Final Report 

VALUATION OF REDUCTIONS IN HUMAN HEALTH

SYMPTOMS AND RISKS

Volume 1 

EXECUTIVE SUMMARY 

 George Tolley 

 Lyndon Babcock 

and 

 Mark Berger 

 Anthony Bilotti 

 Glenn Blomquist 

 Michael Brien 

 Robert Fabian 

 Gideon Fishelson 

 Charles Kahn 

 Austin Kelly 

 Don Kenkel 

 Ronald Krumm 

 Tracy Miller 

 Robert Ohsfeldt 

 Sherwin Rosen 

 William Webb 

 Wallace Wilson 

 Martin Zelder 

The University of Chicago 

 Cooperative agreement between the University of Chicago and the U.S. 

Environmental Protection Agency with participation by University of 

Illinois at Chicago, University of Kentucky and University of Wyoming. 

USEPA Grant #CR-811053-01-0 

PROJECT OFFICER: Dr. Alan Carlin 

Office of Policy Analysis 

Office of Policy, Planning and Evaluation 

U.S. Environmental Protection Agency 

Washington, D.C. 20460 

January 1986 
DISCLAIMER

Although funded by the United States Environmental Protection Agency 

under Cooperative Agreement No. CR811053-01, the views expressed in this 

report do not necessarily represent those of the Environmental Protection 

Agency. Mention of trade names or commercial products does not constitute 

endorsement or recommendation for use. 
VALUATION OF REDUCTIONS IN HUMAN HEALTH SYMPTOMS AND RISKS

Abstract of Executive Summary

1. INTRODUCTION 

 The project undertakes an assessment and reconciliation of attempts to 

value reductions in human health risks, and it develops new methods and 

estimates for these values. The report on the project consists of four 

volumes. Volume 1 (this volume) contains the Executive Summary of project 

findings. The Executive Summary is abstracted here. 

2. COMPARATIVE ANALYSIS OF APPROACHES TO VALUING HEALTH RISKS 

 Volume 2 contains a comparative assessment of work on valuing health 

risks. Based on the assessment, a set of interim morbidity and mortality 

values applicable to effects of criteria air pollutants is developed. 

 Following the introduction to Volume 2, section 2.2 presents a model 

for valuing health risk reductions which can be used to compare alternative 

approaches to valuing health risks. Plausible assumptions imply that cost 

of illness and preventive expenditures measures are lower bounds to 

willingness to pay for health risk reductions. Contingent valuation, 

hedonic measures and other valuation approaches are compared conceptually. 

 Section 2.3 gives a critique of econometric evidence on the effects of 

environmental quality on human health. One of several concerns with 

comparability and reliability is how estimates are affected by avoidance 

measures taken by individuals in response to adverse environmental 

conditions. The assessment considers in detail five major empirical studies 

of the effects of air pollutants on mortality. 

 Section 2.4 is concerned with the cost of illness approach to 

measuring health benefits. A contribution of the present project is to put 

estimates of the aggregate cost of illness (medical expenditures and 

foregone earnings) due to morbidity on an individual per case and per day 

spent ill basis. Section 2.4 includes an evaluation of previous cost of 

illness studies. 

 Section 2.5 is concerned with contingent valuation studies in which 

interview estimates are obtained of willingness to pay for health. The 

three major existing contingent valuation studies of morbidity are 

evaluated. 

 In section 2.6, a comparison is conducted of cost of illness 
and contingent valuation benefit measures obtained for a group of 

individuals for a common set of symptoms. The results indicate that 

willingness to pay as revealed through contingent valuation greatly exceeds 

cost of illness. The two measures do not move together in any systematic 

fashion. 

 Section 2.7 considers the household production approach, in which the 

individual produces health by combining his own time and effort with 

purchased goods. Two studies are reviewed that use this framework to 

produce illustrative empirical estimates of willingness to pay for health 

improvements. 

 Section 2.8 reviews the housing market hedonic literature throwing 

light on housing price premiums for air quality. Estimates from this 

literature are used to obtain suggestive upper bound estimates of the value 

of mortality risks. 

 Section 2.9 brings together the foregoing results to arrive at a set 

of health risk values for use in environmental assessments. Interim values 

applicable to air pollution are developed. High, low and medium estimates 

are developed for morbidity conditions and mortality. Medium estimates of 

the value of reducing various types of acute or short term morbidity range 

from $25 to $125 per day. Medium estimates of the value of reduced 

aggravation of previously existing chronic morbidity conditions range from 

$60 to $150 per day. Medium estimates of the value of reduced new incidence 

of chronic morbidity conditions range from $800 per year for uncomplicated 

angina to $60,000 per year for non-fatal cancer. The medium estimates for 

mortality range from $2 million for an unforseen instant death to $4 million 

for a death due to lung cancer. 

3. CONTINGENT VALUATION STUDY OF LIGHT SYMPTOMS AND ANGINA 

 Volume 3 reports on a contingent valuation study conducted as part of 

this project to estimate the benefits of light symptom reductions and angina 

relief. The approach is based on focus group experimentation followed by 

systematic household sampling. 

 Section 3.2 addresses the problem of quantifying reductions in 

symptoms. To cover the range of conditions encountered in environmental 

assessments, respondents needed to be asked about a variety of situations, 

but the variety had to be manageable. Four survey instruments were used. 

Two of the instruments were for relief from seven light symptoms, with one 

instrument pertaining to one day of relief and the other to thirty days of 

re1ief. Two of the instruments were for relief of angina, with one of these 

pertaining to ten days of relief and the other to twenty days. 

 Sections 3.3 and 3.4 explain the structure of the contingent valuation 

instrument. Section 3.5 explains the household sampling procedure, which 

was carried out in Chicago and Denver. 
 In Section 3.6 the empirical results are presented. A relationship 

was found between the number of days a symptom is experienced and the bid 

per day, indicating the existence of increasing marginal disutility of 

symptoms. Independent variables in regressions explaining bids included 

age, education and income, and these generally had postive coefficients. 

 Section 3.7 reports the results of an experimental mail survey where a 

response rate of 48 percent was achieved. Results were corroborative of the 

household surveys. 

4. CONCEPTS AND APPROACHES TO THE VALUATION OF SERIOUS ILLNESES 

 Volume 4 extends the analysis of health valuation to serious or life 

threatening illness. 

 Section 4.2 considers alternative definitions of health and, for the 

study of serious illnesses resulting from environmental causes, concludes 

that a definition in terms of absence of symptoms should be used. The 

potential contributions of various pollutants to the risks of serious 

illnesses are reviewed, in order to choose which diseases should be studied 

and what ranges of risks are relevant. Specific measures of health status 

are evaluated including symptom description, self-assessment, health risk 

appraisal, health indexes and multi-attribute utility functions. The first 

three of these are recommended for contingent valuation studies. 

 Section 4.3 develops a life cycle explanatory framework for valuing 

reductions in life-threatening illness that guides the remainder of the 

study. Within this framework, longevity (i.e. mortality) and quality of 

life (as affected by morbidity) are considered together in a unified 

context. Young people, presented with improved prospects for greater health 

and longevity only after a long period of time, will heavily discount the 

benefits and will pay little, even though aware that their preferences many 

years hence will be different. Policies that promise a near-term benefit 

will be valued much more highly by people of any age. If people can easily 

substitute near term consumption for deferred consumption, they will place 

less value on additions to life expectancy. The capacity for consumption 

changes over the life cycle. An added year of life accompanied by high 

income or accumulated wealth, together with a high quality of leisure time, 

will be valued relatively highly. Latency is modelled within the life cycle 

framework. 

 Section 4.4 develops a model of choice under uncertain preferences, bringing 

utility theory to bear on the problem of valuing small changes in events that are 

thought of only infrequently and may involve low probabilities of occurrence. The model 

is applicable to contingent valuation approaches to serious illness. The model assumes 

environmental health risks are unfamiliar to most people, and that because people seldom 

have occasion to think carefully about them they are uncertain about
their preferences concerning them. The model leads to twelve theorems for 

stimulating people to obtain improved knowledge about their preferences and 

to state valid, consistent risk reduction values. 

 Section 4.5 applies the preceding sections to contingent valuation of 

life threatening illness. A structure for an intensive interviewing process 

is developed, based on techniques of in-depth interviewing. 

 The proposed interview structure contains four modules. The first 

module concerns the repsondent's health experiences. The defensive measures 

module is the second module. The third module pertains to risk perception 

and risk behavior. This module teaches respondents basic notions of 

probability and conveys information about probabilities involved in health. 

Information is obtained about repsondent perceptions and attitudes towards 

risks. 

 Contingent valuation questions form the fourth module. The module 

begins with simple questions involving certainty scenarios and mortality 

only, after which serious illnesses are introduced. Then life path 

scenarios are introduced that combine morbidity and mortality in a life 

cycle setting. Respondents are asked to choose among and value the 

scenarios, first in a certainty and then an uncertainty setting. 

(End of Abstract of Executive Summary) 
PREFACE TO STUDY 

 One of the chief reasons for concern with the environment is to 

protect and improve human health. Yet health effects remain among the most 

difficult of all effects of environmental measures with which to deal. 

Evaluating health effects calls for answers on two questions: 1) What is 

the contribution of environmental improvements to better health? and 2) How 

much is improved health valued? The latter question--how much is health 

valued, or how much is it worth in terms of other goods and services to 

obtain a better state of health--is the focus of the present study. 

National environmental legislation requires estimation of benefits of 

proposed environmental measures. This mandate cannot be fulfilled without 

consideration of the second question. 

 Values attached to improved health in turn break down into two 

components--mortality and morbidity. The estimation of both mortality and 

morbidity benefits has remained fragmentary. From an early misplaced 

emphasis on foregone earnings as a measure of the value of reducing 

mortality, progress has been made on approaches recognizing satisfactions 

people enjoy over and above those from earnings in the market place. 

Meanwhile, values attached to reduced morbidity have been based for the most 

part on medical expenses and foregone earnings. Methods of valuing 

morbidity have lagged behind mortality. 

 For both mortality and morbidity, benefits are affected by risk 

considerations including risk perceptions and behavior toward risk, and by 

actions taken by people to avoid exposure to pollutants. Empirical work has 

been hindered by lack of an adequate conceptual framework, data shortcomings 

and econometric estimation problems. 

 A broad assessment and reconcilation of approaches to valuing 

mortality and morbidity is needed. The close but often unrecognized 

relation between the two phenomena makes it important to carry out the 

assessment for mortality and morbidity within a common framework. 

 Building on the assessment, contributions are needed to provide a more 

adequate framework for valuing health benefits. A common framework for 

mortality and morbidity will recognize the inter-temporal nature of 

benefits, leading to a life cycle approach that gives attention to the 

quantity and quality of life over time. The effects of risk behavior, 

imperfect knowledge of risks and averting behavior need to be brought in. 

 New empirical methods need to be tried. The contingent valuation 

method, which has been applied to aesthetic benefits, is a contender for 

throwing light on mortality and morbidity benefits which other methods 

either measure imperfectly or do not measure at all. 
 The present report gives the results of the first phase of a study 

concerned with contributing to the estimation of mortality and morbidity 

benefits. The purposes of this phase have been to carry out a comparative 

assessment of previous work, to help meet the needs for a more adequate 

framework revealed by the assessment, and to apply the contingent valuation 

method to health benefits. A field study of light symptoms has been carried 

out, and an approach of 1ife threatening i11nesses has been developed. 

 Direction of this study was shared by George Tolley of the University 

of Chicago and Lyndon Babcock of the University of Illinois at Chicago. 

William Schulze, formerly at the University of Wyoming and now at the 

University of Colorado, shared in the early formulations and directed a 

related wage hedonic study not presently included in this report. The 

affiliations of the authors are as follows: 

 Department 

Name or 

 School Institution 

-------------------------------------------------------------------------

George Tolley Economics University of Chicago 

 

Lyndon Babcock Public Health University of Illinois 

 at Chicago 

 

Mark Berger Economics University of Kentucky 

 

Anthony Bilotti Public Health University of Illinois 

 at Chicago 

 

Glenn Blomquist Economics University of Kentucky 

 

Michael Brien Economics University of Chicago 

 

Robert Fabian Economics University of Chicago 

 

Gideon Fishelson Economics Tel Aviv University 

 

Charles Kahn Economics University of Chicago 

 

Austin Kelly Economics University of Chicago 

 

Don Kenkel Economics University of Chicago 

 

Ronald Krumm Public Policy University of Chicago 

 

Tracy Miller Economics University of Chicago 

 

Robert Ohsfldt Economics Ball State University 

 

Sherwin Rosen Economics University of Chicago 
William Webb Economics University of Chicago 

 

Wallace Wilson Public Health University of Illinois 

 at Chicago 

 

Martin Zelder Economics University of Chicago 
CONTENTS OF EXECUTIVE SUMMARY 

Introduction 1-1 

Volume 2 Summary: Comparative Analysis of Approaches to 

 Valuing Health Risks 1-1 

Volume 3 Summary: Contingent Valuation Study of Light Symptoms 

 and Angina 1-14 

Volume 4 Summary: Concepts and Approaches to the Valuation of 

 Serious Illness 1-21 
List of Tables

Table 1-1: Framework for Health Values 1-9 

Table 1-2: Interim Values for Morbidity and Mortality Effects 

 of Air Pollution 1-12 

Table 1-3: Seven Light Symptom One Day Regression Results 1-18 
 Executive Summary 

1-1 

EXECUTIVE SUMMARY

INTRODUCTION 

 Health effects are among the most difficult effects of environmental 

measures with which to deal. National legislation requires that estimates 

of the benefits of environmental measures be made. This mandate cannot be 

carried out without addressing the question of how much improved health is 

valued. 

 The estimation of mortality and morbidity benefits has remained 

fragmentary. Benefits are affected by risk and by actions taken by people 

to avoid exposure. Empirical work has been hindered by lack of an adequate 

framework, data shortcomings and econometric estimation problems. A broad 

assessment and reconciliation of approaches to valuing morbidity and 

mortality is needed, followed by new efforts to estimate benefits. 

 This report gives results on the first phase of a larger study. The 

purposes of this phase are to contribute to a comparative assessment of 

previous work on mortality and morbidity, to help meet the conceptual needs 

revealed by the assessment -- taking into account averting behavior, life 

cycle, risk and health measurement considerations -- and to undertake new 

measurements by applying the contingent valuation method to health benefits. 

Contingent valuation work has included a field study of light symptoms and 

development of approaches for life threatening illnesses. 

COMPARATIVE ANALYSIS OF APPROACHES TO VALUING HEALTH RISKS 

(Volume 2) 

 A wide variety of approaches to valuing health risk reductions have 

been proposed. While valuing mortality risks has received a good deal of 

attention, the problems of valuing morbidity risks and -- of even greater 

importance -- valuing combinations of morbidity and mortality risks have 

received less attention. The goal of Volume 2 is to provide a comparative 

review of approaches to valuing changes in health and a synthesis of the 

empirical results of the various approaches. A set of interim morbidity and 

mortality values is developed for use in environmental assessment. 

Framework For Valuing Health Risks (Section 2.2) 

 A comparative model for valuing health risk reductions incorporates 

cost of illness, partly endogenous health reflecting preventive 

expenditures, uncertainty, mortality and morbidity. The willingness to pay 

measure from this model can be used to compare alterntive approaches to 

valuing health risks. 
 Executive Summary 

1-2 

 In the general case, an adequate willingness to pay measure for 

reductions in health risks consists of two terms: a utility term, which 

reflects the cost of illness as well as other factors; and a term reflecting 

preventive expenditures. It does not follow, however, that benefit measures 

involving the cost of illness alone or preventive expenditures alone are 

special cases of the general willingness to pay measure. Even the weaker 

result that the alternative benefit measures are lower bounds to the 

willingness to pay measure does not necessarily hold. Without additional 

assumptions, we cannot establish any general comparisons between the measures. 

We do find a set of plausible assumptions under which some comparisons of the 

alternative benefit measures can be made. If these assumptions are made, for 

the special cases of pure mortality and pure morbidity, both the cost of 

illness and the preventive expenditures measures will be lower bounds to 

willingness to pay. The theoretical model thus implies that meaningful 

comparisons may plausibly be made between these measures and an exact measure 

of willingness to pay for a reduction in health risks as revealed either in 

implicit markets, or discovered through contingent valuation experiments. 

Health Econometrics: An Assessment (Section 2.3) 

 As part of the present study, a critique was undertaken of econometric 

evidence on the effects of environmental quality on human health. The focus 

is on mortality effects. A primary concern is whether or not the studies can 

shed light on the structure of demand for health, not just net responses to 

changes in environmental characteristics on health. A fundamental concern is 

with the role of avoidance measures taken by individuals in response to 

adverse health conditions. A reason for this concern is that impacts on 

health of differences in environmental quality can be inferred only as net 

effects after avoidance has taken place. The question is the extent to which 

specification and estimation in econometric models of past studies allow valid 

inferences of the net effects. 

 If avoidance procedures are perfect substitutes for the outside 

influences, very little if any net impact results from differences in outside 

conditions. Even in this case, the benefits of environmental improvements are 

not zero but equal to the costs of the avoidance procedures. More generally, 

differences in environmental conditions will be reflected in differences in 

health status even after avoidance procdures. The resulting calculation of 

benefits due to improvement in environmental conditions needs to consider not 

only cost savings from a reduction in avoidance expenditures but also the 

value of the increased health that results. 

 The assessment considers five empirical studies of the effects of environmental 

pollutants on mortality: Lave and Seskin (1977), Crocker et al (1979), Chappie and Lave 

(1982). Mendelsohn and Orcutt (1979), and Schwing and McDonald (1976). 
 Executive Summary 

1-3 

 Comparison between studies of single pollutant effects are made 

difficult by differences in the pollutants considered in any particular 

study. Correlation between included and excluded pollutants hampers 

comparisons. Except for the estimates from Crocker, et.al. effects of 

sulfur oxides (SO2 and S04 are positive and often substantial. The sign of 

effects of particulates (TSP) are not consistent across studies. Except for 

the results in Mendelsohm and Orcutt, effects of nitrogen oxides appear 

positive. 

 Besides differences in the pollutants considered, the studies contain 

a variety of study designs differences. The Lave and Seskin and Mendelsohm 

and Orcutt studies do not control for smoking or dietary behavior. 

Correlation between these measures and the pollutant variables may bias the 

estimated pollutant effects making serious inference from these two studies 

suspect. The Schwing and McDonald study suffers similarly from lack of 

inclusion of many of these potentially important variables. 

