Our latest Freakonomics Radio episode is called “Are We Running Out of Ideas?” (You can subscribe to the podcast at Apple Podcasts or elsewhere, get the RSS feed, or listen via the media player above.)

Economists have a hard time explaining why productivity growth has been shrinking. One theory: true innovation has gotten much harder – and much more expensive. So what should we do next?



Below is a transcript of the episode, modified for your reading pleasure. For more information on the people and ideas in the episode, see the links at the bottom of this post.



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John VAN REENEN: Yeah. I know whenever I go to parties and people ask me, “What you do?” and I say “I am an economist,” they say, “What do you study?” I say “productivity.” And they usually walk off at that point.

Yeah, well, I can identify with that.

VAN REENEN: And if I then say, “Well, actually my measure of productivity is whether you stay alive,” then that really gets people interested.

Hmh, that is interesting. Let’s find out more, shall we? Today on Freakonomics Radio: we will look at productivity in a whole new light. From the good …

Kelly WEINERSMITH: He estimates you can make a house in about 24 hours.

To the bad …

Kelly WEINERSMITH: We’ve been working on it for over 50 years, and we still haven’t managed to make it power a toaster.

To the ugly …

Zach WEINERSMITH: So we might destroy our species as we know it while chasing total-factor productivity.

Wait a minute – what does powering a toaster and building a house in 24 hours have to do with destroying our species? What ties all these together?

Nicholas BLOOM: The only way to tie these together is: it’s just getting harder and harder to find new ideas.

* * *

Let’s start with: the power of an idea.

Steve LEVITT: I am a believer in the power of ideas, and the kind of ideas that I really cherish are those ideas that are incredibly simple.

That’s my Freakonomics friend and co-author Steve Levitt. He’s an economist at the University of Chicago.

LEVITT: I’ve really come to think that many companies that are successful are really successful on the back of one or two simple ideas. I often get the feeling that they believe they’re good at everything — when the evidence is probably that they’re about average at everything, except for one or two things that they happen to be really good at.

If ideas are so powerful, and if all it takes is one or two great ideas to make a company successful, you’d think that everyone would spend a lot of time searching for great ideas. That’s not what Levitt sees:

LEVITT: I am a believer that, in general, people spend far too little time devoted to trying to come up with ideas and far too much time, in contrast, in executing on day-to-day things that could be transformed through the power of ideas.

Levitt’s idea about ideas is really just … an idea. But what if we upgraded it to a “hypothesis”? Could this hypothesis then be tested?

VAN REENEN: The power of ideas makes it something which is very different from any other goods.

That’s John Van Reenen, an economist at M.I.T.

VAN REENEN: Well, thanks for having me.

And Nicholas Bloom is an economist at Stanford:

BLOOM: Hi, Stephen, good to hear from you.

Bloom and Van Reenen, along with two more economists, Charles Jones and Michael Webb, have written a paper with a deliciously provocative title. It’s called “Are Ideas Getting Harder to Find?” It begins with the assumption that ideas are, indeed, extraordinarily powerful. That a good idea can create exponential leverage.

VAN REENEN: So, it took a long time for the first person to come up with the invention of the wheel, but once that was discovered, lots of other people could start using that information to make wheels. New ideas can spread very easily and can actually drive the forces of productivity growth.

Economists see a natural connection between an idea and productivity, and the growth thereof. And, for economists, productivity growth is a really big deal. It’s what keeps pushing our standards of living higher. Which means it’s a big deal for the rest of us. It’s incorporated into all our economic models – like the ones that tell governments and firms how much money to set aside for future budgets and pensions and healthcare costs. If you base your calculations on a certain growth rate, and then the growth rate falls – well, that’s a problem. For many decades, our economy grew at a robust and fairly predictable rate. The computer revolution, and all its bounty, seemed to suggest more of the same. We spoke about this with the economist Robert Gordon in an earlier episode. It was called “Yes, the American Economy Is in a Funk – But Not for the Reasons You Think.”

GORDON: Yes, during the heyday of the dot-com revolution, we had our nationwide measures of progress, namely productivity growth, catching up, briefly, for about a decade to the kinds of measures of progress that we had back in the Second Industrial Revolution. So it was transformative. But it didn’t last long. The revival of productivity growth occurred only between about 1995 and 2005.

