Dr. Brian Moyer is director of the U.S. Bureau of Economic Analysis . BEA, made up entirely of career civil servants, is an impartial producer of official statistics on the U.S. economy. Its statistics are used by businesses, policymakers and households to inform their decision-making. BEA is part of the U.S. Commerce Department .

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Rosemary Pennington: In news stories about the health of the American economy or sometimes on Sunday morning talk shows, you might hear experts talking about the GDP or Gross Domestic Product. The GDP is a measure of the value of all goods and services produced during a particular time period and as you might imagine it's quite the undertaking to keep track of all that information. The organization that does that among other things is the Bureau of Economic Analysis and it's the focus of this episode of Stats and Stories, where we explore the statistics behind the stories and the stories behind the statistics. I'm Rosemary Pennington. Stats and Stories is the production of Miami University's Departments of Statistics and Media, Journalism and Film and the American Statistical Association. In the studio...our regular panelists, Statistics Department Chair John Bailer, and Media, Journalism and Film Department Chair, Richard Campbell. Our special guest today is Brian Moyer who's the director of the US Bureau of Economic Analysis or BEA. Thank you so much for being here today Brian.

Brian Moyer: Thank you very much.

Pennington: Just to get the conversation started, give us a real quick overview of what it is your agency does?

Moyer: Sure, so BEA is a federal agency made up entirely of career civil servants whose work is to produce official statistics on the US economy. So we have about 500 economists, statisticians, and accountants on staff at BEA. If you look at our formal strategic plan, our mission is to promote a better understanding of the US economy by providing the most timely, relevant and accurate economic data in an objective and cost-effective manner. Most of the folks that think about BEA associate with our flagship product as you mentioned a moment ago, Gross Domestic Product or GDP but you know we're a lot more than just GDP. So if you want to know how the broad economy is performing, we can tell you that. But if you want to know how a particular state or a metro area is doing, we can also tell you that. There is also lot of information we provide at the sector level so if you want to know how manufacturing or finance or retail trade is performing, we can tell you that too. Finally, I mentioned that we have a whole suite of international statistics. So if you want to know how the US is faring on the global stage we have lots of information to answer all those questions as well. And these are just a few examples of the hundreds of millions of data points BEA produces each year.

John Bailer: That leads to a really natural follow-up question. What exactly is the Gross Domestic Product?

Moyer: Well I guess the question here is how wonkish do you want me to be in answering this question?

Bailer: Well you know... so people talk about things like you hear about the Gross National Product, then you hear about Gross Domestic Product and you hear about other kinds of indicators. So could you give us the high-level view of what is such an index and why is it an important index for us to consider as a nation?

Moyer: Yeah absolutely. So the official formula for GDP is consumer spending plus business investment plus government spending plus net exports, which is the difference between exports and imports. But another way of thinking about this or another way of putting this is that GDP is the broadest measure of economic activity for the US economy. It's the total value of goods and services from machinery to manicures produced within the United States during a given period. Now GDP reflects the value of production solely within the US borders. GNP or Gross National Product as you mentioned a moment ago, reflects the value of production by US residents within US borders and the production from operations abroad. Now you know, we actually produce both GDP and GNP here at BEA. GDP is BEA's primary or so-called featured measure of economic output. But prior to 1991, GNP was the primary measure. So you know you might ask why the change in emphasis? Why did we switch featured measures? The rationale was that GDP was the more appropriate measure for better grasping what was happening specifically inside the United States. GDP is also the worldwide standard so we can make inter-country comparisons by using the measure of GDP.

Richard Campbell: I read over the recent press release on the economic impacts of art and culture in the US and first of all I want to compliment whoever wrote the lede to this press release, I'll just read it real quickly here.

Sure, Broadway and Hollywood employ lots of creative people but when it comes to artistic and cultural work not all the action is on the coast. New data show Arts and Culture accounts for a larger share of jobs in Wyoming, Utah and Colorado than they do nationally.

That's well done.

Moyer: Yeah, this is actually a brand new product that we're beginning to publish now on a regular basis. It's interesting because it's a partnership with the National Endowment of the Arts and this account measures not only sort of national level impact of Arts and Culture activity on GDP but as you just mentioned a moment ago, it breaks that activity out by states so we can say something state by state. Now, as we're getting started here we're just looking at compensation and employment but as we move on we're going to be able to break out those value-added measures state-by-state as well. And let me add one more thing before we move on. This is a nice example of what BEA calls a satellite account. So the arts and cultural production account is one of those accounts that is not included in the core set of counts per other accounts produced by BEA but rather it sits on the side and is consistent with the core set of accounts. But it's an area where... it's an account where we're able to pull out information from our national accounts or industry accounts, our regional accounts and our international accounts and tell a cohesive picture or story about a particular sector of the economy and that's what this is all about. We have a lot of these satellite accounts but we find this is a particularly useful way of addressing user's specific questions about economic performance.