 The Chappie and Lave and Crocker, et.al studies are similar in that 

they include smoking and dietary variables, and they consider the effect of 

physicians per capita on mortality rates. Yet, the estimates differ 

substantially. Substantially larger effects of protein consumption on 

mortality rates are found by Crocker, et.al than by Chappie and Lave. These 

effects are more precisely estimated by Crocker, et.al. This finding 

suggests a potentially important influences of correlation between dietary 

characteristics and the various pollutants considered in each study. The 

differences may also be due to the difference between the effects of 

sulfates and the effect of S02- 

 Both Crocker, et.al and Chappie and Lave address the endogeneity of 

physicians per capita within a cross-sectional setting. Endogeneity is 

expected if use of physician services is one form of avoidance or averting 

behavior. However, avoidance behavior may also be reflected in dietary, 

smoking, and alchohol consumption which needs to be seriously treated in 

further empirical work. 

 Avoidance or averting behavior in place, such as described above, does 

not exhaust avoidance possibilities. People may also change their residence 

location. Individuals may locationally sort themselves according to 

environmental quality, with those least affected living in relatively low 

quality areas. Estimates of mortality rates differences between areas as a 

function of pollution could then understate the effect of changes in overall 

pollution levels (especially those occuring in high pollution areas to begin 

with). Furthermore, individuals may change location in response to what 

would otherwise be continued ill-health effects of pollution in one area. 

Persons adversely affected by pollution may then end up dying (and 

increasing the mortality rate) in low pollution areas. This effect would 

also lead to an understatement of the true effect of pollutants on mortality 

rates such as those based on the existing crosssectional analysis. 
 Executive Summary 

1-4 

Cost of Illness Approach (Section 2.4) 

 Turning to studies that have been explicitly concerned with placing 

monetary values on illness, the cost of illness approach is the most widely 

used approach. A recent survey by Hu and Sandifer (1981) identifies over 

200 studies using the approach. The cost of illness is measured as the sum 

of three components: 1) medical expenditures; 2) the earnings lost due to 

morbidity; and 3) the earnings lost due to “premature" death due to illness. 

Since the valuation of small changes in the risk of death and the possible 

relation of foregone earnings to this measure has received much attention, 

section 2.4 emphasizes the problem of valuing changes in morbidity, and the 

role of medical expenditures. 

 A contribution of the present project has been to put aggregate costs 

of illness on an individual per case and per day spent ill basis. Results 

indicate that a typical case of acute respiratory disease involves $87 of 

medical expenditures, and $56 of foregone earnings. A case of emphysema 

involves $441 of medical expenditures, and $2,753 of foregone earnings. A 

day spent ill due to a typical case of acute respiratory illness costs $35, 

while a day spent ill due to emphysema implies costs of $89. Estimates of 

this kind on an individual basis needed to evaluate environmental policy 

changes have not been available heretofore. 

 The cost of illness approach is an important source of estimates for 

the value of health, because it is commonly accepted by many researchers in 

the health care fields, and it provides estimates for the value of a wide 

range of health effects. Therefore, section 2.4 includes a careful 

evaluation of the approach to assess its usefulness and accuracy. 

 The cost of illness approach ignores the costs of pain and suffering 

due to illness, the value of leisure time, and the role of preventive 

expenditures. While the quantities the cost of illness approach measures 

are clearly related to the value of a health improvement, they are not 

identical to the willingness to to pay for an improvement. Though it seems 

reasonable to assume that the cost of illness approach understates 

individual willingness to pay, the extent of the underestimate is uncertain. 

 The problem is further complicated when the distinction is made 

between individual and societal willingness to pay. The treatment of 

consumption, non-labor earnings and taxes by the cost of illness approach 

might be described as an uneasy compromise between adopting an individual or 

a societal viewpoint. Characteristics of the market for health care that 

may cause further divergences between individual and societal willingness to 

pay include the extent of third party payments, the importance of non-profit 

organizations in providing hospital services, the role of the physician in 

influencing demand for his own services, and the possible lack of 

competition in the supply of physician
 Executive Summary 

1-5 

services. Paid sick leave, and altruism complete the list of possible 

reasons the cost of illness approach may not produce a measure of societal 

willingness to pay for health improvements. While these problems have yet 

to be rigourously addressed, it is apparent that the distinction between 

individual and societal willingness to pay is both an important and a 

complex issue. No simple rule for adjusting the cost of illness approach to 

better reflect the viewpoint of society is found. 

 In typical cost of illness studies such as Rice (1966) and Cooper and 

Rice(1976), the calculation of medical expenditures and foregone earnings 

due to illness is quite involved, since the expenditures and earnings must 

be allocated to particular illnesses or disease categories. In allocating 

medical expenditures to specific illnesses, the problems lie in the numerous 

inaccuracies in the estimation of the expenditures by service category and 

in the estimation of the weights needed to allocate expenditures to disease 

categories. The net result is that the estimates of medical expenditures 

due to particular diseases are inaccurate, but by how much or even in which 

direction the estimates are biased is difficult to determine. The 

estimation of foregone earnings due to different diseases is also subject to 

error, mainly because of limitations of the data available. In this case, 

most of the errors tend to understate the foregone earnings due to 

morbidity. 

Review of Contingent Valuation Studies of Health (Section 2.5) 

 One approach to valuing a non-market good is to conduct a survey and 

ask people what they would pay for the good, hypothetically assuming 

(contingent upon) the existence of a market for the good. This approach, 

the contingent valuation method (CVM), has been applied to a variety of 

environmental goods including air quality and health. 

 This section reviewed three major studies that applied the CVM to the 

problem of valuing health effects related to air pollution: Loehman et al. 

(1979), Rowe and Chestnut (1984), and Tolley et al. (1985). Each of these 

studies seems to be carefully designed, though certain problems are noted. 

As a result, the value estimates are probably as accurate as any estimates 

based on contingent valuation; similar to Cummings et al. (forthcoming), the 

reference accuracy may be set at plus or minus 50 percent. 

 While the health effects valued are not exactly the same, certain 

comparisons can be made between the results of the three studies. For 

instance, each of the studies implies a value for one day of respiratory 

symptoms, though not always of the same symptoms. From the Loehman et al. 

study, one day of of coughing/sneezing has a mean value of $138 (mild day) 

or $236 (severe day). The Rowe and Chestnut study implies that relief from 

one day of asthma symptoms is worth on average about $20.
 Executive Summary 

1-6 

The Tolley et al. study finds that relief from one day of coughing, throat, 

and sinus problems has a mean value of $113. 

 These different values can be reconciled, to some extent. First, the 

Rowe and Chestnut value is not a value for a marginal day of relief, but an 

average value for one day, given an average of 19 days of symptoms relieved. 

Thus, it is not really comparable to the other estimates. The Loehman et 

al. and Tolley et al. studies are more directly comparable. In general, 

though, different values result. But comparing median bids across the two 

studies, or comparing mean bids across the two studies, the values do not 

seem to be necessarily inconsistent. 

Comparing Costs of Illness and Continigent Valuation (Section 2.6) 

 The cost of illness (COI) approach and contingent valuation (CV) are 

two important methods that allow a dollar value to be placed on a change in 

morbidity or sickness. A direct comparison of values based on these methods 

is undertaken in this section. This comparison is especially interesting 

because the methods are in some sense complementary. The cost of illness 

approach, focusing on medical expenditures and foregone earnings, uses 

widely available data and comparatively straightforward empirical 

techniques, so it is generally accepted on a practical level. However, 

there is no strong theoretical basis for using COI values in benefit cost 

analysis. As noted, COI may be below and not very close to what an 

individual would actually be willing to pay. In contrast, contingent 

valuation experiments can be designed to directly estimate what an 

individual, would be willing to pay, but proper design of CV experiments is 

So on a practical level COI values are often judged superior to CV values, 

while on a theoretical or conceptual level, CV values are preferred. 

 Our empirical work provides direct comparisons of WTP and COI from the 

same study of seven symptoms: coughing spells, stuffed up sinuses, throat 

congestion, itching eyes, heavy drowsiness, headache, and nausea. The WTP 

values that are obtained are equivalent to consumer surpluses. The results 

suggest that WTP exceeds COI, but there is no strong indication that WTP and 

COI move together in any systematic fashion. Assuming that exogenous 

changes affecting health risks reduce preventive expenditures, our results 

also imply that the WTP for reduction in health risks which arises from our 

uncertainty based model exceeds expected COI. We then provide an 

illustrative lower bound estimate of willingness to pay for a reduction in 

health risks from our contingent valuation survey. The results of the 

contingent valuation survey only directly apply to the case of changes that 

occur with certainty, however. 

 The results of the new empirical work tend to confirm Rowe and 

Chestnut's (1984) preliminary results that WTP exceeds COI. It should be 

noted that this relationship is also found in the
 Executive Summary 

1-7 

experimental mail survey completed (see section 3.7); but the results are 

for a very small sample. So there is a growing body of evidence that 

suggests contingent valuation responses on WTP exceed COI, as predicted by 

several theoretical models. 

Household Production of Health and Averting Behavior (Section 2.7) 

 In studies following the household production approach, as in Grossman 

(1972), the individual is visualized to produce the commodity health by 

combining his own time and effort with purchased goods such as medical care, 

diet, and so on. Health is partially under the control of the individual or 

partly endogeneous, though it is also affected by exogeneous factors such as 

environmental quality. Some recent theoretical and empirical work has used 

this framework to derive expressions for what an individual would be willing 

to pay for an exogeneous improvement in environmental quality. The 

theoretical studies, such as the model developed in section 2.2 and the 

studies referenced therein, investigate how the conceptually correct 

willingness to pay measure will be related to observable quantities such as 

the costs of illness and preventive expenditures. 

 Two empirical studies have taken the analysis further and attempt to 

estimate willingness to pay directly. Gerking and Stanley (1984) estimate 

willingness to pay for health risks related to ozone exposure, and Cropper 

(1981) estimates willingness to pay for health risks related to an index of 

air pollutants. The implied values for health are about $40 for a day of 

restricted activity from the Gerking and Stanley study, and $176 for a work 

loss day in the Cropper study. Since a work loss day is a more severe 

effect than a day of restricted activity (as defined in these studies), it 

is not unexpected that the Cropper estimate is larger than.the Gerking and 

Stanley estimate. The magnitude of the difference does seem large. 

However, due to the limitations of these studies noted by the authors, these 

value estimates are probably best described, as illustrative of the order of 

magnitude of the value of health. In this context, the two studies do not 

produce inconsistent results. 

Housing Values and the Value of Health (Section 2.8) 

 One way that individuals reveal their willingness to pay for 

environmental quality is through their location choices and the 

corresponding housing price premiums for various locational attributes, 

including air quality. The benefit estimates thus obtained represent the 

total benefits of an improvement in air quality, not just the health 

benefits. So these estimates could be upper bound estimates of the benefits 

of improved health. On the other hand individuals may not have full 

knowledge of environmental effects in purchasing property, leading to 

underes-
 Executive Summary 

1-8 

timation. Finally, in applying hedonic analysis to the demand for air 

quality, a number of econometric problems are encountered that could cause 

bias or inaccuracy. 

 Bender et al. suggest that a permanent 10 percent reduction in 

suspended particulates would result in a $700 to $1800 benefit (present 

value) per household. Similarly, Harrison and Rubinfeld estimate that a 2 

ppm reduction in nitrogen oxides would create a benefit of $800 per middleincome household. Estimates of this kind from from the housing market 

hedonic literature can be combined with estimates from the health 

econometrics literature of the effects of air pollution on mortality, to 

arrive at an idea of how much people are willing to pay through property 

values for a reduction in mortality risk. Using typical values from the 

housing market hedonic literature and the health econometrics literature 

gives a value for marginal risk reduction, or a value of life in the 

statistical sense, of $740,000. This figure must be viewed with caution in 

view of the problems noted above. 

 However, the value of $740,000 is not inconsistent with the values of 

risk reduction resulting from hedonic analysis of labor markets, or 

consumption activity. It lies somewhere in the middle of the very wide 

range of empirical results existing in this literature. The value also can 

be reconciled to estimates of the value of health risks from the cost of 

illness approach, especially when considering the argument that neglecting 

averting behavior causes the cost of illness approach estimates to be lower 

bounds to the willingness to pay for health risk reduction. 

Conclusions: Interim Values for the Health Effects of Air

 Pollution (Section 2.9) 

 The purpose of section 2.9 is to bring together the foregoing results 

to arrive at a set of health risk values useable in environmental 

assessments. The application in this study is to health effects of air 

pollution. 

 In section 2.9.2 a framework for value estimates is discussed. The 

framework addresses two major questions: First, for what types of health 

effects are values needed ? Second, what constitutes complete and 

conceptually correct value estimates for these health effects? The answers 

to these questions are summarized in Table 1. The first column indicates 

that the health effects due to air pollution include various types of acute 

or short-term morbidity, aggravation of previously existing chronic 

morbidity, increased incidence of non-fatal chronic morbidity. and mortality 

whose value may vary according to cause of death. The second column 

indicates the forms taken by the value components for each of these effects 

and indicates the need to value morbidity preceding death. 
 Executive Summary 

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Table 1-1 

Framework for Health Values 

Health Effects Valued Value reflects

 

Acute or Short-term Morbidity 

 

--light symptoms --physical and mental 

 discomfort 

 

--marginal change in --work time lost 

 time spent ill 

 --other time lost 

 

 --medical expenditures 

 --costs of averting 

 behavior or preventive 

 measures 

 

Aggravation of Previously 

Existing Chronic Morbidity 

 

--chronic lung conditions --a larger degree of 

 all of the above 

--chronic heart conditions 

 --individuals' health 

marginal and non-marginal status is already low 

changes in time spent ill 

 

Increased Incidence of 

Non-fatal Chronic Morbidity 

 

--chronic lung conditions --all of the above 

--chronic heart conditions --lifestyle and work 

 changes due to the 

--cancer existence of chronic 

 illness 

 

Mortality 

 

--unforseen instant death --mortality risks 

--chronic lung conditions --morbidity preceding 

 mortality valued as 

--chronic heart conditions above 

 

--cancer --psychic costs of 

 imminent death 
 Executive Summary 

1-10 

 In section 2.9.3 the framework is used to arrive at a set of interim 

values applicable to air pollution. For each of the health effects, value 

estimates are brought together and expressed on a comparable basis noting 

the components of value included and excluded for each estimate and the 

ranges that have been obtained for particular components. Previously 

published estimates are used, as well as the cost of illness and contingent 

value estimates developed as part of the present project. The available 

evidence is compared to the framework, in terms of which health effects are 

valued, and how complete these values will be. In light of this discussion, 

reasonable ranges and interim values are developed. These values are 

presented in Table 2. 

 In placing a value on a day of acute or short-term morbidity, five 

separate sources of estimates are used.. The most complete estimates come 

from the contingent valuation study described in Volume 3 of this report, 

and from the contingent valuation study of Loehman et al (1979). A lower 

bound value from cost of illness estimates expressed on a per day basis is 

also used. Additional information is available from the health production 

studies of Cropper (1981) and Gerking and Stanley (1984). These sources are 

combined to yield values for specific symptoms and a likely combination of 

symptoms, for an average day of restricted activity, a severe day of work 

loss, and a mild day of discomfort alone. As a rough rule of thumb, a 

severe day is valued at twice the value of an average day, and an averate 

day is worth twice a mild day. For instance, the medium estimate for an 

average day of a likely combination of symptoms is $60, while a severe day 

is valued at $125 and a mild day at $25. 

 To move on from acute or short-term health effects, the second major 

class of health effects to be valued is the aggravation of previously 

existing chronic morbidity. Values are placed on one additional day of 

symptoms for people who even without air pollution suffer from emphysema, 

asthma/bronchitis, or a heart condition. To value an additional day of 

emphysema or asthma/bronchitis, the evidence on the value of acute or shortterm respiratory illness is clearly relevant, but the per day values for 

chronic lung conditions will generally be higher. Additional evidence from 

the contingent valuation study of Section 3 of this Report, cost of illness 

per day estimates, and the Rowe and Chestnut (1984) contingent valuation 

study is used to develop the interim values. Due to more uncertainty of the 

estimates, wider ranges of interim values are developed: for example, an 

additional day of angina may be worth as little as $75 or as much as $400, 

but the best medium estimate is $150. 

 In addition to the aggravation of previously existing chronic 

conditions, it is possible that air pollution will cause new cases of 

chronic conditions. Interim values are developed for one year of non-fatal 

cases of emphysema, asthma/bronchitis. lung cancer, and heart conditions. 

Most of the evidence for the value of these serious health effects comes 

from the cost of
 Executive Summary 

1-11 

illness approach, such as the study by Hartunian, et al (1981). In 

developing the interim values an attempt is made to take into account the 

fact that cost of illness estimates are incomplete measures, ignoring the 

value of discomfort (pain and suffering), and the costs of preventive 

actions. Evidence from the contingent valuation study in Volume 3 of the 

present report of the value of relief from 30 days of light symptoms, and 

the value of 10 to 20 days of relief from angina is also important, as is 

the Rowe and Chestnut estimate of the value of a 50 percent reduction in 

asthma symptoms. There is a wide range of severity of chronic symptoms, so 

a case of asthma/bronchitis is valued at only $900, while preventing a year 

of emphysema is judged to be worth $7000. The final effect to be valued is 

an increase in mortality risks. Most empirical estimates of the value of 

mortality risks have been obtained from job-related or traffic accident 

data. These estimates suggest that a risk of an unforseen instant death is 

worth somehwhere between $0.5 million and $5 million, with a medium estimate 

being about $2 million. 

 However, air pollution at the levels found in the U.S. could not cause 

instant death, but instead must influence mortality risks by increasing the 

mortality rates due to chronic illnesses. The value of preventing a death 

from these causes is clearly higher than the value of preventing an instant 

death, in view of the difference in physical suffering before the death, and 

the psychic costs of imminent death. Developing methods to estimate the 

value of mortality risks depending upon the cause of death is an important 

achievement of this section. 

