The Past and Future of Economic Growth: A Semi-Endogenous Perspective is a growth economics paper by Charles I. Jones, asking big questions about what has powered economic growth1 over the last 50+ years, and what the long-run prospects for continued economic growth look like. I think the ideas in it will be unfamiliar to most people, but they make a good amount of intuitive sense; and if true, they seem very important for thinking about the long-run future of the economy.
Key quotes, selected partly for comprehensibility to laypeople and ordered so that you should be able to pick up the gist of the paper by reading them:
“Where do ideas come from? The history of innovation is very clear on this point: new ideas are discovered through the hard work and serendipity of people. Just as more autoworkers will produce more cars, more researchers and innovators will produce more new ideas … The surprise is that we are now done; that is all we need for the semi-endogenous model of economic growth. People produce ideas and ... those ideas raise everyone’s income ... the growth rate of income per person depends on the growth rate of researchers, which is in turn ultimately equal to the growth rate of the population.”
A key idea not explicitly stated in that quote, but emphasized elsewhere in the paper, is that ideas get harder to find: so if you want to maintain the same rate of innovation, you need more and more researchers over time. This is a simple model that can potentially help explain some otherwise odd-seeming phenomena, such as the fact that science seems to be “slowing down.” Basically, it’s possible that how much innovation we get is just a function of how many people are working on innovating - and we need more people over time to keep up the same rate.
So in the short run, you can get more innovation via things like more researcher jobs and better education, but in the long run, the only route is more population.
“Even in this … framework in which population growth is the only potential source of growth in the long run, other factors explain more than 80% of U.S. growth in recent decades: the contribution of population growth is 0.3% out of the 2% growth we observe. In other words, the level effects associated with rising educational attainment, declining misallocation, and rising research intensity have been overwhelmingly important for the past 50+ years.”
“The point to emphasize here is that this framework strongly implies that, unless something dramatic changes, future growth rates will be substantially lower. In particular, all the sources other than population growth are inherently transitory, and once these sources have run their course, all that will remain is the 0.3 percentage point contribution from population growth. In other words … the implication is that long-run growth in living standards will be 0.3% per year rather than 2% per year — an enormous slowdown!”
“if population growth is negative, these idea-driven models predict that living standards stagnate for a population that vanishes! This is a stunningly negative result, especially when compared to the standard result we have been examining throughout the paper. In the usual case with positive population growth, living standards rise exponentially forever for a population that itself rises exponentially. Whether we live in an “expanding cosmos” or an “empty planet” depends, remarkably, on whether the total fertility rate is above or below a number like 2 or 2.1.”
“Peters and Walsh (2021) ... find that declining population growth generates lower entry, reduced creative destruction, increased concentration, rising markups, and lower productivity growth, all facts that we see in the firm-level data.”
So far, the implication is:
- In the short run, we’ve had high growth for reasons that can't continue indefinitely. (For example, one such factor is a rising share of the population that has a certain level of education, but that share can't go above 100%. The high-level point is that if we want more researchers, we can only get that via a higher population or a higher % of people who are researchers, and the latter can only go so high.)
- In the long run, growth (in living standards) basically comes down to population growth.
But the paper also gives two reasons that growth could rise instead of falling.
“The world contains more than 7 billion people. However, according to the OECD’s Main Science and Technology Indicators, the number of full-time equivalent researchers in the world appears to be less than 10 million. In other words something on the order of one or two out of every thousand people in the world is engaged in research ... There is ample scope for substantially increasing the number of researchers over the next century, even if population growth slows or is negative. I see three ways this ‘finding new Einsteins’ can occur …
“The rise of China, India, and other countries. The United States, Western Europe, and Japan together have about 1 billion people, or only about 1/7th the world’s population. China and India each have this many people. As economic development proceeds in China, India, and throughout the world, the pool from which we may find new talented inventors will multiply. How many Thomas Edisons and Jennifer Doudnas have we missed out on among these billions of people because they lacked education and opportunity?
“Finding new Doudnas: women in research. Another huge pool of underutilized talent is women …. Brouillette (2021) uses patent data to document that in 1976 less than 3 percent of U.S. inventors were women. Even as of 2016 the share was less than 12 percent. He estimates that eliminating the barriers that lead to this misallocation of talent could raise economic growth in the United States by up to 0.3 percentage points per year over the next century.
“Other sources of within-country talent. Bell, Chetty, Jaravel, Petkova and Van Reenen (2019) document that the extent to which people are exposed to inventive careers in childhood has a large influence on who becomes an inventor. They show that exposure in childhood is limited for girls, people of certain races, and people in low-income neighborhoods, even conditional on math test scores in grade school, and refer to these missed opportunities as ‘lost Einsteins.’”
The other reason that growth could rise will be familiar to readers of this blog:
“Another potential reason for optimism about future growth prospects is the possibility of automation, both in the production of goods and in the production of ideas … [according to a particular model,] an increase in the automation of tasks in idea production (↑α) causes the growth rate of the economy to increase … if the fraction of tasks that are automated (α) rises to reach the rate at which ideas are getting harder to find (β), we get a singularity! [Caveats follow]”
Oversimplified recap: innovation comes down to the number of researchers; some key recent sources of growth in this can't continue indefinitely; if population growth stagnates, eventually so must innovation and living standards; but we could get more researchers via lowering barriers to entry and/or via AI and automation (and/or via more population growth).
None of these claims are empirical, settled science. They all are implications of what I believe are the leading simple models of economic growth. But to me they all make good sense, and I think the reason they aren’t more "in the water" is because people don’t tend to talk about the drivers of the long-run past and future of economic growth (as I have complained previously!)
Here are Leopold Aschenbrenner’s favorite papers by the same author (including this one).
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