Results for “small group theory” 49 found
Does Demand for New Currencies Increase in a Recession?
Every time there is a recession we hear more about barter and new currencies, especially so-called “local” currencies. An inceased interest in barter and new currencies suggests a theory of recessions, the lack of liquidity theory:
Bloomberg: “In times of crisis like the one we are jumping into, the main issue is lack of liquidity, even when there is work to be done, people to do it, and demand for it,” says Paolo Dini, an associate professorial research fellow at the London School of Economics and one of the world’s foremost experts on complementary currencies. “It’s often a cash flow problem. Therefore, any device or instrument that saves liquidity helps.”
I wrote about this several years ago but on closer inspection it’s not obvious that interest in barter or new currencies increases much in a recession or that these new currencies are helpful. Here’s my previous post (with a new graph) and no indent.
Nick Rowe explains that the essence of New Keynesian/Monetarist theories of recessions is the excess demand for money (Paul Krugman’s classic babysitting coop story has the same lesson). Here’s Rowe:
The unemployed hairdresser wants her nails done. The unemployed manicurist wants a massage. The unemployed masseuse wants a haircut. If a 3-way barter deal were easy to arrange, they would do it, and would not be unemployed. There is a mutually advantageous exchange that is not happening. Keynesian unemployment assumes a short-run equilibrium with haircuts, massages, and manicures lying on the sidewalk going to waste. Why don’t they pick them up? It’s not that the unemployed don’t know where to buy what they want to buy.
If barter were easy, this couldn’t happen. All three would agree to the mutually-improving 3-way barter deal. Even sticky prices couldn’t stop this happening. If all three women have set their prices 10% too high, their relative prices are still exactly right for the barter deal. Each sells her overpriced services in exchange for the other’s overpriced services….
The unemployed hairdresser is more than willing to give up her labour in exchange for a manicure, at the set prices, but is not willing to give up her money in exchange for a manicure. Same for the other two unemployed women. That’s why they are unemployed. They won’t spend their money.
Keynesian unemployment makes sense in a monetary exchange economy…it makes no sense whatsoever in a barter economy, or where money is inessential.
Rowe’s explanation put me in mind of a test. Barter is a solution to Keynesian unemployment but not to “RBC unemployment” which, since it is based on real factors, would also occur in a barter economy. So does barter increase during recessions?
There was a huge increase in barter and exchange associations during the Great Depression with hundreds of spontaneously formed groups across the country such as California’s Unemployed Exchange Association (U.X.A.). These barter groups covered perhaps as many as a million workers at their peak.
In addition, I include with barter the growth of alternative currencies or local currencies such as Ithaca Hours or LETS systems. The monetization of non-traditional assets can alleviate demand shocks which is one reason why it’s good to have flexibility in the definition of and free entry into the field of money (a theme taken up by Cowen and Kroszner in Explorations in New Monetary Economics and also in the free banking literature.)
During the Great Depression there was a marked increase in alternative currencies or scrip, now called depression scrip. In fact, Irving Fisher wrote a now forgotten book called Stamp Scrip. Consider this passage and note how similar it is to Nick’s explanation:
If proof were needed that overproduction is not the cause of the depression, barter is the proof – or some of the proof. It shows goods not over-produced but dead-locked for want of a circulating transfer-belt called “money.”
Many a dealer sits down in puzzled exasperation, as he sees about him a market wanting his goods, and well stocked with other goods which he wants and with able-bodied and willing workers, but without work and therefore without buying power. Says A, “I could use some of B’s goods; but I have no cash to pay for them until someone with cash walks in here!” Says B, “I could buy some of C’s goods, but I’ve no cash to do it with till someone with cash walks in here.” Says the job hunter, “I’d gladly take my wages in trade if I could work them out with A and B and C who among them sell the entire range of what my family must eat and wear and burn for fuel – but neither A nor B nor C has need of me – much less could the three of them divide me up.” Then D comes on the scene, and says, “I could use that man! – if he’d really take his pay in trade; but he says he can’t play a trombone and that’s all I’ve got for him.”
“Very well,” cries Chic or Marie, “A’s boy is looking for a trombone and that solves the whole problem, and solves it without the use of a dollar.
In the real life of the twentieth century, the handicaps to barter on a large scale are practically insurmountable….
Therefore Chic or somebody organizes an Exchange Association… in the real life of this depression, and culminating apparently in 1933, precisely what I have just described has been taking place.
What about today (2011)? Unfortunately, the IRS doesn’t keep statistics on barter (although barterers are supposed to report the value of barter exchanges). Google Trends shows an increase in searches for barter in 2008-2009 but the increase is small. Some reports say that barter is up but these are isolated (see also the 2020 Bloomberg piece), I don’t see the systematic increase we saw during the Great Depression. I find this somewhat surprising as the internet and barter algorithms have made barter easier.
In terms of alternative currencies, the best data that I can find shows that the growth of alternative currencies in the United States is small, sporadic and not obviously increasing with the recession. (Alternative currencies are better known in Germany and Argentina perhaps because of the lingering influence of Heinrich Rittershausen and Silvio Gesell).
Below is a similar graph for 2017-2020. Again not much increase in recent times.
In sum, the increase in barter and scrip during the Great Depression is supportive of the excess demand for cash explanation of that recession, even if these movements didn’t grow large enough, fast enough to solve the Great Depression. Today there seems to be less interest in barter and alternative currencies than expected, or at least than I expected, given an AD shock and the size of this recession. I don’t draw strong conclusions from this but look forward to further research on unemployment, recessions and barter.
Blood Money
NYTimes: Around the world, scientists are racing to develop and mass produce reliable antibody tests that public health experts say are a crucial element in ending the coronavirus lockdowns that are causing economic devastation. But that effort is being hamstrung, scientists say, by a shortage of the blood samples containing antibodies to Covid-19, the disease caused by the virus, that are needed to validate the tests.
Recognizing a rare opportunity, some companies are seeking to cash in on the shortages, soliciting blood donations and selling samples at rich markups in a practice that has been condemned by medical professionals as, at the very least, unethical.
“I’ve never seen these prices before,” said Dr. Joe Fitchett, the medical director of Mologic, one of the British test manufacturers that was offered the blood samples. “It’s money being made from people’s suffering.”
I am reminded of Walter Williams who asks his students whether it is wrong to profit from the misfortune of others:
But I caution them with some examples. An orthopedist profits from your misfortune of having broken your leg skiing. When there’s news of a pending ice storm, I doubt whether it saddens the hearts of those in the collision repair business. I also tell my students that I profit from their misfortune — their ignorance of economic theory.
A price is a signal wrapped up in an incentive so if you want a strong signal and a strong incentive you need to let prices rise. The prices in this case don’t even seem that high:
From March 31 to April 22, prices asked by Cantor BioConnect for its cheapest samples — always sold by the milliliter, the equivalent of less than a quarter of a teaspoon — rose more than 40 percent, to $500 from $350.
Bear in mind the costs of collecting the sample, including nurse time and PPE. Some samples which are especially rich in antibodies, do sell for prices that are well above cost which is not surprising as those samples are in high demand as they may offer a cure.
Do the firms willing and able to pay the highest prices necessarily have the best science? No, not necessarily, but on balance the decentralized allocation process offered by markets and civil society will likely be far more effective than centralized, political allocation. We also know from field experiments around the world that higher prices for blood increase supply, a key consideration.
As Hayek said the moral rules of the tribe which appear natural to us–like don’t profit from misery–cannot maintain a civilization so we struggle between what we think is right and what actually works to prevent misery.
There can be no doubt that our innate moral emotions and instincts were acquired in the hundreds of thousand years—probably half a million years—in which Homo sapiens lived in small hunting and gathering groups and developed a physiological constitution which governed his innate instincts. These instincts are still very strong in us. Yet civilization developed by our gradually learning cultural rules which were transmitted by teaching and which served largely to restrain and suppress some of those natural instincts.
