I think the problem with the models built by Dent and others may not be so much that they are wrong, but that they are incomplete. As someone with a physics and engineering background, I know that the most important aspect of any model is defining the boundary conditions and the starting points. Dent’s (and many economic models that contributed to the financial crisis) don’t reach wide enough to include parameters such as energy decline, or they make assumptions (like housing prices always go up) which they treat as fact. The models work great using the input they are provided, but then the world doesn’t quite turn out that way.

A far more useful approach with models is to do what the “Limits to growth” studies have done – use models to explore plausible future scenarios, and especially to reveal the assumptions we are making about the situation. But this is using models in a very different way – to anticipate rather than to predict.
So often, humans see what happened yesterday continuing to happen today, and expect it to happen tomorrow. The challenge is understanding when this extrapolation is valid and when it is not.

If someone makes a prediction, all their subsequent information gathering tends to be filtered by that prediction. They look for information that supports the prediction, and tend to ignore information that contradicts the prediction. (That’s why researchers used double-blind studies.) And if their prediction is also more desirable than the alternatives, they are even more likely to block contradictory information.

No easy solutions, just keep putting the information out there, and gradually attitudes will change.

Best regards,
Randy Park
Author, “The Prediction Trap – and how to avoid it”