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

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1

Valuing Health Risk Reductions

W. Douglass Shaw, Texas A&M University

Delivered by DA Bessler October 7, 2008

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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?

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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?)

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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

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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

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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

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(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

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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

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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?

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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

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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

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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

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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)

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Cost of regulations

Cost of Risk-Reducing Regulations that fail a benefit-cost test (source: V. Kip Viscusi, 1996, J. of Economic Perspectives)

Regulation Agency/Yr

Status (final, rejected)

Initial risk Annual lives saved

Cost per life saved ($m, 1984)

Benzene

Arsenic

Asbestos

Radionuclides at DOE facilities

OSHA, 1987, F

EPA, 1986, R

OSHA, 1986, F

EPA, 1984, R

8.8 in 104

2.6 in 104

6.7 in 105

4.3 in 106

3.8

0.09

74.7

0.001

17.10

764.00

53.0

210.0

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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)

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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)

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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)

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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?

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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)

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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?)

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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

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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

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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.

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RP values/shifting leisure (L) demand (shift by increase in quality or risk)

L

P

D1

D2

Increased consumer’s surplus (value)

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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

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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

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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