Nicholas Bloom on Management, Productivity, and Scientific Progress

Conversations with Tyler is produced by the Mercatus Center at George Mason University, bridging the gap between academic ideas and real-world problems. Learn more at mercatus.org. And for more conversations, including videos, transcripts, and upcoming dates, visit conversationswithtyler.com. Hello everyone. Today I'm honored to be chatting with Nick Bloom, who is Professor of Economics at Stanford. I sometimes put it this way: if I read a new and interesting article, whether it be on productivity in science, the productivity of firms, how effective it is to work from home, the effect of uncertainty on economic output, and then I think, well, who's the most likely economist to be a co-author or author of this article? That one person is Nick Bloom. Nick, welcome.

Thanks very much for having me on, Tyler. It's great to be here.

Let's start with your piece with co-authors on whether progress in science has slowed down, and you argue that it has. I would ask, which are the areas where progress in science has not slowed down?

Ooh, that's a good— that's a good question. Why, that's not what I'm normally asked about. Where has it not slowed down? I mean, I guess in some senses, I mean, I'm not drawing in any deep personal insight here, but just looking at the valuations of firms in exciting areas, but it's going to be things like AI. I mean, I guess social media, genetic medicine. If I think of what's going on at Stanford, I know there's a huge explosion of work in Stanford. Several of my friends and colleagues on campus are working on genetic medicine. I mean, all kinds of amazing things there actually. Wearables. So one of my friends here is actually working with Apple on getting devices like in the Apple Watch, it can check your heart rate and tell you in advance if there's complications in your heart and basically pre-warn you. So I don't want to be too super pessimistic that all science is dying. And you're right, you're exactly right. In the research we looked at, we showed, for example, progress on cancer had an acceleration in the '80s and '90s. It's just, it seems that field after field eventually starts to decline and there aren't enough new fields that are growing to offset the bulk of the current fields that are declining.

So if progress in Moore's Law is slowing down, progress in crop yields is slowing down, cross-sectionally, what is different about the areas where progress in science is speeding up?

I mean, in some senses they're new. It's just, you know, it seems pretty obvious, you know, this is why it's useful to have economists to look seriously at the data. In a sense, it seems pretty obvious that individual areas are going to slow down. The wheel was a fantastic innovation, but at some point, progress slows down. The horse and cart, corn yields, and you can just go through innovation after innovation. They're incredibly important, but at some point, of course, progress in those areas slows down. You mentioned Moore's Law. The number of transistors you can pack onto a silicon chip has been roughly doubling every 2 years. That was kind of Moore's Law. Been roughly held constant actually for about 50 years. It's just we've been pouring in way more scientists into that. So we estimate since the '70s there are 18 times more scientists just to hold that constant. So in that sense, if you're putting in a lot more scientists to generate the same increase in compute power, you'd say that progress is slowing down. Now, that all seems obvious that each field is slowing down. The question is, are there enough new fields that are coming into being to offset that? And it just appears that at least since the 1950s in the US, The answer is no, there are new fields coming on board, but just not fast enough to offset the decline.

How do we know what counts as a new field? So you mentioned progress in genetics, but Mendel was some time ago. You mentioned the wheel, but Tesla now has a phenomenal valuation. That's the wheel plus electricity. Electricity is another old sector, right? So aren't some of the old sectors currently the most dynamic?

Well, Tesla's the electric motor. I mean, you're right, the electric motor. I think the first cars— again, it's not my expertise, but I think the first cars were in fact electric cars. Back in like 1900. Whether you call that a new field or an old— I mean, a part of that is driven— the progress is driven on batteries. So batteries, we looked at this actually, one of the— there are several areas we looked at in our paper. We never actually— so I had a paper with Chad Jones, John Van Reenen, and Michael Webb looking at whether innovation productivity is slowing down. And we looked at several sectors to try and evaluate this. And some of them lacked complete data on either inputs or outputs. But one of them is batteries. And batteries have made slow but steady progress. And recently, you know, for example, lithium-ion batteries are much more effective. But recently batteries have got to the stage where electric cars are feasible because you need to obviously store enough energy. So it's not so much the electric motor is a new idea, it's that batteries make it possible. If you want to ask what areas are new, I would, you know, practically look at, say, patents. So there's an enormous amount of debt or stock, you know, new companies floating on the stock market. Patents are a very simple way to look at what technologies are new in the sense that they add new fields. And you look at patents that don't seem to patent or cite much that's gone before them, they're truly radical. And there's a huge research literature on exactly this.

Now, if I understand your estimates correctly, efficacy per researcher, as you measure it, is falling by about 5% a year. That seems phenomenally high. What's the mechanism that could account for such a rapid decline?

Yeah, so the big picture, just to make sure everyone's on the same page, is if you look in the US, productivity growth— in fact, I could go back a lot further. It's interesting, if you go back much further and you think of European and North American history. So in the UK, that has better data, there was very, very little productivity growth until the Industrial Revolution. So, you know, literally from the time the Romans left and whatever, you know, roughly kind of 100 AD until 1750, technological progress was very slow. So sure, the British were, you know, more advanced at that point, but not dramatically. So the estimates are like 0.1% a year, so very low. And then suddenly the Industrial Revolution starts and it starts to speed up and speed up and speed up. And technological progress in terms of productivity growth peaks in the 1950s. At something like 3 to 4% a year, and then has been falling ever since. And then you ask, you know, that, that rate of fall, uh, it's 5% roughly it would have fallen if we'd held inputs constant. But the one thing that's been offsetting that fall in the rate of progress is we've put more and more resources into it. So again, if you think of the US, the number of research universities has exploded, the number of firms having research labs. Now, Thomas Edison, for example, was the first lab about 100 years ago, but post-World War II, most large American companies have been pushing huge amounts of cash into R&D. But despite all of that increase in inputs, actually productivity growth has been slowing over the last 50 years. So that's the sense in which it's harder and harder to find ideas. We're putting more inputs into labs, but actually productivity growth is falling.

But let's say paperwork for researchers is increasing, bureaucratization is increasing, How do we get that to be -5% a year as an effect? Is it that we're throwing kryptonite at our top people? Your productivity is not declining 5% a year, or is it? COVID aside, right?