And what about lately? Nick Bloom again:

BLOOM: The most recent few years in the U.S. and globally have been so dismal and so depressing, we started to think, “Well, is this part of a longer trend?”

But what about all these amazing new technologies?

BLOOM: You know, living in Silicon Valley, I definitely drink the Kool-Aid and get very excited about the technology.

But…? You know there’s a “but” coming, right?

BLOOM: But it just seems when you add up all the numbers, there just aren’t enough new technologies to offset the decline.

How can that be? We’re being bombarded by new technologies. And, even more persuasive, there’s the standard growth models used by economists.

VAN REENEN: The standard model says, “Well, as long as you can keep that number of researchers researching and coming out with the new ideas — the self-driving cars, the new drugs, the new technologies, we’ll continue to have those rates of growth.” But that’s always been a bit weird to me in a sense, because with most activities in life you get diminishing returns. You know, you get more out from anything you put in — but the amount you get out slows down at a certain point. Stephen DUBNER: Can I just say I’m so glad to hear you say exactly what you just said, because — you’ve expressed my layperson’s view of I guess what you call Endogenous Growth Theory. And you expressed it much better than I ever could. But in this paper, you write here — I’ll quote you to yourself: “a key assumption of many endogenous growth models is that a constant number of researchers can generate constant exponential growth.” And to me as a non-economist, that just sounds absurd. I mean, your profession is the one that invented the phrase “diminishing returns,” so why on earth should the assumption be that growth is not only constant, but exponential? VAN REENEN: Yeah, I mean, I think to give to give Endogenous Growth Theory its due, before then, the idea, economists always thought technology is critical for growth, but the assumption was that technology dropped on us like manna from heaven. It was exogenous. It was just going to continue. So actually trying to incorporate the choice of doing research and development, to create innovations, I think, is a very strong part of Endogenous Growth Theory. So that part I like where I think this other assumption, as you said, sounds a bit, you know, that’s going to go on forever with a fixed number of inputs does — isn’t something which I think is so compelling.

That’s the relationship Van Reenen, Bloom, and their colleagues set out to explore – the relationship between growth and technology, including where the ideas for new technologies come from. Their paper includes three primary case studies. The first deals with the computer industry, and what’s known as Moore’s Law.

BLOOM: Moore’s Law goes back to an observation made by Gordon Moore, who is one of the co-founders of Intel back way, way, way back in 1965. And he noticed that the number of transistors per square inch on a circuit doubled roughly every other year. VAN REENEN: And that’s led to something like, every year, 35 percent improvements of productivity in semiconductors. So enormous rates of improvements of technological progress in that sector driving the kind of digital revolution/computer revolution. So people often point to this. So what we did was we said, “Okay, that’s great. But to get that 35 percent improvement every year, how much research and development had to go into doing that?” And what we show — the amount of research going into semiconductors has enormously increased, but productivity growth in that sector hasn’t accelerated. BLOOM: So back in 1965, there were a few teams around the country working on this. Now, there’s hundreds and hundreds of millions, billions, globally spent on trying to improve the speed of silicon chips. And as a result, we calculate the amount of resources has gone up by 25-fold. So we’ve had a 25-fold increase in inputs just to maintain the same speed. DUBNER: It’s so interesting, because Moore’s Law is held up as the banner for human progress, and the amazing gains that technology has to offer. And you’re saying, “Yeah that benefit is real, but the costs have just been totally overlooked, at least by people outside the industry,” yeah? BLOOM: Yes. It’s become harder and harder. And they do spend more and more money.

The second case study: agricultural productivity.