 One approach to valuing mortality risks depending upon the cause of 

death is to use cost of illness and other estimates to value the morbidity 

preceding the mortality. Morbidity values are added to the value of an 

instant death, using the fact that every current death due to a condition is 

associated with a much larger prevalence of cases that eventually will be 

fatal. For instance, if the average life expectancy with a condition is 10 

years, the value of 10 person-years of morbidity is added to the the value 

for an unforseen instant death. Calculations along these lines are combined 

with information from a survey by Jones-Lee et al (1985) that included 

questions about how people valued different causes of death. These sources 

allowed the interim values to reflect important differences in the value of 

mortality risks depending upon cause of death. So the medium value of a 

death from lung cancer ($4 million) is much higher than the medium value of 

an instant death ($2 million) that is commonly reported. Estimates of the 

value of health risks developed in this study combined with previous 

empirical estimates allowed the development of these interim values of 

morbidity and mortality effects. These values should be useful for 

assessing environmental policy scenarios. However, considerable additional 

work is required to refine these interim values, to narrow the ranges of 

values and allow more confidence to be placed in them. 
 Executive Summary 

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Table 1-2 

Interim Values for Morbidity and Mortality Effects of Air Pollution 

 Value Estimate 

Category Low Medium High

 

Acute or short-term morbidity 

 

average day (restricted activity 

day): 

 

--sinus $20 $35 $60 

--throat 10 25 40 

--respiratory symptoms 15 30 50 

--eye irritation 20 40 100 

--headache 30 50 110 

--likely combination 35 60 100 

severe day (work loss day): 

--likely combination 80 125 175 

mild day (discomfort): 

--likely combination 10 25 50 

Aggravation of previously existing 

chronic morbidity (per day)

 

 

lung conditions: 

--emphysema 50 100 300 

--asthma/bronchitis 35 60 100 

heart conditions: 

--angina, possibly with 

 other heart disease 75 150 400 

 

--likely combination of lung and 

heart 45 80 190 
 Executive Summary 

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Table 1-2 

Interim Values for Morbidity and Mortality Effects of Air Pollution 

 Value Estimate 

Category Low Medium High

 

Increased Incidence of 

Non-fatal Chronic Morbidity 

(per case per year) 

 

lung conditions: 

--emphysema $3,200 $7,000 $10,000 

--asthma/bronchitis 200 900 1,200 

--lung cancer 30,000 60,000 100,000 

heart conditions: 

--angina uncomplicated 500 800 2,000 

--other heart disease 2,500 4,000 10,000 

--likely combination of 

 lung and heart 1,700 3,800 5,900 

Mortality 

(per statistical life) 

 

--unforseen instant death .5 mill. 2 mill. 5 mill. 

--emphysema .64 m 3.5 m 9 m 

--asthma/bronchitis .53 m 2.5 m 5.5 m 

--lung cancer .58 m 4 m 10 m 

--heart disease .54 m 3 m 7 m 

--weighted average of 

 all causes .58 m 3.8 m 9.4 m 
 Executive Summary 

1-14 

CONTINGENT VALUATION STUDY OF LIGHT SYMPTOMS AND ANGINA (Volume 3) 

Introduction (Section 3.1) 

 The purpose of this part of the study is to devise and apply a 

theoretically sound approach to estimating the benefits of light symptom 

reduction and angina relief resulting from improvements in ambient air 

quality. Contingent valuation is the research method used to accomplish 

this objective. Contingent valuation offers a technique capable of getting 

at values that are difficult to measure by other means, such as property 

value or revealed behavior methods. While some previous contingent 

valuation studies of health effects have been undertaken, the present study 

apparently represents the most intensive effort of this kind to date. 

 The approach of the study has been based on extensive focus group 

experimentation prior to systematic household sampling. The study has given 

particular attention to three methodological areas. These are, first, the 

information and prefernce context of contingent valuation. This area frames 

the problem for the respondent and helps him research his preferences in 

order to provide a high quality response. 

 The second area, the structure of the contingent market, defines the 

good to be valued in a clear, concise and quantitative manner. - The area 

also considers the importance of both the payment vehicle and the delivery 

vehicle of the good. In this study, pure willingness to pay questions 

without specific payment vehicle (outright payment rather than through, say, 

utility bill or increased taxes) and without specific delivery vehicle 

(outright relief rather than relief through, say, a pill) were selected 

because they were acceptable to respondents and avoided distractions, bias 

and information overload. 

 The third methodological area is the bidding game process. Based on 

focus group experience, an iterative bidding process was chosen as the 

method of eliciting willingness-to-pay responses. Care was taken to avoid 

the problems of the respondent choosing a convenient unvarying bid for all 

programs (anchoring) and the respondent being influenced by the initial bid 

(starting point bias). These types of problems tend to occur when the 

respondents' understanding of the good and the market and of their own 

preferences is so limited that extraneous information predominates in 

determining bids. 
 Executive Summary 

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The Dose-Response Problem and the Definition of Symptom Relief 

(Section 3.2 

 The values that respondents place on improvements in ambient air 

quality levels depend on the degree of pollution reduction and the time 

pattern of reduction, e.g. whether pollution is reduced on many days or only 

a few days. The value of an extra day of relief may depend on the level of 

symptoms prevailing before the relief. People might value an extra day of 

relief from symptoms differently if they have been experiencing several 

weeks of symptoms than if they have been experiencing only one or two days. 

 The general problem is to develop a way of valuing reductions in 

symptoms from pollution depending on the amount of relief from symptoms, 

where the relief may vary among areas and of people (sensitive vs. 

nonsensitive) in amounts that are not known beforehand. In short, the 

problem is to estimate, not a single value, but a function that specifies 

value depending on both the amount of relief given and the symptom level 

prevailing in the absence of the policy being evaluated. This function 

provides a tool that can be used to value the variety of symptom reductions 

among areas and types of people. 

 Respondents had to be asked about a sufficient variety of situations, 

but the variety had to be in the realm of reality. The requirement of 

reality is to be partiuclary stressed. if values are obtained for far 

greater or far less relief than will actually be brought about by 

environmental controls, then their applicability will be suspect. For 

example, the willingness to pay to be completely rid of a large number of 

days of a symptom may throw little light on how much would be paid to be rid 

of one day. If values are not obtained for realistic degrees of relief, it 

will be necessary to tenuously extend estimates into unkown regions. 

 The problem of choosing realistic values is made difficult by the 

imperfect state of knowledge about pollutant reduction. The critique of 

evidence undertaken as part of this study makes clear that a great range of 

uncertainty still attaches to the health effects of the criteria air 

pollutants, particularly with respect to light symptom effects. However, 

two conclusions stand out. First, realistic pollution control po1icies wi11 

give fractional day or at most a few days of relief to the majority of 

people. Second, the evidence is more tenuous regarding sensitive 

populations. The possibility needs to be allowed for that sensitive or 

susceptible persons would obtain greater relief. 

 For the light symptoms, one version of the questionnaire asked about 

one day of relief to establish values per day attaching to fractional-day 

relief or at most a few days of relief applicable to large numbers of people 

under many policies. A second version of the questionnaire asked about 

relief of thirty days to encompass sensitive groups whose allergic balance 

could be affected by ambient air quality changes. 
 Executive Summary 

1-16 

 A similar strategy was followed in the questionnaires on angina. To 

find out how the value of varying degrees of relief are related to a 

prevailing level of symptoms, in one version of the angina survey people 

were asked to suppose alternatively that they started from levels of one, 

five and ten days of mild and severe angina. In the second version of the 

survey respondents were asked to suppose alternatively that they started 

from levels of one, ten and twenty symptom days of mild and severe angina. 

Structure of CV Instrument (Sections 3.3 and 3.4) 

 The structure of the health survey is reflected partly in the 

organization of the questionnaires, and partly in the relationship of the 

questionnaires to each other. Four questionnaires were used, each with 

essentially the same organization: 1) one day of relief from each of seven 

light symptoms and some combinations of the symptoms, 2) thirty days of 

relief from the same symptoms, 3) relief from up to ten days of angina and 

4) relief from up to twenty days of angina. 

 All survey instruments feature questions on health endowment in the 

beginning followed by contingent valuation questions and ending with 

questions on socioeconomic characteristics. The questionnaires feature a 

high degree of interaction between interviewer and respondent. Responses 

were pooled during analyis into single data sets for the seven symptom and 

for angina. 

Household Sampling (Section 3.5) 

 An objective of the sample design was to obtain a representative cross 

section of households on which to base inferences about health values. Two 

metropolitan areas were sampled--Chicago and Denver. 

 One hundred ninety nine interviews were conducted, divided about 

equally between the two cities. Twenty three interviews had to be deleted, 

due to various inconsistencies in the bidding. Median income for 

respondent's census tract was used as a default for those respondent's not 

revealing their income. 

Empirical Results for Household Survey (Section 3.6) 

 The seven light symptoms considered were coughing, sinus problems, 

throat congestion, itchy eyes, drowsiness, headache and nausea. The mean 

bids to relieve a one day endowment of each of the seven light symptoms 

range from $50.28 to relieve one day of nausea to $25.20 to relieve one day 

of coughing. The range of the bids to relieve thirty days of each symptom 

was $488.20 to relieve thirty days of headaches to $166.50 to relieve thirty 

days of coughing. Large bids were obtained for the relief of
 Executive Summary 

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various combinations of hypothetical and actual endowments. 

 The angina ten day survey yielded a range of $261.84 to relieve ten 

days of severe angina when the respondent is endowed with ten days, to 

$66.08 to relieve one day of mild angina when only afflicted with one day of 

the condition. The angina twenty day results ranged from $844.38 to relieve 

twenty days of severe angina when confronted with twenty days of the 

condition, to $90.24 for eliminating one day of mild angina a month when the 

respondent experiences only one day of mild angina. The bids, in general, 

varied with the level of relief provided and the severity of the endowment. 

 The respondent's experience with each symptom or class of symtoms was 

obtained. For example, in the one day seven-symptom survey, experience with 

the symptom days range from 19.75 days of itchy eyes to 1.3 days with 

nausea. 

 Regressions performed to explain the willingness to pay bids used 

household income, age, sex, education, and race of the respondent, a measure 

of general health status and experience with the symptoms were used as 

independent variables. 

 The regression results are consistent with the hypothesis of 

increasing marginal disutility of symptoms. The actual experience with a 

symptom or class of symptoms is often a positive and significant determinant 

of the willingness to pay bids. Adding further credence to this proposition 

is the performance of the health status variables. It indicates that the 

respondents who are in poor hea1th are wi11ing to bid more to re1ieve the 

additional endowments. 

 Other independent variables, such as age, education, and income, tend 

to have coefficients that vary in significance and sign. The regression 

results are thus consistent with other findings in the survey that indicated 

the main reason for the willingness to pay bids was personal comfort, i.e. 

the taste for health. It is not surprising that the socioeconomic variables 

were not systematically related to the respondents' degree of discomfort, 

and so also not systematically related to the willingness to pay bids. 

 Table 1-3 gives a sample of the regression results from the seven 

symptom health one day data. As can be seen by the large t-statistic, the 

respondent's experience with the particular symptom is a significant 

influence on the bid. 
 Executive Summary 

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Table 1-3 

Seven Light Symptom One Day 

Regression Results 

Bids to Relieve One Additional Day of: 

Variable Coughing Sinus Problems Throat Itchy Eyes

 

Intercept -103.79 -56.73 -46.75 -95.05 

 (-2.84) (-1.48) -(1.00) (-2.69) 

Income -0.000026 0.000036 -0.00051 -0.000023 

 (-0.10) (0.14) (-1.57) (-0.11) 

Educationl 2.85 2.72 2.51 4.22 

 (1.91) (1.71) (1.33) (2.79) 

White, 22.41 -3.47 21.21 19.02 

 (1.47) (-0.21) (1.13) (1.42) 

Agel 1.56 0.74 0.46 0.64 

 (3.23) (1.46) (0.83) (1.65) 

Sex -20.77 10.57 -10.98 4.91 

 (-1.62) (0.77) (-0.69) (0.42) 

Noexhlth 4.58 8.95 31.53 20.36 

 (0.30) (0.59) (1.86) (1.65) 

Days of Depen- 1.43 0.71 1.12 0.15 

dent Variable (3.43) (3.23) (2.14) (1.79) 

F Value 3.23 2.83 2.00 2.07 

R-Square 0.48 0.45 0.37 0.38 

Note: t values in parentheses 
 Executive Summary 

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Table 1-3 (continued) 

 Drowsiness Headaches Nausea 

 

Intercept 45.40 47.84 -101.20 

 (0.93) (0.74) (-1.62) 

Income -0.00018 -0.00081 -0.00019 

 (-0.54) (-1.82) (-0.45) 

Education1 -2.24 1.21 3.53 

 (-1.10) (0.45) (1.38) 

White 3.62 39.18 43.93 

 (0.18) (1.46) (1.77) 

Agel 0.74 -1.88 0.77 

 (1.16) (-2.15) (1.06) 

Sex -28.63 29.87 -4.24 

 (-1.61) (1.27) (-0.20) 

NoExhlth -2.22 73.32 47.05 

 (-0.11) (2.83) (2.08) 

Days of Depen- 3.25 -0.006 16.91 

dent Variable (2.93) (-0.03) (8.23) 

F Value 2.11 2.84 18.22 

R-Square 0.38 0.45 0.84 

Note: t values in parentheses 
 Executive Summary 

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Mail Questionnaire (Section 3.7) 

 An experimental mail survey was conducted to determine whether it 

would be feasible to greatly expand the number of cases on which the 

contingent valuation estimates could be based. As in the personal interview 

questionnaires, the indirect symptom based approach to willingness to pay 

was adopted, using six common air pollution caused symptoms, including those 

caused by general air pollution, ozone, and carbon monoxide. Two 

questionnaires were developed, identical except that one questionnaire, Type 

B, added a set of comparative questions which measure earnings lost and 

medical care expense occasioned by the symptoms. The Dillman mail survey 

method was employed for this survey. 

 An equal probability sample of 103 names and addresses representing 

the Chicago metropolitan area adult resident population was drawn from 

reverse telephone directories. Discounting 15 addresses which had changed, 

a response rate of 48 percent of the 88 possible interviews was achieved, 

forming a data-base of 42 cases. 

 The willingness to pay question was based on an endowment of 3 symptom 

days per month for each symptom. The bids were for an effective, safe, 

side-effect-free medication which would have to be taken only once a month. 

The mean bids to eliminate the personal discomfort symptoms of headache, 

coughing, stuffed up sinuses, irritated throat, and itching eyes ranged 

between $8.42 and $9.68 per month, or $101 and $116 per year. The mean 

willingness to pay to eliminate heavy drowsiness when driving was $5.41 per 

month, or $65 per year. 

 By far the most common reason underlying the amount of the bids was 

personal comfort. Next most frequently mentioned was to avoid loss of work 

or other usual activity. 

 Stuffed up sinuses were the most commonly experienced symptom, 

followed by headaches, irritated throat, and coughing, which also were 

common. In terms of days of work or other usual activity lost, headaches 

produced the largest mean number of days lost, 1.1 per year averaged over 

all respondents. Earnings lost because of headache was by far the largest--

averaging $108 per year across all respondents. Medical care expenses were 

also by far the largest for headaches--averaging $60 per year over all 

respondents. Coughing caused the next highest mean level of earnings loss 

and stuffed up sinuses the next highest mean medical expenses. In terms of 

comparative analysis, mean willingness to pay greatly exceeded both mean 

earnings loss and medical expense and the total of these two means for all 

symptoms except headache, for which mean willingness to pay, mean earnings 

lost and mean medical expense all were of the same approximate magnitude. 

 A comparison of the mail questionnaire results with results from the 

personal interviews reveals that the mail survey mean
 Executive Summary 

1-21 

bids, which involve the elimination three symptom days, are intermediate in 

value between the one day and thirty day relief bids from the personal 

interviews. Also comparable to the personal interviews, the mail survey 

sample indicates a positive relationship between the mean bid for a symptom 

and the number of days the symptom was actually observed, corroborating the 

hypothesis of increasing marginal disutility for experiencing a particular 

symptom. 

CONCEPTS AND APPROACHES TO THE VALUATION OF SERIOUS ILLNESES (Volume 4) 

Introduction (Section 4.1) 

 Volume 4 extends the analysis of health valuation to the domain of 

life threatening illness. It develops an original framework that can be 

used to obtain values of increased longevity and reduced risks of death from 

serious illness. 

Health Definition and Measurement (Section 4.2) 

 Section 4.2 provides an evaluation of approaches to the definition and 

measurement of health status. This evaluation is a prerequisite to 

determining how to measure health attributes and design a study aimed at 

determining health values. This section provided a number of guides to 

later sections, including guides as to estalishment of health endowment as a 

determinant of value of health improvement, clear definition of the health 

good, and the development of warm-up health experience questions needed if a 

a contingent valuation approach is to be used . 

 Section 4.2 first considers alternative definitions of health, making 

a distinction between definitions cast in terms of positive attributes of 

well-being and definitions cast in terms of the absence of undesirable 

symptoms or diseases. The multifaceted nature of health is stressed. For 

the study of serious illnesses resulting from environmental causes, it is 

concluded that a definition in terms of absence of symptoms should be used. 

Section 4.2 next considers the role of the causes of ill health in defining 

and measuring health. The indication that lifestyle is a far more pervasive 

determinant of health and longevity than the environment is brought out. An 

implication is that environmental values need to be considered in a context 

where they are additions to larger risks from other causes. The potential 

contributions of various pollutants to the risks of serious illnesses are 

reviewed, in order to choose which diseases should be studied and what 

ranges of risks are relevant in a study seeking to obtain health values for 

environmental assessment. 
 Executive Summary 

1-22 

 Finally section 4.2 considers the measurement of health status. Self 

assessed health status is observed to be the most widely used health status 

measurement technique. While this approach has limitations, it is seen to 

have an important role to play in health risk reduction benefits research. 

Its importance stems partly from the role that self-perception plays in the 

benefits that people perceive they receive from improvements in their health 

prospects. Because health is a multi-dimensional condition, it is necessary 

to supplement self-assessment with other measures of health status. 

The Quantity and Quality of Life and the Relation Between Morbidity and

Mortality Benefits (Section 4.3) 

 Section 4.3 develops an explanatory framework for studying the values 

that result from reductions in life-threatening illness. This framework 

makes it clear that people's decisions regarding health and longevity depend 

on their life situations and the streams of experiences that have developed 

over long periods of time. This framework puts the intertemporal decision 

process in the forefront. An implication is that the quality of life and 

longevity are part of a single decision making process, and that they must 

be considered together in a unified context. 

 Some important specific implications were derived from the framework. 

One implication is that young people, presented with a public health policy 

that improves their prospects for greater health and longevilty only after a 

long period of time, will heavily discount the benefits. Hence they are 

willing to pay relatively very little for the prospect, even though they may 

be fully aware that their preferences many years hence will be very 

different. On the other hand, policies that promise a near-term benefit 

will be valued much more highly by people of any age. 

 Another implication is that intertemporal substitution of lifetime 

consumption may occur. If people feel that they can not substitute near 

term consumption for long deferred consumption, they will place greater 

values on additions to life expectancy. The theory also identifies changing 

capacity for consumption over the life cycle. An added year of life 

accompanied by high income or accumulated wealth, together with a high 

quality of leisure time, will be valued relatively highly. This result 

underscores the inseparability of quantity and quality of life 

considerations. 

 One of the greatest challenges revealed by the life cycle framework is 

measuring the value people place on the reduction of threats to health that 

have their effects only after a latency period that may be many years in 

duration. Analysis of this problem is one of the contributions of section 

4.3. 
 Executive Summary 

1-23 

 The life cycle framework leads to the recognition that contingent 

valuation questions must be framed in a way that takes account of the 

respondent's life cycle situation. That recognition is reflected in the CV 

module of the contingent value approach considered later in Volume 4. It is 

also reflected in the health experience module, which obtains information on 

the life cycle experience most pertinent to health valuation. It is 

reflected in various ways in the defensive measures and risk modules. 

