“Let whoever needs to die, die”:  China’s Abrupt COVID Reopening To Achieve Rapid Herd Immunity and Resumption of Industrial Production, at the Cost of a Million Deaths

Scott Buchanan3 Comments

I noted a month ago that President Xi and the CCP have taken credit for relatively low (reported) deaths from COVID, due to strict lockdown protocols. By “strict” we mean locking down whole cities and blockading residents in their apartment buildings for months at a stretch. However, public protests rose to an unprecedented level, and so the Chinese government has done a surprising full 180 policy change, towards almost no restrictions.

According to Dr. Ezekiel Emanuel in the Wall Street Journal, the way this policy is being carried out has the makings of a mass human tragedy:

Zero Covid was always untenable and had to be ended. But it could have been done responsibly.

Among other things, that would involve buying Pfizer and Moderna bivalent vaccines and administering them to the elderly and other high-risk people, and purchasing Paxlovid and molnupiravir to treat those who test positive. Supplies of these products are ample. Authorities could continue mask mandates to reduce transmission. And China could institute a rigorous wastewater testing program to identify potential SARS-CoV-2 variants as soon as possible – and commit to sharing the data with the world.

Due to nationalistic pride, China has spurned the purchase of effective mRNA vaccines from Pfizer and Moderna, pushing instead the less-effective in-house vaccine.

Readers may recall in the early days of COVID spread in the West, masking and social distancing were promoted, not because they would prevent everyone from ultimately becoming infected, but because these measures would “flatten the curve” (i.e. reduce the peak load on hospitals at any one time, but instead spread it out over time). China is headed into a very un-flattened infection curve; some 800 million people (10% of the world’s population) may get COVID in the next 3 months, overwhelming hospitals and leading to over a million deaths. Besides the near-term human costs, this concentration of active COVID cases is likely to lead to a slew of new, even more virulent variants which will affect the rest of the world, along with China. What should help mitigate the situation is that the newer, most virulent variants of COVID may be somewhat less fatal than the original strain.

Why is the Chinese government doing it this way? Well, the sooner the country gets through mass exposure to the virus, the sooner everyone can get back to their factories and start producing stuff again. If in the process a bunch of (mainly older) people die, well, that’s just the price of progress. Let ‘er rip…

From MSN:

[U.S.] Epidemiologist and health economist Dr Eric Feigl-Ding estimate that 60 per cent of China’s population is likely to be infected over the next 90 days. “Deaths likely in the millions—plural,” he added.

According to Eric, bodies were seen piled up in hospitals in Northeast China. “Let whoever needs to be infected infected, let whoever needs to die die. Early infections, early deaths, early peak, early resumption of production,” the epidemiologist said terming it to be summary of Chinese Communist Party’s (CCP) current goal.

But don’t expect any acknowledgement of mass death from the official Chinese media. Just as the initial COVID outbreak was denied and censored by the Chinese propaganda machine, so the current surge is being minimized. From Barrons:

On Friday, a party-run newspaper cited an official estimate of half a million daily new cases in the eastern city of Qingdao. By Saturday, the story had been amended to remove the figure, an AFP review of the article showed….

Several posts on the popular Weibo platform purporting to describe Covid-related deaths appeared to have been censored by Friday afternoon, according to a review by AFP journalists.

They included several blanked-out photos ostensibly taken at crematoriums, and a post from an account claiming to belong to the mother of a two-year-old girl who died after contracting the virus.

Posts about medicine shortages and instances of price gouging were also taken down, according to censorship monitor GreatFire.org.

And social media users have posted angry or sardonic comments in response to the perceived taboo around Covid deaths.

Many rounded on a state-linked local news outlet after it reported Wu Guanying — designer of the mascots for the 2008 Beijing Olympics — had died of a “severe cold” at the age of 67.

Perhaps we should not be surprised that the Chinese Center for Disease Control and Prevention just reported zero COVID deaths for December 25 and 26.

Average US Consumption: 1990 Vs 2021

Zachary Bartsch7 Comments

On Twitter, folks have been supporting and piling on to a guy whose bottom line was that we are able to afford much less now than we could in 1990 (I won’t link to it because he’s not a public figure). The piling on has been by economist-like people and the support has been from… others?