COVID aside, yeah, it's hard to tell your own productivity. I mean, it always feels like it. I mean, oddly enough, I always feel like, ah, the stuff that I did before was better research ideas, and then something comes on. I'd say personally, it's very stochastic. I find it very hard to predict. Predict it. Increasingly, it comes from working with basically great and often younger co-authors. Why is it happening at the aggregate level? I think there are 3 reasons going on. One is actually come back to Ben Jones, who had an important paper which is called, I think, Renaissance Man. This came out like 15 years ago or something. The idea was it takes longer and longer for us to train. Just in economics, when I first started in economics, it was standard to do a a 4-year PhD. It's now a 6-year PhD, plus many of the PhD students have done a pre-doc. So they've, they've done an extra 2 years. So we're taking 3 or 4 years longer just to get to the research frontier. So there's so much more knowledge before us. It just takes longer to train up. So that's one story. A second story I've heard is research is getting more complicated. So I remember, um, I sat down with a former CEO of SRI, Stanford Research Institute, which is a big research lab out here that's done many things. For example, Siri came out of SRI, and he said increasingly it's like interdisciplinary teams now. So it used to be you'd have, you know, one or two scientists could come up with great ideas, and now you're having to combine— I can't remember what he said for Siri, but he said, you know, there are 3 or 4 different research groups in SRI that were being pulled together to do it. And that, of course, makes it more expensive. And when you think of, you know, biogenetics, you're kind of combining biology or genetics or bioengineering. There's many more cross-field areas. And then finally, as you say, I suspect, you know, regulation costs, various other factors are making it harder to, to make, you know, to undertake research. A lot of that's probably good. So it's less of it. I mean, I'd have to look at individual regulations, but health and safety, for example, is probably a good idea, but in the same way that is almost certainly making it more expensive to run labs. And in fact, COVID, is a huge pushback from talking— you know, I was talking just before the shutdown to a good friend of mine, and she said she has a big lab that has a number of animals and longer-running experiments going on, and in fact, the shutdown has been extremely expensive, and when we reopen with social distancing, of course, the costs are going to go up again. So these are all factors pushing on, you know, your point of regulation at the expense of running research.

But what if I argued none of those are the central factors? Because if those were true as the central factors, you would expect the wages of scientists, especially in the private sector, to be declining, say by 5% a year. But they're not declining, they're mostly going up. So doesn't the explanation have to be that scientific efforts used to be devoted to public goods much more, and now they're being devoted to private goods, and that's the only explanation that's consistent with rising wages for science?, but a declining social output from per research or scientific productivity?

Okay. So great question. There are two responses before I lose track in it. So first is, you know, I'm about to say I forgot the fourth reason. So you're right. A fourth factor on this could be just as a, just as a simple empirical fact, the share of R&D in the US, uh, and, you know, Europe, which we have best figures on that's funded by the government, has been declining over time. So in fact, in the US, When our data— when you go back to the '60s, roughly two-thirds of it is funded by the government and one-third by private firms, and now it's the reverse. In fact, it always made me wonder when I first pulled out this data 6, 7 years ago, it made me wonder about the story of Stanford because when I arrived at Stanford, I was told that Stanford pre-war really was like a finishing university. It wasn't really a big deal, and post-war Stanford got its big break because of lots of research from NASA dollars. I was kind of thinking, well, Government R&D is not such a big factor anymore. It's mainly private firms. And that's because post-war, it was the big driver, and the government's pulled back from R&D, and private firms have taken over. And the reason that's the fourth possible driver of the decline in productivity, as you point out, is government R&D tends to be more focused on the R, the research, and private R&D more on the D, the development. And the R, you may think, has more spillovers, longer-run benefits. And is what's going to drive long-run growth. So yes, that would be another role for policy. In fact, I'm embarrassed I left it out, but a big driver would be— I mean, it feels hard to be saying this being in a university, but the government should fund more public R&D. I can come back and answer the Santa's wages question if you want, but I can see you have a question because we're looking at each other on Zoom.

But if you assign the blame to government, ideas are a global public good. Isn't it true that global governmental expenditure on R&D in absolute terms is up?— even if it may be down as a percentage of budgets or total R&D, and thus say scientific progress in the United States, which can draw upon governmental support in China, Japan, India, the UK, Switzerland, should still be going up. And it has to be within private scientific progress that there's a diversion of effort away from public goods and toward more private goods, or no?

No, it's a good question. I— it's certainly true our paper only focused on the US, the puzzle gets much harder if you include global R&D. So you see that productivity per researcher or per research dollar is falling in the sense of the rate of progress per dollar we're spending. I mean, you've looked at that. I mean, just to be clear, this is not a new thesis. You have your book, The Great Stagnation, and Patrick Collison, for example, has worked on this more recently. And there's— Jesus, that book, The Death of Science, I'm embarrassed I've forgotten who the author was, but—

John Horgan.

Yeah, that's it. And so the puzzle gets even more extreme if you look globally, because of course now, I'm sure, you know, it's tricky because Europe has become slightly less of a powerhouse, but obviously Asia has completely taken off. And the amount of R&D being spent in, say, India and China has exploded. Has that offset the reduction in US publicly funded R&D, certainly as a share of GDP? It's not obvious. One reason is there's plenty of evidence on knowledge spillovers being localized. So there's a lot of evidence, for example, that you're more likely to co-author with your colleagues in your own university or in the same firm. I mean, I guess the same firms are more obvious, but if that was true, you may think the transmission of ideas from China to the US is less effective than within the US. I also don't know if the increase in Chinese and Indian R&D by their government sectors is enough to offset the reduction by the US, and whether it's in the right areas. It may be that a lot of developing countries' R&D is more say, defense and national security focus, which I suspect has lower trade-offs. And the nice thing about the US and things like the National Science Foundation, the National Institute for Health, is they would put huge amounts of funding on very basic research that had broad value. I mean, MIT researcher goes to the NSF, gets funding for research. They tend to be focused on very basic things that have interest to broad science, and that has I suspect, the largest value add.

Apart from possibly giving them more money, how should we improve the NSF and the NIH? How can we raise their productivity?

I mean, the more money seems the most obvious part of it. There's obviously, secondly, how you distribute it. And, you know, again, I remember seeing a couple of papers on how exactly you evaluate research proposals, and it's hard. And, you know, do you get insiders in the field to evaluate it who tend to have be more informed, but tend to be, you know, more biased towards their own field or outsiders. I think the broad issue is, I mean, I'm not aware of any huge criticisms of how the research agencies hand out the money. I'm sure there's lots of quibbling around the edges. I've been involved in refereeing for the NSF, for example. I've always been very impressed the way they've run it. And the ESRC, for example, in the UK. I think the big issue is just their budgets. Their budgets sure are growing, but they're not growing nearly as fast as GDP. And so as a result, government is basically pulling back from R&D. It's being at some extent replaced by universities. So if you think of these elite universities, their enormous endowments are partly being funneled into early-stage R&D. And in fact, it's why— another fascinating observation on the US is increasingly growth is being driven by kind of knowledge flows out of elite research universities. So just even in the stock market, the stock market over the last 10, 15 years has almost entirely been driven by high-tech. High-tech, in many ways, you can think of it as clustering around elite US research universities. So they are stepping in to some extent to fill the gap left by government.

How much of the measured productivity edge of American multinationals is just tax arbitrage and where profits get assigned to?

