Rajiv Sethi, Professor of Economics at Bernard College at Columbia University, discusses prediction markets and how they harness the wisdom of the crowd. They explore the concept of markets as speculation and aggregation of information, compare prediction markets to epidemiological models, and suggest using prediction markets to capture rare events more effectively.
Prediction markets, which gather opinions and bets from the general public, can outperform experts' models in certain situations, particularly those involving social aspects.
Prediction markets allow for input from non-experts and consider a wide range of variables and perspectives, making them depolarizing tools compared to echo chambers found on other online platforms.
Deep dives
Prediction markets as an alternative to model building
Prediction markets offer an alternative approach to model building in science and forecasting. Rather than relying on experts and model construction, prediction markets gather opinions and bets from the general public. While this may initially seem less reliable, prediction markets have proven to be effective in certain situations, particularly those involving social aspects. These markets not only allow individuals to predict future events, but also enable them to bet against each other based on their beliefs. This approach, known as the wisdom of the crowd, has shown promising results in accurately predicting outcomes.
The concept and function of prediction markets
Prediction markets are financial markets where individuals trade contracts predicting outcomes of specific events. These contracts have a simple payoff structure: if the referenced event occurs, the buyer gets paid; otherwise, they receive nothing. For example, there may be contracts on predicted, trading the likelihood of different candidates winning an election. These markets operate as peer-to-peer markets, connecting buyers and sellers, with the market price serving as an indicator of the perceived probability of an event occurring. The contracts can be bought, sold, and traded, allowing for quick responses to changing beliefs and information.
The history and performance of prediction markets
Prediction markets have been around since the 1980s, with the Iowa electronic markets being one of the earliest examples. Over time, other markets like InTrade and PredictIt gained popularity. Research has shown that prediction markets can outperform traditional models in forecasting certain events, especially when models fail to capture social variables or rapid changes in beliefs. These markets respond quickly to new information, even if it contradicts conventional wisdom. However, prediction markets also have limitations and are susceptible to manipulation and herding behavior.
The role of prediction markets in wisdom of the crowd
Prediction markets embody the concept of the wisdom of the crowd, where the collective intelligence of a diverse group can lead to accurate predictions. Unlike traditional models that rely on experts, prediction markets allow for input from non-experts and consider a wide range of variables and perspectives. Traders in these markets, even if they hold strong preferences, separate their beliefs from their trading positions. The diversity of traders and their opposing bets ensures that different views are considered, making prediction markets depolarizing tools compared to echo chambers found on other online platforms.
Experts often build models to help predict how systems will behave. But what happens if, instead of asking the experts to build models, we ask laypeople to simply predict outcomes?
This is what happens in 'prediction markets'. And it turns out that in some situations, the 'wisdom of the crowd' often outperforms experts' models.
To break down what prediction markets are and how they work, we're joined by Rajiv Sethi, Professor of Economics at Barnard College at Columbia University and External Professor at the Santa Fe Institute.