Why didn’t ancient Rome have Dungeons and Dragons? I am talking, of course, about the game. Anton Howes presents the general problem:
A theme I keep coming back to is that a lot of inventions could have been invented centuries, if not millennia, before they actually were. My favourite example is John Kay’s flying shuttle, one of the most famous inventions of the British Industrial Revolution. It radically increased the productivity of weaving in the 1730s, but involved simply attaching a little extra wood and string. It involved no new materials, was applied to the weaving of wool — England’s age-old industry — and required no special skill or science. Weaving had been “performed for upwards of five thousand years, by millions of skilled workmen, without any improvement being made to expedite the operation, until the year 1733”, was how Bennet Woodcroft — one of the nineteenth century’s most important historians of technology — put it. (Lest you doubt that description of Woodcroft, he was, in addition to being an inventor himself, the man who compiled and categorised England’s entire patent record up to 1852, and who collected the inventions that would later form the basis of London’s Science Museum, particularly some of the earliest steam engines — among the most important machines in human history — that grace its engine hall today. My hero!) Weavers had been around for millennia, as had shuttles: one is even mentioned in the Old Testament (“My days are swifter than a weaver’s shuttle, And are spent without hope”). As a labour-saving invention, Kay’s flying shuttle was even technically illegal.
I keep coming back to this example, because it goes against so many common notions about the causes of innovation. When it comes to skill, materials, science, institutions, or incentives, none of them quite seem to fit. But I keep seeing more and more such cases. There’s the classic example, of course, of suitcases with wheels – why so late? Was the bicycle another candidate?
…The economist Alex Tabarrok calls these cases “ideas behind their time”. I tend to just call them low-hanging fruit. Hanging so low, and for so long, that the fruit are fermenting on the ground. I now see them everywhere, not just in history, but today — probably at least one per week. And I now have a new favourite example, suggested yesterday on Twitter by Jordan Chase-Young: tabletop role-playing games.
Was it lack of the right the bureaucratic mindset? Lack of numeracy? Lower population densitie? Were such games invented but then lost to history? Ultimately Howes rejects these explanations, I think correctly.
Physically, there was nothing that actually stopped the invention of such games centuries or even millennia earlier. It required no special level of science, skill, or materials. So why did it take so long? Rather than there being any constraints, soft or otherwise, I think it’s simply because innovation in general is so extremely rare. It’s a matter of absence, rather than of barriers. The reason we have had so many low-hanging fruit throughout history is just because very few people ever bother to think of how to do things differently. We are, most of us, quite set in our ways. So even today, when there are many more inventors alive than at any previous point in human history, the fermenting fruit still abound.
Innovation doesn’t happen very often. How many people have ever invented a new way of doing anything? If stasis is the norm, then we should expect that many great ideas are routinely overlooked. For an economist this is an uncomfortable thought because we tend to think that profit opportunities are quickly exploited (no $500 bills on the ground). But while that is certainly true for choices within constraints it may not be true for choices that change constraints. This is also consistent with Paul Romer’s views on the combinatorial space of possible innovations—when the combinatorial space is vast and the explorers few, the innovations will be few and far between. What times, places and institutions generate more explorers?
Jason Crawford on twitter has more background and thoughts.
Is the world fortunate that the coronavirus hit China first? China’s government has totalitarian impulses but that–for the most part– is working to its favor in combating the virus. What other country in the world could quarantine a city of 11 million people on the basis of (at the time) 17 reported deaths?
CNN: Across China, 15 cities with a combined population of over 57 million people — more than the entire population of South Korea — have been placed under full or partial lockdown.
Wuhan itself has been effectively quarantined, with all routes in and out of the city closed or highly regulated. The government announced it is sending an additional 1,200 health workers — along with 135 People’s Liberation Army medical personnel — to help the city’s stretched hospital staff.
China’s response to the virus has been unprecedented and one cannot help but be a little bit impressed.
