Obviously his talents in crypto and programming are well-known, but he is also a first-rate thinker on both economics and what you broadly might call sociology. You could take away the crypto contributions altogether, and he still would be one of the very smartest people I have met. Here is the audio and transcript. The CWT team summarized it as follows:
Tyler sat down with Vitalik to discuss the many things he’s thinking about and working on, including the nascent field of cryptoeconomics, the best analogy for understanding the blockchain, his desire for more social science fiction, why belief in progress is our most useful delusion, best places to visit in time and space, how he picks up languages, why centralization’s not all bad, the best ways to value crypto assets, whether P = NP, and much more.
Here is one excerpt:
COWEN: If you could go back into the distant past for a year, a time and place of your choosing, you have the linguistic skills and immunity against disease to the extent you need it, maybe some money in your pocket, where would you pick to satisfy your own curiosity?
BUTERIN: Where would I pick? To do what? To spend a year there, or . . . ?
COWEN: Spend a year as a “tourist.” You could pick ancient Athens or preconquest Mexico or medieval Russia. It’s a kind of social science fiction, right?
BUTERIN: Yeah, totally. Let’s see. Possibly first year of World War II — obviously, one of those areas that’s close to it but still reasonably safe from it…
Basically, experience more of what human behavior and what collective human behavior would look like once you pushed humans further into extremes, and people aren’t as comfortable as they are today.
I started the whole dialogue with this:
I went back and I reread all of the papers on your home page. I found it quite striking that there were two very important economics results, one based on menu costs associated with the name of Greg Mankiw. Another is a paper on the indeterminacy of monetary equilibrium associated with Fischer Black.
These are famous papers. On your own, you appear to rediscover these results without knowing about the papers at all. So how would you describe how you teach yourself economics?
Highly recommended, whether or not you understand blockchain. Oh, and there is this:
COWEN: If you had to explain blockchain to a very smart person from 40 years ago, who knew computers but had no idea of crypto, what would be the best short explanation you could give them, basically, for what you do?
BUTERIN: Sure. One of the analogies I keep going back to is this idea of a “world computer.” The idea, basically, is that a blockchain, as a whole, functions like a computer. It has a hard drive, and on that hard drive, it stores what all the accounts are.
It stores what the code of all the smart contracts is, what the memory of all these smart contracts is. It accepts incoming instructions — and these incoming instructions are signed transactions sent by a bunch of different users — and processes them according to a set of rules.
Wealthier countries allocate a greater proportion of their workers to science and engineering, fields which produce ideas that often benefit everyone. This is one reason why we all gain when other countries become rich. It’s not just the number of scientists and engineers that matters, however. In a clever paper, Agarwal and Gaule demonstrate that equally talented people are more productive in wealthier countries.
Agarwal and Gaule collect the scores of thousands of teenagers who entered the International Math Olympiad between 1981 and 2000 and they follow their careers. Every additional point earned at the Olympiad increases the likelihood that a participant will later earn a math PhD, be heavily cited, even earn a Fields medal. But Olympians from poorer countries are less likely to contribute to the mathematical frontier than equally talented teens from richer countries. It could be that smart teens from poorer countries are less likely to pursue a math career–and that could well be optimal–but Agarwal and Gaule find that many of the talented kids from poorer countries simply disappear off the world’s radar. Their talent is wasted.
The post-Olympiad loss is not the largest loss. Most of the potentially great mathematicians from poorer countries are lost to the world long before the opportunity to participate in an Olympiad. But it is frustrating that even after talent has been identified, it does not always bloom. We are, however, starting to do better.
You can see from the graph that upper-middle income countries are as good as turning their talent into results as high-income countries. Agarwal and Gaule also find some evidence that the low-income penalty is diminishing over time.
As incomes increase around the world it’s as if the entire world’s processing power is coming online for the first time in human history. That, at least, is one reason for optimism.
Hat tip: Floridan Ederer.
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I see this claim in my Twitter feed pretty often, but I don’t get how it is supposed to run. Let’s try an analogy with the non-human animal kingdom.
Right now there are many cows in the world, and even more potential cows to be bred, or cows in low-value situations that could be moved around by boat or even helicopter, if need be. Call it the “moo reserve army of the unemployed.” If the market as a whole increased its demand for cows, the price of cows would go up. It would not make sense to say “that happens only when all the cows are busy all the time and there are no extra cows or potential cows left.” Very likely, there is an upward-sloping cost curve for mobilizing more cows.
