Why is Growth Clumpy, and Should we Attempt to Change Its Clumpy Nature?

In last Wednesday’s post, I ended by saying this, in the context of recent scientific advancements:

But on a personal level, the past year has also taught me this, and I have Morgan Housel to thank for the central insight: the seeds of calm are planted by crazy.3
So when things are really bad and grim (and again, this is not over yet), look to the bright side. And not just because it’s a good thing to do! But also because the bright side is likely to be brighter precisely because of everything else being so goddamn dark.
Tomorrow, I’ll attempt to answer a question I have, and I am sure you do as well: why?

https://econforeverybody.com/2021/03/24/whats-up-with-the-world-outside-of-covid-19/

I didn’t write the follow-up post, not because I forgot to, but because I couldn’t figure out how to think through what to write about. It turns out that I am still not sure! But in this post I’ll try and tell you why I’m not sure, what I’ve been thinking about, and what I’ve started reading to help me think through aspects of growth.

First, I think I’ve understood the central message of Tyler Cowen’s Stubborn Attachments, and agree with it: growth matters.1

Which then begs the question: how should we promote more growth, and more learning?

More learning, for me, means dramatically changing (or perhaps entirely discarding) the way higher education is currently handled, and that’s something to think about for years to come.

More growth, for me, means trying to understand the nature of growth, why it occurs at all, how it occurs, and what factors contribute to and hamper growth. And this topic is, well, a rather large one. It is large in terms of building out an edifice around which I can attempt to learn more about the subject, let alone the actual learning itself.

Here is what I mean by that: when I think about growth, and find myself wanting to learn more about growth, I want to be systematic about the process. If I say I want to learn mathematics, for example, I’ll want to divide, in my head, different branches of the subject. Then learn about the topics, and the mathematicians associated with those topics, and drill down accordingly.

How to do that with growth?

Should we begin by analyzing all of human growth over all of its (available) history? Watch videos like this Ted Talk, go through courses such as this one, and read books such as this one? Or focus on one country/civilization and examine it’s growth over time? Say, the Indian civilization over time? Or modern India, since 1947? Or focus on a group of countries over a period of time, such as say Joe Studwell’s How Asia Works? Or all of the above?

The answer is, obviously, all of the above, but then in that case where to begin?


Hopefully you have been through the same process for different things/projects/concepts in your own life – that feeling of where to start, even?2

Here is how Robert Pirsig helped me understand the answer to that question:

A memory came back of his own dismissal from the University for having too much to say. For every fact there is an infinity of hypotheses. The more you look the more you see.

She really wasn’t looking and yet somehow didn’t understand this.

He told her angrily, “Narrow it down to the front of one building on the main street of Bozeman. The Opera House. Start with the upper left-hand brick.”

Her eyes, behind the thick-lensed glasses, opened wide. She came in the next class with a puzzled look and handed him a five-thousand-word essay on the front of the Opera House on the main street of Bozeman, Montana. “I sat in the hamburger stand across the street,” she said, “and started writing about the first brick, and the second brick, and then by the third brick it all started to come and I couldn’t stop. They thought I was crazy, and they kept kidding me, but here it all is. I don’t understand it.”

Pirsig, Robert M.. Zen and the Art of Motorcycle Maintenance (p. 171). HarperCollins e-books. Kindle Edition.

The brick that I have chosen to begin with is Robert Gordon’s book, The Rise and Fall of American Growth. It is a rather large brick, at 784 pages, and I am only one chapter in, but it is already worthy of a blogpost.

Consider this chart, for example:

Gordon, R. J. (2017). The rise and fall of American growth: The US standard of living since the civil war. Princeton University Press.

The book focusses on the period 1870 through until 2014, and attempts to explain the cause, the nature and the effect of growth on the United States of America for that period. As I said, a rather large brick. And the chart above shows that most of the growth during this period occurs in fact between the period 1920-1970, when measured in terms of output per hour and output per person. Growth went up, in other words, the most in this period.

And what caused this growth?

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Gordon, R. J. (2017). The rise and fall of American growth: The US standard of living since the civil war. Princeton University Press

It wasn’t education-augmented labor, or more machinery, but rather, Total Factor Productivity. Here’s a previous post about the Solow Model, if you want to learn more about TFP.


This, of course, begs the obvious question: why?

Why was growth so very impressive in that period? As a prospective answer, at least in that first chapter, Gordon supplies a hypothesis that we are familiar with here on EFE: Paul David’s essay about the dynamo and the computer.

So quite simply, it takes time for us as a society to accept, internalize and then optimize for a new technology. The invention of a new technology doesn’t necessarily imply its adoption. For example, and this is a true story, we still get invites for faculty meetings at my Institute by hand, not online calendar invites.

