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Valuing Health Risk Reductions

Valuing Health Risk Reductions. W. Douglass Shaw, Texas A&M University Delivered by DA Bessler October 7, 2008. Why Care?. Every day decisions are made involving risks of life and death

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Valuing Health Risk Reductions

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  1. Valuing Health Risk Reductions W. Douglass Shaw, Texas A&M University Delivered by DA Bessler October 7, 2008

  2. Why Care? • Every day decisions are made involving risks of life and death • The federal government regulates many of these decisions through FAA, NTSB, DOE, EPA, etc. – many require a look at B-C ratios • What is an acceptable when constructing the B-C ratio? • How do deaths figure into the calculations?

  3. Somewhat Controversial Economic Ideas • What is the “value” of a human life? • The Value of a statistical life, or VSL • What is the value of reducing morbidity or illness? • (To whom? • The patient? The family?)

  4. Risks • Almost everything we can think of relating to health, illness, terrorism, security involves a risk • We do not get sick with a disease and die with certainty (from a particular disease) • Rather: we have risks of dying or getting ill from viruses, diseases, etc. • Worst case is when we don’t know (cannot measure) the risks • Assume we do and these are π

  5. Objective vs. Subjective Risks • Objective assessments from “experts” vs. your own subjective assessment • What are the annual increases in risks of the chance of death below? Write down each • smoking 1.4 cigarettes per year • eating 100 charcoal broiled steaks • eating 40 TB of peanut butter • Traveling 10 miles by bicycle • Drinking ½ liter of wine • from accident if you live within 8 km of a nuclear reactor, for 50 years

  6. Answer… • They are all the same • one in one million, per year • There is a great need for risk communication, assessment with public feedback • People react to what they believe

  7. (Environment and Health) • Environmental Degradation • Air pollution – CO, Ozone affects respiratory system, heart/cardiovascular system • Water – toxics (e.g. carcinogens) or bacteria, microorganisms • “q” is env. quality, H is health “production” function • Utility = f (H, X, Z) Z are activities, X goods • H = h(q, Exp, other) Exp = expenditures on H

  8. The VSL • EU(π,Y) = expected utility, Y is income • Assumes two states, alive (a) and dead (d) • = πUa(Y) + [1- π]Ud(Y) • (-∂Y/ ∂ π) = marginal rate of substitution is the tradeoff between money and survival probability (risk), holding utility constant • THIS IS THE VSL

  9. Do you trade money for survival, risks of dying? • Do you ever do anything that is unsafe perhaps because it is convenient, or fun? • Ride your bike? • Eat steak, drink wine/beer? • Drive cars? Fly in an airplane?

  10. So… • Trading time/money for mortality risk or vice versa is something we do all the time, even if we do not realize this • We drive in cars to save time/money

  11. Abstract VSL example • N = 1,000 people • Program reduces risk by 1/1000, or 0.001. • Each person is willing to pay $1,000 for this; total WTP = $1 million • Policy is expected to reduce risk and “save” 1 life (1 in the 1,000 people), so VSL = $1 million

  12. Accepted range in VSL • EPA: assumes VSL is in range of $1 to $9 million • Often uses about $4.5 million (midpoint) • To my knowledge – no current accepted practice on the value of avoided illness or VSI • A current interest of EPA is to find numbers for this

  13. Example: EPA Estimates of air quality risk reduction benefit • Mathech Inc. Study for EPA, 1983 • Response to Reagan’s E.O. 12291 • RIA for tightening air quality stds. For particulate matter • $1.12 billion in reduced mortality • $0.12 billion for reduced chronic morbidity (this probably did not use a “VSI” – statistical illness)

  14. Cost of regulations

  15. How does q change U? • We typically measure q as a “good” so ∂U/∂q > 0 • And assume ∂U/∂Z and ∂U/∂H > 0, but ∂H/∂q > 0, so if q declines, then H declines • Also, we try to assess if ∂Z/∂H > 0, and to what extent (the response or elasticity of activity) • Eg. See asthma study: Yen, Shaw and Eiswerth (Review of Economics of the Household, 2004)

  16. How do people respond to change in q or in risk? • Do nothing – risk adverse health impacts • Increase subsequent expenditures that come later: increased doctor’s visits, medicines, treatment, miss work, die! • Or: • Mitigate Sooner • Defensive Expenditures made now • Avoidance (stay indoors, move away)

  17. What is the value of preventing decline in q, or increase in risk? • Health: Cost of Illness (COI) Approach • Sum up expenditures • Examine Lost wages (work missed) • Calculate increase if q declines • Value = “saved” expenditures • Willingness to Pay (WTP) or minimum willingness to accept compensation (WTA)

  18. Similarly • Could look at cost of avoidance of risk • Risks increase – people change behavior • Travel less, use airplanes less, go out to events less, avoid foods/beverages (drink bottled water only) • Increase expenditures on security and protection • What does this cost society?

  19. Maximum WTP to avoid decline in q, or increase in risk • Q is typically a “public” good • Area under demand curve for q is “consumer’s surplus” (CS) • WTP, related to this public good demand function (it is the CS) • Minimum willingness to accept compensation (WTA) may be preferred measure in some cases (property rights issue)

  20. WTP, continued • Direct method, Stated Preference (SP) • Ask participants in a survey questionnaire • WTP to avoid illness - Key issue in new studies of morbidity (not mortality) • Contingent Valuation Method (CVM) or Approach • Conjoint or Choice Model approach similar to CVM • Indirect method, Revealed Preference (RP) • Ask people what they “do” (example: the Risk Analysis paper – do you treat your well water for arsenic, or not?)

  21. Pro’s and Con’s • COI • simple to use • misses true costs of mitigation and avoidance behavior • misses values for all impacted by an illness who do not actually spend • Or at least those whose expenditures are difficult to observe

  22. Pro’s and Con’s (continued) • WTP • Gets actual “value” of risk reduction • But…Stated - Hypothetical? (if based on stated value CVM or stated choice and conjoint) • Critiques of the CVM • Do people understand the “good” being valued? What about a future illness? • Incentive compatible framework? • If Revealed – harder to do with risks

  23. Alternative to direct WTP: RP Approach • Activities (Z) – we can infer values for changes in q from choices of activities • Go to work • Issue: how productive if working while sick? • Engage in outdoor inactive or active leisure • Engage in home work • Play with children • Sleep, rest, etc.

  24. RP values/shifting leisure (L) demand (shift by increase in quality or risk) P Increased consumer’s surplus (value) D2 D1 L

  25. II. New thoughts about risks • Ambiguity is important in many contexts • We just do not know the risks (pure uncertainty) • Perceived Risks are what matter – Strong evidence of underweighting (arsenic project) • relatively high health risks (still perhaps “Low” probabilities by some standards) • Conventional expected utility model with objective risks will not be particularly useful – might provide benchmark • Develop alternative empirical models

  26. Nuclear Waste Transport/Perceived risks • Riddel and Shaw (2006, Journal of Risk and Uncertainty) • Looked at WTA to bear the increased mortality risk (perceived) for the Yucca Mountain shipping project

  27. Key finding (Nuclear waste transport) consistent in the literature • “Certain” about risk of transport • 734 deaths per 100,000 (average) • “Uncertain” about risk of transport • Females: 486 deaths per 100,000 • Males: 455 deaths per 100,000 • Compare to DOE’s 2 in 10 million! • VSL calculated, within EPA range

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