Induced Economic Effects Part 2 - Template Entities and "Buck Rot"

So last week we introduced the concept of money flowing into, through, and out of an economy based on an initial investment and subsequent transactions.

We also promised to update, and failed to deliver.

Of course I'm using the royal "we", in both senses, but that's neither here nor there.

Today, I want to introduce the concept of iterated transactions, because when we talk about how much money remains in an economy after a given period of time based off of an initial investment, what we're really trying to capture is a sequence of iterated transactions.

One of the fundamental truths of economics is that money itself has no value, and only its use gives it utility in the traditional economic/utilitarian sense. This is true whether we're talking about USD, BTC, or CNY. It's the ability to spend money that gives it its value, and consequently, the velocity of money is a core concept in economic analysis.

What is "the velocity of money"? It's very similar to the physical concept of velocity, in that it is the number of hands a unit of currency moves through in a given period of time. So in the case of economics, it is helpful to think of money (or value) as "mass", people (or entities) as "distance", and time as ... well time.

One of the derivations of this, and I won't go into too much detail in this post on it is the "stickiness" of prices in the New Neoclassical Synthesis, which is that prices are not perfectly fluid, because it takes a shock of sufficient "force" (similar to Newtonian F=ma) to move prices, and that they have a proportional rate of change equal to their momentum (big transactions that have been happening frequently for a long time change more slowly than little transactions that have been happening infrequently for a relatively short period of time).

When we talk about induced economic effects, and attempt to quantify the size of the residual impact after a given time, we need to talk about how much of each dollar stays in the economy after each transaction. To do that its useful to discuss template entities. The reason we have template entities, is that in practical terms, it's very difficult to quantify each individual transaction, but in aggregate, we can take averages, and develop a theorem with strong statistical validity as long as there's a solid average.

Last week I used a 7-11 as our example entity, and discussed the purchase of a candy bar. If we assume that every entity has a similar structure in terms of money that stays in the economy vs money that leaves the defined region, we can come up with a formula.

So again, for simple discussion, let's assume in each transaction, roughly 50% stays in the geographic region. That number is of course a placeholder, and there's a substantial body of work to calculate the actual value, primarily by the US Bureau of Economic Analysis through their Regional Input/Output Multiplier System, known colloquially as RIMS II.

What our simplified assumption tells us, is that for every dollar spent in the region under analysis, fifty cents stays in the region. Combining that with a velocity of money, which we'll assume to be at 1.5 per quarter, or 6 per year (which is close enough to the actual value for this simplified analysis) we can see that within a year, each dollar is spent 6 times, each time, half of it leaves the economy, or that our residual is equal to:

or the initial investment times the one minus the amount left after each transaction raised to the number of transactions we expect to have occurred in the time period. In our simplified example, this is effectively a half-life.

Barring outside reinvestment, the money in an economy decays at a predictable rate, hence the term of art I like to use, "buck rot".

In this example world, every year ~98.5% of our initial investment decays out of the economy, which is why reinvestment and exports play a crucial economic role.

Which we'll talk about soon. Before that though, there's a few posts I've been meaning to publish on the emerging Bitcoin phenomenon.