ArticleslgStudy

science

Shapley–Shubik power index

Shapley–Shubik power index is a science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Shapley–Shubik power index rather than just read about it. In short: The Shapley–Shubik power index (SSPI) is a measure of a participant’s a priori voting power in a decision-making body. It was introduced by Lloyd S.

Key takeaways

  • Shapley–Shubik power index belongs to science; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect Shapley–Shubik power index to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Shapley–Shubik power index from memory before moving on to harder problems.

Reference excerpt

The Shapley–Shubik power index (SSPI) is a measure of a participant’s a priori voting power in a decision-making body. It was introduced by Lloyd S. Shapley and Martin Shubik in 1954 as an application of the Shapley value from cooperative game theory to simple yes–no voting games. The index assigns to each player the probability of being pivotal—that is, the first to turn a losing coalition into a winning one—over all possible orderings of voters.

Definition Let there be n voters with weights (possibly all 1) and a quota q for passage. For any permutation (ordering) of the voters, the pivotal voter is the first whose addition to the running total weakly meets q. The Shapley–Shubik index for voter i is the fraction of all n! permutations in which i is pivotal; indices sum to 1 across voters.

Mathematical formulation Let N {\displaystyle N} be the voter set and v ( S ) ∈ { 0 , 1 } {\displaystyle v(S)\in \{0,1\}} indicate whether coalition S ⊆ N {\displaystyle S\subseteq N} is winning. Under the assumption that v {\displaystyle v} is a simple, monotone voting function, the Shapley-Shubik value obeys the following equation. For player i {\displaystyle i} ,

φ i = 1 n ! ∑ π ∈ Π [ v ( P i π ∪ { i } ) − v ( P i π ) ] {\displaystyle \varphi _{i}={\frac {1}{n!}}\sum _{\pi \in \Pi }{\big [}\,v(P_{i}^{\pi }\cup \{i\})-v(P_{i}^{\pi })\,{\big ]}}

where Π {\displaystyle \Pi } is the set of all permutations of N {\displaystyle N} and P i π {\displaystyle P_{i}^{\pi }} is the set of players preceding i {\displaystyle i} in permutation π {\displaystyle \pi } . The bracketed term is 1 iff i {\displaystyle i} is pivotal in π {\displaystyle \pi } .

Historical background Shapley and Shubik’s original 1954 paper introduced the index as a way to quantify individual influence in committees, parliaments, and other decision-making bodies. Their work built on cooperative game theory and the Shapley value, adapting it for monotonic binary voting games. Subsequent research expanded the theory, connected it to other power indices, and applied it to legislative design, corporate governance, and international organizations.

Properties The SSPI satisfies standard axioms for power measures in simple, monotone games (also called simple voting games):

Efficiency: ∑ i ∈ N φ i = 1 {\displaystyle \sum _{i\in N}\varphi _{i}=1} . Symmetry: equally situated voters have equal indices. Dummy: a voter who never turns any losing coalition into a winner has index 0. Additivity/transfer: behavior is consistent under sums of games. It is sensitive to both the quota and the distribution of weights. Unlike the Banzhaf power index, which averages over coalitions, SSPI averages over orderings and therefore embeds an ordering-based notion of pivotality.

Worked examples

Four-member weighted body Let weights be A=3, B=2, C=1, D=1 with quota q=4. Enumerating the 24 permutations shows A pivotal in 12, and each of B, C, D pivotal in 4. Thus A has 0.50, while B=C=D=1/6.

Shareholder meeting With shares (40, 30, 30) and q=51, the pivotal-probability rule yields indices (0.50, 0.25, 0.25). The largest shareholder’s influence exceeds proportional ownership.

Supermajority example For five equal voters and q=4 (a 4/5 supermajority), each voter’s index equals 0.2: symmetry implies equal power even under a high quota, though actual passage rates drop.

Computational complexity and algorithms Direct enumeration uses n! permutations. For weighted majority games, dynamic programming over weight sums reduces computation to pseudo-polynomial time O(n·W), where W is the total weight, or O(n·2^n) over coalitions; sampling methods estimate indices with probabilistic error bounds. Computing Shapley-value-based indices in general cooperative games is #P-complete, implying no polynomial-time algorithm exists unless P=#P.

Applications Legislatures and councils. SSPI is used to quantify influence under different seat allocations and quotas, including supermajorities and veto rules. International organizations. Analyses of the United Nations Security Council and the Council of the European Union compare permanent-member veto power and weighted voting under treaty reforms. Corporate governance. Shareholder power under dual-class structures or staggered thresholds can diverge substantially from proportional ownership. Constitutional and institutional design. Designers assess how proposed rule changes (quotas, membership, weights) affect ex ante influence before adoption.

Variants and extensions Researchers have extended the index to settings with abstention, probabilistic approval, communication structures, and hierarchical or multiple-issue games; the SSPI appears as a special case of the Shapley value under simple games and uniform ordering probabilities. Methods based on the multilinear extension and marginal-contribution distributions provide efficient approximations in large electorates.

… excerpt ends here. Continue reading the full article.

Worked examples

Example 1 — a first encounter with Shapley–Shubik power index

Start with the simplest possible case. Write down what Shapley–Shubik power index claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Shapley–Shubik power index before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Shapley–Shubik power index ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Shapley–Shubik power index

In research
Shapley–Shubik power index appears in science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses Shapley–Shubik power index in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
Shapley–Shubik power index is common in secondary-school and first-year university syllabi. It links to neighbouring topics Cooperative games, Game theory, Lloyd Shapley, so understanding it makes those chapters shorter.
In everyday life
Look for Shapley–Shubik power index outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.
Ask Teacher Smith questions about this articleOpens your AI tutor with a question about “Shapley–Shubik power index” →

Affiliate

Preply — study more efficiently by working with a personal tutor. 50% off.

How to study Shapley–Shubik power index in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Shapley–Shubik power index means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain Shapley–Shubik power index out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Shapley–Shubik power index in simple terms?

The Shapley–Shubik power index (SSPI) is a measure of a participant’s a priori voting power in a decision-making body. It was introduced by Lloyd S.

Why does Shapley–Shubik power index matter?

Because it connects several science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Shapley–Shubik power index?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Shapley–Shubik power index.

Tags

  • Cooperative games
  • Game theory
  • Lloyd Shapley
  • Voting theory

Keep exploring