Here’s what academic social, behavioral, and economic scientists should be working on right now.

In a recent comment thread on the lack of relevance of academic social and behavioral science to the current crisis, Terry writes:

We face a once-in-a-lifetime event, and the existing literature gives mostly vapid-sounding guidance. Take this gem at the beginning of the article:

One of the central emotional responses during a pandemic is fear. Humans, like other animals, possess a set of defensive systems for combating ecological threats. Negative emotions resulting from threat can be contagious6, and fear can make threats appear more imminent.

But, the pandemic seems to be a huge opportunity for future work delving into the details of how the pandemic will change society and behavior. Forget the vague, overarching studies of generalities and focus instead on the myriad of details. Things like how the meat-packing industry is going to change its assembly line procedures. How will STD transmission change. Look carefully at working remotely, when does it work and not work. How can distance education be made better; how can the collegiate experience be replicated among distance learners. Etc.

I agree. It’s funny for me to be making this argument, given that I’m not doing this work myself. When I’m not writing, I’m doing statistical modeling. I’m not redesigning meat-packing assembly lines. But, yeah, I think Terry is right that there are lots of exciting applied problems for social science to be working on. Also, God is in every leaf of every tree, so if you really push hard to solve these applied problems, the theory will come along with it.

16 thoughts on “Here’s what academic social, behavioral, and economic scientists should be working on right now.

  1. Good news: many social scientist couldn’t find work in the terrible academic job market, so we joined the private sector instead. There, doing applied like this is our bread and butter. So just because it isn’t happening at the elite universities who have decided to fund administrators and activity centers and sports teams instead of research and teaching doesn’t mean it isn’t happening in reality. I guess I really can tell my advisor, who considers me a failure because I joined the private sector, that I am reliable after all.

  2. I think this is a symptom of a bigger problem in the US. The US is stagnating heavily in terms of innovation. Almost all the big effort is in a few areas that I consider mostly harmful. We have:

    1) Marketing: how to convince people to purchase things they mostly don’t want by spying on them.

    2) Market Segmentation: How to extract more money from people without increasing your real goods/services output at all (airlines, broadband overage fees, special pricing for students, special pricing for first responders, special pricing for xyz)

    3) Government Subsidized Monopoly: Coming up with ways to extract money from people at monopolistic prices for things like copyrighted or patented products, or locally granted monopolies or competition protected oligopolies (cable/broadband).

    4) Heavily protected industries with leverage due to low elasticity of demand: Medical industry, university education.

    5) Predatory financial practices: student lending, housing lending, payday loans

    6) Getting the government to bail you out: cruise ship edition, airline edition, meat packing edition, General Motors edition…

    7) Getting the government to buy your quack medicines in stockpile quantities (tamiflu edition) or your “brand new design for ventilators” even though yeah, ventilators probably kill COVID patients.

    If you came up with a way to make meat packing plants safer and more efficient, my guess is the response would be “why, when we can just get the govt to indemnify us from people who get sick and pack them in even tighter in the name of “national food security” and make easily way more profits compared to the investment to make our plant a little more efficient and safe? Besides there are 20M people out of work, there’s plenty more where they came from”

    It’s sickening how much business relies on the largess of government policies. Small businesses can’t even get the loans intended for them because nationwide chain restaurants are snapping up the free funds using their full time “teat suckling department”

    • +1 to all of this. I would add that the worst bailout industry offender is easily investment banking. By and large, the Fed props up the Too Big to Fail banks who then make most of the major decisions shaping our economy. They have the ultimate ‘heads we win, tails taxpayers lose’ racket.

  3. Just pointing out that while the critique of behavioral / social science in the pandemic is justified regarding some narrow (but disproportionately visible) slice of behavioral scientists, there are many people tackling the important issues, too. Unfortunately, there’s a selection issue: producing high quality research typically takes more time than has passed since the start of the pandemic. Hence, the studies that are currently available are disproportionately likely to be quick, dirty, minor, and shallow (though not all of them are, of course).

    Regarding the importance of the less publicly visible slice of social scientists, I’m copying some great points that Ivan Korolev (https://sites.google.com/view/ivan-korolev/home) has made:

    [quote begins]

    1. I don’t think that “curing coronavirus” is only about epidemiology and/or medicine. There are some parts of the problem that are, indeed, about medicine, e.g. finding appropriate treatments or developing new medications. But there are also parts of the problem that are multifaceted and extend far beyond epidemiology in itself. For instance, forecasting the spread of the epidemics involves:
    a) epidemiological modeling;
    b) studying parameter identification;
    c) estimating parameters from the data;
    d) quantifying the uncertainty about the resulting forecasts.
    While an epidemiologist is better equipped to do (a) than a social scientist, this is not necessarily true for (b)-(d). Tasks (b)-(d) are way more common in statistics and econometrics than in epidemiology, so a statistician or econometrician may be able to deal with those better than an epidemiologist.

