Measuring Benefits

1. Measuring Benefits How much pollution is too much?

2. National Center for Environmental Economics USEPA • Repository of technical expertise regarding benefit and cost analysis

3. Types of Benefits of Environmental Policies • Human health • Reduced risk of death • Reduced risk of sickness • Ecological improvements • Marketed products (food, fuel, fiber, timber) • Recreational activities • Ecosystem functions (climate moderation, biodiversity) • Nonuse values (aka existence values; specie and ecosystem specific) • Aesthetic improvements • Reduced damages to materials (soiling, corrosion)

4. Benefits and channels of impacts

5. Environmental Risk and Human Health • ‘Risk’ exists when one can assign a probability to the chance that an event will occur. • Two elements to environmental risk: • The probability of an unfavorable event, and • The severity of the event if realized.

6. Environmental Risk • Overall risk assessment of a pollutant: actual risk to exposed individuals (probability) * number of people exposed. • Low risk pollutants may have a high risk assessment if many people are exposed. • High risk pollutants may rank low if few people are exposed.

7. Relative environmental risks (EPA)

8. Risk aversion • Most people are risk averse: a risk averse person is more likely to choose a certain payoff over a fair bet. • For the risk averse, a potential gain in income does not create a proportional increase in welfare. • And a loss of income causes a disproportional loss of welfare.

9. Risk aversion • For the risk averse, a $20,000 increase in wealth has less affect on welfare than a $20,000 decrease in wealth. • As a result, people value ways to avoid risk. • Risk averse people will give extra value to polices that would avoid natural disasters.

10. Valuing reduced risk of death • Three primary methods of valuing reduced risk of death: • Wage-risk studies: infer value of a life from wage and risk tradeoffs involving on-the-job risks, • Averting behavior studies: infer value of life by examining purchases that affect mortality risk, such as bicycle helmets, and • Stated preference studies: surveys that ask about WTP for reduced mortality risk.

11. Valuing reduced risk of death • What happened to the value of foregone earnings as a measure of the value of life? • Method has been rejected. • Not based on WTP for small risk reduction.

12. Characterizing mortality effects • Reduced mortality is measured as ‘statistical lives saved’. • Aggregation of many small risks over an exposed population. • Formula: ‘statistical lives saved’ = reduction in risk per individual * size of population.

13. Statistical lives saved • Example: A policy reduces risk of mortality by one in 10,000 for each individual. • The population affected by the policy is 100,000. • ‘Statistical lives saved’ = (1/10,000)*100,000 = 10 persons. • 10 premature deaths would be averted by this policy.

14. Reduced risk of death • Q: How do people value an increase in the risk of death? • A: The compensation they would accept in exchange for a small increase in the likelihood of death.

15. Reduced risk of death • Formula: value of the risk of mortality = WTA / change in risk of death. • Example: suppose a construction worker is willing to work in an occupation that pays $1,000 more, but has a 3 in 10,000 chance of death compared with 1 in 10,000 for other occupations. • Value of mortality = $1,000 / ((3-1)/10,000) = $5 million.

16. Reduced risk of death • $5 million is the value of a statistical life (VSL) for a construction worker. • This is how much construction workers are willing to trade for one of their lives. • Value of a life on average. • Could potentially be used in environmental benefits studies.

17. Application: valuing reduced mortality risks to children • Uses estimates from averting behavior to measure the statistical value of life for children. • Only such study.

18. Application: valuing reduced mortality risks to children using bicycle helmets • Infers valuation through purchase of safety products (averting behaviors). • Purchase product if value for the reduced risk is greater than the cost of the helmet. • VSL (value of statistical life): cost of helmet / change in the probability of death due to helmet purchase. • Lower bound for VSL.

19. Application: valuing reduced mortality risks to children • Determining the annualized cost of a helmet • Assume helmet lifetime is four years. • Use an average of helmet market prices. • Ages 5-9 and 10-14: $6.51 per year. • Ages 20-59: $10.76 per year.

20. Application: valuing reduced mortality risks to children • Determining reduced risk of mortality Risk reduction = deaths prevented / bike riding population.

21. Application: valuing reduced mortality risks to children • VSL estimates (assume helmet worn 100% of time) • Ages 5-9: • VSL = $6.51 / 0.0000044 = $1.5 million. • Ages 10-14: • VSL = $6.51 / 0.0000061 = $1.1 million. • Ages 20-59: • VSL = $10.76 / 0.0000054 = $2.0 million.

