Forecasting Round-Up No. 5

This is the latest in a (very) occasional series: No. 1, No. 2, No. 3, and No. 4.

1. Pacific Standard ran a long feature by Graeme Wood last week on the death of Intrade CEO John Delaney and the rise and demise of the prediction market he helped build. The bits about Delaney’s personal life weren’t of interest to me, but the piece is very much worth reading for the intellectual history of prediction markets it offers. Wood concludes with an intriguing argument about which I would like to see more evidence:

More traditional modes of prediction have proved astonishingly bad, yet they continue to run our economic and political worlds, often straight into the ground. Bubbles do occur, and we can all point to examples of markets getting blindsided. But if prediction markets are on balance more accurate and unbiased, they should still be an attractive policy tool, rather than a discarded idea tainted with the odor of unseemliness. As [economist Robin] Hanson asks, “Who wouldn’t want a more accurate source?”

Maybe most people. What motivates us to vote, opine, and prognosticate is often not the desire for efficacy or accuracy in worldly affairs—the things that prediction markets deliver—but instead the desire to send signals to each other about who we are. Humans remain intensely tribal… More than we like accuracy, we like listening to talkers on our side, and identifying them as being on our team—the right team.

2. One thing I think Graeme Wood gets wrong in that article is this prediction: “The chances of another Intrade’s coming into existence are slim.” Au contraire, mon frère. Okay, so for regulatory reasons we many never see another market that looks and works just like Intrade did, but there’s still a lot of action in this area, including the recently-launched American Civics Exchange (ACE), “the first U.S.-based commercial market for political futures.” ACE uses play money (for now), but the exchange pays out real-cash monthly prizes to the most successful traders. I registered when they launched and have focused my trading so far on the 2014 Congressional elections. I don’t have any expectations of winning the prizes they’re offering, but I’m excited to see that the forum even exists at all.

3. Speaking of actual existing prediction markets, have you seen Sean J. Taylor‘s brainchild, Creds? This is a free and open market in which the currency is reputational. Anyone can create statements and make trades, but you have to register to participate so that your name, and thus your credibility, is attached to those trades. The site needs more liquidity (hint, hint) to become really useful as a forecasting resource, but some of the features and functions Sean is experimenting with on the site are novel and very cool.

I’ve been trading on Creds for a little while and recently used it to create a couple of statements about the possibility that Saudi Arabia will acquire nuclear weapons in the next five years (here and here). Those statements were inspired by a tweet from Ian Bremmer and an ensuing report on BBC News. It’s nice to have open venues to quantify our collective beliefs about topics like this one, something we simply couldn’t do not so long ago.

4. Why is quantifying our beliefs so important? I recently had an email exchange with a colleague on this issue. After that colleague wrote a piece on a timely situation that amounted to a “maybe, maybe not” prediction, I pushed him to assign some probabilities to his thinking. He pushed back, saying that any number he produced would “simply be a guess,” and that numeric guesses would smack of “false precision.” In the end, I failed to convince him to offer what I would consider a real forecast.

The next time that debate comes up, I will point my antagonist toward Mike Ward & co.‘s new Predictive Heuristics blog, and in particular to this passage from this post of Mike’s on “Prediction versus Explanation?“:

Pretending that our explanations don’t have to supply accurate predictions—i.e., we are explaining rather than predicting—leads to worse understanding. Rather than ignoring or hiding predictions we should put them front and center so that they may help us in the evaluation of how well our understandings play out in political events and remind us that our understandings are incomplete as well as uncertain… Real understanding will involve both explanation and prediction. Time to get on with it rather than pretending that these two goals are polar opposites. We have a long way to go.

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