Freakonomics Radio - 310. Are We Running Out of Ideas?

Episode Date: November 30, 2017

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? ...

Transcript
Discussion (0)
Starting point is 00:00:00 Yeah, I know whenever I go to parties and people ask me, you know, what you do, and I say, I'm an economist, I say, what do you study? I say productivity, and they usually walk off at that point. Yeah, well, I can identify with that. If I then say, well, I actually, my measure of productivity is, you know, whether you stay alive, then that really gets people interested. Huh, that is interesting. Let's find out more, shall we? Today on Freakonomics Radio,
Starting point is 00:00:28 we will look at productivity in a whole new light. From the good. He estimates that you can make a house in about 24 hours. To the bad. 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. 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? The only way to tie these together is it's just getting harder and harder to find new ideas. From WNYC Studios, this is Freakonomics Radio, the podcast that explores the hidden side of everything. Here's your host, Stephen Dubner.
Starting point is 00:01:25 Let's start with the power of an idea. 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. 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,
Starting point is 00:02:09 you'd think that everyone would spend a lot of time searching for great ideas. That's not what Levitt sees. 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, executing on day-to-day things that could be transformed through the power of ideas. Lovett's idea about ideas is really just an idea. But what if we upgraded it to a hypothesis? Could this hypothesis then be tested? The power of ideas makes it something which is very different from any other goods. That's John Van Rienen, an economist at MIT.
Starting point is 00:02:51 Well, thanks for having me. And Nicholas Bloom is an economist at Stanford. Hi, Stephen. Good to hear from you. Bloom and Van Rienen, 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. So, you know, it took a long time for the first person to come up with the invention of the wheel,
Starting point is 00:03:21 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,
Starting point is 00:04:09 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 seem 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.
Starting point is 00:04:32 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. The most recent few years in the U.S. and globally have been so dismal and so depressing. We start to think, well, is this part of a longer trend? But what about all these amazing new technologies?
Starting point is 00:05:16 You know, living in Silicon Valley, I definitely, you know, drink the Kool-Aid and get very excited about the technology. But, you know, there's a but coming, right? But it just seems when you add up all the numbers, there just aren't enough new technologies very excited about the technology. But, you know there's a but coming, right? 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.
Starting point is 00:05:37 And, even more persuasive, there's the standard growth models used by economists. The standard model says, well, as long as you can keep that number of researchers researching and, you know, coming up with the new ideas, the kind of 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, you know, with most activities in life, you get diminishing returns, you know, you get more out from everything you put in, but the amount you get out slows down at a certain point. Can I just say, I'm so glad to hear you say exactly what you just said, because,
Starting point is 00:06:13 I mean, you've expressed my layperson's view of, you know, I guess what you call endogenous growth theory, and you expressed it much better than I ever could. But, you know, 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? Yeah, I mean, I think to give, you know, endogenous growth, you know, theory, it's due. I mean, you know, before then, the idea economists always thought that technology is critical for growth. But the assumption was that kind of that technology kind of dropped on us like manna from heaven. It was kind of exogenous, it was just going to continue. So actually trying to incorporate the choice of doing research and
Starting point is 00:07:11 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 that's going to go on forever with a fixed number of inputs, isn't something which I think is so compelling. That's the relationship that Van Rienen, 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. Moore's Law goes back to an observation made by Gordon Moore, who was one of the co-founders of Intel, way back in 1965. And he noticed that the number of transistors per square inch on a circuit
Starting point is 00:08:02 doubled roughly every other year. And that's led to something like every year, 35% improvements of productivity in semiconductors. So enormous rates of improvements of technological progress in that sector, driving the kind of digital revolution, the computer revolution. So people often point to this. So what we did was we say, OK, that's great. But to get that 35% improvement every year, how'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. It's so interesting because Moore's Law is held up as kind of the banner for human progress
Starting point is 00:09:09 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? Yeah, so it's become harder and harder. They do spend more and more money. The second case study, agricultural productivity. So agriculture is another nice sector to look at because you can look at crop yields produced per kind of acre of land.
