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GDP is “the size of our economy,” the sum total of goods and services produced by “our economy” consolidated into a single dollar figure. In case you didn’t already know this, how big it is, and how fast its growing, is considered by many observers to be important. When it doesn’t seem to be growing as fast as it was in the past, people write books.
It’s also probably not surprising to anyone who reads this blog (BREAKING: it still exists) that how we measure GDP is, when you dig into it, at least a little weird. For starters, the border between what is and isn’t “the economy” as opposed to “stuff people do with their time” is a little fuzzy. Plus, stuff that seems to definitely be party of “the economy” is occasionally hard to measure. This ends up with the rent that homeowners don’t actually pay themselves but are “imputed” to pay themselves to work out to be 5-10% of all of GDP!
When you think about it, that isn’t wrong—we obviously spend a lot of money building houses, buying new and used houses, fixing broken houses, and renting houses we don’t own, in a way that suggests a) houses are definitely part of the economy and b) if we don’t measure the benefits homeowners get from owning very larger economic objects then GDP will look weird as a result. The folks who do this for a living explain it better and more thoroughly than I can.
But when you think about it, it does suggest that the legal and economic structure of relationships between people and institutions can matter a lot in deciding what does and doesn’t go into GDP. To wit, let’s visit a parallel universe, one where America is just the same as it is today except for one big difference.
In this universe, there is a very popular thing called The Netflix Organization that millions of Americans use to stream content. Everything physically and institutionally about The Netflix Organization and how people use it is the same as Netflix in our universe, but legally it’s structured just a little differently:
- The Netflix Organization is collectively owned by its members, not its shareholders.
- Its shareholders are actually all creditors who just have a set of unusually-structured debt contracts with the Netflix Organization.
- The monthly fees that owners pay to The Netflix Organization are actually collective contributions by the owners to
- pay organization staff and other costs;
- service debt payments (actual debt + dividends in our universe)
- cover depreciation; and
- engage in capital improvements (improving streaming performance and UIs, creating and buying rights to new content).
So here’s what would be weird about this universe—if you just left it here, GDP would be exactly the same as it is in our universe. But you wouldn’t just leave it here. Because the owners of Netflix don’t seem to be making any income! Yet they’re collectively paying billions every year to support this capital that they collectively own, which wouldn’t make any sense if it wasn’t producing economic value to its owners. So you need to impute the value of streaming Netflix content to users, and consider that economic output that would be added to GDP.
And depending on how you calculate it, that’s a lot of value. Netflix claims American users streamed 42.5 billion hours of content last year. How would you impute a dollar value onto that? Well, an average movie ticket last year cost $8.43. The average movie is around 2 hours; so you could impute a value of $4.215/hour streamed. But of course each hour streamed is probably viewed by more than one person; let’s just stipulate that the average works out to around two.
You would then impute a value of Netflix Organization income to its owners of $358 billion—which would add around 2% to 2015 GDP! And not only that—Netflix streaming is growing rapidly, from 29 billion hours in 2014. That figure would’ve only added 1.3-1.4% to 2014 GDP; put another way, the growth in Netflix streaming alone boosted nominal GDP growth by 0.6-0.7 percentage points last year.
Now, the assumptions I used to impute economic value to Netflix streaming are more than challengeable. But the point is that, in this parallel universe, you would very likely have to go through the exercise and impute something. We don’t do that in our universe because Netflix is considered to be selling a product to consumers, and therefore the product is automatically valued at the purchase price when it’s considered for addition to GDP. Which is fine! Fundamentally what I’ve done above is to rearrange a bunch of activity not considered economic in our current framework into something different purely on paper, with no real world change, and yet prompt a potential—and potentially large—reevaluation of our core economic metric.
The point of this exercise—and this post—isn’t that “GDP is bad” or “GDP isn’t accounting for disruptive tech, bro” or “the Lucas critique/Goodhart’s law/Cambell’s law,” although it necessarily includes a little of all those things. It’s mostly just that there’s an inherently arbitrary nature to measuring anything, and that if you want to measure something, you should probably measure it in a lot of different ways.
