The Scarily Inconsistent Statistic that Could Cost Human Lives

When looking at the value of anything, we can take two approaches. The first approach: straight forward reasoning. If a bottle of water costs slightly over two cents to make, then its value should be right around that amount. The second: the free market approach. If people are willing to pay $4.25 for a bottle of water at the movie theater, then the bottle of water should be valued at $4.25.

When calculating the Value of Statistical Life, we take a free market approach. The most common method used for calculating VSL is called Willingness to Pay (WTP). Just as it sounds, the WTP method asks people the dollar amount they would be willing to pay to get rid of something that has a risk of killing them. Another approach is Willingness to Accept (WTA). This approach involves stating how much money one would accept for an additional risk of death. In reading meta-analyses on the VSL, I found that WTA VSL estimates tend to be much higher than WTP VSL estimates. Why? Because when you are talking about how much money you are willing to accept, you are not constrained by your financial situation.
What matters is not how big the difference is between methods, but instead, that there is a difference. Just to refresh, the VSL is used to calculate the benefit of regulations that save human lives. This is a concept that is of the upmost importance.  The fact that there is a difference in results between methods exposes the true problem with tying a free market approach to a human life: humans can be irrational.
We will buy a water bottle at the movie theater for $4.25, but we would never buy a bottle of water at that price in a supermarket. Our willingness to pay for goods and services fluctuates based on factors as basic as our mood or the weather. Humans’ willingness to pay for goods can be irrational and fluctuate greatly, and that is understood in economics. The problem occurs when we take something that is irrational and treat it as a perfectly scientific calculation, yet even worse, use that ‘calculation’ to make decisions that could cost human lives.
One could argue that a ‘rationality adjustment’ for VSL is possible. Nonetheless, the mere idea of adjusting the VSL is hypocritical. By basing the VSL on what people are willing to pay, we are essentially saying, “using the free market, we can get the best VSL.” However, when we adjust it, we are saying, “Well actually, the free market is kind of right, but not entirely, so we need to change it.” This forces us to answer an awkward question: does it really matter what people are willing to pay to reduce their risk of death? The EPA would answer “yes”, citing the use of studies using the WTP method. On the other hand, any adjustment in the VSL, even a small one, demonstrates the idea that those stating their WTP are wrong in some way. Even if an adjustment is deemed beneficial, who decides how much or how little? Any adjustment pulls large amounts of credibility away from the already-shaky VSL concept.
The above paragraphs bring me to one conclusion: the VSL, at this stage, is too inconsistent and subjective to be used for something as cherished as human life. I understand that we need some way to create the costs-benefit analysis of a life-saving regulation, but after my research, I firmly believe using a highly variable statistic does more to demean human life than protect it. We need to develop more consistent methods of calculating VSL before using it in our regulatory evaluations.