Nicholas Bloom on Management, Productivity, and Scientific Progress (Ep. 102)

And why periodicals and podcasts trump books.

What might the electrification of factories teach us about how quickly we’ll adapt to remote work? What gives American companies an edge over their competitors on the international stage? What value do management consultants really provide? Stanford professor Nick Bloom’s research studies how management practices, productivity techniques, and uncertainty shape outcomes across companies and countries.

He joined Tyler for a conversation about which areas of science are making progress, the factors that have made research more expensive, why government should invest more in R&D, how lean management transformed manufacturing, how India’s congested legal system inhibits economic development, the effects of technology on Scottish football hooliganism, why firms thrive in China, how weak legal systems incentivize nepotism, why he’s not worried about the effects of remote work on American productivity (in the short-term), the drawbacks of elite graduate programs, how his first “academic love” shapes his work today, the benefits of working with co-authors, why he prefers periodicals and podcasts to reading books, and more.

Listen to the full conversation

You can also watch a video of the conversation here.

Read the full transcript

TYLER COWEN: Hello, everyone. Today I am 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, then I think, “Well, who’s the most likely economist to be a coauthor or author of this article?” That one person is Nick Bloom. Nick, welcome.

NICHOLAS BLOOM: Thanks very much for having me on, Tyler. It’s great to be here.

COWEN: Let’s start with your piece with coauthors 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?

BLOOM: Ooh, that’s a good question. That’s not what I’m normally asked about. Where has it not slowed down? I’m not doing any deep personal insight here, but just looking at the valuations of firms in exciting areas, it’s going to be things like AI. I’m going to guess social media, genetic medicine.

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. All kinds of amazing things there, actually.

Wearables — one of my friends here is actually working with Apple on getting devices in the Apple Watch so it can check your heart rate and tell you in advance if there’s complications in your heart and basically pre-warn you.

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 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.

COWEN: 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?

BLOOM: In some instances, they’re new. It seems pretty obvious. 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. So, the wheel was a fantastic innovation, but at some point, as progress slows down, and the horse and cart, corn yields. 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 two years. That was kind of Moore’s Law, and that’s been roughly held constant, actually, for about 50 years. It’s just, we’ve been pouring way more scientists into that. We estimate since the ’70s, there are 18 times more scientists just to hold that constant.

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, it seems obvious that each field is slowing down. The question is, are there enough new fields that are coming into being to offset that? 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. So right now —

COWEN: How do we know what counts as a new field? 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?

BLOOM: Yep.

COWEN: Aren’t some of the old sectors currently the most dynamic?

BLOOM: Well, Tesla is the electric motor. I mean, you’re right. The electric motor — 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 one, the progress is driven on batteries.

So batteries — we looked at this, actually. There are several areas we looked at in our paper. I had a paper with Chad Jones, John Van Reenen, and Michael Webb looking at whether innovation and productivity is slowing down. We looked at several sectors to try and evaluate this. Some of them lacked complete data in either inputs or outputs, but one of them is batteries, and batteries have made slow but steady progress. For example, lithium-ion batteries are much more effective.

Recently, batteries have gotten to the stage where electric cars are feasible because you need to, obviously, store enough energy. 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 practically look at, say, patents. There’s an enormous amount of 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. 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.

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

BLOOM: 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 — you go much further, and you think of European and North American history. In the UK that has better data, there was very, very little productivity growth until the Industrial Revolution. Literally, from the time the Romans left in whatever, roughly 100 AD, until 1750, technological progress was very slow.

Sure, the British were more advanced at that point, but not dramatically. The estimates were like 0.1 percent a year, so very low. Then 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 percent a year, and then it’s been falling ever since.

Then you ask that rate of fall — it’s 5 percent, roughly. It would have fallen if we held inputs constant. The one thing that’s been offsetting that fall in the rate of progress is we’ve put more and more resources into it. Again, if you think of the US, the number of research universities has exploded, the number of firms having research labs.

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. That’s the sense in which it’s harder and harder to find new ideas. We’re putting more inputs into labs, but actually productivity growth is falling.

COWEN: Let’s say paperwork for researchers is increasing, bureaucratization is increasing. How do we get that to be negative 5 percent a year as an effect? Is it that we’re throwing kryptonite at our top people? Your productivity is not declining 5 percent a year, or is it? COVID aside.

BLOOM: COVID aside. Yeah, it’s hard to tell your own productivity. Oddly enough, I always feel like, “Ah, you know, the stuff that I did before was better research ideas.” And then something comes along. I’d say personally, it’s very stochastic. I find it very hard to predict it. Increasingly, it comes from working with basically great, and often younger, coauthors.