Regardless, the claim can be analyzed in a variety of ways. I’m more intimate with the macro statistics, so here’s one of many valid stabs at addressing the claim. I’ll be using aggregates and averages from the BEA consumer spending accounts.

Continue reading →

College Major, Marriage, and Children Update

James Bailey2 Comments

In a May post I described a paper my student my student had written on how college majors predict the likelihood of being married and having children later in life.

Since then I joined the paper as a coauthor and rewrote it to send to academic journals. I’m now revising it to resubmit to a journal after referee comments. The best referee suggestion was to move our huge tables to an appendix and replace them with figures. I just figured out how to do this in Stata using coefplot, and wanted to share some of the results:

Points represent marginal effects of coefficient estimates from Logit regressions estimating the effect of college major on marriage rates relative to non-college-graduates. All regressions control for sex, race, ethnicity, age, and state of residence. MarriedControls additionally controls for personal income, family income, employment status, and number of children. Married (blue points) includes all adults, others include only 40-49 year-olds. Lines through points represent 95% confidence intervals.
Points represent coefficient estimates from Poisson regressions estimating the effect of college major on the number of children in the household relative to non-college-graduates. All regressions control for sex, race, ethnicity, age, and state of residence. ChildrenControls additionally controls for personal income, family income, employment status, and number of children. Children (blue points) includes all adults, others include only 40-49 year-olds. Lines through points represent 95% confidence intervals.

Many details have changed since Hannah’s original version, and a lot depends on the exact specification used. But 3 big points from the original paper still stand:

  1. Almost all majors are more likely to be married than non-college-graduates
  2. The association of college education with childbearing is more mixed than its almost-uniformly-positive association with marriage
  3. College education is far from uniform; differences between some majors are larger than the average difference between college graduates and non-graduates

The Wealth of Generations: Latest Update

Jeremy Horpedahl10 Comments

I’ve covered the topic of generational wealth before, and here’s the latest data on how each generation was doing at roughly the same age. The data is updated through the 3rd quarter of 2022.

The main takeaways:

  • Millennials are roughly equal in wealth per capita to Baby Boomers and Gen X at the same age.
  • Gen X is currently much wealthier than Boomers were at the same age: about $100,000 per capita or 18% greater
  • Wealth has declined significantly in 2022, but the hasn’t affected Millennials very much since they have very little wealth in the stock market (real estate is by far their largest wealth category)

Food Price Increases Won’t Be Solved by Raising Interest Rates

Scott Buchanan1 Comment

I make a hobby of reading, and sometimes acting on, investment advice, particularly regarding high-yielding securities (many of my holdings are now yielding over 10%/year). One of the best authors on the Seeking Alpha investing site writes under the name of Colorado Wealth Management. He mainly writes on REIT (real estate investment trust) stocks, but recently opined on the wisdom of raising interest rates to combat inflation regarding some of the major components of CPI.

His article, Why High Yields Will Be Popular Again, may be behind a paywall for some readers, so I will summarize some key points. He kind of sidesteps the influence of massive federal deficit spending that injected trillions and trillions of new dollars into the economy for COVID, which I think has been the major driver for this inflation; and the reignited deficit spending which is already on the books for November and likely even huger for December of this year. However, he does make some interesting (and new to me) points regarding food prices in particular.

He sees the price 2021-2022 price increases in some major food items as being driven by supply constraints, rather then by excessive demand. Specifically eggs, coffee, and vegetable oils have been hit by exogenous factors which have constrained supply; raising interest rates will not help here, and may even hurt if higher rates make it harder for farmers to recover and re-start high production. I’ll transition to his charts and mainly his excerpted words, in italics below:

Avian Flu, Culled Hens, and the Price of Eggs

The background here is that tens of millions of chickens, including egg-laying hens, have been deliberately killed (“culled”) this year in an attempt to slow the spread of avian flu. This, of course, cuts into the egg supply and raises egg prices. We went through a similar cycle in 2015 with avian flu, where culling led to a rise in egg prices, but then prices fell naturally as a new crop of chicks grew into egg-laying hens. Similarly, the current shortage in eggs should correct itself:

Raising interest rates has never produced additional eggs. Raising interest rates and driving a recession (with larger credit spreads) only makes it more difficult for farmers to get the funding necessary to replace tens of millions of hens that were culled to slow the spread of the avian flu….If interest rates don’t work, what will? The cure for high prices is high prices. We can see how it played out with the Avian flu in 2015:

  • Is Jerome Powell going to lay even one egg? Probably not.
  • Are farmers going to focus on turning their chicks into egg-laying hens? Absolutely.