More on economists and epidemiologists
From my email box, here are perspectives from people in the world of epidemiology, the first being from Jacob Oppenheim:
I’d note that epidemiology is the field that has most embraced novel and principles-driven approaches to causal inference (eg those of Judea Pearl etc). Pearl’s cluster is at UCLA; there’s one at Berkeley, and another at Harvard.
The one at Harvard simultaneously developed causal methodologies in the ’70s (eg around Rubin), then a parallel approach to Pearl in the ’80s (James Robins and others), leading to a large collection of important epi people at HSPH (Miguel Hernan, etc). Many of these methods are barely touched in economics, which is unfortunate given their power in causal inference in medicine, disease, and environmental health.
These methods and scientists are very influential not only in public health / traditional epi, but throughout the biopharma and machine learning worlds. Certainly, in my day job running data science + ml in biotech, many of us would consider well trained epidemiologists from these top schools among the best in the world for quantitative modeling, especially where causality is involved.
From Julien SL:
I’m not an epidemiologist per se, but I think my background gives me some inputs into that discussion. I have a master in Mechatronics/Robotics Engineering, a master in Management Science, and an MBA. However, in the last ten years, epidemiology (and epidemiology forecasting) has figured heavily in my work as a consultant for the pharma industry.
[some data on most of epidemiology not being about pandemic forecasting]…
The result of the neglect of pandemics epidemiology is that there is precious little expertise in pandemics forecasting and prevention. The FIR model (and it’s variants) that we see a lot these days is a good teaching aid. Still, it’s not practically useful: you can’t fit exponentials with unstable or noisy parameters and expect good predictions. The only way to use R0 is qualitatively. When I saw the first R0 and mortality estimates back in January, I thought “this is going to be bad,” then sold my liquid assets, bought gold, and naked puts on indices. I confess that I didn’t expect it to be quite as bad as what actually happened, or I would have bought more put options.
…here are a few tentative answers about your “rude questions:”
a. As a class of scientists, how much are epidemiologists paid? Is good or bad news better for their salaries?
Glassdoor data show that epidemiologists in the US are paid $63,911 on average. CDC and FDA both pay better ($98k and $120k), as well as pharma (Merck: $94k-$115k). As explained above, most are working on cancer, diabetes, etc. So I’m not sure what “bad news” would be for them.
b. How smart are they? What are their average GRE scores?
I’m not sure where you could get data to answer that question. I know that in pharma, many – maybe most – people who work on epidemiology forecasting don’t have an epidemiology degree. They can have any type of STEM degree, including engineering, economics, etc. So my base rate answer would be average of all STEM GRE scores. [TC: Here are U. Maryland stats for public health students.]
c. Are they hired into thick, liquid academic and institutional markets? And how meritocratic are those markets?
Compared to who? Epidemiology is a smaller community than economics, so you should find less liquidity. Pharma companies are heavily clustered into few geographies (New Jersey, Basel in Switzerland, Cambridge in the UK, etc.) so private-sector jobs aren’t an option for many epidemiologists.
d. What is their overall track record on predictions, whether before or during this crisis?
CDC has been running flu forecasting challenges every year for years. From what I’ve seen, the models perform reasonably well. It should be noted that those models would seem very familiar to an econometric forecaster: the same time series tools are used in both disciplines. [TC: to be clear, I meant prediction of new pandemics and how they unfold]
e. On average, what is the political orientation of epidemiologists? And compared to other academics? Which social welfare function do they use when they make non-trivial recommendations?
Hard to say. Academics lean left, but medical doctors and other healthcare professionals often lean right. There is a conservative bias to medicine, maybe due to the “primo, non nocere” imperative. We see that bias at play in the hydroxychloroquine debate. Most health authorities are reluctant to push – or even allow – a treatment option before they see overwhelming positive proof, even when the emergency should encourage faster decision making.
…g. How well do they understand how to model uncertainty of forecasts, relative to say what a top econometrician would know?
As I mentioned above, forecasting is far from the main focus of epidemiology. However, epidemiologists as a whole don’t seem to be bad statisticians. Judea Pearl has been saying for years that epidemiologists are ahead of econometricians, at least when it comes to applying his own Structural Causal Model framework… (Oldish) link: http://causality.cs.ucla.edu/blog/index.php/2014/10/27/are-economists-smarter-than-epidemiologists-comments-on-imbenss-recent-paper/
I’ve seen a similar pattern with the adoption of agent-based models (common in epidemiology, marginal in economics). Maybe epidemiologists are faster to take up new tools than economists (which maybe also give a hint about point e?)
h. Are there “zombie epidemiologists” in the manner that Paul Krugman charges there are “zombie economists”? If so, what do you have to do to earn that designation? And are the zombies sometimes right, or right on some issues? How meta-rational are those who allege zombie-ism?
I don’t think so. Epidemiology seems less political than economy. There are no equivalents to Smith, Karl Marx, Hayek, etc.
i. How many of them have studied Philip Tetlock’s work on forecasting?
Probably not many, given that their focus isn’t forecasting. Conversely, I don’t think that Tetlock has paid much attention to epidemiology. On the Good Judgement website, healthcare questions of any type are very rare.
And here is Ruben Conner:
Weighing in on your recent questions about epidemiologists. I did my undergraduate in Economics and then went on for my Masters in Public Health (both at University of Washington). I worked as an epidemiologist for Doctors Without Borders and now work as a consultant at the World Bank (a place mostly run by economists). I’ve had a chance to move between the worlds and I see a few key differences between economists and epidemiologists:
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Trust in data: Like the previous poster said, epidemiologists recognize that “data is limited and often inaccurate.” This is really drilled into the epidemiologist training – initial data collection can have various problems and surveys are not always representative of the whole population. Epidemiologists worry about genuine errors in the underlying data. Economists seem to think more about model bias.
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Focus on implementation: Epidemiologists expect to be part of the response and to deal with organizing data as it comes in. This isn’t a glamorous process. In addition, the government response can be well executed or poorly run and epidemiologists like to be involved in these details of planning. The knowledge here is practical and hands-on. (Epidemiologists probably could do with more training on organizational management, they’re not always great at this.)
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Belief in models: Epidemiologists tend to be skeptical of fancy models. This could be because they have less advanced quantitative training. But it could also be because they don’t have total faith in the underlying data (as noted above) and therefore see fancy specifications as more likely to obscure the truth than reveal it. Economists often seem to want to fit the data to a particular theory – my impression is that they like thinking in the abstract and applying known theories to their observations.
As with most fields, I think both sides have something to learn from each other! There will be a need to work together as we weigh the economic impacts of suppression strategies. This is particularly crucial in low-income places like India, where the disease suppression strategies will be tremendously costly for people’s daily existence and ability to earn a living.
Here is a 2014 blog post on earlier spats between economists and epidemiologists. Here is more from Joseph on that topic.
And here is from an email from epidemiologist Dylan Green:
So with that…on to the modelers! I’ll merely point out a few important details on modeling which I haven’t seen in response to you yet. First, the urgency with which policy makers are asking for information is tremendous. I’ve been asked to generate modeling results in a matter of weeks (in a disease which I/we know very little about) which I previously would have done over the course of several months, with structured input and validation from collaborators on a disease I have studied for a decade. This ultimately leads to simpler rather than more complicated efforts, as well as difficult decisions in assumptions and parameterization. We do not have the luxury of waiting for better information or improvements in design, even if it takes a matter of days.
Another complicated detail is the publicity of COVID-19 projections. In other arenas (HIV, TB, malaria) model results are generated all the time, from hundreds of research groups, and probably <1% of the population will ever see these figures. Modeling and governance of models of these diseases is advanced. There are well organized consortia who regularly meet to present and compare findings, critically appraise methods, elegantly present uncertainty, and have deep insights into policy implications. In HIV for example, models are routinely parameterized to predict policy impact, and are ex-post validated against empirical findings to determine the best performing models. None of this is currently in scope for COVID-19 (unfortunately), as policy makers often want a single number, not a range, and they want it immediately.
