October 17, 2020
Math's biggest question, the end of science, UI, soccer goals, many thoughts on debt
Welcome to the Weekend Reccs. Today’s world is curious and cacophonous. This newsletter delivers an eclectic sample of some of the best things to read, watch, and ponder over your weekend. There’s a lot of economics and politics, but there is also so much more.
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Hi friends,
A long one this week — enjoy!
The Weekend Reccs
What is Math? Do mathematicians discover mathematical truths or invent them? Smithsonian Magazine wrote a short piece covering the debate. To the degree I’ve considered the question at all, I’d say I fall into the Platonist camp (math is a thing to be “discovered”). I trace this back to learning hexadecimal and binary number systems in computer science. While at first blush these alternative counting systems shine a light on the arbitrary nature of our decimal system, they actually opened my eyes up to the fact that the rules of mathematics are not dependent on the “language” in which we state them: “3C-28=14” is the same as “111100 - 101000 = 10100” is the same as 60-40=20. This settles none of the issues raised in the article, but was an important realization of the depth of mathematics. With regards to the article, I feel very strongly that the nature of mathematical predictions about the world (e.g. physics) is a strong tally in the column of the Platonists, even despite the poor accounting Smithsonian gave of this point.
The End of Science: Relatedly, I am so tired of people arguing that there are no facts. This view seems to be proliferating across the internet and intelligentsia and the political right and it is so terribly misguided and peculiar.
Somehow, especially in the social sciences, we overcorrected from a strict adherence of frequentist approaches (e.g. “My paper disproves this theory! Here is the new reigning theory.”) to relativism (e.g. “Well your paper says that X is true, but I say Y is true! It just depends on what model you use! There’s no such thing as truth!”) without stopping at a solid Bayesian perspective (e.g. “This paper grants evidence to a particular view. We should update our beliefs about the world based on the strength of the evidence presented.”).
There’s a such thing as a bad paper, but it is a different exercise to critique methodologies than to wave a hand and say that one can make a paper say whatever they wish.
Slowly it seems we’re disentangling ourselves from the snare of epistemic relativism (footnote), however I fear much more damage will be done, especially in the public discourse, before we set our collective feet solidly in the Bayesian approach.
If I may turn a little more theoretical, one of the interesting ideas that falls out of the position that there are scientific facts to learn and know, is that theoretically at some point we would reach an end of science. That is to say that there is some place off in the far temporal distance where we have created perfect models of all phenomena that are able to be modeled. Will we ever get here? Likely we will not, but it does exist and we do approach it daily. We shed old ideas as they fail to make accurate predictions, and replace them with more accurate models. At the heart of all of this, though, is the fact that we can peer into the future a little clearer and predict what will happen. To illustrate this we can take a canonical example.
You and I are on a roof. I tell you that when I drop two marbles, one light and hollow and another heavy and made of lead, they will reach the earth at the same time. I drop the marbles and they do just that. I have successfully predicted the future using science.
This is harder to see in larger problems we are still grappling with, but still exists. Although frequent readers know my feelings on improving meteorological models, it is undeniable that we are better today at forecasting the weather than we were 50 years ago. We don’t need to be 100% right to show that we are using a more superior model. Part of the improvement has been a computational feat (faster processing = more equations. Famously, a meteorologist in the early 1900s spent months solving a forecast for six hours after he began) but part of it has also been a theoretical feat (that six hour forecast was also infamously bad compared to our modern forecasts even 14 days out).
These predictive powers are what make our modern science different from Aristotle’s astronomy. Our predictive powers allow us to know that Aristotle’s ideas were wrong and that we’re closer to right than ever. Which means some day we very well could arrive at as right as possible.
For those interested in the end-of-science thesis, you can get a different argument with a much bolder vision (not just that an end exists but that we are near the end) from John Horgan.
Money printer go brrrr: A pretty staggering look at the dissaving happening by the unemployed. Perhaps more interesting though is the saving leading up to the cut in benefits. A huge congrats to Tessa Bonomo, whose research is featured here.
