Richard H Thaler - Misbehaving- The Making of Behavioral Economics (epub)

y Schelling’s analysis, without asking anyone to play Russian roulette. I
searched but could not find any source of occupational mortality rates.
My father, Alan, came to the rescue. Alan was an actuary, one of those
mathematical types who figure how to manage risks for insurance companies. I
asked him if he might be able to lay his hands on data on occupational mortality.
I soon received a thin, red, hardbound copy of a book published by the Society
of Actuaries that listed the very data I needed. By matching occupational
mortality rates to readily available data on wages by occupation, I could estimate
how much people had to be paid to be willing to accept a higher risk of dying on
the job.
Getting the idea and the data were a good start, but doing the statistical
exercise correctly was key. I needed to find an advisor in the economics
department whom I could interest in supervising my thesis. The obvious choice
was the up-and-coming labor economist mentioned earlier, Sherwin Rosen. We
had not worked together before, but my thesis topic was related to some
theoretical work he was doing, so he agreed to become my advisor.
We went on to coauthor a paper based on my thesis entitled, naturally, “The
Value of Saving a Life.” Updated versions of the number we estimated back then
are still used in government cost-benefit analyses. The current estimate is
roughly $7 million per life saved.
While at work on my thesis, I thought it might be interesting to ask people
some hypothetical questions as another way to elicit their preferences regarding
trade-offs between money and the risk of dying. To write these questions, I first
had to decide which of two ways to ask the question: either in terms of
“willingness to pay” or “willingness to accept.” The first asks how much you
would pay to reduce your probability of dying next year by some amount, say by
one chance in a thousand. The second asks how much cash you would demand
to increase the risk of dying by the same amount. To put these numbers in some
context, a fifty-year-old resident of the United States faces a roughly 4-in-1,000
risk of dying each year.
Here is a typical question I posed in a classroom setting. Students answered
both versions of the question.
A. Suppose by attending this lecture you have exposed yourself to a rare fatal disease. If you
contract the disease you will die a quick and painless death sometime next week. The chance you
will get the disease is 1 in 1,000. We have a single dose of an antidote for this disease that we will
sell to the highest bidder. If you take this antidote the risk of dying from the disease goes to zero.
What is the most you would be willing to pay for this antidote? (If you are short on cash we will
lend you the money to pay for the antidote at a zero rate of interest with thirty years to pay it
back.)