VAN REENEN: So agriculture is another nice sector to look at because you can look at crop yields produced by acre of land. BLOOM: Yeah, so productivity in agriculture has been declining for a long time, though there was a huge burst of productivity growth between the ’30s and the ’60s with modern hybrid seeds, with better fertilizer, with better farm management. But most of those gains have been eked out. American farmers, in fact, are incredibly efficient and businesslike. And as a result, now, it’s third down on the four yard line; it’s really grinding out yardage with incredible pain. VAN REENEN: Just like in semiconductors, you see the amount of R&D which has gone in has been very large in order to maintain more or less the same rate of growth. DUBNER: Well, let me ask you, related to agriculture — let’s say agriculture versus semiconductors: is there a correlation between an industry’s maturity, how long it’s been around, agriculture versus A.I., let’s say, and its growth rate? VAN REENEN: There is. Certainly the more mature industries are going to struggle more to have fast rates of technology growth compared to the new sectors. So, when you think about A.I. or some parts of medicine or virtual reality — those are areas where they’ve come from nothing. So, their rate of productivity growth is enormous! Which is not true of more mature technologies. There’s less that you can squeeze out. So, I think your broad point is right. There are possibilities of some improvements of technology. But across all of them, you see in order to get those, you have to put more resources in to be able to get that juice out. DUBNER: Okay, so you’ve looked at semiconductors, you’ve looked at agriculture. I think a lot of people, even if they don’t deal in economics at all, can relate to the idea of productivity growth in those fields. But the next one is a little bit different: mortality and life expectancy. Talk about what you were looking for there, what the data were, and what you found. VAN REENEN: So, we look at how different types of treatments have improved people’s life expectancy. So, treatments towards breast cancer or other forms of cancer. To what extent has research there helped improve people’s length of life and that kind of quality of life that they live? BLOOM: Yeah, mortality and life expectancy. You know, the numbers there are great examples of the offsetting forces. We looked at the cost to increase a human life-year. And in fact, you see over most of the time that’s been increasing. But there is actually a surge in productivity in the late ’80s and ’90s; and that was part of the era of modern professionalization of drug discovery. So pharmaceutical firms got very effective at mass screening of thousands of compounds in a more automated way; and of course, that made them more productive. We could again see something going forwards with genetic medicine. So this depressing downward trend isn’t universal, certainly not by field. You know, it’s more of a roller coaster. VAN REENEN: I mean, there have been these phenomenal improvements in survival rates after cancers and other kinds of diseases. But in order to get those, again, we’ve had to put in huge amounts of resources in terms of research and development; and those have increased by very large orders. And it hasn’t improved at the accelerating rate that you’d expect, given the amount of research dollars which have gone into it.

In addition to the case studies in the medical, agricultural, and computer industries, the researchers also used the Compustat database to examine firm-level data across all sorts of industries.

BLOOM: Yes, so we also looked at thousands of firms publicly listed in the U.S. And we looked at how much they spent in R&D and how that translated into gains in sales, gains in employment, and gains in market capitalizations. And in all cases there’s a positive relationship. The more you spend, generally the more you sell, and the more valuable you are. But that relationship has been falling over time. So for a million dollars of R&D in the ’60s, you got something like three times as much impact in terms of sales as you would in the ’80s. And again, it’s been falling ever since. The low-hanging fruit has all gone, and it’s becoming far harder.

Between the R&D story, the cases studies, and the fact that productivity growth is slowing in the economy as a whole, Van Reenen and Bloom think the data show a clear picture.

BLOOM: Growth is slowing down at the same time as we’re spending ever more money on research and development. So what that tells us is it’s just taking more and more dollars of R&D to increase growth, or to increase output, to keep growth at a reasonable rate. And the only way to tie these together is it’s just getting harder and harder to find new ideas. VAN REENEN: As our knowledge grows greater and greater, getting the next increments of knowledge, the next idea becomes more challenging. BLOOM: Think of some of the most important innovations that have happened; things like penicillin. Alexander Fleming, he basically discovered it on his own. Or flight. The Wright Brothers. They more or less invented the modern aircraft. The electric light, Thomas Edison in the U.S. and Charles Swann in the U.K. independently basically came up with modern lights. They were massive inventions that came about from one or two people more or less tinkering around in their own labs. So I visited an L.E.D. factory the other day. And the L.E.D. factory for modern light bulbs looks like something out of the Terminator movie — machines and robots everywhere — but they also told me they’ve spent hundreds of millions on R&D. So in every case huge inventions that have changed the world seemed to in history come from one or two individuals. And now it’s taking huge corporations, universities, and the government hundreds or typically billions of dollars to push it ahead.

Again, this is not what economists had been predicting. Economists had predicted that new technologies would continue to push growth forward.

