country’s economic performance. It gives us GDP growth estimates and a whole bunch of other important indicators. Australian Bureau of Statistics Principal Advisor Robert Ewing takes us behind the scenes at the ABS and provides some great info and insights into how the GDP figures are prepared. Learn about the huge range of economic data from households, businesses, and governments that go into the National Accounts, the roles played by algorithms and judgment, and how the numbers are crunched using the time series database FAME, short for Forecasting Analysis and Modeling Environment.
Links relevant to the conversation
Economics Explored EP153 which also considered the National Accounts
Transcript: How the Australian Bureau of Statistics prepares the National Accounts w/ Robert Ewing – EP162
N.B. This is a lightly edited version of a transcript originally created using the AI application otter.ai. It may not be 100 percent accurate, but should be pretty close. If you’d like to quote from it, please check the quoted segment in the recording.
Gene Tunny 00:01
Coming up on Economics Explored.
Robert Ewing 00:04
It’s the work of hundreds of people across the ABS once you count the people in the survey divisions, the data acquisition divisions, all the other publications such as the balance of payments, the capital expenditure, the business indicators publication, which all feed into the national accounts.
Gene Tunny 00:24
Welcome to the Economics Explored podcast, a frank and fearless exploration of important economic issues. I’m your host Gene Tunny. I’m a professional economist based in Brisbane, Australia, and I’m a former Australian Treasury official. This is episode 162 on how the national accounts are put together, my guest is Robert Yuen from the Australian Bureau of Statistics, the ABS. Rob is the principal adviser to the ABS statistical services group. In this episode, Rob takes us behind the scenes of the ABS and provide some great info and insights into how the GDP figures are prepared. While Rob and I chat about the Australian National Accounts, I hope this conversation is useful for you, wherever you’re living. statistical agencies around the world will be using similar data and procedures to the ABS as they prepare their own GDP figures. Please check out the show notes relevant links Information and for details of how you can get in touch. Please let me know what you think about either Rob or I have to say in this episode, I’d love to hear from you. Right now for my conversation with Rob Ewing on the national accounts. Thanks to my audio engineer, Josh Crotts for his assistance in producing this episode. I hope you enjoy it. Robert Ewing from the Australian Bureau of Statistics, good to have you on the programme.
Robert Ewing 01:42
Very happy to be here Gene, always keen to spread the gospel of the great work that the ABS is doing statistics and trying to tell people the story of what’s going on in the economy.
Gene Tunny 01:53
Excellent. Well, I’ve been really impressed, Rob, that you’ve been communicating on LinkedIn, you’ve been talking about the data and giving us some insights into how the ABS compile the data. And I mean, one of the sets of data I’m really interested in is the national accounts and GDP, which is the statistic that measures the amount of economic activity in a certain period of time. And I’d be keen to chat with you about GDP given that you’re at the ABS and you’re involved in, in collecting the data and, and crunching the numbers to create the GDP figures. I chatted previously with a colleague of mine, Brendan Marquis Taylor, we chatted about the three different measures of GDP, would you be able to kick off by telling us what those measures are, please Rob, why do we need three different measures?.
