Notice the scare quotes around 'investment'. To many people, 'investment' means to 'build new capacity'. Hence, governments are always chasing 'investment' dollars.
But here's the thing: 'investment' is purely about transferring property rights.
The word 'invest', @BichlerNitzan observe, has feudal origins. In feudal societies, 'investiture' was the "symbolic ceremony of transferring property rights from the lord to the vassal".
OK, so 'investment' is everywhere and always a transfer of property rights. Still, there are many kinds of property rights, so 'investment' can have many different forms.
I can 'invest' in land, houses, machines, factories, etc.
Here is the twist: if I own a corporation, I can also get that corporation to invest in *other corporations*.
In corporate speak, the act of buying up other corporations is call 'mergers and acquisitions'.
But why would I want to buy other corporations? In a word, *power*. The drive to merge is about acquiring the power to set prices.
This price-setting power is written in the data. Big firms tend to have a higher 'markup' (profit as a portion of sales) than smaller firms. Here's the trend in US firms.
Back to mergers and acquisitions. An important question to ask is --- to what extend are corporations buying other corporations rather than investing in 'stuff'? And what is the trend?
These are the questions behind @BichlerNitzan's 'buy-to-build' indicator.
The first published stab at constructing a 'buy-to-build' indicator was in a 2001 paper by Jonathan Nitzan
called 'Regimes of Differential Accumulation.'
Here's the US results. Notice two things: 1. the trend is upward 2. there are big oscillations
Much of the underlying data above is proprietary. Noting this fact, @joefrancis505 later constructed buy-to-build indicators using open source data. US trends are on the left, UK trends on the right.
Back to the buy-to-build indicator. @joefrancis505 uncovered a calculation error in @BichlerNitzan's original estimates. His new estimates differed slightly from the original. @BichlerNitzan noted this in an accompanying commentary:
A side note here about this commentary. As @joefrancis505 himself showed, debate and commentary is becoming increasingly rare in economics. Here's its rise and fall in the big 5 economics journals.
Now lets back up 20 years. In Jonathan Nitzan's first paper on the buy-to-build indicator, he looked at it's short term fluctuation. Turns out that it correlates negatively with a 'stagflation' index --- a measure of inflation and unemployment.
In other words, when corporations merge more, unemployment and inflation tend to decrease. And when corporations fail to merge, they turn to inflation to make money.
@BichlerNitzan updated the data in 2009, finding much the same thing:
When @joefrancis505 did new estimates, he found the same thing. The buy-to-build indicator moves inversely with stagflation. Here's the US and Britain.
.@BichlerNitzan use these results to classify different regimes of capitalism. Firms' goal is always to increase their capitalization relative to other firms. But there are different ways to do it. Here's @BichlerNitzan's classification:
'Greenfield' investment is building new factories. When people think of 'investment', that's their default. But the other major option for getting bigger is to buy other firms: 'Mergers and acquisitions'.
The trend has been towards more mergers, less greenfield.
Alternatively, instead of getting larger, firms can try to boost their profitability per employee. Economists will tell you that firms do this by 'cost-cutting'. The dirty secret, though, is that firms have a secret weapon for increasing profits: *inflation*.
1. the buy-to-build indicator tends to increase over the long term 2. short-term movements in the buy-to-build indicator correlate negatively with stagflation.
What we need now is for researchers to see if this research replicates in other countries.
If you complete such research, please consider submitting it to the Review of Capital as Power.
The 'value' in art is what it contributes to society. Same goes for science. Because that's essentially a public good, there's no way to measure the 'value'. Let's just settle for this: both art and science are good.
Don't confuse 'value' (that social thing) with 'price' --- which is purely about property rights. NFTs are about a clever way to put property rights around internet art that is otherwise free.
Capital, they say, is about *power*. Stocks are the symbolic representation of capitalists power. In their paper 'A CasP model of the stock market', Bichler and Nitzan further develop their theory of the stock market.
[Thread] (1) Here's the twitter summary of my recent post on the rise and fall of empires. Although the motivations for empire building differ, the end result is always the same. Empires concentrate the flow of energy.
(2) That means we can judge the extent of imperial power using relative energy use. We compare energy use (per person) in the empire's core to energy use in the periphery. The greater this ratio, the more "successful" the empire. (Note scare quotes. I'll return to this later).
(3) Let's look first at the largest scale ... the entire history of civilization. Along with agriculture, the first empires arose in the 'West' (the Mediterranean basin). We can chart this rise and fall with energy.
This study takes the spread of the "church" as the independent variable. It then shows that this spread correlates with a host of behavioral changes, including a drop in cousin marriages and a change to more individualistic personalities. 2/n
The study concludes that the spread of the church caused the other changes. At first, this sounds superficially convincing. But after thinking about it, there's big problems. 3/n
1/N. This is the first in a series of posts about the philosophy of science. In honor of Richard Feynman's famous phrase, I'm calling this thread "How we fool ourselves".
2/N. In grad school, I constantly heard fellow students (and some professors) marvelling at the explanatory scope of some theory. "It explains so much about the world", they would say. Few seemed to realize that explaining too much is a liability.
3/N. Theories that explain "so much" often have the appearance of being "profound". But in reality, they are "not even wrong". This is physicist Wolfgang Pauli's, phrase for theories that fail to make falsifiable predictions. They are immune to evidence. en.wikipedia.org/wiki/Not_even_…
I use to think group think was a problem unique to economics. But it seems to be everywhere in science. Sabine Hossenfelder does an excellent job documenting group think in physics: goodreads.com/book/show/3634…