Starting point is 00:09:36 Yeah, so productivity in agriculture has been declining for a long time. There was a huge, you know, a 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 kind of on the third down in the four-yard line. It's really grinding out yardage with, you know, incredible pain. Just like in semiconductors, you see that 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. Well, let me ask you related to agriculture, let's say agriculture versus semiconductors. Is there a correlation between an industry's
Starting point is 00:10:20 maturity, how long it's been around, you know, agriculture versus AI, let's say, and its growth rate? There is. I mean, certainly the more mature industries are going to struggle more to have faster rates of technology growth compared to the new sectors. So, you know, when you think about AI 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. So it is not true of more mature technologies. There's less that you can squeeze out. I think your broad point is right. There are possibilities of some improvements of technology,
Starting point is 00:10:58 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. 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. So we look at how different type of treatments have improved people's
Starting point is 00:11:31 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 the kind of quality of life that they live. Yeah, so mortality and life expectancy, you know, the numbers there are a great example 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 was 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.
Starting point is 00:12:17 We could again see something going forwards with genetic medicine. So this depressing downward trend isn't universal, certainly not by fields. You know, it's more of a roller coaster. I mean, there have been these, you know, phenomenal improvements in survivor 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,
Starting point is 00:12:57 and computer industries, the researchers also used the Compustat database to examine firm-level data across all sorts of industries. Yeah, so we also looked at, you know, thousands of firms publicly listed in the U.S., and we looked at how much they spent on R&D and how that translated into gains in sales, gains in employment, and gains in market capitalizations. And in all cases, you know, 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, you know, for a million dollars of R&D in the 60s, you got something like three times as much impact in terms
Starting point is 00:13:35 of sales as you would in the 80s. And again, it's been falling ever since. You know, the low-hanging fruit is all gone and it's becoming far harder. Between the R&D story, the case studies, and the fact that productivity growth is slowing in the economy as a whole, Van Rienen and Bloom think the data show a clear picture. 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, so to keep growth at a reasonable rate. And the only way to tie this together is it's just getting harder and harder to find new ideas. As our knowledge grows greater and greater, getting the next increments of knowledge,
Starting point is 00:14:23 the next idea becomes more challenging. Think of some of the most important innovations that have happened, things like penicillin. So Alexander Fleming, he basically, you know, discovered it on his own, or flight, the Wright brothers, they more or less invented, you know, the modern aircraft or the electric light. Thomas Edison in the US and Charles Swan in the UK 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 a LED factory the other day.
Starting point is 00:14:57 And the LED factory for modern light, it looks like something out of the Terminator movie with machines and robots everywhere. But they also told me they've spent hundreds of millions in R&D. So in every case, you know, huge inventions that have changed the world seem to in history come from one or two individuals. And now it's taking huge corporations, you know, 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.
Starting point is 00:15:31 So the basic assumptions in these models that a given number of scientists or expenditure in R&D would deliver a fixed amount of growth is just wrong. So how upset should we be at the economics profession? Ooh, should we be upset? Of course we shouldn't be upset with the economics profession. I mean, in this case, it's, you know, don't shoot the messenger. You know, we're kind of delivering some hard truths. I mean, of course, fair enough. You know, I think in Greek legend, the messenger got shot and it was the crow. But in this case, I'm hoping I don't get shot.
Starting point is 00:16:09 Coming up after the break, what if these economists who are saying the other economists were wrong, what if they're the ones who are wrong? In other words, what if there are a lot of new ideas in the pipeline that might create a productivity explosion. 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... But, you know, why are we so obsessed with growth? That's coming up right after this. 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
Starting point is 00:17:11 there just aren't as many good ideas. 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. So my training is as a parasitologist. That's Kelly Wienersmith. I study parasites that manipulate the behavior of their hosts at Rice University.
Starting point is 00:17:41 I draw a comic called Saturday Morning Breakfast Cereal. And that is Zach Wienersmith. And I run a show called The Festival of Bad Ad-Hoc Hypotheses. The Wienersmiths are a married couple, and they've written a book together called Soonish, 10 Emerging Technologies That'll Improve and or Ruin Everything. This is the first time we've sort of formally worked together on something big. 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.