I hope for all of our sakes we will see the modeling coordination efforts in COVID-19 improve. And I ask my fellow epidemiologists to stay humble during this pandemic. For those with little specialty in communicable disease, it is okay to say “this isn’t my area of expertise and I don’t have the answers”. I think there has been too much hubris in the “I-told-ya-so” from people who “said this would happen”, or in knowing the obvious optimal policy. This disease continues to surprise us, and we are learning every day. We must be careful in how we communicate our certainty to policy makers and the public, lest we lose their trust when we are inevitably wrong. I suspect this is something that economists can likely teach us from experience.
One British epidemiologist wrote me and told me they are basically all socialists in the literal sense of the term. not just leaning to the left.
Another person in the area wrote me this:
Another issue that isn’t spoken about a lot is most Epidemiologists are funded by soft money. It makes them terrifyingly hard working but it also makes them worried about making enemies. Every critic now will be reviewed by someone in IHME at some point in an NIH study section, whereas IHME, funded by the Gates Foundation, has a lot of resilience. It makes for a very muted culture of criticism.Ironically, outsiders (like economist Noah Haber) trying to push up the methods are more likely to be attacked because they are not a part of the constant funding cycle.I wonder if economists have ever looked at the potential perverse incentives of being fully grant funded on academic criticism?
Here is an earlier email response I reproduced, here is my original blog post, here is my update from yesterday.
My Conversation with Hal Varian
Hal of course was in top form, here is the audio and transcript. Excerpt:
COWEN: Why doesn’t business use more prediction markets? They would seem to make sense, right? Bet on ideas. Aggregate information. We’ve all read Hayek.
VARIAN: Right. And we had a prediction market. I’ll tell you the problem with it. The problem is, the things that we really wanted to get a probability assessment on were things that were so sensitive that we thought we would violate the SEC rules on insider knowledge because, if a small group of people knows about some acquisition or something like that, there is a secret among this small group.
You might like to have a probability assessment of whether that would go through. But then, anybody who looks at the auction is now an insider. So there’s a problem in you have to find things that (a) are of interest to the company but (b) do not reveal financially critical information. That’s not so easy to do.
COWEN: But there are plenty of times when insider trading is either illegal or not enforced. Plenty of countries where it’s been legal, and there we don’t see many prediction markets in companies, if any. So it seems like it ought to have to be some more general explanation, or no?
VARIAN: Well, I’m just referring to our particular case. There was another example at the same time: Ford was running a market, and Ford would have futures markets on the price of gasoline, which was very relevant to them. It was an external price and so on. And it extended beyond the usual futures market.
That’s the other thing. You’re not going to get anywhere if you’re just duplicating a market that already exists. You have to add something to it to make it attractive to insiders.
So we ran a number of cases internally. We found some interesting behavior. There’s an article by Bo Cowgill on our experience with this auction. But ultimately, we ran into this problem that I described. The most valuable predictions would be the most sensitive predictions, and you didn’t want to do that in public.
And:
COWEN: But then you must think we’re not doing enough theory today. Or do you think it’s simply exhausted for a while?
VARIAN: Well, one area of theory that I’ve found very exciting is algorithmic mechanism design. With algorithmic mechanism design, it’s a combination of computer science and economics.
The idea is, you take the economic model, and you bring in computational costs, or show me an algorithm that actually solves that maximization problem. Then on the other side, the computer side, you build incentives into the algorithms. So if multiple people are using, let’s say, some communications protocol, you want them all to have the right incentives to have the efficient use of that protocol.
So that’s a case where it really has very strong real-world applications to doing this — everything from telecommunications to AdWords auctions.
And:
VARIAN: Yeah. I would like to separate the blockchain from just cryptographic protocols in general. There’s a huge demand for various kinds of cryptography.
Blockchain seems to be, by its nature, relatively inefficient. As an economist, I don’t like this proof of work that this is. I don’t like the fact that there’s one version of the blockchain that has to keep being updated. I don’t like the fact that it’s so slow. There are lots of things that you could fix, and I expect to see them fixed in the future, but I would say, crypto in general — big deal. Blockchain — not so much.
And finally:
COWEN: Now, users seem to like them both, but if I just look at the critics, why does it seem to me that Facebook is more hated than Google?
VARIAN: Well, you know, I actually don’t use Facebook. I don’t have any moral objection to it. I just don’t have the time to do it. [laughs] There are other things of this sort that can end up soaking up a substantial amount of time.
I think that one of the reasons — and this is, of course, quite speculative — I think that one of the reasons people are most worried about Facebook is they don’t really understand the limits of what can be done at Facebook. Whereas at Google, I think we’re pretty clear that we’re showing you ads. We’re showing you ads that are targeted to one thing or another, but that’s how the information’s used.
So, you’ve got this specific application in our case. In Facebook’s case, it’s more amorphous, I think.
There is much, much more at the link.
*The Marginal Revolutionaries: How Austrian Economists Fought the War of Ideas*
That is the new and very interesting forthcoming book by Janek Wasserman, focusing on the history of the Austrian school of economics and due out in September. A few comments:
1. It is the best overall history of the Austrian school.
2. It is in some early places too wordy, though perhaps that is necessary for the uninitiated.
3. I don’t think actual “Austrian school members” will learn much economics from it, though it has plenty of useful historical detail, far more than any other comparable book. And much of it is interesting, not just: “Adolph Wagner and Albert Schaeffler taught in the Austrian capital in the 1860s and early 1870s, but quarrels with fellow incumbent Lorenz von Stein led to their departure.”
4. Even a full decade after its release in 1871, Menger’s Principles was not achieving much attention outside of Vienna.
5. The early Austrians favored progressive taxation and fairly standard Continental approaches to government spending.
6. The Austrian school of those earlier times was in danger of disappearing, as Boehm-Bawerk was working in government and the number of “Austrian students” was drying up, circa 1905.
7. The very first articles of Mises were empirical, and covered factory legislation, labor law, and welfare programs.
8. Wieser and some of the others lost status with the fall of the Dual Monarchy after WWI; Wieser for instance no longer had a House of Lords membership. Schumpeter and Mises responded to these changes by writing more for a broader public, often through newspapers (not blogs). Mises’s market-oriented views seemed to stem from this time.
9. Hayek in fact struggled in high school, though his grandfather had gone on Alpine hikes with Boehm-Bawerk.
10. The Lieder of the original Mises circle were patterned after the poems of Karl Kraus, and one of them mentioned spaghetti and risotto.
11. Much of this book is strong evidence for the “small group” theory of social change.
12. The patron institution for Hayek’s business cycle research of 1927 to 1931 was partly sponsored by the Rockefeller Foundation.
13. By the mid-1930s, Mises, Tinbergen, Koopmans, and Nurkse were all living in Geneva. There was a Vienna drinking song saying farewell to Mises.
14. I wonder how these guys would have looked as Emergent Ventures applicants. [“We’re going to run away from the Nazis and recreate anew our whole school of thought in America, with thick Austrian accents…and with a night school class at NYU to boot.”]
15. The Austrian school eventually was reborn in the United States, which accounts for many more chapters in this book, some of them concerned with the ties between the Austrian school and libertarianism. There are some outright errors of fact in this section of the book, sometimes involving matters I was involved with personally (and which are non-controversial, not a question of “taking sides”). I think also the latter parts of the book do not quite grasp the extensive influence of the Austrian school on America, extending up through the current day, and covering such diverse areas as regulatory policy and tech and crypto.
Nonetheless, recommended as an important contribution to the history of economic thought.
Bitcoin is Less Secure than Most People Think
I spent part of the holidays poring over Eric Budish’s important paper, The Economic Limits of Bitcoin and the BlockChain. Using a few equilibrium conditions and some simulations, Budish shows that Bitcoin is vulnerable to a double spending attack.
