In this episode of the McKinsey Global Institute’s Forward Thinking podcast, co-host Janet Bush talks with Chad Syverson. Syverson is George C. Tiao Distinguished Service Professor of Economics at the University of Chicago Booth School of Business. His work focuses on the interactions between firm structure, market structure, and productivity.
In this podcast, he covers topics including the following:
- Why productivity is important
- How the world economy is doing on productivity
- What major themes of our age, from the path to net zero to trade fragmentation and aging, could impact productivity
- The potential role of AI to change the game for productivity
- How productivity growth is diffused
Janet Bush (co-host): So, Michael, productivity is a perennial issue—the endless quest, the Holy Grail—for economists. And today we are talking to one of the experts on this subject. What would you think might be a key driver of productivity in the years ahead?
Michael Chui (co-host): Well, as you know, I do a lot of work on AI, and that has to be in the frame for being a game changer. It is going to be everywhere and have an impact in practically every sector. And my guess is that it will have a profound impact on productivity over time.
Janet Bush: Spot on. Our guest today believes that AI is, and I quote, “the best candidate for a new general-purpose technology we’ve had in decades” and he thinks it could be the key to ending the productivity slowdown we have all been seeing.
Michael Chui: That really interests me. I would like to hear more.
Janet Bush: So, Chad, welcome to the podcast.
Chad Syverson: Thank you. It’s nice to be here.
Janet Bush: So tell us a bit about your journey to becoming an economist. What fascinated you in particular about productivity?
Chad Syverson: I was a mechanical engineering student in college. Like, I think, a lot of high school students who are good at science and math, everyone tells you, “You should be an engineer.” And I liked airplanes, so I thought, “OK, I’ll be a mechanical engineer.”
I didn’t quite understand what a mechanical engineer did, but that’s what I started at, and we had to take principles of microeconomics to fulfill the engineering degree requirements. And I loved it. I loved it so much I decided to take principles of macroeconomics, even though it didn’t matter for any requirement. And I loved that, and so on and so forth.
Eventually, there came an epiphany. February 18, 1994. I heard someone give a speech. I couldn’t tell you what they said today. I couldn’t tell you what they said one year after I heard it, but all I know is I walked out of that speech thinking, “I’m going to be an economist. I don’t want to be an engineer. I want to be an economist.”
And from that point forward, that was kind of my trajectory. I finished my engineering undergrad degree but got a side degree in economics at the same time. I went and got my PhD at the University of Maryland, and now I’m here. This is my first academic placement after my PhD, here at Chicago. And I’ve been here for 23 years.
I don’t think engineering’s completely left, though. We’re going to be talking about productivity today. And I think the whole reason I got interested in productivity as an economist is, I still like to think about how things are put together, so to speak. It’s just the conceptualization of it is different when you study productivity as an economist than when you’re actually thinking about design and production of physical products as a mechanical engineer.
Janet Bush: A lot of people would see economics as terribly boring and a black box and a complete mystery. What was it that spoke to your soul?
Chad Syverson: At first, it was like a fascination of how the discipline took what I thought were intuitive things—like, “Oh, if this is true, then you would think this, then you would think that,” and so on—and actually formalized it.
So when I saw supply and demand and how it works, it’s like, “Oh, yeah. That’s totally it.” That boils down things you think through and hear people talk about in a way that’s really crisp and useful. So I liked that, initially. But the more I learned about it, it was just, like, “This is just the best framework for understanding the world with the fewest moving parts,” you know?
It doesn’t explain everything, but boy, it explains a lot. Both how people act and how organizations and companies act. That’s what I love about it. It’s just the best way. I want to know about the world, and I wanted to learn the tool kit that I thought would be the most useful for it. And that’s economics.
Janet Bush: When I was an economics journalist, I used to say, “Economics is about life, it’s about everything. So you should be interested in it.” So why is productivity important?
