1. Stross on development economics (Krugman)
Civilizations are complicated.
That statement ought to be ploddingly obvious to the point of banality, but it’s astonishing how often it seems to elude pundits, politicians, and—yes—science fiction authors.
As Paul Krugman observes, we don’t really know why development economics started working better around 1980. I’d go further: I’m not sure 1980 wasn’t simply a coincidence. All we know for sure is that given access to a sufficiency of tools and ideas, sometimes a nation or group of nations (or a region within a nation—huge parts of China’s interior still remain locked in peasant farming poverty) figures out how to build institutions and infrastructure at a dizzying rate, only slowing when they near the then-prevailing state of the art. (Which itself is moving forward only slowly.)
The Merchant Princes series is to some extent a failed thought experiment in development economics. (I say failed because, for various reasons, the series is probably ending with book six; the scale of the canvas exceeds my ability to do it justice, and the style of the series—effectively a series novel, where each book is a chapter rather than a stand-alone—makes it difficult for me to remember what I’m doing.)
But it’s also shaping up as a morality play about the dangers of blithely walking into a situation and attempting to impose reorganization from the top down.
Miriam’s intervention in Clan politics in the second book (The Hidden Family) generates blowback, with a vengeance, because she’s failed to realize that the changes she is proposing will destroy the power base of a group of elderly women who, through their iron grip on the arranged marriage structure of the Clan, have carved out a tolerable niche for themselves in an otherwise intolerable world. She’s challenging the business model that has made the Clan’s conservative faction wealthy (and as we know, the first rule of politics in any place and time is “don’t be disrespecting the Money”). And she’s provoked them into actions that result in counter-actions outside the Clan, by antagonizing the monarchy and indirectly exposing the Clan’s existence to the US government. Societies, as I noted earlier, are complex: there’s never just one power center, no matter how centralised a culture might appear to an outsider.
It’s all a house of cards, a nest of delicate interlocking dependencies. Trying to introduce change is one way to kick-start the development process; but too many changes, too fast risks generating revolution or civil war, not to mention massive disenfranchisement and deprivation among the general public (as suggested by Klein’s “The Shock Doctrine”).
2. Money makes singularity (Quiggin)
Here’s a confession you won’t hear too often: I’m ignorant and under-educated—especially in economics and finance (but I’ll cop to the arts and languages too, if push comes to shove).
Trying to learn about somebody else’s discipline when you’re an outsider is an interesting experience. The first stage is bafflement, as you’re confronted by a thorny hedge of impenetrable jargon and recursive definitions. The second stage is over-simplification, as, equipped with a Bluffer’s Guide level of understanding of some of the basics, you pry apart the thorny branches and decide that the jargon is, in fact, a Shavian conspiracy against the laity and conceals the essential simplicity of the field in question. And the third stage in learning occurs when you push further into the hedge, and the branches behind you whip back into position behind and impale you on the thorns of your own misconceptions.
I’m a bit like that with money. (It’s probably why I write for a living, rather than being a hedge fund manager.) Because, when you get down to it, I don’t understand money. In fact, I’m not sure anybody does. So I’m going to retreat towards more solid ground and talk about an area where I’m at least able to grasp the scale of my own ignorance: programming.
There’s a paper I read a couple of years ago—I ran across it on the internet, but can’t find it right now—by a couple of eminent computer science academics, discussing the failure of the first fifty years of teaching programming. Fifty years ago, they explained, they could take a class of students and by the end of the class approximately 50% of them would master three essential abstract concepts. (In ascending order of abstraction these are: named variables, loop constructs, and pointers.) The other 50% of the students would flail around, programming by cutting and pasting chunks of code from elsewhere, without real understanding—as could be demonstrated by testing. In the early years of the 21st century, the outcomes are no better: 50% of folks who try to understand programming simply don’t seem to be able to grasp the core abstractions, especially pointer indirection. (It’s an inability I can sympathise with: it took me ages to get my head around what was going on.)
Money, it seems to me, is an indirection layer between barter transactions—a pointer that can reference any number of types of variable (or commodity). You can do arithmetic on money, establish how many oranges are equivalent to a gross of apples, and convert between types! (But don’t be surprised if your conversion of gasoline into lemons fails to fill the fuel tank of your car.) It lets you encapsulate a whole lot of information in a single unidimensional variable. And then …
You hit the third stage of enlightenment and the bramble patch bites you on the ass.
Money is a unidimensional signal: it tells us how much a participant in a transaction is willing to pay for something, but not why. It gives no measure of the internal state of the participant. Direct barter is more obviously amenable to theory of mind, to the participants gaming each others’ inner states—but it works really badly when you’re trying to keep a complex supply chain running. And I can’t help feeling that the unidimensional nature of the information encoded by money is somehow responsible for many of the problems we’ve seen over the past year. Let’s take a random example: Would we have had a housing bubble if houses—real estate bought, used, and sold over a period of decades—was denominated in, call it, “slow” money, accounted for and evaluated over many years and only used in the housing market, which could not be interchanged directly with our everyday “fast” money (profit and loss statements due quarterly, please), used in every other transaction? A second type of money—or, from another angle, money that encodes a different type of information—might have kept the damage from propagating. (Although I’m inclined to think that some brilliant financial super-programmer somewhere would have figured out a way to leverage the slow money in the housing market to build fast money futures, as a way around the barrier. Idiots are ingenious.)
Where was I? Oh: Accelerando.
I began writing Accelerando in 1999, in the middle of the first dot-com bubble. I’d been hired on contract in 1997 to be the first programmer in a start-up. We were writing software glue to allow merchants to accept credit card payments over the internet. Back in 1996, nobody was doing this: by 2000, when I left, it seemed like everybody was in the game. As Tim Berners-Lee put it, five internet years pass for every year in the real world: by that metric, I spent two subjective decades inside Datacash. My job was to write the server-side software that allowed a Linux box to talk to the British banks’ credit card processing systems (which operate completely differently to the US system). I was under a bit of strain in 1999. Our business was growing at a compound rate of 30% per month, and the code I’d originally hacked out as a proof-of-concept demo was now a mission-critical monster that the company was basing its IPO prospectus on.
(I said I didn’t understand money, didn’t I?)
“Lobsters”, the first story in what became Accelerando, was what I did instead of having a nervous breakdown: I bottled up the angst of acceleration and tried to distil it into a novelette, as a way of explaining to outsiders just what it was like to be inside the internet bubble. Then, in 2000, I began writing a sequel story, because I’d left the characters in “Lobsters” dangling over the abyss of an uncertain future. It took me another four years to finish the process—by far the longest it’s ever taken me to write a novel: three decades of internet bubble-time.
If I understood money, I’d be looking at the current economic situation and licking my metaphorical chops. But you’ll have to find someone else to write you the “Accelerando” of the CDS market.