To be sure, under a constant cost assumption, the price of cows would not go up, following an increase in demand. The quantity of eligible, working cows would rise, stifling upward price pressure, and possibly this would take the form of a Malthusian equilibrium. But note: in this situation you should expect the price of cows never to go up, as the cost structure is preventing that.
Alternatively, you might think that demand for cows and the cost structure for cow expansions interact in some very particular way. If you pinned this down in just the right manner, you could model a situation where an increase in demand for cows won’t boost the price of cows now, but in broader situations the price of cows can sustainably rise. Indeed that is possible, I just don’t see particular reason to believe that such a convoluted construction is doing most of the explanatory work for current labor markets.
I look at it this way: measured wages for male labor near the median haven’t gone up much in decades, and this is poorly understood (you may or may not think the same is true for actual real wages, and for women the story is somewhat more complicated). So if measured wages for non-supervisors are not going up much now, that is hardly a huge shock. The fact that we don’t understand it well doesn’t mean some remaining particular hypothesis — in this case about the size of reserve armies — has to be the true one.
Most cow parables, upon closer examination, collapse into structural explanations anyway. And in labor markets, it is almost always both blades of the scissors that matter.
Addendum: You might try a matching model. Imagine that potential workers are fully passive, stoned so to speak, but will accept credible good offers from well-capitalized employers. The cost structure of the workers, or worker search, does not influence the outcome. Over the course of the recovery, employers invest more in searching for the right workers because their profits are higher and they make a successively greater number of offers to well-suited workers, but at constant wages. The number of employed keeps on rising, wages stay flat, but longer-run wages nonetheless may rise with productivity (and with enough bids for their labor, workers move out of passive strategies). I’m not saying this is a good representation, only that it might capture the claimed mix of flat wages and a large reserve pool of labor, yet without forcing wages into a longer-run flatness. It also suggests, by the way, that some measure of monopoly/high profits has been good for social welfare, as it has boosted employment.
Yes, I am continuing to read David Edgerton’s The Rise and Fall of the British Nation: A Twentieth Century History, and it is one of the must-read non-fiction books of this year. Here are a few points I gleaned from my time spent with the book on the plane last evening:
1. During WWII, British imports kept to their pre-war levels, with imports of munitions picking up the slack. The book stresses how much the British empire did in fact pay off, as Britain through a variety of mechanisms forced or induced its colonies to lend it resources during this critical time. Along some dimensions, the British economy became more global due to the conflict.
2. In 1942, exports from Malaya (mostly rubber) to the U.S. were higher than UK exports to the U.S. at that time.
3. Early in the 20th century, wheat in Great Britain was about ten times more expensive than coal. Britain was the largest importer of food, and in essence sold coal for foodstuffs.
4. British coal was centered in rural areas, and this kept British country life economically vital. Furthermore this mining was largely horse-powered.
5. From the end of WWII to the 1980s, more people left Britain than migrated to it.
6. Goods trade as a percentage of gdp was about 32% for Britain around 1920, and then lower at about 20% in 2000.
I hope to write about this book more, but I’ll tell you two of the overall messages right now. One is that the history of British economic globalization is more lurching and back and forth than you might think. Another is that British industry was more successful, innovative, and scientific during periods of supposed decline than you might think.
And by the way, while we are on the topic of must-read books, here is another rave review for Varlam Shalamov.
When people evaluate two or more goods separately versus jointly it’s common to see “preference reversals”. In a random survey, for example, people were asked to value the following dictionaries:
- Dictionary A: 20,000 entries, torn cover but otherwise like new
- Dictionary B: 10,000 entries, like new
When asked to value just one dictionary, either A or B, the average value was higher on Dictionary B. But when people were asked to evaluate both dictionaries together the average value was higher on Dictionary A.
What’s going on? Most people have no idea how many words a good dictionary has so telling them that a dictionary has 10K or 20K entries just fades into the background–it’s a dictionary of course it defines a lot of words. On the other hand, we all know that “like new” is better than “torn cover” so dictionary A gets the higher price. When confronted with the pair of dictionaries, however, we see that Dictionary A has twice as many entries as Dictionary B and it’s obvious that more entries makes for a better dictionary and in comparison to more entries, the sine qua non of a dictionary, the torn cover fades into importance.
