Category: Uncategorized
Sunday assorted links
1. Assorted links on progress studies.
2. James Altucher is bearish on NYC. Not my view, but worth a hearing. Of course I would never live there, but that has always been the case.
3. Arbitrage with stolen books?
4. Manufacturing vaccines, excellent piece (Bloomberg).
6. Professional sports already increase influenza mortality (shh!).
The new quicker, cheaper, supply chain robust saliva test
The FDA has just approved a new and important Covid-19 test:
“Wide-spread testing is critical for our control efforts. We simplified the test so that it only costs a couple of dollars for reagents, and we expect that labs will only charge about $10 per sample. If cheap alternatives like SalivaDirect can be implemented across the country, we may finally get a handle on this pandemic, even before a vaccine,” said Grubaugh.
One of the team’s goals was to eliminate the expensive saliva collection tubes that other companies use to preserve the virus for detection. In a separate study led by Wyllie and the team at the Yale School of Public Health, and recently published on medRxiv, they found that SARS-CoV-2 is stable in saliva for prolonged periods at warm temperatures, and that preservatives or specialized tubes are not necessary for collection of saliva.
Of course this part warmed my heart (doubly):
The related research was funded by the NBA, National Basketball Players Association, and a Fast Grant from the Emergent Ventures at the Mercatus Center, George Mason University.
The NBA had the wisdom to use its unique “bubble” to run multiple tests on players at once, to see how reliable the less-known tests would be. This WSJ article — “Experts say it could be key to increasing the nation’s testing capacity” — has the entire NBA back story. At an estimated $10 a pop, this could especially be a game-changer for poorer nations. Furthermore, it has the potential to make pooled testing much easier as well.
Here is an excerpt from the research pre-print:
The critical component of our approach is to use saliva instead of respiratory swabs, which enables non-invasive frequent sampling and reduces the need for trained healthcare professionals during collection. Furthermore, we simplified our diagnostic test by (1) not requiring nucleic acid preservatives at sample collection, (2) replacing nucleic acid extraction with a simple proteinase K and heat treatment step, and (3) testing specimens with a dualplex quantitative reverse transcription PCR (RT-qPCR) assay. We validated SalivaDirect with reagents and instruments from multiple vendors to minimize the risk for supply chain issues. Regardless of our tested combination of reagents and instruments from different vendors, we found that SalivaDirect is highly sensitive with a limit of detection of 6-12 SARS-CoV-2 copies/μL.
No need to worry and fuss about RNA extraction now. Here is the best simple explanation of the whole thing.
The researchers are not seeking to commercialize their advance, rather they are making it available for the general benefit of mankind. Here is Nathan Grubaugh on Twitter. Here is Anne Wyllie, also a Kiwi and a Kevin Garnett fan. A further implication of course is that the NBA bubble is not “just sports,” but also has boosted innovation by enabling data collection.
All good news of course, and Fast at that. And this:
“This could be one the first major game changers in fighting the pandemic,” tweeted Andy Slavitt, a former acting administrator of the Centers for Medicare and Medicaid Services in the Obama administration, who expects testing capacity to be expanded significantly. “Rarely am I this enthusiastic… They are turning testing from a bespoke suit to a low-cost commodity.”
And here is coverage from Zach Lowe. I am very pleased with the course of Fast Grants more generally, and you will be hearing more about it in the future.
The T-Cell immune response that didn’t bark
T-Cell immune response (not to be confused with invulnerability) is hardly a new idea in public health. Yet what is striking is how long it took you to hear about it — from the mainstream at least — in the context of coronavirus.
If you go back to February, March, even April or dare I say May, you will not find too many mainstream public health commentators suggesting “there is some possibility of T-cell immunity playing a major role here. That could significantly ease the future casualties and economic burden of Covid-19.” David Wallace-Wells dates the beginning of the discussion to late May, and the “dark matter” hypothesis of Friston, though I believe earlier precursors will be found.
You didn’t even hear much of: “We really are not sure T-cell immunity is a factor. But it could be a factor with probability [fill in the blank], and it is worth keeping that in mind.”
The major New York Times piece on T-Cell immunity doesn’t run until August 6. And the Wallace-Wells piece is dated August 9.
Think about the underlying equilibrium that could lead to such a strange result.
if you do public health, your status incentives are to deliver warnings, not potential good news.
Your status incentives are always to hedge your bets, and to be reluctant to introduce new hypotheses.