Robert Ewing 02:48
Sure, so I should just say at the outset that, you know, today, I’m going to skip over an awful lot of the technical detail. And so I’m sure that the more statistical methodology knowledgeable are going to be screaming occasionally. But it is very complicated. The manual for the national accounts is several 100 pages long, and you know, can take a lot to get into. I think to start with, I tend to think of the GDP as it’s one concept that you can measure three ways. So GDP, as you say, is the measure of all economic activity. But we have to get a bit more specific than that. One of the things I’ve been talking about on LinkedIn is this idea of the production boundary, we have to put boundaries around GDP, because really, anything you could think of could be economic activity, we have to narrow that down a bit. And so we focus on market activity. And we focus within market activity on production. So GDP is a measure of the total value of production for the market sector in an economy over a period of time. It turns out that the way that the national accounts frameworks are set up, and it very clever frameworks developed over you know, more than 50 years by international groups. You could also measure this two other ways. So the first way is to measure how much income everybody in the economy has gotten from these productive activities. So if you measure the total amount of money that goes to labour, what’s called compensation of employees in the national accounts, and if you measure broadly, the national accounts concept of profit, what’s called gross operating surplus. And so if you add those two together across the entire economy, then you also get a measure of GDP. And that’s because if you think about production, well the measure of production is how much what you produce is worth minus how much you had to buy, in order to produce it, or the two things that are left over after that are income and profit. So it’s quite easy to see how those two match up. The third way, which is the expenditure method of GDP, is to think about it from the other side and think that will, we know, in economies and in markets, that there’s both a supply the production, but also a demand the consumption of the goods. And so the expenditure approach looks at where all this production of goods and services in the economy gets used. And so it adds together, the total amount of money spent by households, the total money spent by governments, some of the things that we produce gets sent overseas. And so we count the exports. Some things go into a warehouse, even though be produced, so we count inventories. And then we didn’t produce all the inputs that we use. So we subtract imports. And so that also gives you that same measure of how much was produced in the economy. And so those are the three measures of GDP, which are normally called the E measure, the I measure and the P measure in Australia. In theory, if you have measured everything absolutely perfectly, they will be equal.
Gene Tunny 05:58
Yeah, conceptually, from the way that they’ve that just because of the theory, and there’s a national accounting framework, isn’t there. So you were talking about this has been developed over 50 years? I mean, that’s since the you’re talking about since the UN codified it, I think, did they try and codify it in the late 60s? And then there’ll be various iterations of that approach? And we follow that there’s an international methodology.
Robert Ewing 06:27
Yeah, that’s right. So there’s the system of national accounts. So I think the first one was 1968. And that was building off kind of a lot of international cooperation. But I believe 1968 was the first time they really sit down like a consistent set of international rules. There was an update to it in 1993, and update in 2008. And if you do the math between those, you won’t be surprised to know that there’s an update currently underway thinking about further changes to the system of national accounts. And that will be due out for hopefully for endorsement by the UN statistical commission in 2025.
Gene Tunny 07:04
Yeah, yeah. And I remember from my time being on ABS reference committees for different things, or the technical reference groups, just all of the the issues you have to think about and R&D is a tricky one. I remember that, but we don’t need to go into into that today. I’m keen to understand what sort of data go into this Rob. I mean, you mentioned there’s production, there’s, there’s income, there’s expenditure. So is the ABS collecting data on all of these different transactions? You’re collecting data from businesses, you’re collecting it from households? What sort of data go into the mix, Rob for GDP?
Robert Ewing 07:46
Well, I think the short answer is anything that you can get your hands on. So a good national accountant is a bit of a data scavenger, because we’re only ever looking through kind of little windows into the economy. Kind of weird, we only have these narrow snapshots. So probably the two absolute most core measures of that production side, firstly, the annual economic activity survey. And so that’s a quite a large survey that we do once a year. And we go out to businesses, and we asked them quite a lot of questions about what they produce, how much money they made, you know, kind of how their money was spent, and so forth. And that allows us, in particular, to do what is quite a complicated little fiddly job, which is to try and convert things from the world of business accountancy, into national accountancy, because there are some things where there are some very, very important differences between the way that GDP is measured. And the way that business accounts are put together. The two most important are probably the concept of profit, which can be measured quite differently to that concept of gross operating surplus I talked about before, and also the concept of depreciation, and the differences between economic depreciation and accounting depreciation. But, you know, there are a lot of very complex nuances about that. And so a lot of the economic activity surveys asking the questions that allow us to take the business’s accounting estimates and convert them into economic estimates. So that’s absolutely kind of a foundational piece of us understanding that business side of the economy. So at a quarterly level, then its equivalent will be the quarterly business indicators survey. So that’s a somewhat smaller survey and asks a much smaller set of questions was kind of trying to give us a bit of an idea about what’s happening quarter to quarter, as well. And that’s kind of a very important survey there but the range of inputs is enormous. I’m household final consumption expenditure quarterly uses something like 15 or 20 different input data series, including retail trade, data from APRA, data from various private sector organisations who provide information, data from the quarterly business indicators surveys. So there’s a, an absolute broad range, because things like those big economic activity survey or the quarterly business indicators survey don’t necessarily cover everything. And so we bring the other bits of information to kind of tell us about, particularly the expenditure side of GDP, but also thinking about the role of government, where we have a lot of data that comes directly from federal, state, territory and local governments and tells us about their activities. We have detailed trade information, probably some of our most detailed data sets on the trade side, which allows us to get a pretty good idea of what’s going on with exports and imports. We rely very heavily on the consumer price index and the Producer Price Index publications, because they give us an idea of prices in the economy. And they allow us to convert those current price numbers into volume estimates of what’s going into GDP. So the real GDP as it’s often called.