Chad Syverson: Well, there are two answers. One is, at the micro level, if you’re a company, productivity is one of the best predictors of the fortunes of your business. So just a fact: If you look at any even narrow-slice industry or market, you’ll find big differences in productivity across the businesses that operate within that.
And what people have found in thousands of studies now, and basically without exception, the more productive businesses are much more likely to survive. They’re more likely to grow faster. If you want to be a successful business, you need to be a highly productive business.
It’s also good for workers. Workers at more productive companies get paid more. It’s good for consumers. Consumers who buy products from more productive companies tend to pay lower quality-adjusted prices. So productivity is good for kind of everything on the business side of things. That’s the micro level.
And then the macro level is where the importance really kicks in, because we know productivity growth is the only way we can get sustained increases in material well-being. You cannot get increases in, say, GDP per capita over the long run without productivity growth. It’s that simple.
And it’s quantitatively one for one, so if productivity growth slows down by 1 percent a year, you should expect GDP per capita growth to slow down by about 1 percent per year, and vice versa if it speeds up. So both the existence of increases in material well-being and the rate at which they increase are determined by productivity growth.
Janet Bush: There’s a perception that productivity means efficiency and lost jobs. I remember somebody said to me, “Oh, productivity—you’re fired.” Unpack that for us.
Chad Syverson: That is an example of the fallacy of reasoning causality from an accounting identity. There are many specific ways to measure productivity, but they’re all basically ratios of output to input, how much comes out of a production process divided by how many inputs go into it.
And the notion that you’re describing with that person’s comment comes from looking at that definition and thinking, “Oh, that’s how you causally affect productivity. So OK, I want productivity to be higher. It’s outputs over inputs, so if I make inputs smaller, productivity will go up.”
Well, the problem with that is—and this is true whenever you reason from an accounting identity—it’s not just inputs that are changing when you decide to cut inputs. You know, those inputs are doing something, presumably, and you’re going to affect what they’re doing if you try to cut those inputs, like, say, workers or worker hours.
And that might be useful stuff that makes output. And it’s quite possible you could actually reduce output even more than you reduce input, so therefore, your productivity actually has gone down.
It’s kind of interesting. You know, I totally understand sort of the sentiment behind what that person said. I hear it a lot, but it’s usually in that direction, the messing up the identity for causality. Because if someone said, “Oh, I need productivity to go up, I know what I’ll do, I’ll just make more output”—if you said that to someone, they’d say, “OK, what magic wand do you have that lets you wave and get more output for nothing?”
Because everyone recognizes, well, if you want more output, you need more inputs, too, et cetera. But somehow that doesn’t quite always become as obvious when someone does the inverse, which is, “Well, I’ll just cut inputs, and of course productivity will go up.” But as I said, that’s not the only thing that’s going to change when you do that.
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Janet Bush: I like that. So how are we doing on productivity? MGI’s recent report, which is about investing in productivity, said that over the past quarter century, median economic productivity had jumped sixfold. But then there were huge variations, so emerging economies did very well. They were in the fast lane. They’re catching up with advanced economies, maybe in the next 25 years. But then, in advanced economies, productivity is stagnant. There are slow-lane emerging economies. So all together, how are we doing?
Chad Syverson: I think, more recently, not so great, to be honest. Over the long, long haul, we’ve got reasonably good data in the USA going back about 130, 140 years. Labor productivity, output per worker, per worker hour goes up by, roughly speaking, an average of 2 percent per year.
But there are big sort of long cycles of acceleration and deceleration, so periods where it’s above it, periods where it’s below it. And it’s been pretty clear in the US that since the mid–2000s, we’re in a productivity growth slowdown.
It’s been somewhere between 1 and 1.5 percent per year, which is below the long-run average and even trending more towards the bottom end of that, so closer to 1 percent per year in the late 2010s, say. It’s not just in the US, so basically the world overall, most countries at all income levels experienced a productivity growth slowdown over the past decade, decade and a half.
