People are more willing to pay for insurance against low-probability disasters when the risks are ambiguous rather than known, due to greater worry about ambiguous risks. An experiment measured people's willingness to pay for insurance covering risks ranging from 1 in 5,000 to 1 in 5. It found that willingness to pay was higher and fewer people refused to pay anything when risks were ambiguous rather than precisely defined. Worry had a greater impact on willingness to pay than subjective probability estimates for small-probability risks. Changing the risk level by a factor of 1,000 had no significant effect on willingness to pay.

1. Protecting Against Low-Probability Disasters
The Role of Worry
Rakesh Sundru
0909424

2. Introduction:
Insurance is paid by the customer , to the providing company, only
because we are ambigious.
There is relatively higher importance of worry, compared to our
confidence in ourself.
Disasters happen if we don't opt for insurance against low probability
issues or accidents.
Willingness To Pay (WTP) is the answer to ambigious i.e, for common
folk, and here is where the company profits.

3. Classification:
Using an experiment , there are Questions that need to be studied
:The study is as follows...
Nature of the experiment
Sample
Experimental Conditions
Nature of the risk and timing
Eliciting willingness to pay for insurance
Eliciting subjective probability estimates
Eliciting the level of worry

4. Results:
General considerations
Willingness to pay and subjective probabilities in the
different experimental treatments
Comparing relative impact of worry and subjective
probability using elasticities
Ruling out alternative explanations of the impact of worry

5. Median willingness to pay across treatments
Ambiguity Known risk Kruskal–Wallis
test between
ambiguous and
known risk (df=1
Low risk (1/5000), 100DMa 10DMb p = 0.0001
separate insurance
policies
Low risk (1/5000), one 80DMc 5DMd p = 0.0002
insurance policy
High risk (one in five), 120 DMe
separate insurance
policies
Kruskal–Wallis test p=0.72f
between low and high
risk with separate
insurance (df=1)

6. Share of subjects with WTP= 0 across treatments
Ambiguity Known risk Kruskal–Wallis
test between
ambiguous and
known risk (df=1
Low risk (1/5000), 13%a 36%b p = 0.0001
separate insurance
policies
Low risk (1/5000), one 20%c 35%d p = 0.04
insurance policy
High risk (one in five), 13e
separate insurance
policies
Kruskal–Wallis test p=0.94f
between low and high
risk with separate
insurance (df=1)

7. Low risk (1/5000), 1/61 1/35 1/37 p = 0.0002
separate insurance (N = 10) (N=68) (N=78)
policies
Low risk (1/5000), one 20%c 35%d p = 0.04
insurance policy
High risk (one in five), 13e
separate insurance
policies
Kruskal–Wallis test p=0.94f
between low and high
risk with separate
insurance (df=1)

8. Answers to the questions posed......
1..
When the probability of a loss is ambiguous, fewer
individuals specify WTP = 0 than with exact
probabilities.
Those who are willing to purchase coverage pay
considerably more for insurance when the probability is
ambiguous than when it is exact. Both differences are
large and statistically significant.

9. 2....
The relative importance of worry is much larger than
that of subjective probability for WTP for insurance
when the probability of a disaster is small as indicated
by a comparison of the two relevant elasticities.

10. 3....
The comparison of WTP in situations differing by a
factor of 1000 in loss probabilities leads to a non-significant
effect on WTP.

11. Thank you