Gene Tunny 11:17
Right, okay, yep. And that’s, that’s what’s often reported, that’s the that’s seen, that’s the data set that are the item that is looked at to determine whether the economy is going into recession or not. It’s that real GDP number, that volume number where you’re trying to abstract or control for inflation that occurs? Okay, so you’ve got less data for quarterly GDP than annual, it seems, is that right? So you’ve got detailed estimates, annually, you’ve got this other survey, quarterly, you’ve got, I mean, you still got a whole bunch of data. And what are you doing? You’ve got all of these models? You’ve got I mean, Is it done in spreadsheets? Are we able to go into that, or is it in R or or Python? And then is there some way of describing what goes on?
Robert Ewing 12:10
Well, so it is, fundamentally, it’s a very large code base, in our language and computer stuff, piece of software called Fame. And if anybody listens here, knows Fame and doesn’t currently work at the ABS, please immediately make a job application, we’ll fast track you, we need as many people who know this fairly obscure computer language as possible. And so we have here that’s 1000s and 1000s, of lines of code across all sorts of different modules. The basic approach is we’re trying to build things up from the absolute base level estimates. So we’re trying to look at the lowest level of the information that comes in and when we build the GDP up from that, so it’s very much a bottoms up approach to estimating it. The approach that we take is quite different in different areas. So in some cases, we get pretty good information, quarter by quarter on what is happening in the economy. So exports and imports, as I mentioned, is a pretty good case. We know, not perfectly but you know, we have almost census level data, we know almost every transaction that’s happening with imports and exports, there are some complexities around imports and exports of services where we don’t have as strong information. But we have a pretty good idea about what’s happening there. And so all we really need to do is just make some conceptual and timing adjustments and add everything up at the other end of the spectrum would be something like imputed rent. This is a really interesting kind of concept here in GDP. So one of the really important parts of the overall economy is the service we all get from the houses that we live in. Now some of us pay for that to the rent that we send to our landlord, kind of once every week or fortnight or month. But if you own your own home, we still want to count that value, because it’s still an economic service that’s being provided in a market like environment. And so for that we have what’s called imputed rent. So we impute how much rent is there. The data set that we have for that is primarily the Australian census. So every five years as part of the census, we go out and measure every household in Australia. And that also gives us an estimate of how many households they are there are and in what type of houses and in what locations. And so putting that into a model allows us to estimate imputed rent. But between censuses, we don’t have a solid survey or a data point. And so we have to model that. So it’s really a form of nowcasting. We’re using the information that we have about changes in the population, information about household formation and information about kind of your building construction. estimates of how much demolitions are happening to us forget how the number of households are changing and we obviously have information about rents from other series. And so at that end of the spectrum, it’s really a model, which is using a bit of data. But it’s not a massive amount of data compared to like its base, which is set every five years with the census. And that will be something the team will be turning its mind to very shortly having just had the second set of census results released.
