Simpler Than You Think: The Practical Dynamics of Ranked Choice Voting

Abstract

Ranked Choice Voting (RCV) adoption is expanding across U.S. elections, but faces persistent criticism for complexity, strategic manipulation, and ballot exhaustion. We empirically test these concerns on real election data, across three diverse contexts: New York City's 2021 Democratic primaries (54 races), Alaska's 2024 primary-infused statewide elections (52 races), and Portland's 2024 multi-winner City Council elections (4 races). Our algorithmic approach circumvents computational complexity barriers by reducing election instance sizes (via candidate elimination). Our findings reveal that despite its intricate multi-round process and theoretical vulnerabilities, RCV consistently exhibits simple and transparent dynamics in practice, closely mirroring the interpretability of plurality elections. Following RCV adoption, competitiveness increased substantially compared to prior plurality elections, with average margins of victory declining by 9.2 percentage points in NYC and 11.4 points in Alaska. Empirically, complex ballot-addition strategies are not more efficient than simple ones, and ballot exhaustion has minimal impact, altering outcomes in only 3 of 110 elections. These findings demonstrate that RCV delivers measurable democratic benefits while proving robust to ballot-addition manipulation, resilient to ballot exhaustion effects, and maintaining transparent competitive dynamics in practice. The computational framework offers election administrators and researchers tools for immediate election-night analysis and facilitating clearer discourse around election dynamics.

Figures (8)

• Figure 1: The 2017 plurality voting results from New York City's Democratic Mayoral primary, from the official election website. (The extensive list of write-in votes is partly omitted here.) Bill de Blasio was elected in a single-round count, by securing more votes than any other candidate.
• Figure 2: The 2021 Ranked Choice Voting (RCV) results from New York City's Democratic Mayoral primary, as reported by the official election website. Eric L. Adams was elected in the 8th round, following the elimination of 10 candidates and the transfer of their votes.
• Figure 3: Margin of victory or competitiveness distributions before and after RCV adoption in NYC Primaries (left) and Alaska statewide contests (right), overlaid on competitiveness categories. The violin outlines smoothed density curves, and the internal boxplots mark the median and inter‑quartile range. Both jurisdictions show clear shifts toward tighter races after RCV implementation.
• Figure 4: Ballot exhaustion in NYC elections. Left: Excess of exhausted ballots over victory gaps; if this difference is positive, ballot completion can lead to alternative winner(s). Right: Probability of alternate winners vs. victory gap-to-exhaustion ratio, using six different models.
• Figure 5: Ballot exhaustion in Alaska elections (same interpretation as Fig. \ref{['fig:exhaustion_nyc']}).

Theorems & Definitions (19)

• Proposition 1
• proof : Proof Sketch
• Proposition 2
• proof : Proof Sketch
• Theorem 2.1
• proof : Proof Sketch
• Theorem 2.2
• proof : Proof Sketch
• Definition B.1
• Proposition 2