Spatial voting: majority rule, pivots, Pareto sets and win sets

MajorityCompare: weighted sincere votes between two alternatives under (weighted) Euclidean preferences. PivotPoints: weighted median and supermajority, veto and bicameral pivots (Krehbiel 1998). ParetoSet: convex-hull Pareto set. WinSet: majority win set of a status quo on a grid (Plott 1967). Identical to the Python arm morie.fn.spatialvote.

Usage

MajorityCompare(ideals, x, y, weights = NULL, quota = 0.5, A = NULL)

PivotPoints(
  ideals,
  weights = NULL,
  supermajority = NULL,
  veto = NULL,
  chambers = NULL
)

ParetoSet(ideals, points = NULL)

WinSet(ideals, status_quo, grid, weights = NULL, quota = 0.5, A = NULL)

Arguments

ideals

Ideal-point matrix (or vector in one dimension).

x, y

Alternatives.

weights

Voter weights.

quota

Winning share.

A

Salience vector or positive definite matrix.

supermajority, veto

Supermajority and veto-override quotas.

chambers

List of member index vectors (1-based).

points

Points to test.

status_quo

Status quo.

grid

Candidate points (matrix).

Value

List.

References

Krehbiel, K. (1998). Pivotal Politics. University of Chicago Press.

Plott, C. R. (1967). A notion of equilibrium and its possibility under majority rule. American Economic Review 57, 787-806.

Examples

MajorityCompare(matrix(c(0, 2, 3)), 1, 2.5)$winner
#> [1] "y"
PivotPoints(1:5, supermajority = 0.6)$gridlock
#> [1] 2 3