GEF Caspian EVE 2005/UNDP and WBI Morteza Rahmatian, Value of Statisical Life Session 10A Value of...

Caspian EVE 2005/UNDP and WBI Morteza Rahmatian, Value of Statisical Life

GEF

Session 10A

Value of Statistical Life

Morteza Rahmatian

California State University, Fullerton

[email protected]

Ashgabad, November, 2005

GEF

Quantitative Risk Assessment (QRA) and the Value of a Statistical Life

The dominant benefit identified in benefit/cost analysis of the Clean Air Act (1970-90) was reduced premature mortality due to reductions in particulate matter, which contributed $16.6 trillion of the estimated mean benefits of $22.2 trillion (in constant 1990 dollars), or approximately 75 percent of the total economic benefit.


GEF


But how do researchers go from risk assessment of a pollutant such as particulate matter to the economic value of premature mortality prevented by regulation?

One method is the value-of-statistical-life (VSL) approach. Warning: Controversial…


GEF


Economic estimates of the value of a statistical premature death usually use information on (i) people's willingness to pay for a reduction in the probability of premature death, or (ii) willingness to accept higher pay in return for higher risk.

1. Stated preference approach: Survey people on willingness-to-pay to avoid a given risk.

2. Revealed preference approach: Observed wage-risk relationships in actual jobs.


GEF

Quantitative Risk Assessment (QRA) and the Value of a Statistical Life (VSL)

Suppose that a wage-risk study estimates that when the annual risk of premature death on the job increases by 0.0001 (1 in 10,000), workers receive an annual wage premium of $700 per year as compensation for this added risk. Assume that all other work characteristics are held constant. If we assume that those workers are fully informed and the labor market is competitive, then what is the implied VSL?


GEF


Concept:

Wage premium = VSL × (increased probability of death).

With a bit of algebraic rearranging we get:

VSL = (wage premium) ÷ (increased probability of death).

Plug in our value for increased probability of death (0.0001) and a wage premium ($700). What do you get?


GEF


Based on analysis of 26 wage-risk and hypothetical willingness-to-pay studies, the EPA (1997) estimated a mean value of a statistical premature death avoided to be $4.8 million (in constant 1990 dollars).


GEF


What are some problems or issues associated with VSL estimation?

Here’s one: How can we ethically assign a dollar value to human life?

• If we don’t, then on what basis can a widow(er) sue for economic damages due to wrongful death? Is there no economic dimension to saving statistical lives?

• If we do, then what are we saying about high wage-earner’s lives vs. low wage earner’s lives?


GEF


VSL and high vs. low wage earner’s lives:

Bowland and Beghin (1998) offers a good example of VSL differences across rich and poor countries. They estimated that the value of a statistical life saved in Santiago Chile due to reduced air pollution is approximately $600,000, which is only about 12.5 percent of the $4.8 million value of an American statistical life used by the EPA (1997). The logic of benefit/cost analysis might then suggest locating hazardous life-threatening industrial activity and toxic wastes in the poorest regions of the world, which many would consider an unacceptable example of environmental injustice.


GEF


Other issues associated with VSL estimation:

While most of the 26 VSL studies involved the value of risks to middle-aged working people, those who die prematurely from particulate matter are more likely to be aged and past their working years. Moreover, job-related risks are more likely to be borne voluntarily, and involve the risk of sudden and catastrophic death, while pollution-related risks are borne involuntarily and involve the risk of longer periods of disease and suffering.


GEF


While there are many problems with the VSL approach, simply ignoring the economic cost of premature death and leaving it out of benefit/cost analysis leads to a substantial underestimate of the benefits of environmental conservation and restoration.

An alternative approach taken by Tengs et al. (1995) is to evaluate the cost of regulatory intervention per statistical life-year saved by the intervention. This type of analysis allows policymakers to allocate regulatory resources to those interventions that generate the most statistical life-years saved per dollar of intervention.

GEF Caspian EVE 2005/UNDP and WBI Morteza Rahmatian, Value of Statisical Life Session 10A Value of...

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