Why is it happening at the aggregate level? I think there are three reasons going on. One is actually come back to Ben Jones, who had an important paper, which is called, I believe, “[Death of the] Renaissance Man.” This came out 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 four-year PhD. It’s now a six-year PhD, plus many of the PhD students have done a pre-doc, so they’ve done an extra two years. We’re taking three or four years longer just to get to the research frontier. There’s so much more knowledge before us, it just takes longer to train up. That’s one story.

A second story I’ve heard is, research is getting more complicated. I remember 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. He said, “Increasingly it’s interdisciplinary teams now.”

It used to be you’d have one or two scientists could come up with great ideas. Now, you’re having to combine a couple. I can’t remember if he said for Siri, but he said there are three or four different research groups in SRI that were being pulled together to do that. That of course makes it more expensive. And when you think of biogenetics, combining biology and genetics, or bioengineering, there’s many more cross-field areas.

Then finally, as you say, I suspect regulation costs, various other factors are making it harder to undertake research. A lot of that’s probably good. I’d have to look at individual regulations. 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.

In fact, COVID is a huge pushback. 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. In fact, the shutdown has been extremely expensive. When we reopen with social distancing, of course, the costs are going to go up again. These are all factors pushing on your point of regulation. It’s just expensive running research.

COWEN: 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 percent a year. But they’re not declining. They’re mostly going up.

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? That’s the only explanation that’s consistent with rising wages for science but a declining social output from her research, her scientific productivity.

BLOOM: Great question. There are two responses before I lose track in it. First is, I’m embarrassed to say, I forgot the fourth reason, so you’re right. A fourth factor on this could be, just as a simple empirical fact, the share of R&D in the US and Europe — which we have best figures on this — funded by the government has been declining over time. In fact, in the US, when you go back to the ’60s, roughly two-thirds of it is funded by the government and one-third by private firms. Now it’s the reverse.

In fact, it always made me wonder — when I first pulled up this data six, seven years ago — it made me wonder about the story of Stanford. Because when I arrived at Stanford, I was told that Stanford prewar really was like a finishing university. It wasn’t really a big deal. Postwar, Stanford got its big break because of lots of research from NASA dollars.

I was thinking, “Well, government R&D is not such a big factor anymore. It’s mainly private firms.” That’s because postwar, it was the big driver, and the government pulled back from R&D, and private firms have taken over.

The reason that’s the fullest 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. The R, you may think, has more spillovers, longer-run benefits, and is what’s going to drive long-term growth.

So yes, that will be another role for policy, in fact. I’m embarrassed I left it out, but a big driver would be . . . It feels hard to be saying this, being in a university, but the government should fund more public R&D. I can get on the economic-status-on-wages question if you want, but I can see you have a question because we’re looking at each other on Zoom.

COWEN: 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 for total R&D? Thus, scientific progress in the United States, which can draw upon governmental support in China, Japan, India, UK, Switzerland, should still be going up.

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?

BLOOM: No, it’s a good question. It’s certainly true, our paper only focused on the US. The puzzle gets much harder if you include global R&D. You see that productivity per researcher or research dollar is falling, in the sense of the rate of progress per dollar we’re spending.

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. There’s that book, The Death of Science. I’m embarrassed I’ve forgotten who the author was.

COWEN: John Horgan.

BLOOM: Yeah, that’s it. The puzzle gets even more extreme if you look globally. Sure, it’s tricky because Europe has become slightly less of a powerhouse, but obviously Asia has completely taken off in 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. There’s a lot of evidence, for example, that you’re more likely to coauthor with your colleagues in your own university or the same firm. I guess the same firm is 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 focused, which I suspect has lower tradeoffs.

The nice thing about the US and things like the National Science Foundation and the National Institute for Health is they would put huge amounts of funding on very basic research that had broad value. An MIT researcher goes to the NSF, gets funding for research. They tend to be focused on very basic things that are of interest to broad science, and that has, I suspect, the largest value in.

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

BLOOM: More money seems the most obvious part of it. There’s obviously, secondly, how you distribute it, and, again, I remember seeing a couple of papers on how exactly you evaluate research proposals, and it’s hard. Do you get insiders within the field to evaluate, who tend to be more informed but tend to be more biased towards their own field, or outsiders?

