R.I.P. Borders

An analytics textbook is usually full of success stories (i.e. XYZ Corp. invested in a data warehouse and everything got better). I decided that my students needed to hear a downer for balance. What better example than Borders?

Borders was a fixture of suburban New Jersey in the 90’s. You could browse books or media and get coffee there. When I asked undergraduates in 2018 if they remember Borders, I learned how far south Borders had expanded (to Nashville, but not to Birmingham).

Never fear. All of my students knew the Kanye West song “All of the Lights”. The lyrics are:

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Blood Clots for You and Me

On April 13, 2021, CDC and FDA recommended a pause in the use of Johnson & Johnson’s Janssen COVID-19 Vaccine. When I first heard that the FDA was pausing the J&J vaccine because of less than 10 blood clots out of millions of patients, I thought I’d really get to the bottom of blood clots and blog about it. Other people (some of them are the kind of doctor that helps people) have already done a pretty good job in the past few days.

First, it is a tragedy that the vaccine is not being give to every male over 50 who wants it. Doing so would free up many thousands of other types of vaccines for young women.

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The Tall and Short of Student Experience

Every semester in my intro STAT course I have my students create a variety of survey questions. After I combine their questions into a single survey, they collect responses from the student body at Ave Maria University. Most of the questions are vanilla. Other are not. They typically get in excess of 100 responses from the ~1,100 person student body.

While exploring the data, I found a really beautiful example for the week that we spend on multiple regression and dummy variables.  The survey results illustrate a clear, linear association between student height (inches) and their student experience at AMU (scored 1-10).

So strange! Why might this be? Except for that solitary 7 ft+ student on the basketball team, how in the world might height matter for student experience?

As it turns out a separate relationship holds the key.

Confirmed with a simple unpaired t-test (unequal variances), women rank their student experience much more highly. For this, students have multiple explanations at the ready.

  • Our school is in a rural location and women are more socially satisfied.
  • Men are less happy generally.
  • Men are less studious or have lower grades.
  • Men get less sleep and stay up later

The list goes on and I don’t know what the reasoning is or which ones actually play a role. But what I do know, is how to make fun scatterplots in Stata. As it turns out, if you control for sex, height loses all of its effects on student experience. Men are taller on average and they aren’t happy students relative to women (apparently). We can see in the figure below that all of the action in the two fitted lines occurs in the intercept. The slopes are practically flat for both men and women. In other words, height neither adds nor subtracts from a student’s experience rating.

What’s going on is that neither men’s nor women’s experience is affected by being taller. But, what’s actually going on here – you know – statistically? The simple version is that the bar chart above dominates the scatter plot. If we subtract the mean male experience score from the male values and do the same for the females, then we’re left with what is practically white-noise. How do all those other students of a different height experience the world? Well, as students, not so differently from you.

The Value of Life, Again

Bryan Caplan argues that the life of a 10-year-old is worth 100-1,000 times that of an 80-year-old. But he suggests the modal answer people would give is that the two lives are equally valued.

I’m not sure if he is right about what the modal answer would be that they are exactly equal (though see below for an attempt to answer this question). Surprisingly, though, roughly equally valuing all lives is actually the answer that a normal economic calculation, willingness-to-pay for risk reduction, would give you! Or at least roughly. I haven’t seen an estimate for a 10-year-old, but estimates of the Value of a Statistical Life for 20-year-old is roughly equal to an 80-year-old. I’ve written about this before, and here’s a summary of a working paper by Aldy and Smyth that I am drawing on. Middle age lives are worth more, using this method, though perhaps just 2-3 times more.

Caplan doesn’t directly connect his hypothetical to the COVID pandemic, but in the comments Don Boudreaux does make that connection and says that “surely the correct level of precaution to take against a disease that kills X number of old people is lower [than a disease that kills the same number of young people].” I find this a very interesting statement because Don Boudreaux, and many others, have been against just about any precaution (other than asking the elderly to isolate) in the current pandemic. Would he and others support more caution if they believed the VSL estimate to be true?

So who is right? Caplan’s intuition? Or the modeled VSL calculations? For surely these are miles apart, and they can not both be correct.

As an economist, I have a strong preference in favor of willingness-to-pay over our intuitions. Indeed, Caplan himself as defended the VSL approach quite forcefully!