Your status incentives are to steer talk away from the virus “simply continuing to rip,” even if you are quite opposed to that outcome. Other than hitting it with an immediate scold, you are not supposed to let that option climb on to the discussion table for too long.
Your status incentives are to discourage individuals from thinking that they might be have some pre-existing level of protection. That might lead them to behave more irresponsibly, and then you in turn would look less responsible.
Since public health commentators are so concerned with “doing good by us,” they fail to see that their altruistic (and status) motives in these matters mean they do not end up telling us the truth. Not the entire truth, and not upfront in a very prompt matter.
To be fair, I don’t recall seeing mainstream commentators making false claims about T-cell immunity, rather their filters end up being very selective ones and they bring it up only slowly. And because they smush together in their minds the actually quite distinct concepts of “doing good,” “status,” and “informing the public,” they genuinely have no idea that they are not entirely on the side of truth.
And they genuinely have no idea why so many smart people look to “the cranks” for advice and counsel.
And, to be clear, the commentary of “the cranks” in this area has plenty of problems of its own, even though in some ways they have turned out to be a more informative (as distinct from accurate) source on T-cell immunity.
Finally, to recap, we still are not sure how much overall social protection T-cell immunity will bring. Furthermore, we are pretty sure that not many places have a chance of current herd immunity from “a mix of previous Covid exposure plus pre-existing T-cell immunity.”
So I am not trying to induce you to overrate the T-cell immunity idea. I am trying to illuminate the biases of the filters at work in your everyday consumption of Covid-19 information. Those biases too, the mainstream commentators are not so keen to tell you about.
Using Social Media to Bring Down the Power Grid
Social media are a coordination device and coordinated behavior has many advantages. Social media was used to motivate, organize and coordinate movements like the Arab Spring and Black Lives Matter. Of course, coordination can also lead to conspiracy theories like QAnon, twitter mobs that police political correctness and riots that lead to death and destruction. For better or worse, coordinated behavior is likely to increase, creating more and more quickly moving mobs. The use and abuse of such mobs is only just beginning. One insidiously clever prospect is the use of seemingly benign coordination to bring down a power grid. What if everyone turns on their air conditioner and lights at the same time? In How weaponizing disinformation can bring down a city’s power grid, Raman et al. discuss how such a scenario could be generate by something seemingly as simple as sending fake coupons!
Social media has made it possible to manipulate the masses via disinformation and fake news at an unprecedented scale. This is particularly alarming from a security perspective, as humans have proven to be one of the weakest links when protecting critical infrastructure in general, and the power grid in particular. Here, we consider an attack in which an adversary attempts to manipulate the behavior of energy consumers by sending fake discount notifications encouraging them to shift their consumption into the peak-demand period. Using Greater London as a case study, we show that such disinformation can indeed lead to unwitting consumers synchronizing their energy-usage patterns, and result in blackouts on a city-scale if the grid is heavily loaded. We then conduct surveys to assess the propensity of people to follow-through on such notifications and forward them to their friends. This allows us to model how the disinformation may propagate through social networks, potentially amplifying the attack impact. These findings demonstrate that in an era when disinformation can be weaponized, system vulnerabilities arise not only from the hardware and software of critical infrastructure, but also from the behavior of the consumers.
Hat tip: Kevin Lewis.
Addendum: California is once again issuing rolling blackouts. Welcome to the future.
Saturday morning assorted links
Claims about Richard Wagner
The truth is that Wagner’s popularity was already in relative decline during the Weimar Republic and simply fell further, more quickly, under the Nazis. During the last years of the Kaiser’s Germany (and despite the cost and privation of the First World War), the Master’s works were still hugely popular, accounting for over eighteen per cent of all opera performances, a share no other composer came to matching. By the mid-1920s, though, the figure had dropped to around fourteen per cent.
After Hitler took power, Wagner’s share plunged to well below ten percent.
The truth is that many Nazis, in high and low places, were bored to tears by Wagner.
That is all from Jonathan Carr’s excellent book The Wagner Clan.
Friday assorted links
2. Deaton interviews Sen, with Tim Besley moderating, full of interesting content.
3. 80,000 hours Shruti Rajagopalan interviewed by Howie Lempel podcast, “What India did to stop Covid-19 and how well it worked,” self-recommending.
