IOV LABSForecasting the 2026 Korean Local Elections: A Reproducible Polls-plus-Fundamentals Model with a Pre-registered Validation Protocol
Abstract
We forecast the 16 metropolitan-executive (광역단체장) races of South Korea's 9th nationwide local election (3 June 2026) by combining a structural fundamentals estimate — each region's 2022 two-way vote swung to the 2026 environment on the logit scale — with method-normalized poll aggregates, fused by poll-count-weighted hierarchical shrinkage. Outcome uncertainty is propagated through a 50,000-draw correlated Monte Carlo with a three-level error budget (national ⊕ cluster ⊕ local) and heavy-tailed (normal-mixture ≈ Student-t) innovations, so that a single nationwide polling miss moves correlated blocs together. The pipeline is seeded and reproducible to the bit. The central estimate is the Democratic Party winning 12 of 16 seats (90% range 8–15), with five genuine toss-ups and only two regions leaning conservative. The error model is calibrated on the 2022 final phone polls (bias −0.1pt, MAE 2.2pt), and the dominant failure mode — a correlated poll bias — is quantified by an explicit ±4pt scenario sweep. A parallel silicon-sampling experiment (an LLM-persona electorate) is reported as a negative result. The paper is pre-registered: the forecast is committed before the result and graded by a fixed script after polls close.
Keywords
- election forecasting
- poll aggregation
- house effects
- hierarchical shrinkage
- correlated Monte Carlo
- heavy-tailed errors
- calibration
- Brier score
- silicon sampling
- reproducibility
- pre-registration