From different levels. As you mentioned, different economies tend to have different average productivity growth levels. But everyone’s seeing the slowdown from the average over the last ten, 15 years. And that’s really been, I think, for the people who pay attention to the macro end of productivity, that’s been the thing that’s gathered the most attention from us. It’s, like, “OK, why did this happen?”
Just to give your listeners a quantitative sense of what that means, in the US, productivity growth between ʼ95 and 2004, before the slowdown started, was about 2.9 percent per year. So we’ve experienced a productivity slowdown of about half.
Which means, like I was saying before, the relationship is about one to one with GDP per capita growth. So if you experience a labor productivity growth decline of 1.5 percent per year, that implies about a 1.5-percent-per-year slowdown in GDP growth per capita. You sustain that over 15 years, and now you’ve got a real gap in what your GDP is versus what it could’ve been. And if you run out the math on that, it’s easily over a third of GDP right now.
That is to say, had productivity growth not slowed down, US GDP would be about 35 percent higher than it is right now. So it matters. One year of a slowdown is one year, but you stack it up year after year after year, like we’ve been experiencing—“we,” the world, really—it adds up to something quite big.
Janet Bush: So, as you say, a lot of work is going into the reason why. What’s your theory?
Chad Syverson: Well, I think there’s a couple things going on. One is that the acceleration that we saw in the late ʼ90s, early 2000s, I think, was the first IT wave sort of coming to fruition. Businesses really started to figure out at a high clip how to use IT technologies to change what they were doing and to do what they were doing better.
And so there was that period of gathering the low-hanging fruit, so to speak. And I think that naturally worked itself through the system, and what didn’t come quite as readily is the next thing to do with the technologies.
Now, it’s been really transformative over that 15 years and some narrow-slice businesses—you think about media and stuff like that, it’s greatly affected that—but just broadly speaking, it hasn’t diffused through as much of the economy as it did in the early IT period. So I think that’s the biggest thing. I don’t have a short story of why the fruit stopped there. I think it’s probably multicausal and multifaceted, but I think that’s the biggest thing.
Something I’ve written about lately is that there can also be a period when new technologies arise where you actually get slow measured productivity growth. And so, the technology can be present. It can be being placed into service by businesses, but you don’t actually see it in the productivity numbers.
Now, I don’t think—and we actually ran through the calculations in our studies on the issue—that’s not the cause of the productivity slowdown, but I think it’s something to keep in mind as we look at the situation now and going forward.
Janet Bush: AI is on everybody’s minds. And obviously it’s not diffused enormously widely, but it is beginning to diffuse. Is that a game changer, do you think?
Chad Syverson: I think it can be. I will say, I think it’s the best candidate for a new general-purpose technology we’ve had in decades. And it’s made me more optimistic that we will end the productivity growth slowdown than anything else that’s happened since I started looking deeply at the slowdown ten years ago. So, yeah, I’m on the optimistic side.
I think it has amazing potential. As you say, it hasn’t diffused that widely yet, but the early returns, so to speak, I think are quite optimistic. And one can have fun imagining all the potential gains that could come from applying AI tools in a number of different situations.
Janet Bush: What sectors do you think might see the biggest gains?
Chad Syverson: That’s a hard one. And I’m not just punting because no economist wants to be pinned down on predictions, but that’s a little bit of it. But one lesson of general-purpose technologies is, their full effect comes when they’re put together with complementary investments, often intangible.
It’s not usually the direct replacement effect that drives the productivity gains. It’s these complementary things. What that means is, you wouldn’t look at AI and say, “Oh, what does AI do?” “Well, it predicts text, so I’m going to go look and see where text prediction would be the biggest thing.”
OK, if you’re a lawyer and you’re writing briefs, you’re not going to do that anymore. That all may happen. I’m not denying that’s going to be part of what AI does. But I think the biggest things and the broadest things that AI could do, we haven’t really fully grasped yet, because it needs to be put together with other stuff that’s currently being invented and created.