The Economy In 1000* Emoji
The Key Facts
Each emoji represents one one-thousandth (0.1%) of GDP. All data from 2013 BEA NIPA tables, with the exception of estimates of federal non-defense and state & local consumption expenditure breakdowns, derived from CBPP, Mercatus, and Tax Policy Center estimates.
*Gross emojis actually total 1,334 because of imports and net foreign travel; net emoji equal 1,003 due to rounding.
Without further ado, here’s your economy:
STATE AND LOCAL
LEGEND (similar categories merged):
Sports and Recreation
Watches and Jewelry
Phones and Faxes
Gas and Fuel
Pharmaceuticals and Medical Equipment
Supplies and Inventories
Newspapers, Magazines, etc
Owner Housing and Housing Construction
Net Foreign Travel
Other Federal Services
subtraction from the total
Basically, they inverted the BEA’s Regional Price Parities and mapped it – cool!
It needs a bit of context, though. Specifically, there’s something very clearly driving this outcome. Fortunately for us, BEA subdivides the RPPs into Goods, Rents, and Other Services, and provides us with a good-enough guide to how it weights them that we can create a parallel “non-housing cost” index and see what happens. And what do you know?
Once you exclude housing, the distribution of outcomes is much narrower and much more clustered around its central tendency. Or more bluntly – everywhere costs a lot more like everywhere else when you don’t consider housing.
Of course we should consider housing! It’s really important! But we should also be clear what expensive housing means – lots of people want to live somewhere. Often because wages are high. And guess what? If we graph the state rent index against state per capita income:
It becomes pretty clear that higher wages (or at least higher average incomes) are likely the reason housing prices are high.
So if you live in DC, you’re probably not paying that much more for most things than an Alabaman is; you’re just paying a premium to live in a high-wage area that can’t – or won’t – build enough housing to keep up with the demand to live somewhere wages are high.
Maybe it’s my anticipation to read The Leading Indicators (right after Piketty, that’ll be a breezy one, right?); maybe it was listening to the Planet Money podcast on Kuznets; or maybe it’s just because it’s Friday, but the question popped into my head this morning – how much is the nonconomy worth?
The boundary between what is and is not “the economy” is both a very well-defined and a very fuzzy one; the NIPA Handbook does a very nice job explaining the division criteria but the more you muse over them the more they reveal themselves as pragmatically arbitrary with a dash of “I know it when I see it.” Which is all fine and useful but still means that all the stuff that’s not “the economy” is not only, you know, the stuff of life, but also just as measurable and worthwhile to measure. Because I am a giant nerd, I have decided to measure it. Because I am decidedly not a one-man BEA, this is going to be pretty back-of-the-napkin stuff. All data 2012:
Americans worked 230 billion hours in 2012. There were 314 million Americans in 2012, so they experienced roughly 2.75 trillion hours. Which means the economy took up ~8% of American time in 2012.
But that’s a little unsatisfying, for the following reasons:
1) It includes retirees and children.
2) It neglects the question of sleep.
3) It neglects the question of work-supporting activities, like commuting. I’m going to exclude them from the nonconomy for now.
So let’s pinpoint working-age Americans, of which there were ~201mm in 2012. Let’s assume that, of their total time spent existing, they spend 1/3 sleeping and another 10% in work-support (the average round-trip commute is roughly an hour, and I rounded well up to encompass all the other little things that shouldn’t be lumped in with the nonconomy with that definition. That leaves us with a pool of ~1 trillion hours pretty much exactly; subtracting the 230 billion hours working, Americans spent 770 billion hours in 2012 laboring in the nonconomy.
How to attach a number? Simplifying assumption: output-per-hour is the same in the nonconomy as in the economy, so you just divide GDP by hours worked. In 2012, that was just around $70/hr; multiplied by 770 billion, you discover the nonconomy was $53 trillion in 2012. Let’s use a sophisticated data visualization to compare:
GDP is Gross Domestic Product; GDA is Gross Domestic Awesome.
If anything, this is a substantial undermeasurement, because old people count too! And since by this calculation they don’t work at all, they would be contributing an additional 200 billion hours to the nonconomy, which is another $14 trillion of nonconomic activity:
Just a little perspective on life and the economy on this new-jobs-number Friday.