I never really thought a huge amount of it was that. My personal view, I guess this is again, I'm biased by my research is American firms in particular are just fantastically well managed. So I've done a lot of work for many years looking at management practices, trying to collect data in cross-country surveys. And to explain what I mean, management practices, the basics around, do you collect information and use it to improve yourself? So think of lean, collecting information all the time and having improvement processes. And secondly, do you train and promote employees, try to promote the best people, trying to avoid things like promoting family, friends, or long-serving employees. So meritocratic HR systems. And I don't say American firms are perfect. They're definitely not perfect. There are many management scandals. But on average, American firms are much better managed. And they take that with them abroad. And there's this whole literature that's been sometimes called dark matter, or explaining why we seem to have this endless negative balance of trade, but positive balance on investments abroad. American companies seem to make huge profits abroad. And one big explanation is they're just exploiting lots of this intangible capital, which we think of as good management. So American multinationals around the world are well managed, and they make a lot of profits where they're located—in the UK, in France, in Ghana, you know, in Thailand, wherever they are—and that's helping keep the US economy afloat, that return profits. So I don't see that as being related to transfer pricing and offshore tax manipulation. That is a factor, but I think American firms are primarily driven actually by better innovation and better management.

Why hasn't information technology boosted productivity more? So productivity is sluggish. IT has been taking off like crazy. Companies, big business is what uses IT. How do we fit the whole picture together?

Yes, so this was another— age-old debate goes back to Robert Solow's quip about— in The New York Times, he wrote, I think in '86, you see computers everywhere except in the productivity figures. You're right. Paul David and Tim Bresnan at Stanford, my colleagues, have had various— this again is an old literature about general-purpose technologies, these technologies that change society. At least two previous ones were the steam engine, the electric motor. The big question is, why haven't computers done that? They seem as transformational as the previous two. But we, I mean, as we discussed, productivity growth rates in the US have been declining since the '50s and don't seem to have picked up much anyway with computers. I think the primary reason people make, you know, argue for this is you need to change society in order to exploit this. And in fact, in an odd way, COVID, the pandemic, and working from home is one example of this. So all the technology necessary for working from home. So just to be clear, the email, you know, internet and email cheap personal computers, and video calls have all been around since the late 2000s. So the last piece, Skype, came out in 2003, but it isn't until the pandemic that we actually massively embraced working from home. Why is that? I think it's just social norms and firm organizational practices were slow to change. So I think something holding back the impact of ICT is firms and society doesn't change that rapidly. And, you know, and a good example Paul David mentions about electricity, that when electricity came in, which I believe is like the 1910s, 1920s, factories were slow to adopt it. And the reason was, in the older factories where you had a big steam engine or even water wheel, it made sense to have the building very vertical. So you'd have 4 stories around this one central shaft which belts would connect to, which drove all your mechanical power. With electricity, instead, you can have lots of little localized electric motors, which is a large flat building. So, you know, that explains if you look at really old-fashioned factories and like the center of Manhattan and places where they were built 200 years ago, they're very tall buildings. Modern factories are low-slung massive sheds. But of course, when electricity came in, it's very hard to reshape all those buildings and it takes decades. And it's kind of like that with reshaping the management organizational structures of society. I think that's one reason why it's taken so long for IT to affect productivity.

So Italy has had almost no per capita income growth for about 20 years now. Is that because of the deficiencies of Italian firms? That life in Italy hasn't changed enough?

I mean, Italy is just a productivity basket case. When I talk to Raffaella Sadun, for example, my long-term co-author, when I talk to her about Italian productivity, I mean, a lot of the issues you hear about— regulations, political instability, challenges of the education system, migration. Another thing for Italy, it's even more so for Greece, actually, is that a lot of Southern Europe has suffered from a large negative brain drain. I know lots of highly able Italians, but they basically tend to— many of them I know that are in the US and the UK, and they've left the country because it's poor economic prospects. Italy is almost a laundry list of what's gone wrong and what not to do. I think a lot of it comes down to poor government. That then feeds through into all these policies that make it hard for firms to innovate. Italy's R&D performance isn't great. It's very uncertain. It drives a lot of people abroad. The education system's poor.

What exactly is the value of management consultants? Because to many outsiders, it appears absurd that these not-so-well-trained young people come in, they tell companies what to do. Sometimes it's even called fraudulent if they command high returns. How does this work?

What's the value added? You know, I don't know if everyone knows, but I worked at McKinsey for about a year and a half. So I should state that. I no longer work for them. I don't take any money from them anymore. I mean, that was a long time ago. That was almost 20 years ago. But just from that and from my research, there's 2 or 3 things they do. I mean, it is true on the negatives. To start with the negative side, the critique that's often thrown at them is they either tell you the obvious. They ask to borrow your watch and tell you the time. Or they tell you things that the CEO normally knew, but she or he basically didn't want to fess up to tell the workers. And it is true that I felt there was some element of that, that, you know, there was one project in particular when I was involved in, I remember it seemed to us to be reasonably clear what to do. I think it seemed to be reasonably clear to the division head what to do, but it was hard for her to tell the whole group. And, you know, McKinsey came in, you know, the project was highly successful, the division improved dramatically, but It was partly we were there to bolster evidence. The third element I think is generally useful, and I've seen this, and you know, when I think of the randomized control trial I did out in India where we hired Accenture to work in a number of firms is, a lot of management improvements aren't that obvious to people on the ground. So just to give you one example, going back in history, after World War II, the big movement in the US was what's called mass production. So Henry Ford had the production line The idea is you just scale up, get bigger and bigger and bigger and make more and more Fords and roll it off in a massive factory setup. Toyota and the Japanese car manufacturing sector at that time in the 1950s, because they're obviously so devastated by the war, didn't have access to capital and had to produce things on a small scale. They went for an alternative system called lean. The whole idea of lean is that you try and spot mistakes and immediately stop the line. It's very painful in the slow run. If you see a problem in the car, you stop it, you go through it, you figure out, and then you restart. And it takes time to start off, and it's a slow burn. But by the 1980s, the Japanese car factories were clearly starting to dominate. They had lower costs and higher quality. In fact, there's a great MIT book called The Machine That Changed the World that documents that. Now, if you think of the way consultants are operating in the '90s, 2000s, it isn't obvious to many firms that lean was a far better way to run your factory, that you really want to introduce, you know, these kaizen production processes, etc. And consultants come in and help you adopt them. And it's not just factories. Healthcare, so there's been a huge transformation in lean health whereby when you go in and see a doctor, you really, really don't want there to be process mistakes. And lean is actually very good at reducing quality defects and improving productivity. So that's the area where consultants are great. I remember when I was at McKinsey and one of the projects I did with a retailer, we had someone that used to work at Toyota. And this Toyota guy had been there for 3, 4 years and was just fantastic. He went around the retailer and said, you know, here's the kind of tools we used in Toyota and just applied them, and it was extremely valuable. So that's the positive side of management consulting, highlighting things that maybe ex post after the event are obvious why it works, but in advance, you know, just aren't.

