This is a real big update to my simulation and reworks the entire logic of it. Though doing so allows me to investigate even more stuff. Check out the post on the old sim if you haven’t seen it.

At this point, the sim has become so complex, I don’t think I can explain it in as much depth as the previous one.

So I’ll keep it simple and show you my assumptions, results, and code. There are 10 sectors in the economy this time (so the visualization has changed)

As always, “economic reproduction” is the condition where nobody in the economy gains or looses money by the end of the production period.

The code and pictures are in the comments.

Also, I’d like /u/Sebrof and /u/pancake@lemmygrad.ml to see this post.

Assumptions:

  1. There are no banks, governments, population growth or technological changes. None of these things are modeled yet since they distract from the point of the model, which is to see how labor prices and economic reproduction are related.

My next model will try to model these things to see if the relationship between labor prices and economic reproduction still holds

  1. The logic of this model is inverted to the last one. In the previous model, we started with a net output (sold to consumers) then calculated how much gross output would be needed (sold to consumers and to factories) to maintain this. This time, I randomly generate a gross output then compute a net output.

  2. I randomly generate 100,000 economies, each with its own technological level (the 10x10 A matrix), a set of prices (10x1 column vector), and employment in industries (10x1 vector). I assume everyone is employed. Also, this time, there is only 1 price vector per economy.

  3. For each economy, I randomly generate a “basket of consumption”, which is the amount of products that its people will consume. I scale the basket so that it could be produced by half the labor of the economy, and keep the basket constant for all time.

  4. This time, there is foreign trade. If the economy produces more of a product than what is required for the basket, that’s exports. Otherwise it imports.

  5. I simulate 100 time steps for each economy. Every time step, the sectors of the economy will update their prices and employment. There were many possible rules for choosing how these updates happened. I made it so that the sectors hire workers in proportion to how much money they have (divided by how much it costs to hire workers). Prices are scaled down as a sector grows (due to competition)

  6. Then I compute all the financial data (like revenues, wages, incomes, costs, trade imbalances, profits, etc) and plot it.

The important accounting identities are:

National income = Wages + trade balance

National income = Revenues of industry - Costs of industry (not including wages)

    • Sebrof [he/him, comrade/them]@hexbear.netEnglish
      2·
      24 days ago

      I’ve tried looked into this with the world input output tables. But the time baseline on that is much smaller, but you gain a global view of the economy in exchange for just national views. In fact, using it to calculate labor exploitation is something that can be done, as well as tracing the flow of commodities between nations.

      In the world input output tables I’ve noticed that some nations lack labor data, like China. Idk why. So that may have to be imputed with a reasonable guess for some nations or compiled from other sources.

      When working with real input output tables the most important aspect of them is that they are set up differently from the input output tables you find in theory. I will explain in the next paragraoh In addition to the set up, they also have extra tidbits like taxes, tariffs (the most beautiful word in the dictionary, folks) government spending, gross fixed capital investment, etc. Those wouldn’t be too hard to handle, though I would need help in understanding some of details if doing it alone.

      Now for the world input output tables, the given data isn’t your typical input output table A where ai,j is the quantity flow of product i required as input for the production of a unit product of type j. Instead, the data is typically a monetary input output table. For the data, A is in money terms. So ai,j is the money flow of for product i paid to create one “dollar” output of product type j.

      You can still use the same equations you find in input output analysis, but one must keep in mind that instead of a vector of quantity flows (q or n) you are dealing with a vector of money flows such as gross or net product for each sector. The labor coefficients (l) or value vectors (v) are also in units of labor per dollar (or whatever currency gets used).

      Perhaps not all data is like this, but most of the input output table data i have found has this set up that is slightly different from how input output tables are set up and used in theory

      I think it would be cool to have some way of integrating those calculations into a network or the @hexatlas map

      I stalled out on that project as life got in the way. But most of the math is worked out. Given the data you can find how much labor one country consumes from another, and how much it gives in return by tracing labor inputs through this input output tables (i.e. a production network)

      Also, if you want to find profitability or wage data, one thing you would need to find data on or make assumptions about is productive labor vs unproductive

      Some sectors, like finance, insurance etc, are unproductive and simply take away from the surplus without producing any. But even productive sectors that create surplus, like manufacturing, are going to have some fraction of labor inputs that are included in the data but are not actually productive labor. Think management.

      Anwar Shaikh and Tomak (spelling?) Actually have a paper and book about how to make these profitability calculations using BLS data. So that is a source. And Basu has a paper with an overview of quantitative methods in Marxism that also overviews it.

      To my knowledge, Shaikh’s method aggregates data across sectors, but with an input output table the beauty is sectoral analysis.