I was in India recently and if the coronavirus hits India it could spread very rapidly and millions could die not just in India but around the world. India does not have a strong public health system (it has invested instead in sickness treatment, another example of premature imitation), it also has plenty of other opportunistic diseases and bacteria which would magnify viral sickness and overwhelm the public health system, and India does not have a state strong enough to effectively lock down cities. India’s only big advantage versus China is that it’s relatively free press and communication system could make an outbreak more quickly spotted. China, in contrast, tried to hide the initial outbreak. This does, however, cut both ways. India’s 1994 outbreak of the plague quickly became news, which led to official action, but hundreds of thousands of people quickly left the epicenter in Surat–smart action at the time but deadly if those fleeing are infectious.
We need a Manhattan Project to research, develop and produce new vaccines at a faster pace; the US is best placed to be the world leader in this regard. On other actions, the United States stands somewhere in between China and India. US quarantine action would certainly be slower than in China but it could happen, probably through the military, as we are seeing now.
The US approach of slow but eventually decisive action is probably best but how slow is too slow? Right now most people assume that the coronavirus is a blow to China but if does create a serious pandemic then China may be the first to recover and stabilize.
Hat tip: Lunch discussions with Robin, John and Ajay.
Innovation responds to both demand and supply. New scientific discoveries can arise exogenously and lower the cost of some types of innovation. Innovation, however, also responds to demand. The patenting of new energy devices increases as the price of oil increases. Similarly, new pharmaceuticals to treat diseases of old age increase as the number of elderly increase.
Similarly, the Civil War and World War I created a boom in the demand for artificial limbs and that in turn created a boom in innovation that led to better artificial limbs. The demand for new prosthetics was in some cases personal, as MacRae writes:
…the person who launched the era of modern prosthetics was also the first documented amputee of the Civil War–Confederate soldier James Edward Hanger. Hanger, who lost his leg above the knee to a cannon ball, was first fitted with a wooden peg leg by Yankee surgeons. Unhappy with the cumbersome appendage, Hanger eventually designed and built a new, lightweight leg from whittled barrel staves. Hanger’s innovative leg had hinges at the knee and foot, which helped him to sit more comfortably and to walk with a more natural gait. Hangar won the contract to make limbs for Confederate veterans. The company he founded–Hanger, Inc.–remains a key player in prosthetics and orthotics today.
In a highly original paper, Jeffrey Clemens and Parker Rogers document the increase in patents during the war eras but they also show that the type of innovation not just the quantity also responded to economic incentives.
In the Civil War era, the quantity of limbs demanded increased but the government was quite stingy in paying for artificial limbs. As a result, innovators focused on process innovations that enabled the production of more limbs at lower cost. In contrast, WWI payments were more generous and the government emphasized reintegrated soldiers into society which made appearance a more dominant feature in limb patenting.
More generally, Clemens and Rogers show how the type of procurement contracts directs not just the quantity but the form of innovation. The lessons are relevant for modern health care costs. Many people, for example, have wondered why innovation tends to lower costs in most fields but raise costs in health care. Clemens and Rogers point to the nature of procurement contracts as a possible important influence.
In Delhi, street hawkers will sell food, flowers, and balloons to cars paused at an intersection and, sadly, small children will dance for alms. My favorites are the book hawkers. I suspect Banerjee and Duflo would approve of my choice of both title and seller. Good price also.
The long-held belief that pollution is the cost a country has to pay for development is no longer true as bad air quality has a measurable detrimental impact on human productivity that could in turn reduce GDP, Canadian-American economist Alex Tabarrok said.
…“There is this old story that pollution is bad, but it increases GDP… When the United States and Japan were developing, they were polluted. So India and China also have to go through that stage of pollution — so that they get rich, and then they can afford to reduce pollution,” Tabarrok said.
“I want to say that that story is wrong. What I want to argue is that a lot of the new research indicates that we may be in a situation where we could be both healthier and wealthier at the same time by reducing pollution,” he said.
