This is a neat write-up by Matt Ridley regarding some research done by anthropologists Michelle Kline and Rob Boyd (ungated original paper here). They collected information on marine foraging technology used by 10 different Pacific Islander tribes at the time they first met Western explorers/colonizers. According to Ridley they assigned scores not only for the number of tools but also for their complexity. "A stick for prying clams from the reef, for example, counted as one techno-unit, whereas a bamboo crab trap with a baited lever counted as 16, because it comprised 16 working parts, each a technology in its own right." The actual paper can give you a more detailed idea of the method.

The big take-away is that the higher the population, the more complex the technology being used. Hawaii, with 275,000 people, had seven times as many tools and those were of twice the complexity of those in Malekula, which only had 1,100 people. Further, the size of the network mattered. Island tribes that had more connections with other tribes also tended to have more tools and tools of higher complexity.

This is precisely what goes into our standard models of technological innovation. We tend to say something like $\dot{A}/A = \theta L/A$, so that the growth rate of technology is increasing in population, as the anthropologists found, but decreasing in the level of technology itself. Moreover, that population L need not be limited to a country, but is really the population of those economies that are integrated enough to share ideas. Regardless, the idea that technological change is positively related to population size can seem counter-intuitive the first time you encounter it. But Kline and Boyd's study gives a really nice demonstration of the power of scale. Simply put, more people means more chances for someone to have an "Aha!" moment, and more people tinkering around with existing ideas.

A model like this has the implication that long-run technological change is proportional to the rate of population growth (of integrated economies). In other words, long-run living standards depend positively on the population growth rate. Population growth may instill some drag on living standards because of fixed resources and/or lower capital/labor ratios, but ultimately the positive effect of population growth on technology wins out.

I'm absolutely saving this paper to use next time I teach growth at any level.