Starting point is 00:18:18 Quote, this is one of those books where we predict the future. Fortunately, predicting the future is pretty easy. So it's just it's 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 Wienersmiths 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.
Starting point is 00:18:55 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. In terms of, you know, 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. I don't know, maybe you'll go to Mars and they come back with some sort of 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.
Starting point is 00:19:29 Okay, let's say space travel is not the productivity game changer we're looking for. How about another hot technology, fusion energy? The Wienersmiths are kind of cool on this one, too. 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. 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 3D printer that builds you a new organ layer by layer. Also, synthetic biology.
Starting point is 00:20:07 A big exciting thing is you can create organisms that make complex molecules that we like, such as medicines or fuels. And precision medicine. 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.
Starting point is 00:20:33 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. 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.
Starting point is 00:20:59 So that seems like a good benefit. 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. 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. So my opinions are largely negative on that.
Starting point is 00:21:34 But to an economist, that might seem great. One of the most promising technologies to boost productivity, augmented reality. So the idea with augmented reality is through your augmented reality glasses or through the iPhone or iPad that you're looking through. And maybe in the future, that's a contact lens or something. You're looking at the real world
Starting point is 00:21:53 and layered on top of the real world are things that don't really exist there. 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. There's companies who are integrating augmented
Starting point is 00:22:09 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. 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. 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 primetime technology, robotic construction.
Starting point is 00:22:50 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. 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. It slaps mortar down, sticks a brick on, and just keeps rolling, and does it very quickly. And SAM, coupled with a person, is able to work three times faster than one person
Starting point is 00:23:26 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. Baruch Koshnevitz at the University of Southern California. And what this is, is essentially a giant gantry, so like an upside-down U that has a 3D 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,
Starting point is 00:23:57 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 that 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. 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,
Starting point is 00:24:30 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 all this shakes out is a big question, big set of questions, really. It's something we've looked into before on this show and past episodes like how safe is your job and is the world ready for a guaranteed basic income? Because if machines can do most of our work better, faster, cheaper, and more safely, how does that change the shape of a society that's built around human labor? Here's what the MIT economist Eric Brynjolfsson told us earlier. We're now beginning to have machines be able to augment and automate our brains
Starting point is 00:25:22 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 do 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? It brings to mind Stanley Kubrick's 2001 A Space Odyssey and the rebellious computer robot HAL. Technologically speaking, we are just about there. Open the podious computer robot HAL. Technologically speaking, we are just about
Starting point is 00:26:06 there. Open the pod bay doors, HAL. I'm sorry, Dave. This mission is too important for me to allow you to jeopardize it. 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 Rienen.
Starting point is 00:26:39 I asked Bloom which camp he puts himself in, techno-optimist or techno-pessimist. 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 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,
Starting point is 00:27:10 these kind of depressing futuristic technologies. But I see more of the same, which is, you know, slow growth eked out by millions of scientists and engineers around the world working away in labs. We're not saying growth is going to stop. It's just getting more and more expensive. But, you know, why are we so obsessed with growth? Yeah, I mean, you've basically just summarized my view, which is that, I mean, twofold. A, why are we, and by we, I mean you, economists, so obsessed with growth? Because I think that's where we, the populace, gets this idea from, which is that
Starting point is 00:27:46 economists have been preaching for the past, I don't know, 50, 80 years, that growth is kind of 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% growth. So why are we so obsessed with growth? Well, 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 kind of 2000 years of which growth was, people estimate,
Starting point is 00:28:31 about 0.1%. It then exploded to 1% during the Industrial Revolution. If you think of what's happening now, we're something like, you know, 2%. So compared to most of the history of humankind, we have actually incredibly high growth rates now and should be very thankful. 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. You know, I think our expectations have been normed by, you know, 40, 50 years of fantastic growth since World War II. So, you know, it, 50 years of fantastic growth since World War II. So, you know, it's like take a very rich man and make him rich.