Given the high returns to management advice to India and other emerging economies, what's the main constraint that prevents that from being scaled up much more? Why don't those consultants just transform those management practices and productivity levels?

Yes, a great question. I've long thought about this. I think the biggest, one of the major constraints, India and Novesco have just been out there a lot. And one of the huge constraints is the legal system. So it sounds odd, but I'll just go through it. So in India, the actual law as it's written down in the statute book is good. There's no obvious issues with it, at least as people I talk to. But the big constraint is processing cases through the courts. So the courts are dramatically undersupplied in terms of judges. And so what happens is it's very slow to process cases through court. As a result, when you talk to Indian firms, they're very skeptical of taking any issues through the court system. So just to be clear, if you're in the US and you're a manager and you discover somebody stealing stuff from you, you're pretty likely to report it to the police, and then it goes to the court system. That manager faces, you know, potential prison. They clearly lose their job. They have a big loss of career earnings. They So in the first place, they probably won't do it.

If the courts are the binding constraint, why doesn't that make all management advice for India worth less? Why is that particularly an issue with respect to scaling? Because they all live under that court system. Oh, okay.

I was going to say, well, one solution you'd think for— I mean, I use India, but it's basically all developing countries, and including honestly large parts of Southern Europe, is private equity. So look, you see all these badly run firms. Why doesn't PE come in, buy up firms, and turn them around? The problem is the legal environment is not great. I remember talking to someone that said it was Blackstone came in, a big PE firm, bought a large retailer— sorry, a large apparel manufacturer in India and really struggled because sure, they can improve management practices, but profit wasn't going up. There's a lot of money, basically illegally leaking out of the company. Because the legal system is weak, it was hard to turn this around. Then you're right, the alternative, look, even if private equity doesn't come in, why can't they do it organically? They are. To be clear, management practices in India, which I know best, have been improving over time. There are some very successful Indian multinationals like Tata and Reliance. The issue is that isn't scaling. If you think of it, the frontier of management practices is improving every year. We're getting better at managing firms in the US. Below that frontier, there are countries that are closer, say Northern Europe, that are further, say Southern Europe, and even further below, the developing world. They're improving too. It's just there's a big gap, and it takes time. It's like innovation. It takes time for it to diffuse. And a better legal system would accelerate that. If you could have ruthless private equity backed by tough laws, I think it would be painful economically and socially, but the growth rate would improve because you'd have much more transfer of management practices.

You mentioned The Machine That Changed the World, also a favorite book of mine. What's another book on management you find especially rewarding?

Another book on management. I'm not a huge book reader. Having said that, I've been recently reading Hillbilly Elegy, which is fantastic. But I tend to, oddly enough, I tend to be a huge reader of news, like The Times, The Wall Street Journal, The Economist, The FT. I'm trying to think management books. I'm sure as soon as the interview is over, I'll kick myself and think there was some fantastic book.

Let me re-point the question. Why are management books so bad? If I ask myself, if I had to go into a big Barnes Noble and had to read all the books in one section, management might be the last section I would pick. Even though I'm an economist, and to a more modest extent, a manager. Why is there so much junk in that area? It's endogenous that you don't read more of it, correct?

Yeah, I mean, there are great books, I'm sure. I don't mean to imply they're all terrible. I'm sure there are. I'm going to— As soon as this is over—

Enter Tyler Cowen. You go to the history section, most of the books are at least pretty good. Yeah.

One issue that struck me, why I got into management in the first place— just to explain what I've been doing for years, I've been working with a huge coalition of people. So I mentioned Rafael Esedín, John Van Reenen, Renato Lemos, Daniel Asker, Erik Brinjolfsson, Luc de Vos, there's a huge group of us, Scott Allmacher, that have been trying to measure management practices across firms and countries, just very methodically, in some ways, very boringly running. We must have surveyed several million organizations by now to create a big data set. And we take populations of firms, run these surveys, collect data, and compare them. Now, that was just— most of the books that I read that are popular, Good to Great and Built to Last and things like this, are generally based on individual anecdotes and case studies. And I think that's quite— I mean, it's great for teaching. I use case studies and Harvard Business School case studies all the time to teach because it's very inspirational. But there are always positive stories of how Mrs. X or Mr. Y turned the firm around. But they're not great for research. And the reason is I know from personal experience having to write one case study. I wrote a case study on a firm that I'd was owned by someone that was in my Stanford MBA course called Gorkodas. And it's called The Challenge of Change. And the problem was we wrote this case study. It was a fascinating company that actually eventually got taken over by private equity in India. And they were a huge, very successful apparel firm. But we had to get legal sign-off from everyone involved. So we interviewed 6 or 7 people, and they all had to legally sign off and say they were fine with us using the material. And you can imagine what that does for selection effects. It means that Basically, these books are own— you know, it's very hard for them to get proper information on firms that do badly because they refuse, you know, they threaten lawsuits. So I think a lot of management research is correct. You know, most of these books are probably saying the right thing. The problem is, for every story you want to come up with, every theory, there's a book supporting it. So it's kind of hard to know where to look. What we really need ideally is, you know, what we're trying to build— I wouldn't say it's our research, but more our data that hopefully people will use because it's publicly available data— is to You know, say, look, here are 5 hypotheses of management. Is this supported in large-scale data? I think that would put more discipline on it and then therefore put more credibility on these books.

If teaching management techniques to companies is so effective, can we expect similarly large gains to teaching personal productivity techniques to individuals who, if anything, should absorb it more rapidly, right? No collective action problem. But it seems overall self-help books, life coaching, they seem pretty ineffective. How do we square that larger picture? I'm not sure they're pretty ineffective.

I don't know how I'd evaluate it. There is a large, you know, I can flip it around. I'll take The Economist's take. I'm going to kind of take your line on this, which is there is an enormous volume of like self-help books and podcasts and newsreels, et cetera. And the fact that they exist means people are spending a lot of time reading them. And I presume if you assume that people are rational, it means they get value out of it. I actually find these things quite useful. I'm not sure I absorb most of the tips. But you know, I guess my mental model is like I listen to some, I mean I don't tend to listen to podcasts, but I read a lot. And I read something, there may be 10 tips in there. In fact, before the podcast started, I was talking to Dallas, your producer. And she was, she'd sent me this whole list of things on what to do with your microphone and video. And I had read it all. In fact, she concluded a link and I went onto that. I found a couple of them really useful. I'd say 90% of them I'd seen or maybe it wasn't applicable. But 10% were great. So I actually think they potentially are quite helpful. The issue is maybe on the evidence base. Again, as an economist, ideally, you'd have an RCT. How you'd execute it is not obvious, but you may take 1,000 Americans or 1,000 Spaniards or something, some sample, and then give 500 of them intensive self-help coaching for a month and see what happens. I mean, quite possibly somebody's done this. I don't— it may exist, but that would be my way to evaluate. These kind of interventions.