I’m not aware of any huge criticisms of how the research agencies hand out their 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. As a result, government is basically pulling back from R&D. It’s being, to some extent, replaced by universities. If you think of these elite universities — their enormous endowments are partly being funneled into early-stage R&D.

Another fascinating observation on the US is, increasingly, growth is being driven by knowledge flows out of elite research universities, even in the stock market. The stock market, over the last 10, 15 years, has almost entirely been driven by high tech. In many ways, you can think of it as clustering around elite US research universities. They are stepping in, to some extent, to fill the gap left by government.

Another fascinating observation on the US is, increasingly, growth is being driven by knowledge flows out of elite research universities, even in the stock market. The stock market, over the last 10, 15 years, has almost entirely been driven by high tech. In many ways, you can think of it as clustering around elite US research universities. They are stepping in, to some extent, to fill the gap left by government.

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

BLOOM: I never really thought a huge amount of it was that. My personal view — I guess this is, again, biased by my research — is American firms are particularly just fantastically well managed. I’ve done a lot of work for many years, looking at management practices, trying to collect data in cross-country surveys.

To explain what I mean, management practices — the basics are, do you collect information and use it to improve yourself? Think of lean, collecting information all the time, and having improvement processes. 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.

I’m not going to 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. There’s this whole literature that has been sometimes called dark matter, or explaining why we seem to have this endless negative balance of trade but positive balance on our investments abroad. American companies seem to make huge profits abroad.

One big explanation is they’re just exploiting lots of this intangible capital, which we think of as good management. American multinationals around the world are well managed, and they make a lot of profits where they’re located in the UK and France, in Ghana, in Thailand — wherever they are. That’s helping keep the US economy afloat, that return profits. I don’t see that as being related — 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.

COWEN: Why hasn’t information technology boosted productivity more? 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?

BLOOM: [laughs] Another age-old debate goes back to Robert Solow’s quip in the New York Times. He wrote, I think, in ’86, “You see computers everywhere except in the productivity figures.”

So you’re right. Paul David and Tim Bresnahan at Stanford, my colleagues, have had various . . . Again, there’s an old literature about general-purpose technologies, these technologies that change society, and at least two previous ones were the steam engine and the electric motor. The big question is, why haven’t computers done that? They seem as transformational as the previous two.

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 argue for this is, you need to change society in order to exploit this. In fact, in an odd way, COVID, the pandemic, and working from home is one example of this — all the technology necessary for working from home.

Just to be clear, the internet and email, cheap personal computers and video calls have all been around since the late 2000s. 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. I think something holding back the impact of ICT is firms and society don’t change that rapidly.

A good example: Paul David mentions about electricity that when electricity came in — which I believe is in the 1910s, 1920s — factories were slow to adopt it. The reason was, in the older factories where you had a big steam engine or even a waterwheel, it made sense to have the building very vertical. You’d have four 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. That explains, if you look at really old-fashioned factories in 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.

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.

COWEN: Italy has had almost no per capita income growth for about 20 years now. Is that because of the deficiencies of Italian firms? Italy hasn’t changed enough?

BLOOM: Italy is just a productivity basket case. When I talk to Raffaella Sadun, for example, my long-term coauthor — when I talk to her about Italian productivity, a lot of the issues you hear about are regulations, political instability, challenges in 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 many of them I know are in the US and the UK, and they’ve left the country because of its poor economic prospects.

Italy is almost a laundry list of what’s gone wrong and what not to do, but 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 is poor.

On the value of management consultants

COWEN: 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?

BLOOM: I don’t know if everyone knows, but I worked at McKinsey for about a year and a half. I should state that I no longer work for them. I don’t take any money from them anymore. That was a long time ago. It was almost 20 years ago. Just from that and from my research, there’s two or three things they do.

It is true on the negatives. To start with the negative side, the critique that’s often thrown at them is they 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.

Now, it’s true that I felt there was some element of that. There was one project in particular that 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. McKinsey came in, 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. When I think of the randomized controlled trial we did in India, where we hired Essentia to work in a number of firms, is a lot of management improvements aren’t that obvious to people on the ground.

Just to give you one example, dating back in history — after World War II, the big movement in the US was what’s called mass production. Henry Ford had the production line, and 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 were 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.

It takes time to start off, and it’s a slow burn. 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 were 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 these Kaizen production processes, et cetera, and consultants come in and help you adopt them.

It’s not just factories. Healthcare — 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. Lean is actually very good at reducing quality defects and improving productivity. 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. This Toyota guy had been there for three, four years and was just fantastic. He went around the retailer and said, “Here’s the kind of tools we use in Toyota, and just apply them.” And that was extremely valuable. That’s the positive side of managing consulting — highlighting things that maybe, ex post after the event, are obvious why it works, but in advance just aren’t.

