Global climate change will influence human health and well-being.  Heat related deaths will mount as heat waves become more severe. Rising sea levels will threaten coastal cities and their fresh water supplies. Greater severity of storms and forest fires will put more people at risk. Certain insect vectors that carry human diseases will extend their ranges to higher latitudes and altitudes. Warmer temperatures and altered precipitation patterns will shift food production. Policies to abate greenhouse gases will likely force people to spend more time at routine tasks such as commuting to work, heating water, and discarding wastes.
Economic assessments of human welfare depend on complex value judgments. What is the value of a human life? How important is quality of life and how much money is involved?
Value of Statistical Life
A standard measure for the monetary value of a human life, the so-called value of statistical life, estimates what society is willing to pay for reducing each member’s risk of fatality by a small amount.  Planners use hedonic price or contingent valuation analyses to estimate values of statistical life. Hedonic price analyses examine what firms pay employees as a function of the risk of fatalities in different industries or jobs (Figure 10.23). Contingent valuation analyses survey the willingness of people to pay for decreasing the risk of fatalities. For example, respondents indicate whether they would pay $10 for the reduction in risk from two deaths per 10,000 people to one death per 10,000 people. If 100,000 people would be willing to pay $10, the value of statistical life would be $1 million ($10 multiplied by 100,000).  Estimates of the value of statistical life from such surveys are highly variable. Various governmental agencies rely on different meta-analyses of surveys. The air pollution branch of the U.S. Environmental Protection Agency recently lowered their value of statistical life from $8.0 million to $6.9 million.  This has a large effect on policy. For example, this branch in 2005 estimated that the U.S. Clean Air Interstate Rule provided $130 billion (in year 2008 $U.S.) in annual health benefits (U.S. Environmental Protection Agency 2005). With their new value of statistical life, annual health benefits of cleaner air decline to $112 billion.
Quality of Life
One common approach for assessing the cost effectiveness of medical treatments is the quality adjusted life year.  This measure takes into account changes in both human life expectancy and quality of life. EuroQol, a network of European researchers, has developed a survey that ranks quality of life on five issues: mobility, pain/discomfort, self-care, anxiety/depression, and general activities such as those involved in work, study, housework, and play.  For each issue, respondents choose one of three levels: “no problems,” “some problems,” or “major problems.” Responses to the survey yield composite scores that range from 0.0, which indicates that a person is as good as dead, to 1.0, which indicates a person has no health and happiness problems. To compare cost effectiveness of alternative treatments, one divides their costs by the quality-adjusted life years. A quality-adjusted life year, if one estimates the monetary value for a life year, can provide a measure of human welfare for cost–benefit analyses of environmental policies. This measure differs from the value of statistical life in many respects, however.  For example, quality-adjusted life year explicitly evaluates quality of life but assumes that it is independent of longevity, whereas value of statistical life empirically determines the relationship between quality and longevity. Nonetheless, both measures tend to reach similar conclusions about policies that impact mortality. 
Time = Money
Time spent at work has a well-defined market value equal to wages plus benefits. Time spent at other activities may have direct market equivalents. For example, some people pay others to do their laundry or to change the oil in their vehicle, and so one can estimate the value of the time saved from the cost of these services. Other activities may be more difficult to evaluate. Time spent commuting to and from work or traveling for personal reasons has no direct market value, so planners use revealed preference or stated preference techniques to survey the real or hypothetical choices of travelers between faster, pricier modes and slower, cheaper modes. For example, if a traveler selects a train over a bus when the train journey takes 2 hours at a cost of $30 and the bus trip takes 3 hours at a cost of $20, the traveler values their travel time at $10 per hour because they are willing to spend an additional $10 to save an hour of travel time. All of these factors influence cost–benefit analyses of environmental policies that involve transportation.
 Gamble, J. L., ed. (2008) Analyses of the Effects of Global Change on Human Health and Welfare and Human Systems, Final Report, Synthesis and Assessment Product 4.6. U.S. Climate Change Science Program, U.S. Environmental Protection Agency, Washington, D.C., http://downloads.climatescience.gov/sap/sap4-6/sap4-6-final-all.pdf.
 Dockins, C., K. Maguire, N. Simon, and M. Sullivan (2004) Value of Statistical Life Analysis and Environmental Policy: A White Paper, U.S. Environmental Protection Agency, Washington, D.C., http://yosemite.epa.gov/ee/epa/eerm.nsf/vwRepNumLookup/EE-0483?OpenDocument.
 Kochi, I., B. Hubbell, and R. Kramer (2006) An empirical Bayes approach to combining and comparing estimates of the value of a statistical life for environmental policy analysis. Environmental&Resource Economics 34:385-406 doi:10.1007/s10640-006-9000-8.
 Borenstein, S. (2008) An American life worth less today. Associated Press, July 10, 2008.
 Phillips, C. and G. Thompson (2001) What is a Qualy?, Vol. 1, No. 6, Hayward Medical Communications, http://www.medicine.ox.ac.uk/bandolier/painres/download/whatis/QALY.pdf.
 Hammitt, J. K. (2002) QALYs versus WTP. Risk Analysis 22:985-1001.
 Hubbell, B. J. (2006) Implementing QALYs in the analysis of air pollution regulations. Environmental&Resource Economics 34:365-384 doi:10.1007/s10640-004-7437-1.
This is an excerpt from the book Global Climate Change: Convergence of Disciplines by Dr. Arnold J. Bloom and taken from UCVerse of the University of California.
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