My guess is, the biggest, the most affected sectors, we don’t really know yet. And we might be surprised actually by quite a few of them. Now, if you want to say, “What things are going to be affected the earliest?,” then it is going to be the direct replacement stuff like I was talking about. But the biggest effects, I think, it’s really hard to pin down, and we’ll have a better idea ten, 15 years from now than we do now.
Janet Bush: MGI did some work on the link between intangibles investment and productivity, and one of the interesting things that came out of that was that it’s not just the investment in digital or intangibles or whatever. It’s the way you manage it. It’s the managerial skill that’s twinned with that. That sounds to me very much what you were saying.
Chad Syverson: I totally agree. In fact, I would classify the managerial skill, talent, processes as intangible inputs of a business.
You know, I mentioned those big productivity differences within even narrowly defined industries before. Even before AI was around, we have good evidence that some of those differences are caused by differences in management practices, manager skill, et cetera. I view that as an intangible that is paired with technologies like AI, and the quality of that pairing is going to matter hugely for the productivity effect.
Janet Bush: When you look at general-purpose technologies from the past and AI, are there big differences? Is there a timing difference? I mean, can you guess how it’s going to roll out and what the macroeconomic effect is going to be?
Chad Syverson: We know a little bit, so we did some calculations. This is work I did on what’s called the productivity J-curve. You get this period of initial undermeasurement of the true productivity effects of new technology, and then, later, overmeasurement.
This is work I did with Erik Brynjolfsson and Daniel Rock. We did some calculations treating existing technologies, kind of going back in time and supposing, “Oh, here comes this new technology. We’re going to pretend like it’s got this AI sort of effect going, where you’re not going to fully see it early and to compute exactly what you ask.”
Like, how long does this stuff take for it to work through this measurement issue? And the answer is, we looked at computer hardware, computer software, and R&D spending in general. In each of those cases, the answer is decades. You can have a period of undermeasurement that’s ten to 20 years long. And then, of course, the overmeasurement period on the back end can last just as long.
The size of this undermeasurement varies over that period. So it might be five to ten years before you hit bottom of the undermeasurement, and then you start coming back in the other direction.
But the point is, you can go pretty long periods of time where the technology’s out there, it’s being installed, it’s starting to be used, but you’re still not seeing its full effect reflected in the productivity statistics. And we talk about historical examples, Solow’s famous comment that he saw the computer age everywhere except in the productivity statistics. That was exactly that phenomenon.
And then there are other examples, going back in history even further, of periods where the technologies are commercially available and they’re starting to be used, but you don’t see it in the productivity stats yet. This can go on for a period of multiple years.
Janet Bush: I think that there’s a general agreement that AI has massive potential. But you’re not going to see that in the productivity numbers, so is that leap of faith mean that we’re not going to invest enough?
Chad Syverson: I don’t know. I mean, that’s a good question. Like, do companies look at the productivity statistics when they’re making their investment decisions, or do they have a more sort of ear-to-the-ground feel for the true effects? I think it’s a little more the latter.
The problem is, it’s hard to aggregate up those ears to the ground for people who want to measure what’s going on economy-wide, so you can tell stories about specific companies, like, “Oh, it’s not in the productivity numbers, but look at that company, how transformative the technology has been there.” That can be true. If you can quantify that across all companies and add it up, you’d have a nice alternative to the official productivity statistics that might help you see things better, but that’s super hard to do.
So to answer your question more directly, I don’t think the mismeasurement is going to cause too much of a malinvestment problem or a misallocated investment problem. But I think it’s going to be hard for those of us who track the total effects of these one-by-one investments. It’s really going to be hard to know what’s going on.
I should be a little careful. The undermeasurement problem means an undermeasurement; doesn’t mean it wouldn’t show up at all. I mean, it could be that the true productivity effect of AI ends up being an acceleration in the productivity growth of one-and-a-half percent per year, but you’re only going to see 0.8 percent per year or something in the actual statistics. So it’s undermeasurement, but you might still see a bump in the actual stats.
