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T H's avatar

Regarding critiques: #1 and 5 are in direct opposition to each other. If you made this policy revenue neutral, neither would apply. You can make the policy revenue-neutral by setting an overall benchmark of safety (e.g. 2023 fatality/mile) and penalizing/rewarding in proportion to deviation from that baseline.

Regarding #2, more niche models wouldn't benefit as much from the law of large numbers.

Is there a selection bias, where more dangerous drivers are drawn to certain models (e.g. racier cars)? Given the strong brand resonance with cars, I find that likely, but I don't know how big the effect size is.

Regarding #4, that is the most obvious solution to me. Insurance should fully internalize the economics of which car models lead to what economic damages. What is it about insurance regulations that inhibit insurance companies from charging exactly enough to cover the expected damages from each car model?

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Dennis's avatar

It's an interesting approach. However, the example of F-Series is tricky - it might be the highest selling car in the country, but fatalities also depend on where it's driven. If most of the F-Series cars are driven in non-urban areas, I imagine the fatalities will be low.

If we really want to do this, we will have to segment the "safety baseline" based on the environment it's targeted towards and where it's used. If a car is primarily driven in dense urban areas, its safety bar should be higher than a pickup truck. However, if we force a pickup truck to be as safe as a small sedan, it might not be able to perform its main job (being a good pickup truck) well.

We can argue as a second order effect - if Ford F-series gets lower fatalities, and it gets government subsidies, it will get cheaper and people might buy it for urban environment, resulting it's fatalities going up (as it's not actually a safer car, it was just driven in sparse environments). But now we are just playing with incentives without lowering the actual fatalaties.

We already have standardized tests for this (crash test ratings) - we should invest more in these tests so they reflect the real world better. The hypothesis would be that these ratings will effectively reduce the overall fatalaties, and help people make better decisions.

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