A Model of Uncertain Preferences for Explaining Inidividual Behavior Toward

Risk (Section 4.4) 

 Section 4.4 is another source of theoretical guidance to the study of 

life threatening illness. This section brings utility theory to bear on the 

problem of valuing small changes in events that are thought of only 

infrequently and may involve low probabilities of occurrence. This problem 

encompasses a large class of events, important to environmental policy, 

about which people's preferences are unclear--even to themselves. 

Researchers have found under these circumstances that people's expressions 

of value may appear internally inconsistent. Various explanations have been 

advanced to explain the phenomena. The present theoretical framework 

provides an approach, based on information costs rather than assuming 

irrational behavior, that is suited to estimating values of health risk 

reductions. 

 Section 4.4 brings economic theory to bear on the problem of how 

people think about and value small changes in small probabilities of damage 

to health or risk to life. The theoretical perspective is that 

environmental health risks are unfamiliar to most people, and that health 

risks are unfamiliar to most people, and that because people seldom have 

occasion to think carefully about them they are uncertain about their 

preferences concerning them. 

 The model developed in section 4.4 leads to a series of theorems that 

have implications about efficient ways of stimulating people to obtain 

improved knowledge about their own risk preferences and to state valid, 

consistent risk reduction values in a contingent valuation context. 

Apparent inconsistencies are interpreted as reflecting uncertain preferences 

among respondents. The framework is developed in a way that provides 

operational approaches to resolving these difficulties by assisting 

respondents in clarifying their own preferences. 

 The model unfolds in terms of a series of theorems that deal with the 

process of preference revelation. Several theorems address the problem of 

how respondents think about their preferences. One theorem is concerned with 

the question: Which would you rather have--a benefit (such as better health) 

or a sum of money. The theorem states that the closer the sum of money is to
 Executive Summary 

1-24 

the (unknown) value of the program benefit, the harder the respondent will 

think about the choice. Iterative bidding begins with a rather arbitrary 

starting point. In subsequent bidding, however, the theorem is applied by 

taking account of previous completed bids on related programs. The starting 

point is made identical or close to the final bid on the similar previous 

program to encourage careful thinking from the beginning. 

 An important objective is to realistically relate contingent goods to 

the respondent's own circumstances. This means tailoring the good to the 

respondents's own endowment. An implication of the theorems is that 

introspection. about preferences is much more effective when this is 

accomplished. Much of the work of this project was accordingly devoted to 

tailoring contingent market goods to individual endowments. 

Design of Contingent Valuation Approaches to Serious Illness (Section 4.5) 

 Section 4.5 brings together and applies all of section 4 research on 

life threatening illness. A structure for an intensive interviewing process 

is developed, based on tyechniques of in-depth interviewing. It embodies 

refinements growing out of focus group experiments conducted as part of the 

present project. 

 The proposed interview structure contains four modules. The interview 

is designed to be conducted with from six to ten people and last about four 

hours including breaks. The extended encounter is necessary because of the 

great difficulty of achieving its central task--obtaining values of events 

that entail small changes in small probabilities. 

 The first module concerns the repsondents' health experiences. It 

establishes the health endowmment and prepares respondents to give detailed 

thought to their health preferences and values. One possible approach, the 

health risk appraisal, gives a computer-based statement of respondents' risk 

of death by comparing their health characteristics with the average 

experience of a large population. It holds considerable promise for future 

application by permitting detailed tailoring of questions to respondents' 

own endowments, and construction of realistic life path scenarios for 

comparitive valuation. 

 The defensive measures module is the second module of the intensive 

interview framework. Defensive measures, or averting behavior, are a part 

of many people's efforts to increase the probability of good health over the 

life cycle. They are evidence of a willingness to pay for improved life 

prospects even when returns are not immediate. Smoking, diet, drinking and 

exercise are examples. This is a challenging area of research because it 

can not be measured by expenditurees; in some cases averting behavior 

entails increased expenditures (for example air
 Executive Summary 

1-25 

conditioning), while in other cases reduced expenditures occur (for example 

smoking). The defensive measures module develops some contingent market 

structures directed at obtaining expressions of willingness to pay for 

improved health prospects in terms of averting behavior. 

 The third module pertains to risk perception and risk behavior. This 

module begins by teaching respondents the basic notion of probability and 

relates it to their everyday experience. It then obtains information about 

their perceptions of and attitudes towards risk in a variety of situations. 

Next it conveys an idea of the kinds of probabilities that are involved in 

matters that concern their health. This module brings home to respondents 

the pervasive importance of risk in their lives and the fact that they have 

already made many conscious or subconcious judgements and valuations about 

risk. Thinking about these problems prepares them to think about the risks 

presented to them in the contingent markets that follow, and helps them to 

be more receptive to the contingent valuation exercise. 

 Contingent valuation questions form the fourth module. The contingent 

valuation module establishes contingent markets in health. There are 

hypothetical life experiences involving both quality and length of life that 

people are asked to evaluate in comparison with their own prospects, 

established in the health status module. The questions increase in 

complexity, beginning with simple questions involving certainty scenarios 

and mortality only. Next, serious illnesses are introduced, and respondents 

are asked their willingness to pay to eliminate the risks of getting 

diseases. These questions are followed by life path scenarios that combine 

morbidity and mortality in a life cycle setting. Alternative life path 

possibilities are presented and respondents are asked to choose among and 

value them, first in a certainty and then an uncertainty setting. 

 It is believed that the survey approach developed in Volume 4, and the 

extensive preparation for obtaining expressions of willingness to pay 

described in the modules, constitute an advance in survey research on the 

values of health improvements, and that intensive empirical applications are 

needed. 
19 ’

Final Report

VALUATION OF REDUCTIONS IN HUMAN HEALTH ___-_--_- _- _------_-- -- ----- ------

-------- SYMPTOMS AND RISKS -_- _----

Volume 2

COMPARATIVE ANALYSIS OF APPROACHES

TO VALUING HEALTH RISKS

George Tolley

Lyndon Babcock

and

Mark Berger

Anthony Bilotti

Glenn Blomquist

Michael Brien

Robert Fabian

Gideon Fishelson

Charles Kahn

Austin Kelly

Don Kenkel

Ronald Krumm

Tracy Miller

Robert Ohsfeldt

Sherwin Rosen

William Webb

Wallace Wilson

Martin Zelder

The University of Chicago

Cooperative agreement between the University of Chicago arid

the U.S. Environmental Protection Agency with participation b:;

University of Illinois at Chicago, University of Kentucky and

University of Wyoming.

USEPA Grant #CR-811053-01-O

PROJECT OFFICER: Dr. Alan Carlin

Office of Policy Analysis

Office of Policy, Planning and Evaluation

U.S. Environmental Protection Agency

Washington, D.C. 20460

January 1986
DISCLAIMER

Although prepared with EPA funding, this

report has neither been reviewed nor

approved by the U.S. Environmental

Protection Agency for publication as an

EPA report. The contents do not

necessarily reflect the views or policies

of the U.S. Environmental Protection

Agency, nor does mention of trade names or

commercial products constitute endorsement

or recommendation for use.
TABLE OF CONTENTS

Volume 2: Comparative Analysis of Approaches to Valuing

Health Risks

List of Tables

List of Figures

2.1 Introduction 2-l

2.2 Framework for Valuing Health Risks 2-3

2.2.1 Approaches to Valuing Health Risks 2-3

2.2.2 Human Health Risk Reduction Benefit

Model 2-6

2.2.3 Valuation of Changes in Risks to Human

Health 2-11

2.2.4 Concluding Remarks 2-20

2.3. Health Econometrics: An Assessment

2.3.1 Introduction and Overview

2.3.2 Findings in Health Econometric Studies

2.3.3 Assessment

2.3.4 Concluding Comments

2.4 Cost of Illness Approach

2.4.1 Introduction

2.4.2 Linking the Cost of Illness Approach to

Willingness to Pay

2.4.3 Individual Versus Societal Willingness

to Pay

2.4.4 Quality of Cost of Illness Estimates

2.4.5 Empirical Estimates of the Cost of

Illness

2.4.6 Concluding Remarks on the Cost of

Illness Approach

2-26

2-26

2-28

2-30

2-34

2-36

2-36

2-38

2-42

2-46

2-5i(

2- 70
2.5 Contingent Valuation of Health

2.5.1 Introduction

2.5.2 Overview and Assessment of

Contingent Valuation

2.5.3 Applications of Contingent Valuation to

Health

2.5.4 Conclusions and Summary

2.6 Comparing Cost of Illness and Contingent

Valuation

2.6.1 Introduction

2.6.2 Previous Work Comparing Cost of

Illnessand Contingent Valuation

2.6.3 Comparing Cost of Illness and

Contingent Valuation--New Results

2.6.4 Conclusions

2.7 Household Production of Health and Averting

Behavior

2.7.1 Introduction

2.7.2 Gerking and Stanley (1984)

2.7.3 Cropper (1981)

2.7.4 Conclusions

2.8 Property Values and the Value of Health

2.8.1 Introduction

2.8.2 Hedonic Analysis of Housing Markets

2.8.3 Implied Values of Mortality Risks

2-76

2-76

2-76

2-79

2-99

2-99

2-99

2-100

2-102

2-106

2-110

2-110

2-110

2-112

2-113

2-115

2-115

2-116

2-124

2.9 Conclusions: Interim Values for the Health Effects

of Air Pollution 2-131

2.9.1 Introduction 2-131

2.9.2 Framework for Valuing the Health Effects

of Air Pollution 2-131
2.9.3 Interim Values for the Health Effects of

Air Pollution 2-136
---- -- List of Tables --_---

Table

Table

Table

Table

Table

Table

Table

Table

Table

Table

Table

Table

Table

Table

Table

Table

Table

2-l Comparative Static Results of the Health Risk Model 2-15

2-2 Estimated Effects of 1 Microgram Per Cubic Meter

Increases in Selected Pollutants on the

Mortality Rate 2-32

2-3 Comparison of Cracker et al. and Chappie and Lave

Estimation Results 2-56

2-4 Total Medical Expenditures and Foregone Earnings Due

to Selected Illnesses

2-5 Per Case Medical Expenditures and Foregone Earnings

2-6 Background Information for Table 2-5

2-7 Cost of Illness Per Day Spent Ill

2-8 Contingent Values of Health from Loehman et al.

2-9 Contingent Values of Health from Tolley et al.

2-10 Willingness to Pay and Private Cost of Illness

2-11 Estimates of Marginal Prices of Air Pollution

2-12 Estimates of Elasticities of Demand for Clean Air

2-13 Framework for Health Values

2-14 Values of Acute Morbidity

2-15 Values of Chronic Morbidity

2-16 Values of Different Kinds of Mortality

2-17 Interim Values for Morbidity and Mortality Effects

of Air Pollution

2-62

2-62

2-64

2-69

2-85

2-96

2-103

2-118

2-123

2-132

2-138

2-140

2-158

2-161
VALUATION OF REDUCTIONS IN HUMAN HEALTH SYMPTOMS AND RISKS --------- -- -_---__--- _- ----- ------ -------- --- _____

This is Volume 2 of a four volume report. The total project

undertakes an assessment and reconciliation of attempts to value

reductions in human health risks, and it develops new methods and

estimates for these values. Volume 2 contains a comparative

assessment of work on valuing health risks. Based on the

assessment, a set of interim morbidity and mortality values

applicable to effects of criteria air pollutants is developed.

Volume 3 reports on a study developing and applying contingent

valuation techniques to the types of light symptoms often

attributed to air pollution. Volume 4 reports on the design of

approaches for valuing serious or life threatening illnesses.

Abstract of Volume 2 -------- -- ------ -

COMPARATIVE ANALYSIS OF APPROACHES TO VALUING HEALTH RISKS

Following the introduction to Volume 2, section 2.2 presents

a model for valuing health risk reductions which can be used to

compare alternative approaches to valuing health risks.

Plausible assumptions imply that cost of illness and preventive

expenditures measures are lower bounds to willingness to pay for

health risk reductions. Contingent valuation, hedonic measures

and other valuation approaches are compared conceptually.

Section 2.3 gives a critique of econometric evidence on the

effects of environmental quality on human health. One of several

concerns with comparability and reliability is how estimates are

affected by avoidance measures taken by individuals in response

to adverse environmental conditions. The assessment considers in

detail five major empirical studies of the effects of air pollutants on mortality.

Section 2.4 is concerned with the cost of illness approach

to measuring health benefits. A contribution of the present

project is to put estimates of the aggregate cost of illness

(medical expenditures and foregone earnings) due to morbidity on

an individual per case and per day spent ill basis. Section 2.~

includes an evaluation of previous cost of illness studies.

Section 2.5 is concerned with contingent valuation studies

in which interview estimates are obtained of willingness to pav

for health. The three major existing contingent valuation studies of morbidity are evaluated.

In Section 2.6, a comparison is conducted of cost of illness

and contingent valuation benefit measures obtained for a group of

individuals for a common set of symptoms. The results indicate

that willingness to pay as revealed through contingent valuation

greatly exceeds cost.of illness. The two measures do not mo*:*
together in any systematic fashion,

Section 2.7 considers the household production approach, in

which the individual produces health by combining his own time

and effort with purchased goods. Two studies are reviewed that

use this framework to produce illustrative empirical estimates of

willingness to pay for health improvements.

Section 2.8 reviews the housing market hedonic literature

throwing light on housing price premiums for air quality. Estimates from this literature are used to obtain suggestive upper

bound estimates of the value of mortality risks.

Section 2.9 brings together the foregoing results to arrive

at a set of health risk values for use in environmental assessments. Interim values applicable to air pollution are developed,

High, low and medium estimates are developed for morbidity conditions and mortality. Medium estimates of the value of reducing

various types of acute or short term morbidity range from $25 to

$125 per day. Medium estimates of the value of reduced aggravation of previously existing chronic morbidity conditions range

from $60 to $150 per day. Medium estimates of the value of reduced new incidence of chronic morbidity conditions range from

$800 per year for uncomplicated angina to $60,000 per year for

non-fatal cancer. The medium estimates for mortality range from

$2 million for an unforseen instant death to $4 million for a

death due to lung cancer.
___- List of Figures -- -- ----

Figure 2-l Endogeneous Health and Environmental Quality 2-27

Figure 2-2 Benefits of Air Quality Improvement 2-117
2. COMPARATIVE ANALYSIS OF APPROACHES TO VALUING HEALTH RISKS

2.1 INTRODUCTION

A wide variety of approaches to valuing health risks or the

benefits of health improvements have been proposed and in many

cases implemented. Though this work has been reviewed, there is

a continued need for a comparison of the various approaches, on

both a theorectical and an empirical level. In particular, while

the special case of valuing mortality risks alone has received a

good deal of attention, the problems of valuing morbidity risks

alone, or of valuing the more general case of a combination of

morbidity and mortality risks has received less attention. The

goal of Volume 2 is to provide a comparative review of approaches

to valuing changes in health, and a synthesis of the empirical

results of the various approaches..

In the next section, competing approaches are defined and

briefly reviewed, but the main result is the development of a

model of health investment which yields a general expression for

the value of changes in risks to human health. Thus section 2.2

serves as an introduction to, and a conceptual framework for, the

remainder of the volume. The contention that costs of illness

and preventive expenditures are lower bounds to the preference

based willingness to pay measure is carefully examined. In

addition, the section explores the relationship between the value

of a certain change in health, and the value of a change in

health risks.

In the remaining sections, the theoretical justification and

empirical results of the particular approaches are examined at

greater length. The general goal of these sections is to

discover what empirical estimates of the value of health exist,

and to assess how accurate and complete these value estimates are

likely to be.

Section 2.3 reviews health econometric results on the

relationship between air pollution and health. These studies may

shed light on the structure of the demand for health, and the

role of avoidance practices undertaken by individuals in response

to poor environmental quality. If so, the results will have

important implications for measuring the benefits of improved

health due to air quality improvements.

Turning to studies that have been explicitly concerned with

placing monetary values on illness, section 2.4 reviews the cost

of illness approach. This is the most widely usedmeasure of the

value of health. Estimates from existing aggregate cost of

illness studies are put on a per case of illness or per day of

illness basis, to be comparable to what an individual would be

willing to pay. In this way, estimates of the value of a range

of health effects are developed that can be used to evaluate

environmental policy changes. A careful review of the conceptual

and empirical backgound of the cost of illness approach is also

undertaken.

2-l
Section 2.5 examines the results of the limited number of

studies that apply the contingent valuation method to valuing

morbidity. This section includes the new results from the

contingent valuation experiment discussed in detail in Volume 3

of this report. Consi'deration is given to the questions of how

accurate estimates from contingent valuation may be, and to how

results from the different studies compare.

Since the cost of illness approach and contingent valuation

are probably the most important methods currently used to value

morbidity, Section 2.6 reviews the available evidence on how

these two methods compare. The most conclusive evidence on this

question is from the data collected in the contingent valuation

experiment of Section 3. Section 2.6 uses these data to test the

hypothesis that a cost of illness measure is a lower bound to

willingness to pay as revealed by contintent valuation.

Section 2.7 draws out implications for the value of health

from studies of the household production of health. While

relevant work is extremely limited, two studies are reviewed that

yield illustrative.empirical estimates of the value of acute

morbidity due to air pollution.

Section 2.8 reviews work relating property values to air

quality. A number of conceptual and econometric issues that have

Yet to be totally resolved are examined. Following this

discussion, the relationship between housing values and air

quality is used to imply values for mortality risks.

Section 2.9 is a synthesis of the results from the previous

sections. Based on what is known about the health effects of air

pollution, and on what a complete estimate of the value of health

would include, a framework for estimating the value of health is

reviewed. Using this framework, a table of interim values for

the morbidity and mortality effects due to air pollution is

developed.

2-2
2.2. FRAMEWORK FOR VALUING HEALTH RISKS

In this section we develop a model of health investment

which yields a general expression for the value of changes in

risk to human health. The preference based values of morbidity

risks and mortality risks are ex ante dollar equivalents of

changes in expected utility associated with risk changes. The

values of changes in morbidity risks and and mortality risks are

related to two alternative measures, costs of illness and

preventive expenditures, which are thought to be lower bounds on

the value of risk reductions. We demonstrate that these

alternative measures are not even special cases of the more

general measure and that the size relationships among the three

measures are complex. Also, we derive the relationship between

willingness to pay for risk changes and the consumer surpluses

associated with health changes which occur with certainty.

The section begins with a review of several approaches to

valuing changes in risks which are currently in use. The model

of health risk behavior is developed in Section 2.2.2. In

Section 2.2.3 implications for benefit estimation of the benefit

measure derived from the model are discussed and concluding

remarks are given in Section 2.2.4.