Janet Bush: Going back to the “where is productivity growing” question, do you see any sign of the slump ending? Is there any evidence that things are beginning to pick up, with or without AI?
Chad Syverson: Yes, a little. If you just look at, say, in the US numbers, quarterly output per worker, the last year’s been pretty good. We’ve, well—zoom back. We’re on this trend. The trend wasn’t great, OK? What happened through COVID is, actually, we went well above trend, huge acceleration in 2021 and then flattened out, then came down and now have accelerated again.
Now, that whole process basically created a wave that got us back to the trend we would have been on had COVID never happened—which, again, wasn’t a great trend—but we’re back on the trend. That COVID volatility was basically, I think, a lot of composition- and utilization-affected stuff. Things that tend to happen to productivity statistics in the business cycle. It’s not, quote, “real,” it’s just noise measured because of how we actually measure stuff.
But, and here’s the but, the last year and a half, to get us back to that trend on the back end of that wave, now that we’re at that trend, the next year’s going to be really important, because it’s going to be, “All right, are we going to flatten out back on that discouraging trend we were in, in the 2010s, or are we going to continue accelerating through the trend?”
Because right now, the last three quarters have been well above that trend growth rate. And I actually am a little thinking the latter, because of some other data. So what’s been going on—and this is another trend that’s been parallel to and may be somewhat connected with the productivity growth slowdown—is there’s been a long-running decline in measures of dynamism in the economy, especially in the US, but throughout much of the OECD.
What do I mean? Total labor turnover, people leaving jobs and getting new jobs, for example. Business formation. How many new businesses are being created every year? Those things have been on a long-run decline, and when I say long run, I mean, back to the ʼ80s at least. OK, so there have been 30, 40 years of slowdowns in measures of dynamism. And some people were saying, “Well, maybe this is tied to the productivity growth slowdown.” Like, these chickens are coming home to roost.
Well, what’s happened since COVID, as we’ve emerged from COVID, those things have turned around. After decades of decline, labor market dynamism accelerated again. Business formation in the US is up one-third. One-third more businesses are being formed per month now than were in 2019.
This isn’t just folks who are tired of the office life starting a consulting company in their spare bedroom. If you look specifically at what are called high-propensity businesses, or businesses that at foundation have features that we know predict hiring and growth for those businesses in the future, those are also up a third.
So it really does look like there’s a reinjection of whatever the secret sauce is that creates a dynamic economy in the last several years. And I think that that’s what makes me encouraged that the last three quarters of pretty fast productivity growth might continue. We might actually accelerate through that return to trend, rather than just stop at the trend.
I don’t know if that stuff has anything to do or a lot to do with AI one way or the other, but I view it as sort of a second piece of evidence, aside from the specific productivity statistics, that makes me optimistic about the near run at least.
Janet Bush: In the US, what do you think the secret sauce is that has caused this uptick in these indicators?
Chad Syverson: Honestly, I don’t know. If I had to say something, it might be optimism about AI or other new technologies, you know, biotech and stuff like that. There’s been a lot of investment in manufacturing lately, especially tied to the energy sector, so it might be a little of that as well. But I’m kind of just guessing. I’m not sure, and I don’t know if anyone’s really pinned it down in a way that I thought was specific yet.
Janet Bush: Is there an element of sustainability innovation, do you think?
Chad Syverson: You mean, environmental sustainability?
Janet Bush: Yes.
Chad Syverson: I think the only way we’re going to achieve climate goals that have been set is through innovation. I mean, that’s the only way forward. We have to innovate our way out of it.
I think it’s already happening. You look at the advances that have been made in solar and battery technology in the past ten years. They’ve been amazing and basically unpredicted by the experts. So now that we have to, I think, reduce barriers to installation, that’s a real issue, I know, in the States and in some other countries, too.