COWEN: 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?

BLOOM: Yeah, it’s a great question. I’ve long thought about this. India I know best because I’ve been out there a lot. One of the huge constraints there is the legal system. I’ll just go through it. 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. The courts are dramatically undersupplied in terms of judges, so what happens is, it’s very slow to process cases through court. As a result, when you talk to Indian firms, they are very skeptical of taking any issues through the court system.

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. Then it goes to the court system. That manager faces potential prison. They clearly lose their job. They have a big loss of career earnings, so in the first place, they probably won’t do it. In India, you can’t —

COWEN: 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.

BLOOM: I was going to say, I use India, but it’s basically all developing countries and including, honestly, large parts of Southern Europe, is private equity. Look, you see all these badly run firms. Why doesn’t PE come in, buy out firms, and turn them around?

The problem is, the legal environment is not great. Blackstone came in, a big PE firm, bought a large apparel manufacturer in India, and really struggled because, sure, they can improve management practices, but profit wasn’t going up. There was 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 is, look, even if private equity doesn’t come in, why can’t they do it organically? And 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 it isn’t scaling. If you think of it, the frontier of management practice is improving every year. We’re getting better at managing firms in the US. Below that frontier, there are countries that are closest — 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 to diffuse, and a better legal system would accelerate that. If you could have ruthless private equity backed by tough laws, I think it will be painful economically and socially, but the growth rate would improve because you’d have much more transfer of management practices.

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

BLOOM: Another book on management — I’m not a huge book reader. Having said that, I’ve been recently reading Hillbilly Elegy, which is fantastic. 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 were some fantastic books.

COWEN: Let me re-point the question: Why are management books so bad? If I asked 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?

BLOOM: Yeah. There are great books, I’m sure. I don’t mean to imply they’re all terrible. I’m sure there are, but yeah.

COWEN: You go to the history section — most of the books are at least pretty good.

BLOOM: 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. I mentioned Raffaella Sadun, John Van Reenen, Renata Lemos, Daniela Scur, Erik Brynjolfsson, Lucia Foster. There’s a huge group of us that have been trying to measure management practices across firms and countries — just very methodically and, in some ways, very boringly.

Oh, we must have surveyed several million organizations by now to create a big dataset. We take populations of firms, run these surveys, collect data, and compare them.

Most of the books that I read that are popular — Good to Great and Built to Last and things like these — are generally based on individual anecdotes and case studies, and I think that’s great for teaching. I use case studies in the Harvard Business School all the time to teach because it’s very inspirational. [laughs] They’re always positive stories of how Mrs. X or Mr. Y turned the firm around, but they’re not great for research.

The reason is, I know from past experience, having to write one case study. I wrote a case study on a firm that was owned by someone that was in my Stanford MBA course called Gokaldas, and it’s called The Challenge of Change.

The problem was, we wrote this case study — it was a fascinating company that actually eventually got taken over by a private equity in India. They were a huge, very successful apparel firm. We had to get legal sign-off from everyone involved. We interviewed six or seven people, and they all had to legally sign off and say they were fine with us using the material.

You can imagine what that does for selection effects. It means that, basically, these books — it’s very hard for them to get proper information on firms that do badly because they refuse. They threaten lawsuits.

I think a lot of management research is correct. Most of these books are probably saying the right thing. The problem is that every story you want to come up with, every theory, there’s a book supporting it. It’s kind of hard to know where to look.

What we really need, ideally, is 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 — to say, “Look, here are five hypotheses of management. Is there support in large-scale data?” I think that will put more discipline on it and, therefore, put more credibility on these books.

COWEN: If teaching management techniques to companies is so effective, can we expect similarly large gains 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?

BLOOM: I’m not sure they’re pretty ineffective. I don’t know how to evaluate it. I could flip it around. I’ll tell you the economist’s take. I’m going to take your line on this, which is, there is an enormous volume of self-help books and podcasts and newsreels, et cetera. The fact that they exist means people are spending a lot of time reading them, 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. I don’t tend to listen to self-help podcasts, but I read a lot. I read something — there may be 10 tips in there. In fact, before the podcast started, I was talking to Dallas, your producer. She had sent me this whole list of things on what to do with your microphone and video. I had read it all. In fact, she included a link that I went onto. I found a couple of them really useful. I’d say 90 percent of them I’d seen, or maybe it wasn’t applicable, but 10 percent were great.