Then you must think people are remarkably productive and effective because self-help books are very cheap. The advice Dallas sent you, that was for free. So if you think of it in terms of marginal value, given the low price, the marginal gains to being more productive personally, well, you must be very close to the frontier, right? But that strikes me as counterintuitive. I see people sort of screwing up all the time, not realizing their potential. I think the market for talent is remarkably inefficient, and that people don't do their very best.

Well, there's two issues. I think one is you've got to consider what it would be like without it. Humanity is dramatically more productive than it was, and some of it could be self-help. The other issue is I think this unknown unknowns. The problem is you don't know what you don't know. And just again, as a personal anecdote, I always thought I was reasonably good at energy efficiency in my Brother came around before COVID and it was a couple of years ago, and pointed out, look, I should be using LED bulbs throughout the entire house rather than the old halogen or CFL fluorescent ones. My brother's an engineer, and I sat down and went through the numbers. It paid off within 2 to 3 years, and that's clearly a fantastic rate of return. So, pretty rapidly, I switched out every single bulb in my house to LED. I didn't know it until someone had pointed it out. Ex post, it seems obvious. I could have easily gone to Amazon and worked out the cost of it, worked out the electricity usage and done the calculation. I just never thought of it. So a lot of this just is like Dallas's recommendations. I can't remember what she said. There's various things. That's it. She said, you're using this microphone, turn the gain thing down to zero. I didn't realize that. And there was a knob at the back of the microphone I'd never even looked at. I then looked at it and thought, oh yeah, there is that. I turned it down to zero and hopefully it sounds okay. But I think a lot of it is honestly, you see this in firms all the time. When we were out in India, or when I was in McKinsey, you'd often give pieces of advice and ex post it was really useful. So for example, just as another concrete piece of analysis, when I was out in India, a big issue in a lot of modern management is quality defects. So we went, these companies were large companies making say fabric that goes into making shirts and trousers and upholstery coverings. And a lot of the learnings from coming out originally from Japan is you should zero in on quality defects and fix them instantly. So Accenture said, look, your factory of 100 looms, we're going to take 6 looms at the back row and have a quality defect index and have a quality control process, a kaizen process. And after 2 to 4 weeks, it was so effective in spotting repeated issues that the factory owner said, look, this is great. It's worth the effort setting up this QDI index and this committee. We're just going to roll it out to the whole factory. But in advance, they were skeptical. So I think that's— there were so many things in life, unfortunately, we just don't know what we don't know. And so we're skeptical on advice.

How bullish are you on Chinese management? Chinese management has—

I don't have fantastic recent data. So I'll give you my best data. We surveyed them last at scale in 2005. At that point, they were roughly in line with GDP. They were OK. They weren't fantastic. I've had some other surveys, but they're not internationally comparable. Or more recently, they're pretty good. I have to say, manufacturing, a lot of what drives good management practices is being large, being around for a while, being open to competition. China has— and having educated employees. China has those inputs. A lot of their manufacturing firms in particular are big. They're competing ferociously with other companies. They actually— China's education system is churning out vast numbers of engineers. They've been operating now for quite a while. I suspect at this point now, Chinese manufacturing management is pretty good, actually. It's harder to tell in other sectors, particularly those that are not internationally comparable. The financial services, who knows? That's harder to evaluate. But typically, if you want to look for well-run companies, it's size, high levels of competition, open to trade, educated employees, no family firms where it's handed down by primogenitor, the eldest son inherits it. Go into the sectors that don't have these issues, then you tend to see very good management, and China typically tick most of those boxes in manufacturing.

Over 20 years ago, your Stanford colleague, Frank Fukuyama, wrote a book on trust. He basically said, "Well, China will never have successful large firms in the way that Japan does because there's not enough trust in Chinese society." That seemed plausible at the time, yet obviously, it's turned out to be wrong. What did we miss about China? Since you emphasize trust and corruption, and ability to delegate authority without too many bureaucratic checks and balances. And ex ante, China seemed bad on all those things. And yet, Chinese big business has done pretty phenomenally well.

A lot of trust, I think, derives from rule of law. And so, in China, again, I mean, this is getting sensitive into politics, but there's rule of law around political system, which I really don't want to comment on, but there's rule of law around things like contractual enforcement. Which turns out to be important for trust between firms. If you, Tyler Cowen, set up a company and give me a contract for 3 years for providing ball bearings, I'm going to go and put a bit of money into R&D and improving them, set up a process. If you then say after 6 months, I've changed my mind, can I sue you and get the money back? If I can effectively do it through the court system, I can trust you. That's maybe an odd concept of trust. It's not an It's not based on some cultural or religious thing. It's based on the fact that the legal system works. If you look in, for example, the World Values Survey, which measures interpersonal trust, trust measured there is highly correlated with the effectiveness of the legal system. Some of the lowest countries in the world in terms of trust are some of the African countries whereby the legal system is in chaos because they're undergoing civil war. The highest countries are like Norway, Sweden, North America. America. So, currently in China, the rule of law is applied to commercial contracts, I think is reasonable. I'm not an expert, but you don't hear endless stories of scandals and corruption, at least as commercial contracts go, and I think that's what enables these large firms to grow. When we've collected survey evidence, in reverse, we definitely don't hear endless stories of managers ripping off firms and stealing ideas, which is a big problem. So, just to reverse it around, What happens in countries with very weak legal systems where you can't trust anyone is you hire your family members. So if I want to set up a company and I can't trust any outsiders, I start to stuff it full of, you know, sons, daughters, brothers, brothers-in-law, sisters, sisters-in-law, aunts, uncles, etc. Now that's good because I can trust them. But the problem is, you know, these people aren't naturally the best managers to run the place. And of course, as I get bigger and bigger, I'm running out of good family members. So do I appoint a second cousin? Or that pretty incompetent younger son of mine. And you can imagine the trade-offs that are going on. But it means that unless you have a proper legal system, which generates trust, it's very hard to grow large firms without professional managers.

How do you think about trust and management in England versus trust and management in Scotland?

I don't know if you know, my wife is a Scot. Yes, of course. My mom is Scottish. So I don't think they're that different, actually. I mean, having now lived in the US, even the US-UK difference I don't think is enormous. Increasingly, as I travel around the world, you realize that there are huge differences between Northern and Southern Europe. That strikes me as quite striking, actually. England and Scotland are very similar. We effectively have the same legal system, the same educational standards. My mother-in-law, who's in Glasgow, I should send her this podcast, she'll probably kill me for saying that, but the Scots, I should point out, have had some of the most successful members of British government, like Gordon Brown and various prime ministers. They're overrepresented, but I don't think they're very different. I think, in fact, in reverse, they're really pretty similar.