BLOOM: So, the basic assumptions in these models, that a given number of scientists or expenditure on R&D will deliver a fixed amount of growth, is just wrong. DUBNER: So, how upset should we be at the economics profession? BLOOM: Ooh, should we be upset? Of course we shouldn’t be upset with the economics profession. I mean in this case it’s don’t shoot the messenger. We’re delivering some hard truths. I mean, sure, of course, fair enough, I think in the Greek legend the messenger got shot. I think it was the crow. But in this case I’m hoping I don’t get shot.

What if these economists who are saying the other economists were wrong – what if they’re the ones who’re wrong? In other words, what if there are a lot of new ideas in the pipeline that might create a productivity explosion?

Zach WEINERSMITH: If you improve people’s IQs, they tend to become not just more productive, but happier, more social, less likely to commit crimes, that sort of thing.

And: we’ve all been told about the need for continuing economic growth. But…

BLOOM: But why are we so obsessed with growth?

* * *

So, a bunch of economists have recently concluded that a bunch of other economists — the entire economics profession, really — has historically been kind-of wrong about economic growth. That growth has slowed in large part because there just aren’t as many good ideas.

BLOOM: You know, the low-hanging fruit is all gone, and it’s becoming far harder.

And these economists have assembled a mountain of data to make this argument. But that doesn’t necessarily mean they’re right, either. Let me introduce you to a couple of people who offer a different view. Warning: they are not economists.

Kelly WEINERSMITH: So my training is as a parasitologist.

That’s Kelly Weinersmith.

Kelly WEINERSMITH: I study parasites that manipulate the behavior of their hosts at Rice University. Zach WEINERSMITH: I draw a comic called Saturday Morning Breakfast Cereal …

And that is Zach Weinersmith.

Zach WEINERSMITH: … and I run a show called The Festival of Bad Ad Hoc Hypotheses.

The Weinersmiths are a married couple. And they’ve written a book together, called Soonish: Ten Emerging Technologies That’ll Improve and/or Ruin Everything.

Zach WEINERSMITH: This is the first time we’ve formally worked together on something big. Kelly WEINERSMITH: It was definitely stressful, but that was because he had a full-time job as a cartoonist, I had a full-time job at Rice University, and I was pregnant, and we had a two-year-old. So it was nuts, but it was a good time.

Soonish begins with some welcome sarcasm: “This is one of those books where we predict the future. Fortunately, predicting the future is pretty easy.”

Kelly WEINERSMITH: So it’s just really hard to make these kinds of predictions, and just about all the data suggests that the people who make these predictions are often wildly wrong. They all, almost always still have jobs, which is good for those people.

The first emerging technology the Weinersmiths look at is space travel. It currently costs somewhere around $10,000 per pound to escape Earth’s gravity. Which is a lot. But reusable rockets from companies like SpaceX and Virgin Galactic could change that.

Kelly WEINERSMITH: Well, if you can bring that cost way down, then you can imagine that it would be much cheaper to launch satellites, for example. And if you launch satellites, then our communication systems are going to get better. They’re going to get cheaper. Zach WEINERSMITH: In terms of going to other planets, it’s not clear to me how you get rich other than having tourists. And that’s awesome, and I’m all for it, but as far as I know, it doesn’t boost productivity. Maybe people go to Mars and they come back with some sort of a better sense of self, and they become more productive, but I doubt it. Yeah, so, beyond tourism, the economic applications of space are pretty questionable.

Okay, let’s say space travel isn’t the productivity game-changer we’re looking for. How about another hot technology — fusion energy? The Weinersmiths are kind of cool on this one too.

Kelly WEINERSMITH: Because we’ve been working on it for over 50 years, and we still haven’t managed to make it something that we can use to, for example, power a toaster.

Okay, but here’s an idea they’re bullish on: biotechnologies. Bioprinting, for instance:

Kelly WEINERSMITH: So the idea here is that you harvest cells from an individual who has an organ that’s failing. You grow up those cells in large numbers, and then you put them through a 3-D printer that builds you a new organ layer by layer.

Also: synthetic biology.

Zach WEINERSMITH: A big exciting thing is just you can create organisms that make complex molecules that we like, such as medicines or fuels.

And: precision medicine.

Kelly WEINERSMITH: So the idea with precision medicine is that if we know enough about you in particular, we can figure out the best treatment for exactly the disease that you have, and the best treatment for you in particular.

