Prediction Model Bias

Brad Plumer provides a very practical reason why he believes environmental cost predictions tend to be over-estimates:

[M]arkets always tend to be smarter than these forecasters, and adjust in ways that no one expected.

Let’s assume arguendo that this is correct (and I think it is, as a general statement about markets vs. planners – I’m about as Hayekian as they come). This leads to two questions, one far more important than the other.

1. The narrow point is that, per prior discussion on this, if one could actually observe a reasonably consistent over-estimate in a provably-relevant reference class of prior predictions, this would lead a competent forecaster to make a transparent “topside” adjustment to get a best-available forecast.

2. The more important point is that this same logic ought to apply to the damage estimates that similar bodies forecast for the costs of climate change. That is, markets should be smarter than forecasters think when it comes to adapting to climate change as well (e.g., crop selection, transitions to other economic sectors, clever infrastructure developments and so on). To only focus on this kind of error on one side of the cost / benefit calculation is loading the dice.