gwern, I find your position against bubbles to be incredibly unlikely, and that is post my studying economics and finance informally for the last 3 decades. But you are gwern who my post (as opposed to my prior) warns me against dismissing.
If you can suggest any reading that you found particularly compelling against the usual interpretation of market manias, I'd love to take a look. I will google Famous First Bubbles, haven't done that yet.
As far as real estate bubble, first I would point at Mortgage Backed Securities (MBS) rather than the direct real estate market. These were rated AAA, insured for less than a penny on the dollar, and purchased by ancient and venerable banks and others. And then in 2007/2008 they almost uniformly as a class blew up. Returned pennies on the dollar. Caused multiple firms and banks around the world to go bankrupt. Resulted in governments around the world pumping trillions of dollars of liquidity into the system in a process analagous to foaming the runway when a plane crashes. And the essence of it predicted publicly by many of the smartest minds in finance and investing. I am thinking of Buffett and Munger referring to MBS derivatives as Weapons of Financial Mass Destruction BEFORE the blowup, and I had in print in a book printed before the destruction a speecy by Munger talking about how there was going to be a tremendously horrible event because of derivatives "in the next 5 to 10 years" in a speech he gave in I think 2002. While MBS were hot, they were so in demand that brokers such as Salomon would create "synthetic" MBS, which were essentially just well documented bets that would pay off exactly as an MBS would pay off over their life, but were made up because there was still demand for MBS even after the last homeless person with a pulse in the US had been given a 100% non-doc mortgage to buy a house which would not be sellable for even 80% of what was financed two years later.
Is even this not a bubble? Not the market chasing a dream instead of a business proposition and trying to fly up to heaven with the dream and failing?
How high are the stock prices of Amazon, Google, and Apple now? Oh look, Bitcoin is at $160, how did that happen when everyone knew it was a bubble which popped?
The NASDAQ composite peaked in early 2000 at over 4000. More than 13 years later it is STILL not back up to that level. Perhaps at least some of the investors in AMZN and AAPL in 1999 were not caught in a bubble, but what about the bulk of the money, of which about 70% of the value evaporated in less than 3 years, and which on the whole has not crept back up to even yet? And the NASDAQ composite is not the only place to find this result, CSCO, INTC, and QCOM were all bid up much higher in 2000 than they are selling for even now. Proof that they were overvalued in 2000, no? By a factor of a few? I'd like to know the error I make when I think of this as a bubble, as momentum overshooting value and rationality by a factor of a few?
Mortgage Backed Securities (MBS) ... returned pennies on the dollar.
No, the AAA rates MBS did very well; 90% suffered no loses. It was the ABS CDOs (Asset Backed Security Colateralised Debt Obligations) that did badly.
In an unrelated thread, one thing led to another and we got onto the subject of overpopulation and carrying capacity. I think this topic needs a post of its own.
TLDR mathy version:
let f(m,t) be the population that can be supported using the fraction of Earth's theoretical resource limit m we can exploit at technology level t
let t = k(x) be the technology level at year x
let p(x) be population at year x
What conditions must constant m and functions f(m,k(x)), k(x), and p(x) satisfy in order to insure that p(x) - f(m,t) > 0 for all x > today()? What empirical data are relevant to estimating the probability that these conditions are all satisfied?
Long version:
Here I would like to explore the evidence for and against the possibility that the following assertions are true:
Please note: I'm not proposing that the above assertions must be true, only that they have a high enough probability of being correct that they should be taken as seriously as, for example, grey goo:
Predictions about the dangers of nanotech made in the 1980's shown no signs of coming true. Yet, there is no known logical or physical reason why they can't come true, so we don't ignore it. We calibrate how much effort should be put into mitigating the risks of nanotechnology by asking what observations should make us update the likelihood we assign to a grey-goo scenario. We approach mitigation strategies from an engineering mindset rather than a political one.
Shouldn't we hold ourselves to the same standard when discussing population growth and overshoot? Substitute in some other existential risks you take seriously. Which of them have an expectation2 of occuring before a Malthusian Crunch? Which of them have an expectation of occuring after?
Footnotes:
1: By carrying capacity, I mean finite resources such as easily extractable ores, water, air, EM spectrum, and land area. Certain very slowly replenishing resources such as fossil fuels and biodiversity also behave like finite resources on a human timescale. I also include non-finite resources that expand or replenish at a finite rate such as useful plants and animals, potable water, arable land, and breathable air. Technology expands carrying capacity by allowing us to exploit all resource more efficiently (paperless offices, telecommuting, fuel efficiency), open up reserves that were previously not economically feasible to exploit (shale oil, methane clathrates, high-rise buildings, seasteading), and accelerate the renewal of non-finite resources (agriculture, land reclamation projects, toxic waste remediation, desalinization plants).
2: This is a hard question. I'm not asking which catastrophe is the mostly likely to happen ever while holding everything else constant (the possible ones will be tied for 1 and the impossible ones will be tied for 0). I'm asking you to mentally (or physically) draw a set of survival curves, one for each catastrophe, with the x-axis representing time and the y-axis representing fraction of Everett branches where that catastrophe has not yet occured. Now, which curves are the upper bound on the curve representing Malthusian Crunch, and which curves are the lower bound? This is how, in my opinioon (as an aging researcher and biostatistician for whatever that's worth) you think about hazard functions, including those for existential hazards. Keep in mind that some hazard functions change over time because they are conditioned on other events or because they are cyclic in nature. This means that the thing most likely to wipe us out in the next 50 years is not necessarily the same as the thing most likely to wipe us out in the 50 years after that. I don't have a formal answer for how to transform that into optimal allocation of resources between mitigation efforts but that would be the next step.