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Facebook Disrupts a Phishing Spy Campaign

Written by Braden Murray, a Samford business school student:

Facebook is a social media platform, with more than one billion users (GCFGlobal.org). Facebook is also a data warehouse, and an analytics powerhouse. The company uses its technology to track user activity and obtain information on preferences. Information is used to update its newsfeed algorithm or sell advertising. Because Facebook monitors users, analysts know how many accounts are inactive or have suspicious activity. The WSJ reports a phishing attempt recently caught by Facebook.

Facebook has reported a security issue affecting the Uyghurs population. The social media company has just taken down multiple accounts connected to China being used online to “spy on journalists and dissidents in the overseas Uyghur Muslim community” (Horwitz). Facebook did not blame the Chinese government. It pinned the hacking on a network that used infected apps created by Chinese companies. Facebook also said the hacking activity happened outside of its social media platform, although the hackers did use Facebook accounts pretending to be members of the Uyghur community. They would send their victims links to the infected apps over Facebook, which is known as social media phishing. However, the only way the malware would download and corrupt the device is if it met the criteria of using Uyghur-language settings. 

Phishing is a crime committed on the internet that causes malware to corrupt a computer system and personal information to be stolen. It is usually conducted through email, text, or over the phone in some cases. A link is sent to the victim from a random source that seems like it could be reliable. If the link is clicked, the hack occurs and corrupts their technological device. The results of phishing include identity theft, financial fraud, and malware. The FBI said phishing was the most popular cybercrime of 2020 and doubled in cases from 114,702 to 241,324 (Tessian). Phishing is a very common occurrence that people need to be aware of in order to avoid consequences. 

Mike Dvilyanski is a Facebook employee who handles cyber threat intelligence. He said he “saw attackers injecting malicious code into the website pages” and how it would “then infect them with specific malware if they met criteria that attackers set up.” After noticing the hacking efforts, Dvilyanski and other coworkers would shut down the accounts. The hacker group was identified by a joint effort of several companies working along with Facebook. The Chinese hacker group called Earth Empuse or Evil Eye posed as journalists in the Uyghur community and other nearby places.

The effort was to shut down as many fraudulent accounts as possible to disrupt the network and decrease the number of successful phishing attacks. This is just one example of the security issues that Facebook encounters and combats using data analytics.

Note by Joy Buchanan: I encounter fraud and phishing attempts regularly on the internet, and usually it doesn’t faze me. Twice in the past year, I have gotten an email to my work address from someone pretending to be the dean of my school. I wasn’t tricked successfully either time, but I found those attacks to be particularly creepy.

The Problem is the Science

The University has been the engine of basic science in the US and abroad for a long time. Any hand-wringing in recent years over its imminent obsolescence was borne of advances in remote learning and new found capacities to exponentially scale single instructors to reach tens, if not hundreds, of thousands of students across the globe. How, in this brave-ish new world, would matriculant tuition accruing to a handful of instructional specialists/celebrities continue to subsidize the scientific mission?

If the arrival of YouTube and Khan Academy gave credence to the academic apocalypse theory, then the coronavirus pandemic and the global adoption of Zoom instruction would surely make a reality of it. I will admit, for the first time in my career, I’m seeing the cracks in the edifice of the academy. And, yes, it was the pandemic that made them more prominent to me.

But its not on the educational side of our dual mission. It’s the science.

Dr. Katalin Kariko is very likely to win a Nobel prize for her immense contributions to our understanding of messenger RNA (mRNA) and how it can be manipulated to create an entirely new class of vaccines that, it is not hyperbole to say, stand to offer a global shift in health. The prospect is there for not just an HIV vaccine, or a broad-spectrum influenza vaccine, or a malaria vaccine, but the broad mitigation of viruses as a burden on humanity.

Dr. Kariko has been pursuing her scientific mission with a single-mindedness that jumps off the page in everything that has been written about her. What also jumps off the page, at least to those of use who have been trying make a career in academic research, is the university system that has worked diligently for decades to push Dr. Kariko, and her scientific mission, out of the academy. At every stage of the hiring, retention, and grant application process, Dr. Kariko’s research has been bludgeoned with not so much criticism or doubt, but what seems more like horrifying indifference. Grant reviewers saw little value, her colleagues noted that she lacked finesse in writing grant applications, and the academic institutions that employed her saw little value in employing someone, even for less than $60k a year in salary, that was unable to consistently bring in large grants (sidenote: her husband often estimated her effective wage to be roughly a dollar an hour: from the university’s point of view, it wasn’t the expense she represented on the balance sheet, it was the opportunity cost of the grants she wasn’t winning that someone else in her slot would).

