This article covers a technique to value human life.
Putting a financial value on human life can be a controversial thing for many moral reasons, but in reality there are a number of ways to measure it. Perhaps surprisingly, these techniques are already used in policy evaluation and other areas.
In some industries there is a risk premium of death for work, often paid in the form of hazard pay. This can be utilized to back-door a person’s valuation of their own life through an economic principal called revealed preferences. I’ll describe how the principal works, create an initial rough value for human life, describe weaknesses with this technique and attempt to indicate an improved or adjusted measurement for the value of human life.
Revealed preference says that we can figure out how much you value things through how you act with your money. Sometimes you do things that reveal an implied preference or a subconscious evaluation of a good or service, even if you are not actually aware of your preference for that good or service.
An example would be as follows: You like apples and bananas, but you can’t tell which you like more. Alternatively, maybe you know that you like bananas more but you aren’t sure how much more. We can get a value for this by looking at what you recently bought at the grocery store. You bought 9 bananas and 3 apples. Let’s assume 1 banana cost as much as 1 apple in this example. In that case, you have revealed a 3:1 preference for bananas, which means that you like bananas 3 times as much as or 200% more than the amount you like apples. If a banana cost $1 then you like a banana about $.67 more than you like an apple!
Now let’s take the same principal and apply it to compare preference for a job with hazard pay to a job with less or no hazard pay. What we will find is that the difference implies a financial value for that chance of death. If a person will accept money for a higher chance of death, it implies a value of life.
Let’s get specific and look at a common example of hazard pay, in the military. This article puts hazard pay at $225 for working in a combat zone. In reality hazard pay varies in the military on a variety of factors, but that is not far off from what many will receive so it is a pretty good general number for us to use in an example. You have the choice to enter or not enter the military. Let’s assume for a moment that all jobs in the military are hazard pay receiving. This article, by the same source as above for internal consistency, gives information on death risk according to the following:
On average, 50 military members are killed in action and 481 are wounded in action each month in Iraq…there are about 133,000 troops deployed to Iraq at any given time.
This indicates a death risk of about 50/133,000. The important value in my equation is perceived chance of death, which can be different from real chance of death, but let’s assume in this example the two values are equal. If you enter the military you demonstrate that you value your life at less than or equal to the value of Y|Y =
Y = Revealed Value of Own-Life Preference for a Risk Taker = (Accepted Risk Payment)/(Perceived Chance of Death) = $225/(50/133000) = $598,500
This means that the average military member reveals a valuation of their own life of about $598,500 on average.
Let’s talk about weaknesses with this technique. There are 3 points I want to bring up.
- As I already mentioned, this calculation involves perceived chance of death, not actual chance of death. In the ideal world the values are equal, but in the real world they are often not. Since we do not know if the perception effect will under or overvalue our original evaluation we are not going to make an adjustment to our formula, but we should keep this mind.
- We may call people who accept the risk premium payment risk takers. Risk takers will value their life at less than those who are risk averse, and also at less than the full population average, which will be in between the risk taker and risk averse normal values. This implies that the average own-life valuation for risk takers is less than the average population own-life valuation. To adjust, we assume that the average own-life preference for risk averse players is twice the average of the revealed preferences from risk takers, because this follows from the risk minimizing hypothesis from statistical ignorance, 0<pAverse<pTakers, => E(pAverse) = .5*pTakers.
- Forecasting with this method is sensitive to all the weaknesses and difficulties of statistical forecasting. Specifically, a prediction interval for an individual is adjusted to be much wider than the confidence interval for a group average. Related to prediction of individual preference from group preference, I would like to comment on the expected distribution shape. I would expect a highly nonlinear and possibly normal distribution, complete with a very wide range of observed values. I think you may even see some negative evaluations of own-value life, and I expect these observations to be highly consistent with suicidal tendency or extreme risk taking and recklessness.
Adjusted formula for average expected own-life value, NOT for individual observation prediction of own-life value:
Pbar = .5*Ybar| Ybar = average(Y)
The idea is that Pbar can be used for a somewhat objective value of a life in financial terms.