How Much Does Money Help With Innovation?

Picture taken on February 2, 2012 in Bruyeres-Le Chatel, near Paris shows a part of the Tera 100 supercomputer.

Photo by ERIC PIERMONT/AFP/Getty Images

Technological breakthroughts in the field of clean electricity production or, say, curing cancer would be extremely welcome. So it’s natural to want to subsidize research in these fields. But Tyler Cowen posted a smart email the other day questioning whether such subsidies are really all that effective. There’s a substantial analysis there at the link, but I’d say the basic point is that hard scientific problems are hard and that it’s pretty rarely the case that direct lack of funds is really the key barrier to progress.

I would only add that similar considerations apply a fortiori to a lot of conservative dogma about taxes.

To the extent that simple lack of money is the key impediment to devising useful innovations, then lower tax rates on capital gains and dividends is key to driving innovation forward. Lower rates will make investment more desirable, freeing-up much-needed funding streams for innovation. But does anyone really believe this? Does anyone think, in other words, that Tim Cook could look at Apple’s balance sheet see how much cash is on it and order up $50 billion worth of innovation? Obviously Tim Cook doesn’t think innovation works like that. Even in terms of a relatively well-defined goal like “build a super-reliable highly scalable set of server-side software services” the limiting factor seems to be something other than money. It’s just really hard to do. Money helps in the sense that it helps a given firm bid for scarce resources, but there’s some kind of objective scarcity of “great ideas” or “brilliant people capable of fundamental technical breakthroughs” that limits how far forward we can go.

Similarly, Farhad Manjoo has a great piece about the seemingly inescapable tradeoff between smartphone performance and battery life. It’s been clear forever that big breakthroughs in battery technology would be very lucrative, but we haven’t really seen them not for lack of financial incentive but simply because people haven’t figured out a way to do it and maybe it’s impossible.

This kind of consideration is also why I think we should be pretty deeply worried about the rise of algorithmic trading. If the supply of people and institutions capable of doing cutting-edge computer science is fairly inelastic, it’s really bad to have a large and growing share of such people working on the Red Queen’s Race of faster and faster trading.