4. The British economy in pandemic (NYT).
5. Herbert Blomstedt back to conducting at age 93, an example for us all.
Young “stars” in economics
I had not seen this paper before, by Kevin A. Bryan, here is the abstract:
We construct a data set of job flyouts for junior economists between 2013 and 2018 to investigate three aspects of the market for “stars.” First, what is the background of students who become stars? Second, what type of research does the top of the market demand? Third, where do these students take jobs? Among other results, we show that stars are more likely to be international and male than PhDs overall, that theoretical and semi-theoretical approaches remain dominant, that American programs both produce the most stars and hire even more, that almost none are hired by the private sector, and that there is a strong shift toward having pre-PhD full-time academic research jobs.
Is this good news or bad? The paper is interesting throughout, here is another bit:
…both Americans and women are nearly twice as likely to have Applied Micro as a primary field compared to non-Americans and men.
As for country of origin of these star students, see p.5, I was surprised to see Germany rank second after the United States, with Italy and France not far behind, China coming next, then Argentina (!).
Via Soumaya Keynes.
The future of higher education could be India
This is a fantasy, not a prediction, still we can hold out hope, here is my latest Bloomberg column:
In my fantasy, the [Western] schools that are open to expanding their India operations will rise considerably in reputation. India, and South Asia more generally, is in the midst of a phenomenal explosion of talent in diverse fields…
You might wonder whether India actually needs all of these foreign branches, when it has some superb schools of its own, for instance the various Indian Institutes of Technology. In my fantasy, some Indian institutions of higher education will improve and force some competitors — shall we say UC Berkeley? — to leave the country. Yet many talented Indians will find attending a branch of Harvard or Yale to be an appealing option. Furthermore, the top foreign schools may form alliances with Indian institutions (as Yale has done in Singapore), giving students the best of both worlds.
This future gets better yet. Over time, the population of Indian alumni of prestigious U.S. universities will increase, relative to those who studied and graduated in America. America’s top schools thus will become engines of opportunity. It might also become obvious that the students attending in the U.S. are underperforming their Indian counterparts. What better way to light a competitive fire under the current dominant institutions?
And maybe some of the keenest and most ambitious American students will prefer to study in India rather than in America. (Perhaps a “canceled” American student could be sent to Brown Uttar Pradesh?) Wouldn’t you want to study with the very best of your peers, knowing you might be sitting next to the next generation’s Einstein, von Neumann or, of course Ramanujan?
There is more at the link, noting that this is a Swiftian fantasy of sorts.
Thursday assorted links
The Supply and Demand Model Predicts Behavior in Thousands of Experiments
It is sometimes said that economics does not predict. In fact, Lin et al. (2020) (SSRN) (including Colin Camerer) find that the classic supply and demand model predicts behavior and outcomes in the double oral auction experiment in thousands of different experiments across the world. The model predicts average prices, final prices, who buys, who sells, and the distribution of gains very well as Vernon Smith first showed in the 1960s.
Indeed, the results from simple competitive buyer-seller trading appear to be as close to a culturally universal, highly reproducible outcome as one is likely to get in social science about collective behavior. This bold claim is limited, of course, by the fact that all these data are high school and college students in classes in “WEIRD” societies (Henrich et al.,2010b). Given this apparent robustness, it would next be useful to establish if emergence of CE in small buyer-seller markets extends to small-scale societies, across the human life cycle, to adult psychopathology and cognitive deficit, and even to other species.
It is true that economic theory is less capable of explaining the process by which prices and quantities reach equilibrium levels. Adam Smith’s theory about how competitive equilibrium is reached (“as if by an invisible hand”) has been improved upon only modestly. The authors, however, are able to test several theories of market processes and find that zero-intelligence theories tend to do better, though not uniformly so, than theories requiring more strategic and forward thinking behavior by market participants. The double-oral auction is powerful because the market is intelligent even when the traders are not.
The authors also find that bargaining behavior in the ultimatum game is reproducible in thousands of experiments. Simple economic theory makes very poor predictions (offer and accept epsilon) in this model but the deviations are well known and reproducible around the world (participants, for example, are more likely to accept and to accept quickly a 50% split than a split at any other level).
The experiments were run using MobLab, the classroom app, and were run without monetary incentives.
Tyler and I use Vernon Smith’s experiments to explain the Supply-Demand model in our textbook, Modern Principles, and it’s always fun to run the same experiment in the classroom. I’ve done this many times and never failed to reach equilibrium!
What is good news and bad news on the Covid-19 front
Following on my earlier analysis, ideally you want that super-spreaders are a fixed group who do not rotate much. That makes semi-effective herd immunity easier to reach in a region. So, in Bayesian terms, for a given super-spreader event, exactly which kind of story should you be rooting for?