Gene Tunny 15:21
Yes, yes. Great, great work. Everyone’s excited about that. So I saw your boss, David Gruen who’s well, it was, I mean, we both worked for him and within the various times in Treasury when we were there, and you’re working for him again, at ABS. He’s been getting a bit of media on that on people working from home, which is good to see. So all very good. Rob, can I ask you about this quarterly data? So you’ve got all of these bits of data going into it? And you’ve got these different modules? And there’s all this code? Which was a revelation. So I’ll have to do some research on that. I found that fascinating. What’s the quality of the quarterly data like? I mean, I know you revise it in the future, and there’s a statistical discrepancy, isn’t there? Could you tell us a bit about what the quality of that is like first, and then we might go into the annual data and what you’re doing there? How you’re trying to, yep. If you can tell us about that, please. That’d be great.
Robert Ewing 16:20
Yes, sure. So I think that’s so I think there’s two answers given to the quality of the quarterly data. So this is all in the context of we kind of spent a lot of time and a lot of resources and a lot of effort on making the quality, the highest it can be. But inevitably, a lot of the systems and the data in the economy is fundamentally on an annual, particularly financial year basis. So if you think about the financial accounts of the company, they will be producing kind of view monthly and quarterly financial information. But it’s only at the end of the year, that they really do that complete process of producing a full set of accounts, and making all of the adjustments and thinking about all of the different bits and pieces they need to take into account. And no matter how well you’ve gathered the quarterly data, the annual data is always going to be better. So you’re always going to have this view of the world that is a little bit sketchy. And yeah, and I think that if you look at the revisions, the revisions, they will move the numbers around, they very rarely change the story of what’s going on. So GDP might move up a little point one or point two, down to point one or point two, but very rarely does the story of what’s happening to the economy change very substantially. The other element to that is that even the quarterly estimates get a bit better with time. So we produce the estimates for GDP, roughly nine weeks after the end of the quarter. So our June quarter is published in the first week of September, on the first Wednesday in September. So that is a pretty good amount of time. But there’s still information that continues to come in, there will be businesses that we surveyed, who didn’t have time to respond, there will be data sources, for instance, ATO tax data, some of that won’t even arrive until after the national accounts has been published. So our picture of each quarter gets better with time as we gather more data, and you know, some late returns come in. And so that’s part of what contributes. But the big story is that really, GDP is fundamentally an annual measure that we can do on a finer time horizon using really a combination of different approaches. And for some things, such as household final consumption expenditure, there’s not a massive difference in the quality between the quarterly and the annual household final consumption expenditure has pretty much the same sets of information. But if you’re thinking about production, it’s quite different. And yeah, you mentioned statistical discrepancy. I think this is probably a good, a good way to talk about how we actually measure those three measures of GDP in practice, and how we actually make them equal to each other as they theoretically should be. So when we measure GDP every quarter, we can. It is very rare that the three measures come out exactly the same. Probably has happened once or twice. We were probably very suspicious when it did happen. As of now that can’t be right. There can’t be equal. We do two things in response there. Firstly, we use the differences between them as a way of looking at the different components and models and data sources and thinking about, are there gaps here? Are there adjustments that we should be making? There are other pieces of information that we should be seeking that would allow us to bring those measures closer together, but we’re not going to arbitrate them all together without some source of evidence for that. And so the three measures will be a little bit different from each other. So in order to get the measure of GDP that’s published on the front page of the webpage, what we do is we average the three of them. And so we have what’s called GDP A for average. And that is really just literally you add the three measures, and you divide by three. And you know, for those who are fans of the details, you’d notice, now we’re doing that in terms of the level of GDP, not the percentage change. Now, of course, it would be nice to get rid of that statistical discrepancy. And to do that, we need that information set that we have for the annual publication. And this brings us to, I suppose, what is the core of kind of producing like the