But the Scots have done much better fighting against the pandemic in the public sector. If you look at globally known brands, I know England has a greater population, but it seems to do disproportionately better than than Scotland does. So it seems to me the two cultures are not that similar across critical margins. Maybe there are small differences in an absolute sense, but those compound into large differences in final outcomes.

It's an interesting point. The Scots also voted what I would say is the right way on Brexit. They were against Brexit. I mean, I'm going to be very open here. I was against Brexit because Britain leaving the European Union, I think, is bad economically for the UK. And I think it's kind of this whole concept of being a little Englander, looking inwards. Scotland voted against Brexit quite resoundingly. It's true that they've handled the pandemic much better. Why that is, is not clear. I regularly talk to my mother-in-law in Scotland. In some ways, they seem to be more educated, at least as far as I'd say it, in the way they vote. Their OECD-measured levels of education are not higher. I'm not aware of any other striking differences. I I think I like Nicola Sturgeon, who is the, I think is what's called the First Minister. She's effectively the Prime Minister of Scotland. She's done a very good job. She locked down faster in Scotland. I think that's why they dealt with the pandemic sooner. Again, on the pandemic, I'm not enough up to the news on England versus Scotland, living in the US, to give more of an answer, but I am aware the Scots have done better on that, and they certainly did better on Brexit.

Does Scotland have a different cultural notion of hooliganism?

Do you know about the famous old firm rivalry, Celtic-Rangers? You probably think no. The two Glaswegian teams. Again, I know in Scotland, I really spent the vast amount of my time in Glasgow. I don't think it's— I wasn't expecting, Tyler, I think, to be asked about Scottish football hooliganism, but as far as I'm aware, no. I mean, the interesting thing, by the way, on technology, one of the issues that afflicted the UK was hooliganism. And there's kind of various elements of it, but one was just fighting and violence, but another one was racism. And both of them, technology has been fantastic at combating. Just on both of them, cameras in the ground, ID cards, online. There was an incident just over the weekend, I was looking just this morning about the racial comments made against a Crystal Palace football player that the police checked through online and turned out to be a 12-year-old boy in the west of Midlands making this stuff. But just in terms of the ground, technology has improved attendance at sports games because of this, we can stamp it out. And that's something that doesn't show up in productivity figures. So another concern you could have, and there's been a big debate in terms of productivity, is it the case that the quality of life has risen in ways that we're not measuring it? I could get into that debate. I think the answer is primarily no, but you could make that claim. And, you know, hooliganism has been pushed back a lot by technology.

If policy uncertainty is so important for the macroeconomy, pre-COVID, why was the reign of Donald Trump just fine for the American economy? Because there was high uncertainty. I woke up every morning not knowing what would happen or what would be said. I'm not sure ex post that uncertainty was realized until COVID, but in fact, it was realized on a massive scale. Yet ex ante, the uncertainty didn't seem to have much of a negative drag.

Yeah, Donald Trump, in terms of economic performance, How would you assess it? Before COVID he, you know, it was fine. You could sometimes be slightly— I mean, again, I'm not a Trump supporter, so definitely don't get me wrong. You could be mildly positive on it and saying, look, he took the Obama boom and continued it. And as expansions go on, maybe you think it's harder and harder to keep that expansion going. Growth didn't pick up, but it also didn't slow down under Trump. So that would be a passing grade. It wouldn't be fantastic, wouldn't be terrible either. One thing that aided growth under Trump was the corporate tax cuts. There's another political uncertainty in changing his mind all the time, and honestly, a lot of bad policy with reduced growth under Trump. Net-net, it seems to have netted out to about zero. It was no higher or no lower than in Obama's second term. So the policy uncertainty was a negative, but there were other things he did that were positive. It's also true that under Obama, there was considerable policy uncertainty because things like the debt ceiling debate and the fiscal cliff., and who you blame is less obvious there. Congress was fighting. The President Obama wanted to pass various pieces of legislation, couldn't. The same thing is true now, of course, though we have a mixed control of Congress. I think Trump made it a lot worse, to fault him quite explicitly. He just changed his mind, and he also didn't listen to advisors. When he talked to firms, it's very hard to predict which way policy was going to go, because a lot of decisions didn't seem entirely thought-out, rational, predictable. I don't know what words you use, but firms who complain about, we didn't see this coming, and he changed his mind on tweets. And that, by the way, US physical investment, even before COVID was not great.

But that could be intangibles, right? Yes. I mean, the stock market is doing well.

Yes, but the stock market does not reflect the US economy. The stock market, for example, right now is 30% high-tech, which is only 7% of US jobs.. And also, when interest rates drop because the economy slows, it makes the stock market go up because it's suddenly a relatively better investment. So I think the stock market and the state of the US economy are only weakly linked.

Maybe we take the 1960s, which is one of the golden eras of macroeconomic growth, many wonderful things about it. It seems policy uncertainty was quite high. There was the Cold War. There was the Vietnam War. There's the civil rights movement, not clear how it would turn out. There were riots in cities all the time. We were on the verge of major changes in regulatory policy, like the environmental movement. So anecdotally, very high policy uncertainty. Things proceed just great, it seems, or no?

This is why long-run measures are actually useful. It's very hard when you talk to people, they often raise different eras as particularly more or less uncertain. And often, it's driven by their own personal experiences. And there's actually a phenomenon. I mean, it's interesting you raise the '60s. It's actually a phenomenon to think the past was more certain than the present. Because you see the past as having happened, you forget all the alternative scenarios that could have been. So just on data, the '60s, in terms of stock market volatility, were quite low. In terms of macro volatility, were moderately low. There was the whole Great Moderation. And the '70s and '80s were very volatile macro growth, but the '60s were reasonably calm. In terms of our index, Economic Policy Uncertainty Index, where we scraped newspapers, it didn't appear to be particularly high levels of uncertainty. You could argue newspapers are— in that era, it wasn't clear how completely open they were. Watergate was opening the floodgates of being more transparent, but I don't see in the evidence I've seen the '60s as a period of particularly high policy uncertainty. You're right, those incidents happened, but in other areas like domestic economic policy, again, I'm going off newspapers, but on average, in stock market reactions, it doesn't seem to be particularly high. The two great spikes, in the stock market volatility, by the way, in the '60s with the Cuban Missile Crisis and the assassination of JFK.

We're speaking in July 2020. Given that there's so much working at home going on right now, how long will it take before tech company productivity declines as people grow frustrated or disconnected, or they become too restless? It's too hard to bring on board new hires. How much time do we have before things really start to fray? Great question.