More of this, but British: Some rule changes (alongside improved player performance) have caused a huge jump in goalscoring this year in the English Premier League. Sports leagues, as I’ve noted, are not just about enforcing a fair assessment of who is “best” at executing within an unchanging set of rules. There is a fine balance to navigate between legitimacy (soccer needs to look and feel like what people believe “soccer” is), excitement (the outcome should not be determined before play), and discernment (better teams should win more often, on average). It seems so far that these changes haven’t been the main culprit of shaking up the game, but one of the great things about sports is that they are massive data generating machines. By the end of the season we should have a much clearer picture of what is happening.
Quick Links:
Re: last week’s discussion on processing ballots, NYT has a great graphics
A deep dive on HappyOrNot terminals (and more Goodhart’s Law from the VA)
How some medieval bridges were made (s/o Benedict Brady)
Lagniappe
This past week some friends and I stumbled upon Ted Lasso, a comedy literally based on this commercial. I finished the season within two days. It is funny and has a great cast, but more importantly it is just a good-natured show. You just feel good watching it. Similar to Kim’s Convenience (s/o Ata Baltacı), even when it is not particular clever it somehow just makes you happier.
Graph(s) of the week
[WSJ] Aggregate debt is a tricky thing to make normative statements about. Generally, expanding debt is a good thing, because it results from heightened optimism and can expand economic opportunity (think young couple getting first home, low-income student getting a degree that will earn them a higher wage, things are going well so family puts a vacation on their credit card, etc).
However it also appears debt can slow a recovery if levels are too high (I have a lot of debt + things look uncertain = I don’t spend much), and that this, paired with a constriction of available credit (the “credit crunch”) contributed to the languid recovery after the Great Recession.
Similarly, the reason(s) for the debt matters. Currently the highest 40% of income earners hold 60% of student debt. This makes most all of this debt easily serviceable (think: doctors and lawyers). On the other hand, about 15% of outstanding student debt is held by those who earned an AA or less. This debt has a much lower likelihood of being serviced and almost certainly was a bad decision to take on.
On the housing side of things in ‘06 we see a run up in housing debt, and part of that was due to new buyers in the market (good!) but part of that was due to higher loan-to-value ratios (e.g. lower down-payments) on overpriced properties (bad!) and part of that was due to people cashing out equity they had in their house via HELOCs — Home Equity Lines of Credit (unclear!).
HELOCs essentially are when you cash out the principal you’ve paid on your mortgage. If you’re using this to clean up your balance sheet (e.g. pay down credit card debt) it can be a great thing (mortgages typically have much lower APRs than credit cards). However what happened in ‘06 is that people were using it to fuel further consumption (no longer unclear, definitely bad!!). If you want to break out in a stress rash here is an NYT piece from November 2006 discussing just that. The last paragraph is painful in retrospect.
This is all a longwinded way of saying that people think debt is bad, but in aggregate debt is usually good (debt = opportunity and activity) but that’s way too simple a story when confronted with aggregated statistics like these.
[u/Feemirror] This is a graph of car colors in Poland. I want to know why green went out of style. (s/o Benedict Brady)
[WSJ] Just in case you haven’t heard enough about debt in this issue.
Again, this is much closer to how you should think about government debt. I use revenues instead of GDP because the rate at which we tax folks matters. The larger point, though is that the government is an everlasting entity. It does not need to pay down its debt, it needs to service it. The same rules apply for businesses with solid business models. They do not pay down their bonds, they issue new bonds. Ideally the US should be issuing consols given how low rates are and have been for most of this year. Lock in the low rate, cover the maintenance on it with revenues forever. Easy.
The takeaway from this graph should be that we have a lot more fiscal space to work with in low-rate environments (and we increasingly are living in a low-rate world). We additionally should be sure to take advantage of the low-rates with lots of long-dated securities, that way we don’t have to re-issue bonds at a higher rate.
To recap the month of October: Get lots of sleep, don’t buy things with added sugars, lock in low rates.
Your friend,
Harrison
Footnote: c.f. the much more reasonable cultural relativism, in which Monet’s Water Lilies may be as beautiful to me as Cuevos de las Manos was to a nearby resident 9300 years ago because conceptions of beauty are based on ontogenetic experiences and not some discoverable formulae.