benchmark GDP estimates, which is a process that’s called supply use balancing. And so I talked before about the idea that we can match production to income to expenditure at that top level. But in theory, we can also do that for every individual product that’s produced in the economy, that we should be able to say, for every products, let’s say, mushrooms, just picking on that one, because it’s very early in the list. We know, you know, in theory, we know we’ve produced you know, this many mushrooms. And you know, we know this many mushrooms got used by restaurants and other people and food manufacturers, this many mushrooms got sold to households, this many mushrooms got exported. And so in theory, we know well, those two numbers, the supply of the product and the use of the product have to be equal. We’ve defined as the way we’ve defined GDP, of course, the way that we’ve measured everything, through all these different surveys, we haven’t gotten a complete survey of every single person in the economy, we haven’t asked every single household what they consume. So we know there are some errors there and they don’t balance. And so every year, we go through this process of supply use balancing where we look at products, we don’t look at it at the level of every single kind of view, 375 mil Coke can, and 750 mil Coke can, and we have about 300 products that we look at so that we broad categories, like legal services, or metal, steel manufacturing products, or things like that. And we look for each of those products. We want to balance, how much was produced, how much got used by households, by government, how much got exported, how much went into inventories, and how much was used by other industries in their own production. And we make sure across all of those products, the supply and use is balanced. And once we’ve achieved that, then we have the three measures of GDP will be equal, because we’ve now brought those two halves of the measurement of the economy together. And so that’s, I suppose that’s the really, that’s the big work that kind of goes on, after a year is completed. So once we’ve finished the financial year, then the work starts on producing those supply use tables and doing that balancing. And when you’ve done that, the reason that’s important is I suppose it gives you that foundation that you can build on. So when policymakers are looking at GDP, they’re mainly going to be focused on what’s happening to GDP. Right now, they don’t care about what happened to GDP a year and a bit ago, which is about how long it takes us to produce those supply use tables. But through producing them, we make sure we’ve got an accurate representation of how much every different industry and sector and product matters. And so when we take that information, that’s you know, kind of you know, that lesser information set that we have quarterly to update the numbers and say, well, this is how much this bid has grown. We’ve given GDP the best base to sense, put everything together and give you the most accurate information out of the most recent quarter.
Gene Tunny 24:14
Okay, we’ll take a short break here for a word from our sponsor.
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Gene Tunny 24:48
Now back to the show. So this they supply use tables. That’s what you’d call an input-output table. Is that right Rob? This is an input-output table your developing, how these industries interact with each other, the flows of resources between them and then what goes to sales, what’s exported, etc?
Robert Ewing 25:09
It’s a very closely related cousin of an input-output table. So there are a couple of pretty technical differences between supply use tables and input-output tables. Importantly, in Australia, the input-output tables that we produce are a lot more detail. So I mentioned supply use, we’ve got about 60 industries times 300 products, when we get to the input-output tables, we’re able to expand that to about 115 industries and a bit over 900 progress. So we can give you more detail in the parameters as a couple of other technical details. But it’s broadly that same sort of concept. It’s trying to understand what is produced in the economy, and how it flows through the economy. And they’re a very powerful analytical tool.
Gene Tunny 25:53
Yeah, absolutely and Rob what I think’s interesting is you meant just, I mean, you’ve got all of this data and you’ve got these three measures that on a quarterly basis, you’re trying to get as close as possible. And you mentioned that, look, you have to make some adjustments. I mean, so there’s some judgement involved, but that’s going to be informed as much as possible by other data or whatever information you’re gathering. And you talked about he getting data from a huge range of sources, government and your own surveys, from the private sector. You probably can’t go into this. But what I’ve what I’ve been surprised at now is just how much real time data or up to date data that banks for instance, so the who else is Dun and Bradstreet, they’ve got whatever they’re called now, they’ve got more up to date data about how things are going into the economy, I presume the ABS is, is trying to get hold of some of that data.
