The Impact of the Pandemic on US States: GDP and Deaths

Following up on my recent post on country GDP growth rates and mortality in 2020, we now have the first look at state GDP growth rates for 2020 from the BEA.

As with the national data, I would look to caution against over-interpreting this data. I’m presenting it here to give a picture of how 2020 went for states (including a few months of 2021 for morality data). One thing you will notice is that there appears to be little correlation with the raw data between GDP declines and mortality. Lots of important factors (policy, behavior, demographics, weather, luck) aren’t controlled for here. Still, I think it’s useful to see all the data in one picture, given how much many of us have been following the daily, weekly, and monthly releases.

Here is the data. Below I’ll explain more how I created this chart, especially the excess mortality data.

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On Cylindrical Revolutions

The three technological innovations new to my life in the last year with the greatest impact are:

  1. Pfizer mRNA vaccines (price = $19.50, input costs: no less than $2 Billion, probably more)
  2. Amazon Basics Foam Roller (price $18.99, input costs: $4.44 per ounce of styrofoam)
  3. Zoom teleconferencing (price: $no idea what my school pays for it, input costs: $146 Million in venture funding)

The vaccine, of which I am scheduled to receive my first dose of tomorrow, will allow me to (sort-of) return to my pre-pandemic life. The introduction and regular use of a cylinder of high-density styrofoam has given me a better functioning left leg than I’ve enjoyed in 5 years. Zoom has arguably done more to maintain my the short-term integrity of my income (i.e. it’s allowed me to teach online effectively).

That is a very oddly shaped distribution of investments in high-utility yield innovations.

Biotechnology and medicine as a high investment, high risk, big payoff innovation game is well understood. Less known was whether or not a rapid “innovation on demand” vaccine project was an achievable outcome, no matter how much money was thrown at it. Turns out it was, and we’re left with what might be the most impressive feat of willed innovation since the moon landing. High-resolution teleconferencing technology, on the other hand, is exactly the kind of product we’ve grown accustomed to modern tech firms producing– the supply of such innovative products via the private capital-entrepreneurship pipeline is almost always less in question than the eventual demand it may or may not find in the marketplace.

But what of treating your muscles like sugar cookie dough? This is neither a sophisticated new composition of materials nor, at face value, a particularly complex theory of musculature. But, to my knowledge, this is not something even professional athletes were doing 7 years ago, yet now is both the bleeding edge of physical maintenance and such common knowledge that everyone who’s strained a muscle in the last 6 months currently has one of these cylinders leaning against a wall in their home. And, while I don’t mean to oversell it, the introduction of foam rolling has massively improved the quality of my life, not just when I try to play any sort of sport, but when I walk down a flight of stairs. It’s not crazy to suggest it may buy me an extra decade of easy use of my preferred mode of transportation, and while using my natural knees at that.

Investment in innovation is an interesting thing – there appears to be significant returns to scale at the micro, meso, and macro levels. Firms flush with capital can focus teams on single problems, fill them with talent, and grant them the keys to every piece of equipment deemed to hold even the slightest possibility of aid en route to an end product. There are simply innovative outcomes on the horizon for the Pfizers of the world that will never be available to scrappy new start-ups. At the same time, we can see the network-driven returns to scale in markets, a la Silicon Valley or Hollywood, that only begin to appear when a critical mass of agents all find themselves drawn to the bubbling creative soups that appears in the diners, salons, and coffee shops of whatever place has become the place.

But there are scale returns at the most macro of macro levels as well, and that is where we get miraculous cylinders of foam, as well as wheels on suitcases and the polymerase chain reaction. People are many things. Occupiers of space. Emitters of carbon dioxide. Consumers of fried dough. Sometimes while doing all three they also come up with ideas.

Humans as idea machines lies at the core of Michael Kremer’s theory of economic growth, and it is perhaps my favorite idea within economics in the last 40 years. Simply put, more people leads to more ideas. Population growth is not just a product of innovation, it is a source of it. Every individual is a lottery ticket that we hope pays off with a world changing eureka moment that the rest of us can benefit from and build on for all time going forward. More people, more lottery tickets.

Those organic globules of cognitive betting slips coalesce into the long tail of innovation return on investment. We take the brightest minds, throwing them and piles of cash at our biggest problems, hoping that for the closest thing to a assured payoff. But it’s within the billions of people, and their billions of bad ideas that sometimes aren’t, within which we get countless miracles that change our lives for the better bit by bit, one smoothened middle-aged stride at a time.

Wait for the Lower Cost Version of Policy

I’ve written previously about initial US state compulsory schooling laws in regard to literacy and in school attendance rates. I ended with a political economy hypothesis. Here’s the logic:

  1. Legislators like lower costs, all else constant (more funding is available for other priorities).
  2. Enforcing truancy and educating an illiterate populous is costly.
  3. Therefore, state legislatures that passed compulsory attendance legislation will already have had relatively high rates of school attendance and literacy.