We could also, using the CRISPR gene-editing tool, address entire diseases in the gene pool. We looked at this possibility in an earlier episode called “Evolution, Accelerated.” And then there’s the idea that brain-computer interfaces could jack up our cognitive abilities. Which might have a lot of positive externalities.

Zach WEINERSMITH: And so there’s pretty robust evidence that if you improve people’s IQs, they tend to become not just more productive, but happier, more social, less likely to commit crimes, that sort of thing. So that seems like a good benefit. Kelly WEINERSMITH: So at the moment, these devices are being used for things like trying to give amputees the ability to move their arms again, or to move their fingers again. But it’s possible that at some point many of us will have devices on our brain that help us be a little bit more efficient. Zach WEINERSMITH: The ominous thing there is — and this is already happening with pharmaceuticals — is once one person is using, everybody else in the industry is going to feel the obligation to use. So there’s this weird thing where we might destroy our species as we know it while chasing total-factor productivity. My opinions are largely negative on that, but to an economist that might seem great.

One of the most promising technologies to boost productivity? Augmented reality:

Kelly WEINERSMITH: So the idea with augmented reality is through your augmented-reality glasses, or through the iPhone or iPad that you’re looking through— Zach WEINERSMITH: And maybe in the future that’s a contact lens or something— Kelly WEINERSMITH: You’re looking at the real world, and layered on top of the real world are things that don’t really exist there. Zach WEINERSMITH: And so, there are obviously entertainment applications for this. But from an economic perspective, there’s a lot of amazing stuff. So, one, you could drastically cut down training time. Kelly WEINERSMITH: There’s companies who are integrating augmented reality into construction helmets. And the task that the people did was done with fewer errors, the very first time, when they were wearing these helmets. Zach WEINERSMITH: It’s not just that you can do it because you have the system set up. You actually learn how to do it faster. So the economic benefit of that could be huge, especially right now when some people argue there’s a skills mismatch. So if you can fix that skills mismatch without having to have people go to two years of training, if you can cut it down to a year or six months, that’s potentially really huge. Kelly WEINERSMITH: So in general, it could make our workforce more efficient, more likely to catch errors before they happen, and it could make training happen much more quickly.

Another almost-ready-for-prime-time technology: robotic construction.

Zach WEINERSMITH: If you look around your office, mostly you’re going to see things that were cheaply manufactured in mass-manufacturing systems. And that’s why they’re relatively inexpensive compared to what it would have cost to hand-make them. Buildings are essentially handmade. Kelly WEINERSMITH: Yeah. So robotic construction is an area that I’m particularly really excited about. And so one of the robots that we came across was a robot called SAM, or the Semi-Automated Mason. And SAM is a robot that’s able to lay bricks. Zach WEINERSMITH: It slaps mortar down, sticks a brick on, and just keeps rolling and does it very quickly. Kelly WEINERSMITH: And SAM, coupled with a person, is able to work three times faster than one person alone. And so you can imagine that that could have really major impacts on home-building. And there are a number of other technologies that we came across, for example, a technology called Contour Crafting, which is made by Dr. Behrokh Khoshnevis at the University of Southern California. And what this is, is essentially a giant gantry — like an upside-down U — that has a 3-D printer attached to it, that uses a special kind of concrete, and it makes the outside of the house. And it also has an arm, so as the house is being built, it sticks pipes in and stuff as it goes. So the only thing you have to do at the end of the day is stick the windows and the door in, when you’re finished printing out the rest of the house. And he estimates you can make a house in about 24 hours, and I believe it was for something like $5,000. So pretty cheap, and super-fast, relative to how long it takes to make and build a house now. Zach WEINERSMITH: So there are all sorts of exciting possibilities. And I think it’s pretty obvious how that would improve productivity. You’re either going to make individual construction workers a whole lot more productive on the job, or perhaps a bit more ominously, you might just replace them entirely, which obviously on paper economically makes the average worker more productive, though it would displace a lot of people. And how that would shake out is questionable, especially in the short term.