…At the seminar, Tabarrok pointed out that expecting people to make sacrifices for the sake of future generations is not a politically fruitful way to deal with pollution.
Citing the issue of crop burning in India, he said farmers are not going to be inclined to change their behaviour if they are told to stop stubble burning for the sake of Delhi residents.
“However, if these farmers are made aware of how the crop burning harms them and their families and affects their soil quality, they are more likely to participate in mitigation measures,” he said.
I was pretty tough on government policy as Business Today India reported:
More than half of India’s population lives in highly polluted areas. Research by Greenstone et al (2015) proves that 660 million people live in areas that exceed the Indian Ambient Air Quality Standard (NAAQS) for fine particulate pollution. In this context, having measures such as banning e-cigarettes and having odd-even days for vehicles to solve the problem of air pollution seems ridiculous, says Alex Tabarrok, Professor of Economics at the George Mason University and Research Fellow with the Mercatus Centre. “These are not appropriate solutions to the scale and the dimensions of the problem,” he says.
People suffering from diabetes have turned to sophisticated do-it-yourself technologies. Here’s the abstract to an excellent article on these developments by Crabtree, McLay and Wilmot:
Diabetes technology has been advancing rapidly over recent years. While some of this is driven by medical technology companies, a lot of the driving force for these developments comes from people living with diabetes (#WeAreNotWaiting) who have developed their own ‘do-it-yourself’ artificial pancreas systems (DIY APS) using continuous glucose monitoring, insulin pumps and smartphone technology to run algorithms shared freely with the intent of improving quality of life and glycaemic control. Existing evidence, although observational, seems promising but more robust data are required to establish the safety and outcomes. This is unregulated technology and the off-label use of interstitial glucose monitors and insulin pumps can be disconcerting for people living with diabetes, health care professionals, organisations, and diabetes technology companies alike.
Here we discuss the principles of DIY APS, the outcomes observed so far and the feedback from users, and debate the ethical issues which arise before looking to the future and newer technologies on the horizon.
Hat tip: Dennis Sheehan.
In a new paper, Robert Ellickson makes a simple but important point: local land-use zoning freezes land use into place preventing land from moving from low-value to high-value uses even over many decades.
Recall the neighborhood where you spent your childhood. For most Americans, it would have been a neighborhood of detached single-family houses.My thesis in this Article is simple: if you were to visit that same neighborhood decades from now, it would remain virtually unchanged. One reason is economic: structures typically are built to last. But a second reason, and my focus here, is the impact of law. The politics of local zoning, a form of public land use regulation that has become ubiquitous in the United States during the past century, almost invariably works to freeze land uses in a neighborhood of houses.
…The zoning strait-jacket binds a large majority of urban land in the United States. Los Angeles and Chicago, two of the nation’s densest central cities, permit the building of only a detached house on, respectively, 75% and 79% of the areas they zone for residential use. In suburban areas, the percentage typically is far higher. In a companion study of zoning practices of thirty-seven suburbs in Silicon Valley, Greater New Haven, and Greater Austin, I found that, in the aggregate, these municipalities had set aside 91% of their residentially zoned land (71% of their total land area) exclusively for detached houses.
…Absent overly strict regulation, suppliers of goods in a market economy are able to adapt to changes in supply and demand conditions. The freezing of land uses in a broad swath of urban America prevents housing developers from responding to changes in consumer tastes about where and how to live.
I’m in India and they have similar problem, except in India it’s agricultural land that is frozen in place and made difficult to transform to new uses (in the process depriving farmers of the true value of one of their only assets and creating opportunities for regulatory arbitrage that politically-connected special interests exploit by buying at the farm price, obtaining approvals to convert that other cannot obtain and then selling at the much higher post-conversion price.)
Freezing agricultural land in place seems backward because ubanization is clearly India’s future but it’s no less backward than what has happened in the United States. In both cases, an important right in the land bundle was expropriated and collectivized and the market process of creative destruction impeded.