    2. I’ve always thought that one should evaluate research based on the methods rather than based on the results, authors’ background, or authors’ institutional affiliation. I don’t understand why this time should be any different.
    In particular, I think that one should apply the same standard to studies from different fields. In *every* empirical economics seminar that I’ve seen, at some point someone raises a hand and asks the question: “How do you identify your parameters from the data?” or “Why do you think your model is reasonable?”
    If the presenter is not able to answer these questions well, a disaster is looming. Yet, when we are talking about epidemiology studies, for some reason we shy away from asking the same questions. I cannot understand why we automatically assume that epidemiologists’ methods are reasonable just because “they are experts in their field.”

    3. Unfortunately, I’ve seen many, many studies related to the coronavirus that had serious issues. Not just studies written by social scientists, but also (and perhaps primarily) studies written by epidemiologists. Some of the issues have been noticed and widely discussed (e.g. the issues with the Stanford antibodies studies), others have been largely ignored.

    For instance, independently of my work, Charles Manski (an econometrician who is famous for his work on partial identification and who should get the Nobel Prize one day) and Francesca Molinari show that the infection rate (the proportion of the population that is infected) cannot be point identified from the data. As a result, the case fatality rate also cannot be point identified. (https://arxiv.org/abs/2004.06178)

    [quote ends]

    • Sandro –

      Given that Manksi/Molinari paper you linked was dated a month ago…how do you reflect at this date on their conclusion that…”We find that the infection rate might be substantially higher than reported. We also find that the infection fatality rate in Italy is substantially lower than reported.”

      I mean “than reported” is a bit vague. But mixing the subsequent data and the methods described in that paper – I’m curious how you’d bound the infection rate, and the fatality rate in Italy (understanding that there is a large regional variability)?

    • Are you saying that biostatisticians and infectious disease modelers in network epidemiology and disease ecology that are already doing (b)-(d), they are somehow mistaken with their methods given the rich literature THAT ALREADY EXISTS. Economists do not have special any special tools. Instead, there are number of issues related to the pandemic that they could contribute to such as the distribution of money to unemployed and furloughed workers.

        • Given economists’ reputation of being “cold”, it would be interesting to see a projection of what the economic effects of an unmitigated pandemic would have been, under a range of plausible projections of severity (ie. 30%, 50%, 70% infected; 0.3%, 0.6%, 1% IFR), vs. costs of the lockdown/social distancing measures.

          It would be nice to have a reputable analysis of that, especially for future pandemics – I don’t think much of anyone thinks we should have done lockdowns for 2009-10 H1N1. So at what level of severity do the measures make sense (benefit outweighs cost)? How much does that answer change by how you quality-weight life-years lost? Etc.

        • With 2009 H1N1 there was a vaccine and they heavily promoted it especially to high risk such as pregnant women and the elderly. I remember my wife who was pregnant going out of her way to go to a county walk up vaccine site where they took one look at her and zoomed her to the front of a special high risk line where she was given a free thimerosal free dose and sent on her way without needing to spend any time near others in line. I too got a dose relatively easily and free.

          They also mixed in H1N1 in the following year dose. So we got double vaccinated for that. Also the vaccine was highly effective in that case.

          In that environment it seems getting sick was a choice people made, when they ignored free vaccines and widespread public health messaging.

        • Except that the vaccine was not available to most of the public until after the 2nd wave had already peaked. (I caught it at college, in the 2nd wave, during September. It wasn’t widely available until Oct or Nov.) I think posting a link will get this comment in moderation, but the CDC website section on historical flu pandemics has a good timeline.

          And the elderly were not really more at risk in 2009 H1N1, unlike seasonal flu (or COVID).

          Yet colleges weren’t closed down. (Which I think was the right decision! 2009-10 was a very mild pandemic, comparatively.)

          I think the difference is more the severity, not the vaccine. (It was only about 7-8 months to a vaccine then, and even then, the second wave was already declining.)

        • “it would be interesting to see a projection of what the economic effects of an unmitigated pandemic would have been”

          I can’t imagine a credible presentation of such a thing. Every way of estimating would be so assumption dependent that it would be an assumption contest and there’s no way of knowing – regardless of how “sensible” or not the assumptions may appear to be – which if any would have been right.

        • Well, that’s why I was suggesting not one estimate, but a range of estimates based on clearly-stated assumptions.

          And the value would be not so much “second-guessing” policy makers on this pandemic, but planning for future outbreaks. If lockdowns were the smart choice here, but not in 2009, what’s the threshold? How much of the impact on the economy is due to governmental measures vs. customer fear vs. actual sickness (eg meatpacking plants closing)? That sort of thing.

        • confused said,
          “that’s why I was suggesting not one estimate, but a range of estimates based on clearly-stated assumptions.”

          +1

  4. I’m curious to see how valuable certain HOT statistical methods such as “causal mediation” or “DAGs” are perceived once we have time to reflect on this pandemic and the ostensibly relevant research that comes out of it.

  5. I think helping people stick to public health recommendations and public health communication are potentially areas where social scientists can contribute. Unacast and Apple find people are moving around more, maybe because of quarantine fatigue.

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