Economic growth is generally modeled exponentially. But, what if it was wrong?

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Yesterday the Bureau of Economic Analysis reported that the US economy contracted 1.4% in the first quarter of 2022, the first quarterly decline in GDP since the pandemic hit in 2020.

This is an alarming but ultimately misleading number; most of it is due to changes in international trade (imports, which reduce GDP figures, increased as companies knew the war in Ukraine was coming) and lower inventories held by companies as consumers have purchased. “Final sales to domestic buyers,” which excludes these factors, rose 0.6% for the quarter, or 2.6% annually.

Whichever way you analyze the release, it seemed like the perfect time to discuss the long-term future of growth in the US and the rest of the world. I’m starting to worry about that, to be honest! And I’m worried because of an economics paper by NYU’s Thomas Philippon with the unassuming name “Additive Growth.”

The implication of Philippon’s article is as simple as it is troubling: we should expect economic growth to slow in the long term, and the great leaps forward of the past two centuries may be an aberration.

This conclusion is far from certain and goes against decades of assumptions about how to model economic growth. But Philippon brings a lot of data to his thesis, which makes intuitive sense, and even the possibility of it being true should alarm us.

The big pile of things we know how to do

Philippon’s article is not interested in economic growth per se, but in a key variable to explain long-term growth: total factor productivity, or TFP.

Defining or mastering the idea of ​​PTF can be tricky. Technically, it’s just a residual: the annual TFP growth rate is what you get when you look at annual economic growth and remove the growth attributable to an increase in the labor force (plus hours worked) or capital accumulation (more factories built, more labor). save purchased machines, etc.).

For now, think of TFP as measuring something like “the ability of humans to use labor and tools to do things.” If TFP increases, it means we can get more economic output from the same people and the same things we already have.

This makes TFP the “secret sauce” behind economic growth more generally. Labor inputs may increase, of course, but people can only work a certain number of hours and don’t really want to work also many hours. Population growth contributes to this, but less so when it comes to economic growth per capita, which is undoubtedly what matters most.

Capital accumulation—using more labor-saving equipment and tools—also helps, but there’s not a lot of money to invest. The key is to use the resources you have more efficiently — and TFP roughly measures how efficiently we use our resources. We can become more efficient in the use of our resources through advances in science, business management and other changes.

Economic growth is usually modeled exponentially: our economic output increases by a set percentage each year, and while that percentage varies, it also compounds itself. The PTF is generally modeled in the same way. If you have $100 that grows by 2% every year, that’s exponential. If he only earns $2 a year, it’s linear.

What Philippon is doing is trying to assess whether the TFP Is, in practice, grows exponentially. He first examines two data sets covering TFP in the United States and finds, instead, linear growth since World War II: TFP does not increase by a set percentage each year, but by a whole amount (0.0245 points, if you’re curious) every year. It doesn’t get worse; it grows little by little, steadily. You earn $2 a year, not 2% of an ever-growing stack.

Going back to 1890, he finds linear growth, but with a pause: slower growth from 1890 to 1933, and faster after 1933, but regular and not exponential at each period. He then extends the analysis to 23 relatively wealthy countries, from Japan to Germany to Spain. A linear model works best here too.

Linear growth implies, as Philippon writes, that “new ideas add to our stock of knowledge; they do not multiply it. It also implies a slowdown in long-term economic growth. Or, as Jason Crawford, who writes about the history of science and technology in Roots of Progress, put it, “GDP per capita can continue to grow without limit, but that growth will slow over time.”

How doomed are we, exactly?

The United States and other rich countries have experienced a well-documented decline in productivity growth, especially TFP growth, since around 2004. Philippon’s findings might help explain why. The slowdown is only there if you assume that the PTF should experience exponential growth. If you assume simple linear growth, it’s not that things have gotten any worse over the past few decades. It’s just that they’ve never tasted so good.

This is an alarming conclusion, especially because from the point of view of human history, the last centuries have been very Well. Prior to around the 17th to 18th century, human economies developed extremely slowly. Agriculture showed low productivity growth, meaning there was a fixed population that agricultural societies could support. The standard of living varied mainly according to the number of people present; when the population suddenly declined (as during the Black Death in Europe), people got richer per capita, and when the population swelled, the reverse happened. This is called the “Malthusian trap”.

“Until about 1800, the vast majority of people on this planet were poor,” noted Northwestern economic historian Joel Mokyr. “And when I say poor, I mean they were on the brink of physical starvation for most of their lives.”

This pattern began to break down from the 17th to the 19th century, a process sometimes shortened to the “industrial revolution”, but including a wide variety of cultural, scientific, technological and economic changes. In short: productivity has increased sustainably for the first time in human history. And it’s been growing, by historical standards, quite rapidly, so that a far lower share of people alive in 2022 are on the brink of starvation than in 1800, even though the population needing food has never been as big.

Philippon identifies this break in human history in his article, examining TFP data on England. TFP growth is linear throughout English history, he points out, but the rate of linear growth becomes sharply higher around 1650 and 1830. These “breaking points”, according to him, correspond to the so-called first and second industrial revolutions (the first characterized by textile work and the discovery of steam, the second through mass production, industrial steel/plastic, electricity, etc.) starting with England. I’m less sure than Philippon – the precise timing of the industrial revolution(s) is one of the most debated topics in all of history, and 1650 in particular seems a bit early to date its start.

But if he’s right, it means humanity would need another equally big break to keep economic growth from slowing in the long term.

Philippon’s paper is toned, but I’m not 100% convinced. I agree with Tyler Cowen’s question about the usefulness of treating TFP as a real, observable attribute of the economy.

What is TFP, anyway? It is sometimes abbreviated as a measure of “technological progress”, but it does not really measure technological change; TFP can increase or decrease without a change in technology, and technological changes can occur without affecting TFP. In a 1956 article, the late economist Moses Abramovitz called it “a measure of our ignorance of the causes of economic growth.”

We should try to reduce this ignorance – but how important are changes in the unexplainable share of economic growth? They probably mean Something, but it’s hard to say what. TFP has been incredibly useful for comparing productivity between, for example, firms, to identify which are the most effective and efficient; here, for example, is an excellent article on the productivity of African smallholder farms.

But I’m not sure that TFP has the same explanatory weight to explain the growth of countries over a long period of time.

All the same, Philippon’s article should at the very least open up an important new direction for research. An observer I respect concluded after reading the article that if this is true, it means “human extinction seems much more likely”. I wouldn’t go that far. But this poses an important question, and answering it correctly matters a lot.

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