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 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.

True, of course in Krugman's case I suspect most of his predictions amounted to predicting that the financial crisis was going to be really but, and thus were also correlated.

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