Here is the lemmygrad post I made it at (don’t wanna have to copy everything over).

Please give the post lots of heart-sickle, the post would really appreciate it

Don’t be afraid to ask questions.

  • sodium_nitride [any, any]@hexbear.netOP
    link
    fedilink
    English
    arrow-up
    1
    ·
    5 days ago
    1. the 1000 different prices are there to see what happens to the reproduction condition with 1000 different prices. I am not directly calculating reproduction prices for each economy. I am just letting random guesses show me what happens to the reproduction condition at various price points.

    2. The net income being normalised was there just to improve the visualisation. I have run the code with all sorts of parameters with and without the normalisation, and it is difficult to decide which is more useful for gaining insight.

    I’ve tried generating economies with upto 100 sectors (my poor laptop), but right now, I am facing a different problem I am trying to solve (with more and more sectors, my current random price generation strategy rarely ever produces prices close to LTV. Law of large numbers and all).

    unit cost = A^T p

    This is what I have done in C (except I also multiplied by gross output yo get total costs per sector)

    If you wanted an aggregate quantity across all sectors, this would be the p q - you have already calculated this as R.

    R is a vector denoting the revenue by sector. I think part of your misunderstanding might be from MatLab’s element-wise multiplication function, whose output can be difficult to understand.

    O is a n long coming vector, P is a n long column vector, when element wise multiplied, the output is also a n long column vector.

    And I do suppose that using standard notation (which I have never seen before tbh) would probably help greatly.

    And perhaps this is what you’ve done, but just in an aggregate way.

    thonk-cri my shitty code is causing people to think I aggregated everything even though everything is disagregated.