Campbell: Just to follow up on the surprising thing here and I think you have this in the lede is that you have something called the location quotient which I want you to talk about. But explain to me, you would expect New York and California to have lots of arts and culture type jobs, but you found that Wyoming, Utah, those do very well too. Can you explain the location quotient a little bit?

Moyer: I'll first by saying I'm not the experts on this set of accounts here but the location quotient basically tells you how much of that activity is centered on that particular state in this case relative to the nation as a whole. And so while you would think that states like California, New York, and others would be those sorts of hubs of this kind of activity, there are lots of national parks and government operations and so forth spread around the country whose mission is related to arts and culture. And that's what you're seeing when you see those higher location quotients for areas which sort of you know you scratch your head a little bit about why are these arts and culture related.

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Pennington: You're listening to the Stats and Stories where we explore the statistics behind the stories and the stories behind a statistics. I'm Rosemary Pennington with Miami University Statistics Department Chair, John Bailer and Media, Journalism and Film Department Chair, Richard Campbell. Our guest today is Director of the US Bureau of Economic Analysis, Brian Moyer. This discussion of satellite accounts, Brian, seems like a story that's probably underreported as far as things coming out of your agency, are there other kinds of stories that you think are underreported that your agency is working on?

Moyer: Yeah we have a lot of new products. Let me just say that I think one of the biggest challenges BEA faces of course is keeping our statistics up with the ever changing economy. So we need to make sure our data is meaningful for the world and meaningful for our customers and of course to do that we have to constantly evolve our statistics. So let me give you a couple examples of some new things that we're doing. So we've developed new health care statistics that break out spending by type of disease such as heart disease or diabetes rather than breaking out spending by place of service. So by place of service, I mean hospitals or doctor's offices. So you know why is this important? It's important because it gives us a more complete and accurate picture of health care spending and allows us to capture the substitution of treatments over time. Now that sounds technical but I'll give you a quick example why these accounts are so important?

Let's suppose you're suffering from depression. Thirty years ago if you were suffering from depression you would have to undergo a regimen of talk therapy, very expensive talk therapy. Today, you are going to take some kind of narcotics, some kind of drugs to abate that situation. They're relatively inexpensive compared to the talk therapy. If we're to accurately measure health care spending costs over time, we want to be able to capture that substitution from one type of treatment to the other. In this new set of accounts allows us to do that because we're looking at this disease by disease.

I'll give you another quick example of an area that we've been doing some work on and that is beginning to produce consumer spending measures broken out by state. So as you know we've long produce consumer spending measures for the nation as a whole as part of GDP, clearly. But this is our first look at consumer spending broken out on a state-by-state basis. So these new data show not only sort of the top-line numbers of consumer spending by state but it also digs in and shows exactly what consumers are buying in each state and these are just a couple examples but there's lots of products like this that BEA has to continually developing, continually innovate and continually expand because after all we have to keep our statistics current with the ever changing economy.

Bailer: You know, so if you're breaking down health care expenses by type of disease, I recall that you can see pretty dramatic differences in treatment across the country, even within a state you can find pretty dramatic differences. With some of the data that you're collecting on these types of health care expenditures by disease, also provides some insight to that differential?

Moyer: They may in the future. So right now we're focused on the national level statistics but longer run plans are to break these out by state. This kind of leads into a slight digression here but I think it's a useful one. The way we've developed this health care spending satellite account is really an excellent example of how a statistical agency can blend the world of big data and traditional survey data. So we're actually looking at billions and billions of insurance claims data to build this disease based on health care spending account. So given that as the basis for this set of accounts, one could conceivably think about breaking the state dimension, the regional dimension would be embodied in those data and one to think about breaking that out at some future point. I'll tell you, the challenge this set of accounts is facing right now is one that we face in some other areas in the accounts like the high tech sector is adjusting for quality. So when you think about these different treatments over time, you have to be able to account for what that means in terms of quality adjustment, in terms of better quality of life and so forth. So that's really the focus of this research now. But as you suggest in the longer run having a regional, a state-level dimension to this would be an important expansion.

Campbell: A lot of the data that you report, the studies you report, get interpreted and reported through news media, could you talk a little bit about what frustrates you about journalistic coverage, what they do well, what they don't do well?

