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Prediction Markets: Bidding to Fund Public Goods


Throughout our discussion of markets and the spread of information, we’ve examined how prediction markets play a role in prediction aggregation within a population. While we compared and contrasted the typical prediction market to betting in horse races, this article applies the concept of prediction markets to the funding of public goods. Specifically, this blog post describes the counterintuitive process as one in which you bet against a public good in order to fund it.

To give us a better understanding of how this form of betting works, the blogger introduces the “Wall Street performer protocol”, where “bonds[, or bets], pay out when a certain public good is provided”(Ideophilus 2013). This protocol, and consequently the prediction market for funding public goods, is fundamentally based on a shift of incentives: if many individuals demonstrate their desire for a public good by betting that it will not be provided, there must be someone betting that the good will be provided, and that someone has an incentive to ensure that the good is provided. This can be seen in an example of building a school in your neighborhood. You and others who want the school to be built will bet that the school will NOT be built, and if enough people join you, a contractor can short that bet, or bet that the school will be built, claim the profit, and actually build the school.

Ultimately, this article’s examination of the existence of a prediction market where people bet against providing public goods to actually fund them connects to our course readings and lectures on prediction markets in which price outcomes reflect the aggregation, specifically averaging, of beliefs of participants in the market population. However, this specific instance prediction market with the Wall Street performer protocol introduces a different interpretation of incentives, where the “optimal/ideal” bid is to bid against the public good you want funded. This interesting perspective on bidding strategy contrasts the incentives in bidding situations similar to typical prediction markets or the horse races discussed in class, where the bid considered “optimal” aligns with your own beliefs.



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