2.2.1. Approaches ------A --To Valuing Health Risks ____-- ------ -----

2.2.1.1. Cost of Illness

The traditional approach to measuring the benefits of

improved health is based on avoidance of disease damages. The

damage avoidance approach, which is the form used by health

professionals and some health economists, is also referred to as

the cost of illness approach or sometimes the earnings

expenditure approach. The cost of illness approach relies

heavily on the idea that people are producers i.e., human

machines. Outlays for health services are seen as investments

which improve people as productive agents and yield a continuing

return in the future. The yield for improvements in health is

the labor product created plus any savings in health care

expenditures due to any reduction in disease (see Mushkin 1962.

PP. 130 and 136). The costs of health degradation are the

damages caused by the disease (or accident). The health

expenditures made, the value of the resources used in supplying

health care, are referred to as the direct cost of illness. The

loss of labor earnings due to sickness and premature death, the

value of the lost product of labor, is referred to as the

indirect cost of illness. The value of health improvements is thr

sum of the reductions in direct and indirect costs of illness.

i.e., the damages which will be avoided. Studies employing the

cost of illness approach include Weisbrod (1971), Cooper and Rice

(1976), and Mushkin (1979).

Several deficiencies in the cost of illness approach arr

recognized: (1) the indirect costs are zero for retirees, ful i

2-3
time homemakers and other people who do not work in the market,

(2) an arbitrary decision must be made about forgone consumption

expenditures, i.e., gross or net labor earnings, (3) individuals

are viewed as having no control over their health or health care

expenditures and (4) there is little basis in economic theory for

the use of the costs of illness in benefit-cost analysis. An

attempt has been made by Landefeld and Seskin (1982) to

reformulate costs of illness values to more closely approximate a

theorectically correct measure, but their study primarily focuses

on externalities and an approach more closely tied to individual

optimization seems more appropriate. Section 2.4 below examines

in much greater detail the cost of illness approach as a possible

source of estimates of the benefits of health risk reduction.

2.2.1.2. Willingness to Pay in Contingent Markets

The absence of a market for health as such prompted

consideration of direct questioning techniques to elicit

willingness to pay for changes in health risks. Through a survey

interview or laboratory experiment a hypothetical market is

established, and individuals are asked to purchase changes in

health directly contingent upon the existence of the market.

Contingent valuation of mortality risks was pioneered by Acton

(1973) in his study of heart attack treatment and has been used

by Loehman (1979) et al. to value morbidity related to air

pollution. Currently there is renewed interest in direct

questioning because it yields conceptually correct values of

health risk which are difficult to estimate using other

techniques.

Contingent valuation is considered in detail in Volume 3 of

this Report, and empirical results applied to the value of

morbidity are reviewed in section 2.5.

2.2.1.3. Household Production of Health and Preventive

Expenditures

While the cost of illness approach concentrates on damages

or costs following the onset of illness, individuals can and do

incur costs in efforts to prevent illness from ever occurring.

In Grossman's (1972) model of consumption and production of the

commodity "good health", individuals combine purchased goods such

as medical care and their own time to produce health capital.

Willingness to pay is the value ofhealthytime and is the sum of

two terms: (1) the increment in labor earnings which is possible

and(2)the monetary value of the gaininutility associatedwith

better health. Thus, the household production model gives a

conceptual foundation for the relevance of labor earnings

(indirect costs) for morbidity, but it also implies that a

preference-based value will depend on the costs of producing

health (preventive expenditures) and a utility, or consumption,

value. An example of the household production approach is

Cropper's (1981) micro study of the effect of air pollution on

days lost from work due to illness. To value the health changes

2-4
she multiplies the wa e

F

rate by a factor derived from a specific

production function. This study and a study by Gerking and

Stanley (1984) are discussed in section 2.7.

The recognition that health is partly endogenous has also

spawned the idea that health improvements permit a reduction in

preventive expenditures and that the savings of preventive

expenditures is the value of the health improvement. This

general approach has been suggested as a way to measure the

benefits of reducing pollution where the expenditures prevent not

only damages to human health, but also damages to property and so

forth. Courant and Porter (1981) characterize the literature as

having reached a limited consensus that such expenditures

represent a lower bound to the total costs of pollution, a

conclusion they dispute.

In a recent empirical investigation, Smith and Desvousges

(1985) find that households do make adjustments to reduce the

risk of exposure to hazardous wastes through drinking water. In

their sample of households in suburban Boston nearly thirty

percent purchased bottled water regularly to avoid hazardous

wastes, while smaller fractions installed water filters and

attended public meetings as ways to reduce the risks. This study

provides important evidence that averting or preventive behavior

in response to pollution risks can be significant. However, the

relation between preventive expenditures and the benefits of

improved health has received little attention. We explore this

relationship.

2.2.1.4. Willingness to Pay in Implicit Markets

One implication of household production models of health is

that individuals will make expenditures of money and time to

improve their health and reduce risks to their health. By

observing people's behavior in well-developed markets for

ordinary goods and services values can be derived for health,

which is not traded explicitly. Much of this type of evidence

comes from the labor market in the form of estimates of

compensating wage differential for jobs with extraordinarily high

risks to health and survival. Most of the studies focus on

implicit values of changes in the risk of a fatal accident.

Consumption activity also can involve exchanges between

health and safety and other desirables. Estimates of willingness

to pay have been made based on analyses of residential housing

site choice, automobile seat be t use, speed of travel on

highways and cigarette consumption. 2 This work, like that in the

labor market, has focused on mortality risk. Inherent in this

methodology of estimating implicit values of health risks is that

individuals know and perceive differences. in health risks

associated with various jobs and consumption activity and that

they can choose among various alternatives.

2-5
Theoretical and empirical problems in viewing housing

markets as implicit markets for valuing health are examined in

Section 2.8. Estimates from these studies are reviewed as well.

2.2.1.6. A General Framework for Valuation

At this point there appear to be two disparate approaches to

valuation of health and risks: cost of illness perhaps inclusive

of preventive expenditures, and willingness to pay. Research has

proceeded using one approach or the other, but only limited

effort has been made to compare and reconcile the approaches. A

recent paper by Harrington and Portney (forthcoming) is

noteworthy in that they show that for morbidity, under certain

conditions, the cost of illness values will be a lower bound on

the theoretically preferred willingness to pay values. Below we

develop an eclectic model with endogenous health risks and derive

the preference based values for changes in health risks. The

model considers morbidity and mortality and allows the

probabilities of various health states and survival to be

influenced by preventive activity and exogenous factors such as

environmental quality. Terms for preventive expenditures and

costs of illness in the benefit expression are identified for

purposes of comparison with the conceptually correct willingness

to pay. The model provides a framework for comparing values of

health risks estimated using various techniques.

2.2.2. ----- ------ ---- --------- ------- Human Health Risk Reduction Benefit Model -----

Assume a person's utility depends on the consumption of

goods and services and the state of health. Utility may be

expressed as

(1) u - U(C,q> I

where U is utilijzy, C is consumption and q is a vector of health

characteristics.

A person does not know with certainty, however, what his

health will be, or for a given state of health, whether or nothe

will survive the period in question. In order to incorporate

these uncertainties into the model, we specify probability of

health characteristics and probability of survival functions.

The probability density function for health characteristics can

be represented as

(2) h(q;X,E),

2-6
where X is preventive expenditures and E is any exogenous shift

variable, such as environmental change. Thus, the health

characteristic probabilities are not immutable, but rather are

influenced by preventive measures chosen by the individual person

and exogenous changes ‘such as environmental improvement.

It is reasonable to assume that the healthier a person is,

the greater are the chances of survival of a given period. In

other words, probability of survival can be expressed as a

function of health characteristics:

(3) P - p(q),

where p is the probability of surviving the period.

A final element of the model facilitates comparisons with

the cost of illness approach for valuing health risk reductions.

When in poor health, a person incurs cost such as medical

expenditures and earnings lost due to days not worked. These

costs will vary according to the degree of illness malfunction

that occurs:

(4) z - f(q),

where Z is the cost incurred as a result of illness malfunctions.

These expetditures reduce consumption, and provide no utility on

their own.

In this framework, a person chooses preventive expenditures

X, in order to maximize the expected value of utility given the

following income constraint:

(5) M - C +x + z,

where M is money incogme in the absence of any' costs due to

illness malfunctions, Preventive expenditures influence the

expected value of utility in three ways: (1) X increases the

probability of being in good health, therefore increasing utility

if alive; (2) at the same time, increasing the probability of

being in good health also increases the probability of being

alive; (3) finally, by increasing the probability of being in

good health, X expenditures decrease malfunction costs Z that can

be expected, increasing the amount of income expected to be left

over for consumption. These benefits must be weighed against the

direct loss d-

'n consumption made necessary by the preventive

expenditures.

More, formally, the consumer's problem can be stated as

2-7
.

(6) Max E(U) - the integral from negative infinity

to positive infinity of

subject to the income constraint (5). Reexpressing the income

constraint in terms of C and substituting it into (6), the

consumer's problem becomes

(7) Max E(U) - the integral from negative infinity

to positive infinity of

1 U(M-X-f(q>,q>p(q>h(s;X,E)dql

where U,

p7

and h come from equations (l), (3) and (2)

' respectively.

The integral in (7) gives utility under different health

outcomes weighted by the probability of the various outcomes.

Since utility always depends upon health, the situation could be

described as a continuum of state dependent utility functions,

the possible states being the possible health outcomes.

Different attitudes toward risk are allowed for through the shape

of each state dependent utility function. When utility is

expressed as U(M-X-F(q),q), it becomes apparent that preventive

expenditures X directly reduce the amount of income left over for

consumption. The term p(q) in (7) adjusts utility by the

probability of being alive. Assuming no utility if dead, U(M-Xf(q), 4)

health.

p(q) gi.ves expected utility conditional on the state of

A more extended analysis might consider utility of heirs

as affected by bequest. The density function h(q;X,E) weights

expected utility by the probabilities of different states ol

health. The integration over health states thus gives expected

utility for the period;

The model as described does not specify fully the mechanisms

available to the individual to adjust to risk such as market

insurance. The only opportunity the individual has is to make ex

ante preventive expednditures X that change the probabilities of

the different states. V. Kerry Smith suggests that another

extension of this analysis could be to carefully describe what

opportunities are av.ailabe to the individual to adjust

expenditures made in each state of the world. Though these

opportunities could easily be made explicit in the present model.

this section retains the simpler framework in order to make the

comparisons between preventive expenditures, cost of illness, and

willingness to pay for risk reductions more straight forward

However, in general willingness to pay values are affected by the

opportunities available to adjust to risk, so it is vital to not*

the simplified framework used.

2-8
The problem also becomes more tractable if a single health

outcome measurable as a zero-one condition is considered. An

example is occurrence of a specified type of cancer as affected

by environmental irritants. Another example is occurrence of

traffic accidents due to poor visibility brought on by air

pollution, provided the major cost is associated with frequency

of accidents, all having about the same expected severity, rather

than the severity of an individual accident being importantly

related to the degree of visibility. Tissue damage from contact

with pollutants, such as liver damage,

as the principle effect is

is another example as long

absence of unimpaired functioning

rather than the degree of malfunctioning being associated with

the degree of pollutant level.

A damage function, as might be the case for ozone, where the

degree of discomfort rather the presence or absence of discomfort

is related to the level of pollution, requires a more extended

analysis considering probabilities for more than two states of

the world. Various degrees of symptoms along with their

associated probability densities have to be considered rather

than just presence or absence of symptoms. The integral in (7)

would not simplify as it does in the case where there is only one

malfunction state.

If health is a matter only of absence or presence of a

deleterious condition, the probability density function h(q;X,E)

is discrete rather than continuous with probability concentrated

at q-l for presence of condition and q-0 for absence of

condition:

(8) h(q;X,E) - H(X,E) if q-l

h(q;X,E) - (1 - H.(X,E)) if q-0,

where H(X,E) is the probability of the absence of the condition.

In this case, the person decides at the beginning of the

period what his preventive expenditures will be and then takes

the resulting chance of what the health outcome will be for the

period. A long planning period can be considered by letting

consumption expenditures, illness costs, and preventive

expenditures be average discounted present values, with the

probabilities associated with survival and health status being

averages of shorter term probabilities, possibly allowing for

cumulative exposure effects.

Because of the discreteness of q when health is a matter

only of the absence or presence of a condition, the integral in

(7) simplifies to a sum of two discrete states corresponding to

q-0 and q-l. Using (a), the consumer's maximization problem is

2-9
(9) Max E(U) - UOPO(l-H)+UIPIH

where UO - U(M-X,O)is utility if free of the disease

ul - U(M-X-Z,l) is utility with the disease

pO -p(O) is probability of survival iffree ofthe

disease

Pl - p(l) is probability of survival with the disease

H - H(X,E) is the probability of contracting the disease.

Equation (9) states that the expected utility to be maximized is

the sum of utilities in the absence and the presence of the

deleterious health condition, weighted by the probabilities of

contracting and not contracting the disease and of surviving. As

can be seen from the expressions for U. and Ul, utility depends

both on the presence or absence of the disease, i.e. there is

state dependence. The income constraint has been substituted

into the utility function just as in equatio3 (7). In the

discrete case, this constraint can be expressed as

(10)

C - (M - X) if q - 0,

C - (M - X - Z) if q - 1.

Differentiating equation (9) with respect to preventive

expenditures X and setting the result equal to zero gives the

first order condition for a maximum:

(11) F - U' P (l-H)-(U'P H) - (U P H ) + (U P H ) - 0,

0 0 1 1 0 0 x 11x

where U' and U' are the marginal utilities of income when q - 0

0 1

and q-l respectively, and H,, the change in the probability of

contracting the disease resulting from an extra dollar spent on

prevention. The first two terms give the decline in expected

utility due to decreased consumption when an extra dollar is

spent on defensive measures. The last two terms give the rise in

expected utility due to decreased probability of contracting the

disease as a result of the extra dollar spent on prevention. The

first order condition for a maximum is that the sacrifice of

consumption given by the first two terms must just offset the

gain from the reduced probability of contracting the disease

given by the last two terms.

In order for the consumer to obtain a maximum, the second

2-10
derivative of the expected utility function with respect to

preventive expenditures must be less than or equal to zero. This

second-order condition can be expressed as

(12) delta - - U"P (l-H)-(U"P H) - (U P H ) + (U P H > < 0,

0 0 1 0 0 xx llxx -

where H,, = is the second partial derivative of H(X,E) with

respect to X, and U". and U" 0 are the second derivatives of

utility with respect to income when q-0 and q-l respectively.

2.2.3. ---e----B Valuation Of Changes -- ---- -- --In Risks To Human Health s---m -- ----- --___-

2.2.3.1. Willingness to Pay

Expressions for the marginal willingness to pay (WTP) for an

exogenous reduction in health risks can be derived from this

model. The totally differentiated expected utility function must

be solved for the change in income thatwouldbe required to keep

expected utility constant when there is an exogenous change. The

individual would be willing to pay the negative of this

compensating variation for the exogenous improvements in health

risks.

(13) dE(U) - [U' P (1-H) + U'P H] dM

0 0 1 1

+ [(-VIP (1-H)) -(U P H ) - (U'P H) + U P H ] dX

0 0 0 0 x 1 1 11x

+ [(-U P H ) + (U P H )] dE

OOE 11E

As before, U' and U' are the marginal utilities of income

0 1

when healthy and ill, respectively. Just as with the levels of

utility, these marginal utilities may differ from each other for

two reasons. First, the level of consumption is higher when

healthy, because of the costs incurred when ill (Z). Second, the

presence or absence of a condition directly enters the utility;

function.

Holding expected utility constant in equation (13) bv

settinggdE(U) - 0, equation (13) can be solved for the WTP

measure:

(14) - dM/dE - - [(uopo- ulpl>/ '=I+

[1 + uuopo - UIPI)/ m)H,]dX/dE.

2-11
The numerator of the first term is the difference in expected

utility when healthy and when ill. This is div.ided by m -

(U'P (1-H) + U'P H), which is a weighted average of the expected

0 0 1 1

marginal utility when healthy and the expected marginal utility

when ill, with the weights being the probabilities of being

healthy or ill. Thus m can be interpreted as the expected

marginal utility of income.

So far, the analysis has neglected the fact that individuals

choose the level of defensive expenditures so as to maximize

expected utility. Rearranging the first-order condition given by

equation (11) yields:

(15) (“opo - UIPl)/m - -l/H,.

The left hand side is familiar from the WTP expressions. As the

dollar value of the difference in expected utilities when healthy

and ill, it can be interpreted as the marginal benefit of

defensive expenditures that reduce the probability of illness.

The right hand side is the marginal cost of defensive

expenditures.

Allowing the optimal choice of defensive expenditures as

individuals adjust to the exogenous changes in health risks or

the environment implies that equation (14) satisfies the first

order conditi,on. Substituting the first order condition as given

by (15) into the WTP expression given in (14):

(16) - dM/dE - HE/H, + L-1 + W,/H,HdV - HE/H,.

This simplification allows the WTP measure to be expressed

independently of the non-observable utility function, but instead

in terms of the health risk function H. In particular, equation

(16) gives the WTP for a change in environment as a ratio of the

marginal product of the environment in reducing health risks and

the marginal product of preventive expenditures in reducing

health risks. This result is very similar to the findings of

others who suggest WTP for an environmental improvement can be

expressed solely in terms of the production function (see Courant

and Porter (1981), Harrington and Portney (1983),, Gerking and

Stanley (1984), and Needleman and Grossman (1983)). One obvious

difference is that while in these models health is

deterministically a function of the environment and defensive

expenditures, in our model the probabilities of being healthy or

ill are a function of these variables. Another difference is

that our model considers mortality as well as morbidity.

Equation (16) is the basis for one approach to obtaining

2-12
empirical estimates of willingness to pay. In principle, the

health risk function H(X,E) could be estimated, yielding the

marginal products necessary to compute WTP. Gerking and Stanley

(1984) use this strategy to estimate WTP for ozone reductions in

a model with pure morbidity under certainty. (See section 2.7

for a discussion of this study). However, Harrington and Portney

(forthcoming) and Maureen Cropper emphasize the difficulties in

correctly estimating a health or health risk production function.

The fundamental problem with the health production function

approach is that it is hard to identify and measure all of the

inputs that affect health. Harrington and Portney point out that

typical epidemiological studies only explain a small fraction of

the total variation in illness, suggesting that a number of

important variables may have been omitted. In estimating a

health production function applicable to air pollution-induced

morbidity, the health outcome would be acute respiratory illness

and not general health status. This could make the empirical

estimation even more difficult, since respiratory health is

jointly produced with other aspects of health. Finally, equation

(16) only holds as a marginal condition. Bockstael and McConnell

(1983) show that it may also be very difficult to use the

household production approach to estimate the value of nonmarginal changes. All of these problems indicate that the health

production function approach to estimating WTP may be of limited

usefullness. Below, other estimation strategies are

investigated.

To allow for a more intuitive interpretation, equation (16)

can be rewritten recalling that H - H(X,E)

(17) dH/dE - Hx(dX/dE) + HE

or rearranging,

HE - (dH/dE) - H,(dX/dE).