How this all shakes out is a big question; a big set of questions, really. It’s something we’ve looked into before on this show — in episodes like “How Safe Is Your Job” and “Is the World Ready for a Guaranteed Basic Income?” Because if machines can do most of the work we need done better, faster, cheaper, and more safely – well, how does that change the shape of a society that’s built around human labor? Here’s what the M.I.T. economist Erik Brynjolfsson told us earlier:

Erik BRYNJOLFSSON: We’re now beginning to have machines be able to augment and automate our brains and replace mental tasks. Machines can do computations and make decisions. And we’re still in the early stages of this, but we believe that the implications will be at least as profound as what the Industrial Revolution did for our muscles.

This of course raises even more questions. What will we do with all the time we used to spend working? If we’re not being paid to work, where will our money come from? And: will those machines and robots eventually conclude that we humans aren’t worth having around? A lot of technologists and economists see a huge upside in the spread of artificial intelligence. And they say that upside will show up in the productivity numbers before long. Others are more pessimistic. One reason for pessimism? Good ideas are getting harder and harder to find. That, at least is the theory put forth by Nick Bloom and John Van Reenen. I asked Bloom which camp he puts himself in: techno-optimist or techno-pessimist.

BLOOM: Ooh, good question. I’m going to claim I’m a techno-realist. But if that has to put me in one of those two camps, I guess a techno-pessimist. You know, if you claim the optimists see a future where everything’s fantastic and growth explodes — I just don’t see that happening. You know, look back over the last 40–50 years, extrapolate out. And growth continues — but you know, there’s no nirvana over the rainbow. It’s certainly not Clockwork Orange or Wall-E, these kind of depressing futuristic technologies but — I see more of the same, which is slow growth eked out by millions of scientists and engineers around the world working away in labs. We’re not saying growth’s going to stop. It’s just getting more and more expensive. But you know, why are we so obsessed with growth? DUBNER: Yeah. I mean you’ve basically just summarized my view, which is two-fold: A) Why are we, and by “we,” I mean you, economists, are so obsessed with growth, because I think that’s where “we,” the populace, gets this idea from, which is that economists have been preaching for the past, I don’t know, 50, 80 years that growth is the natural, necessary state of the body economic, and that if it doesn’t proceed apace, then we’re in a lot of trouble. And there’s a lot of malaise associated with 1 or 2 percent growth. So why are we so obsessed with growth? BLOOM: We like growth because growth enables us to spend more money on things that we like. So: schools, hospitals, cars, nice meals out. But on the other hand, there’s no necessary level of growth. If you look back at humanity from about the Roman Empire to something like 1800, there was almost no growth. So there’s 2,000 years at which growth was — people estimate about 0.1 percent. It then exploded to 1 percent during the Industrial Revolution. If you think of what’s happening now with something like 2 percent. So compared to most of the history of humankind, we have actually incredibly high growth rates now, and should be very thankful. DUBNER: Yeah. So why aren’t we? Other than the fact that we had what may turn out to have been a temporary Golden Era of absurdly high growth. BLOOM: You know, I think our expectations have been normed by 40, 50 years of fantastic growth since World War II. So it’s like, take a very rich man and make him rich — he feels poor. It’s much like we’ve had 3 or 4 percent growth since World War II. We have now — our outcome has plummeted to 2 percent growth. But again, if you look back to, you know, our great-grandparents would have been incredibly happy with 2 percent growth, since that was faster than anything they’d ever seen before in their time, and generations back over the history of humankind.

John Van Reenen agrees that we should appreciate the dramatic growth of the past. But he also recognizes the limits of that appreciation.

VAN REENEN: People seem extremely angry that the growth rates that they got used to over the last 50 years don’t seem to be happening. My impression is that most people are not at all comfortable with that — that they have come to expect that they will be better off than their parents were. And the fact that seems not to be happening is something which I think is creating a lot of political and social unrest all over the West at the moment.

So if we can agree that more growth is better than less growth; and if we can agree that good ideas are both a) necessary for better growth and b) increasingly harder to find – what’s to be done about it?