Moyer: Generally our output, our products, our statistics are covered well. But from time to time, there are some challenges we face and let me just use GDP as an example. As you're well aware we produce three estimates of GDP in a given quarter. First estimate comes out about 30 days after the quarter end, for instance BEA is going to release its first estimate of GDP for the first quarter of 2017, next Friday, April 28th but then we'll update that figure a month later. In this case on May 26th as new and more complete source data become available and then we'll update that number again on June 29th as even more complete and new source data become available. Because we want to always provide the most timely estimates for our customers. We don't want to wait until all these data are complete before we release a measure of GDP, right? Actually if we waited until all the data were complete and everything was finalized we wouldn't have a GDP, quarterly GDP estimate for about five years so that wouldn't serve anyone. But those quarterly updates or revisions as they're known in the economic circles, are really just that...they're updates. But sometimes, they are incorrectly reported as errors and I'm sure you've seen such headlines from time to time. These quarterly updates reflect our best calculations based on the available source data that we have at that time and we're very clear with our customers exactly what data we have and what we're missing and we make all those assumptions available to our users but nevertheless, nevertheless there are some times when we just get misinterpreted as errors and I can tell you it's quite frustrating.

Bailer: I'm curious if part of that is that there's just not an appreciation of some of the uncertainty that goes into a calculation that's this complex.

Moyer: Yeah, I think it's the uncertainty factor. I think it's also just frankly us not doing as good a job we can about explaining the process. The process is a technical process. It's a relatively complicated process, you know thousands and thousands and thousands of data components go into GDP and we don't always perhaps do the best in relating that to the average person.

Bailer: If someone were just meeting you and finding out you're at BEA, what would they be most surprised to learn that BEA does or that BEA produces?

Moyer: The thing they'd be most surprised about is the fact that BEA is not primarily a data collector. That we don't go out and collect all the components that go into GDP, pull the estimates together and publish that number. That's what everybody thinks but rather in this decentralized statistical system that we have here in the United States, that isn't the way it works. In fact what we do is we pull together thousands and thousands and thousands of data points every single month to compile that GDP number. What we do is to basically curate these economic frameworks, these economic accounting frameworks to which all those dataflow in and once they're there, we then harmonize and reconcile within those frameworks. So for example, for the GDP numbers we pull all the data into something we call the national income and product accounts. That's an accounting framework that is populated, harmonized and at the other end out comes GDP. Of course what this means for BEA is that we are often the first ones to see any inconsistencies in the data. We like to say that we're often viewed as a mineshaft canary of the Federal Statistical System, right? We smell it first and there are often cases where... I mean let me just give you a very quick example.

A few years ago, we were estimating output per worker for the computer industry. So into these frameworks we pulled the output measures that are produced by the Census Bureau and we pulled in the employment numbers produced by the Bureau of Labor Statistics. Everything seemed good until we started computing these ratios and they looked absolutely crazy. So we say "Wait, wait, wait we got to stop, take a look at this." So we dug into the details come to find out that the establishment list, that the Census Bureau was using to sample its output measures was different from the establishment list that the Bureau of Labor Statistics was using to sample or to compile its employment numbers. Put these two things together and tell oh what wonder we have such very strange-looking output per worker numbers. And so we were able to go back to the agencies and say "Hey you know we need to address this issue."

Anyway, so I've strayed a bit from the initial question but I think that the basic thing that I find, that most users are confused about is sort of the fact that BEA is not out there collecting millions and millions of data points through surveys.

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Pennington: This is Stats and Stories; our guest today is Brian Moyer, Director of the US Bureau of Economic Analysis. Brian, I'm going to ask you a question that's not about the data that you're collecting or analyzing there but really you're sort of about yourself. How did you come to become the director of BEA? How did you get into this line of work?

Moyer: Actually I'll be honest, BEA is my first federal job, my only federal job. I'm here right out of grad school. I moved from an entry-level economist in the GDP by industry branch straight up through the Director of BEA. So I'm certainly a BEA person through and through. BEA is a great organization and I guess if I had to say what I like the best about it, is the people. You know, working with BEA's dedicated public servants who care so deeply and are truly committed to the mission of the agency, this is one of the things I just find so satisfying about this job, something that I'm proud of. You know, in measuring this $18,000,000,000,000 US economy is certainly a challenge but it's also really rewarding. One of the hallmarks of BEA statistics is behind every one of those detail numbers that you might pull off our website. There is a person that's doing their very best to accurately measure that component of economic activity and not only that but they're willing to talk to you about that particular component. The dedication of our staff is just one of the reasons it makes me so happy that I've been here for 24 years and I wouldn't trade this job for anything.

Campbell: We're in a kind of a political climate right now where there's a lot of assaults on evidence and science and data, what can we do to do a better job of promoting evidence-based research, promoting data, promoting evidence, you have any thoughts about that and are these conversations that you have?

Moyer: Yeah, there are conversations that we have and you know I think that at BEA we like to think that what we do is so important and so relevant and of such value that when decisions are made around budgets and so forth that yeah sure maybe we will have to re-prioritize programs here and there but we're hopeful that the overall logic of the policymakers is that the core mission of BEA will be preserved and I think we as an agency sort of hold to that and it's proved over time that does hold.

