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This tweet from Joe Weisenthal:

Reminds me of a thought I had the other day.

I had this thought when driving from DC to northern Florida, which Mrs. Rooted and I do in a single day when we visit the in-laws, partially because it means we can bring this guy:

i'm sunning

But also because it’s cheaper. And when you’re chugging along 95’s least-compelling stretch for hours on end you think a lot, especially about cars, and especially about how much longer we have to wait until our promised jetpacks arrive. A good amount of attention has been focused on the long-term consequences of self-driving cars for intra-metropolitan transportation, but less has been focused on inter-metropolitan travel. But this is at least equally fertile ground for a major shake-up.

Speed limits are fairly high along southern 95, mostly 65 or 70 mph. It gets even higher out west where things are flat and straight, and there’s a patch of Texas where you can legally go 85 mph. But that’s still pretty slow – less than a fifth the speed of an airplane. But self-driving cars will likely be able to (barring congestion or poor conditions) go much, much, faster. And that can make a huge difference.

When we drive to my in-laws, we drive 774 miles, mostly along I-95, which at an average speed of 70 mph plus just an hour for various breaks is still a 12-hour door-to-door journey. When we fly, the flight is only 2.5 hours to the nearest large airports (Orlando or Jacksonville – they’re much closer to Daytona but flights to that airport are fewer and often more expensive in our experience). But the trip, as Joe points out, is actually a lot longer. If we want to get to the airport with at least 45 minutes to spare before takeoff, we have to leave at least that long before the flight, and that’s if we’re leaving from the closest airport to our home (DCA). Once we land, it takes roughly half-an-hour before we’re in the car heading to our destination, and then it’s at least another hour before we arrive. Adding it all together, the trip is more like six hours, not two-and-a-half. And that’s assuming the plane leaves on time.

To go 774 miles in six hours you’d have to go 130 mph. That’s really fast. But in a world where cars are doing the driving along highways especially designed for that purpose, it’s totally plausible. And what that means is that once self-driving cars are universal they will demolish short-haul flights. So long as road capacity accommodates, flights under two hours in length will likely vanish, and flights under four hours will decline markedly. Shoot, at 200 mph, if no driver needed to be conscious you could leave DC at 8PM Eastern and sleep most of the way across the continent, arriving in San Francisco at 7AM Pacific. Even at 15 mpg and $5/gallon, that’s a < $1,000 trip, which if you’ve got more than two people in the car, is quite competitive; if you imagine that self-driving cars will be much more efficient than that, it’s a almost a no-brainer for personal travel.

This gets us back to the promise in the title of the post. If self-driving cars really do displace short- and even medium-haul domestic flights, a once-scarce resource becomes suddenly plentiful – airport capacity. Assuming energy scarcity is not a crippling obstacle (and if it is we have bigger problems), this should mean a much greater volume of international flights, especially flights across the ocean. If our cars can drive us from New York to New Orleans, then we have more planes, pilots, runways, and fuel to take us to New Delhi.

Cost-benefit analysis is big these days. In broad strokes, it makes perfect sense – policies have benefits and costs, and ceteris paribus the former, properly measured, should outweigh the latter, properly measured. But the words “properly measured” are doing a lot of work. Actually computing costs and benefits are a thorny business. An example I’ve been musing on lately really demonstrates this.

A few blocks from my house, there is a “Wings to Go,” and naturally as a consequence of this chicken bones can often be found strewn about the neighborhood. This is, of course, a huge choking hazard for dogs, such as my dog:

hai

So let’s say I proposed a regulatory ban on the sale of wings to go. Well, a good regulatory agent would go about calculating the costs and benefits. Primary among the costs would be loss of consumer surplus, and if our agent were a god agent she would also tabulate the disparate impact this might have on people based on their socioeconomic status. In terms of benefit, though, you would have to measure “dog lives saved.” How do you value a dog’s life?

Turning to her trusty cost-benefit manuals, our agent would find a very consistent answer – when such information is available, use price data. Therefore, the amount paid for the dog should be a good proxy for it’s market value.

The fee to rescue our dog was $300. You know what else cost $300?

Apple Introduces Two New iPhone Models At Product Launch

Therefore, a market-oriented cost-benefit analysis would judge the death of my dog to impose costs on me equivalent to the death of my iPhone. But if you ask anyone who owns both an iPhone and a dog, that’s obviously insane. I would rather see orders of magnitude more of my physical possessions destroyed then see harm come to my dog. Yet that’s not how cost-benefit analysis would view it.

A lot of criticism of cost-benefit analysis comes from the difficulty of imputing monetary values onto costs and benefits that are totally outside markets, or at least distant enough from markets so as to make assigning them a single price ambiguous, such as the cost to health from pollution. But we should also be skeptical of  using prices to imply value.

And if you were wondering to what extent this post was an excuse to post pictures of my basset hound:

ohai

Mystery solved.

check out my vertical integration. and my beard. and my gun.

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 paribusitywhat 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.

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