This is a problem.

To be clear, this indifference is far more damning than any sort of broad disagreement would have been. The nature of science is such that most advances are incremental, but every now and then there are the rare revolutionary upheavals, where something we thought we absolutely knew for sure turns out to be completely wrong. That scientific mavericks that push such theories, most of which are completely wrong, meet resistance is natural (and probably optimal). But indifference is a problem, because indifference does more to reveal the underlying incentives propelling researchers. Universities were indifferent to her research because it wasn’t generating grant money, and that is the job she was hired to do.

Patents are great. Prestigious awards are welcome. Published papers are not entirely a waste of your time. But make no mistake, if you don’t successfully apply for grants, your days in academic science are numbered. I spent three years as an oddly appointed economist in arguably the greatest medical school of the last decade. I got to hang around brilliant physicians who spent a lot of their time every week actually (not figuratively or indirectly) saving lives. I also witnessed dedicated researchers break down into tears upon receiving the news that their grant application had been denied, which meant their contract with the university would not be renewed and their research career effectively terminated. I saw how little grant application aptitude correlated with talent or passion. I saw people thrive in system while others failed, with little in the way of scientific aptitude to distinguish them.

The most practical advice I was privy to was this: work in someone’s lab, pursue your project in parallel with their resources. Once you have an advance that would be worthy of a grant application, write up the application for a project you‘ve already completed. List your previous PI as a collaborator, promise exactly the results you already have, describe your budget, schedule, and proposed outputs in shocking detail, and then radically oversell the importance of the discovery. Once you win the grant, use that money to pursue your next project while writing up the outcome of your previous one. Once you have results, apply for yet another retrospective funding grant, and continue to daisy chain that until you win a massive grant, a coveted NIH R-1 perhaps, within which you can bundle a series of projects, hiring as many post-docs and early researchers as you can. You will then manage this team who will execute your research while hopefully starting their own retrospective grant application daisy chains. Is this a common strategy? I don’t know – it seems odd that the dates of human subjects testing could be obscured. But the point was made to me – this isn’t about science, this is a career life-or-death game where only the 20% of applicants are funded.

To be honest, I don’t care that people are gaming funding institutions. And, to be clear, “playing the game” is part of any career, no matter how idealistic you want to be. Academic research science is in deep, deep trouble, however, if grant application gamesmanship dominates scientific ingenuity in the talent acquisition and retention strategies of major universities. It means we’re no longer scientists, we’re rent-seekers. We’re the person in the village best at memorizing Mao’s Little Red Book: smart, talented, but in the end wasted. Or, much worse, we’re just poseurs.

Piecing together what I’ve read in articles and her Wikipedia entry, after Penn demoted her to adjunct status, Dr. Kakri found a home at BioNTech in 2013, where they and other biotech firms saw tremendous value in her work, yada yada yada, her research with Draw Weissman saved millions of lives going forward and maybe just the whole damn world.

Two takeaways:

  1. If Penn, after demoting her to being an adjunct, tries to claim her and her work as their own we riot.
  2. What is the marginal value of university research if all we’re producing is grant applications?

Part of the blame, of course, has to be placed at the door of the NIH and NSF grant application review process. But how much longer are they going to matter either?

  1. 2021 NSF Budget: $8.5 Billion
  2. 2021 NIH Budget: $43 Billion
  3. Tesla Market Cap: $650 Billion
  4. Elon Musk net worth: $167 Billion

The whole point of the NSF, NIH, and the academic research project is the production of the public good that is basic science. Absent private profit incentives, they should be able to pursue the big picture project that are too broad in application for private companies and the high risk-high reward projects that are or venture too risky even for venture capital.

The advantages of government agencies, however, are limited if they are overwhelmingly surpassed in scale by private market science. Even if 99% of firms can’t overcome the public goods problem, the 1% (ironically within public economics what would be referred to as “privileged groups”) of firms that stand to profit from advancing basic science have the scale to execute such ambitions. More importantly, however, they may also have better incentives. Yes, they are greedily trying to make a profit off of their innovations, but at least the innovation remains their goal.