In a double spending attack, the attacker sells say bitcoin for dollars. The bitcoin transfer is registered on the blockchain and then, perhaps after some escrow period, the dollars are received by the attacker. As soon as the bitcoin transfer is registered in a block–call this block 1–the attacker starts to mine his own blocks which do not include the bitcoin transfer. Suppose there is no escrow period then the best case for the attacker is that they mine two blocks 1′ and 2′ before the honest nodes mine block 2. In this case, the attacker’s chain–0,1′,2′–is the longest chain and so miners will add to this chain and not the 0,1… chain which becomes orphaned. The attacker’s chain does not include the bitcoin transfer so the attacker still has the bitcoins and they have the dollars! Also, remember, even though it is called a double-spend attack it’s actually an n-spend attack so the gains from attack could be very large. But what happens if the honest nodes mine a new block before the attacker mines 2′? Then the honest chain is 0,1,2 but the attacker still has block 1′ mined and after some time they will have 2′, then they have another chance. If the attacker can mine 3′ before the honest nodes mine block 3 then the new longest chain becomes 0,1′,2′,3′ and the honest nodes start mining on this chain rather than on 0,1,2. It can take time for the attacker to produce the longest chain but if the attacker has more computational power than the honest nodes, even just a little more, then with probability 1 the attacker will end up producing the longest chain.
As an example, Budish shows that if the attacker has just 5% more computational power than the honest nodes then on average it takes 26.5 blocks (a little over 4 hours) for the attacker to have the longest chain. (Most of the time it takes far fewer blocks but occasionally it takes hundreds of blocks for the attacker to produce the longest chain.) The attack will always be successful eventually, the key question is what is the cost of the attack?
The net cost of a double-spend attack is low because attackers also earn block rewards. For example, in the case above it might take 26 blocks for the attacker to substitute its longer chain for the honest chain but when it does so it earns 26 block rewards. The rewards were enough to cover the costs of the honest miners and so they are more or less enough to cover the costs of the attacker. The key point is that attacking is the same thing as mining. Budish assumes that attackers add to the computation power of the network which pushes returns down (for both the attacker and interestingly the honest nodes) but if we assume that the attacker starts out as honest–a Manchurian Candidate attack–then there is essentially zero cost to attacking.
It’s often said that Bitcoin creates security with math. That’s only partially true. The security behind avoiding the double spend attack is not cryptographic but economic, it’s really just the cost of coordinating to achieve a majority of the computational power. Satoshi assumed ‘one-CPU, one-vote’ which made it plausible that it would be costly to coordinate millions of miners. In the centralized ASIC world, coordination is much less costly. Consider, for example, that the top 4 mining pools today account for nearly 50% of the total computational power of the network. An attack would simply mean that these miners agree to mine slightly different blocks than they otherwise would.
Aside from the cost of coordination, a small group of large miners might not want to run a double spending attack because if Bitcoin is destroyed it will reduce the value of their capital investments in mining equipment (Budish analyzes several scenarios in this context). Call that the Too Big to Cheat argument. Sound familiar? The Too Big to Cheat argument, however, is a poor foundation for Bitcoin as a store of value because the more common it is to hold billions in Bitcoin the greater the value of an attack. Moreover, we are in especially dangerous territory today because bitcoin’s recent fall in price means that there is currently an overhang of computing power which has made some mining unprofitable, so miners may feel this a good time to get out.
The Too Big to Cheat argument suggests that coins are vulnerable to centralized computation power easily repurposed. The tricky part is that the efficiencies created by specialization–as for example in application-specific integrated circuits–tend to lead to centralization but by definition make repurposing more difficult. CPUs, in contrast, tend to lead to decentralization but are easily repurposed. It’s hard to know where safety lies. But what we can say is that any alt-coin that uses a proof of work algorithm that can be solved using ASICs is especially vulnerable because miners could run a double spend attack on that coin and then shift over to mining bitcoin if the value of that coin is destroyed.
What can help? Ironically, traditional law and governance might help. A double spend attack would be clear in the data and at least in general terms so would the attackers. An attack involving dollars and transfers from banks would be potentially prosecutable, greatly raising the cost of an attack. Governance might help as well. Would a majority of miners (not including the attacker) be willing to fork Bitcoin to avoid the attack, much as was done with The DAO? Even the possibility of a hardfork would reduce the expected value of an attack. More generally, all of these mechanisms are a way of enforcing some stake loss or capital loss on dishonest miners. In theory, therefore, proof of stake should be less vulnerable to 51% attacks but proof of stake is much more complicated to make incentive-compatible than proof of work.
All of this is a far cry from money without the state. Trust doesn’t have the solidity of math but we are learning that it is more robust.
Hat tip to Joshua Gans and especially to Eric Budish for extensive conversation on these issues.
Addendum: See here for more on the Ethereum Classic double spend attack.
Income risk-sharing in baseball
Pando Pooling is a startup headquartered in Palo Alto, Calif. The company’s founders, Charlie Olson and Eric Lax, met in 2015 at Stanford’s Graduate School of Business where they dreamed up an endeavor that would support people in high-volatility careers—entrepreneurs, primarily. (Pando is Latin for “I spread out,” and also refers to a colony of aspen trees, whose roots intertwine to make a massive underground network.) What if, they wondered, a large enough group of entrepreneurs pooled shares of their earnings, ensuring that each entrepreneur stood less chance of going bust? In theory this would allow entrepreneurs to take more risks in pursuing their ideas.
Olson and Lax didn’t start with entrepreneurs, though. They took their idea to a different field—literally. Just as MLB teams pool a third of their revenue to support smaller-market teams, Olson and Lax saw an opportunity to give young baseball players more security. As with entrepreneurs, only a small set of players go on to earn fortunes; many talented, driven players leave with little. (Less than 25% of first-round draft picks play more than three years in the majors.) Unlike tech founders, though, players are paid at regular intervals.
Here’s Pando’s pitch: A young player contributes a fixed share of his salary to his pool after he receives at least $1.6 million in MLB earnings. There is more than one pool, but every member in each pool must agree on every other poolmate, and Pando takes 10% of each pool. Pando recruits players through agents, financial advisers and players who have already signed with the company; Olson says he has 150 members so far. Once a player is on board, Pando then tries to match him with a handful of similar players to form a pool.
Here is the full Sports Illustrated article. It is a longstanding puzzle why such arrangements never have taken off. Is it some mix of adverse selection, excess optimism, too high resulting marginal tax rates, and bad PR because it is vaguely reminiscent of slavery? Still, just think — if this could work the incentive to invest in the talent of other people would be so much higher.
Via Conor Durkin.
Shopping While Black: Past, Present and Future?
The original Sears mail-order catalogue changed how African Americans in the South shopped:
…the catalogue format allowed for anonymity, ensuring that black and white customers would be treated the same way.
“This gives African Americans in the Southeast some degree of autonomy, some degree of secrecy,” unofficial Sears historian Jerry Hancock told the Stuff You Missed in History Class podcast in December 2016. “Now they can buy the same thing that anybody else can buy. And all they have to do is order it from this catalogue. They don’t have to deal with racist merchants in town and those types of things.”
More recently, Uber has alleviated many of the traditional difficulties that blacks have had hailing taxis.
In a heartfelt essay Ashlee Clark Thompson explains how the “grab and go” technologies now being tested at Amazon Go made her confront lessons learned from decades of shopping while black:
The idea of walking into a store, taking an item or several off the shelves and strolling right back out again boggled my mind. It ran counter to everything I had learned about being black and shopping.
…I grabbed one of the orange Amazon Go bags and began to make my way around the perimeter of the store. I was studying the various bottled waters and debating whether to get fizzy or still, or a bottle of kombucha, when I realized what I was really doing: I was stalling. The fear I had carried with me for decades reared its head as I stood in front of the refrigerated display. I was afraid to make a choice, remove it from a shelf and put it in my bag. I was afraid someone would pop out from behind a display of Amazon-branded merch and scream, “Get your hands off that!” And I was mad that this fear couldn’t even let me fully enjoy an experience that’s designed for everyone to grab and go, no questions asked.