I'll tell you, when I talk to staff about sort of the new world of economic statistics or the new world of big data, this is the thing that really gets them excited. This idea of being able to bring these unstructured data, if you will, administrative data, big data sources, and private data sources into the accounts. This is something that really motivates, really motivates staff and I think that it's a bit of a paradigm shift for the statistical agencies because this type of skill sets, more of those data science type skill sets are not what we've traditionally looked to in the economics profession or in the statistical profession and our world is changing. As I said a minute ago when I start talking about health care satellite account, I mean I think there's a place for both this new big data approach and also the structured survey data. But it's just that, it's a blended approach. It's combining these two worlds and as I say I really do find great excitement especially among the more junior staff coming to BEA around the opportunity that the entire effort reports.

Bailer: So to me it's amazing to think about 18 trillion dollars as a number and so I've got sort of two questions, how do you communicate the idea of 18 trillion dollars to people when you're saying you know millions, billions, trillions that I think is really hard to think about magnitude comparisons of this size? So that's kind of my first question and my second question is how does the US economy at 18 trillion, if you look internationally, what's the next economy in the magnitude of their GDP?

Moyer: Let's start with the 18 trillion dollar question. You know most analysts looking at GDP, they're interested in the overall level but I'll tell you, the featured thing is really the growth rate. It's obviously important to know about the components and the shares of those components in GDP but I'll say most of the focus from users is on the GDP did increase, did decrease, did it grow 2.1%, did it grow .5%, I mean these are the typical questions that we get. I mean, I think we do a very nice job in the various dissemination platforms that we have clearly articulating how that 18 trillion dollars is broken out not only by sort of esoteric components of consumer spending and government spending and business investment. But I think it becomes a little more real to people and they sort of get it a little bit more when we then break that out by industry and by state and so I think when you start looking at GDP decompose another way it gives some meaning, it gives some context around that like a stream astronomically large top number.

Bailer: What's the largest share of that 18 trillion?

Moyer: Consumer spending.

Bailer: Consumer spending?

Moyer: Consumer spending is about 70% of that 18 trillion. Now consumer... now going back to the growth story I was telling you a minute ago, when you look at the NIPA, the National Income and Product Accounts Tables, you'll see that consumer spending is not always the largest contributor. I mean it is big but it's a fairly stable growing component of GDP where compared to something like inventory change that bounces all over the place. So I guess my point here is just to get a large component doesn't necessarily mean that it's going to be any more important than something like inventory changed that make a very large jump in any particular quarter.

Pennington: You've mentioned that you're using sort of new kind of ways of measuring economic activity and I'm wondering given sort of the digital environment we live in and for instance social media, is your agency looking for ways of sort of leveraging social media spaces to better communicate this information to the public directly?

Moyer: Yeah, we certainly are. We are on the social media bandwagon and I will... so if you think about our...I'll just sort of broadly speak about our dissemination. So everything that we produce is on our website www.bea.gov and we considered some of these similar data for the most important thing that we do in sort of aside from getting the GDP numbers right. One of the things that we've learned is that you really have to keep sort of up to date with the latest dissemination tools and platforms and we now have a complete set of API's that cross all four of our program areas and we've discovered that there's a great demand for that and we're seeing great use and that we're very pleased with that. But the other thing that we just introduced and this is only been a few months ago is something we're calling B-E-A-R, bear, but the R part of that stands for R the programming language. So for the first time we've got this very slick sort of hip way of accessing BEA's data for... obviously this is for our more tech savvy users but it really does allow a user to go in and pull something from across all of our program areas, put it together in a snap and just see exactly what it is... answer the question they were trying to answer.

So I just give you a fast example. So suppose someone's looking to gauge the impact of energy goods and services on the US economy. Well certainly that's in consumer spending in GDP, right? Or it's also contained in the international accounts. It's in the regional accounts. It's across all of our accounts. With this API, this R base platform that pulls from our API's will do is just go out there grab all that relevant information, mash it all up and return to you sort of an overall picture of how energy related goods and services impact the economy from a variety of perspectives. So we discover the folk people really like this but first what's happening is now those folks that are really engaged in this kind of work are calling up and wanting more and more and more so we're going to have to prioritize some of it going forward.

Pennington: Well thank you so much for being here. That's all the time we have for this episode of Stats and Stories. Brian Moyer, Director of the US Bureau of Economic Analysis. Again, thank you so much for spending part of your day with us. Stats and Stories is a partnership between Miami University's Departments of Statistics and Media, Journalism and Film and the American Statistical Association. You can follow us on Twitter or iTunes. If you'd like to share your thoughts on the program, send your e-mail to statsandstories@miamioh.edu and be sure to listen to future editions of Stats and Stories where we discuss statistics behind the stories and the stories behind statistics.