Expert Forecasts. Their Uses and Limits. I. Who Counts as an Expert Forecaster?. Expertise: Subject-specific (generally discipline and subfield, but some problems are interdisciplinary) Requires hundreds or thousands of hours of work/practice Accepted as expert by other experts (problems?)
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Their Uses and Limits
1. Asymmetric Loss Bias: Bias can be created by “asymmetric loss functions” – that is, when making an overly optimistic/pessimistic prediction that turns out to be incorrect carries greater costs that if the forecaster had erred in the opposite direction.
1. Problem: Because both experts and no-experts can influence policy (see the reading for limits on this influence), there is cognitive bias against admitting failure. “Cognitive blinders” include post-hoc justification and “selective amnesia” (I was right despite evidence to the contrary, I was only wrong because of some improbable and unforeseeable event, I wasn’t really involved in the policy, I was on the other side all along, I’ve “moved on” and so should you – all the way to actual mental illness)
2. Are these excuses?
A. Opinion Polls: Frequently wrong, but right when outcome is obvious.
Example: Forecasting Election Winners (Oct)