That’s it. Standard political economy incentives. But is it true? Well, we can’t tell what’s going on in politician heads today, much less 150 years ago. Though, we can observe evidence that might corroborate the story. In plain terms, consistent evidence for the hypothesis would be that school attendance and literacy rates were rising prior to compulsory schooling legislation. The figures below show attendance and literacy rates for children ages 10 to 18.

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Working Hard for the Money

40 hours. That’s what we think of as a typical workweek. 8 hours per day. 5 days per week. Perhaps the widespread practice of working from home during the pandemic (as well as the abnormal schedule changes for those unable to work from home), has led some to rethink the nature of the workweek. But the truth is that the workweek has always been evolving.

Take this chart, for example. It comes from Our World in Data (be sure to read their excellent related essay as well), and the historical data comes from a paper by Huberman and Minns. I’ve singled out 4 countries, but you can add others at the OWiD link.

The historical declines are dramatic. This is especially true in Sweden. The average Swedish worker labored for over 3,400 hours per year in 1870. Today, that’s down to 1,600 hours. In other words, the typical Swede works less than half as many hours as her historical counterpart. Wow! The decline for the US is not quite as dramatic, but still astonishing: a US worker today labors for only about 57% of the hours of his 1870 predecessor.

It’s tempting to focus on the differences across countries today: the average worker in the US works about 250 hours more than the average French worker. That’s 6 weeks of vacation! And as recently as 1980, the US and France were roughly equal on this measure. We might also wonder why these historical changes happened. For a very brief introduction to the research, I recommend the last section of this essay by Robert Whaples.

But still, the historical declines are dramatic, even if we in the US haven’t seen much improvement in the past generation (and those poor Swedes, working 100 hours per year more than 40 years ago).

I think another natural question to ask is whether GDP data is distorted, at least as a measure of well being, given these differences in working hours. The answer is partially. Let’s look at the data!

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Berkson’s Paradox nay Bias and Spring Break Blogging

You may be tempted to observe a negative correlation between the length of my blog posts and fraction of the previous 7 days that can be accounted for as “Spring Break”, but I submit that you may simply be omitting from the sample all of the short blog posts I could hypothetically be writing in crisp fall months.

Do read Lionel’s whole thread though. It’s good.

Thoughts on end-of-semester lectures (Part 1)

At the end of the semester, I like to make a splash with students. For example, in my intermediate microeconomics course I put together a fun lecture. We have some laughs talking about models. We talk Rolling Stones songs like “you can’t always get what you want” (budget constraints) as well as Queen songs like “I want it all” (monotonicity).

We wax philosophical with Robert Frost’s “The Road Not Taken” about opportunity cost. We reiterate that the arguments in utility functions can be a richer set of desires than food and shelter. As Adam Smith says, “Man naturally desires not only to be loved, but to be lovely.” We emphasize that our models are simplified because good models try to get to the heart of the matter.

Sometimes models are dangerous. Like the “monkey illusion” we become so distracted we miss the heart of the matter. One prime example is how Samuelson continued to update the projection about when the USSR would surpass the US economy (check this out for more info) or Easterly’s depiction of the World Bank notion that if you build it, growth will come.

We discuss the importance of models, how they organize our thinking, the dangers of being too wed to a model but also the importance of empirical testing. We use MobLab in class to test our models as I’ve written about here. But, MobLab can’t give us an empirical test of all the important questions. We have to look elsewhere, out in the world to find evidence. One of my favorite examples of this are cross-border comparisons like East and West Germany, North and South Korea, Haiti and the Dominican Republic, etc.

I remind students that incentives matter. Economic institutions influence the costs and benefits of human action. When costs and benefits change, we expect for behavior to change. Throughout the semester we learned to formalize these ideas and they are not without consequence. As this New York Times piece discusses the work of Amartya Sen,

“Nature causes floods and droughts, but most societies have found ways to get food to those afflicted most of the time. Human folly causes famine, which occurs when those ways are blocked. Amartya Sen, a Harvard economist, argued that there has never been a serious famine in a country — even an impoverished one — with a democratic government and a free press. The press acts as a warning system and the pressures of democracy dissuade rulers from famine-producing policies.”

While economics is fun, interesting, and can be light-hearted, economics can also be deadly serious. The stakes of economic illiteracy are enormous.

Next week we go on to Part 2 where I pivot from this section of the end-of-semester talk to the applications of economic ideas to the everyday life of students.

The Luck (?) of the Irish

Poor Ireland. Long oppressed by the Brits. Losing 25% of their population in the Great Famine due to both deaths and emigration. Today, there are possibly 10 times as many Irish Americans as there are residents of Ireland. There are as many Irish Canadians as there are residents of Ireland.

Poor Ireland.

And indeed, Ireland used to be literally very poor, at least in an economic sense. In 1960, their GDP per capita was about half of the United Kingdom. As recently as 1990, they were still only at about 70% of the United Kingdom and the rest of Western Europe. That’s all according to the latest Maddison database figures, which are probably as close to accurate as we can find. But after 1990, we probably shouldn’t use those figures, for reasons peculiar to Ireland.