Eff this, I thought. I’m getting some Vitamin Water.
Once the plastic bottle hit the bottom of my reusable bag, I glanced around to see if anyone noticed. The Amazon employees shuffled around the small store and restocked shelves. Tourists chatted in small groups as they pointed and looked for the sensors that were keeping track of our every move. One guy with his phone on a selfie stick recorded himself as he selected snacks. And then there were the folks for whom the novelty had worn off and just wanted a vegetarian banh mi sandwich.
No one cared what I was doing. Is this what it feels like to shop when you’re not black?
…Amazon Go isn’t going to fix implicit bias or remove the years of conditioning under which I’ve operated. But in the Amazon Go store, everyone is just a shopper, an opportunity for the retail giant to test technology, learn about our habits and make some money. Amazon sees green, and in its own capitalist way, this cashierless concept eased my burden a little bit.
The similarities in these cases are interesting but so are the differences. In the Sears case most of the effect of diminished discrimination was driven by greater competition in one-shop towns. In the one-shop town the owners sometimes took a share of their monopoly profits in invidious racism–this appears to explain why shop owners would prevent blacks from buying more expensive products (or perhaps the one-stop shop had to cater to racist customers who demanded invidious discrimination.)
In the Uber case my bet is that a large share of the reduction in discrimination was due to the fact that Uber drivers don’t carry cash and so are less worried about robbery and the app increases safety because it records in detail rider, driver and trip data. In other words, the Uber system reduced the value of statistical discrimination. It’s difficult to know for sure, however, because there was probably also some decline in invidious discrimination brought about by Uber hiding some rider information from drivers until trips are accepted.
The last case, the Amazon Go case, is in part a decline in the value of statistical discrimination since shoplifting is no longer a problem (in theory, assuming the technology works) but in this case the decline in statistical discrimination is driven by much finer discrimination. The moment a shopper enters the Amazon Go store, Amazon knows their name, address, entire shopping history, credit history and potentially much more. Moreover, a shopper’s every movement within the store is tracked to a level of detail that no store detective could ever hope to match. To the customer, especially the black customer, it may feel like they are no longer being watched but in fact they are watched more than ever before–the costs of technological monitoring, however, are mostly fixed which means that everyone is monitored equally. No need for statistical discrimination in the panopticon.
Addendum: A good dissertation might be to incorporates the cost of information, the value of statistical discrimination and the demand for invidious discrimination in a general theory that explains the various cases mentioned here and the effects of information bans such as ban the box.
William Nordhaus and why he won the Nobel Prize in economics
These are excellent Nobel Prize selections, Romer for economic growth and Nordhaus for environmental economics. The two picks are brought together by the emphasis on wealth, the true nature of wealth, and how nations and societies fare at the macro level. These are two highly relevant picks. Think of Romer as having outlined the logic behind how ideas leverage productivity into ongoing spurts of growth, as for instance we have seen in Silicon Valley. Think of Nordhaus as explaining how economic growth interacts with the value of the environment. Here is their language:
- 2018 Sveriges Riksbank Prize in Economic Sciences is awarded jointly to William D Nordhaus “for integrating climate change into long-run macroeconomic analysis” and Paul M Romer “for integrating technological innovations into long-run macroeconomic analysis”.
Both are Americans, and both have highly innovative but also “within the mainstream” approaches. So this is a macro prize, but not for cycles, rather for growth and long-term economic prospects. Here is the Prize committee citation, always well done.
Both candidates were considered heavy favorites to win the Prize, sooner or later, and these selections cannot come as a surprise. Perhaps it is slightly surprising that they won the Prize together, though the basic logic of such a combination makes good sense. Here are previous MR mentions of Nordhaus, you can see we have been mentioning him for years in connection with the Prize.
Here is the home page of Nordhaus. Here is Wikipedia. Here is scholar.google.com. Here is Joshua Gans on Nordhaus.
Nordhaus is professor at Yale, and most of all he is known for his work on climate change models, and his connection to various concepts of “green accounting.” To the best of my knowledge, Nordhaus started working on green accounting in 1972, when he published with James Tobin (also a Laureate) “Is Growth Obsolete?“, which raised the key question of sustainability. Green accounting attempts to outline how environmental degradation can be measured against economic growth. This endeavor is not so easy, however, as environmental damage can be hard to measure and furthermore gdp is a “flow” and the environment is (often, not always) best thought of as a “stock.”
Nordhaus developed (with co-authors) the Dynamic Integrated Climate-Economy Model, a pioneering effort to develop a general approach to estimating the costs of climate change. Subsequent efforts, such as the London IPCC group, have built directly on Nordhaus’s work in this area. The EPA still uses a variant of this model. The model was based on earlier work by Nordhaus himself in the 1970s, and he refined it over time in a series of books and articles, culminating in several books in the 1990s. Here is his well-cited piece, with Mendelsohn and Shaw, on how climate change will affect global agriculture.
Nordhaus also was an early advocate of a carbon tax and furthermore note that his brother Bob wrote part of the Clean Air Act, the part that gave the government the right to regulate hitherto-unmentioned pollutants in the future. The Obama administration, in its later attempts to regulate climate, cited this provision.
I would say that much of Nordhaus’s work has its impact through being “done,” rather than through being “read.” Few economists have read through this model, which has computer programs and spreadsheets at its core. But virtually all economists read about the results of such models and have a general sense of how they work. The most common criticism of such models, by the way, is simply that their results are highly sensitive to the choice of discount rate.
In recent years, Nordhaus has shifted his emphasis to the risks from climate change, for instance in his book The Climate Casino: Risk, Uncertainty, and Economics for a Growing World. Marty Weitzman offers a good review, as does Krugman.
Assorted pieces of information on Nordhaus:
Nordhaus was briefly Provost at Yale. He also ended up being co-author on Paul Samuelson’s famous textbook in economics.
He co-authored a recent paper arguing we are not near the economic singularity; in this area his work intersects with Romer’s quite closely.
Here is a good NYT profile of Bill Nordhaus and his brother Bob, an environmental lawyer:
Bill Nordhaus, 72, a Yale economist who is seen as a leading contender for a Nobel Prize, came up with the idea of a carbon tax and effectively invented the economics of climate change. Bob, 77, a prominent Washington energy lawyer, wrote an obscure provision in the Clean Air Act of 1970 that is now the legal basis for a landmark climate change regulation, to be unveiled by the White House next month, that could close hundreds of coal-fired power plants and define President Obama’s environmental legacy.
Bob, Bill’s brother, once said: ““Growing up in New Mexico,” he said, “you’re aware of the very fragile ecosystem.””
Perhaps my personal favorite Nordhaus paper is on the returns to innovation. Don Boudreaux summarized it well:
In a recent NBER working paper – “Schumpeterian Profits in the American Economy: Theory and Measurement” – Yale economist William Nordhaus estimates that innovators capture a mere 2.2% of the total “surplus” from innovation. (The total surplus of innovation is, roughly speaking, the total value to society of innovation above the cost of producing innovations.) Nordhaus’s data are from the post-WWII period.
The smallness of this figure is astounding. If it is anywhere close to being an accurate estimate, the implication is that “society” pays a paltry $2.20 for every $100 worth of welfare it enjoys from innovating activities.
There again you will see a complete intersection with the ideas of Romer. Another splendid and still-underrated paper by Nordhaus is on the economics of light. Nordhaus argues that gdp figures understate the true extent of growth, and shows that the relative price of bringing light to humans has fallen more rapidly than gdp growth figures alone might indicate. Check out this diagram. Here is a BBC summary of what Nordhaus did, in other words rates of price inflation have been lower than we thought and thus rates of real gdp growth higher.
Again, you will see Nordhaus and Romer intersecting on this key idea of economic growth.