I’m not worried about the value of university professors as educators. It turns out that education doesn’t scale as well as we thought. That there is tremendous value to be in a room together when you’re trying to pass on explicit, complex, and tacit knowledge. Nor am I worried in the slightest about capital-S Science. There is a bright future for any and every institution producing science, even the most basic, broadest science that no private company or patent strategy could ever exclude others from benefiting from. But, I’m afraid, there is no future for the production of grant applications or the institutions that pursue them at the expense of brilliant minds trying to solve our most important puzzles.

Joy’s Cartoon is in a French Textbook

This is my day in the sun. A decade ago, I started ecoNomNomNomics.com. Back then, I knew that my dream job was “economics professor”, but I was years away and also thousands of miles away from where I am now. I have barely updated the site since 2011, but every now and then new people find it. My hope has always been that it would be both helpful and happy.

A French publisher reached out to me and asked for permission to use one of my cartoons in their workbooks that will reach actual French students. I was delighted to say yes.

Allons-y! With their permission, I reproduce the page that has my picture:

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Growing a Financial Advisory Practice Using Data

Lance Rybka is a current finance major at Samford University. He hopes to start a business that uses data analytics to help fee-based financial advisers grow firms.

According to data from the most recent Tiburon Summit, small fee-based financial advisers are increasingly facing pricing pressures that place their businesses at risk. Since 2009 the average fees charged by these advisors have decreased from 1.2% of AUM to .96%,, and 86% of Tiburon CEOs believe that these fees will continue to decrease over the next five years. While robo-advisers and data analytics are partially responsible for this restrictive pricing trend, many traditionalists do not realize the potential they have to grow their practice by embracing this technology instead of resisting it.

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Teaching Economics with COVID

In many of my blog posts I address either issues related to COVID or teaching economics. In this post, I want to combine the two. One thing economists of a certain age struggle to do is find examples to illustrate economic concepts which will actually connect with 18-22 year olds. The silver lining of the pandemic is that we now have an example that everyone is familiar with, and can be used to illustrate a host of economic concepts.

A great new book by Ryan Bourne, Economics in One Virus, really pushes this idea to the limit. He uses examples related to COVID to explain almost every single concept you would cover in a typical introductory economics course: cost-benefit analysis, thinking on the margin, the role of prices, market incentives, political incentives, externalities, moral hazard, public choice issues, and more.

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Thank you Tyler and Alex

Tyler Cowen and Alex Tabarrok have done really good work on saving America and beyond from Covid and from bad Covid takes. It’s worth saying this in more places.

Here is Alex on how great Tyler’s work has been on advancing disease-fighting science. Here is Ezra Klein (NYT) on how Alex’s advocacy.

Recall how this all started, as per the Econtalk podcast record in March 2020:

Tyler Cowen: I have been hunkered down at home every day, with some quick trips outside, typically to use the printer at work or maybe to refresh some grocery supplies as quickly as I can. But, , I wake up; I get onto my sofa; I get into information-absorption mode, and just let it rip until it’s time to go to bed at night. And, I’ve been blogging and writing about this the whole time, and really not doing very much else. Although I am spending more time cooking.

So, what I see as the data come in is we ought to have greater concern as to the possible risks here, for this being a very large scale negative event.

… And in fact, I don’t think I’ve ever been busier in my entire life. Reading materials, writing, passing along advice, just processing information. Every day feels like an enormous rush of things I have to do, even though in the sense of my physical surroundings it’s quite static.

No one had all the right answers in the Spring of 2002. How many people devoted themselves to figuring it out? Who was reading dense medical research papers instead of watching extra Netflix, after being forced into semi-quarantine? There have been many heroes of the pandemic (see data heroes). The Marginal Revolution blogging team is certainly among them.

I have a virtual heap of notes on pieces I would like to write. I made notes a few years ago for an essay with the working title “Tyler Cowen as pro life economist” (which has nothing to do with abortion, by the way). I was going to construct an original argument and pull together disparate facts. Someday, maybe I will write it, but now I’ll be leading with the example of the pandemic response. It’s so obviously “a matter of life and death”. If they caused the vaccine to arrive a month sooner, then we can count the lives saved.

I didn’t plan to phrase it this way, in my original essay, but everything is life and death to economists. Occupational licensing is life and death. Deflation is life and death, because if economic output is lost due to deflation that will be someone’s prescription payment and someone else’s ability to live a full life. Economic growth is life and death. Tyler is one of the few people pointing out that it’s not only today’s low-income people but also future generations that will have longer fuller lives if economic growth is higher.