I actually think that, potentially, they 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 a thousand Americans or a thousand Spaniards or something, some sample, and then give 500 of them intensive self-help coaching for a month and see what happens. Quite possibly, somebody’s done this. It may exist, but that would be my way to evaluate these kinds of interventions.

COWEN: 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. 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.

But that strikes me as counterintuitive. I see people 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.

BLOOM: 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, there’s unknown unknowns. The problem is you don’t know what you don’t know.

Again, as a personal anecdote, I was recently given an energy efficiency. My brother came around a couple of years ago and pointed out, 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, and it paid off within two to three years.

That’s clearly a fantastic rate of return. That’s pretty rapid. I switched every single bulb in my house to LED. But I didn’t know it until someone had pointed it out. Ex post, it seems kind of obvious. I could have easily gone to Amazon and worked out the cost of it, worked the electricity uses and done the calculation. I just never thought of it.

A lot of this is like Dallas’s recommendations. She said, using this microphone, turn the gain thing down to zero. I didn’t realize that. There was a knob at the back of the microphone I’d never even looked at. I then looked at it. And, “Oh yeah, there is that.” Turned it down to zero and, hopefully, it sounds okay.

Honestly, you see this in firms all the time, and 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. For example, as another concrete piece of analysis, when I was out in India, a big issue in a lot of modern management is quality defects. These companies were large companies making, say, fabric, that goes into making shirts and trousers and upholstery coverings.

A lot of the learnings coming out originally from Japan is, you should zero in on quality defects and fix them instantly. Essentially, I said, “Look, your factory of a hundred looms — we’re going to take six looms at the back row and have a quality defect index and have a quality control process, a Kaizen process.”

After two to four weeks, it was so effective in spotting repeated issues that the factory owner said, “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. I think that — as with so many things in life, unfortunately — we just don’t know what we don’t know, and so we’re skeptical on advice.

COWEN: How bullish are you on Chinese management?

BLOOM: 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 okay. They weren’t fantastic. I’ve had some other surveys, but not internationally comparable.

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, and having educated employees. And China has those inputs. A lot of their manufacturing firms, in particular, are big. They’re competing ferociously with other companies.

Actually, Chinese education system is churning out vast numbers of engineers, and they’ve been operating 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. Their financial services — who knows as much? That’s harder to evaluate.

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 primogeniture — the eldest son inherits it. If you go into the sectors that don’t have these issues, then you tend to see very good management. In China, typically, tick most of those boxes in manufacturing.

COWEN: 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, ex ante, China seemed bad on all those things. Yet Chinese big business has done pretty phenomenally well.

BLOOM: A lot of trust, I think, derives from rule of law. In China — again, this is getting sensitive into politics, but there’s rule of law around political systems, 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 three years for providing ball bearings, I’m going to go and put a bit of money into R&D in improving and set up a process. If you then say after six 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 a kind of odd concept of trust.

It’s not based in some cultural, religious thing. It’s based on the fact that the legal system works. If you look in, for example, the World Value Survey, which measures interpersonal trust, trust measured there is highly correlated with 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’s in chaos because they’re undergoing civil war, and the highest countries are like Norway, Sweden, North America.

Currently in China, the rule of law as applied to commercial contracts, I think, is reasonable. I am not an expert, but you don’t hear endless stories of scandals and corruption, at least as commercial contracts go. 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.

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. If I want to set up a company and I can’t trust any outsiders, I start to stuff it full of sons, daughters, brothers, brothers-in-law, sisters, sisters-in-law, aunts, uncles, et cetera. Now, that’s good because I can trust them, but the problem is, these people aren’t naturally the best managers to run the place.

Of course, as I get bigger and bigger, I’m running out of good family members. Do I appoint a second cousin, or that pretty incompetent youngest son of mine? You can imagine the tradeoffs 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.

On Scottish management

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

BLOOM: [laughs] I don’t know if you know, my wife is a Scot.

COWEN: Yes, of course.

BLOOM: My mum is Scottish. I don’t think they’re that different, actually. 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. There are huge differences between Northern and Southern Europe. It 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 will probably kill me for saying that. The Scots, I should point out, have had some of the most successful members of the British government, like Gordon Brown and various prime ministers. They’re overrepresented. I don’t think they’re very different. I think, in fact, in reverse — they’re really pretty similar.

COWEN: 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 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.

