Month: October 2020
Well, which one is it?
If you consider the treatments of remdesivir or monoclonal antibodies for President Trump, their application is either positive expected value or negative expected value.
If they are positive expected value, you should be for using them! (I don’t mean that as a political statement, sub in another patient’s name if you need to.)
If they are negative expected value, you should oppose the current widespread use of remdesivir in hospitals (not necessarily in every case, of course), and you should probably oppose the Advance Market Commitment already in place for Regeneron’s monoclonal antibody treatment, not to mention its successful advance through various trials.
I don’t see anyone taking those stances.
Instead, I see commentators — including highly esteemed public health experts — claiming there is not yet enough data, “expressing reservations,” referring to other public health catastrophes, referring to more general irresponsible habits of the patient under consideration, and serving up various other rhetorical devices to indicate a negative attitude toward the treatment without actually saying “I think this treatment is negative expected value.”
That is a very bad thought and writing habit!
Made worse by Twitter, I might add. You are trying to create negative affect and mood affiliation without making the corresponding epistemic and predictive commitment.
Please just say you think it is negative expected value, and then apply that view consistently across the board. Stand your ground and defend it.
Or if you think it is positive expected value, praise its use, and then of course it is fine to add qualifiers and reservations.
If you genuinely have no opinion (ha), it is fine to say that too, but then you can drop the negative rhetoric and maybe don’t tweet about it at all.
To be sure, there are various heterogeneities and I am not applying the appropriate qualifiers in each sentence above, for reasons of expositional convenience. For instance, is Trump different from other patients? Are the treatments being applied at the right time? Who exactly has the private information here? And so on. Incorporating those factors should not change the basic analysis above, though for the most part they should push you toward a more positive attitude toward the treatments.
Mayank Gupta emails me:
The absolute number of false positives would rise dramatically under slightly inaccurate, broad surveillance testing. At least initially, the number of people going to the doctor to ask what to do would also rise. One can imagine if doctors truly flubbed and didn’t know how to advise patients accurately, a lot of individual patients would lose trust in the medical system (testing, doctors, or both). The consequence of this would be more resistance to health public policy measures in the future.
I see this as quite similar to what happened on three mile island. There was a clear utilitarian benefit to taking on some small amount of nuclear accident risk. The public was never taught how or why to internalize and cope with this risk. When the risk manifested, individuals saw the risk but not the public benefit and turned against nuclear. This change of public opinion was reflected in public policy after.
I’m sure there’s some mismatches in this analogy, but I’m using it to point out that in general I find thinking on the margin without thinking about the public’s ability to think on the margin can result in setbacks on the margin.
In an age where science is both more capable of solving social problems and more complex to understand, but the public has too much complex information to sort through, the central problem of governance seems to be how to solve public choice, without creating a monopoly on information.
To be clear, I do favor rapid testing, but it is worth giving this problem further thought.
Here is a new study by Valerie Michelman, Joseph Price, and Seth D. Zimmerman:
This paper studies social success at elite universities: who achieves it, how much it matters for students’ careers, and whether policies that increase interaction between rich and poor students can integrate the social groups that define it. Our setting is Harvard University in the 1920s and 1930s, where students compete for membership in exclusive social organizations known as final clubs. We combine within-family and room-randomization research designs with new archival and Census records documenting students’ college lives and career outcomes. We find that students from prestigious private high schools perform better socially but worse academically than others. This is important because academic success does not predict earnings, but social success does: members of selective final clubs earn 32% more than other students, and are more likely to work in finance and to join country clubs as adults, both characteristic of the era’s elite. The social success premium persists after conditioning on high school, legacy status, and even family. Leveraging a scaled residential integration policy, we show that random assignment to high-status peers raises rates of final club membership, but that overall effects are driven entirely by large gains for private school students. Residential assignment matters for long-run outcomes: more than 25 years later, a 50-percentile shift in residential peer group status raises the rate at which private school students work in finance by 37.1% and their membership in adult social clubs by 23.0%. We conclude that the social success premium in the elite labor market is large, and that its distribution depends on social interactions, but that the inequitable distribution of access to high-status social groups resists even vigorous attempts to promote cross-group cohesion.
You can think of this as another attempt to explain the relatively high returns to education, without postulating that students learn so much, and without emphasizing signaling so much. Going to Harvard is in fact winning access to a very valuable set of networks (which in turn is signaling as well, to be clear).
For the pointer I thank Tyler Ransom.
In an interview Friday afternoon, Regeneron’s chief executive, Dr. Leonard S. Schleifer, said Mr. Trump’s medical staff reached out to the company for permission to use the drug, and that it was cleared with the Food and Drug Administration.
