Long Straight Highway (redux)

What I’ve been thinking about lately is just how little is knowable about macroeconomics in the real world. Does austerity help? Or is it ruinous? Hundreds of people who’ve made this their life’s work say yes. Hundreds of their colleagues, similarly experienced, say no. Questions on the macroeconomic level are absurdly complex because there are millions of variables. Nobody can even list them all let alone control for them.

This makes me think of the brain, the really complicated system that I know something about. And then I think: if the state of knowledge about economics is so shitty, then how can we know so much about how the brain works, since that’s even more complicated? [1] The answer is that at least with the brain we can do experiments. And people have done experiments for a hundred years, of increasing sophistication, on animals and people. (What does early visual cortex do? Let’s stick some probes into a cat and find out!)

The point of an experiment is that you have a hypothesis, you make an experimental manipulation, you see what happens, and you accept or revise your hypothesis. There is almost none of that in macro econ. Almost all data is post-facto, correlational data. And what ‘experimental’ data there is (how does the US economy react to the stimulus package?) has a sample size of 1.

I can’t decide if this makes it really good or really bad to be a macro economist. On the one hand, you really can’t ever know anything, or resoundingly win an argument. On the other hand, you can pretty much not be proven wrong on any opinion that isn’t completely retarded.

[1] Arguable depending on how you choose to define complexity. But you can make a defensible case that brain complexity > world economy complexity.

Brody sent a link to an interesting discussion with an economist who talked about income inequality, its implications, its causes, and who gave some references to what look like some cool stuff. Excerpt:

This [The Race Between Education and Technology] is a really wonderful book. It gives a masterful outline of the standard economic model, where earnings are proportional to contribution, or to productivity. It highlights in a very clear manner what determines the productivities of different individuals and different groups. It takes its cue from a phrase that the famous Dutch economist, Jan Tinbergen coined. The key idea is that technological changes often increase the demand for more skilled workers, so in order to keep inequality in check you need to have a steady increase in the supply of skilled workers in the economy. He called this “the race between education and technology”. If the race is won by technology, inequality tends to increase, if the race is won by education, inequality tends to decrease.

You can read the whole thing here. My feeling is that the crazy gaps — and the change in the rate of gap growth — is cancerous to a democracy; and will, in effect, transform the democracy into some quasi-democracy, which is essentially what’s already happened.

But my other gut feeling is that there might not be any other way: for the same reason that preferential link attachment in networks leads to vastly unequal linkage properties (where the most popular nodes are millions of times more influential than the average nodes), income calls out to income. You might try to dampen what happens at the upper part of the distribution, but in a world with free movement of capital and industry, the issue would just pop up somewhere else. The Republicans always talk about people and businesses chasing the lowest tax rates; mostly that’s bullshit (okay dude, enjoy the Libertarian wonderland of Somalia) but there’s a grain of truth to it.

Anyway, worth a read.