And so growth is clumpy for at least the following reasons:

  1. The discovery of a new technology doesn’t necessarily mean it’s immediate wholesale adoption
  2. This is partly because of inertia, resistance to change and the sunk cost fallacy
  3. And it is partly because we as a society simply take time to try and figure out how to make best use of the new technology.

This involves job losses, restructuring, adjustments – and not all of these processes are smooth or even remotely pleasant. The long run consequences of adopting new technology are beneficial, while the short run adjustments are anything but. Focusing on reducing short term pain might well induce more long term pain, but focusing on long term gain is an impractical solution for politicians and policy-makers on the ground, unless a crisis makes it imperative and (at least somewhat) acceptable.

Think driverless cars today (per the link above), or think 1991 economic reforms. Selling either of these things without the crisis of that particular time would have been harder than it already was. As Morgan Housel says, crazy plants the seed of calm.

Leading me to ask myself the question: is growth necessarily lumpy? Might we be worse off for attempting to change it’s lumpy nature? I don’t know the answer to these questions, but they are questions worth keeping in mind as I proceed with Gordon’s book.

  1. As I wrote towards the end of that post, the spread of learning is what I would want to maximize, but that learning contributes towards growth, and more growth leads to more learning, so we’re on the same page for the most part[]
  2. I was tempted to use the excavator/Ever Given meme here. Please congratulate me for resisting the temptation.[]

Notes on “Why Tech Didn’t Save Us From Covid-19”

The MIT Technology Review recently published an interesting, thought-provoking article with the title in quotes above. It was also a little bit one-sided, but we’ll get to that later.