Substituting this expression for the marginal product of the

environment in reducing health risks into equation (16) we have

(18) - dM/dE - [(dH/dE) + H,WWEHWH,)

- (l/H,)(dH/dE) - (dX/dE).

Writing this benefit expression in terms of utility by using the

left hand side of the equation (15) we have

(19) - dM/dE - - [(UoPo - UIPl)/ml(dH/dE) - (dX/dE).

This form of the benefit expression states that a person's WTP

2-13
for an environmental improvement can be expressed as the sum of

two terms. The first term is the dollar value of the expected

difference in expected utilities when healthy or ill multiplied

bY the change in health risks due to the change in the

environment or other exogenous factor. The second term is the

change in preventive expenditures resulting from the exogenous

change.

Our model yields an expression for willingness to pay which

is ex ante in nature, i.e., before it is known whether or not the

individual is sick. The value is that amount of income we have

to take away from both states to keep expected utility constant.

The value is defined by:

(20) U P (1-H) + U P H - U.(M-X - dM/dE,O)P (1-H)

0 0 1 1 0

h h

- U(M-X-Z dM/dE, 1) P H - 0

0

where the * indicates the value of a variable after a change in

E. In the context of uncertainty our willingness to pay,

-dM/dE, is similar to an option price (see Smith (1983)), since

it is a constant payment regardless of the state of nature that

actually occurs. V. Kerry Smith points out that in the model

described in this section, however, the framework in which

individuals can purchase state contingent contracts is not fully

specified, so it is difficult to restrict the payments to be

constant across the states of nature. As explained earlier, the

only opportunity for individuals to adjust to risk is the

purchase of preventive expenditures. These features of the model

mean that the willingness to pay measure, -dM/dE, may not be

consistent with conventional measures of option price. The

measure is nevertheless a valid ex ante compensating variation

for changes in risk.

2.2.3.2 Comparisons to Preventive Expenditures and

Costs of Illness

It seems natural to assume that people will pay a positive

amount for an environmental improvement. This means that to keep

expected utility constant in the face of an exogenous improvement

in the environment, an individual's income would have to be

reduced, i.e., dM/dE < 0 and positive willingness to pay is

equal to - dM/dE. Inspection of the benefit expression given in

equation (17) reveals that WTP could be positive if both terms,

the utility value and the preventive expenditure value, are

positive. Since the total derivatives, dH/dE and dX/dE, show how

risk and expenditures change after optimizing behavior, however,

the terms cannot be unambiguously signed. For the total

derivatives the general and plausible results and accompanying

conditions are summarized in Table 2-l.

2-14
TABLE 2-1: COMPARATIVE STATIC RESULTS OF THE HEALTH RISK MODEL

General Result Plausfble Results

Sufficient Condftfons

for Plausible Results

Preventive

Expenditures

Morbidity Risk

Wfllfngn&s to Pay and

Preventive Expenditures

. a

Willingness to Pay and

Cost of Illness

a

Willingness to Pay and

Preventive Expenditures

- Pure Morbidity Case

.a

Willingness to Pay and

Costs of Illness

- Pure Morbidity Case

.a

dM;dX . *

- aK-TE

gco .

'Willingness to pay is equal to - $.

HEX > 0 and

N,P, - UIP1) > 0 and

($Po - u;PQ 2 0.

g< 0 and

HE > HX g .

or

g2 0.

g<Oand

Many exist

g< 0 and

g< 0.

. $ < 0 and

$ < 0 and

UK,01 > U&I) and

U(Z)h** > z

bit is implausible that - g = - 2%. A set of sufffcient conditions for this result is

dX

dE’ -

0, U (.) f U (.;q), U (.,2)/x* P Z, and PO = PI = 1.

2-15
Preventive Expenditures

Consider the expenditure response of the individual to a

change in the environment, dX/dE. Using the first order

condition, F, shown in equation (11) and the implicit function

rule, its-follows that:

(21) dX/dE = - FE/FX - - FE/delta

where delta < 0 from the second order condition given by equation

(12). The sign of dX/dE then is the same as the sign of Fe.

Differentiating F with respect to E we get:

(22) F - (U'P - U'P > H - (U P - U P ) H

E 0 0 11 E 0 0 11 EX

which cannot be signed unambiguously. The implication is that

dX/dE need not be negative in that preventive expenditures could

increase with an environmental improvement. Nonetheless, under

plausible conditions dX/dE will be negative. If HEX > 0, which

is the case if H and E are substitutes,and if (UoPo - UIPl) > 0,

which is the case if expected utility when healthy exceeds the

expected utility when sick, and if the difference between

expected marginal utilities is small, then

then dX/dE < 0.

FE < 0. If FE < 0,

Change in Health Risk

The risk response to a change in the environment, dH/dE.

depends in part on dX/dE as can be seen from equation (17). The

sign of dH/dE is negative if dX/dE < 0 and if HE is larger in

absolute value than H dX/dE; the sign of dH/dE is also negative

if dX/dE >_ 0. In otE er words, the sign of dH/dE is negative

except' when dX/dE < 0 and, what seems to be unlikely, the direct

effect (HE) is less than the indirect effect (HE dX/dE). While

it is possible that the indirect effect can dominate even where

there is evidence of counterproductive exogenous changes,

alternative explanations are offered as being more plausible,

e.g. see Viscusi (1984).

.The upshot of this discussion is that while the two terms in

equation (19) taken together surely imply that a positive amount

will be paid for an environmental improvement, it is not strictlv

true that the terms separately will each imply positive payments

It is the case, however, that the payments for reductions in risi

and preventive expenditures will be positive under the plausib!c

conditions that X and E are substitutes and the direct effect ot

E on H dominating the indirect effect through dX/dE. Under these

conditions the willingness-to-pay for an environmental

2-16
improvement is the sum.of the utility value of the reduction in

risk and the savings in preventive expenditures. Also under

these conditions the savings in preventive expenditures, dX/dE,

is a lower bound on willingness to pay. If the conditions

described above do not hold, then dX/dE is not necessarily a

lower bou-nd on WTP. Under no plausible conditions is dX/dE a

special case of WTP.

Cost of Illness

On the basis of the benefit expression it is tempting to

consider a value of exogenous improvement based solely on the

costs of illness as special case of the general WTP measure.

Indeed, there might appear to be conditions under which the

expression approaches being a special case of WTP. For instance,

if (1) defensive expenditures are nonexistent or unchanging, and

if (2) health does not enter the utility function directly, the

WTP expression shown in equation (19) collapses to the first

term, and the difference in expected utilities when healthy and

ill only reflects the reduced level of consumption when ill due

to the costs of illness incurred, Z. Even with these severe

restrictions, however,

U(M-X)P - U(M-X-Z)P

0 1

(23) - Z dH/dE f ----------------------- dH/dE

m*

where m* - U'[PO(l-H) + PIH]. For Z to equal WTP additional

questionable restrictions are necessary. For example sufficient

conditions are that (3) the monetary value of the utility of

consumption be equal to consumption expenditures, Z - U(Z)/m*,

and (4) the probability of survival be equal to one, PO - Pl - 1,

see Table 2-l. In fact, there are no plausible assumptions which

can be made to simplify the WTP measure to cost of illness. It

is even less likely that WTP will equal Z*, the more commonly

used cost of illness measure which excludes the value of lost

nonwork time.

Morbidity Risk

For the sake of brevity and because considerable attention

has been given to mortality risk in pr?Jious articles we focus on

valuing changes in morbidity risks. For the pure morbidity

case, there is no possibility of death whether healthy or ill, so

PO - Pl - 1. The general WTP expression, equation (19),

simplifies to:

2-17
U(M-X,0) - U(M-X-Z,l)

(24) - dM/dE I i ----_-------------__-- dH/dE - dX/dE

P-P-1 m-k*

0 1

U - u

0 1

I - -m-------e dH/dE - dX/dE

m**

where m* - U'(l+H) + U'H

0

which is expected marginal utility of

1

consumption for the morbidity case.

The relationship between WTP and preventive expenditures is

again, as in the case of morbidity and mortality, complex in that

neither is unambiguously larger than the other. however,

under similar plausible conditions

Again,

dX/dE is lower bound on WTP;

see Table 2-l.

As in the case of morbidity andmortality there is no reason

to believe that WTP equals the savings in costs of illness, - Z

dH/dE. Plausible conditions do exist however, under which - Z

dH/dE is a lower bound on WTP. If dH/dE < 0 and dX/dE < 0,

then WTP > - Z dH/dE because Z dH/dE. One reason is that

health enters directly in the utility function and utility is

enhanced by health; U(C,O) > U(C,l). Another reason is that we

expect the dollar value of utility lost due to losing Z dollars

of consumption to costs of illness is less than Z. This

relationship between the value of the utility of consumption and

consumption expenditures, or labor earnings, has been explored in

depth in the "value of life" literature. Conceptually it cannot

be shown, strictly, what the empirical relationship should be,

see Linnerooth (1979). Still, a representative theoretical

conclusion is that the value of utility of consumption or

earnings will "usually" exceed their dollar value; see Bergstrom

(1982). Reviews by Blomquist (1981, 1982) and Violette and

Chestnut (1983) of the estimates of the value of mortality risks

are consistent with Bergstrom's conclusion. The implication for

our case of morbidity is that U(Z)/m** >' Z dH/dE. This

relationship along with U(C,O) > U(C,l) lead WTP > - Z dM/dE. If

also dX/dE < 0, then WTP exceeds - Z dH/dE by a greater amount.

so, while we cannot definitely conclude that cost of illness

measures produce a lower bound for willingness to pay, the lower

bound conclusion seems plausible. These results are sumarized in

Table 2-l.

2.2.3.3 Comparisons to Certainty Values of Morbidity

The willingness to pay expression in the pure morbidity case

is shown in equation (24). The WTP holds expected utility

constant in the face of an exogenous change in health risk. This

2-18
can be compared to measures of certain changes in morbidity as

follows.

Define consumer surplus (CS) as the dollar amount which

holds utility constant in moving from the certainly sick to the

certainly well state. For an irreplaceable commodity such as

health this measure is what Cook and Graham ((1977) call a

"ransom." In terms of the model, CS is thus the difference

between the utility in the healthy state and sick state (UG - Ul)

expressed in dollar terms by dividing by the marginal utility of

income. The expected consumer surplus associated with an

exogeneous change in the environment is the product of CS and the

change in the probability of the certainly well state caused by

the exogenous change:

(25) Expected CS - - CS dH/dE.

-~--~~------~~~~~~- dH/dE

(marginal utility

of income)

Comparing equations (24) and (25), it is clear that the

willingness to pay for changes in morbidity risks given by (24)

is almost the expected value of consumer surplus, adjusted for

changes in preventive expenditures. That is, equation (25) is

almost the first term of equation (24). The only ambiguity in

this comparison is that in expressing the change in utility in

dollar terms in equation (24), m**, the expected marginal utility -----

of income or money is used. Since m**<< a weighted average of

marginal utilities when healthy and when ill, if we assume the

marginal utilities are the same, the problem is resolved. In

general, it is not clear when these two marginal utilities will

be equal, since differences in consumption levels and health

status are involved. The relationship between the marginal

utilities of income across states also depends upon the

opportunities the individual has to adjust expenditures across

states. For instance, with actuarially fair insurance available

the individual will equate marginal utilities across states,

though this will not necessarily result in full insurance in the

sense that levels of utility are equal across states (see Cook

and Graham (1977)). In any case, if the marginal utilities of

income across states are close to each other, willingness to pay

for a change in health risks is approximately equal to the

expected value of consumer surplus, adjusted for changes in

preventive expenditures.

Consumer surplus is what previous studes which address the

pure morbidity case have measured in their valuation eXpreSSiOnS

since they have avoided the question of uncertainty. The

empirical work in Volumes 2 and 3 of this report also makes use

of consumer surplus, In particular, since it is difficult to

2-19
appropriately incorporate uncertainty into the contingent

valuation sxperiment, we measure consumer surpluses associated

with certain changes in morbidity. However, we are able to

approximate willingness to pay for risk changes by the expected

value of these consumer surpluses as explained above.

2.2.4 --e-e---- Concluding Remarks -------

The main purpose of this paper has been to compare

preference-based willingness to pay measures for human health

risk reduction with the main alternative approaches that are

currently in use. After providing discussions of the various

approaches, we construct an eclectic model from which we derive

preference-based (WTP) values for changes in health risks, which

are then compared with the alternative approaches. The model

incorporates partly endogenous health, uncertainty, mortality,

and morbidity. In fact pure mortality and pure morbidity, to

which previous studies have been confined, are considered as

special cases of the more general framework.

In the general case, we find that the preference based

willingness to pay measure for reductions in health risks

consists of two terms: a utility term, which reflects the cost of

ilness as well as other factors; and a term reflecting preventive

expenditures. It does not follow, however, that benefit measures

involving the cost of illness alone or preventive expenditures

alone are special cases of our general willingness to pay

measure. It is difficult or impossible to specify truly

reasonable assumptions under which the willingness to pay measure

collapses to a cost of illness measure or a preventive

expenditures measure. Our emphasis is somewhat different from

that of Harrington and Portney's in that their willingness to pay

measure for a reduction in morbidity is reduced to the cost of

illness measure under the assumptions that there are no

preventive expenditures, and health does not enter the utility

function directly.

Even the weaker result that the alternative benefit measures

are lower bounds to the willingness to pay measure does not

necessarily hold for our model. Without additiona. assumptions,

we cannot establish any general comparisons between the three

measures. We do find a set of plausible assumptions under which

some comparisons of the alternative benefit measures can be made.

First, it is necessary to assume that the environment and

preventive expenditures are substitutes in reducing health risks.

Second, the direct effects of a change in the environment on

health risks must outweigh the indirect effects, so HE >

(HX)(dX/dE). Third, the marginal utilities of consumption when

healthy and ill must be approximarely the same.

If the above assumptions are made, for the special cases of

pure mortality and pure morbidity. both the cost of illness and

the preventive expenditures will plausibly be lower bounds to

2-20
willingness to pay. The cost of illness approach understates the

true willingness to pay for several reasons. First, it neglects

the savings of preventive expenditures. Second, it does not

allow for individuals to enjoy health directly, i.e., it implies

in our formulation that health q does not enter the utility

function.' Third, from the "value of life" literature it seems

reasonable to conclude that the value of the utility of

consumption will exceed consumption expenditures, so the utility

lost due to expenditures lost resulting from cost of illness is

greater than the cost of illness. It should be stressed that

this result directly applies to the case of mortality, but would

seem to be plausible for morbidity as well.

Preventive expenditures also are likely to be a lower bound

to willingness to pay. The preventive expenditures are not a

complete measure of the benefits of health risk reduction to an

individual because the individual enjoys gains in expected

utility as well as the savings of expenditures. Our model does

not suggest any necessary relationship between the cost of

illness and preventive expenditures measures.

One additional result is that the benefit of an exogenous

change that improves both mortality and morbidity risks is not

the simple sum of the benefits of mortality risk reduction and

the benefits of morbidity risk reduction.

Our results'come from a model of individual maximizing

behavior which considers the private costs and benefits. Thus,

our results cannot be immediately generalized to social costs and

benefits. However, we are able to draw some conclusions. For

instance, we find in the case of pure mortality that private WTP

and private cost of illness are unrelated since the latter does

not matter to an individual if he dies. Only if we were to build

in bequests, or.to impose some constraint on the amount of debts

thatcouldbe leftatdeath,would costofillness enter the pure

mortality framework. But we know costs of illness are not

necessarily zero for society. So society's willingness to pay

for a reduction in mortality risk may exceed the willingness to

pay of the individual.

Empirical research on mortality risks has tended to confirm

the prediction that benefit measures based on cost of illness

will be lower bounds to benefit measures based on a willingness

to pay approach. Further empirical work is needed to

substantiate or refute the theoretical result that for morbiditv

the cost of illness will be smaller than the willingness to pay

Work.along these lines is reviewed in Section 2.6. In addition.

future empirical work could shed some light on the case where

both mortality and morbidity risks are present. Data which

contain contingent value estimates of willingness to pav.

estimates of direct and indirect costs of pollution related

illness, and also pollution related preventive expenditures could

be highly useful. These data would enable us to further

investigate the questions examined in this section.

2-21
2.2.5 --------- Footnotes

1. Cropper (1981) does obtain estimates of valuation of health

than-ges, she does so only under very specific assumptions.

Gerking and Stanley (1984) do so more generally, estimating

the value of a change in health as the cost of preventive

activity times an estimated ratio of marginal products of

inputs in the heatlh production function.

For a review of labor market studies see Smith (1979). For

a comprehensive survey of the literature on willingness to

pay and fatality risks see Blomquist (1982).

C consists of both expenditures on market goods and services

and on time, combined in fixed proportions. If the value of

time is constant at the market wage rate, then consumption

time expenditures are simply the product of the wage and the

amount of time spent in consumption activities. Preventive

expenditures (X) and costs of illness (Z) introduced below

are also assumed to consist of expenditures on time and

market goods combined in fixed proportions.

Typically, the cost of illness approach only includes

earnings lost or the value of time lost from work and

excludes the value of time lost from consumption activities.

Define Z* - Z - CL, where CL is the value of time lost from

consumption. In our comparisons of the cost of illness and

willingness to pay approaches in section 2.6 we will employ

the more widely used Z* definition of the cost of illness.

M is the sum of nonlabor income and potential earnings.

Assuming the wage rate is constant, potential earnings are

simply the product of the wage rate and the total time in

the period. The individual's problem can be expressed in

terms of the choice of X, rather than its goods and time

components, because of the fixed proportions assumption for

x, c, and Z.

6. Just as with Z expenditures, X expenditures provide no

utility directly by themselves.

7. Although the consumer's problem as expressed in equations

(6) and (7) is single period in nature, it can be

generalized to allow for multi-period planning as has been

done by Crooper (1977). In particular,' suppose the

probability density function, the probability of survival

function, and the utility function all vary over time.

Assuming an infinite planning horizon, the consumer's

problem can be restated as

MAX E(U) - the integral from T to infinity of the integral

2-22
from negative infinity to positive infinity of

8.

9.

10

WQ-X, -F(q,),q,;t)p(q,,t)h(q,,X,,E,,t)dqdt.

Note that for any given individual, Z is fixed once the

disease is contracted. In a more extended analysis, Z could

be made to depend on other variables such as the price of

medical care. Z could be made endogenous in the current

framework if it were specified as a function of preventive

expenditures.

Terms involving the partial derivative of U with respect to

q, disappear, since these terms are multiplied by dq, and dq

- 0 since q is set at either 0 or 1. Similarly, recalling

that the costs of illness Z are given by Z - f(q), dZ -

fl(s> dq = 0, since again dq = 0.

