Adam Smith famously illustrated his ideas about how the division of labor created more wealth with the example of a pin factory: Workers could make many fewer pins if they worked independently than if they specialized in single aspects of a pin’s production. The more diverse the activities, the greater the complexity, and the wealthier and more developed an economy would be. More recently, endogenous growth theory has also argued this point. But calculating and charting that complexity has proved to be a very difficult thing indeed, leaving economists with little choice but to simplify.
“Economists have tended to aggregate, to just add up, flip flops with motorcycles, apples with haircuts,” says Ricardo Hausmann, head of the Center for International Development and professor of practice at Harvard Kennedy School. “We believe that with this approach, economists threw out the baby with the bathwater, because the secret of production is in the structure of production, and by aggregating you lose that. But since production is such a messy thing you need to have the tools that let it speak, and you need tools that can handle this.”
These tools have come from the field of network science, a relatively new discipline that examines relations and interconnections and has allowed the authors to create a three-dimensional view of a country’s economic landscape.
Hausmann and Cesar Hidalgo, a physicist who applies his knowledge of networks to economics, first looked at the number of products a country makes and then gradually refined their calculation of that country’s economic complexity by looking at factors such as how common its products were in the global market — T-shirts versus microprocessors, say — and how its product range compared with those of other countries making similar products. The process, which the researchers called the “method of reflections,” lifts flattened aggregates into complex pictures of a country’s economy.
On the simplest measure, for example, Singapore and Pakistan, which make roughly the same number of products, appear similar. But as their relative complexity is explored the countries diverge dramatically: Singapore uses far more capabilities and makes more unique products than Pakistan does.
“Seen from this angle, development is about the accumulation of more complex sets of capabilities and finding paths that create incentives for those capabilities to be accumulated and used,” Hausmann says.
Hausmann and Hidalgo also found that their measurements of a country’s complexity correlated strongly with its per capita income. Moreover, as they looked through 20 years’ worth of data (1985–2005) they found that if a country’s income was below what its complexity suggested it should be in 1985, it caught up in the following two decades.
Mapping a country’s economic structure — what the authors described in an earlier paper as the “product space”— is also predictive of future exports. Understanding which products and capabilities a country possesses makes it possible to see in which direction that country might most productively develop.
These insights have already been put to use in countries across Latin America, Africa, Asia, the Caribbean, and Europe, Hausmann says, although he cautions that it is still too soon to measure the results.
“It sounds on the one hand rather abstract, but on the other it’s super-practical, because it allows a description of economies that was not possible before,” Hausmann says. “This is important information for the private sector in terms of reimagining the possible future. It’s also useful for governments to try to figure out what is preventing that future and what they could do to eliminate the obstacles on the road ahead.” - by Robert O'Neill