Since eggs go into several other products, it drives inflation throughout the grocery store. Even if a product doesn’t use eggs, the drop in egg production means more people eating other foods.

Drought in Brazil and the Price of Coffee

Coffee prices have been rising rapidly. Well, domestic prices have been rising rapidly. Global prices actually declined since peaking in February 2022:

So, what drove the price up? Brazil normally produces over 35% of the world’s coffee and bad weather in Brazil (not to mention the pandemic impacts) drove dramatically lower production in 2021. As the shortfall in production became evident, global prices began rising rapidly. That’s why the global [wholesale] prices were ripping higher in 2021, not 2022. However, [retail] consumers are seeing most of the impact over the last several months.

War in Ukraine and the Price of Sunflower Oil

Margarine requires vegetable oil. Soybean, palm, sunflower, and canola oil are the key ingredients. What country produces the most sunflower oil? Ukraine. This is one of several inflationary impacts of the war. You can see the impact of reduced supply in the following chart:

Government Bungling in Indonesia and the Price of Palm Oil

What happened to palm oil? How could it soar so much and then fall so hard?

The first issue is that dramatic increases in the price of fertilizer made production more expensive. … That contributed to a reduction in supply. However, Indonesia is the world’s largest exporter of palm oil. Yet exports of palm levy were subject to a huge levy. That made exporting far more expensive. Despite the levy, it was still worth producing and exporting palm oil. Then the Indonesian government decided to simply ban exports over concern about higher domestic prices. Banning exports for a country that produces 59% of the world’s total palm oil exports had a predictable impact.

If you guessed that the supply of palm oil couldn’t be sold domestically, you’d be right. The ban was lifted. However, it was only after:

“High palm oil stocks have forced mills to limit purchases of palm fruits. Farmers have complained their unsold fruits have been left to rot. There were 7.23 million tonnes of crude palm oil in storage tanks at the end of May, data from the Indonesian Palm Oil Association (GAPKI) showed on Friday.“

With palm oil prices at all time-record highs, nearly triple the level from two years prior, the supply was left to rot. Each business tried to make the best decision they could, given the ban on exports. Rather than record profits for mills and record profits for farmers, the produce was wasted. That’s supply constraints for the global market, and it destroys the local economy.

Global prices are plunging now as mills seek to unload their storage. As bad as the higher prices were for the rest of the world, no one suffered worse than the farmers whose product became worthless as a result of government failure.

Contrary to today’s popular opinion, higher interest rates won’t do anything to improve production of vegetable oil.

What happened to EconTwitter?

mdmakowsky1 Comment

EconTwitter might be dead. Might be. Maybe. Regardless of it’s status, I thought it would be interesting to think about what EconTwitter was, what happened to it, and where (if anywhere) it might be going.

https://twitter.com/ben_golub/status/1604347951530360832?s=20&t=qkyE3L6Z6ITEdwoCyKA5pA

What was/is EconTwitter?

EconTwitter was a sub-network of (mostly) economists, policy professionals, and journalists that produced an unusually tidy amount of useful content and mutual support. The culture was largely positive, even amidst the occasional spats and political aggression. Research was promoted and discussed, expertise valued (especially in applied metrics), and policy ramifications argued over. The discourse was, by both the standards of Twitter and economics, broadly civil. Perhaps most importantly, voices often marginalized in more traditional academics institution attained prominence, most notably women and faculty in less famous institutions. Wit could carry you a long way, being helpful farther still.

What happened?

Elon happened is too simple of an answer, but it’s not a trivial component. I mean, Donald Trump used to have overwhelming gravity on the site, but EconTwitter persisted nonetheless. The negative impact of Elon Musk’s attempts to curtail criticism from journalists, failed changes to verification, and general ability to troll his way into being the main character of seemingly every Twitter sub-network all had negative effects on the discourse everywhere, but it seemed to hit EconTwitter particularly hard. Why? To get into this without careening off into a 6,000 word thinkpiece, let’s revisit the three sub-groups that make up the consituents of any collective action: privleged, intermediate, and latent members.