- Baseball Card Package A: 10 valuable baseball cards, 3 not-so-valuable baseball cards
- Baseball Card Package B: 10 valuable baseball cards
- Congressional Candidate A: Would create 5000 jobs; has been convicted of a misdemeanor
- Congressional Candidate B: Would create 1000 jobs; has no criminal convictions
In each case B tends to have a higher value when evaluated separately but A tends to evaluate higher with joint evaluation. When is separate evaluation better? When is joint evaluation better?
There is a tendency to think that joint evaluation is always better since it is the “full information” condition. Sunstein pushes against this interpretation because he argues that full information doesn’t mean full rationality. Even with full information we may still be biased. The factor that becomes salient when the goods are evaluated jointly, for example, need not be especially relevant. Is a dictionary with 20k entries actually better than one with 10k entries? Maybe 95% of the time it’s worse because it takes longer to find the word you need and the dictionary is less portable. We might let the seemingly irrefutable numerical betterness of A overwhelm what might actually be more relevant, the torn cover.
Sellers could take advantage of the bias of joint evaluation by emphasizing information that consumers might think is important but actually isn’t–our computer screen has 1.073 billion color combinations while our competitors only has 16.7 million–while making less salient 6 hours of battery life versus 8 which may in practice be more important.
Personally, I’d go for full information and trust myself to figure out what is truly important but maybe that is my bias. See the paper for more examples and thought-experiments.
From David Card, Ciprian Domnisoru, and Lowell Taylor, the last few sentences are the most interesting:
We use 1940 Census data to study the intergenerational transmission of human capital for children born in the 1920s and educated during an era of expanding but unequally distributed public school resources. Looking at the gains in educational attainment between parents and children, we document lower average mobility rates for blacks than whites, but wide variation across states and counties for both races. We show that schooling choices of white children were highly responsive to the quality of local schools, with bigger effects for the children of less-educated parents. We then narrow our focus to black families in the South, where state-wide minimum teacher salary laws created sharp differences in teacher wages between adjacent counties. These differences had large impacts on schooling attainment, suggesting an important causal role for school quality in mediating upward mobility.
This result is not logically inconsistent with the signalling model, but I think it fits more readily into the human capital story. If you think employers cannot easily distinguish between different qualities of worker (without the educational signal, that is), probably you also should think employers cannot distinguish among the quality of adjacent schools on the basis of what they pay their teachers in relative terms. And in that case, the schools hiring the better teachers are probably increasing the productivity of their students.
For the pointer I thank the excellent Samir Varma.
By Michael Lovenheim and Alexander Willén:
Teacher collective bargaining is a highly debated feature of the education system in the US. This paper presents the first analysis of the effect of teacher collective bargaining laws on long-run labor market and educational attainment outcomes, exploiting the timing of passage of duty-tobargain laws across cohorts within states and across states over time. Using American Community Survey data linked to each respondent’s state of birth, we examine labor market outcomes and educational attainment for 35-49 year olds, separately by gender. We find robust evidence that exposure to teacher collective bargaining laws worsens the future labor market outcomes of men: in the first 10 years after passage of a duty-to-bargain law, male earnings decline by $2,134 (or 3.93%) per year and hours worked decrease by 0.42 hours per week. The earnings estimates for men indicate that teacher collective bargaining reduces earnings by $213.8 billion in the US annually. We also find evidence of lower male employment rates, which is driven by lower labor force participation. Exposure to collective bargaining laws leads to reductions in the skill levels of the occupations into which male workers sort as well. Effects are largest among black and Hispanic men. Estimates among women are often confounded by secular trend variation, though we do find suggestive evidence of negative impacts among nonwhite women. Using data from the 1979 National Longitudinal Survey of Youth, we demonstrate that collective bargaining laws lead to reductions in measured non-cognitive skills among young men.
Augur is finally live.
The decentralized platform for betting on real-world predictions was one of the first applications built on top of the ethereum blockchain, and its creators sold “reputation” (REP) tokens for over $5 million in 2015 – a time when few were talking about “ICOs” or “utility coins.” A public beta version of the platform came out the following year, and its team published a revised version of its white paper in January.
Now, the Forecast Foundation, the not-for-profit behind Augur’s development, has announced the launch of the long-awaited platform, which was accompanied by the release of the final version of the Augur application as open-source software.
Augur allows participants to bet on anything.
As long as the outcome can be verified in the real world, users can create a prediction market for anything from ether’s price, an election in Brazil or the outcome of Iceland v. Argentina in the World Cup.
What distinguishes Augur from a traditional betting market is that no single party sits in the middle, meaning that users are likely to pay lower prices.
