citizen investor

Homoploutia is the situation where the same people (homo) are rich (ploutia) in terms of both labor and capital income. We measure it by the share of top decile capital-income earners who are also in the top decile of labor income.

First finding: Homoploutia has increased considerably since 1950, from about 10% to 30%, most notably in the past 35 years.

Second finding: The rising labor income inequality during the 1970s and 1980s fueled the increase in homoploutia. Either through higher saving leading to higher capital income, or higher incentives to participate in the labor force for the capital-income rich.

Third finding: in turn, rising homoploutia acted to increase (total) income inequality, accounting to 2 percentage points (or 20%) of the rising top 10% income share from 1986 to 2020. It may have played a bigger role in increasing US inequality than the capital share.

Interesting 3d here https://twitter.com/bermanjoe/status/1340008088892547072

related, K shaped recovery in Coronatimes, where educated people with stock holdings are doing well, while no-degree workers in hospitality type works with no savings take the brunt of it all

also related, the growing importance of startups, unicorns etc which give options at early stages making both well paid and capital rich employes

The idea would be to teach pupils about savings, investments, taking and managing risks, using all the tools to buy and sell financial isntruments which are readily available today. The citizen investor, teaching kids to a better economic and financial position in the world.

Related, in 1948 this movie was shown to high school freshmen https://twitter.com/BrianRoemmele/status/1340758766896041984

This movie was shown to seniors about judging and discernment https://twitter.com/BrianRoemmele/status/1340738021058990080

shaky foundation of economics

still on the issue of the cancelled singularity

a dinner chat between a physicist and an economist on the physical limits to infinite growth , the infinite growth postulated by economists in their models.

I got there from this tweet on ergodicity economics https://twitter.com/DrCirillo/status/1201782869712146432

and gave another read to Ole Peter’s Nature paper which sinks deeper in my reasoning on economics.

It all started because some economist on Facebook complained that some other economist had opposing views, but this is not the point, he started with an “in science, no economic theory …” science and economics so close in one sentence got me thinking about epistemics

a comprehensive article on “is economics a science?” lots of quotes so probably it isn’t you would not need so many instead

EDIT: I found today Noah Smith arguing that economic policy today seems limited to “Give poeple money” without any attempt to ground the directive in theory, unlike what happened in 2008 crisis where economists resorted to theory and in course they wrecked the economy even more. So the state of economics, macroeconomics I mean, is dismal https://noahpinion.substack.com/p/the-new-macro-give-people-money

UPDATE june2021:I had not realized that Noah Smith had a rebuttal of the physicts and economist dialogue https://noahpinion.substack.com/p/murphys-law-or-follies-of-a-finite

efficient markets, or not

on askblog I read of Fama efficient market hypothesis and monetary policy https://www.arnoldkling.com/blog/finance-theory-and-the-fed/

he says that “Actually, the central banks don’t do anything real. They are issuing one form of debt to buy another form of debt. If you are an old Modigliani–Miller person the way I am, you think that’s a neutral activity: You’re issuing short-term debt to buy long-term debt or vice-versa. That’s not something that should have any real effects

I should study the Efficient Market hing. It also prompted me to punt on reading list Mandelbrot The (Mis)Behavior of Markets https://www.goodreads.com/book/show/665134.The_Mis_Behavior_of_Markets

things to grow

of models

yesterday I have to give some advise on Covid and while I was talking I said to myself, “you re not anexpert why would you do that” and I answered to myself that “I ve read thinks from good sources, I have checked facts, I have a model of the pandemia in my mind and I believe it is true”

So I felt the urge to reread something I had read sometimes ago in Douglas Hoftadter Strange Loopes and I went looking for it and was the story on Simmballism, SImms and Careenium the billiard pool with vibrating edges

and yes, this is what I needed to read to feel good about models, my belief do not have to be justified alla the way down to single evidences and experiments

Bayes is lean

an ignorant definition lerts me understand Bayes success in recent times

“Bayes’ core insight of gradually getting closer to the truth by constantly updating in proportion to the weight of the evidence” really lean statistics 🙂

the quote from Tetlock book on Superforecasters, I haven t read it. I neither read Lean startup, I don’t really remeber Bayes Theorem so I might be wrong in putting together things I do not study, but still the quote is suggestive

It come from here https://arbital.com/p/bayes_rule/?l=1zq

I did not know arbital, it is in less wrong territory I guess, I am going to study Bayes there

BTW all orginitase here “What relevance does this have for the LW-Yudkowsky-Bayesian rationalist project?” found in this SSC article about metis vs high rationalism. I think it’s all in the zeitgeist https://slatestarcodex.com/2017/03/16/book-review-seeing-like-a-state/

step back “seeing like a state” recycled as “seeeing like an algorithm” ref TikTok, I think misusued nd rather sinister but here it is Eugene Weiwei https://www.eugenewei.com/blog/2020/9/18/seeing-like-an-algorithm

Fad chasing pigs

the story of Soros and Druckenmiller (was it at quantum fund?) taking opposite sides on the dotcom boom

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

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/