Robert Ewing 26:52
Yeah, no, absolutely. And we have, for instance, on the bank data, we have a new publication, it’s been running since February this year, which is the monthly household spending indicator. And so that takes information from bank transactions, so credit card and debit card data. And it gives you a much broader picture of what’s happening to household consumption, then the retail trade survey does, the retail trade survey was a great survey. It’s one of the longest running surveys, and it’s very closely watched. But it only tells you about a third of consumption. Because today, in terms of things, you can walk into a store and buy or kind of buy through a retailer online, that’s only about a third of what households consume every day, when we’ve got the amount of the household spend indicator variable to expand out to more categories of consumption. And so that covers a little over two thirds of consumption of households. So that kind of finer grained data is definitely something we’re very interested in. Another example is the monthly business turnover indicator, which is another fairly recent publication. I think that started a little under 12 months ago, that takes ATO business activity statement data, and it gives you a month by month picture of how the turnover is moving in different industries. And so these are giving us that month by month picture of what’s happening in the economy. And that’s something which in the past, we’ve had to rely on the quarterly surveys and the quarterly national accounts for and I think that’s really exciting development with the data becoming more available. And, you know, the ABS showing its capability to transform that data into useful insight for people is definitely something we see is a growing kind of part of the business but going forward.
Gene Tunny 28:51
Yeah, absolutely. And it’s so important as we’re trying to monitor the economy as the RBA and the Treasury are monitoring the economy. And, and you know, that obviously feeds into policy. But yeah, that’s, that’s something for another another time. Right, on the supply use balancing, if you just got some a little bit, a few more minutes, while you’re trying to get these data internally consistent, it’s all about making sure everything adds up. All of these data are consistent. It’s the story makes sense. This balancing, I think I asked you about this on LinkedIn, what do you do, how do you do this, this a some sort of algorithm, is it..
Robert Ewing 29:31
So it’s a mix of things here? So for a lot of the large things, it is a human being looking at the data and looking at the whole picture and making a decision about all based on what I know, this is the bit here that must be wrong. So there’s a lot of it, which we’re not yet able to put into an algorithm. But if you think about I mean, I described that kind of 60 by 300 kind of matrix, you know, it’s an enormous number of cells. Once you’ve got to fill in, and so once we get past those things where you can reasonably make a human judgement. We use an algorithm, it’s a constrained optimization algorithm. And what we do is we tell that algorithm, the same things that we know from the national accounts framework. So we tell that algorithm, things like, Well, we know, you know, this supply has to equal this use. And we can also give it some other parameters, kind of like, it’s rare that the financial sector consumes many sheep directly, for instance, you know, so you can apply a bunch of constraints there, and it can then kind of go away, and it can algorithmically kind of find a sensible solution for you based on that. But the reality is that, you know, right, this second, there isn’t a good solution from a lot of this beyond a human being who can look at and just make a judgement about what makes sense here, you know, does it make more sense to kind of say that the excess rolled steel production is going to be going to export or to households? Because the algorithm is not going to have a view on that one, but the human is going to be able to say, no, no, we must have just mismeasured some exports there. Yeah, let’s have a look at that.
Gene Tunny 31:15
Yeah, gotcha. Okay. Yeah. So some constraint optimizations and judgement. Very good. And right so Rob, this is all fascinating. Is there any, any other points you think would be important for, for us to understand in detail to appreciate just the magnitude of this task? So I think I’m hoping we people understand how important these data are. And I’ve covered that in a previous episode. But is there anything else we should know, in terms of just the, the, you know, what, what are the challenges for ABS in doing this? Because it does take several months, doesn’t it, you do this on a quarterly basis, and it comes out, it comes out two months after the end of the quarter, doesn’t it? So there’s obviously a lot of work involved.