Starting point is 00:29:09 He feels poor. Much like, you know, we've had 3%, 4% growth since World War II. We've now, inverted commas, plummeted to 2% growth. But again, if you look back to, you know, our great grandparents would have been incredibly happy with 2% growth since that was faster than anything they'd ever seen before in their time and, you know, generations back over the history of humankind. John Van Rienen agrees that we should appreciate the dramatic growth of the past, but he also recognizes the limits of that appreciation.
Starting point is 00:29:41 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'll be better off than the 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?
Starting point is 00:30:23 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 actually we're facing massive tax bills. Right. So if you were the politician, you would say, look, here's the sad truth,
Starting point is 00:31:00 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? If I was an honest politician, I would, you know, face up to the fact growth is slowing down. You know, 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. All right. So let's pretend you are, however, an honest politician or an advisor to an honest politician. What kind of policy prescriptions would you make based on your findings in this paper, Nick? I would spend more on research and development. So we can have higher growth
Starting point is 00:31:45 with more R&D. So the ways to do that was 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, science and engineering, more government labs. So what you see in the U.S. is why 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 has actually been cut. John Van Rienen offers another policy idea drawn from a paper he wrote with several co-authors. It's called The Life Cycle of Inventors.
Starting point is 00:32:32 They analyze data from more than 1.2 million U.S. inventors from 1996 to 2014. 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 one of the most striking things was if you're born to family in the top one percent of the income distribution you were 10 times more likely to grow up to be an inventor than if you're born in the bottom 50 of the income distribution and one story why that is is well maybe you know kids of rich parents just so much smarter than the kids of poor parents but we could look at the kind of test scores of what you know what these kids got at a very early age, like in third grade, and we found that the kind of ability in maths and other subjects,
Starting point is 00:33:10 although it was higher for the rich kids and the poor kids, there wasn't so much difference that it could explain these kind of very large differences in future invention rates. And so what we argued in that paper is that if you're born into a poor family or if you're in some disadvantaged group, there are, you know, big barriers to you growing up to becoming an inventor. This is a big loss to American society. If you could kind of remove those some of those barriers to becoming inventors, you might actually find some lost Einsteins, some people who could really make a huge difference to, you know, knowledge and productivity of the economy. One of the ways you might want to improve the rate of invention and the rate of growth
Starting point is 00:33:50 is to think about kind of policy interventions to help improve the chances of disadvantaged kids becoming inventors. So who's right? The techno-optimists or the techno-pessimists? 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 Wienersmith. The one thing that gives me a little bit of optimism is I think somewhat famously in the 19th century physics,
Starting point is 00:34:30 there were a lot of people that thought they had reached the point where we were just figuring out the details. Now we 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're in that situation. I like to say it's very important to remember that there's a strong cognitive bias to 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
Starting point is 00:35:19 probably somewhere in the middle. Nice. Let's raise a glass to being somewhere in the middle. Nice. Let's raise a glass to being somewhere in the middle. Coming up next time on Freakonomics Radio, the problems with ticket pricing. This is a market that's been screwed up for a long time. We talked to a lead producer of Hamilton. There was a point where we knew that up to 70% of our tickets were being purchased through automated bots. We talked to a former bot wizard and scalper. Everybody's making money on scalping. Yeah, everybody from top to bottom. And we talked to some very disappointed
Starting point is 00:35:58 Bruce Springsteen fans. I don't know. I think I'm just going to go for a drink or something. It's next time on Freakonomics Radio. Freakonomics Radio is produced by WNYC Studios and Dubmere Productions. This episode was produced by Greg Brzozowski. Our staff also includes Allison Hockenberry, Merit Jacob, Stephanie Tam, Harry Huggins, and Brian Gutierrez. We had help this week from Dan DeZula. The music you hear throughout the episode was composed by Luis Guerra. Thank you. You can also read the transcripts and find links to the underlying research. We can also be found on Twitter, Facebook, or via email at radio at Freakonomics.com. Thanks for listening.

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