How Technology Adoption Affects Global Economies
In a series of research papers, Associate Professor Diego A. Comin and colleagues investigated the relationship between technology adoption and per capita income. They found that the rate at which nations adopted new tools hundreds of years ago strongly affects whether those nations are rich or poor today.
It's not often that a best seller inspires academic research. If anything, it's usually the other way around. But Harvard Business School Associate Professor Diego A. Comin was motivated by reading Guns, Germs, and Steel, Jared Diamond's 1998 Pulitzer Prize-winning book that explores the historical hegemony of Western Europe through the lens of technology and geography.
"What we showed is that past technology determines current technology."
"It was a nice story, but the evidence was mostly anecdotal," Comin says. "I thought it would be very natural to test that story with my data. I wanted to look at how technology interacts with geographical diffusion."
In a series of research papers, Comin and colleagues investigated the relationship between a country's historical rate of technology adoption and its per capita income. It stands to reason that adopting a new technology would increase a nation's wealth. After all, new tools—from the telegraph to the PC—enable expedited production of goods and services, eventually facilitating economic growth. Technological tools also improve a country's perceived standard of living, as in the case of the light bulb or the cell phone.
But Comin's research is striking in what it shows about the historical reach of technology adoption. According to his findings, the rate at which countries adopted new tools hundreds of years ago strongly affects whether they are rich or poor today. Comin also has begun to uncover why there's still such a disparity in the wealth of nations, in spite of the fact that technology adoption lags have shortened dramatically in the past few decades.
In their paper An Exploration of Technology Diffusion, Comin and fellow researcher Bart Hobijn described a scientific model to track the effects of technology adoption, testing the model on 15 technologies in 166 countries from 1820 to 2003. They covered major technologies related to transportation (from steamships to airplanes), telecommunication (from the telegraph to the cell phone), IT (the PC and the Internet), health care (MRI scanners), steel (namely tonnage produced using blast oxygen furnaces), and electricity. For each technology, they compared when it was invented with when it was adopted by each country: for instance, the automobile was invented in 1885, but didn't reach many nations until the latter half of the twentieth century.
According to the data, countries have adopted new technologies an average of 47 years after they are invented, with the United States and the United Kingdom leading the way in adoption rates over most of the past two centuries. More importantly, adoption lags account for at least 25 percent of cross-country per capita income differences: in short, the longer the lag in technology adoption for any given nation, the lower the per capita income.
Was the wealth of nations determined in 1000 BC?
Further research showed that a region's economic performance in the twenty-first century is directly related to its technology adoption activity as far back as AD 1500. Comin, William Easterly, and Erick Gong explain these findings in their paper Was the Wealth of Nations Determined in 1000 BC?
To prepare the paper, the team compiled a series of data sets on the history of technology spanning some 2,500 years prior to the era of colonization. They measured the level of technology adoption for more than 100 countries in three periods: 1000 BC (pack animals, vehicles, and pottery, for example), AD 0, and AD 1500. They also tracked technology adoption in the modern era.
The researchers wanted to determine whether there was an association between a country's ancient historical technology adoption rate and its adoption of technology in the twenty-first century, reasoning that this could help determine whether ancient technology adoption predicted current per capita income. (To correlate the geographical borders of modern-day nations with the cultures and civilizations of the ancient time periods, the team used maps from the 2006 edition of The World Factbook, published by the Central Intelligence Agency.)
There appeared to be no significant correlation between technology adoption in 1000 BC or AD 0 with the level of technology adoption in modern times. However, the paper states, the data set from AD 1500 turned out to be "an excellent predictor of per capita income today."
According to the research, when a geographical area had a high technology adoption rate in AD 1500, then the corresponding modern-day nation tended to adopt technologies shortly after their invention. However, areas with slow adoption rates in AD 1500 evolved into nations that didn't adopt new technologies until several decades after their inventions.
"What we showed is that past technology determines current technology. The dynamics of technology adoption are very persistent," Comin says.
Extensive vs. intensive margins
While those findings were significant, Comin was puzzled by one apparent paradox related to the fact that technology adoption lags have diminished dramatically in recent decades, across the globe. For example, the United States launched the Adams Power Station at Niagara Falls in 1895, only a few years after the invention of a three-phase power system. India, meanwhile, didn't adopt electricity until the 1900s. But when it comes to modern technology, the lags tend to be almost identical: both the United States and India adopted cell phone technology in the 1980s. However, the difference in per capita income between those nations remains huge: in 2011, the United States had a per capita GDP of around $48,000, while India's was the equivalent of US$3,600.
So why doesn't the shrinking gap in technology adoption lags naturally lead to a smaller disparity between per capita incomes? Comin says the answer lies in the difference between "extensive" and "intensive" margins. In his aforementioned research, technology adoption was measured according to extensive margins; that is, how long it takes a country to adopt a technology at all. But that research did not account for intensive margins; that is, the extent to which a technology is adopted by the nation as a whole.
For instance, the extensive margin of cell phones would measure the gap between the invention of the cell phone and the date when cell phone technology first entered a country. But the intensive margin would measure the number of cell phones in a country relative to that country's population. When applicable, the intensive margin also takes into account the amount of output associated with a new technology, such as the tons of steel produced in blast oxygen furnaces in any given country.
Comin focused on intensive margins in his working paper "The Intensive Margin of Technology Adoption," coauthored with Martí Mestieri. Studying the same 15 technologies and 166 countries from Comin's earlier research, they found that while adoption lags have diminished extensively across the globe, they have not diminished intensively. In other words, while a new technology may reach a third-world country faster than ever before, it's not necessarily reaching the majority of people in that country.
Significantly, they found that differences in the intensive margin of technology adoption account for some 45 percent of cross-country differences in per capita income. "This intensive margin has not converged at the same rate of extensive margins," Comin says. "In fact, it has diverged."
Taken together, the results of Comin's research with Mestieri and the results of his research with Hobijn, Easterly, and Gong suggest that up to 70 percent of differences in cross-country per capita income can be explained by differences in technology adoption.
Comin reports that future research will elaborate on how intensive adoption margins affect growth"We're getting closer at understanding the drivers of technology and its effects on the wealth of nations," he says.