Privleged members are those who benefit so much from the public good being collectively produced that they would independently produce the good absent contribution from any other member types. For EconTwitter, you can imagine the 15-20 people with sufficient followings or fame that they can run profitable substacks or blogs, produce leading textbooks, or write a regular column for a major publication. These are the people with the most gravity on EconTwitter, who create the most within-cluster connections. Were any of us more than two degrees from Paul Krugman?

Privleged members could probably produce a club good that re-produces a lot of the EconTwitter discourse, but it would be unlikely to ever have the same reach outside of the academic and wonk bubble. The reach of EconTwitter only happened because of intermediate members, without whom the net benefit of the collective good meaningfully declines, but standard collective action obstacles would typically undermine the public good in question. These are the people who produced the research grist for EconTwitter mill, connected it to other clusters of journalists and policy influencers outside of the economist core, and consistently stirred the conversational pot.

Finally, there were the latent members, those whose contributions were negligible or even negative to the collective good. What EconTwitter seemed to be especially good at was keeping these people safely on the periphery, rarely taking the bait from trolls and “reply-guys”. There were a handful of economists who attracted thousands of followers from outside of EconTwitter simply by trolling and generally being a jerk, making wild accusations or throwing political wildfire seemingly at random, but EconTwitter was pretty good at rendering them irrelevant at best, annoying at worst.

So what happened? If we think of EconTwitter as a collective network good, the damage done to Twitter by Elon seemed to hit the intermediate members of EconTwitter especially hard. Journalists saw their peers attacked and became both less attached to the site and, when there, less concerned with content produced by non-journalists or less directly relevant to journalism as a protected enterprise. People promoting their newest research felt less urgency to take the conversation to Twitter. Perhaps most importantly, the urbane wits that ignited and maintained our conversations simply found less joy in holding a conversation on a platform being actively debased by it’s new owner. Less importantly, but perhaps non-trivially, those net-negative latent members became more prominent in threads, choking off conversations before they could get started. EconTwitter became less fun, a fact that left privleged member contributions largely unchanged, but dipped intermediate contributions sufficiently that the broader network good suffered to the point of flirting with a line it long ago surpassed: critical mass. It was worth taking time out of your day to curate a thread explaining your research or walk a stranger through the vagaries of standard error clustering because you knew there was an audience ready to both pay it back (by further sharing your work) and pay it forward (by helping the next person with a useful question).

The conversation slowed down just enough, combined with the usual holiday lull, that EconTwitter fell to the back of our minds. Some of the most frustrated tried to move to Mastodon, taking their contributions with them, pushing EconTwitter further below the critical mass threshold while simultanesouly producing nowhere near a criticial mass of discourse at Mastodon. Every day below the critical mass is another day of EconTwitter decay, making a revival that much harder save a massive shift in the platform.

What’s next?

I see a couple possibilities.

  1. Nothing. EconTwitter heals.
  2. Nothing. EconTwitter dies.
  3. Re-creation on a private, invite-only server run by the NBER or the AEA. I think this would be an enormous failure because the goods produced would be almost entirely redundant with the club goods already produced. Re-creating an exclusive club good in the current climate would also be fraught with a liability risk that these institutions would be wise to avoid.
  4. A moderated sub-Reddit or Discord. This would be potentially extremely useful, but success would come down to the quality and commitment of what would have to be nearly full-time moderators, otherwise risking being hijacked by the troll legions on the site-that-shall-not-be-named (no, I’m not going to link to it).
  5. A collaboration of previously privleged substack writers, bloggers, and columnists to start a Discord or Mastodon Server. This would do the most to recreate the economic discourse. It would be fabulous for metrics conversations and other technical concerns. It would be good for getting feedback on working papers. But could it ever have the same reach to policy influencers and the lay public?

It’s the last one I find most intriguing. That attempt to collectively create a mini-Twitter on Mastodon. The interface is clunkier, the server less reliable, a critical mass discouragingly far in the distance. And yet.

I can’t help but think that if we built it they would come. If a converstaion amongst academics and wonks were to start and persist for a couple years, then those beloved intermediate members, journalists, wonks, lay enthusiasts, meme geniuses, and, yes, even the joyful sh*tposters might find their way over. It sucks to have to start over, and maybe EconTwitter will recover, but if there is one thing I believe about society, it is this: once you’ve achieved proof of concept on a large-scale collective good, you should never give up on it, not matter how much water it’s taken on. These things are hard, but necessary for the broader social project. We made it work before, we can make it work begin.

