What Prediction Markets Can See: Market Formation, Settlement Legibility, and the Geography of Tradable Uncertainty in Africa and Latin America

Economics > General Economics [Submitted on 13 Jun 2026] Title:What Prediction Markets Can See: Market Formation, Settlement Legibility, and the Geography of Tradable Uncertainty in Africa and Latin America View PDFAbstract:Prediction markets are usually evaluated after their contracts exist, by asking how well prices forecast outcomes. We study the prior institutional margin of market formation, asking which uncertainties become tradable contracts at all. Using an audited dataset of 6,047 Africa-topic and Latin America-topic contracts listed on Polymarket and Kalshi, we construct a coded measure of settlement legibility, the degree to which an uncertainty can be worded, sourced, and credibly resolved by third parties, and validate it on 451 units under a frozen codebook, where independent double scoring reaches ordinal reliabilities of 0.92 and 0.96 on the primary dimensions and blind human benchmarks reach 0.97 and 0.92. Using this measure, we find that formation is selective in ways that public importance does not explain, with African inventory concentrated overwhelmingly in football while salient civic events produce little or no inventory, and Latin American inventory deeper but dominated by Venezuela, where attention to prospective United States military action sustains the largest civic cluster in the data. Legibility orders the inventory steeply, with sports and elections near the top of the scale and conflict at the bottom. In a formation test against an externally assembled frame of 131 civic events, legibility predicts listing in the expected direction but falls short of pre-specified acceptance criteria, while among listed contracts the relation between legibility and trading value is negative, as a model of selective listing implies and as we predicted before estimation. Prediction-market inventories therefore measure what platforms can settle as much as what traders believe, and reading them as maps of public interest conflates the two. Current browse context: econ.GN References & Citations Loading... Bibliographic and Citation Tools Bibliographic Explorer (What is the Explorer?) Connected Papers (What is Connected Papers?) Litmaps (What is Litmaps?) scite Smart Citations (What are Smart Citations?) Code, Data and Media Associated with this Article alphaXiv (What is alphaXiv?) CatalyzeX Code Finder for Papers (What is CatalyzeX?) DagsHub (What is DagsHub?) Gotit.pub (What is GotitPub?) Hugging Face (What is Huggingface?) ScienceCast (What is ScienceCast?) Demos Recommenders and Search Tools Influence Flower (What are Influence Flowers?) CORE Recommender (What is CORE?) arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.