You are currently browsing the tag archive for the ‘GDP’ tag.
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
So these are the three largest components of GDP, all indexed to 1960:
Clearly one of these is not like the others, but the well-known fact that investment, not consumption or government spending, is mostly what fluctuates with the business cycle is very visible. I wanted to dig a little deeper, though, especially to compare the current recession to priors. So I made this graph:
Bars are unbroken periods of percent change in GPDI; their height is the total percent change in the period, their width is the length.
Here it is smoothed a bit using a highly-advanced method called “arbitrary eyeballing”:
And this time with feeling:
While none of these three graphs is perfect, looking at all of them the various recessions we’ve experienced and their depth and breadth become quite clear. And it seems striking that our current mess represents a vastly larger and longer decline in private investment then any prior recession since WWII.
So let’s break down GPDI; the biggest component is the broad heading of “fixed non-residential investment:”
Looking at the log (which is quite often a good idea, see James Hamilton for more) you can see that this recessions seems notably but not dramatically more severe than past downturns, and that we are on a decent track for recovery.
But here’s residential structures:
Wowzers. Two facts worth noting: residential investment has fallen off a cliff and is nowhere near recovering; the so-called “housing boom” is barely visible.
That becomes a little clearer, though, when you look at single-family construction vs. multifamily and “other” (dorms, trailers, etc):
Single-family construction clearly gets a little wacky during the mid-aughties, whereas multifamily is catching up from slacking on trend; since then, multi-family is rebounding while other is wishy-washy and single-family is really terrible.
What’s remarkable about all this, though, is that you can with some confidence say non-causally that recessions are, for all intents and purposes, fluctuation in housing construction.
In the past, we’ve had recessions, interest rates are cut, recession over. Now, interest rates can’t be cut, and we’re not building enough housing, and therefore there’s too much unemployment (especially among the young who are largely the building class):
In fact, relative to older folks, this is the worst the young have had it since the 70s:
Now, why does lowering interest rates reverse recessions? There are many good reasons, but to some extent they’re all about setting expectations. When the Fed “cuts rates,” what is doing is what its doing is just buying lots of government securities, which is what “quantitative easing” is; the difference between the former and the latter is the ends, not the means. The former is a kind of credible expectation setting of broader outcomes – “we will buy bonds until interest rates are where we say they should be, dammit.” The latter sets a much narrower expectation that doesn’t necessarily imply broader changes in the economy.
Now, there is an idea out there that Paul Krugman calls “the confidence fairy,” which he belittles…and he’s right (at least in practice)! As it is formulated by conservative pols and pundits as a partisan cudgel, it basically amounts to a non-sequitur; recessions, ergo, implement the tangential policies we support regardless of economic conditions (derp).
But I’m not sure the confidence fairy is entirely a fiction. In what I think is a bit of a cousin to Steve Waldman’s story of finance as the world’s most important confidence game, it seems like in the past recessions have been alleviated because the Fed creates self-fulfilling prophecies – by buying bonds to depress interest rates, they incentivize individuals to invest based on an implicit assumption about future growth dependent on their investment. And it all worked rather nicely until we hit the ZLB:
The thing that the Fed has fundamentally failed to do is pull their usual trick; they haven’t convinced anyone that the economy will be better tomorrow, so they’re not doing the things today that will create that improvement.
This, in a roundabout way, is where I get to responding to Ryan Cooper’s terrific article making the case for helicopter money. Helicopter money is a good idea. I like it. I support it. It is a humane, fair, and efficient way to help everyone get through hard times. But my gut tells me its not, on its own, enough to kickstart us out of the funk our economy is in. While the biggest reason the 2008 tax rebate didn’t help the economy was its puniness relatively to the impending crisis, it was doubly hobbled by the fact that it was a one-off with no guarantee of being repeated (which it hasn’t, though the payroll tax cut was it’s cousin). Ryan supports giving the Fed the power to mail checks unilaterally, not by implicitly supporting a fiscal-side program, which is a great idea – coordinating the king and the wizard can be a tricky game. But even then, a $2000 check can be extraordinarily helpful in the medium term to people in need, but it in-and-of-itself does not a housing construction recovery make. Helicopter money works best, and may work only, as the whip hand of a credible promise by the Fed of meeting a broader economic target; it can, though, be a very persuasive whip.