“All we can say is that they asked to be able to use it, and we were happy to oblige,” he said. He said that so-called compassionate use cases — when patients are granted access to an experimental treatment outside of a clinical trial — are decided on a case-by-case basis and he is not the first patient to granted permission to use the treatment this way. “When it’s the president of the United States, of course, that gets — obviously — gets our attention.”
In my non-specialist but not entirely uninformed opinion, this is basically an effective treatment, and barring major unobserved genetic risk factors Trump will recover. The risk of side effects is not significant. But of course neither the FDA nor Regneron will let me do the same. Or you.
There is such cacophony when Trump pushes the FDA to speed vaccine approval — mere pressure rather than an action. Yet when he actually gets a promising treatment through the process “prematurely” — only for himself — not a single person is yelping. Not even his worst enemies and most vicious opponents. Nor do I see anyone arguing that the President is being allowed to take excess risk, and that the judgments of the regulators should be enforced consistently and for the good of the office of the presidency.
Nope. Model that! (Hint: start with the idea of status.)
In the meantime, I think the common intuition about the Trump monoclonal antibodies case is essentially correct, and it ought to be applied most broadly. And not just for presidents.
Here is the full NYT story.
In this paper, we argue that there was a strong link between the surge of support for the Socialist Party after World War I (WWI) and the subsequent emergence of Fascism in Italy. We first develop a source of variation in Socialist support across Italian municipalities in the 1919 election based on war casualties from the area. We show that these casualties are unrelated to a battery of political, economic and social variables before the war and had a major impact on Socialist support (partly because the Socialists were the main anti-war political movement). Our main result is that this boost to Socialist support (that is “exogenous” to the prior political leaning of the municipality) led to greater local Fascist activity as measured by local party branches and Fascist political violence (squadrismo), and to significantly larger vote share of the Fascist Party in the 1924 election. We document that the increase in the vote share of the Fascist Party was not at the expense of the Socialist Party and instead came from right-wing parties, thus supporting our interpretation that center-right and right-wing voters coalesced around the Fascist Party because of the “red scare”.
That is from a new paper by Daron Acemoglu, Giuseppe De Feo, Giacomo De Luca, and Gianluca Russo.
1. Were the experts too slow to embrace travel restrictions? (NYT) And the Covid culture that is German (short video).
2. Does personality drive moral judgement?: Polite deontologists and curious consequentialists.
3. My rewrite of this thread: doctors hate highly beneficial but somewhat inaccurate testing methods that lower their status and good feelings about themselves.
4. Further results on “dry tinder” in the Nordics: “My results show that a large share of the excess mortality in Sweden in April 2020 may be partially explained by a vulnerable, elderly population due to very mild flu seasons in 18/19 and 19/20 as well as very few deaths during the 2019 summer compared to earlier years and compared to other Nordic countries.”
Comments are open. But if you as a reader click on the comments link, the fault is yours not mine.
By Kyle Myers:
This paper identifies the degree to which scientists are willing to change the direction of their work in exchange for resources. Data from the National Institutes of Health are used to estimate how scientists respond to targeted funding opportunities. Inducing a scientist to change their direction by a small amount—to work on marginally different topics—requires a substantial amount of funding in expectation. The switching costs of science are large. The productivity of grants is also estimated, and it appears the additional costs of targeted research may be more than offset by more productive scientists pursuing these grants.
In this issue:
Five cities, five stories? Robert Kaestner explores the heterogeneity of results across Baltimore, Boston, Chicago, Los Angeles, and New York in the work of Raj Chetty, Nathaniel Hendren, and Lawrence Katz, arguing that it is misleading to suggest that moving before the age of 13 to lower-poverty neighborhoods promises better outcomes. Chetty, Hendren, and Katz respond.
The AEA: Republicans need not apply: Mitchell Langbert investigates the American Economic Association, using voter-registration data and political-contribution data to show that the AEA officers, editors, authors, and other players are quite thoroughgoingly Democratic.
The AER: How much space is given to articles on gender, race and ethnicity, and inequality?: Jeremy Horpedahl and Arnold Kling track the trends 1991–2020 for the American Economic Review and Papers & Proceedings.
Lockdowns and covid hospitalizations: John Spry criticizes a JAMA research letter by Soumya Sen, Pinar Karaca-Mandic, and Archelle Georgiou about the effectiveness of stay-at-home orders, for eliding available placebo comparisons. Sen, Karaca-Mandic, and Georgiou reply.
Reading, writing, and Adam Smith: Scott Drylie uses Smith’s final words on school financing to review interpretations of Smith on schooling.