Let’s say (hypothetically) that being a super-spreader has to do with your innate propensity to be infectious, as might be determined say by your genetic make-up. Then it is easier for the super-spreaders to acquire at least partial immunity, without a new group of super-spreaders rising up to take their place.
Alternatively, let’s say that being a super-spreader has to do with being in some relatively well-defined occupations and situations, such as singing in a church choir. That is a less optimistic prognosis, but still one of the better scenarios, as in principle it is possible to shut down many of those opportunities and thus block out the potential super-spreaders from doing their thing.
You should feel less good when you read of super-spreading events in very general public spaces, such as elevators, movie theaters, and office buildings. Those events, in Bayesian fashion, boost the probability that super-spreading is a generic ability, attached to a wide variety of fairly general situations. That raises the chance that, even after some super-spreaders acquire partial immunity, other super-spreaders will step in and play similar roles. Quite possibly all sorts of individuals — and not just those genetically endowed with super-powerful sneezes — are capable of super-spreading in small, enclosed public spaces.
You really do want those super-spreaders to be inelastic in supply.
Probabilistic profit from UFOs?
Let’s say the rest of the market was undervaluing the chance of UFOs being “something interesting.” What might be the proper trade? David S. emails me, and I will dispense with further indentation but what follows are his words not mine:
“Some potential food for thought:
– Going long volatility or long defense stocks seems like the most conventional answer.
– An even more conventional answer would be that it wouldn’t matter since any apocalypse means that even a correct bet is unlikely to have material redeemable value.
– Rather than framing the payout event as the binary of an actual UFO invasion, an alternative framing would be to bet on further government leaks causing the market to move it’s probability of invasion / apocalypse from 0.00% to 0.01%.
- Should you at least shorten the duration of your holdings on the margin? With interest rates near zero and record(-ish) high PE multiples, shouldn’t you be (marginally) less willing to pay for far-out cash flows? Could this finally fuel a resurgence of the value factor vs the growth factor?
- To take it a step further, should people consume more today and invest less given that the EV/NPV of these payouts will be somewhat lower?
- Other than high-dividend stocks and cash, what other trades are short-duration without going to zero if the apocalypse fails to arrive on time?
– My contrarian approach would be to go very long due to the underrated potential of technology transfer and overrated potential of apocalypse (especially in the near-term). For instance, if we found intelligent life on a planet like Mars (but less intelligent than humans), it would likely be decades between first contact and when humans would muster a military force to extinguish or fully dominate the other species (if ever). Also, based on the continued existence of thousands of species (many of which are flourishing) on earth in parallel with human existence, its not clear why we would assume that a more intelligent form of life that engages with humans would even try to extinguish. Per Steven Pinker, more intelligent species would likely also be more moral and therefore less likely to be focused on zero-sum extinction.”
TC again: Obviously many short positions would be in order. In terms of longs, my intuitions would be to buy a very diverse bundle of natural resources. Presumably the aliens have not brought many minerals with them, and they will need some minerals to do…whatever it is they plan on doing. Maybe lots of minerals. But you don’t know which ones.
Wednesday assorted links
1. “On November 9th, 2019 the Center for Genomic Gastronomy will install the Smog Tasting project in Hong Kong City Hall. Citizens will be able to taste and compare a range of smog meringues collected from around the city considering the flavors, ingredients, and composition of Hong Kong’s atmospheric taste of place.” Link here.
2. An example of objectionable “medical ethics” from blue-check Twitter: “The Russian vaccine gamble is reckless and foolish, whether ‘it works’ or not. Actually, the worst long-term outcome may be for the gamble to pay off, at the cost of decades of health care ethics ruined…” I mean that might be true, but without argument or further calculation? Really? You can read the longer treatment here.
3. The llama cure for Covid-19?
4. Coasean bargaining over ransomware.
5. On-line version of a Donald J. Harris book on income distribution.
My Conversation with Nicholas Bloom
Excellent and interesting throughout, here is the transcript, video, and audio. Here is part of the summary:
He joined Tyler for a conversation about which areas of science are making progress, the factors that have made research more expensive, why government should invest more in R&D, how lean management transformed manufacturing, how India’s congested legal system inhibits economic development, the effects of technology on Scottish football hooliganism, why firms thrive in China, how weak legal systems incentivize nepotism, why he’s not worried about the effects of remote work on American productivity (in the short-term), the drawbacks of elite graduate programs, how his first “academic love” shapes his work today, the benefits of working with co-authors, why he prefers periodicals and podcasts to reading books, and more.
