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As to the Good Samaritan problem:

Poor people are both more likely to remain where they are irrespective of government insurance and less likely to build or invest in risky areas because of such "free" insurance.

The fairly wealthy John Stossel was on O'Reilly the other day admitting that he built a beach house where it could be destroyed based on a calculation regarding "free" government insurance.

The question is how can we get an insurance system, consistent with the rule of law, that leaves our Stossels out to dry while protecting, say, the New Orleans native small business owner.


When I started thinking about the "good samaritan paradox" and the New Orleans situation, data got me thinking about California. Without seeking it, I also hear people speculating that an earthquake in CA might be next.

A lot of people have moved to CA. Consider the pouplation growth in San Francisco relative to New Orleans. People in CA tend to use leverage. Houses are expensive. Is all of this insured? How do insurance companies assess probabilities of "rare" events?

The theory of the fat tails is interesting. Maybe the normal distribution does not always apply.


Sam J.

Cost benefit analysis is key for determining a cause and effect projection. However, it is only a tool for informing what becomes an ethical decision right? Given that math is the language of economics; how might one plot the ethical impact of a given decision? Or would it even be relevant (ever) if benefit was always measured in relation to the greater goodÔøΩ
Specifically, how would one, and has anyone, factored the relationship between the amount of government aid provided New Orleans, and its' subsequent effect on citizens' trust/faith-in the government throughout the entire country? And finally, what effect that might on our economy?
Perhaps I am a dreamer, but if all monetary transactions were done after calculating the balanced utility for the self and man we could help mankind as we helped ourselves.


Insurance companies openly discuss adverse selection and moral hazard as the primary way of evaluating policies.

I was interested how Becker would work through these issues privately then publicly.

How would he approach a situation where the private insurance company as the underwriter feels the risk is too high to insure?

Then, how would he evaluate the government insurance program?

Does a government insurance program stabilize and add liquidity to the market as it did with mortgages in the thirties?

For Posner, I was wondering if he had insight to particular cases concerning insurance clauses. Obviously, an insurance contract is very involved.

Polinisky at Stanford maintained that law students are under exposed to insurance law. This led to a gap in the law and economics analysis.

The question remains how to narrow this gap, and what cases would we look to in evaluating Katrina?


If people are 'touched' its not by often by some hint of divine inspiration. Rather, disasters test the strength of social solidarity. During WWII it was strong in England, and weak in France. In France tragedy impacts the individual, and if something happens to a child that impacts his parents.(good for rotten kid, usually, bad for too many others) What happens to citizens does impact a figurehead, i.e. George W. Bush is very sorry. However, this is stylized sentimentality. Parents are over-aggressive in their attempt to help their children because they want to artificially prolong life. To the detriment of the greater. Frankly, if New Orleans were only a house, I wouldn't care, but a lot of people love New Orleans and they care.

If the government doesn't step in to help rebuild New Orleans only because an accident occurred. I think that's wrong. Slipping on an icy patch does not necessarily make a person a bad walker. I really think that its such a prized city that its devastating to think that such a city can be relocated at will. If they try, it would be pathetic. Besides, the 'cult of deathers,' the laughing liberals who are all about universal morality. Want New Orleans to die.


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