22. Application: valuing reduced mortality risks to children • What if helmets worn less than 100% of the time? • Reduction of risk is much lower. • But resulting VSL is higher. • Ages 5-9 • 55.3% always wear a helmet instead of 100%. • Deaths prevented = 63.06 * 0.553 = 34.87. • Reduction of risk = 0.00244*10-3. • VSL = $6.51 / 0.00000244 = $2.7 million.

23. Application: valuing reduced mortality risks to children • VSL when helmets worn less than 100% of the time (55.3%) is $2.7 million. • Recall than VSL is $1.5 million when helmets worn 100% of the time. • Why the difference?

24. Reduced risk of sickness • Q: How do people value a reduction in risk of sickness? • A: The sacrifice they would make to improve the chances of not being sick. • Formula: The benefit of risk reduction = WTP / change in risk of illness.

25. Valuing reduced risk of sickness • Example: I am willing to pay $10 a year to reduce the risk of knee surgery from 5 in 1,000 to 2 in 1,000. • The benefit to me of reducing the risk of illness: $10 / ((5-2)/1,000) = $3,333. • This is the implied value of avoiding illness.

26. Methods for valuing morbidity • Desired measure: WTP to reduce the risk of illness. • Ideally, should capture the following: • Costs of averting behavior, • Mitigating costs (cost of disease treatment), • Indirect costs (value of lost time), and • Value of discomfort, pain, suffering. • The goal is to measure the total impact of illness on individual welfare or utility.

27. Costs of averting behavior • Actions people take to avoid the risks and consequences of the reduction of environmental quality. • Examples: • Purchase of air filters, • Boiling water, • Preventative medical care and treatment.

28. Valuing time (digression) • Lost time due to illness: • Work time, • Leisure activities, and • Production of household goods and services (cooking, laundry, etc). • Measure for work time: wages plus benefits. • Measure for non-work time: after-tax wages.

29. Wage-risk study • Probability of being killed by a felon: • Public: 0.3 in ten thousand (0.3*10-4). • Policeman: 1.3 in ten thousand (1.3*10-4). • Suppose police receive $700 more in income than the average worker (after adjustments).

30. Wage-risk study • VSL = WTA risk / change in risk. • WTA risk = $700 per year. • Change in risk = (1.3-0.3)/10,000 • VSL = $700 / ((1.3-0.3)/10,000)) = $7.0 million. • On average, police are willing to trade $7 million for one of their lives.

31. Issues with VSL • Is $7 million an accurate measure of the value of life for environmental studies? • Three issues: • 1) Accurate information: do police and other workers accurately estimate the mortality risk in their jobs? • 2) Selection bias: policemen may be more comfortable with risk, not representative of other occupations, and • 3) Involuntary nature of risk: some occupations voluntarily accept risk for more compensation; environmental damage is usually involuntary; who has the right? • Studies use regression analysis to attempt to control for these issues.

32. Summary • Most people are risk averse. • The value of a reduction of the risk of sickness or death depends on: • willingness to pay to avoid risk, and • the reduction in risk. • Value of life or sickness can be measured by: • Wage-risk studies, • Averting behavior studies, and • Stated preference studies.

33. Summary • Statistical lives saved = reduction in risk of death per person * number of persons. • Value of life = (WTP or WTA) / (change in risk of death. • Value of reducing risk of sickness = WTP / change in risk of sickness.

34. Summary • Life/sickness measures should capture all of the following: • Costs of averting behavior, • Mitigating costs, • Indirect costs, and • Value of discomfort, pain, suffering

35. Summary • VSL can be used in environmental studies if three issues are dealt with: • Do people have accurate information regarding risks? • Is there selection bias? • Is the risk involuntary?

36. Application: Calculating the value of life Calculating the Value of Life As an economist, you have been doing a project trying to estimate the willingness-to-accept risk on the part of workers. You have gathered data on a variety of blue-collar occupations, ranging from clerical work to truck driving to coal mining. Controlling for age, gender, education, work experience and race, you have uncovered the following relationship:

37. Application: Calculating the value of life • Graph shows roughly $400 in additional wages for each 1/10,000 reduction in mortality risk. • What is the value of a statistical life? • What three assumptions are implicit in your estimate that would affect the application of your figure to environmental damage?

38. Application: Calculating the value of life • VSL = WTA / change in risk • = $400 / (1/10,000) • = $4,000,000. • Result can be generalized to the overall population if we assume: • Workers have accurate information about risks, • The sample of workers is representative of all workers, and • The risk accepted is voluntary. Much environmental damage is not, so this estimate would probably be low.