You can find me on Mastodon at: https://econtwitter.net/@mikemakowsky I’m going to try to start contributing to the conversation there while not entirely abandoning Twitter quite yet.

(Thanks to Paul-Goldsmith Pinkham for administering the Mastodon server!)

Empirical Papers for Undergraduate Statistics Students

Joy BuchananLeave a comment

Once undergraduates have learned the basics of interpreting regression results, we would like to introduce them to the world of economics research papers. Reading these papers will help reinforce the statistical concepts, and also we want them to get access to the insights in the literature.

Many empirical papers in economics are too long or too difficult to assign to undergraduates, especially if the course is focused more on analytics than economics specifically. Here I provide materials and instructions for teaching two published econ articles to undergraduates. Assume the students have learned the basics of interpreting a regression model (perhaps from a course textbook) but have had few opportunities to apply theses skills or engage in scientific literature.

“The Effects of Attendance on Student Learning in Principles of Economics” is only 4 pages long! Students do not need to read past page 7 of “My Reference Point, Not Yours” to answer the reading guide questions. So, these readings can be assigned outside of class, but I did some of the reading during our class period.

Handing out printed copies of at least one of the papers and my guided questions can make a good classroom activity. If students do not have experience reading tables of regression results, it can be useful to do it together in person.

The questions in the reading guide help students to identify the main variables and hypotheses. Then, students are asked to pull specific results from the tables in the papers. You can customize this list of questions by deleting lines if you do not want to discuss issues like non-linear effects or the null hypothesis.

I provide links below. First is the reading guide with about 30 short-answer questions about the two articles.

  1. Link to download the reading guide that goes with both papers, starting with the shorter one.
readingguideempiricalpapersDownload link for the reading guide questions (Word doc)

2. This is a web link to download the Effects of Attendance paper. (4 pages long and the topic is relatable to undergraduates)

3. Two web sources for “My Reference Point, Not Yours” (15 pages in total in the JEBO manuscript, but students do not need to read past page 7 for this exercise, and they can skip the Literature Review section)

JEBO link: https://www.sciencedirect.com/science/article/abs/pii/S0167268120300299

SSRN working paper link: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3434182

AI Can’t Cure a Flaccid Mind

Zachary Bartsch5 Comments

Many of my classes consist of a large writing component. I’ve designed the courses so that most students write the best paper that they’ll ever write in their life. Recently, I had reason to believe that a student was using AI or a paid service to write their paper. I couldn’t find conclusive evidence that they didn’t write it, but it ended up not mattering much in the end.

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Farewell to the First Normal Semester in 3 Years

James Bailey1 Comment

Today as I gave my last final and took my kids to a huge school party, it struck me that things are finally back to something like 2019 levels of normality.

2020 was a lost cause, of course. I had high hopes for 2021 that vaccines would immediately get us back to normal. They did get my school back to fully in-person by Fall 2021, but not really back to normal, partly thanks to the variants. My students were out sick more than normal, and I was out watching my sick kids more than normal, as every cold meant they would be home until the school was sure it wasn’t Covid. Toward the end of the Spring 2022 semester worries were subsiding, and my state was pretty much fully re-opened, but things still weren’t really back to normal. Student attendance and effort were still way below normal, partly from the lingering effects of Covid, and partly from celebrating its end- partying to make up for lost time (and cheering on a great basketball team).

Fall 2022 finally felt like a basically normal semester. I still see the occasional mask, still hear from the occasional student out with Covid, and still have one kid missing 2 school days with every cough (policies stricter than 2019, but much relaxed from the days when both kids were at schools that could have them miss 5+ days with every non-Covid cough). Overall though student attendance and effort are back to what seem like normal levels. Up to Spring 22 I’d have students just disappear for a few weeks, not in class, not answering e-mails about why they weren’t showing up or completing work, needing lots of help to get on track once they finally reappeared. This Fall that didn’t happen; in my Senior Capstone everyone turned in a quality paper basically on-time and without me having to chase anyone down for it. Also, everyone just seemed happier now that their stress levels are back down to the baseline for college students.

This semester was nothing special- and that was beautiful.