1001 PredictionBook Nights

gwern

I explain what I've learned from creating and judging thousands of predictions on personal and real-world matters: the challenges of maintenance, the limitations of prediction markets, the interesting applications to my other essays, skepticism about pundits and unreflective persons' opinions, my own biases like optimism & planning fallacy, 3 very useful heuristics/approaches, and the costs of these activities in general.

Plus an extremely geeky parody of Fate/Stay Night.

This essay exists as a large section of my page on predictions markets on gwern.net: http://www.gwern.net/Prediction%20markets#1001-predictionbook-nights

I explain what I've learned from creating and judging thousands of predictions on personal and real-world matters: the challenges of maintenance, the limitations of prediction markets, the interesting applications to my other essays, skepticism about pundits and unreflective persons' opinions, my own biases like optimism & planning fallacy, 3 very useful heuristics/approaches, and the costs of these activities in general.

Plus an extremely geeky parody of Fate/Stay Night.

This essay exists as a large section of my page on predictions markets on gwern.net: http://www.gwern.net/Prediction%20markets#1001-predictionbook-nights

Since the study focused on the period around the 2008 elections, which the Democrats won on nearly all levels, and since most pundits tend to be biased towards believing that what they wish would happen will happen, it's not surprising that liberals' predictions did better and some conservatives scored worse than random. I suspect we'd see the trend go the other way for say predictions about the 2010 midterms. The fundamental problem is that the predictions weren't independent.

Since the correlation between liberalism and correctness was weak, most pundits probably wouldn't gain or lose much score in a more politically-average year. In Krugman's case, for example, most of the scored predictions were economic not political forecasts. In Cal Thomas's case however, your explanation might basically work.

2Will_Sawin15y

In particular, one should be skeptical of having lots of people who consistently do worse than average. I think, though, that it would, in fact, be worthwhile to do the analysis combining 2008 and 2010. I think Paul Krugman had already started panicking by then. More interesting might be to see how much data it takes for prediction markets to beat most/all pundits.

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