Skip to content

Instantly share code, notes, and snippets.

Last active August 28, 2021 01:42
  • Star 23 You must be signed in to star a gist
  • Fork 10 You must be signed in to fork a gist
Star You must be signed in to star a gist
Save stucchio/7447067 to your computer and use it in GitHub Desktop.
Monte carlo simulation of basic income/basic job calculations, from blog.
from pylab import *
from scipy.stats import *
num_adults = 227e6
basic_income = 7.25*40*50
labor_force = 154e6
disabled_adults = 21e6
current_wealth_transfers = 3369e9
def jk_rowling(num_non_workers):
num_of_jk_rowlings = binom(num_non_workers, 1e-7).rvs()
return num_of_jk_rowlings * 1e9
def basic_income_cost_benefit():
direct_costs = num_adults * basic_income
administrative_cost_per_person = norm(250,75)
non_worker_multiplier = uniform(-0.10, 0.15).rvs()
non_workers = (num_adults-labor_force-disabled_adults) * (1+non_worker_multiplier)
marginal_worker_hourly_productivity = norm(10,1)
administrative_costs = num_adults * administrative_cost_per_person.rvs()
labor_effect_costs_benefit = -1 * ((num_adults-labor_force-disabled_adults) *
non_worker_multiplier *
return direct_costs + administrative_costs + labor_effect_costs_benefit - jk_rowling(non_workers)
def basic_job_cost_benefit():
administrative_cost_per_disabled_person = norm(500,150).rvs()
administrative_cost_per_worker = norm(5000, 1500).rvs()
non_worker_multiplier = uniform(-0.20, 0.25).rvs()
basic_job_hourly_productivity = uniform(0.0, 7.25).rvs()
disabled_cost = disabled_adults * (basic_income + administrative_cost_per_disabled_person)
num_basic_workers = ((num_adults - disabled_adults - labor_force) *
basic_worker_cost_benefit = num_basic_workers * (
basic_income +
administrative_cost_per_worker -
return disabled_cost + basic_worker_cost_benefit
N = 1024*32
bi = zeros(shape=(N,), dtype=float)
bj = zeros(shape=(N,), dtype=float)
for k in range(N):
bi[k] = basic_income_cost_benefit()
bj[k] = basic_job_cost_benefit()
width = 4e12
title("Basic Income")
hist(bi, bins=50)
title("Basic Job")
hist(bj, bins=50)
Copy link

bwanab commented Nov 27, 2013

Hi Chris, I followed the original discussion on HN. I found your work to be very worthwhile. I've been working mainly in clojure lately, and using Incanter for statistical applications, but I hadn't tried any simulations. Inspired by your work here, I've reimplemented it in clojure/Incanter form at Thanks for pushing the button.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment