Bryan Caplan  

Final Reply to Ridley

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Matt Ridley once again graciously responds in the comments.  Our differences appear to have largely evaporated.  Ridley's in blockquotes, I'm not.
But your challenge mistakes my argument. I have not argued that there is no positive correlation of innovation with population, only that, as population size increases, population size alone will become a diminishing influence compared with population interconnectedness. You are trying to push me into a rhetorical box I don't wish to occupy: that at some level population growth stops helping innovation or starts harming it. That may be a case somebody wants to make -- but it's not the case I've argued.
Several of your statements seem hard to interpret any other way, especially: "As for small countries leading the world, I would argue it is almost the rule," and "To have 10,000 people is a lot better than to have 5,000. But to have a billion instead of 500m? I'm not convinced."  Still, if you agree that population is good for innovation, I'm satisfied.
Instead I have argued that bigger populations will always be more innovative, of course. But once populations are large the most effective way to make them more innovative is not so much to make them larger as to make them more interconnected.
Sure, as a matter of policy, it's far easier to remove barriers to communication and trade than to increase the number of humans on earth.  But that doesn't mean that interconnection is "more important" than population, just more policy-sensitive. 
A genetic analogy might help. Bigger genomes get more mutations. But genomes that exchange genes more often -- ie, have shorter generation times -- innovate more, because they throw up more combinations of sequences.
A fine analogy, I'm happy to accept it. :-)

COMMENTS (3 to date)
Nathan Smith writes:

Concerning the genetic analogy, there is a sort of arcane challenge to the "ideas have sex" meme that I got forced into when I was working on the third (somewhat orphaned) paper of my dissertation.

Think about a Bayesian world in which your belief system consists of many theories, each of which makes many probabilistic predictions, and each of which has some subjective probability attached to it.

For example, you might have a theory "grass is green," which predicts that whenever you see lawns of small, soft, thin, pointy plants (in short, grass), they will be green with, say, 90% probability. If you see a field of red grass, that might reduce the confidence that you invest in your "grass is green" theory. If you see a field of green grass, that will increase it. You might have another theory "grass is blue," to which I attach little confidence.

But what if I have a theory that "grass is grue," where "grue" means "green before 1/1/2013, blue after 1/1/2013." All of the data points that support your "grass is green" theory, I consider evidence that "grass is grue," and tending to confirm my confidence that, come 1/1/2013, grass will continue to be grue! You find it odd that I expect all grass suddenly to turn blue next year. I find it odd that you expect it to turn bleen (blue before 1/1/2013, green after) next year.

Now this is a well-known problem in the theory of induction, and it may sound a bit silly, but here's the thing: if "ideas have sex," then "grass is grue" seems like just the sort of theory that idea-sex would constantly be generating. I suspect that this critique, variously reformulated in response to different statements and redefinitions of "ideas have sex," would ultimately prove fatal to the analogy between ideas and genes.

allen writes:

The clear extension of "ideas having sex" is that some ideas are more fit to survive then others.

"Grass is grue" may have as much likelihood, as an idea, of coming into existence as "grass is green" but its likelihood of survival to the point it produces ideas of its own as offspring are pretty slim.

The analogy I'd choose is agricultural.

Two acres of soil will produce more food then one acre of soil, all other things being equal.

But all other things aren't equal so 285,000,000 Americans (1991 populations) out-innovate 293,000,000 Soviet citizens and 1.15 billion Chinese citizens. You could probably make a case for 5,700,000 Hong Kong citizens out-innovating their 200-times more populace neighbor to the north.

Within the context of the argument Simon was making and engaged in - that a larger population was inherently more damaging then a smaller population - , and absent proof or a rationale to the contrary, Simon was clearly correct - twice as many people means twice as many geniuses. Simon was standing in opposition to the view of the Malthusians that a larger population was inherently dangerous and had no redeeming qualities.

I don't believe, as Mr. Ridley seems to, that Simon was saying the more the merrier. Rather, Simon was saying that more people didn't necessarily lead to disaster and, in fact, had certain advantages.

It's Mr. Ridley who's imputing to Simon the view that a larger population is inherently superior to a smaller population and should thus be encouraged. Simon's view, I believe, is that the negative consequences of a large population aren't anywhere near as dire as predicted by the Malthusians and a larger population, in fact, has virtues. That it was a wash in terms of positive and negative consequences.

The extension of that view, that there aren't any clear negative consequences to a larger population while there are clear positive consequences would quite naturally be upsetting to those who believe humanity suffers, especially nations governed by representative forms of government suffer, for not being led our superiors.

That would be the Malthusians who, one and all, see themselves as insightful.

If you're incapable of doubting your correctness, or you're the emperor's fashion consultant, a person like Simon is most unwelcome.

Troy Camplin writes:

The real issue with population is not size per se, but interactive density. A million people spread out over a million square miles cannot be as innovative as a million people in a city. Or, to make it clearer, 20 people in 20 square miles cannot be as innovative as 20 people in a Starbucks, but I suspect 20 people in an elevator are not very innovative at all, either. What matters is interactive density, not mere numbers.

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