BLOOM: It’s an interesting point. The Scots also voted what I would say is the right way on Brexit. They’re against Brexit. 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. I think this whole concept of being a little England — they’re looking inwards.

Scotland voted against Brexit quite resoundingly, and 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 in the way they vote. Their OECD-measured levels of education are not higher. I’m not aware of any other striking differences.

I like Nicola Sturgeon, who is, I think 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 in 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.

COWEN: Does Scotland have a different cultural notion of hooliganism?

BLOOM: If you know about the famous Old Firm rivalry, Celtic and Rangers, you probably think, “No.” The two Glaswegian teams. Again, in Scotland, I really spent the vast amount of my time in Glasgow. I wasn’t expecting, Tyler, to be asked about Scottish football hooliganism.

[laughter]

But as far as I’m aware, no.

The interesting thing, by the way, on technology — one of the issues that afflicted the UK was hooliganism. There’s various elements of it. One was just fighting and violence, but another one is racism, and in both of them, technology has been fantastic at combating. On both of them — cameras in the grounds, 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 Midlands making this stuff.

Just in terms of the ground, technology’s improved attendance at sports games. Because of this, we can stamp it out. That’s something that doesn’t show up in productivity figures. Another concern you could have — and is being a big debate in terms of productivity — is the case of the quality of life has risen in ways that we’re not measuring. I could get into that, but I think the answer is, primarily, no. You could make that claim, and hooliganism has been pushed back a lot by technology.

COWEN: 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.

BLOOM: Donald Trump, in terms of economic performance — how would you assess it? Before COVID, it was fine. Again, I’m not a Trump supporter, so definitely don’t get me wrong. You could be mildly positive on it, saying, “Look, he took the Obama boom and continued it.” As expansions go on, maybe you think it’s harder and harder to keep the expansion going. Growth didn’t pick up, but it also didn’t slow down on the Trump. That would be a passing grade. It wouldn’t be fantastic. It wouldn’t be terrible either.

One thing that aided growth on the Trump was the corporate tax cuts. There’s another political uncertainty in changing his mind all the time. Honestly, a lot of bad policy with reduced growth on the Trump.

It seems to have netted out to about zero. It was no higher or no lower than in Obama’s second term. The policy uncertainty was a negative, but there were other things he did that were positive. It is also true that under Obama, there was considerable policy uncertainty because of things like the debt ceiling debate and the fiscal cliff.

Who you blame is less obvious there. Congress was fighting the president. Obama wanted to pass various pieces of legislation and couldn’t. The same thing is true now, of course. We have 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 advisers.

When he talked to firms, it’s very hard to predict which way a 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’d use. Firms who complain about, “We didn’t see this coming.” He changed his mind and the tweets.

By the way, US physical investment, even before COVID, was not great.

COWEN: You talk about the intangibles, right?

BLOOM: Yes.

COWEN: The stock market is doing well.

BLOOM: Yes, but the stock market does not reflect the US economy. The stock market, for example — right now it’s 30 percent high tech, which has only 7 percent of US jobs. Also, when interest rates drop because the economy slows, it makes the stock market go up because it’s suddenly a relatively better investment. I think the stock market and the state of the US economy are only weakly linked.

COWEN: Say we take the 1960s, which is one of the golden eras for macroeconomic growth — many wonderful things about it. It seems policy uncertainty was quite high. There was the Cold War. There was the Vietnam War. It was 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. Anecdotally, very high policy uncertainty. Things proceeded just great, it seems. Or no?

BLOOM: 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. Often, it’s driven by their own personal experiences. There’s actually a phenomenon. It’s interesting you raised the ’60s. It’s actually phenomenal to think the past was more certain than the present because you see the past having happened. You forget all the alternative scenarios that could have been.

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 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 of 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 and stock market reactions — it doesn’t seem to be particularly high. The two great spikes in the stock market volatility by the end of the ’60s were the Cuban Missile Crisis and the assassination of JFK.

On how long working from home can work

COWEN: 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 a 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?

BLOOM: Great question. Just to be clear, my thoughts on work environment in the short run, working from home for those of us that can — only something like 40 percent of Americans can work from home, but that accounts for something like 50, 60 percent of GDP, because they tend to be higher-earning individuals.

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. I had an old paper looking at China, and it showed very large increases in workers’ short-run productivity from people working in call centers.

The big unknown I’m working in — I know other people are looking at this too — which is, what’s the impact on longer-run productivity, which is the concept — coming back to the beginning of the podcast — 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 that come up from water-cooler discussions and meetings and one-on-one stuff.