Just to be clear, my thoughts on working from home in the short run, Working from home, for those of us that can— so just to be clear, only something like 40% of Americans can work from home, but that accounts for something like 50%, 60% of GDP because they tend to be higher-earning individuals. So, for those of us that can work from home, the evidence looks like in the short run, that increases productivity as long as you've got reasonable conditions like proper internet and a room, your own exclusive room to work in. The big question— that's research I've been I had an old paper looking in China, and we showed very large increases in what I call short-run productivity from people working in call centers. The big unknown, in which there's little evidence I'm working on, I know other people are looking at this too, which is what's the impact on longer-run productivity, which the concept of— come back to the beginning of the podcast— is about creation and innovation. Lots of claims, including Steve Jobs before he passed away made several comments about he wanted people to be in the office. You have to be there for the new ideas come up from water-cooled regular discussions and meetings and one-on-one stuff. And obviously, under COVID, that's all stalled. So none of that will really show up right now. You can get away with 3 to 6, maybe even 9 months, probably, of not radically creating new things. But in the long run, I fear there'll be a drop in, say, patenting in 2021, 2022 because of this. And the question is, how firms respond? My guess is, from talking to a lot of US companies, is they will return partly to the office. So I think in the long run, working from home will be fine because we'll be in the office 3 days a week and 2 days a week at home. So that's kind of the best of both worlds. I don't think you need to be in the office 5 days a week to be creative, but you do need some time each week with colleagues. So I'm not too worried now. What I think will be problematic is if we're in late 2021, we were still all 100% working from home, then I would really worry about impacts on productivity.

So your long-term co-authors should be those who are at Stanford or Berkeley. But your short-term co-authors can be anywhere.

My co-authors are just all over the place. I was going to say one of the things I really miss about working from home is going to seminars and conferences, and particularly kind of the two last conferences I went to before lockdown. One was in Mexico, ITAM, and one was in Melbourne at Monash University. And they're both fantastic because they were small. And I got to basically talk to everyone there. And that's the kind of thing that generates For me, co-authors is talking to someone with a quirky idea that comes up with something. So oddly enough, most of my co-authors are not at Stanford, which seems to disobey my own rule. I don't know why that is. Mostly I have overlap with them physically at one point or another. They're former students or former colleagues, like when I was at UCL or LSE. Steve Davis I work with a lot and he's at Chicago. I never physically overlapped with him. You know, two others like Ivan Alfaro, Zhaojie Lin, I met them at Ohio State University.

If you can do it, why can't tech companies do the same?

Okay. So let's take Ivan and Xiaojie Lin from Ohio State University. I first met them physically. I went to give her a seminar at Ohio State University. I sat in Xiaojie's office for half an hour. We kind of got excited about a research idea. That was the critical meeting point. I'm not sure what would have happened if we'd done it remotely. And after talking to him, I thought, this, you know, this guy seems great. It's a really interesting idea. We continued to communicate by email. So my thought is, and it kind of matches roughly what a lot of Silicon Valley types say, is the initial spark or idea is much more effectively generated in person. Often it's over lunch or over coffee. So this is the sense in which productivity now— so I've been running masses of surveys under working from home to try and get the sense of how people are feeling, and both firms and workers are overwhelmingly positive about working from home. But that's now, I mean, again, to be clear, that's July, and we're kind of 3 to 4 months into the lockdown. My fear is if it were full-time working from home 5 days a week for another 6 to 9 months, there's going to be much more discontentment. In fact, I saw that in China when we did the Ctrip study. People were working from home for 9 months, and towards the end of it, it started to really grind and drag on. That was more about loneliness, but there's the other issue is in terms of being productive and being creative.

For our final section of the conversation, I have a number of questions about your own productivity. This is called the Nick Bloom production function. Are you ready? Yes, go ahead, thank you. Now, most people at top 5 schools in economics, as you know, also have PhDs from other top 5 schools. But Nathan Nun has a PhD from University of Toronto, and your PhD is from University College London. What made you an outlier in this regard, and what do you think have been its advantages and disadvantages?

For you? I, you know, for me doing my PhD at UCI, I was extremely fortunate. Oddly enough, I've had this discussion with a lot of people that are applying to Stanford as PhD students. I'm not sure if I effectively sells or undersells Stanford. But there's trade-offs when thinking about grad school. It's true if you go to an elite grad school, you're surrounded by a fantastic cohort and have great faculty. On the other hand, it's hard to work often with faculty because there's so many other good students. Around. At the time I was at UCL, I was doing my PhD in the late '90s, the number of other PhD students was very thin. There were just not— it wasn't a big program. Mostly they, you know, there's a mix. Many of them were not interested in ultimately going into academia. So I was one of the few students that was focused. I mean, there were a few others, don't get me wrong. There were like 5 or 6 in my year, but it was a much smaller cohort, say, compared to Stanford where there's 25 a year. As a result, it was much easier for me to work with faculty. Folks, not just faculty at UCL, but others through the IFS, so people like Richard Blundell, John Van Ryn, and Rachel Griffiths, Frank Wynmar, Steve Bond, these guys were sitting around. Lucy Channels, I remember she was sitting right on the other side of the desk from me. I'd speak to Lucy as a grad student, it was fantastic. This was someone that had been out, or Rachel, for 5, 10 years. Having that exposure was great. If I'd been in an enormous cohort of 25 of us per year over 6 years, I never would have got that.

So are the top 5 schools overrated for economics graduate study?

I think the question to ask is, what's the value added? So remember, the top 5 schools recruit by far the best students. They just— I know Stanford ranks the students, and we tend to get those too. We often make offers to those at the top of the list. We do pretty well out of that. We typically get, you know, pipped by MIT. So the question is, what's the value added? And it's never been obvious to me what that is. I suspect it's positive, but I'm not certain. It's definitely not uniformly positive. For me, almost certainly, it was better off having gone to UCL. It was a fantastic outcome for me versus anywhere else, because I got to work with all these people early on. I was also, I have to say, very lucky because the IFS at that era was big into what they called microeconometrics, which is basically using panel data, which turned out to be exactly the way to go. I was clearly fortunate. I just happened to be in a university that was on the rise at the time.

And you began your career at the British Institute for Fiscal Studies. How did that shape your subsequent research and how you think? Was that a mistake? Was that a wonderful start to have? It's again highly unusual, yes?

Yeah, the IFS was great. When I finished my— I did a master's at Oxford. I wasn't intending to go into research at all, actually. I applied for a lot of investment banks and other— I applied for IT jobs. I mean, I remember getting an offer from BZW, now kind of long-closed British investment bank, to go work in the IT department and thought about it very seriously. I was so all over the place. I took this job at the RFS, turned out to be fantastic. One is it really inspired me to get interested in economics. They answered what I would call pub economics questions. What I mean is in the British sense, they're questions you can talk to your friends in the pub about, which are the same ones, frankly, that the New York Times or anyone They're kind of not obtrusive things like what happens in this model when alpha goes to 7, but more like how would you increase growth rates. So the RFS was very much about inspiring me to do this stuff, and it was also entirely empirically focused. So again, that was in an era where empirical economics wasn't so dominant. It is much more dominant now. But so I just basically focused on data. And I was lucky. At the RFS, I could do a part-time PhD. Just to be clear, when I started there, I was not a PhD student. And they had a program encouraging people to go do part-time PhDs at UCL. So from there, I then went to start my PhD about 9 months after joining the RFS at UCL. So I was oddly kind of an accidental PhD student. It was not something I ever had in mind.