In recent years, new research has significantly increased my belief that air pollution has substantial negative effects on productivity, IQ and health (see previous posts). Research in the field is exploding which means that there must also be more false positives. Consider two recent papers. The first, The Real Effect of Smoking Bans: Evidence from Corporate Innovation by Gao et al. finds that smoking prohibition increased patenting!
We identify a positive causal effect of healthy working environments on corporate innovation, using the staggered passage of U.S. state-level laws that ban smoking in workplaces. We find a significant increase in patents and patent citations for firms headquartered in states that have adopted such laws relative to firms headquartered in states without such laws. The increase is more pronounced for firms in states with stronger enforcement of such laws and in states with weaker preexisting tobacco controls. We present suggestive evidence that smoke-free laws affect innovation by improving inventor health and productivity and by attracting more productive inventors.
But the second, Do Firms Get High? The Impact of Marijuana Legalization on Firm Performance, Corporate Innovation, and Entrepreneurial Activity by Wang et al. finds that marijuana legalization increased patenting!
We find that state-level marijuana legalization has a positive financial impact on firms, likely by affecting firms’ human capital. Firms headquartered in marijuana-legalizing states receive higher market valuations, earn higher abnormal stock returns, improve employee productivity, and increase innovation. Exploiting firm level inventor data, we directly test the human capital channel and find that post legalization, firms retain inventors that become more productive and recruit more innovative talents from out of state. We also find that marijuana-legalizing states experience an increase in the number of new startups and venture capital investments.
Would anyone have been surprised if these two papers had shown exactly the opposite results? Indeed, there is some evidence that nicotine is solid cognitive enhancer and Tyler recently argued, on the basis of good evidence, that pot makes people dumb. Is it a coincidence that anti-cigarette and pro-pot papers appear as the country moves in this direction? Social desirability bias also applies to research. So no knock on either paper but I am unconvinced. As I like to say, trust literatures not papers.
Hat tip: The excellent Kevin Lewis.
I enjoyed the Dracula mini-series on Netflix–it’s smart, stylish and a fresh take. Also, at just three episodes, it’s satisfying without requiring a huge time investment.
Dracula has some pointed commentary on contemporary mores, including economics. After sleeping for a hundred years he finds himself in an ordinary home and speaks to the owner, Kathleen:
D: You’re clearly very wealthy.
D: Yes. Well, look at all this stuff. All this food. The moving picture box. And that thing outside, Bob calls it um, a car. And this treasure trove is your house!
K: It’s a dump.
D: Kathleen, I’ve been a nobleman for 400 years. I’ve lived in castes and palaces among the richest people of any age. Never….never! Have I stood in greater luxury than surrounds me now. This is a chamber of marvels. There isn’t a king, or queen or emperor that I have ever known or eaten who would step into this room and ever agree to leave it again.
I knew the future would bring wonders. I did not know it would make them ordinary.
The Mughals of Northern India are famous for their tombs, Humayun’s tomb in Delhi, Jahangir’s Tomb in Lahore and, of course, the Taj Mahal. Why so many tombs? Culture surely has something to do with it, although conservative Muslims tend to frown on tombs and ancestor worship as interference with the communication between man and God. Incentives are another reason.
Under the Mansabdari system which governed the nobility, the Mughal Emperor didn’t give perpetual grants of land. On death, all land that had been granted to the noble reverted back to the Emperor, effectively a 100% estate tax. In other words, land titling for the Mughal nobility was not hereditary. Since land could not be handed down to the next generation, there was very little incentive for the Mughal nobility to build palaces or the kind of ancestral homes that are common in Europe. The one exception to the rule, however, was for tombs. Tombs would not revert back to the Emperor. Hence the many Mughal tombs
Here is some lovely jali (stone lattice) work in Barber’s tomb in the Humayan tomb complex.
The Aga Khan Development Network has done some great restoration work on Isa Khan’s tomb, again in the Humayun’s tomb complex. Here’s the ceiling and another piece of jali work.