Last but not least, Nordhaus was a pioneer on the theory of the political business cycle, namely the idea that politicians deliberately manipulate the economy, using monetary and fiscal policy, so as to boost their chances of reelection. Dare I suggest that this idea might be making a comeback?
Addendum: From Margaret Collins by email: “I’d like to call your attention to Professor Nordhaus’ longstanding association with the International Institute for Applied Systems Analysis (IIASA), the international science and policy research institution located just outside Vienna. He worked at IIASA shortly after the institute’s creation in 1972, and his work there is closely bound to the issues the Nobel Committee cites in the award — he was employed for a year in 1974-75, doing pioneering work on climate as part of IIASA’s Energy Program, and producing a working paper entitled “Can We Control Carbon Dioxide?”. That was perhaps the first economics treatment of of climate change — and Nordhaus dates his work on climate as having begun there. He has visited IIASA numerous times in the intervening years, and remains a close collaborator, particularly with Nebojsa Nakicenovic, the Institute’s Deputy Director.”
And, from the comments: “Nordhaus also helped pioneer the use of satellite imagery of night time lights as a tool for measuring economic growth, where we’ve played around with some of the publicly available tools to support various analysis.”
My Conversation with Chris Blattman
The very very highly rated but still underrated Chris Blattman was in top form, here is the transcript and audio. We had a chance to do this one when he was in town for a week. We talked about the problem with cash transfers, violence, child soldiers, charter cities, Rene Girard, how to do an Africa trip, Battlestar Galactica, why Ethiopia is growing rapidly, why civil war has become less common, why Colombia and the New World have been so violent, the mysteries of Botswana, and Chris’s favorite Australian TV show, among other topics, including of course the Chris Blattman production function. Here is one excerpt:
BLATTMAN: There’s this famous paper on Vietnam veterans in the US where they find that being conscripted into fighting in Vietnam had positive effects on the wages of blacks and negative effects on the wages of whites. The reason was, it was really down to, what was your alternative labor market and training experience in the absence of this war?
We found something similar in Uganda, something eerily familiar, which is that the women economically weren’t so worse off. I wouldn’t say they were better off, but they weren’t necessarily affected adversely in an economic sense — they were adversely affected in other ways 5 or 10 or 15 years down the road — while the men were.
It spoke to just how terrible women’s options were. Being conscripted and abducted to be a rebel wife, to some degree, wasn’t that different than what your marriage opportunities looked like if there wasn’t a war.
For men, it just meant that you were out of the civilian labor market, getting a bunch of skills that had turned out not to be very useful. It was bad for them. A different war, a different context, and a different labor market, and that can switch.
COWEN: How many northern Ugandan child soldiers have you interviewed?
BLATTMAN: A few hundred. At least a couple hundred, maybe more. It depends if you count someone who’s involved for a month versus two years. Certainly, the long, long-term soldiers who were there for many, many years are few, maybe only a couple dozen.
COWEN: Those contacts, those conversations, how have they changed your outlook on life emotionally, intellectually, otherwise?
And:
COWEN: True or false, most humans are bad at violence?
BLATTMAN: I think they learn quickly. Probably they’re bad at first.
COWEN: In the micro evidence on violence, and the more individual-level evidence, and then finally macro evidence — like will there be a civil war? — do you think there’s ultimately an overarching theory that ties these all together? Or are they just separate levels of investigation, where you have empirical results, and they stand somewhat separate, and they’ll always be distinct areas?
How optimistic are you about a grand unified theory of violence?
BLATTMAN: I think these individual, how I react in the moment, fight-or-flight-type mechanisms are quite distinct from the way that small groups or large groups or nations go to war. But once you get beyond that to the level of small groups and larger groups and nations, I see a lot of unity in the theory.
Do read or listen to the whole thing. By the way, he says the Canadian political system is overrated.
Nobel Prize awarded to Richard Thaler
This is a prize that is easy to understand. It is a prize for behavioral economics, for the ongoing importance of psychology in economic decision-making, and for “Nudge,” his famous and also bestselliing book co-authored with Cass Sunstein.
Here are previous MR posts on Thaler, we’ve already covered a great deal of his research. Here is Thaler on Twitter. Here is Thaler on scholar.google.com. Here is the Nobel press release, with a variety of excellent accompanying essays and materials. Here is Cass Sunstein’s overview of Thaler’s work.
Perhaps unknown to many, Thaler’s most heavily cited piece is on whether the stock market overreacts. He says yes this is possible for psychological reasons, and this article also uncovered some of the key evidence in favor of the now-vanquished “January effect” in stock returns, namely that for a while the market did very very well in the month of January. (Once discovered the effect went away.) Another excellent Thaler piece on finance is this one with Shleifer and Lee, on why closed end mutual funds sell at divergences from their true asset values. This too likely has something to do with market psychology and sentiment, as the same “asset package,” in two separate and non-arbitrageable markets, can sell for quite different prices, sometimes premia but usually discounts. This was one early and relative influential critique of the efficient markets hypothesis.
Another classic early Thaler piece is on a phenomenon known as “mental accounting,” for instance you might treat a dollar in your pocket as different from a dollar in your bank account. Or earned money may be treated different from money you just chanced upon, or won that morning in the stock market. This has significant implications for predicting consumer decisions concerning saving and spending; in particular, economists cannot simply measure income but must consider where the money came from and how it is perceived by consumers, namely how they are performing their mental accounting of the funds. Have you ever gone on a vacation with a notion that you would spend so much money, and then treated all expenditures within that range as essentially already decided? The initial piece on this topic was published in a marketing journal and it has funny terminology, a sign of how far from the mainstream this work once was. It is nonetheless a brilliant piece. Here is more Thaler on mental accounting.
Thaler, with Kahneman and Knetsch, was a major force behind discovering and measuring the so-called “endowment effect.” Once you have something, you value it much more! Maybe three or four times as much, possibly more than that. It makes policy evaluation difficult, because as economists we are not sure how much to privilege the status quo. Should we measure “willingness to pay” — what people are willing to pay for what they don’t already have? Or “willingness to be paid” — namely how eager people are to give up what they already possess? The latter magnitude will lead to much higher valuations for the assets in question. This by the way helps explain status quo bias in politics and other spheres of life. People value something much more highly once they view it as theirs.
This phenomenon also makes the Coase theorem tricky because the final allocation of resources may depend quite significantly on how the initial property rights are assigned, even when the initial wealth effect from such an allocation may appear to be quite small. See this Thaler piece with Knetsch. It’s not just that you assign property rights and let people trade, but rather how you assign the rights up front will create an endowment effect and thus significantly influence the final bargain that is struck.
With Jolls and Sunstein, here is Thaler on a behavioral approach to law and economics, a long survey but also constructive piece that became a major trend and has shaped law and economics for decades. He has done plenty and had a truly far-ranging impact, not just in one or two narrow fields.
Thaler’s “Nudge” idea, developed in conjunction with Cass Sunstein over the course of a major book and some articles, has led policymakers all over the world to focus on “choice architecture” in designing better systems, the UK even setting up a “Nudge Unit.” For instance, one way to encourage savings is to set up pension systems for employees so that the maximum contribution is the default, rather than an active choice people must make. This is sometimes referred to as a form of “soft” or “libertarian paternalism,” since choice is still present. Here is Thaler responding to some libertarian critiques of the nudge idea.