But, yeah, I think innovation is the key to achieving sustainability. That’s the only way we can do it.
Janet Bush: I was just thinking, because America has put a lot of money behind green tech, so that’s why I asked the question, I was thinking that that might be one of the ingredients of the secret sauce.
Chad Syverson: Could be, yeah, I agree.
Janet Bush: And what about other countries? We have talked about the US, but is the picture very different in Europe, for example, or China?
Chad Syverson: It, unfortunately, does seem to be a little different in much of Europe. China, it’s hard to know. The data are perhaps not as reliable as, say, other OECD countries. But if you look at Europe, the UK in particular has kind of had the same sort of slowdown, but quantitatively it’s been perhaps as deep as it’s been anywhere.
And unlike in the US, where you get this volatility over COVID and then this reacceleration in the last year or so, you haven’t seen that in the UK. You haven’t seen that in a lot of the European OECD countries, which raises, I guess, the issue of causality. Again, what’s going on? What part of the secret sauce here isn’t there? Is it that AI is not moving things as much there as here, or is it other stuff that we’re talking about, with green tech, et cetera?
I don’t know the answer, but it is true that what you see in the US statistics is not shining through so brightly in European countries.
Janet Bush: Our recent research suggested that higher inflation and interest rates could actually encourage productive capital allocation and therefore, ultimately, higher productivity growth. Do you buy that?
Chad Syverson: You know, I like the story. The higher the interest rate is, like, “OK, you have a higher hurdle rate now, and so only really good investments are going to be made,” et cetera.
I’ve actually got some colleagues here who looked a lot at businesses’ actual hurdle rates, how they set their hurdle rates, et cetera. And it turns out they’re way higher than market interest rates, and also they don’t move that closely with market interest rates. So while I like the theory, I’m not so sure on the empirical side of movement from, say, 25 basis points fed funds rate up to 450 basis points is going to greatly affect the actual hurdle a company uses. Maybe it will a little, on the edges.
The inflation thing, actually, I had this idea long ago that inflation hides inefficiency. Like, you can get away with just raising prices when your costs go up in a high-inflation environment. But in a low-inflation environment you can’t, so you have to figure out how to keep your costs down.
I tried to test that in the day. I couldn’t find any evidence of it, so I’ve been a little skeptical about that particular thing ever since I went and dug for it and couldn’t find it. But it could well be my own incompetence that kept me from finding it.
Janet Bush: Surely not.
Chad Syverson: Oh, give me a chance. I can be really incompetent.
Janet Bush: One of the other themes of our times is what some people call deglobalization or the fragmentation of trade. And if trade relations were to reconfigure and fragment, that could have an impact on the flows of technology and IP and all the rest of it. Do you see that as a factor in productivity going forward?
Chad Syverson: Yes. I think it could be. I think, I don’t know if it’s a “for everything.” I think it’s a process that could play out over five, ten, maybe 15 years. But surely those involve disruptive costs, just adjustment costs of any type when you reconfigure a production chain.
So, yeah, I think there could be productivity effects to that. I’m not sure how big they are. I sort of view it at the same time as companies might be acting like they’re willing to pay somewhat higher costs to have a reconfigured supply chain, in exchange for, basically, insurance. Like, that certain political economy events that might happen would be less costly in the future if they do this reconfiguration now.
Basically, I think, you could justify it as paying an insurance premium. We’re going to have a new kind of production chain with slightly higher costs, but in exchange, volatility that might exist in the future will be reduced.
That’s kind of how I view the trade-offs that any company could look at. Also, from a macro economy standpoint, you’d want to value that insurance value. The problem is, it’s really hard to actually do that in the numbers. It’s hard to see what didn’t happen. But nonetheless, conceptually, I think that’s one useful way to think about it.
Janet Bush: Casting around for other themes of our age that might have an impact on productivity, we’ve touched on the net-zero transition. You mentioned energy costs. How does that play into it?