. Although we concentrate on morbidity risk we should note

another implication of our model for the cost of illness

approach. Typically CO1 studies separately estimate the

morbidity costs and the mortality costs and simply add them

together, e.g., see Mushkin (1979, p. 385). From our model

it is evident that willingness to pay for combined morbidity

and mortality risks is not the sum of the willingness to pay

for the special cases alone.

2.2.6 ---------- References

1.

2.

3.

4.

5.

6.

Acton, Jan Paul. Evaluating Public Programs to Save Lives:

The Case of Heart Attacks. Rand Corporation R-950-RC,

January 1973.

Becker, Gary S., Human Captial. Columbia University Press,

New York, 1964.

Bergstrom, Theodore C. "When is a Man's Life Worth More

than his Human Capital?" in Michael Jones-Lee, ed. The Value

of Life and Safety Amsterdam: North-Holland Publishing Co.,

1982.

Blomquist, Glenn. "The Value of Human Life: An Empirical

Perspective" Economic Inquiry 19, January 1981. pp. 157-164.

Blomquist, Glenn. "Estimating the Value of Life and Safety:

Recent Developments" in Michael Jones-Lee, ed., The Value of

Life and Safety. North-Holland Publishing Company,

Amsterdam, 1982.

Cook, P.J., and Graham, D.A. "The Demand for Insurance and

Protection: The Case of Irreplaceable Commodities."

Quarterly Journal of Economics, 1977, pp. 143-156.

2-23
7.

a.

9.

10.

11.

12.

13.

14.

15.

16.

17.

18.

19.

20.

21.

Cropper, M. L. "Measuring the Benefits from Reduced Morbidity". American Economic Review 71, May 1981. pp. 235-

240.

Gerking, Shelby and Stanley, Linda. "An Economic Analysis

of Air Pollution and Health: The Case of St. Louis." Mimeo.

University of Wyoming, May 1984.

Harrington, Winston and Portney, Paul R. "Valuing Health

Benefits of Environmental Improvements." Journal of Urban

Economics, forthcoming. Future, May, 1983.

Linnerooth, Joanne. "The Value of Human Life: A Review of

the Models". Economic Inquiry, 17, January 1979. pp. 52-74.

Loehman, E. T. et al. "Distributional Analysis of Regional

Benefits and Cost of Air Quality Control". Journal of Environmental Economics and Management, 6, September 1979. pp.

222-243.

Mushkin, Selma J. "Health as an Investment". Journal of

Political Economy, 70 Supplement, October 1962. pp. 129-157.

2-24

Mushkin, Selma J. Biomedical Research: Costs and Benefits.

Ballinger, Cambridge, Mass, 1979.

Needleman, Herbert and Grossman, Michael. "Health

Econometric Methods for Multimedia Pollutants." Workplan for

U.S. EPA Cooperative Agreement. (September 1983).

Smith, Robert S. "Compensating Wage Differentials and

Public Policy: A Review". Industrial and Labor Relations

Review 32, April 1979. pp. 339-352.

Smith, V. K. "Option Value: A Conceptual Overview,"

Southern Economic Journal, January 1983, pp. 654-68.

Smith, V.K. and Desvousges, W.H. "Averting Behavior: Does

it Exist?" Vanderbilt University Department of Economics

Working Paper, September 1985.

Viscusi, W. Kip. "The Lulling Effect: The Impact of ChildCooper, B. S.'and Rice, D. P. "The Economic Cost of Illness

Revisited". Social Security Bulletin 39, February 1976. 21-

36 PP.

Courant, Paul N. and Porter, Richard C. "Averting Expenditure and the Cost of Pollution". Journal of Environmental

Economics and Management, 8, December 1981. 321-329 pp.

Cropper, M. L. "Health, Investment in Health, and

Occupational Choice". Journal of Political Economy. 85,

December 1977. 1273-1294 pp.
Resistant Packaging on Aspirin and Analgesid Ingestions"

Americ,an Economic Review 74, May 1984. pp. 324-327.

22. Weisbrod, Burton A. "Costs and Benefits of Medical

Research: A Case Study of Poliomyelitis." Journal of

Political Economy-, 79, May/June 1971. pp. 527-544.

2-25
2.3. HEALTH ECONOMETRICS: AN ASSESSMENT

2.3.1. ------------ --- -------- Introduction and Overview

The purpose of this assessment is to determine what the

empirical evidence is with regard to effects of environmental

quality on human health. The focus is on cross-sectional studies

measuring the relationship between mortality rates and ambient

air quality measures. A primary concern is whether or not these

studies taken separately or as a whole can shed light on the

structure of demand for health, not just net responses to changes

in environmental characteristics on health measures. In this

regard a fundamental consideration is the role of avoidance

practices made by individuals in response to adverse health

conditions in specification, estimation, and inference from

econometric models. One reason for such concern is that impacts

on health of differences or changes in climatic conditions,

environmental quality, and other influences reflect the net

effect of these differences after avoidance has taken place in

response to what otherwise would have been adverse health

effects.

An illustration is presented in Figure 2-l where D is the

demand for health, H, and there are two sources of health

production: that from local amenity and environmental conditions

and that produced by individual behavior. An extreme case is

where withOenvirdnmental quality Q. health status on average

would be H in the absence of other behavioral responses (e.g.

defensive or avoidance

%

easures).

is thus inelastic at H .

The supply of health from Q0

At a similar extreme, suppose that

avoidance procedures are perfect substitutes for environmental

conditions and can be produced by an individual at constant cost

C. Then, as depicted in Figure 2-l health status would be H*

with defensive.or avoidance expenditures given by C ( H* - Ho).

Consumer surplus is given by the area inside oefcH'.

Now suppose that instead of Qo, environmental quality was

given by Ql which is less than Qo. The supply of health from

such conditions is now Hl which is less than Ho yet the

difference in health status c n be offset by additional avoidance

procedures at a cost of C (H8

- H1+ Consumer surplus in this

case is given by the ar a oefdH 8

which is less than that

previously by exactly C (H - H1).

In the above example the correlation between observed health

status (averaging H*) and environmental conditions would e zer

even.though benefits o

P

environmental improvements from QY

to Q 8

would be C x (Ho - H ).* On the other hand, in a stochastic

setting, regression of H (or m*ore realistically, variations of

actual health status around H ) on Q and expenditures (or the

level) of avoidance would result in biased estimates of causai

effects of pollutants on health quality because expenditures are

endogenous (aff ected by health status in their absence)

However, controlling for the feedback effect (e.g. through use of

instruments for health expenditures in the econometrir

2-26
.-

P’

C

0

FIGURE 2-l

ENDOGENEOUS HEALTH AND ENVIRONMENTAL QUALITY

:

\

II-e-*-

,--m---

H’

3

\3

H’ -_ H
specfication of health status) the pollutant effect on health is

essentially that which would occur without responding avoidance

supply effects. In th extr me, the effect of an environmental

qualit than e

FL

from Q & f

to Q would lead to a change in health

from H to H , appropriately holding health expenditures

constant.

More generally, differences in environmental conditions faced

will be reflected in differences in health status even after

avoidance procdures. The resulting calculation of benefits due to

improvement in environmental conditions needs to consider not

only cost savings (from a reduction in avoidance expenditures)

but also the value of the increased health that would result.

With this in mind the assessment considers the results from

five empirical studies of the effects of environmental pollutants

on mortality: Lave and Seskin (1977), Cracker et al (1979),

Chappie and Lave (1982), Mendelsohn and Orcutt (1979), and

Schwing and McDonald (1976). The purpose of this assessment is

not to duplicate the critiques of such analyses as presented in

the EPA's "Air Quality Criteria for Particulate Matter and Sulfur

Oxides." Rather it is to determine if estimated effects in these

studies are robust in light of the ways in which avoidance and

other measures are treated.

2.3.2 Study Summaries ---- -e-----eL.Lave and E. Seskin, Air Pollution and Human Health (Baltimore: --- ---_-_--- -_- ----- --__--

Johns Hopkins University Press), 1977.

This analysis compares mortality rates across 117 SMSAs in

1960 related to sulfates and particulates and 69 SMSAs in 1969

considering the effects of S02, N02, and NO3 also. Classical

least squares estimation techniques are applied with control for

effects of population density, percent of population over age 65,

percent of non-white population, and the percent of households

with income less than poverty level. Measure's of avoidance or

defensive activities are not explicitly included.

T. Cracker, W. Schulze, S. Ben-David, and A. Kreese, Methods

------ ---- Development v-s for Assessing Air Pollution Control Benefits, -------- --- _----_--- __----- e-----eVol. I. (Washington, D.C.: Environment Protection Agency)

EPA-600/5-79-OOla, 1979

This analysis compares mortality rates across 60 cities in

1970 and relates these to S02, TSP, and N02. Other exogenous

variables included in the study are measures of population that

was non-white, median age of population, living space density,

2-28
cold temperature, cigarette consumption, and three dietary

variables. Also included as an explanatory variable is a measure

of physicians per capita. An instrument for the latter was

employed in estimation of the mortality rate specification in

order to control for its potential endogenity with respect to

mortality rates.

M. Chappie and L. Lave, "The Health Effects of Air Pollution: A

Reanalyses," Journal ------- --of Urban Economics ----- ---------9 12 (1982),

pp.346-376.

Data for 104 SMSAs in 1974 are employed in this analysis.

Many variants of the previous Lave and Seskin model are examined

which add to the set of control variables many dietary variables,

as well as cigarette and alchohol consumption measures. In

addition the effect of physicians per capita are examined (taking

into account its potential endogeneity).

R. Mendessohm and G. Orcutt, "An Empirical Analysis of Air

Pollution Dose-Response Curves," Journal of Environmental ------- -- __---__-----_

~-------- Economics and Management --- ---- -----' 6 (1979), pp.85-106.

Mortality rates in 1970 for 404 county groups in the

contiguous U.S. are examined in this study. Pollutants

considered are sulfates, nitrates, S02, N02, CO, TSP, and Ozone.

Many control variables are employed in estimating age-sex-race

mortality rates. These include demographic characteristics for

the age- sex-race group, the county group, as well as climatic

condition and region specific characteristics. The estimation

techniques is weighted least squares.

R. Schwing and G. McDonald, "Measures of Association of some Air

Pollutants, Natural Ionizing Radiation and Cigarette

Smoking with Mortality rates", in The Science of the Total

----------- Environment 5, (1976), pp.139-169.--- ------- -- ---

Mortality rates in 46 SMSAs in 1960 are considered in this

study. The pollutants considered are S02, S04, N02, N03, and

hydrocarbons. In total 23 explanatory variable (climatic

conditions, pollutants, cigarette smoking. and natural ionizing

radiation) are employed to study total and disease specific

mortality rates. Three alternative estimation techniques are

applied to these data: ordinary least squares, ridge regression,

and sign constrained (with respect to pollutants) least squares.

2-29
2.3.3. Assessment ----------

2.3.3.1. Pollutant Effect Comparison

Table 2-2 shows the effects of a 1 microgram/meter3

increase- in various pollutants on the mortality rate

(deaths/lOO,OOO) implied by estimates from the five studies

outlined above, Comparison between studies of single pollutant

effects are made somewhat difficult by the differences in the

pollutants considered in any particular study. Correlation

between included and excluded pollutants thus hamper the validity

of inference based on effects of single pollutants. However,

except for the estimates from Cracker, et.al. effects of sulfur

oxides (SO2 and SO4 are positive and often substantial. The sign

of effects of TSP are not consistent across studies. Except for

the results in Mendelsohm and Orcutt, effects of Nitrogen oxides

appear positive.

2.3.3.2. Study Design and Estimation Approach

Besides differences in the sets of pollutants considered

in each study a variety of study design and estimation approach

differences are relevant for assessment of these studies. A

first consideration is that the Lave and Seskin and Mendelsohm

and Orcutt studies do not control for such factors as smoking

behavior or dietary characteristics of the population group

considered. Correlation between these measures and the pollutant

variables would serve to bias the estimated pollutant effects

making serious inference from these two studies suspect. The

Schwing and McDonald study suffers similarly from lack of

inclusion of many of these potentially important variables.

The Chappie and Lave and Cracker, et.al studies, however,

are very similar in that they include smoking and dietary

varibles as well as consider the role of physicians per capita in

affecting mortality rates. Yet, the implications for pollution

effects differ substantially. To understand the reason for these

differences more fully Table 2-3 presents the estimated

coefficients on the other explanatory variables (for

deaths/lOO,OOO) employed in these two studies. The demographic

variables employed differ except for the percent of the

population that is non-white. The coefficients on this variable

are similar, andifthe piece of a package of cigarettes averaged

slightly less than $1.00, the effect of population smoking

characteristics is similar between these two studies. Effects of

physicians per capita are also very similar between the two

studies.

Substantially larger effects of per day protein

consumption on mortality rates are found in the Cracker, et.al

study compared to those in Chappfe and Lave. Moreover, these

effects are more precisely estimated in the Cracker, et.al.

study. This suggests a potentially important influences of

2-30
correlation between dietary characteristics and the various

pollutants considered in each study. Other than this, the

reasons for the differences in pollution effects may be solely

due to the difference between the effects of sulfates and the

effect of S02.

2.3.3.3. Overall Design Consideration

Both the Cracker, et.al and Chappie and Lave studies

address the endogeneity of physicians per capita on mortality

rates within a cross-sectional setting. Such would be expected

as demand for physician services may be one result of avoidance

or averting behavior with respect to health problems. However,

this is only one factor that may be important. Avoidance

behavior may also be reflected in dietary, smoking, and alchohol

consumption which needs to be seriously treated in further

empirical work.

Avoidance or averting behavior in place, such as described

above, is but one avoidance alternative. A second may be

avoidance through changing residence location in response wo what

would otherwise be adverse health conditions in an area. One

implication of this would be that individuals may locationally

sort themselves in accordance with differences in environmental

quality among areas with those least affected living in

relatively low quality areas. If such is the case, estimates of

mortality rates differences between areas as a function of

pollution would likely understate the effect of changes in

overall pollution levels (especially those occuring in high

pollution areas to begin with). Secondly, individuals may change

location in response to what would otherwise be continued illhealth effects of pollution in one area. In such a case persons

adversely affected by pollution might end up dying (and

increasing the mortality rate) in low pollution areas. This

would also lead to an understatement of the true effect of

pollutants on mortality rates such as those based on the existing

cross-sectional analysis.

2-31
Table 2-2

Estimated Effects of 1 Microgram Per Cubic Meter Increases

in Selected Pollutants on the Mortality Rate

(Deaths/lOO,OOO)

Study

________________________________________------------------------------

I L

I I I IMendel- ISchwing

ave and I Lave and1 Chappin andI. Crockerlsohm andland

I a I b I c I d I

Pollutant1 Seskin I Seskin 1 and Lave I et.al. IOrcutt IMcDonald

_____-__---_______--____________________--------------------------- - _ - - _

so2 2.64

Sulfates 5.418 -1.02

(SC4)

TSP .619 -.022

NO2 .17

Nitrates .035

(NC3)

CO(miligram/per

cubic

meter)

03

___-____-_-__-_---------------

a

__

-.313 1.02 2.01

13.052 16.0 18.0

-.322 . 107 -.051

.082 -.082 -1.09

- .059 2.3

7.04

.58

_________-----____-----------------

From Lave and Seskin (1977), Regression 7.1-3

b

From Lave and Seskin (1977), Regression 7.8-10

C

From Chappie and Lave (1982), Regressions 6-9

d

Based on implied effects of'1 microgram per cubic meter change

using estimates in Table III and pollutant means in Table Al in

Mendelsohm and Orcutt (1979), 1970 age characteristics of the

population for creation of adult population mortality rate

effects.

e

Schwing and McDonald present estimated elasticities of'pollutant

effects on mortality rates. The estimates in Table 1 are based

on elasticities for the pollutant at its primary standard level

or, in the case of nitrates, at the average level presented in

Mendelsohm and Orcutt (1979). Results are based on the

constrained least squares elasticity estimates for total

mortality rates given in Schwing and McDonald (1976).

2-32
Table 2-3

Comparison of Cracker, et.al. and Chappie and Lave

Estimation Results

(deaths/lOO,OOO)

Explanatory Variable Crocker,et. Chappie

al. and Lave

Percent of population non-white 5.63 ( 4.56) 3.61 (3.47)

Median age of population

Percent of households with

6.59 (11.54)

31.77 ( 2.35)

greater than 15 persons/room

Number of days with

temperature below 0'

Packages of cigarettes/year/

capita

Per capita expenditures on

smoking items

Per capita expenditures on alchohl

In (population)

Median family income

In (population/sq.mile)

1.44 ( 2.91)

2.2 ( 2.81)

Grams/day/capita of protein

Gram/day/capitaof carbohydrates

70.1 ( 3.55)

-2.92 ( 1.36)

Grams/day/capita of saturated

fatty acids

14.6 ( 1.45)

Physicians/lO,OOO population -.53 ( 4.35)

2.512 (1.92)

1.255 (2.45)

-42.59 (1.98)

- . 036 (2.78)

41.98 (1.90)

8.42 (0.21)

.146 (0.20)

-2.222(0.12)

-.64 (3.79)

2-33
2.3.4. --------- -------- Concluding Comments

All of the empirical findings cited in the studies reviewed

in Section 2.3.2 suggest that pollutants can be related to

measures of human health. The data sets employed and the

statistical techniques employed differ, often substantially, in

these analyses. Yet, one is very much left with the feeling that

little is known regarding the relevance of the empirical findings

for estimation of benefits of health status improvements

associated with reductions in average pollutant levels, pollutant

mix, or changes in pollution dispersion over, for example, a oneyear period of time. One problem that arises is that multiple

pollutants are often correlated in ambient air characteristics,

which potentially reduces the information that can be gained

regarding one particulare pollutant's impact on health isolated

from those of other pollutants. Thi,s problem, however, is one

that methodological approaches using ambient air quality measures

can only hope to acknowledge and minimize using appropriate

methods of inference from empirical results. Three more serious

problems arise (some of which are addressed in the literature)

which are of concern for current purposes. These are outlined

below.

If the demand curve for health were known, in the extreme

setting considered in Figure 2-l comparison of pollutant effects

on mortality rates not holding constant and holding constant the

endogeneous avoidance behavior of individuals in response to

0 adverse health status should indicate the difference H - H .1

Clearly, the health econometric studies examined do not yield

reasonsable means of doing so. This information

1" q8

ite useful

in that it would allow for estimation of area H abH if D were

known. Indeed, the inf

estimate of area H'dcH 8

rmation that is missing but needed is an

the amount of avoidance costs incurred

to offset the decline in environmental quality. An important

piece of information could thus be gained by regressing health

avoidance costs (or at least those measurable) on environmental

quality, giving an indication of this area. In more complicated

avoidance cost situations where C is,

function of (H - Hi)

for example, an increasing

or shifted as a function of Hi, this type

of avoidance cost information would still be needed in order to

determine true benefits of pollution reductions. Regardless,

structural estimates of not just the human health specifications

are needed in order to get an appropriate measurement of the

benefit function for reduced pollution. A need in this regard

is thereby to investigate the opportunities available in

estimating the full set of simultaneous relationships involved.