I first encountered Thaler’s work in graduate school, in the mid-1980s, in particular some of his pieces in the Journal of Economic Behavior and Organization; here is his early 1980 manifesto on how to think about consumer choice. I thought “this is great stuff,” and I gobbled it up, as it was pretty consistent with some of what I was imbibing from Thomas Schelling, in particular Thaler’s 1981 piece with Shefrin on the economics of self-control, a foundation for many later discussions of paternalism. I also thought “a shame this work isn’t going to become mainstream,” because at the time it wasn’t. It was seen as odd, under-demonstrated, and often it wasn’t in top journals. For some time Thaler taught at Cornell, a very good school but not a top top school of the kind where many Laureates might teach, such as Harvard or Chicago or MIT. Many people were surprised when finally he received an offer from the University of Chicago Business School, noting of course this was not the economics department. Obviously this Prize is a sign that Thaler truly has arrived at the very high levels of recognition, and I would note Thaler has been pegged as one of the favorites at least since 2010 or so. When Daniel Kahneman won some while ago and Thaler didn’t, many people thought “ah, that is it” because many of Thaler’s most famous pieces were written with Kahneman. Yet as time passed it became clear that Thaler’s work was holding up and spreading far and wide in influence, and he moved into a position of being a clear favorite to win.
Here is Thaler’s book on the making of behavioral economics. Excerpt:
…my thesis advisor, Sherwin Rosen, gave the following as an assessment of my career as a graduate student: “We did not expect much of him.”
Very lately Thaler on Twitter has been making some critical remarks about price gouging, suggesting we also must take into account what customers perceive as fair. Here is his earlier piece about fairness constraints on profit-seeking, still a classic.
Thaler has written many columns for The New York Times, here is one on boosting access to health care. Here are many more of them. Here is “Unless you are Spock, Irrelevant Things Matter for Investment Behavior.” Here is Thaler on making good citizenship fun. He also told us that trading up in the NFL draft isn’t worth it.
Thaler is underrated as a policy economist, here is an excellent NYT piece on the “public option” for health insurance, excerpt: “…instead of arguing about whether to have a public option, argue about the ground rules.”
His last pre-Nobel tweet was: “The @Expedia web site is using lots of #sludge. Advertised rates include cashing in of “points”, cancellation policies not salient if bad…”
A well-deserved prize and one that is relatively easy to explain, and most of Thaler’s works are easy to read even if you are not an economist. I would stress that Thaler has done more than even many of his fans may realize.
My favorite things Ireland
The last time I was in Ireland I wasn’t blogging yet. What riches lie here, let’s give it a start:
1. Poetry: I pick Joyce’s Ulysses, then Yeats and also Seamus Heaney, especially if the word “bog” appears in the poem. A good collection is The Penguin Book of Irish Poetry, edited by Patrick Crotty. Beyond the ranks of the super-famous, you might try Louis MacNeice, from the Auden Group, or perhaps Nuala Ní Dhomhnaill, who writes in Gaelic but has been translated by other superb Irish poets into English..
2. Novel/literature: Jonathan Swift: Gulliver’s Travels. One of the very very best books for social science too, and one of my favorite books period. After Joyce, there is also Oscar Wilde, George Bernard Shaw, Samuel Beckett, Lord Dunsany, John Banville (The Untouchable), William Trevor, and Elizabeth Bowen. Iris Murdoch was born in Ireland, but does she count? More recently I have enjoyed Anne Enright, Colm Tóibín, Eimear McBride, Claire Louise-Bennett, with Mike McCormack in my pile to read soon. Roddy Doyle is probably good, but I don’t find him so readable. Colum McCann somehow isn’t Irish enough for me, but many enjoy his work. Can the Anglo-Irish Oliver Goldsmith count? His Citizen of the World remains a neglected work. The recently published volumes of Samuel Beckett’s correspondence have received rave reviews and I hope to read through them this summer. Whew! And for a country of such a small population.
3. Classical music: Hmm…we hit a roadblock here. I don’t love John Field, so I have to call this category a fail. I can’t offhand think of many first-rate Irish classical performers, can you? James Galway?
4. Popular music: My Bloody Valentine, Loveless. Certainly my favorite album post-1970s, and possibly my favorite of all time. When the Irish do something well, they do it really really well. Then there is Van Morrison, Them, Bono and U2, Rory Gallagher, Bob Geldof and The Boomtown Rats, The Pogues, The Cranberries, and Sinead O’Connor, among others. I confess to having an inordinate weakness for Gilbert O’Sullivan. Traditional Irish music would need a post of its own, but it has never commanded much of my attention.
5. Painter: Francis Bacon is the obvious and probably correct choice, but I am no longer excited to see his work. I don’t find myself seeing new things in it. Sean Scully wins runner-up. This is a slightly weak category, at least relative to some of the others.
6. Political philosopher: Edmund Burke, who looks better all the time, I am sorry to say.
7. Philosopher: Bishop Berkeley. He is also interesting on monetary theory, anticipating some later ideas of Fischer Black on money as an abstract unit of account.
8. Classical economist: Mountifort Longfield and Isaac Butt both had better understandings of supply and demand and marginalism, before the marginal revolution, than almost any other economists except for a few of the French.
9. Theologian: C.S. Lewis, you could list him under fiction as well. Here is a debate over whether he is British or Irish. Laura Miller’s The Magician’s Book: A Skeptic’s Adventures in Narnia covers Lewis, one of my favorite books from the last decade.
10. Silicon Valley entrepreneur: Patrick Collison (duh), of Stripe and Atlas, here is his superb podcast with Ezra Klein. Here is further information on the pathbreaking Stripe Atlas project.
11. Movie: There are plenty I don’t like so much, such as My Left Foot, The Wind That Shakes the Barley, Waking Ned, and The Commitments. Most people consider those pretty good. I think I’ll opt for The Crying Game and also In the Name of the Father.
12: Movie, set in: Other than the movies listed above, there is Odd Man Out (quite good), The Quiet Man, and The Secret of Roan Inish, but my clear first choice is the still-underrated masterpiece Barry Lyndon.
The bottom line: The strengths are quite amazing, and that’s without adjusting for population.
Upward Mobility and Discrimination: Asians and African Americans
Asians in America faced heavy discrimination and animus in the early twentieth century. Yet, after institutional restrictions were lifted in the late 1940s, Asian incomes quickly converged to white incomes. Why? In the politically incorrect paper of the year (ungated) Nathaniel Hilger argues that convergence was due to market forces subverting discrimination. First, a reminder about the history and strength of discrimination against Asians:
Foreign-born Asians were barred from naturalization by the Naturalization Act of 1790. This Act excluded Asians from citizenship and voting except by birth, and created the important new legal category of “aliens ineligible for citizenship”…Asians experienced mob violence including lynchings and over 200 “roundups” from 1849-1906 (Pfaelzer, 2008), and hostility from anti-Asian clubs much like the Ku Klux Klan (e.g., the Asiatic Exclusion League, Chinese Exclusion League, Workingmen’s Party of CA), to an extent that does not appear to have any counterpart for blacks in CA history. Both Asians and blacks in CA could not testify against a white witness in court from 1853-73 (People v. Hall, 1853, see McClain, 1984), limiting Asians’ legal defense against white aggression. The Chinese Exclusion Act of 1882 and the “Gentlemen’s Agreement” in 1907 barred further immigration of all “laborers” from China and Japan.
…Asians have also faced intense economic discrimination. Many cities and states levied discriminatory taxes and fees on Asians (1852 Foreign Miner’s Tax, 1852 Commutation Tax, 1860 Fishing License, 1862 Police Tax, 1870 “queue” ordinance, 1870 sidewalk ordinance, and many others). Many professional schools and associations in CA excluded Asians (e.g., State Bar of CA), as did most labor unions (e.g., Knights of Labor, American Federation of Labor), and many employers declined to hire Asians well into the 20th century (e.g., Mears, 1928, p. 194-204). From 1913-23, virtually all western states passed increasingly strict Alien Land Acts that prohibited foreign-born Asians from owning land or leasing land for extended periods. Asians also faced laws against marriage to whites (1905 amendment to Section 60 of the CA Civil Code) and U.S. citizens (Expatriation Act 1907, Cable Act 1922). From 1942-46, the US forcibly relocated over 100,000 mainland Japanese Americans (unlike other Axis nationalities, e.g. German or Italian Americans) to military detention camps, in practice destroying a large share of Japanese American wealth. In contrast, blacks in CA were eligible for citizenship and suffrage, were officially (though often not de facto) included in CA professional associations and labor unions that excluded Asians, were not covered by the Alien Land Acts, and were not confined or expropriated during WWII.
