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README powerindices

This package computes the Penrose Banzhaf index (PBI), the Shapley Shubik index (SSI), and the Coleman Shapley index (CSI) for weighted voting games. Both, quota and weights must be integers. Moreover, it is possible to give an optional arguemnent: the minimal size of a winning coalition.

For information about the indices:

PBI: https://en.wikipedia.org/wiki/Banzhaf_power_index

SSI: https://en.wikipedia.org/wiki/Shapley%E2%80%93Shubik_power_index

CSI: The Coleman-Shapley-Index: Being Decisive Within the Coalition of the Interested by André Casajus and Frank Huettner

Installation

Installation guide available on youtube

If you haven't installed python yet, get it, e.g. from https://www.anaconda.com/download/.

Option 1: To install the tool, run pip install powerindices in your terminal. If you use anaconda, run the command in the Anaconda Promt.

Option 2 (without installation): It's just one file, so that an installation of the powerindices package isn't actually necessary: Just download the repository and copy powerindices.py to your working folder. (Or have the files example.py and powerindices.py in the same folder. Then, running the example.py will compute the indices for the UN Security Council.)

Usage

This example.py offers the following examples.

The powerindices for the UN Security Council

Basic tutorial available on youtube 

import powerindices
quota,weights = 39, [7, 7, 7, 7, 7, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1] 
# call the functions compute_pbi, compute_csi, or compute_SSi to compute the corresponding index
PBIs = powerindices.compute_pbi(quota,weights)
SSIs = powerindices.compute_ssi(quota,weights)
CSIs = powerindices.compute_csi(quota,weights)
### The functions return the indices as lists so that
### they are now stored as lists in the PBIs, SSIs, and CSIs.
### We could simply print these list:
print(SSIs)
print(PBIs)
print(CSIs)

Here, the quota is set to 39 and the weights are [7, 7, 7, 7, 7, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], where the veto powers are thought to have 7 and the nonpermanent members have weight 1. Alternatively, set quota = 5, weights = [1,1,1,1,1,0,0,0,0,0,0,0,0,0,0], and pass the optional argument minimalWinningCoalitionSize=9:

import powerindices
quota,weights = 5, [1,1,1,1,1,0,0,0,0,0,0,0,0,0,0] 
# call the functions compute_pbi, compute_csi, or compute_SSi to compute the corresponding index
PBIs = powerindices.compute_pbi(quota,weights,minimalWinningCoalitionSize=9)
SSIs = powerindices.compute_ssi(quota,weights,minimalWinningCoalitionSize=9)
CSIs = powerindices.compute_csi(quota,weights,minimalWinningCoalitionSize=9)

The powerindices for the EU Council (needs to be uncommented)

This can be computed as well: the quota is 65% of the population and the weight of every country is the population of this country. Moreover, the minimal size of a winning coalition must be specified: setting minimalWinningCoalitionSize=16 ensures that only coalitions with at least 16 members (i.e., 55% of the countries) are winning. For details, see the example.py file.

Usage from within R

Quick demo on youtube

You can use this tool from within R by help of reticulate. To this end,

  • Install the package powerindices in your python environment running the command pip install powerindices in your terminal.
  • Install reticulate.
  • Call the package powerindices from within R and make sure to send integers, e.g., the following will store the CSIs for the UN Security Council in the list csis 
    library(reticulate)
powerindices <- import("powerindices")
csis <-powerindices$compute_csi(39L,c(7L, 7L, 7L, 7L, 7L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L))

Requirements

You need to have numpy and math. I did not put it into the setup.py requirements because this seems to bring trouble. Both packages are standard and come with anaconda.

Used algorithm

We use an algorithm following that counts the number of swings of a voter, see e.g.,

S. Kurz: Computing the Power Distribution in the IMF (arXiv).

A. Casajus and F. Huettner: The Coleman-Shapley-Index: Being Decisive Within the Coalition of the Interested'.

Author

Frank Huettner