BLOOM: I think the people that should be listening to this seriously is our politicians. Because the thing that worries me most is our pensions and budget deficits are all based on, frankly, unrealistic growth numbers. So the way it works is you go to Washington, they look back at growth over the last 20, 30 years and say, “Hey, presto, this is what we’re going to get over the next 20, 30 years. So, we can now spend a lot of money and pay it back later.” But if, unfortunately, the U.S. economy doesn’t grow like that, we’ll discover when we all come to retire, there’s nothing left in the pension pot, and that you are facing massive tax bills. DUBNER: Right. So, if you were the politician, you would say, “Look here’s the sad truth, is that productivity is a lot more expensive to come by now,” or “growth is more expensive to come by now. And if we want to keep having it, we have to take money from elsewhere and put it here.” Is that essentially a sort of policy-ish prescription you would advise? BLOOM: If I was an honest politician, I would face up to the fact growth is slowing down. You have to be realistic; if I was a politician fighting for political survival, you know I may be tempted to fudge it a bit and kind of ignore the issue. DUBNER: All right. So let’s pretend you are, however, an honest politician or an adviser to an honest politician. What kind of policy prescriptions would you make based on your findings in this paper, Nick? BLOOM: I would spend more on research and development. So we can have higher growth with more R&D. So the ways to do that is obviously make it more tax-advantageous for firms — so, a more generous R&D tax credit. More government funding— This is why it seems like an insider job, but honestly more government funding to research in universities, and science and engineering. More government labs! So what you see in the U.S. is while private firms’ R&D expenditure has risen, that tends to be more development, more market-focused research. The more basic R of R&D, the research, the kind of high-level stuff is actually done more in government labs and universities and the funding for that is actually being cut.

John Van Reenen offers another policy idea, drawn from a paper he wrote with several co-authors. It’s called “The Lifecycle of Inventors.” They analyzed data from more than 1.2 million U.S. inventors from 1996 to 2014.

VAN REENEN: We found many things, but I think one of the most striking things was if you were born to a family in the top 1 percent of the income distribution, you are ten times more likely to grow up to an inventor than if you’re born in the bottom 50 percent of the income distribution. And one story why that is – well, maybe kids of rich parents are so much smarter than the kids of poor parents. But we could look at the kind of test scores of what these kids got at a very early age, like in third grade. We found that the kind of ability in maths and other subjects, although it was higher for the rich kids than the poor kids, it wasn’t so much different that it could explain these kind of very large differences in future invention rates. So what we argue in that paper is that if you’re born into a poor family, or if you’re in some disadvantaged group, there are big barriers to you growing up to becoming an inventor. This is a big loss to American society. If you could remove some of those barriers to becoming inventors, you might actually find some lost Einsteins, some people who you could really make a huge difference to knowledge and productivity of the economy. One of the ways you might want to improve the rate of invention and the rate of growth is to think about policy interventions to help improve the chances of disadvantaged kids becoming inventors.

So who’s right – the techno-optimists or the techno-pessimists? If there’s one thing we’ve learned over the years doing this show, it’s that predicting the future is a fool’s game. But: a lot of research suggests that, at the very least, optimism is good for your health. So let’s go out with this, from Soonish co-author Zach Weinersmith:

Zach WEINERSMITH: The one thing that gives me a little bit of optimism, is I think somewhat famously in the 19th century physics, there were a lot of people that thought they’d reached the point where, “We were just figuring out the details now. We’ve basically got it figured out.” And then there was Einstein and the quantum revolution. Given the preponderance of people in history, who thought we were out of new things, we should at least be a bit reticent to, at the present moment, decide that we are in that situation. I like to say, it’s very important to remember that there’s a strong cognitive bias to consider that you are at the end of history, because the history books all end with you. But for any given thing, whether it’s increasing human productivity, or it’s some sort of social or cultural institution, wherever you are right now is probably the middle, not the beginning or end, because the middle is the big part of most things. So I think the optimist in me wants to say that the adventure that was started sometime in the 18th century is probably still continuing. We’re probably somewhere in the middle.

Nice. Let’s raise a glass to being somewhere in the middle!

Freakonomics Radio is produced by WNYC Studios and Dubner Productions. This episode was produced by Greg Rosalsky. Our staff also includes Alison Hockenberry, Merritt Jacob, Stephanie Tam, Harry Huggins, and Brian Gutierrez; the music throughout the episode was composed by Luis Guerra. You can subscribe to Freakonomics Radio on Apple Podcasts, Stitcher, or wherever you get your podcasts. You can also find us on Twitter, Facebook, or via email at radio@freakonomics.com.

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