Packing For Perth

In 1953, South Africans went to the polls. The South African government was run by the pro-apartheid National Party, but they were opposed by the more liberal United Party. A majority of white voters disliked the apartheid system, especially wealthy businessmen, and the United Party spent four times as much on campaigning as the National Party.

When the votes were counted, the results were clear: 54% of voters chose the United Party, rejecting apartheid policies. Yet, thanks to gerrymandering and other tricks, the National Party won 60% of the seats. In 1958, the National Party increased their majority despite still losing the popular vote.

Even though it had ‘fair’ elections, with a constitution very similar to Canada’s, the South African government was effectively a dictatorship. It rigged the rules of the game so no one else could win. Faced with an unchangeable government that supported terrible policies, wealthier South Africans did what they could: leave. The best and the brightest, the people who had made South Africa into the richest nation on the continent, started ‘packing for Perth’. Elon Musk – now worth about $7 billion, then just an ambitious teenager – was among them.

There are two options ahead for the US government. Behind door #1, politicians who support unpopular policies get voted out in primaries. (Third parties are not viable in the US due to Duverger’s Law.) If this happens, the government will – slowly and fitfully – move toward the popular position on a host of issues. Politicians, for all their faults, do care about getting re-elected.

Behind door #2, the Democrats and Republicans find a way to block candidates from primaries if they challenge the status quo. This is what John Boehner is currently trying to do with the Tea Party. (I don’t support Tea Party policies, but any kind of reform requires some way for a serious constituency to challenge party leadership, and I support having the latter generally.) If that happens, official US government policies will move farther and farther away from what voters want as culture and demographics change.

In addition, US policies will become ever less effective, as trends continue their progressions and conditions on the ground evolve. When current politicians were elected, in the 1970s, it was viable for the government to not know much about computers. Now, with Obamacare failing due to technical mishaps, it isn’t. It was viable for every student to attend college. Now, with exponentially rising tuition, it isn’t. It was viable for government employees to have defined-benefit pensions. Now, with Detroit bankrupt and all fifty states rewriting their retirement plans, it isn’t.

When that happens, if it happens, Americans will in their turn start ‘packing for Perth’. First in line will be those who can move most easily – the young, the rootless, the skilled but unemployed, the future Elon Musk (South Africa), Sergey Brin (Russia), Vinod Khosla (India), all those who in past decades moved to the US. When voting at the ballot box doesn’t count,  when even voting in the primary doesn’t count, voting with your feet still does.

How Y Combinator Did

“I’m not ready to predict our success rate will stay as high as 50%. That first batch could have been an anomaly. But we should be able to do better than the oft-quoted (and probably made up) standard figure of 10%. I’d feel safe aiming at 25%.” – Paul Graham, March 2007

Seven years later, how have Y Combinator companies done?

YCList names 92 YC companies in the three years between winter 2006 and summer 2008. We can divide them into five categories:

Successful: The company has a large and growing userbase, big revenues, late-stage VC rounds, or other clear evidence of winning.

Product acquisition: The company was bought, and the acquirer keeps selling the product.

Stagnant: The website is still up, but there’s no evidence the company is profitable or has lots of users.

HR acquisition: The company was bought, but the product was shut down shortly afterwards.

Dead: The website is down; the service is no longer available.

Looking at the numbers, we find:

Successful: 12 (13%)

Product acquisition: 6 (6%)

Stagnant: 13 (14%)

HR acquisition: 14 (15%)

Dead: 47 (51%)

This gives us a success rate of about 20%. One notes that the outcome of Paul Graham’s original company Viaweb – a product acquisition – is actually by far the least likely scenario.

Google Can Stop The NSA

Step 1: Get a list of NSA employees, including contractors like Booz Allen. This information isn’t classified, and should be easy for anyone with Google-scale resources.

Step 2: Pick out people in mission-critical roles, like sysadmins, programmers, cybersecurity, etc. Also pick anyone very capable or high-ranking.

Step 3: Look up their addresses online.