Private schools in India teach a remarkable 30-40% of the population, especially among the urban poor. (See my 2013 paper, Private Education in India: A Novel Test of Cream Skimming for more.) But private schools have come under increasing pressure in recent years from government regulation.
Inspired by projects like Doing Business the Center for Civil Society in India did a detailed examination of what it takes to open a private school in Delhi. This excellent video describes the results:
The US offers a limited number of H1-B visas annually, these are temporary 3-6 year visas that allow firms to hire high-skill workers. In many years, the demand exceeds the supply which is capped at 85,000 and in these years USCIS randomly selects which visas to approve. The random selection is key to a new NBER paper by Dimmock, Huang and Weisbenner. What’s the effect on a firm of getting lucky and wining the lottery?
We find that a firm’s win rate in the H-1B visa lottery is strongly related to the firm’s outcomes over the following three years. Relative to ex ante similar firms that also applied for H-1B visas, firms with higher win rates in the lottery are more likely to receive additional external funding and have an IPO or be acquired. Firms with higher win rates also become more likely to secure funding from high-reputation VCs, and receive more patents and more patent citations. Overall, the results show that access to skilled foreign workers has a strong positive effect on firm-level measures of success.
Overall, getting (approximately) one extra high-skilled worker causes a 23% increase in the probability of a successful IPO within five years (a 1.5 percentage point increase in the baseline probability of 6.6%). That’s a huge effect. Remember, these startups have access to a labor pool of 160 million workers. For most firms, the next best worker can’t be appreciably different than the first-best worker. But for the 2000 or so tech-startups the authors examine, the difference between the world’s best and the US best is huge. Put differently on some margins the US is starved for talent.
Of course, if we play our cards right the world’s best can be the US best.
Among experts it’s well understood that “big data” doesn’t solve problems of bias. But how much should one trust an estimate from a big but possibly biased data set compared to a much smaller random sample? In Statistical paradises and paradoxes in big data, Xiao-Li Meng provides some answers which are shocking, even to experts.
Meng gives the following example. Suppose you want to estimate who will win the 2016 US Presidential election. You ask 2.3 million potential voters whether they are likely to vote for Trump or not. The sample is in all ways demographically representative of the US voting population but potential Trump voters are a tiny bit less likely to answer the question, just .001 less likely to answer (note they don’t lie, they just don’t answer).
You also have a random sample of voters where here random doesn’t simply mean chosen at random (the 2.3 million are also chosen at random) but random in the sense that Trump voters are as likely to answer as are other voters. Your random sample is of size n.
How big does n have to be for you to prefer (in the sense of having a smaller mean squared error) the random sample to the 2.3 million “big data” sample? Stop. Take a guess….
The answer is…here. Which is to say that your 2.3 million “big data” sample is no better than a random sample of that number minus 1!
On the one hand, this illustrates the tremendous value of a random sample but it also shows how difficult it is in the social sciences to produce a truly random sample.
Meng goes on to show that the mathematics of random sampling fool us because it seems to deliver so much from so little. The logic of random sampling implies that you only need a small sample to learn a lot about a big population and if the population is much bigger you only need a slightly larger sample. For example, you only need a slightly larger random sample to learn about the Chinese population than about the US population. When the sample is biased, however, then not only do you need a much larger sample you need it to large relative to the total population. A sample of 2.3 million sounds big but it isn’t big relative to the US population which is what matters in the presence of bias.
A more positive way of thinking about this, at least for economists, is that what is truly valuable about big data is that there are many more opportunities to find random “natural experiments” within the data. If we have a sample of 2.3 million, for example, we can throw out huge amounts of data using an instrumental variable and still have a much better estimate than from a simple OLS regression.
A sad day for me. He was a big influence on my life growing up in Toronto and I’d always hope to meet “the professor.” Here is Red Barchetta one of Rush’s great liberty songs.
Addendum: Rolling Stone on Peart.