Chad Syverson: If you want to get really speculative, I talked about the productivity slowdown now. The last worldwide productivity slowdown started in the mid-1970s. In fact, it’s pretty sharp—1974, specifically, it seemed to be. Now, is that coincidence that it was just after the oil crisis and the price of oil tripling and the price of energy in general going up very quickly?
I don’t know. It could be. Some people speculated one way or the other, but, you know, energy is an important input into a lot of stuff. And if it becomes cheaper, you might think a lot of things can happen more economically than it did before.
It’s sort of interesting. It seems important, seems to go into everything, but if you look at, say, the expenditure share, the fraction of revenues that manufacturers spend on energy, it’s like 2 or 3 percent. And so you’d say, “Well, that’s not that important.”
But you know, that 2 or 3 percent isn’t very substitutable for other stuff. You can switch one supplier of widgets for another, but in the end, you kind of need energy. What are you going to substitute for energy, right? So while it might not be a great share of expenditure, it might be a very important cog in the wheel.
If you make that cog really cheap, the wheels you can attach it to could get quite big. I think that would be the story, where energy is sort of a linchpin for productivity growth. Do I know that’s the way the world works for sure? No, but I think that story is alluring.
Janet Bush: In the last of our speculative themes that I was thinking about, aging, do you think that that’s a factor in productivity?
Chad Syverson: There is some evidence that demographics of a country actually affects its business formation rates. We were talking about that, and some other—not just the amount of investment but the direction of investment. If you have an older population, businesses invest in things that are targeted at an older population, which can have different knock-on productivity effects than investments made to serve a younger population.
So there is some evidence that that matters. How big is that right now? I think it varies across countries. Obviously, different countries have different demographic profiles. Do I think that was a big factor in the worldwide productivity slowdown? I’d be surprised if it were, but it might be one more thing adding to the top of the pile.
I think we’re all going to find out, because it’s pretty clear from birth rates that most countries are going to see aging of their population over the coming decades. So that’s definitely one thing I’m going to be keeping an eye on as I age in my own job.
Janet Bush: It was interesting, we did some work on the future of Asia, how Asia’s doing, and we made the observation that productivity had been soaring, or doing pretty well, we think, in China. But China is aging, and Japan, South Korea.
And so that productivity needs to be replaced. Those workers need to be replaced by workers in countries in Asia that are less productive. And therefore, you have a double problem. You’ve got to switch the labor, and that labor is low productivity, say, in India, for example. Is that something that you recognize?
Chad Syverson: It makes sense to me. I haven’t looked at it in my own work, but I can see how that could happen. I think it is happening. Whatever effect it has, what you describe is going on.
We’re seeing—you talked about the reconfiguration of supply chains. You’re seeing things move out of China into Vietnam, into India, two big destination locations. Some here in North America, to Mexico. So yeah, that’s going on, and the question is, how big is it? And then how long is this sort of adjustment process going to be?
You would expect those workers in, say, Vietnam or India to become more productive over time, just as they did in China when China became the major manufacturing center it is now. But the issue is, how long does that take?
Janet Bush: I just wanted to touch on how productivity diffuses. Have you done some work on that?
Chad Syverson: I haven’t done a ton. I’ve done diffusion, sort of, inside a company. But we know—we, the academic researchers who look at productivity—there are spillovers across companies. It’s been identified in a lot of different settings, different kinds of industries, different countries, et cetera.
And you do find evidence that, especially, large companies that tend to spin off a lot of workers, which themselves will start to spin off companies, et cetera, we know that certain industries basically evolved that way.
You look, going back historically, at automobiles and tires. You had one big fount from which the whole industry sprung, and you can see that more recently in certain parts of the tech world as well. You know, the alums of a particular company go off and basically create a whole industry from scratch.