Step 4: Mail them all job offers. No interviews, no brain teasers, just a ready-to-sign employment contract.

Step 5: When they join, have them secure Google’s systems against NSA (and other) attacks. After all, they’re the experts.

Step 6: Sit back. Watch the fireworks.

This is completely legal, and the NSA can’t really do much about it.

Spy on Google? They already do that.

Hire new people? Few good programmers will take the NSA’s starting salary of $42,000.

More contractors? Snowden illustrated the problems with this. In fact, the NSA will have to greatly tighten security clearance requirements.

Get more money? Google already spends more every quarter than the NSA’s entire annual budget. Today’s Congress isn’t going to pass big new appropriations bills.

How Long Until Pregnancy?

Time until one expected pregnancy for some birth control methods. Rates are for typical use.

Unprotected: 7 months
Spermicide: 3 years
Withdrawal: 5 years
Diaphragm and spermicide: 6 years
Condom: 6 years
Calendar method: 8 years
NuvaRing: 11 years
Contraceptive patch: 12 years
Birth control pill: 12 years
Depo injection: 32 years
Copper IUD: 125 years
Tube tying: 200 years
Progestogen IUD: 500 years
Combined injection: 500 years
Vasectomy: 650 years
Implant: 2,000 years

The Trouble with Transfer Payments

GDP is a funny number. The simple version is that a government statistics office takes every transaction in the economy, adds up the amounts, and spits out a total. In practice, it’s a bit more complicated.

Suppose Peter buys an apple for $2. This transaction makes Peter happy – if he paid $2 for the apple, he probably got at least $2 of value from it. $2 is added to GDP, and we can mostly assume higher GDP is better: a higher GDP implies more Peters are buying more apples.

The thing we care about, the thing we want to optimize for, is the apple, not the $2. The $2 is just two bits of paper, or a few numbers on a computer. You can’t eat paper; the end goal is sitting down and having a meal, not paper moving around. The paper is just an accounting device. We add up dollars because it’s simpler than adding up apples; apples are of different shapes, different types, different quality, and are of course only one good out of millions, while a dollar is the same as every other dollar (fungibility). The money is a little tag we attach to the apple to keep track of it, like tagging an elephant so you can follow it through the African jungle.

Now, suppose Peter likes his friend Paul, and gives him $2 for lunch. This is a transaction, but it is not counted as part of GDP. There’s no apple; no goods or services are produced; money has just gone from one pocket into another. The economic term for these transactions is “transfer payments”. On a broader scale, if the government pays $1 billion for a new road, this is part of GDP, because a real good or service is produced (the road construction). But if the government writes people $1 billion in Social Security checks, this isn’t counted. It’s just moving money around from A to B; nothing is produced.

So far, all is well. However, it turns out many government programs are de facto transfer payments, even if they have some other nominal purpose. As a real example, suppose the government spends $400 million on new tanks. The tanks are designed, built, tested, and shipped off to the Army, where they sit around in warehouses because the Army didn’t need them. Clearly, in such a case, the government isn’t really exchanging money for goods, since the ‘goods’ are useless.

If you ask a (relatively) honest politician why this happens, they’ll say it’s to create jobs. But people (mostly) don’t want jobs for the sake of having jobs. They want jobs for the money. Hence, what the government is really doing is transferring money to the politically influential, under the nominal guise of purchasing an (actually worthless) product. It’s as if Peter felt sorry for Paul, bought Paul’s plastic apple for $2, and then promptly threw the fake apple away. The real goal is moving money, not the exchange of value. Call these transactions “quasi transfer payments”.

Quasi transfer payments artificially inflate GDP. Suppose that, in 2010, the government spends $1 trillion on roads, $1 trillion on tanks the Army doesn’t want, and $1 trillion on Social Security. In official statistics, the government share of GDP will be counted as $2 trillion – $3 trillion total spending, minus $1 trillion in transfer payments. But a fair accounting would also subtract the $1 trillion in quasi transfer payments. Hence, the real number is $1 trillion, not the official $2 trillion.