And what do you think it is in either your personality or your background that led you to take these unusual paths? Because again, they're somewhat atypical, as you know. Yeah.

I mean, I, at the RFS, at some point I left and went to work in McKinsey and I went to the UK. Also atypical, right?

Most people just go straight through research, research, research. I was clearly very lucky.

So I wouldn't advise probably my— certainly going to work in McKinsey, as in leaving your PhD and going to a non-academic job, was probably, you know, on average is not a good path. I was just extremely fortunate that I managed to get back into academia afterwards. I wasn't there for that long, for, you know, under 2 years. And I was fortunate the people I worked before were running a research center. So John Van Ryn in particular at the CEP, took me back as what's called a research officer. I was like a souped-up RA. Then I started working on two areas. One is management, one was uncertainty. The management one turned out to be a fertile area to look in just because there's not much data. Uncertainty, I honestly was again fortunate on timing because when I started looking at it, it was during the period of the Great Moderation. When I was working on uncertainty, I was looking at things like 9/11 as an enormous uncertainty shock, started to get into the topic. But, you know, business cycles were kind of quiet. People weren't working on that that much. And then suddenly, of course, '08, '09 happened, and then COVID. So in hindsight, I wouldn't advise that path. The issue is, you know, it's like first and second order stochastic dominance. It's— on average, the path I took was probably a less good path to take. It turned out for me individually, due to circumstance and good luck, it worked out well.

Now, your dissertation was on the topic of adjustment costs. Is there a lens through which I can read a lot of your subsequent major topics as actually all being about adjustment costs? Speeding up progress in science, copying management productivity techniques and why it's so hard, the effects of uncertainty, it's hard to adjust to it. Are you still working on adjustment costs? Yeah, you know, this kind of—

it's like my first academic love was adjustment costs. It seems strange to say that. I remember Bob Hall saying he went to some MBR event and saying there was a huge shouting match about adjustment costs. And he said, how can How can anyone get so excited about— Bob Horwath, some famous folks in adjustment cost speak, it's funny. How can anyone get so animated and excited about something so boring? Bob and I, many others have worked in it. I got really interested in it. I realized halfway through my PhD, it was hard to excite other people about adjustment cost. I'd honestly start talking to people, again, coming back to the pub economics thing, my friends in particular about it, and their eyes would start— eyelids would start drooping. They were just boring them to tears. That's how I ended up morphing to look at uncertainty. Because I realized if you have high adjustment costs, as in it's expensive to hire someone and fire, invest and disinvest, uncertainty is really costly because you can't change your mind. But yeah, it has colored my thinking a lot. I was trying to think of— I'm blanking what it was, but the other day I was talking to someone about something to do with management and talking about how it's a big issue of adjustment costs. That's right. I was thinking about working from home. So just to be clear, under COVID, with social distancing, working from home, I think this is going to last for another, let's say, year. It's hard to know. If after a year more, we are still social distancing, working from home, we've been in that regime for up to 18 months. A lot of firms are going to have adjusted, individuals, to that process. You can call it inertia. You can also think of it as adjustment cost, but this is why I think a lot of what's happening now is going to stick because of that. Yes, in some senses, that has colored my thinking.

Just you personally, relative to your level of talent, are you a person of high or low adjustment costs when you need to adjust?

Yeah, as we get older and older, it feels like our adjustment costs become higher and higher. You know, I have these 3 areas I'm working on, I guess. Innovation, I started working on. Management and uncertainty, the 2 I guess I started working more recently. I mean innovation, just again, this is a random thing. Years, I mean, I don't know how long ago it was. I had a summer internship, an unpaid internship at the ministry long gone in the UK called the Department of Trade and Industry, to do a project looking at patents. I mean, this was like 30 years ago, and I remember pulling up all the data on patents, and that kind of interest in innovation stuck. I tend to think I built up so much knowledge and interest in particularly managing uncertainty innovation, I tend to mostly focus on that. Although recently, through, you know, fortuitous luck, I was working with another couple of co-authors— again, I've never overlapped with Vati Givinen and Sergio Salgado— looking at inequality in firms and skewness and other topics. I mean, for me, I really like to read broadly rather than deeply. It sounds an odd thing to say, but every Monday, for example, or Sunday night, the National Bureau of Economic Research has their vast email of all the recent papers. I tend to try and scan every title and abstract. I read The Papers. I like The Economist and The Economist magazine. It's good. It's often been a source of ideas, actually, of I, you know, I listen, we were talking before the call. I listened to your podcast, actually listen to a lot of podcasts because I try and go out for a walk or a run for about an hour every day and mostly listen to podcasts. I'd say, well, if I'm getting too tired, I have to switch on to music. But yeah, I think for me that's been helpful for coming up with new research ideas.

And what do you think will be the next different thing that you do? It's not just an extension of current work. Geez, that's hard to say.

I, my best guess is, as you say, the other thing that's really helpful for me is working with with co-authors will be some, you know, bright, sparky co-author grad student would suggest we should look at X. And, you know, maybe they're not that interested in it. I say, no, that's a great idea. And, you know, maybe at some point it turns into a collaboration. Often, or I'm giving a seminar, a lot of great ideas come from just, you know, just for those that don't go on the academic seminar route, the way that academic seminars work is Because at GMU, not that long ago, but you go and give a talk and then normally you get meetings in the morning and the afternoon. So a classic day would be you turn up at 10 AM, you have half-hour meetings, and then the lunch, and there's a talk in the afternoon, and then dinner. And what I really like is those one-on-one meetings because you're talking to lots of people for half an hour. And I find them mentally really tiring because you're like fully on. And I actually, whenever I meet people, I go to their website, look them up for half an hour, 20 minutes beforehand, and really try and learn about what they work on. It takes a lot of time. I find it really valuable, and that's the great source of ideas. I'm personally also suffering in the sense of productivity, as I mentioned, I think the US economy is, from working at home full-time because those one-on-one meetings have stopped. My own production function in some ways of continuing current projects is fine, I can do that, but I do feel that if this carries on for another year, I feel like the US economy are going to suffer a little bit. In terms of struggling to come up with new ideas because there's not so much one-on-one discussion. I'm not randomly meeting people. So I'm, you know, I can easily Zoom with current people I know on, but it's much harder to come up with random people at seminars you would have gone to but clearly aren't.

Nick Bloom, thank you very much.

Tyler, thanks very much for having me. That was great.

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