Noah Smith mused about a subject I’m interested in – the fundamental conceptual issues at the nature of saving – in a way I like to muse about it – thought experiments – so how could I not deconstruct his post in excruciating detail?
Specifically, I’d like to focus on the economy of his deer hunter (one of many, in his example, but just one for this purpose): a man who lives, alone, in the woods, hunting deer. I’m going to break this down as much as I can while abstracting away the non-deer parts of his economy (shelter, clothing, tools, etc). Because the deer hunter is an economy – and while he might be an economy of only one human, who we’ll call Vronsky -, we can productively and fruitfully view him as a vertically-integrated economy, and break him down into four sectors:
1) A firm that hunts deer. The firm locates as many deer as possible and kills them, then sells them to the next sector. It has most fixed costs (labor to hunt deer) and therefore pays relatively fixed wages, the rest collected as profit.
2) A firm that processes dead deer into venison. This firm always purchases all the deer killed by the first firm, and always sells all of its venison to the next two sectors. It has more variable wages (because it has variable labor as its primary input) and takes the rest as profit.
3) A firm that stores processed deer. This firm always buys all the surplus venison produced by the processing firm, salts it, and stores it until there is a market for it. We will discuss its economy in more detail below.
4) The consumer. It always buys a certain amount of venison (let’s call it C) no matter what.
Now, in actuality, all these firms are the same person – Vronsky, who owns all the firms, provides all the labor, and collects all the wages and profits (which he then proceeds to, largely, eat). But we can break the internal economy of his life away from Williamson-ian integration and imagine a market that works something like this:
There are flush years and lean years – periods, that is, in which D (the amount of deer caught by the hunting firm) is either greater than or less than C. Let’s see what happens in a flush year.
The first firm kills some amount of deer, D, that is bigger than C (we’ll call it C + S). It sells C + S deer to the second firm, pays its wages, and collects profit (let’s imagine the firm breaks even in years when D = C).
The second firm processes all the deer into venison, and sells C venison to the consumer and S to the third firm. This firm always breaks even because its labor varies in direct proportion to its production which varies in direct proportion to the available venison.
Now, the third firm. What should be clear is that the third firm is the closest this economy has to a financial sector – it buys venison when it’s plentiful and sells it when it’s, er, dear. This means it, essentially, stabilizes the internal price of venison (and also raw deer). It also is a very different firm from the other two, since labor is a minimal input – it is a capital-intensive firm that specializes in storage and market mastery (we’re assuming it inherits all the capital, physical and intellectual). Assuming our flush year is t=1, the firm has costs – purchasing the venison, salting it, and storing it – but no revenue. Which means it has to borrow. From whom? The consumer’s wages should always = C, so it must borrow from the profitable sector of the economy – the first firm, who has profited from a plenty of deer to kill. Essentially, the amount of raw deer necessary to produce an amount of venison = C costs exactly the wages of a year’s worth of deer hunting, and the wages of processing the deer into venison are equal to the mark-up of venison over deer, meaning all the profits flow to the first firm – the hunting firm. So it loans the money to the third firm, the storage firm.
This works in reverse in lean years. In a lean year (let’s say t=2 is exactly as lean as t=1 is flush, so C-S) the hunting firm is in the red, since it pays wages beyond it’s revenue. However, it can call in a loan from the storage firm, which has almost no costs incurred but suddenly tons of revenue from selling its surplus! So it can pay back the loan to the first firm. So there are now no net savings, nominally or physically. Balance. Om.
But let’s say there isn’t long-term balance. That creates two potential scenarios – one of long-term scarcity, whose end is obvious and really quite sad for poor Vronsky. But long-term plenty is more…interesting.