This isn’t quite as bad as it sounds. What people are mostly concerned about with GDP isn’t the absolute number of dollars exchanged (the dollar is an arbitrary unit anyway), but how good things are relative to other times and places. If GDP is 5% higher this year, that’s good; if GDP is lower than some other country, that’s bad. If, say, 20% of the economy is quasi transfer payments, this doesn’t affect GDP growth numbers, because the same extra 20% is added to both this year and last year. An economy that grew at 2% will still grow at 2%.

However, quasi transfer payments do introduce some important biases:

- They cause overestimation of the benefits of government spending. Suppose the economy is $10 trillion, 40% government, 60% private. Half of the government’s spending ($2 trillion) is quasi transfer payments, so the ‘real’ economy is only $8 trillion. Now, suppose all government spending goes up by 20%. The new GDP figure is still $10 trillion – $5 trillion government, $5 trillion private – so it’s like nothing changed. However, quasi transfer payments are now $2.5 trillion, not $2 trillion, and so the ‘real’ economy is only $7.5 trillion; things actually got worse.

- They motivate politicians to spend on useless projects. Consider a road from New York to Chicago, to be built next year for $1 billion. This will add $1 billion to the GDP. Now, suppose a senator from Nowhere, Ohio wants to build the road from New York to Nowhere instead. On paper, this will make no difference, it’s still $1 billion added to GDP. However, in reality, the road is now a quasi transfer payment. If properly subtracted from GDP numbers, we’d discover that it makes the country $1 billion poorer, compared to the original road to Chicago.

Highways Are Socialist

Within the US, leftists often cite the interstate system as a government program everyone likes. Which is reasonable enough.

But US highways share the downsides of socialism, not just the upsides. Consider a Soviet breadline. The bread is free, so everyone wants lots of it, and demand exceeds supply. The way to reduce demand is making everyone wait so long that the annoyance of waiting deters them. Hence, long lines. (And this is a deadweight loss; when bread is expensive, at least the bread company gets rich, but a long line benefits no one.)

US interstates have the same problem. They’re free and well maintained, so demand is high. When demand exceeds supply, everyone wastes time in traffic jams, the American equivalent of the Soviet breadline.

If roads were privatized, they’d be pretty expensive, since infrastructure is a natural oligopoly. But from a road company’s perspective, traffic jams are terrible; they hurt the “customer experience” and reduce revenue (traffic jam = no one can enter the road = no tolls). The natural solution is raising prices until demand goes down. And then you’d never have to wait in traffic again.

Standby Costs

Consider an ice cream stand. Like any business, it has revenues (ice cream sales), and expenses (cones, refrigeration, city permits). One can figure what a cone ‘should’ cost by adding up its components – raw materials, labor, utilities. For example, suppose ice cream costs $2 per gallon wholesale, there are 20 scoops per gallon, it takes a minute to scoop ice cream, labor is $12 an hour, cones cost five cents, and the stand itself costs $144 for a twelve-hour day. A two-scoop cone then ‘should’ cost $0.65, and that’ll be the price in a perfectly competitive market.

But we’ve missed one assumption. What if we aren’t scooping ice cream all the time – what if there are dry spells? We have fixed capital costs (the worker and the stand), which have to be amortized over a large number of sales. If there are fewer sales – if the worker, having nothing to do, pulls up a chair and gazes down the wide open road every now and then – the costs are split fewer ways, making each sale more expensive. If the stand is out in the boonies and only makes one sale per hour, that one sale has to cover the whole hour of worker time and stand time, and that two-scoop cone now has to cost $24.45. A large jump!

Standby costs are a large component of many businesses. Restaurants still have to pay rent at 3 PM, when no one is eating. A rural store only gets a few customers a day, making its products expensive. The railroad mostly runs at rush hour, but the trains are around 24/7/365…

One can be very successful by finding new ways of eliminating standby costs. RelayRides, for instance, makes money by employing capital (people’s cars) more hours per year. Ultimately, self-driving cars will do the same, on a much larger scale. And what a bang that will make.


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