Robert Ewing 32:02
Yeah. And I think I divide that into two halves. So there’s about a month of data gathering and so this is kind of you the various surveys going out and measuring things. So it’s kind of, you know, working with partners, such as the banks and private sector, and governments, and so on to get the information streams. And then there’s about a month of what we call compilation, sitting down, running the pros, running the computer code, seeing how the numbers make sense or not. And then ultimately, you know, writing media releases and producing a publication and getting it onto the website. And just to put it in a plug, also, for our new product, which is, we are each quarter producing a nice little list of, you know, 10 to 15 things you should know about the national accounts. It’s nice and easy to digest. And you can just find that on the ABS web page. So if you find the idea of clicking on a GDP release a little intimidating, we’ve got some much more user friendly products available now. But yeah, it’s as you say, it’s about a couple of months to put it together. It’s the work of hundreds of people across the ABS, once you count the people in the survey divisions, the data acquisition divisions, all the other publications such as the balance of payments, the capital expenditure, the business indicators publication, which all feed into the national accounts, the communications team, the compilation team it’s hundreds of people across the ABS contributing to every quarter. And they are not to forget the 1000s of businesses and households answering surveys out there. I mean, the most fundamental thing is just how grateful the ABS is for the people who take the time out of their busy business and personal lives to kind of give us this data that we need to tell Australia about what’s happening.
Gene Tunny 33:57
Yeah, yeah, that’s a good point. Yeah, absolutely.
Robert Ewing 34:00
And one final point I’d make is, GDP is the figure that gets all the fun headlines. But the national accounts are a very rich publication. They tell you about a lot of different parts of the economy, they can take a bit of expertise to understand. But there’s a lot of information in the national accounts beyond GDP. It tells you about how each state is tracking, it tells you about the consumption of different goods and services in the economy. It tells you about the balance sheets of households and governments and businesses. There’s a massive amount of information beyond that top level GDP figure in there and I think a lot of the criticisms you sometimes hear about GDP not taking into account depreciation or not taking into account other things. An awful lot of that is in there somewhere. But it is a very big publication. I know it can be a bit intimidating to try and find anything in it.
Gene Tunny 34:58
Yes, yeah, but you’re right there, Rob. And, I know that there is work going on. And it may not be in the national accounts, the core national accounts, we do have satellite accounts. I know you’ve, you’ve tried to estimate the contribution of different sectors like tourism. And I’m trying to remember if you’ve done natural, natural capital estimates. So I think there are some other estimates where you’ve tried to estimate them, I’ll have to check. I remember, this is one of the issues or one of the things people are concerned about is that GDP doesn’t take into account environmental degradation. And so but there are estimates, there are people who have looked at those sorts of estimates, I’ll have a look offline and just add something in the show notes if I need to. But I know that that’s one of the issues people are concerned about.
Robert Ewing 35:49
And it looks, it’s there. It’s not my area of expertise. But there’s a whole range of work that the ABS has done on environmental economic accounts, which is really bringing together those two data sources. And I think that’s one of the unique advantages of the ABS is because we kind of sit in the middle of this data architecture, we can bring together the data that we have from these different domains and put them next to each other. And we can see how the story of the environment and particular aspects such of water align with the story of the economy. And you know, it’s something which is still like an ongoing piece of work to fully develop all the products there, but something we’ve been actively developing over the past.
Gene Tunny 36:32
Okay, very good. Rob, in from the ABS. Thanks so much for your time. I really enjoyed that. And, yeah, I look forward to seeing more of your contributions on LinkedIn. I think that I’ve been learning a lot about the work that you’ve that you do over at ABS and I’ve got a renewed appreciation for that work. So thanks again, Rob. Very good.
Robert Ewing 36:53
Thank you very much.
Gene Tunny 36:55
Okay, that’s the end of this episode of Economics Explored. I hope you enjoyed it. If so, please tell your family and friends and leave a comment or give us a rating on your podcast app. If you have any comments, questions, suggestions, you can feel free to send them to firstname.lastname@example.org And we’ll aim to address them in a future episode. Thanks for listening. Until next week, goodbye
Thanks to Josh Crotts for mixing the episode and to the show’s sponsor, Gene’s consultancy business www.adepteconomics.com.au.
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