Despite this intense discrimination, Asian (primarily Japanese and Chinese) incomes converged to white incomes as early as 1960 and certainly by 1980. One argument is that Asians invested so heavily in education that convergence has been overstated but Hilger shows that convergence occurred conditional on education. Similarly, convergence was not a matter of immigration or changing demographics. Instead, Hilger argues that once institutional discrimination was eased in the 1940s, market forces enforced convergence. As I wrote earlier, profit maximization subverts discrimination by employers:
If the wages of X-type workers are 25% lower than those of Y-type workers, for example, then a greedy capitalist can increase profits by hiring more X workers. If Y workers cost $15 per hour and X workers cost $11.25 per hour then a firm with 100 workers could make an extra $750,000 a year. In fact, a greedy capitalist could earn more than this by pricing just below the discriminating firms, taking over the market, and driving the discriminating firms under.
If that theory is true, however, then why haven’t black incomes converged? And here is where the paper gets into the politically incorrect:
Modern empirical work has indicated that cognitive test scores—interpreted as measures of productivity not captured by educational attainment—can account for a large share of black-white wage and earnings gaps (Neal and Johnson, 1996; Johnson and Neal, 1998; Fryer, 2010; Carruthers and Wanamaker, 2016). This literature documents large black-white test score gaps that emerge early in childhood (Fryer and Levitt, 2013), persist into adulthood, and appear to reflect genuine skills related to labor market productivity rather than racial bias in the testing instrument (Neal and Johnson, 1996). While these modern score gaps
have not been fully accounted for by measured background characteristics (Neal, 2006; Fryer and Levitt, 2006; Fryer, 2010), they likely relate to suppressed black skill acquisition during slavery and subsequent educational discrimination against blacks spanning multiple generations (Margo, 2016).
…A basic requirement of this hypothesis is that Asians in 1940 possessed greater skills than blacks, conditional on education. In fact, previous research on Japanese Americans in CA support this theory. Evidence from a variety of cognitive tests given to students in CA in the early 20th century suggest test score parity of Japanese Americans with local whites after accounting for linguistic and cultural discrepancies, and superiority of Japanese Americans in academic performance in grades 7-12 (Ichihashi, 1932; Bell, 1935).
Hilger supplements these earlier findings with a small dataset from the Army General Classification Test:
…these groups’ cognitive test performance can be studied using AGCT scores in WWII enlistment records from 1943. Remarkably, these data are large enough to compare Chinese, blacks and whites living in CA for these earlier cohorts. In addition, this sample contains enough young men past their early 20s to compare test scores conditional on final educational attainment, which can help to shed light on mechanisms underlying the conditional earnings gap documented above.
Figure XII plots the distribution of normalized test score residuals by race from an OLS regression of test z-scores on dummies for education and age. Chinese Americans and whites have strikingly similar conditional skill distributions, while the black skill distribution lags behind by nearly a full standard deviation. Table VIII shows that this pattern holds separately within broad educational categories. These high test scores of Chinese Americans provide strong evidence that the AGCT was not hopelessly biased against non-whites, as Neal and Johnson (1996) also find for the AFQT (the successor to the AGCT) in more recent cohorts.
From Hilger’s conclusion:
Using a large and broadly representative sample of WWII enlistee test scores from 1943 both on their own and matched to the 1940 census, I document the striking fact that these test scores can account for a large share of the black, but not Asian, conditional earnings gap in 1940. This result suggests that Asians earnings gaps in 1940 stemmed primarily from taste-based or some other non-statistical discrimination, in sharp contrast with the black earnings gap which largely reflected statistical discrimination based on skill gaps inherited from centuries of slavery and educational exclusion. The rapid divergence of conditional earnings between CA-born Asians and blacks after 1940—once CA abandoned its most severe discriminatory laws and practices—provides the first direct empirical evidence in support of the hypothesis of Arrow (1972) and others that competitive labor markets tend to eliminate earnings gaps based purely on taste-based but not statistical discrimination.
Hilger’s other research is here.
What I’ve been reading
1. Ronald C. White, American Ulysses: A Life of Ulysses S. Grant. Grant is still underrated, this book is highly readable and to the point and not to fusty. Someone should get Paul Krugman (a Grant fan) to review this book.
2. Jeffrey Edward Green, The Shadow of Unfairness: A Plebeian Theory of Liberal Democracy. “There will always be some plutocracy, don’t get bent out of shape too badly” is my brief summary of this one. This book could be more readable, but it is highly intelligent.
3. Esther Schor, Bridge of Words: Esperanto and the Dream of a Universal Language. I hadn’t known that almost all Esperanto words are accented on the penultimate syllable (bad for poetry), the system of correlatives and “table words” can be quite difficult (“It also has nine groups of word endings, not only for place but also for time, quantity, manner, possession, entity, etc.”), and how much the entire movement was influenced by the intellectual climate of late 19th century Russian Jewish thought. Recommended.
4. Elena Ferrante, Frantumaglia. A revealing look into the mind of the author, but this one works only if you know and love her novels already. Ferrante’s “children’s” story The Beach at Night is worthwhile, very dark, you can read it in a small number of minutes. Here is a good NYT review.
5. Cao Xueqin, The Story of the Stone [Dream of the Red Chamber], Penguin edition, vol.I. I am not confident of my ability to follow along all of the longer plot lines, but it is more absorbing and readable than I had recalled from a much earlier attempt to read it. And overall it does make upper middle class life in 18th century China seem more civilized than its counterpart in Europe.
Are sticky nominal wages an overrated idea?
Via Adam Ozimek, here is one recent (still unfinished) paper, by Kurmann, McEntarfer, and Spletzer:
Using administrative worker‐firm linked data for the United States, we examine the extent and consequences of nominal wage and earnings rigidities for U.S. firms. We find less evidence of downward wage rigidity in the administrative data than has been documented in previous studies based on self‐reported earnings from surveys. In our data, only 13 percent of workers who remain with the same firm (job stayers) experience zero change in their nominal hourly wage within a year, and over 20 percent of job stayers experience a reduction in their nominal hourly wage. The lower incidence of downward wage rigidity in the administrative data is likely a function of our broader earnings concept, which includes all monetary compensation paid to the worker (e.g. overtime pay, bonuses), whereas the previous literature has almost exclusively focused on the base rate of pay. When we examine firm labor cost adjustments on both the hours and wage margins, we find that firms have substantially more flexibility in adjusting hours downward than wages. As a result, the distribution of changes in nominal earnings is less asymmetric than the wage change distribution, with only about 6 percent of job stayers experiencing no change in nominal annual earnings, and over 25 percent of workers experiencing a reduction in nominal annual earnings. During the recent Great Recession, this earnings change distribution became almost completely symmetric and the proportion of job stayers experiencing a decline in annual earnings rose markedly to about 40 percent. Finally, we exploit the worker‐firm link in our data to show that it is mostly smaller establishments that show evidence of asymmetry in their earnings change distribution. For these smaller establishments, we find that indicators of downward wage rigidity are systematically associated with higher job destruction rates.
Here is another recent paper, this one from the NBER. It shows that real estate agents, who have flexible, commission-based wages, do have smaller employment fluctuations than sticky-wage construction workers. But that difference is only by about 10 to 20 percent.
Here is my previous post on sticky wages: Basu and House show that real wages vary a great deal through changes in expected career paths. Here is Alex’s 2014 post on half the men having new jobs since the recession.
Are your views on sticky nominal wages and the minimum wage consistent?
And how are nominal wages sticky for the unemployed?
Perhaps most significantly, high nominal demand economies such as Jamaica and Brazil (yes there are still a few left!) still appear capable of generating quite high rates of unemployment.