If there is long-term plenty, a couple things could happen. If we are speaking strictly ceteris paribus, then we would see larger and larger imbalances between the accumulated bonds of the hunting firm and the accumulated debt of the storage firm, ending in…financial crisis! Salted venison doesn’t last forever, so it would be essentially squatting on toxic assets it would be loathe to revalue without the projected revenue to pay off it’s accumulated debt. It would go belly-up, and basically need its loans forgiven – by which we mean, of course, that Vronsky has to write off a lot of old, stinky venison into the river.
But assuming non-ceteris paribusity, what we would actually see is that, as salted venison becomes plenty, prices decline to the point where no amount of hunting can support the wages of the hunting firm. To skip the boring stuff, what happens is that Vronsky consumes more leisure as he eats down his stock of salted venison and takes up whittling or something.
Now, over the truly long term, endless plenty absent productivity increases is impossible for Malthusian reasons unless you want to assume a Children of Men kind of deal. But even there, we wouldn’t see infinite saving because Vronsky would, sitting on a giant pile of meat, only hunt to the extent he wanted to, not needed to.
The key, in the end, is this – that saving is just as much about production than consumption, and it’s really about the future-orientation of production. In a world where Vronsky is alone, and has no reason to invest in future growth, he won’t endlessly stockpile venison because of diminishing returns and will therefore shift to other forms of spending his time. But in a world where Vronsky was future-oriented, at least minimally, he might spend his savings to create extra time he could use to develop more efficient hunting tools, thus saving even more time in the future. Or he could develop a game that would amuse him. Or he could pack a sack full of salt venison and go on a quest to find a friend, or at least a basset hound.
The real point, in the end, is that nominal savings (which always equal nominal debt) are very disconnected from whether current production is creating value for the future. In the 00’s we simply invested too much of our productive capacity in building overly-large houses in low-cost but low-value locations, which created a lot of nominal debt and therefore nominal savings but didn’t enable the United States to be more productive in the future. On the other hand, higher taxes that built high-speed rail wouldn’t show up as saving, but from the perspective of society, we would be deferring fleetingly pleasurable consumption of movies and candy and craft beer and what have you towards building valuable infrastructure that would make us richer in the future. That’s not nominal savings, and in the short-term GDP looks the same, but that’s true saving in the modern world.
I used to think AirBNB was cool, but now that Thomas Friedman has slurped it in the Times, I’m not so sure. One interesting thing in the piece was how the AirBNB founder confuses his company’s revenue with new economic activity.
Surely most of AIRBNB’s revenues are actually just diversion, no? I’d guess that at least 75% of their revenue is just diverted from hotel/motel revenue.
This is a common mistake. “look how much NAFTA increased trade”, “Look how much the new stadium will boost the local economy” are examples of this kind of erroneous thinking.
Creation vs. diversion is an important and often overlooked distinction.
I just had a great stay in an AirBNB property in Brooklyn, but the Staten Island Hilton Garden Inn lost the revenue that AirBNB generated.
He’s right about Tom Friedman, of course, but wrong about everything else. But wrong for interesting reasons!
The first, and simple reason, is that on the margins AirBNB, by creating cheaper, unique, higher-quality, or differently-located lodging options, may result in more overall travel. I may choose to take that why-the-heck-not weekend trip to FunTown if I know I can book a super-cheap night in someone’s apartment, or stay in the cool gentrifying neighborhood that doesn’t have any formal hotels.
Secondly, and more importantly, it is certainly the case that AirBNB is more often than not “diverting” trips that would have otherwise occurred in hotels. But that doesn’t mean it’s not creating new economic activity!
A house or apartment is capital, a machine that provides a flow of services, primarily “comfortable shelter.” When you own a house, you can choose to consume those services however you want – entirely for yourself, rent them out to others, occasionally donate a share of those services to friends or relatives (for example, my in-laws just stayed with us the past week, and next week a friend is staying with us). However, until recently, was difficult and uneconomical to rent out one’s residence for simply a day or weekend or week because of issues relating to information, trust, payment mechanisms, and insurance.