We know those spillovers exist. We know a little less about the particular mechanisms. Sometimes it’s workers leaving, starting their own businesses. Sometimes it’s conversations where no one ever leaves, but knowledge somehow gets out of the company one way or the other.
Sometimes it’s very local, the spillover. Sometimes it’s much less local. The particular mechanisms can vary, and we don’t know the nuts and bolts—sometimes literally the nuts and bolts—details of how that diffusion happens, but it’s clear that it does. And that certain companies have outsize influence on the future trajectory of an industry than others.
Janet Bush: And just on the public sector, I mean, that is a bit of a black box in terms of measuring productivity, I believe. But the general assumption is that productivity in the public sector is lower than in the private sector. Is there hope for the public sector? And where will that come from?
Chad Syverson: Let me start with the end. Yes, there’s hope. Where will it come from?
Let’s take a step back. The really difficult thing in general with public-sector productivity is, what’s the output, right? And that’s true for some private sectors, too. Like, define the output of the insurance industry. Well, jeez, what exactly is it that they’re creating?
But for the public sector, you see in general, it’s what are they actually creating? How do we want to measure what comes out of a bureaucracy that people value? Nonetheless, I think you can identify whether whatever they do is done well or not.
I’ve been thinking a lot about the poor productivity performance in the construction sector lately. And the way that interfaces with the public sector is infrastructure project management.
You’ve got some department of transportation that needs to build a bridge or whatnot. And it’s managing this construction company, or these construction companies, as it builds it. You can be good at managing construction projects or you can be bad at it. Lately, it seems like in particular, we haven’t been so good at it. But why can’t a department of transportation be a really efficient manager of construction projects?
That’s just one specific example of, even in a world where it’s hard to know exactly what the output of a bureaucracy is, whatever it’s doing, you can do it poorly or you can do it well. And you’d much rather do it well than poorly. And I think there’s a lot of scope for improvements along a number of dimensions beyond just departments of transportation in the public sector.
Part of it is, to go back to our earlier stuff about management, management matters in the public sector too. It’s not just well-managed companies are good private companies. Well-managed governments get things done with fewer resources than poorly managed governments, and that’s what productivity is about, fundamentally, is doing stuff with fewer resources.
Janet Bush: Absolutely. Just before we come to a close, is there anything that is on your mind in particular about productivity, the times we live in? How do you see it? Are you optimistic? Are you pessimistic?
Chad Syverson: I’m as optimistic now as I’ve been in a long time, in part because I started thinking a few years ago, AI might be the next general-purpose technology.
I’m not really a doomer about either the more apocalyptic stories about AI or even the more “so many people are going to lose their jobs.” I can’t make any guarantees, but we’ve had general-purpose technologies diffuse before. We’ve always figured out things for people to do. We’re pretty ingenious, even if we are natural intelligence rather than artificial intelligence. We’ll think of stuff for people to work on.
So that’s part of my optimism. I also mentioned the resurgence in dynamism and those sort of things, which turned around a decades-long decline. That also added to my optimism, after being rather pessimistic for quite some time when I was studying the productivity slowdown.
I’d also add, we talk a lot about AI, but I think biotech has seen some big and really hopeful advances lately. I think that also could be a big factor in the coming decades, so that kind of adds to my optimism, too.
Janet Bush: Yes, the biology sphere is really fascinating, and all of us benefited from mRNA technology.
Chad Syverson: Yes.
Janet Bush: So, last question. What one unproductive activity should we be doing more of?
Chad Syverson: Oh, boy. This is out of my scope of analysis. You know what? Rearing children. I think it’s important. I don’t know if it’s productive, unproductive, or somewhere in between. I’ve got four of my own. It’s the biggest thing you could do with your life, I think. And if you can do it yourself or help people you love with their own children, do it. I think that’s just an important part of life.
Janet Bush: Three cheers to that. Well, Chad, thanks so much for joining us. That was really fun and fascinating.
Chad Syverson: You’re welcome. I had a great time.