Today? Ireland is much wealthier. But how much wealthier? It’s tricky. Ireland’s GDP is inflated significantly due to a lot of foreign investment. And possibly some tax evasion/avoidance. You see, Ireland is a tax haven. It has one of the lowest corporate tax rates in the world. That means we have to interpret the data with care, but only because it is such a great place to invest.

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Consumption as Inflation Hedge

The emerging market in digital art as nonfungible tokens is the strongest signal of expected inflation I’ve seen to date.

Let’s back up.

Digital art is being sold as nonfungible tokens (NFTs). Is this a bubble? Don’t know. Is this art? Don’t care. Is a piece of digital art as an NFT harder easier or harder to duplicate? I imagine it is easier for the artist, but they have an incentive not to issue duplicates, because doing so erodes the market value of all future digital art NFTs the producer might issue. Is a piece of digital art as NFT harder to duplicate for a forger? I imagine so. The NFT as both art and artists signature is certainly harder to duplicate than traditional media and penmanship. Which is to say we have little reason to worry about the value of a piece of art being inflated away by the artist or criminal forgers.

Now that’s interesting.

The general rule of thumb is that the more consumption value a good offers, the worse it will perform, on average, as an investment. Art, baseball cards, comic books, vinyl records, memorabilia, homes – these are all generally inferior to equities as investments. It stands to reason, though I certainly haven’t checked, that the same logic applies to hedging against inflation as well. Precious metals, while less fun, should offer a superior hedge against inflation than art, particular in relation to art by living artists, where the supply is anything but fixed.

In this regard, however, NFTs are a bit of a game changer. The supply of any given Beeple NFT is fixed forever at one, and there is as yet no reason to believe otherwise. Storage and security costs approach zero, which is something that can’t be said about a 20-foot tall metallic balloon dog. The consumption value is subjective and I’ll leave it to market auctions to suss that out. The inflationary hedge value, however – in this manner NFTs may be an game-changing innovation for prominent living artists, allowing them to capture rents from the value they create that has previously eluded them prior to shedding their mortal coil.

The bond market isn’t giving unambiguous signals of inflationary pressures yet, but signs are creeping in, and among those signs I include seemingly rabid excitement for mixing cultural-status consumption with cryptocurrency-enabled hedges against the prospect of what would be the first real wave of inflation we’ve seen in 40 years.

Which is a long winded way of saying I’m not rooting for inflation, but I’d also be happy to sell my mint-condition complete set of 1987 Fleer baseball cards if you’re looking to hedge your portfolio.

Retailer Support for Consumer to Consumer

I was not going to post about consumer-to-consumer markets again, but one of my favorite brands has just set up a re-sale site.

M.M. LaFleur is what would happen if I moved to New York City and started a fashion company along with clones of myself, knowing that my consumers are me as a corporate lawyer. I have bought a few pieces from them that I like and wear to work. Even though I don’t plan to buy from them again soon, I enjoy getting their promotional emails.

I’m not a cynic, not when it comes to M.M. LaFleur or re-using consumer goods. I like that they are giving people a chance to reduce waste by getting unwanted clothes to new users. What they are doing is also good business. M.M. LaFleur is making it easier to clear out your closet and offering to pay you in credits to buy new stuff from them.

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Rationality and economics

Lately I have been thinking a lot about rationality and economics. In my Economics of the Family and Religion course I exhort students to take the approach, “crazy is lazy”. Like archeologists that brush away the dust from artifacts we should brush away the dust of human decision-making and find the rationality. This is especially useful when it comes to understanding observed patterns in religious practice across time and space. You don’t get very far with, “people are nuts”.

Humans make decisions on purpose. They weigh the costs and benefits of an action and make the choice that seems best to them given their available opportunities. Some students have struggled to integrate this message with their other classes. At FSU we have a deep bench of experimental and behavioral economists so there are ample opportunities for students to see courses with a more psychological approach.

In one famous study, Khaneman and Tversky manipulate whether there is a positive or negative frame on a treatment for a deadly disease. In the positive frame, there was a 33 percent chance that treatment could save the 600 people with the deadly disease. In the negative frame, there was a 66 percent chance the treatment could kill the 600 people with the deadly disease. Notice that both of those probabilities result in 200 people being saved. However, people were far more favorable to the positive frame (72%) compared to the negative frame (22%).

Then there are numerous other behavioral economics findings about seemingly small things that impact the decisions people make. For example, in research about bidding behavior psychologists Dan Ariely and Drazen Prelec and economist George Loewenstein passed out sheets of paper and had students write the last two digits of their social security number (SSN) at the top before they placed a bid for each item on a sheet. Students with SSN in the top 20 percent of the distribution bid 216 to 346 percent higher for the items compared to those with SSN in the bottom 20 percent.

We could go on. In the face of those kind of results, it is no wonder that students pause to reflect about how these findings fit into the larger corpus of economics. Are they useful observations to the extent they help us improve the predictions of our models? Are they damning demonstrations that cut out the heart of the economic approach?

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