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> Getting a better risk estimate doesn't get you closer to "not having insurance", but rather closer to "perfect insurance" where everyone gets a distribution t

by croon 7y ago

> Getting a better risk estimate doesn't get you closer to "not having insurance", but rather closer to "perfect insurance" where everyone gets a distribution that exactly matches their risk profile. You say "Quite the opposite", and proceed to rephrase the same thing as GP said, except for the conclusion, which also is the same thing, yet you claim it isn't. Not having insurance IS "perfect insurance", in that you pay exactly your own costs, with the added benefit of having no overhead. Most of us don't want that though, in the same way as we don't want children to have to pay their own healthcare, or chronically debilitated people to die to darwinism (whether we succeed here is another point). But a perfect "risk estimate" also happens to be the same thing as prescience, and if we had that we wouldn't need insurance for other reasons. Not having insurance = paying for yourself = distribution by exact risk profile.

unpopular42 7y ago
No, you miss the point. Not having insurance means losses follow your exact risk distribution, with a non-zero risk of a catastrophic loss. Having a perfect insurance means your losses follow a distribution with the same average as your risk profile suggests (+premium), but much lower variance and with zero density on the higher end, meaning you never have a catastrophic loss.
- zAy0LfpBZLC8mAC 7y ago
  > No, you miss the point. Quite the contrary. > average And that right there is where you are hiding all your assumptions. There is no such thing as "your risk profile", there is only your risk profile according to some risk model, which approaches what actually will happen to you individually the more detailed you make it and the better your predictive capabilities get, because as you do that, you are shrinking the pool of individuals that this average is calculcated over, approaching only you as one individual in the limit, at which point the average is the same as the actual thing. > and with zero density on the higher end, meaning you never have a catastrophic loss. Also, that's not a thing.
  - leetcrew 7y ago
    if I flip a coin, I know exactly the odds of getting heads, but I don't know whether I will get heads unless I can exactly predict the future state of the world. if I had this magical ability, it would still be worth paying me a premium to tell you so you would know how much to save.
    - zAy0LfpBZLC8mAC 7y ago
      > if I flip a coin, I know exactly the odds of getting heads, but I don't know whether I will get heads unless I can exactly predict the future state of the world. No, that is a fundamental misunderstanding of what odds are. Odds are not a property of a system, odds are a description of your knowledge about that system. There is no such thing as "odds of the system", the odds for the same system can be vastly different for different observers. If you know how to control the coin, then the odds for you are almost 1:0 for your intended face. For the person next to you who doesn't know you, it's probably 0.5:0.5. For the person that has watched you for a while, it might be 0.6:0.4, if that's the ratio of the faces that you flip (intentionally). All for the exact same system at the exact same moment. Also, a binary distinction between "having no clue" and "perfect predictions" is not useful. While perfect predictions are the limit of an ever refined model, there are many steps in between a useless model that gives random predictions and a model that makes no mistakes whatsoever.
deleted 7y ago
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by croon 7y ago

unpopular42 7y ago

No, you miss the point. Not having insurance means losses follow your exact risk distribution, with a non-zero risk of a catastrophic loss. Having a perfect insurance means your losses follow a distribution with the same average as your risk profile suggests (+premium), but much lower variance and with zero density on the higher end, meaning you never have a catastrophic loss.

zAy0LfpBZLC8mAC 7y ago
> No, you miss the point. Quite the contrary. > average And that right there is where you are hiding all your assumptions. There is no such thing as "your risk profile", there is only your risk profile according to some risk model, which approaches what actually will happen to you individually the more detailed you make it and the better your predictive capabilities get, because as you do that, you are shrinking the pool of individuals that this average is calculcated over, approaching only you as one individual in the limit, at which point the average is the same as the actual thing. > and with zero density on the higher end, meaning you never have a catastrophic loss. Also, that's not a thing.
- leetcrew 7y ago
  if I flip a coin, I know exactly the odds of getting heads, but I don't know whether I will get heads unless I can exactly predict the future state of the world. if I had this magical ability, it would still be worth paying me a premium to tell you so you would know how much to save.
  - zAy0LfpBZLC8mAC 7y ago
    > if I flip a coin, I know exactly the odds of getting heads, but I don't know whether I will get heads unless I can exactly predict the future state of the world. No, that is a fundamental misunderstanding of what odds are. Odds are not a property of a system, odds are a description of your knowledge about that system. There is no such thing as "odds of the system", the odds for the same system can be vastly different for different observers. If you know how to control the coin, then the odds for you are almost 1:0 for your intended face. For the person next to you who doesn't know you, it's probably 0.5:0.5. For the person that has watched you for a while, it might be 0.6:0.4, if that's the ratio of the faces that you flip (intentionally). All for the exact same system at the exact same moment. Also, a binary distinction between "having no clue" and "perfect predictions" is not useful. While perfect predictions are the limit of an ever refined model, there are many steps in between a useless model that gives random predictions and a model that makes no mistakes whatsoever.

deleted 7y ago

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