Expert Forecasts

IEA-wrong-fcast_panelsBCE-wrong-forecasts

ECB inflation forecasts from 2012 to 2020 mostly wrong in the same direction, in 2020 they changed their direction, maybe they are a reverse benchmark 🙂

IEA sistematically undervalued renewables potential in their yearly forecasts

beware the experts, don’t believe what they say, there’s always room for things to go the way you like best

from growth to risk

1960 the year singularity was cancelled on SSC. History developed mainly in Malthusian trap, with industrialization we got out of the trap and started growing product percapita in an exponential growth. That stopped in the 60’s

German sociologist Beck sensed that capitalism was getting into its second stage, from growth to risk priority. Adam Tooze on Foreign Policy

see also Parrow with normal accidents

Noah Smith on “What happened in 1971 along the lines of singulraty cancelled in 1960. https://twitter.com/Noahpinion/status/1306264582046937088

Assuming that the secular trend was not negated, we are simply in the through of the secular cycles, how long would be this cycle and how high would the upswing carry us ? Check also Turchin and Kondratiev for longer cycles

Turchin Cliodynamics “Cliodynamics is entirely different. Its roots are in nonlinear dynamical systems. We don’t go out looking for cycles; but we don’t shy away from them when there is robust evidence for them. In Structural-Demographic Theory, in particular, oscillations arise because of nonlinear feedbacks between different interacting components of the social system (state-level society).”

with a nice chart:

fuck wordpress and the blocks editor, BTW, when a platform interface becomes baroque for some dynamics clear only to the programmers it’s probabluy time to move, it used to be easy to add an image, no longer

curves, innovation curves of all sorts

Gartner Hype cycle

jazzed up version of traditional Everett Rogers’ diffusion of innovations

this was the trigger https://twitter.com/NickPinkston/status/1278353201905823745

and this is Carlota Perez curve which puts together technology and finance in a play of coupling and decoupling in the installation and deployment phases

carlota perez cycle

I guess it owes something to Kondratiev, that originally was a theory of cycles in commodity prices over long periods (like 60-80 years)

and I wonder the relationships with Urchin Secular cycles more of 2 to 3 centuries due to demographic factors https://www.lesswrong.com/posts/3bPH2az479gzxDMbf/book-review-ages-of-discord

Screenshot 2020-07-16 at 14.48.10

 

invention and implementation

are different, it’s like having an idea and selling it

Greeks had a steam engine, more a steam turbine, aelopyle. The stem engine arrived in 18th century England

Actually it wasn’t only the steam to do the work, the steam created the void and the air did the work in the Newcomen engine. And it was at some point economical only because coal mines flooded and so there was a lot of coal with non shipping costs.

The sumerian had the wheel, but only for toys. Maybe the economnics ewasn’t right. The middle east forgot the wheel in the middle age because four camels could be run by a man instead of a single chariot. The economics.

so, things look at us waiting to be discovered, we had gotten to the moon and still had not put wheels to luggages, implementation can be harder than invention

distilled of a chapter in Antifragile by Taleb and Anton Howes newsletter “Age of Invention: The Weight of Air” of July 3, 2020

Cheap inputs and tech epochs

from Carlota Perez “Technological Revolutions and Financial Capital”Screenshot 2020-06-17 at 11.23.56

4th epoch is cheap oil, 5th is cheap bits. 6th?

If it has to be Green then it has to be renewables energies, cheap renewables?

cheap and abundant, the two things are tied in learning curves. Ramez Naam is working the Pareto curves himself.

Solar Future in Insanely Cheap

But a planet on renewables would require a lot of solar and wind, for example this report on reaching 90% renewables in the US calls for doubling new installation every year in the 20s and trebling in the thirtiesScreenshot 2020-06-17 at 11.55.17

Report 2035 di Goldman Sachs and U. Berkeley.

Forecasting with fat tailed distro

Random variables in the power law class with tail exponent α ≤ 1 are, simply, not forecastable. They do not obey the LLN. But we can still understand their properties.”

“If one claims fitness or nonfitness of a forecasting ability based on a single observation = 1, she or he would be deemed to be making an unscientific claim. For fat tailed variables that “= 1″ error can be made with n = 106. In the case of pandemics, n = ∞ is still anecdotal. (..) It takes 1014 observations for a “Pareto 80/20” (the most commonly referred to probability distribution, that is withα ≈ 1.13) for the average thus obtained to emulate the significance of a Gaussian with only 30 observations.”

https://forecasters.org/blog/2020/06/14/on-single-point-forecasts-for-fat-tailed-variables/

Taleb justifying the precautionary principle on statistcis ground, in a challenge with Ioannidis who called for reopening the economy based on poor data

https://forecasters.org/blog/2020/06/14/covid-19-ioannidis-vs-taleb/

 

Covid Innovation: a lot, not so great

Covid therapies are entering the pipeline at a rate 15 to 80 times faster than any previous epidemic with over 4 new therapies entering the commercial pipeline every single day

The relative share of “short term” solutions – non-vaccines and repurposed drugs – is unusually high. 23 percent of Covid therapies are vaccines, versus at least half for the previous three recent less severe epidemics. Over 60 percent of Covid therapies are repurposed drugs, versus no more than a quarter of those for Ebola, Zika, or H1N1.

the rate at which new vaccines enter the pipeline is essentially the same in February and April!

The increased entry driven by huge payoffs to any successful Covid therapies causes entrants to inefficiently race toward lower-value therapies. If enough small firms begin to race in this way, even the large firms that otherwise would have worked on vaccines will give up. And note that this pattern appears empirically: more severe epidemic leads to more entry by small firms, more work on short-term projects