# Dice displays to prompt intuitive understanding of probabilities

About a week and a half ago, when I looked, iPredict showed approximately a 63% probability that there would be a National Prime Minister after the 2017 general election in New Zealand, and a 37% probability that there would be a Labour Prime Minister. Here’s what that looks like as a horizontal bar:

The problem with this way of looking at it is that (especially in New Zealand, with a proportional voting system), there’s a temptation to interpret the proportions as vote shares, rather than as probabilities. And even when I’ve got the idea of vote shares out of my mind, I can still be inclined to interpret it as a prediction that National will win the 2017 election. It’s not; it’s an estimate that there is a 63% probability that National will win the election.

How can I encourage myself to understand this intuitively? Continue reading Dice displays to prompt intuitive understanding of probabilities

# Betting against public goods that you want

In my first article about funding public goods, I mentioned in passing the Wall Street performer protocol, which involves bonds that pay out when a certain public good is provided. In this article, instead of talking about them as bonds, I’m going to think of them as bets — bets on whether the public good will be provided.

But the curious thing is this: people who want to help fund the public good do so by betting that the good won’t be provided. How does that work? Continue reading Betting against public goods that you want