Obviously, under COVID, that’s all stalled. None of that we’re really sharp right now. You can get away with three to six, maybe even nine months, probably, of not radically creating new things. But in the long run, I fear there’d be a drop in, say, patenting in 2021, 2022 because of this. The question is how firms just run. My guess, from talking to a lot of US companies, is they will return partly to the office.

I think in the long run, working from home will be fine because we’ll be in the office three days a week and two days a week at home. That’s the best of both worlds. I don’t think you need to be in the office five days a week to be creative, but you do need some time each week with colleagues. I’m not too worried now. What I think will be problematic is, if in late 2021, we’re still all 100 percent working from home. Then I would really worry about impacts and productivity.

COWEN: Your long-term coauthors should be those who are at Stanford or Berkeley, but your short-term coauthors can be anywhere.

BLOOM: [laughs] I know, my coauthors 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, particularly the two last conferences we went to before lockdown. One was in Mexico — ITAM — and one was in Melbourne in Monash University. They were both fantastic because they were small, and I got to, basically, talk to everyone there.

That’s the kind of thing that generates, for me, coauthors — talking to someone of a quirky idea that comes up with something. Oddly enough, most of my coauthors 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’ve worked with a lot in Chicago. I never physically overlapped with him. Two others are Ivan Alfaro, Xiaoji Lin — I met them at Ohio State University. It is harder —

COWEN: If you can do it, why can’t tech companies do the same?

BLOOM: Let’s take Ivan and Xiaoji Lin from Ohio State University. I first met them physically. I went to give a seminar at Ohio State University. I sat in Xiaoji’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 it would have happened if we’d done it remotely. After talking to him, I thought, “This guy seems great. There’s a really interesting idea.” We continue to communicate by email.

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. This is the sense in which productivity now . . . I’ve been running masses of surveys on 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.

Now, again, to be clear, that’s July, and we’re three to four months into the lockdown. My theory is, if it were full-time working from home five days a week for another six to nine 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 nine months. Towards the end of it, it started to really grind and drag on. That was more about loneliness, but the other issue is in terms of being productive and being creative.

On the Nick Bloom production function

COWEN: 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?

BLOOM: [laughs] Go ahead, thank you.

COWEN: Now, most people at top-five schools in economics, as you know, also have PhDs from other top-five schools, but Nathan Nunn 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 has been its advantages and disadvantages for you?

BLOOM: For me, doing my PhD at UCL 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 sell or undersell Stanford, but there’s tradeoffs 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 off of a 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. It wasn’t a big program. Mostly there’s a mix. Many of them are not interested in ultimately going into academia. I was one of the few students that was focused. There were a few others, don’t get me wrong. There were about five or six 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. Not just faculty at UCL, but others through the IFS. People like Richard Blundell, John Van Reenen and Rachel Griffiths, Frank Windmeijer, Steve Bond. These guys were sitting around. Lucy Chennells — 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’s fantastic. This was something that had been out with Rachel for 5, 10 years.

Having that exposure is great. If I’d been in an enormous cohort of 25 of us per year, over six years, I never would’ve got that.

COWEN: So are the top five schools overrated for economics graduate study?

BLOOM: I think the question to ask is, what’s the value added? Remember, the top five schools recruit, by far, the best students. I know Stanford ranks the students. We often make offers to those at the top of the list, and we do pretty well at that. We typically get picked by MIT. The question is, what’s the value added? 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, I was better off having gone to UCL. It was a fantastic outcome for me versus anywhere else because I got to work with these people early on. I also have to say I’m very lucky because the IFS in that era was big into what they called micro econometrics, which is basically using panel data, which turned out to be exactly the way to go. So I was clearly fortunate. I just happened to be in a university when it was on the rise at the time.

COWEN: 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?

BLOOM: Yeah, the IFS was great. 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 I applied for IT jobs. I remember getting an offer from VZW, now long-closed British investment bank, to go work in the IT department and thought about it very seriously. So, all over the place. I took this job at the IFS — 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, there are questions you can talk to your friends in the pub about, which are the same ones, frankly, the New York Times or anyone . . . They’re not abstruse things like, “What happens in this model when alpha goes to seven,” but more like, “How would you increase growth rates?”

The IFS was very much about inspiring me to do this stuff, and it’s also entirely empirically focused. Again, that was in an era when empirical economics wasn’t so dominant. It is much more dominant now.