Here is an excerpt:
COWEN: If I understand your estimates correctly, efficacy per researcher, as you measure it, is falling by about 5 percent a year [paper here]. That seems phenomenally high. What’s the mechanism that could account for such a rapid decline?
BLOOM: The big picture — just to make sure everyone’s on the same page — is, if you look in the US, productivity growth . . . In fact, I could go back a lot further. It’s interesting — you go much further, and you think of European and North American history. In the UK that has better data, there was very, very little productivity growth until the Industrial Revolution. Literally, from the time the Romans left in whatever, roughly 100 AD, until 1750, technological progress was very slow.
Sure, the British were more advanced at that point, but not dramatically. The estimates were like 0.1 percent a year, so very low. Then the Industrial Revolution starts, and it starts to speed up and speed up and speed up. And technological progress, in terms of productivity growth, peaks in the 1950s at something like 3 to 4 percent a year, and then it’s been falling ever since.
Then you ask that rate of fall — it’s 5 percent, roughly. It would have fallen if we held inputs constant. The one thing that’s been offsetting that fall in the rate of progress is we’ve put more and more resources into it. Again, if you think of the US, the number of research universities has exploded, the number of firms having research labs.
Thomas Edison, for example, was the first lab about 100 years ago, but post–World War II, most large American companies have been pushing huge amounts of cash into R&D. But despite all of that increase in inputs, actually, productivity growth has been slowing over the last 50 years. That’s the sense in which it’s harder and harder to find new ideas. We’re putting more inputs into labs, but actually productivity growth is falling.
COWEN: Let’s say paperwork for researchers is increasing, bureaucratization is increasing. How do we get that to be negative 5 percent a year as an effect? Is it that we’re throwing kryptonite at our top people? Your productivity is not declining 5 percent a year, or is it? COVID aside.
BLOOM: COVID aside. Yeah, it’s hard to tell your own productivity. Oddly enough, I always feel like, “Ah, you know, the stuff that I did before was better research ideas.” And then something comes along. I’d say personally, it’s very stochastic. I find it very hard to predict it. Increasingly, it comes from working with basically great, and often younger, coauthors.
Why is it happening at the aggregate level? I think there are three reasons going on. One is actually come back to Ben Jones, who had an important paper, which is called, I believe, “[Death of the] Renaissance Man.” This came out 15 years ago or something. The idea was, it takes longer and longer for us to train.
Just in economics — when I first started in economics, it was standard to do a four-year PhD. It’s now a six-year PhD, plus many of the PhD students have done a pre-doc, so they’ve done an extra two years. We’re taking three or four years longer just to get to the research frontier. There’s so much more knowledge before us, it just takes longer to train up. That’s one story.
A second story I’ve heard is, research is getting more complicated. I remember I sat down with a former CEO of SRI, Stanford Research Institute, which is a big research lab out here that’s done many things. For example, Siri came out of SRI. He said, “Increasingly it’s interdisciplinary teams now.”
It used to be you’d have one or two scientists could come up with great ideas. Now, you’re having to combine a couple. I can’t remember if he said for Siri, but he said there are three or four different research groups in SRI that were being pulled together to do that. That of course makes it more expensive. And when you think of biogenetics, combining biology and genetics, or bioengineering, there’s many more cross-field areas.
Then finally, as you say, I suspect regulation costs, various other factors are making it harder to undertake research. A lot of that’s probably good. I’d have to look at individual regulations. Health and safety, for example, is probably a good idea, but in the same way, that is almost certainly making it more expensive to run labs…
COWEN: What if I argued none of those are the central factors because, if those were true as the central factors, you would expect the wages of scientists, especially in the private sector, to be declining, say by 5 percent a year. But they’re not declining. They’re mostly going up.
Doesn’t the explanation have to be that scientific efforts used to be devoted to public goods much more, and now they’re being devoted to private goods? That’s the only explanation that’s consistent with rising wages for science but a declining social output from her research, her scientific productivity.
And this:
COWEN: What exactly is the value of management consultants? Because to many outsiders, it appears absurd that these not-so-well-trained young people come in. They tell companies what to do. Sometimes it’s even called fraudulent if they command high returns. How does this work? What’s the value added?
Definitely recommended