  • The title itself brought to mind Peter Thiel’s quote about being promised flying cars, and being given 140 characters instead. You may want to make a snarky joke about whether 280 characters counts as progress or not, but the point is well taken. And indeed, reinforced by this quote from David Rotman’s article:
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    “In an age of artificial intelligence, genomic medicine, and self-driving cars, our most effective response to the outbreak has been mass quarantines, a public health technique borrowed from the Middle Ages.”
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  • The article then goes on to highlight at least three separate aspects of why tech has failed us: lesser government support for technology and innovation (particularly in the USA), a sclerotic bureaucracy, and policy-making that is not a) proactive enough b) good at managing risks effectively c) far too focused on short-term issues d) aware of the pitfalls of focusing solely on efficiency.
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    Let’s begin with the last of these points:
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  • ““The pandemic has shone a bright light on just how much US manufacturing capabilities have moved offshore,” says Erica Fuchs, a manufacturing expert at Carnegie Mellon University.”
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    I teach courses in international economics at the Gokhale Institute, and one of the fundamental insights that I think students need to walk away with is the concept of a non-zero sum game. Trade makes both parties better off, and therefore more trade is good, is literally the basic starting block of a course on trade. For an excellent summary of this idea, read this article by Paul Krugman, or watch this TED talk by Matt Ridley.
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    But two basic concepts from economics have come to haunt this rather neat idea. One is scale, and the other is the need to diversify. Both are very closely related.
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  • If, conventional theoretical thinking goes, a firm is able to scale up effectively, it will be able to produce more for cheaper. Yes, it is more complicated than that, but that’s the gist of the benefits of scale. Now, think of all countries as firms, and China is the obvious example of a country that scaled more rapidly than other countries, and was able to produce stuff cheaper than almost anywhere else. And that’s how China became the “manufacturing centre of the world”. The more you import from China, the more they scale (and effectively!). The more they scale, they cheaper they can make stuff. The cheaper stuff gets, the more you have an incentive to import from China. And once the loop is up and running, it becomes difficult to stop.
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  • And that’s a simple explanation for how the world ended up putting all of its eggs in one basket. We failed to diversify, because we focused on efficiency, without worrying about risk. What happens if an increasingly efficient global trading order suddenly breaks down? The price of efficiency is two fold: a) a lack of diversification b) not enough risk mitigation measures that allow one to fall back on domestic production. Which is where most of the world finds itself today. Readjusting global supply chains away from China is necessary, but it will not be easy. Especially because most countries will not want to pursue twin objectives: a) diversification away from China into other potential export powerhouses b) some production to be kept at home, especially in crucial sectors such as healthcare.
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    Scale, and a lack of diversification. There’s a lesson in there for us at the individual level as well, of course. A single minded pursuit of some goal (say money, or career growth) at the cost of other things isn’t necessarily a good idea.
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  • “Why couldn’t the US’s dominant tech industry and large biomedical sector provide these things? It’s tempting to simply blame the Trump administration’s inaction.”
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    The truth is always more complicated than you think, and beware simple explanations, but that being said, you might want to read The Fifth Risk. Here’s a slightly tangential review from The Guardian if you are feeling lazy, and a quote from that article follows:
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    “But we’re actually much more likely to die driving to the shops. The fifth risk is something impossible to conceive of in advance, or to prepare for directly. What matters is having a well-organised government in place to respond to these contingencies when they hit – exactly what the Trump administration has failed to do.”
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    No government, or Big Ol’ Central Planner is perfect, of course (and there’s a very readable book about that topic, or here’s a fascinating review of the same book), but Michael Lewis makes the claim that the Trump administration is rather less than perfect even by our less than exacting standards.
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  • “Any country’s capacity to invent and then deploy the technologies it needs is shaped by public funding and government policies. In the US, public investment in manufacturing, new materials, and vaccines and diagnostics has not been a priority, and there is almost no system of government direction, financial backing, or technical support for many critically important new technologies. Without it, the country was caught flat-footed.”
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    The book to read about this topic, if you ask me, is The Entrepreneurial State, by Mariana Mazzucato. Here’s the Wikipedia link about the book. Governments need to play, she says (and I suspect the author of this article would agree), a more active role in fostering the tech ecosystem in a country. Shades of Studwell, perhaps, but I have a counterargument here:
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  • “Incompetence and a sclerotic bureaucracy” is a phrase David Rotman uses early in the article when speaking about the Center for Disease Control in the USA. I find myself in complete agreement with the adjectives used. Why presume, then, that other government departments are likely any better? The truth, as always, lies somewhere in the middle. You can certainly make the case a la Michael Lewis, that the Trump administration took us to one end of the spectrum – but you should beware equally the other end of it!
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  • “Economists like to measure the impact of innovation in terms of productivity growth, particularly “total factor productivity”—the ability to get more output from the same inputs (such as labor and capital). Productivity growth is what makes advanced nations richer and more prosperous over the long run. For the US as well as most other rich countries, this measure of innovation has been dismal for nearly two decades.”
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    Well, yes, sure. And there is more than a grain of truth to the charge laid above, and not just for America. But keep in mind that measuring TFP is really and truly hard, and I am nowhere close to being convinced that we do a good job of it, even for a country like the USA, forget India. I am writing this post while sitting in my bed, using a laptop that allows me to keep multiple tabs (well over 50 right now) open in a modern browser, while being seamlessly connected to an overwhelming variety of news sources. All this while I listen to a Spotify playlist, and sip on excellent coffee that is made using home delivered Arabic beans. I’ll stop channeling my inner Keynes now, but most of this was not possible, especially at these prices, two decades ago.
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    Progress may not be fast enough for our tastes, sure – but it has been taking place. If you would like to read a book with a take contrarian to mine, try this on for size: The Rise and Fall of American Growth, by Robert Gordon.
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  • “The problem with letting private investment alone drive innovation is that the money is skewed toward the most lucrative markets.”
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    Churchill’s quote about democracy comes to mind!
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  • “In a widely circulated blog post, internet pioneer and Silicon Valley icon Marc Andreessen decried the US’s inability to “build” and produce needed supplies like masks, claiming that “we chose not to have the mechanisms, the factories, the systems to make these things.” The accusation resonated with many: the US, where manufacturing has deteriorated, seemed unable to churn out things like masks and ventilators, while countries with strong and innovative manufacturing sectors, such as China, Japan, Taiwan, and Germany, have fared far better.”
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    Here’s is Andreessen’s post, and also, this is your periodic reminder to read How Asia Works. China, Japan, Taiwan and Germany being up there isn’t a coincidence.
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  • ““The great lesson from the pandemic,” says Suzanne Berger, a political scientist at MIT and an expert on advanced manufacturing, is “how we traded resilience for low-cost and just-in-time production.””
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    Options are easy to teach, but difficult to grasp, and even more difficult to implement. See put, long.
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  • “…they are calling for an immediate ramp-up of public investment in technology, but also for a bigger government role in guiding the direction of technologists’ work. The key will be to spend at least some of the cash in the gigantic US fiscal stimulus bills not just on juicing the economy but on reviving innovation in neglected sectors like advanced manufacturing and boosting the development of promising areas like AI. “We’re going to be spending a great deal of money, so can we use this in a productive way? Without diminishing the enormous suffering that has happened, can we use this as a wake-up call?” asks Harvard’s Henderson.”
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    More participation from the government than is currently happening, but throw also into the mix a more venture-capital-ish approach, and don’t forget prizes! In fact, I found myself wishing midway through the article that the author had explored other options, rather than the government-or-markets binary.
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  • I hope I haven’t comes across as overly critical of the article, and my apologies if I have. That has certainly not been my objective. We rely far too much on the private sector now, that is true – and government can and should play a bigger role than is the case currently. But an extreme position, in either direction, always worries me a little!