1 of 15

Computer Simulations of Participatory Planning:

New Evidence for Environmental Protection

​

Mitchell Szczepanczyk

http://www.szcz.org

​

2 of 15

Overview

​

  • Background: MPE, Pequod, Past research in DEP

​

  • Preliminaries: Economics, Mathematics, Computer Code

​

  • Results

​

  • Analysis, Next Steps, Resources

3 of 15

Background

​

  • Participatory Economy: Democratically-planned economic model co-invented by Robin Hahnel and Michael Albert

​

  • Participatory Planning: Non-market, non-command allocation system in the model of a participatory economy

​

  • Goal: Society-wide allocation plan with no excess demand

​

  • Participants: Worker councils (WCs), consumer councils (CCs), iteration facilitation mechanism (IFM), indicative prices

​

  • Councils exchange consumption/production plans, revise in iterated process with help of the IFM

4 of 15

Pequod

​

  • Participatory Planning Procedure Prototype (4 P’s = “pequod”)

​

  • Feasibility study of participatory planning: How many iterations are required?

​

  • Computer implementation of mathematical model of a participatory economy

​

  • Written originally in Netlogo, rewritten in Clojure / Clojurescript

5 of 15

DEP : The Book (2021)

​

  • Hahnel et al (2021) presented findings of research

​

  • 40 Experiments: 60,000 councils, 400 goods categories

​

  • Two “years”, where the second year incorporates augments to represent technological innovation.

​

  • How many iterations are required? “About six” after Year Two.

​

  • What about the environment?

6 of 15

Preliminaries : Economics

​

  • Cobb Douglas production and utility functions: Maximize well-being.

​

  • Supply of pollutants: Derived from permissions granted by consumer councils.

​

  • Demand for pollutants: Pollution rights sought by workers councils.

7 of 15

Preliminaries : Mathematics

​

  • Initialize a price of pollutant (700)

​

  • Each WC has an arbitrary pollutant-exponent value

​

  • Each CC has two values: Positive utility (income, z^k) and negative utility (exposure, (5zp)^j)

​

  • To optimize, take the derivative, giving us kz^(k-1) = 5jp(zp)^(j-1)

​

8 of 15

Preliminaries : Computer Code

​

9 of 15

Preliminaries : Computer Code

​

​

  • Make room in production quantities and production functions for pollutants

​

  • Make room in output for a pollutant category

​

  • Year Two augment: Each WC includes a pollution-exponent augment, while there are no changes to the augment in CCs.

10 of 15

Updates : Pequod

​

  • pequod-plus
    • More automated tests
    • More code consolidation
    • More “Clojurey” code

​

  • Environmental impacts

​

  • New experiments: 60,000 councils, 400 goods categories, 1 economy-wide pollutant

​

  • Five experiments, two years, with and without pollutants

11 of 15

Results : Pollutant Behavior

​

12 of 15

Results : Pollutant Behavior

​

13 of 15

Analysis

​

  • Pollutants are going in the direction we want: high prices, low demand, low supply

​

  • Iterations are still “reasonable” but seeing clear impact

​

  • Economy does converge into a society-wide plan

14 of 15

Possible Next Steps

​

  • Increase number of experiments to 40

​

  • Research/adjust pricing algorithms

​

  • Human intervention research

​

  • Examine more pollutants at different scales of impacts (local, regional)

​

  • Publish findings

15 of 15

Resources