Removing the centralized intermediary from a betting market presents a problem, however: how to bring dispersed, financially interested parties into agreement about the actual outcome of the predicted event?
In Augur’s system, the creator of a prediction market designates a “reporter” to vet the outcome. This designated entity puts down a deposit of REP tokens, which they lose if they incorrectly report the outcome and other REP holders challenge them. The reporter is compensated through fees.
Day-to-day betting is not done in REP, but in ether, the native token of the ethereum blockchain (though, eventually, the plan is to support other ethereum-based tokens). Users can buy and sell shares in particular predictions, which are priced according to the likelihood the market attaches to each outcome.
Tens of thousands of studies correlate family socioeconomic status with later child outcomes like income, wealth and attainment and then claim the correlation is causal. Very few such studies control for genetics, although twin adoption studies suggest that genetics is important. Cheap genomic scanning, however, has made it possible to go beyond twin studies. A new paper, for example, looks at differences in education-associated genes between non-identical twins raised in the same family and they find that children with more education-associated genes tend to have greater educational attainment and higher income later in life. In other words, differences in child outcomes both across families and within the same family are in part driven by genetics.
Surprisingly, however, the authors also find evidence for “genetic nurture” the idea that parental genes drive child environment which drives outcomes. That’s surprising because it’s hard to find strong evidence for big environmental effects in adoption studies but here the authors can rely on more precise data. Specifically, the authors look at maternal education-associated genes that are NOT passed on to the children and yet they find that such genes are also correlated with important child outcomes (fyi, they only have maternal genes). So smart parents benefit children twice. First by passing on smart genes and second–even when they do not pass on smart genes–by passing on a smart environment. Previous studies missed the latter effect perhaps because they focused on rich parents rather than smart parents (the former being easier to measure). The authors suggest that by looking at how smart parents help kids without smart genes we may be able to figure out smart environments and generalize them to everyone. That strikes me as optimistic.
Here is the paper abstract:
A summary genetic measure, called a “polygenic score,” derived from a genome-wide association study (GWAS) of education can modestly predict a person’s educational and economic success. This prediction could signal a biological mechanism: Education-linked genetics could encode characteristics that help people get ahead in life. Alternatively, prediction could reflect social history: People from well-off families might stay well-off for social reasons, and these families might also look alike genetically. A key test to distinguish biological mechanism from social history is if people with higher education polygenic scores tend to climb the social ladder beyond their parents’ position. Upward mobility would indicate education-linked genetics encodes characteristics that foster success. We tested if education-linked polygenic scores predicted social mobility in >20,000 individuals in five longitudinal studies in the United States, Britain, and New Zealand. Participants with higher polygenic scores achieved more education and career success and accumulated more wealth. However, they also tended to come from better-off families. In the key test, participants with higher polygenic scores tended to be upwardly mobile compared with their parents. Moreover, in sibling-difference analysis, the sibling with the higher polygenic score was more upwardly mobile. Thus, education GWAS discoveries are not mere correlates of privilege; they influence social mobility within a life. Additional analyses revealed that a mother’s polygenic score predicted her child’s attainment over and above the child’s own polygenic score, suggesting parents’ genetics can also affect their children’s attainment through environmental pathways. Education GWAS discoveries affect socioeconomic attainment through influence on individuals’ family-of-origin environments and their social mobility.
You can find the appendix with the key results here. I find the lab style difficult to follow. The authors run regressions, for example, but you won’t find a regression equation followed by a table with all the results. Instead the regression is described in the appendix and then some coefficients, but by no means all, are presented later in the appendix.
I’ve been saying this for a while, here is an excellent piece by Shawn Donnan at the FT:
Since it was first created in 1975 as an inter-agency committee, Cfius has been able to review foreign investments only on narrow national security grounds. But if it adopts the broad Trumpian definition of national security as economic security, this could open a whole new range of transactions to its scrutiny. Might a mid-western auto plant that makes components purely for civilian vehicles suddenly be treated as a national security asset and be banned from foreign ownership?
Presidents have for years resisted efforts in Congress to require Cfius to consider an economic benefits test when it approves large foreign investments, as similar bodies do in countries such as Australia and Canada. Mr Trump, however, seems to be embracing the idea. Legislation to reform Cfius, which the Trump administration will have broad powers to shape in its implementation, is nearing its final journey through Congress.
Maybe they’ll have to revise the Star Wars prequels too…
Here is a kind of gravity equation for science:
We develop a simple theoretical framework for thinking about how geographic frictions, and in particular travel costs, shape scientists’ collaboration decisions and the types of projects that are developed locally versus over distance. We then take advantage of a quasi-experiment – the introduction of new routes by a low-cost airline – to test the predictions of the theory. Results show that travel costs constitute an important friction to collaboration: after a low-cost airline enters, the number of collaborations increases by 50%, a result that is robust to multiple falsification tests and causal in nature. The reduction in geographic frictions is particularly beneficial for high quality scientists that are otherwise embedded in worse local environments. Consistent with the theory, lower travel costs also endogenously change the types of projects scientists engage in at different levels of distance. After the shock, we observe an increase in higher quality and novel projects, as well as projects that take advantage of complementary knowledge and skills between sub-fields, and that rely on specialized equipment. We test the generalizability of our findings from chemistry to a broader dataset of scientific publications, and to a different field where specialized equipment is less likely to be relevant, mathematics. Last, we discuss implications for the formation of collaborative R&D teams over distance.
That is from a new paper by Christian Catalini, Christian Fons-Rosen, and Patrick Gaulé.
That is the topic of my latest Bloomberg column, here is one bit:
Instead, it is education that is arguably Mexico’s most fundamental problem. In most emerging economies, if you are ambitious and seek higher wages, you will invest in more education. Mexicans have traditionally had another choice — crossing the border to work in the U.S. Mexicans who make this choice can move from earning a dollar or two a day to 10 or 15 dollars an hour, though with higher living costs. It is hard to beat that boost simply by finishing high school or even college in Mexico.
Admittedly, this [informal, grey or black market] labor can be and often is absorbed into the more formal, more productive sectors of the economy, including exports. But the rate of absorption is quite slow, which in turn helps to set the slow growth rate of the economy. And in any case neither the high-productivity nor the low-productivity firms have that much room to grow within their respective categories, a major difference from many other emerging economies.
The odds are that Mexico will have to opt for the slow but steady long game, as Denmark once did.
David Siegel emails me:
The Civil marketplace is built on a protocol that in turn is built on the Ethereum blockchain.
This ecosystem is built around a token-curated registry, using what we call a “skin-in-the-game coin,” the CVL. This is an application of mechanism design to blockchain-based tokens that can be acquired, exchanged, and go up in value, creating a new micro-economy for – in this case – truthy journalism. The basic unit of Civil is a newsroom. A newsroom is a person or group who can publish anything they like. They can charge readers using CVL tokens or credit cards or anything else. What makes Civil interesting is that anyone can challenge a story’s veracity.
To challenge a story, you send some CVL coins to a smart contract. The community then votes on the veracity of the story, or even the newsroom itself. Anyone who votes must stake coins. If the story is voted true, those who voted true take the pot – they win all the staked tokens. If the community finds it’s false, then those who voted for false share the purse. This skin-in-the-game mechanism is the next evolution of communities like Steem and is game-theoretically far more advanced than Reddit or Quora. It promises to eliminate fake ratings, reviews, and content farms pumping out propaganda. By creating token-based games that reward virtuous behavior – the first one of which was Bitcoin – today’s blockchain entrepreneurs promise to bring us a new era of less biased news, better blogging, more accurate ratings, and potentially better science.
Since its launch in 2009, Zaad, which means “to grow” in Somali, has swelled to 850,000 users—roughly one-quarter of the nation’s population. Locals use the platform on battered old cellphones and, less frequently, on smartphones and a designated app.
Without mobile money, cash has a hard time flowing through the country. No commercial banks really operate here, and hauling physical cash over rough roads is time-consuming. Companies use Zaad for their monthly payrolls, instead of handing wads of cash to their employees.
Today, each user on average makes 35 Zaad transactions a month, and Somalilanders say they try to use Zaad for most transactions. A rudimentary texting system makes it easy even for the many Somalilanders who are illiterate.
It seems to be a kind of free banking:
Apart from phone-to-phone transactions, users can top up their mobile wallets by handing cash—shillings [the Somaliland currency] or dollars—over to an official agent, who is often a single person in a shack on the side of the road.
“This service has been a driving force for the smooth operation of our economy,” said Abdikarim Dil, Telesom’s chief executive.
Since mobile-money services aren’t regulated by the central bank, they aren’t subject to the restrictions that traditional banks face, including requirements meant to block terror financing.