where I assume away any compensation for the initial dip...Garber's data are also consistent with an initial rebound.
No, you don't. You bury it in the 'sank gradually' part:
But Garber would likely have seen the same thing even if there had been an abrupt bubble pop. Suppose a tulip bulb's price peaked at 1000 guilders, crashed to 200 guilders within a week, then sank gradually to 100 guilders over the next five years.
You can get an abrupt pop inside an normal-looking beginning/end comparison if something compensates for the pop, like another rise (unlikely) or prices then falling slower than they normally would ('gradually'). The ground lost in the pop is then made up later.
Plague? Now that's something I don't think he mentions in the papers.
His book's capsule summary of that bit goes
The speculation in common bulbs was a phenomenon lasting one month in the dreary Dutch winter of 1637. A drinking phenomenon held in the taverns, it occurred in the midst of a massive outbreak of bubonic plague and had no real consequence.
It's the topic of chapter 5, "The Bubonic Plague".
(Must...resist...urge to borrow...yet another...book.)
(It's on Libgen, and isn't a very long book.)
No, you don't. You bury it in the 'sank gradually' part: [...] You can get an abrupt pop inside an normal-looking beginning/end comparison if something compensates for the pop, like another rise (unlikely) or prices then falling slower than they normally would ('gradually'). The ground lost in the pop is then made up later.
Ohh, I see what you're getting at. I'd interpreted "compensation" more narrowly as something halting or outright reversing the fall in prices, not merely decelerating it.
Yeah, my scenario implies an unusually slow price drop...
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.