This project archives the pre-result research materials for a study of the veda-consolidation mechanism in Latin American two-round presidential elections, with empirical evidence from Colombia 2022 and Colombia 2026. The study examines why pre-election polls may substantially underestimate rising outsider or opposition candidates in systems where legally mandated polling blackouts prevent the publication of new survey data during the final period of strategic voter coordination. The central purpose of the project is to document a pre-specified forecasting framework that distinguishes between two quantities that may behave differently under polling blackout conditions: aggregate electoral bloc demand and intra-bloc candidate allocation. The paper argues that polling blackouts do not necessarily prevent surveys from characterizing the overall size of an electoral bloc, but they can prevent surveys from observing late strategic vote transfers within that bloc. This produces what the study defines as blackout-induced allocation error: the combined bloc may be estimated accurately, while the final distribution of support among candidates inside that bloc changes after the last observable polling point. The project includes a composite-weighted poll aggregation model using survey recency, sample size, documentation traceability, house-effect adjustment, empirical track-record weighting, and Monte Carlo simulation. The model is evaluated through three formal hypotheses: first, that composite weighting improves on simple averaging; second, that bloc-level forecasts outperform individual-candidate forecasts under blackout-driven consolidation; and third, that errors for the consolidating candidate are directionally consistent across polling firms. The project also includes a retrospective comparison using Colombia’s 2022 presidential first round and a pre-specified runoff forecast for Colombia 2026. The expected outcomes of this project are threefold. First, it provides a transparent record of the model specification, hypotheses, forecast assumptions, and validation criteria prior to final runoff validation. Second, it distinguishes prospective, retrospective, diagnostic, and post-validation analyses in order to reduce ambiguity about which claims were specified before the outcome and which are interpretive or exploratory. Third, it contributes to public opinion and electoral forecasting research by proposing a framework for analyzing polling blackouts as institutional sources of forecast uncertainty in two-round electoral systems. The archived materials include the working paper, model and hypothesis specification, frozen runoff forecast, analysis classification, source audit checklist, and metadata guide. The project is intended to support transparency, reproducibility, and future journal submission by providing a timestamped record of the research design and analytical framework.
Levis Cabrera Abinader (Thu,) studied this question.