But these are all problems that AirBNB, a new technology, has effectively and efficiently solved, making renting out a portion or the whole of one’s home like a hotel or B&B go from “extremely challenging” to “extremely easy.” This makes houses more valuable. To quote the master, Paul Romer:
Economic growth occurs whenever people take resources and rearrange them in ways that make them more valuable. A useful metaphor for production in an economy comes from the kitchen. To create valuable final products, we mix inexpensive ingredients together according to a recipe. The cooking one can do is limited by the supply of ingredients, and most cooking in the economy produces undesirable side effects. If economic growth could be achieved only by doing more and more of the same kind of cooking, we would eventually run out of raw materials and suffer from unacceptable levels of pollution and nuisance. Human history teaches us, however, that economic growth springs from better recipes, not just from more cooking. New recipes generally produce fewer unpleasant side effects and generate more economic value per unit of raw material.
Basically, the combination of AirBNB + house = hotel is a new recipe that makes existing resources more valuable than they once were. If AirBNB really takes off, what we’ll see is that, as more people elect to take trips and stay in people’s homes (as my wife and I have done before and will do again, thanks to AirBNB) the existing stock of homes become more valuable, there will be substantially increased efficiency in the hospitality industry and there will be more efficiency in urban land use since the hotel-to-overnight-stay ratio will decline and thus valuable land downtown can be used for other purposes, like offices, residences, entertainment or commerce.
I’m not a shill for AirBNB, but it’s a great example of how the combination of information exponentiation and aggregation economies of scale that the internet enables can substantially increase economic growth and human welfare by making all the stuff we already had more valuable. My wife and I got an espresso maker on Freecycle, so we didn’t buy one. We bought something else instead (probably a couple of board games). So in one sense that was just consumption diverted from one thing to another, but comparing the equilibria that’s clearly a net increase for human welfare. In the pre-internet days, that espresso maker goes to a landfill. Instead, it goes to us. So the original owners are unaffected, the public waste burden is reduced, and we get the espresso maker we wanted and other stuff. Someone else went on Craigslist and bought a board game for $5 that cost $60 new, and used the savings to help buy a new espresso maker. It’s all about increasing efficiency, and just because it doesn’t always increase GDP doesn’t mean it doesn’t increase welfare and, eventually, growth.
Yesterday a friend of mine tweeted an invitation via a new service called Feastly. The invitation was to come to her home and eat a delicious, home-cooked gourmet meal in exchange for money. The service, Feastly, is set up to do exactly that – while it is still in private beta (and therefore cannot be fully-explored until one is invited in) it clearly aggregates offerings of that sort, sortable by dietary restrictions, price, attire, pet-friendliness, and other criteria. It’s a great idea, and one I wish I thought of.
On a social scale, I think as we see more services like this that directly connect buyers and sellers – think eBay, Etsy, ebook self-publishing – it will throw further into question whether statistics like GDP/GNI are useful metrics, not just of broader concepts like "standard of living," but of what they purport to measure. Every meal eaten on Feastly and not at a formal restaurant is one that involves an exchange of goods and services for money, and most of them will likely not be counted by current methods of measuring GDP. This issue predates the internet, of course, but the internet’s amazing power to match small-scale producers to buyers will accelerate this trend, as will the advent of 3-D printing.
So Ashok and I sparred a bit on Twitter re: the meaning and effect of taxation and spending (and probably pestered the heck out of James Pethokoukis and Joe Weisenthal in the process). I’m not sure how to embed Twitter conversations (if anyone knows how, I’m all ears), but the long-and-short of it is that the actualities of taxes and spending are weirdly different from the optics.
The trick is to remember that every policy change is a change from some baseline. So, from whatever the baseline currently is, there is no fundamental or economic difference between:
1) Cutting taxes by X on some activity, and
2) Spending X subsidizing that activity
assuming that they are both funded identically (though identical tax hikes, spending cuts, or debt incursions).
Now, in practice, there will be differences. Scott Sumner’s thought experiment about the society that taxes 100% of GDP by taxing 100% of income then writing welfare checks equal to taxed income demonstrates that, since we would expect that society really would look different than the one that taxed nothing at all (if only because such a program would have some overhead). But those differences would be based in behavioral economics, not classical or neoclassical economics.
And the same in real-world examples. There would definitely be differences between these two alternative scenarios:
1) A 2% payroll tax cut (debt-funded).