Carl Menger: The Errors of Historicism in German Economics: The first English translation of Menger’s 1884 reply to Gustav Schmoller is provided by Karen Horn and Stefan Kolev, whose Foreword analyzes the not-so-amicable Methodenstreit.
Data alteration: Ron Michener rejoins to Farley Grubb, explaining why he thinks that Grubb had no grounds for altering John McCusker’s data series and thereby generating outliers on which his results depend. (Professor Grubb received Professor Michener’s comment too late to allow for concurrent reply but will reply in the next issue of this journal.)
Frictionless note: With the approval and gratitude of Jeffrey Bergstrand, Nico Stoeckmann corrects the constant in the equation for a special, frictionless case of Bergstrand’s gravity equation for international trade.
Liberalism in Brazil: Lucas Berlanza provides a historical and modern guide to the fortunes of liberal ideas and trends in Brazil, extending the Classical Liberalism in Econ, by Country series to 20 articles.
Readworthy 2050: Nine correspondents respond to the question: What 21st-Century Works Will Merit a Close Reading in 2050?
Karen Horn and Stefan Kolev on Menger vs. Schmoller: The translators discuss Menger’s 1884 The Errors of Historicism in German Economics and the broader Methodenstreit.
And yes, you can find a parking spot in most parts of Manhattan these days, another novelty. Did I mention that my hotel room cost less than a third of what I’ve normally paid?
I visited the Museum of Modern Art, operating under stringent visitor restrictions and with its tourist clientele mostly gone. I had just about every gallery to myself, and thus an unparalleled look at the museum’s masterpieces. If a room had even a few other visitors in it, I moved on and came back later.
The center of the city has moved downtown, to Greenwich Village and surrounding areas. Many streets are closed to cars, and restaurants have put their tables on the sidewalk or the street. Instead of choosing a place on the basis of the food, the menu now just has to be “good enough,” with the key variables being the quality of the seating and the degree of the spacing. I have never seen that part of town feel so alive. The most vibrant single street for both food and socializing was slightly further north in Koreatown, starting at 32nd and Broadway and spreading two blocks to the east.
Here is the rest of my Bloomberg column on that topic. By no means is my entire assessment so positive, but that is the excerpt you are getting today.
4. How did the DOE’s first crop of risky energy tech do? Original research here.
The latest MRU video in our series Economists in the Wild features Orley Ashenfelter talking about his research on wine. One thing I hadn’t known is that Orley used his regressions to figure out that New Jersey was actually a great place to start a vineyard, and he did! See also the results from the Judgment of Princeton.
Here’s a free assignment to help connect this video to class: https://mru.io/1a6ba
Regression analysis assignment: https://mru.io/d8194
More professor resources: http://mru.io/professor-resources-5e7df
High school teacher resources: https://mru.io/high-school-resources-27767
A key unsolved question in the current coronavirus disease 2019 (COVID-19) pandemic is the duration of acquired immunity. Insights from infections with the four seasonal human coronaviruses might reveal common characteristics applicable to all human coronaviruses. We monitored healthy individuals for more than 35 years and determined that reinfection with the same seasonal coronavirus occurred frequently at 12 months after infection.
That is from a new research paper by Arthur W D Edridge, et.al. That is not conclusive proof concerning Covid-19, but it’s not exactly great news either.
How persistent are economic gaps across ethnicities? The convergence of ethnic gaps through the third generation of immigrants is difficult to measure because few datasets include grandparental birthplace. I overcome this limitation with a new three-generational dataset that links immigrant grandfathers in 1880 to their grandsons in 1940. I find that the persistence of ethnic gaps in occupational income is 2.5 times stronger than predicted by a standard grandfather-grandson elasticity. While part of the discrepancy is due to measurement error attenuating the grandfather-grandson elasticity, mechanisms related to geography also partially explain the stronger persistence of ethnic occupational differentials.
That is the abstract of a piece by Zachary Ward, from American Economic Journal: Applied Economics. In a number of regards this paper goes well beyond the previous literature. Here is another interesting sentence:
…I find that 51 percent of initial ethnic gaps in occupational income remained after three generations.
The author also notes:
Rather than argue for an ethnic-specific causal mechanism, I instead point to measurement error and geography as key reasons for the stronger persistence of ethnic differentials across three generations.
I am not so convinced, as where you choose to live is endogenous to your expected labor market quality. I am somewhat more persuaded by this point:
…the ethnic mean provides more information about the father’s true occupational status.
Iin other words, what appears to be an influence of ethnicity might instead be a transmission channel through the background of one’s own father.
At times the author seems naive, at other times Straussian, or maybe just afraid? To be clear, I am myself an extreme culturalist, and that is not a Straussian remark. This is in any case a major contribution to a contentious debate.