So, I just basically focused on data. And I was lucky at the IFS — I could do a part-time PhD. Just to be clear, when I started that, I was not a PhD student. They had a program encouraging people to go do part-time PhDs at UCL. I then went to start my PhD about nine months after joining the IFS at UCL. I was, oddly, an accidental PhD student. It was not something I ever had in mind.

COWEN: 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.

BLOOM: The IFS — at some point I left and went to work in McKinsey. I went to the UK treasury.

COWEN: Also atypical, right? Most people just go straight through — research, research, research.

BLOOM: I was clearly very lucky, so I wouldn’t advise, probably, my . . . Certainly going to work in McKinsey, as in leaving a PhD and going to a nonacademic job, probably, 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 under two years. I was fortunate the people I worked for before were running a research center. John Van Reenen, in particular, at the CEP, took me back. I was called a research officer. I was like a souped-up RA.

Then I started working in two areas. One was 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 to look in it, it was during the period of the Great Moderation. When I was working in uncertainty, I was looking at things like 9/11 as an enormous uncertainty shock, started to get into the topic. Business cycles were kind of quiet, people weren’t working on that that much. Then suddenly of course, ’08, ’09 happened and then COVID.

In hindsight, I wouldn’t advise that path. The issue is, it’s like first and second orders of the stochastic dominance. 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.

COWEN: 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?

BLOOM: Yeah, 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, saying — there was a huge shouting match about adjustment costs, and he said, “How can anyone get so excited about” — you know, Bob Hall has some famous papers on adjustment costs, so it’s kind of funny — “How can anyone get so animated and excited about something so boring?”

Bob and I and many others have worked in it. I realized halfway through my PhD, it was hard to excite other people about adjustment costs. I honestly stopped talking to people. Again, coming back to the public economics thing. My friends in particular — their eyelids would start drooping. I was just boring them to tears. That’s how I ended up morphing to looking at uncertainty.

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 thinking about working from home. Just to be clear, under COVID, with social distancing, working from home, I think this is going to last for another, let’s say a year. It’s hard to know. If, after a year or more, we are still social distancing and 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’d also think of it as adjustment costs, but this is why I think a lot of what’s happening now is going to stick, because of that. Yes, and in some senses, that has colored my thinking.

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

BLOOM: As we get older and older, it feels like our adjustment costs become higher and higher. I have these three areas I’m working on. Innovation I started working on. Management and uncertainty — the two I started working on more recently. Innovation — again, this is a random thing.

I don’t know how long ago it was; I had a summer internship, an unpaid internship — there’s a ministry long gone in the UK called the Department of Trade and Industry — to do a project looking at patents. This is 30 years ago. I remember putting up all the data on patents and that kind of interest in innovation stuff. I tend to think I’ve built up so much knowledge and interest in, particularly, management and uncertainty and innovation, I tend to mostly focus on that.

Although recently, through fortuitous luck, I was working with another couple of coauthors — again, I’ve never overlapped with Faith Guvenen and Sergio Salgado — looking at inequality and firms and skewness and other topics.

For me, I really like to read broadly rather than deeply — sounds an odd thing to say. Every Monday, for example, or Sunday night, the National Bureau of Economic Research has this 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 magazine. It’s good. It’s often been a source of ideas, actually.

We were talking before the call — I listen to your podcast. I 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. I mostly listen to podcasts. [laughs] If I’m getting too tired, I have to switch to music. For me, that’s been helpful for coming up with new research ideas.

COWEN: What do you think will be the next different thing that you do? It’s not just an extension of current work.

BLOOM: Geez, that’s hard to say. My best guess is — as you said, the other thing that’s really helpful for me is working with coauthors — will be some bright, sparky coauthor, grad student who will suggest, “We should look at X.” Maybe they’re not that interested in it. I say, “Oh, that’s a great idea.” Maybe at some point it turns into a collaboration.

Often, I’m giving a seminar. A lot of great ideas come from . . . For those who don’t go on the academic seminar, the way that academic seminars work is — because at GMU, not long ago — you go and give a talk, and then normally you get meetings in the morning and the afternoon.

A classic day will be, you turn up at 10:00 AM. You have half-hour meetings and then lunch, and there’s a talk in the afternoon and then dinner. What I really like is those one-on-one meetings because you’re talking to lots of people for half an hour. I find them fundamentally really tiring because you’re fully on.

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, but I find it really valuable. 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, the US economy is 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. I can easily Zoom current people I know, but it’s much harder to come up with random people at seminars you would’ve gone to, but clearly aren’t.

COWEN: Nick Bloom, thank you very much.

BLOOM: Tyler, thanks so much for having me. That was great.