2) A check mailed to every American for the exact same amount (debt-funded).
But those differences would be instutional, not economics (the check-cashing industry, for example, would obviously prefer the second policy to the first). But there’s no reaosn to think they would "crowd out" (or for that matter, "crowd in") different activities.
The real point is, as Matt Yglesias says, the tax share of GDP is a very poor to think about the “size of government.”
A simple problem – let’s say the central bank has a 2% inflation ceiling. Ergo, if it records inflation expectations as over 2%, it will take action to lower those expectations, usually raising interest rates as a way of draining the money supply, which also has the effect of decreasing total economic activity. Additionally, everyone knows this, so when some activities or events occur that would ceteris paribus increase inflation expectations markets presume the central bank will act to quash inflation and therefore adjust their overall expectations of economic activity. This will probably manifest itself as a reluctance to invest.
Let’s say unemployment is 10%, inflation is 1%, and real GDP growth is 1%. Let’s further say that the central bank is willing to tolerate an unlimited amount of RGDP growth but refuses to budget on its inflation ceiling. Let’s further say that any activation of idle labor will necessitate some inflation due to short-to-medium-run supply inelasticities. And let’s say everyone knows all of this.
Let’s say some large positive exogenous shock causes a boom in labor demand in some sector or another. This model would predict a largely zero-sum net gain in employment or economic growth, as the increase in activity in that sector will be offset by a decline elsewhere. The only net increase would be that commensurate with accommodating short-to-medium run supply inelasticities – that is, there can be some net gain every period, but only enough that it doesn’t push up prices very much.
Consequently, the Committee anticipates that the unemployment rate will decline only slowly toward levels that it judges to be consistent with its dual mandate.
I always enjoy going to zerohedge for the most intelligent, compelling, and engaging iteration of the sociopathic perspective on events. I was disappointed, however, to see Tyler Durden submit this guest post from Bill Buckler, who is apparently of this publication. Anyway, in the course of writing some positive things about Ron Paul, Buckler writes:
The root of the problem is perfectly illustrated in the fact that since August 1971, the funded debt of the US government has risen from $US 400 Billion to $US 15,236 Billion. The severity of the problem is illustrated by the fact that with Mr Obama having yet to complete his third full year as President, he has presided over $US 4,600 Billion (or almost one-third) of that increase. The root of the problem is the abandonment of money – the final legal connection between Gold and the US Dollar was ended in August 1971. The severity of the problem is the grotesque expansion of what has taken its place.
Of course this is a giant stink bomb of the “correlation
equals causation” fallacy. But beyond that this is a comparison equivalent to comparing apples to zebras. This may be painfully obvious to most people, but let’s examine some other things that happened between 1971 and the present.
Firstly, we went from having 200mm people to 300mm. Secondly, NGDP went from $1.1 trillion to $14.6 trillion. And lest hard-money types wave that all away as ruinous inflation, the Inflation Calculator says that $1 in 1971 is equivalent to $5.32 today, which if you take it purely at face leaves today’s RGDP relative to 1971 at $2.7 trillion, a nearly three-old increase even though population increased 50%, leaving per-capita GDP much higher, which can be confirmed by looking at all kinds of measurements of quality of life in the United States over the last 40 years and seeing them all rise. So we are a much wealthier country now than we have been, and we have experienced a decent amount of inflation, so it makes no sense whatsoever to just throw up the nominal gross national debt numbers from 1971 and today and call it “the root of the problem.”
And look – the debt-to-GDP ratio, which is a very useful measurement since it complete controls for any nominal growth that isn’t reflected in real standards, has tripled! In 1971 it was below 40%, now it’s over 100%! If you wanted to push the idea that we are dangerously indebted (we aren’t, but if you did), that’s all you have to say. You don’t have to make grossly misleading comparisons to prove that point.
FWIW, I’m not even mentioning how deeply unfair this is specifically to the President, who was handed a $500b structural deficit and an economic implosion worthy of the Great Depression by his successor. I’m not sure it’s really possible to stabilize debt-to-GDP in those conditions unless you unilaterally abolish most government functions.