Two potentially important areas in which to extend even further

empirical analysis in this regard are discussed below.

2.3.4.1. Location Change Complications

In one very relevant sense, the level of pollution faced by

an individual are subject to choice. Of relevance for current

2-34
purposes is whether or not individuals respond to ill effects of

pollutants on 'human health (or health production) by migrating to

areas with better environmental quality if they do and if past

period pollutant experiences affect future health conditions, in

an extreme case a negative partial correlation between current

health status and currently faced environmental conditions is not

only expected but is also a measure of the severity of the

pollutant's impacts on health preservation.

Endogeneity of location choice and thus environmental quality

means that feedback between current health status and current

pollutant levels needs to be explicitly incorporated into health

econometric studies. It is not sufficient to simply include a

net migration variable into mortality or morbidity rate

specifications. In any case, only health induced migration would

be of concern regarding correlation of the migration measure and

the error term in the health specification.

More generally, effects of exposure to pollutants may be

lagged or cumulative. It is important to deal more adequately

with exposures faced by individuals over longer periods of time

(controlling for location changes) than has heretofore been

attempted. This would be especially relevant in attempting to

measure differences in impacts on health of fluctuation-s in

environmental conditions and long-term differences in exposure.

2.3.4.2. Population Heterogeneity

Almost all of the health econometric studies acknowledge

likely differences in effects of pollutants on individuals. In

fact, even in its most random form where pollutants equally

affect everyone's probability of a certain health effect, some

individuals are spared the impact which others are not.

Controlling for differences in measured demographic

characteristics of the population allows for alleviation of some

of the problems involved with heterogeneity in susceptibility.

still, the problem of heterogeneity in unmeasured characteristics

poses a measurement problem.

One way of starting to deal with this is to consider

measurement of changes in health status of a panel sample of

individuals. Effects of pollutants may then be related to the

actual health status of individuals in prior years to help

address the question of susceptibility. In conjunction with

this,the role of migration in response to deterioating health and

its impact on location of, for example, death, relative to

pollution levels could be more fully examined.

2-35
2.4. COST OF ILLNESS APPROACH

2.4.1. ------------ Introduction

The cost of illness (COI) approach focuses on those aspects

of the value of health that may be fairly directly measured:

medical expenditures and foregone earnings due to illness. The

basic idea of many CO1 studies is simply to convey in some

quantifiable way the impact of illness on the U.S. economy.

These studies range from comprehensive studies of the cost of all

illness in the U.S. for a given year to studies dealing with a

specific disease or group of diseases. The CO1 approach is also

frequently used as a way to measure the benefits of a program or

any change that improves health, for use in benefit cost

analysis. The reasoning is clear: if illness imposes the costs

of medical expenditures and foregone earnings, a reduction in

illness yields benefits equal to the costs saved.

Researchers have used the CO1 approach as away to value the

health benefits resulting from a change in air pollution levels.

For instance, Lave and Seskin (1976) combine their data with the

Cooper and Rice (1976) estimates of the total cost of illness in

the U.S. to find a value for a hypothetical change in pollution

levels. This section is mainly concerned with using cost of

illness estimates as a source for empirical estimates of the

value of health effects linked to air pollution, though a fairly

general appraisal of 'the approach is also undertaken.

The appeal of the CO1 approach is its seemingly straightforward estimation of clear, well-defined and observable

quantities. There is a large amount of information collected on

medical expenditures and foregone earnings due to illness, and

the sources are often good quality, national data bases. Since

the COI approach does not place a value on the more intangible

aspects of health, notably pain and suffering, the approach is

intuivively seen as estimating a lower bound to the true value of

health. As alternative willingness to pay estimates for the

value of reductions in mortality risks have become available, the

CO1 approach is less frequently used to value these risks.

However, alternative estimates for the value of morbidity are

just becoming available, and the range of morbidity effects

valued is still quite limited. The quality of the alternatives

to CO1 values of morbidity is also questioned. For these

reasons, the CO1 approach remains an attractive source of

estimates for the values of a wide range of morbidity effects.

In this section the CO1 approach is mainly applied to morbidity;

mortality is discussed only,incidentally.

A drawback to the CO1 approach as usually implemented is

that it produces estimates of the total medical expenditures and

foregone earnings due to illness in the U.S. However, the data

linking air pollution to morbidity are on an individual basis.

For example, air pollution,can be related to the days an average

individual spends ill inayear. There are twoways to conduct a

benefit cost analysis of air pollution using aggregate cost of

2-36
illness estimates and individual links between air pollution and

health. First, the data linking individual health effects and

air pollution could be used to extrapolate the total amount of

illness caused by air pollution in the U.S. This aggregate

quantity of illness could then be valued using an existing CO1

estimate. (This is the procedure used by Lave and Seskin

(1976)). An alternative route is to derive from the existing

aggregate CO1 studies estimates of an individual's cost of

illness. These individual estimates could then be directly

combined with the data linking individual health effects and

changes in air pollution. If the objective.is to estimate the

aggregate cost of illness due to air pollution, it would be

necessary to make assumptions about the distribution of

individuals and link them to the micro relationships. As V.K.

Smith points out, this "bottom up" approach is probably

intuitively more appealing to many economists. To implement this

approach, estimates of individual cost of illness are required.

Estimates of an individual's cost of illness are desirable

for several other reasons, The theoretical models that suggest

cost of illness measures may be a lower bound to the conceptually

correct measure of the value of health apply to individual and

not aggregate values. In addition, alternative approaches to

valuing morbidity produce estimates of an individual's value of

health. At present, direct comparisons of these individual

willingness to pay estimates and the aggregate cost of illness

estimates can not be made.

The goal of this section is to express existing CO1 approach

estimates on a basis that relates to what an individual would be

willing to pay for a change in health. Section 2.4.5 puts a

number of studies' estimates on a per case and a per day basis.

This procedure is not necessarily ideal, since a "top down"

approach is still used in estimating the individual's costs of

illness: the process begins with the aggregate costs and uses

these to imply the individual costs. This approach was

originally proposed as a means to avoid serious double-counting

of costs (Rice (1966)). Since the relative performances of the

"top down" versus "bottom up" approaches is an open issue, some

estimates based on individual observations of costs are also

presented. Additional information on individual costs was

obtained in the survey described in Volume 3, and reported in

section 2.6 below.

Preceding the presentation of the empirical results obtained

from existing CO1 studies (section 2.4.5), a general assessment

of the usefulness of the CO1 approach is undertaken. Section

2.4.2 discusses the relationship between the CO1 approach and the

conceptually correct willingness to pay approach. Section 2.4.3

extends this discussion to consider differences between

individual and societal willingness to pay for health

improvements. While this distinction is made in the context of

the cost of illness approach, the difference between individual

and societal values is important for all attempts to value the

benefits of health improvements. Following these discussions of

2-37
conceptual issues, section 2.4.4 is a critical evaluation of the

standard methodology of CO1 studies.

2.4.2. ------ Linking she Cost of Illness ___- -- _------ APEroach - ----- to Willingness to Pay -- ---__- ---_ -- __

Researchers using the cost of illness approach have noted a

number of shortcomings of the approach for benefit cost analysis.

For instance, the CO1 approach makes no attempt to measure the

benefits of reduced pain and suffering associated with health

improvements, as noted above, but concentrates on more easily

measured aspects of the cost of illness. Thus benefit cost

analysis using this approach to valuing benefits may indicate

that fewer resources should flow into cancer research, for

example, than the public might desire because of the relatively

high costs in terms of pain and suffering of cancer. (This

example is suggested by Cooper and Rice (1976).) Another general

problem is that little value is placed on activities outside of

the marketplace, since the approach considers only foregone

earnings. While recent studies have attempted to make

adjustments to allow for value to be placed on the time of those

individuals keeping house, leisure time in general, and thus much

of the time of retired individuals in particular, is implicitly

not valued at all. Programs that reduce the illnesses of the

older members of society might be very difficult to justify using

benefit cost analysis, if the benefits are measured using the CO1

approach. Programs aimed at improving the health of another

segment of the population, the very young, may also show few

benefits from the CO1 approach. Since future earnings are

discounted, at a fairly typical discount rate of 10 percent

earnings that start 20 years in the future have a relatively

small present value. This list of troubling implications of

benefit cost analysis using a CO1 approach could be extended,

which suggests that the benefits of improved health that most

people actually perceive may not be well estimated by the CO1

measures.

The fundamental problem with the CO1 approach is that though

the quantities the studies estimate are clearly important aspects

of the benefits of improved health, the methodology originally

was not founded on any rigorous theoretical basis. This point is

forcefully made by Mishan (1971), who particularly emphasizes

changes in mortality risks -- the "value of life." He points out

that benefit cost analysis is based on the proposition that an

action is judged by whether it represents a potential Pareto

improvement, that is, whether the gains resulting from the action

can be distributed so that at least one person is made better

off, and no one is made worse off. To use this criterion, it is

necessary to look at the sum of what each member of society is

willing to pay or accept for the change. The problem with the

CO1 approach to measuring the "value of life" is that there is no

a priori reason to believe that an individual's future earnings

2-38
will be related to his willingness to pay for a reduction in

mortality risks. Studies based on individual preferences for

such reductions are now usually said to follow the willingness to

pay (WTP) approach.

In response to Mishan's and others' criticisms, a good deal

of attention has focused on theoretically relating discounted

future earnings to what an individual would be willing to pay for

a small reduction in the risk of death. Two conclusions emerge

from the theoretical work. First, there is no necessary

relationship between future earnings and willingness to pay (see

Linnerooth, (1981), or Rosen (1981)). Second, however, under

certain restrictive conditions future earnings may be a lower

bound to the willingness to pay measures. (Usher (1971), Conley

(1976)).

Comparisons of empirical work fo'llowing the CO1 approach to

work following the WTP approach support both of these

theorectical conclusions. Blomquist (1981) in his review of

existing empirical studies concludes that while "there is no

close association of value of life with future earnings....there

is a strong indication that the value of life is greater than

future earnings." Thus, there is some theoretical and empirical

justification for one element the CO1 studies estimate: the

foregone earnings due to premature mortality. It must be

stressed that the justification is weak. At best, these foregone

earnings are only a lower bound to the conceptually correct WTP

measure, so there is no reason to believe the measures will be

close to each other.

Much less attention has been paid to justifying the

remaining elements of the CO1 estimates: medical expenditures,

and foregone earnings due to morbidity. Ideally, the cases of

mortality and morbidity should be considered together, to allow

for possible interactions (see section 2.2). The expressions

derived from such a model are fairly complicated, but it is

possible to show that for the case of pure morbidity, under

certain plausible assumptions, the cost of illness will be a

lower bound to the WTP measure.

In short, theoretical models suggest that WTP reflects four

components: 1) lost wages: 2) additional medical expenses;

3) the dollar-value of the disutility of additional illness; and

4) the change in defensive expenditures. This can be seen in the

willingness to pay expression derived in section 2.2 for the case

of pure morbidity:

U(M-X,0) - U(M-X-2,1)

(24) - dM/dE m - ___-___---__-_-___---- dH/dE - dX/dE

P-P-1 m**

0 1

The first three components of willingness to pay for a reduction

in the risks of.morbidity are reflected in the expected

difference in utility when healthy and when ill valued in dollars

2-39
(the first term on the right hand side). The difference in

utility when healthy and when ill depends upon both the cost of

illness term Z and the absence or presence of the condition(0 or

1 as the second argument in the utility function U). cost of

illness Z is defined to include the value of time lost due to

illness, reflecting both foregone earnings and the value of

leisure time, and all the out-of-pocket medical expenditures

necessitated by illness. Willingness to pay also depends upon

the change in defensive or preventive expenditures brought about

by the reduction in risks (the second term dX/dE). (For a more

complete discussion and definition of all variables, see section

2.2.)

In contrast, the CO1 measure only includes the lost wages

(often called the indirect costs) and the additional medical

expenses (the so-called direct costs). The amount an individual

would be willing to pay is largerthanthe CO1 measure as long as

the omitted quantities of the WTP measure are positive. People

will always pay a positive amount to avoid the disutility of

illness. Whi'le Courant and Porter (1981) emphasize that

defensive expenditures may either increase or decrease in

response to an decrease in pollution, the normal cases is that a

decrease in pollution saves defensive expenditures, and so these

savings are a positive part of the WTP measure. In this case., the

CO1 measure of the benefits of a reduction in morbidity is a

lower bound to the theoretically correct WTP measure. However,

as shown in section 2.2, there are no plausible conditions under

which the cost of illness measure is a special case of WTP.

The theoretical model does not suggest how close the CO1

measure will be to the WTP measure. Rigorous comparisons of

these measures are undertaken in section 2.5. Some idea of the

difference between the measures can be gained by considering the

aspects of benefits the CO1 measure neglects: the disutility of

illness and the savings in defensive or preventive expenditures.

While illness may decrease utility in many, possibly subtle,

ways, probably the most important effect is the pain and

suffering caused by illness. Mushkin (1979) attempts to estimate

a dollar value on the total pain and suffering due to illness,

basing her estimates partly on market revealed preferences, such

as expenditures on painkillers, expenditures for medical care due

to a pain symptom, and so forth, and partly on value's given to

pain and suffering in court awards. Her estimates for 1975 range

from $25.8 billion to $228.6 billion, compared to a traditional

CO1 measure of $322.6 billion. That is, allowing for pain and

suffering could represent an increase of 8 to 70 percent in the

CO1 measures of the benefits of improved health.

Unfortunately, no comprehensive estimates could be found of

the total defensive expenditures due to illness. The household

production models of health (Grossman (1972)) do suggest that a

wide variety of activities and goods may play a role in the

production of health, so the change in defensive expenditures is

possibly large. As reported below (section 2.6), as part of the

contingent valuation experiment information was collected on

2-40
individuals' purchase of items for health reasons (air

conditioner and humidifiers) and it was found that non-trivial

proportions of the sample had made such purchases. In relation

to pollution induced health risks, Smith and Desvousges (1985)

find that households do make adjustments to reduce the risks of

exposure to hazardous wastes through drinking water, but are not

able to measure the value of these actions, This evidence

indicates that the change in preventive expenditures may be a

significant determinant of how much individuals are willing to

pay for a reduction in health risks. Thus, consideration of the

elements of the WTP measure the CO1 measure neglects suggests a

tentative conclusion that the CO1 measure seriously

underestimates true willingness to pay for an improvement in

morbidity.

The general conclusion of the work comparing the CO1

approach to valuing improvements in mortality and morbidity to

the WTP approach is that the CO1 benefit measure is a lower bound

to the WTP benefit measure, but not necessarily a very good

approximation of it. Almost all three elements of the CO1

measure can be related to what an individual would be willing to

pay for an improvement in health: medical expenditures due to

morbidity, foregone earnings due to morbidity, and foregone

earnings due to premature mortality are all elements of a

theoretically derived measure. The omission is that medical

expenditures due to fatal illnesses have not been related to the

willingness to pay f&r a reduction in the probability of such an

illness. In a nonrigorous argument, this seems plausible, since

an individual will not value these expenditures if he is not

alive to pay them. The possibility of a bequest motive, though,

implies that an individual does derive utility from his heirs'

consumption possibilities, and so if the medical expenditures due

to a fatal illness reduce the amount of the bequest, the

individual may be.willing to pay to avoid these costs. Other

possible justifications for including the medical expenditures

due to fatal illnesses arise from the consideration of societal,

rather than individual, willingness to pay. The question is

similar to the problem of whether "premature" funeral costs are

of interest in valuing reductions in mortality risk.

A secondary problem stemming from the medical expenditures

due to fatal illnesses is that in many studies where medical

expenditures are used in benefit cost analysis, all medical

expenditures are implicitly asumed to be due to morbidity. The

impact of this incorrect assumption is difficult to assess.

Clearly, most illness does not result in death; simple

calculations show, for instance that less than 1 percent of the

total cases of pneumonia in a year result in death (Vital and ----- ---

------ Health Statistics ----------) various issues). On the other hand, the

treatment of a fatal case is certainly likely to be more

expensive than the treatment of a nonfatal case (unless the fatal

illness is very short), so fatal illnesses may still account for

a significant proportion o,f medical expenditures. In this case,

using total medical expenditures as an estmiate of the benefits

of reducing morbidity alone would overstate these benefits.

2-41
2.4.3. _--------- Individual Versus Societal Willingness to Pay ------ ---_---- ------ ---- -- --

The analysis so far has focused on CO1 measures as

approximations of an individual's willingness to pay for

improvements in his own health risks, but society might also have

an interest in the individual's health. The problem of which

viewpoint to use, individual or societal, has received attention

in the cost of illness literature. Some early researchers, for

instance, reported foregone earnings net of consumption, on the

grounds that it is the net earnings that society lost due to an

individual's morbidity and mortality (see, for instance, Weisbrod

(1961, 1971)). The common practice currently is to estimate

total earnings fore-gone, which is justified by the relation

between total earnings and individual willingness to pay, as

discussed above. In other ways, however, the CO1 studies have

continued to try to consider the societal viewpoint. This can be

seen in further details of the calculation of foregone earnings.

Earnings are estimated gross of taxes, reflecting the value to

society of the taxes that would be paid in the absence of

illness, though what most likely matters to the individual's

utility is his net of tax income. Non-labor income is not

included in CO1 measures of foregone earnings, on the other hand,

because though the individual does consume it, it would not be

lost to society if the individual suffers morbidity or mortality.

In general, the present status of the CO1 approach might be

described as an uneasy compromise between the individual and the

societal viewpoints.

Some attempts have been made to reconcile the differences

between the individual and the societal viewpoints in measuring

the benefits of improved health, though these seem to have

concentrated on the case of mortality risks. Landefeld and

Seskin (1982) develop an adjusted process to calculate foregone

earnings, allowing for the individual's perspective in that

earnings are computed net of tax, non-labor income is included,

an individual discount rate is used (as opposed to the social

discount rate), and a risk-aversion factor is applied. These

adjusted foregone earnings estimates are closer theoretically and

empirically to the measures estimating individual willingness to

pay for a reduction in mortality risks directly. Working in the

opposite direction, Bailey (1980) attempts to adjust individual

willingness to pay measures to allow for benefits to other

persons from the reduction in the risk of an individual's death,

and in some ways his methodology is closer to the methodology of

the CO1 approach. He modifies a WTP measure to allow for future

direct taxes on labor and future indirect business taxes on labor

that would be lost due to an individual's premature mortality,

and to allow for direct costs associated with a fatality not

borne by the family of the victim.

From the perspective of benefit cost analysis, however, many

of the deeper conceptual problems in measuring the differences

between individual and societal perceptions of the benefits of

2-42
health improvement are not resolved, and in fact seem to have

received very little attention in this context. A number of

problems involve the role of medical expenditures in benefit

estimation when considered from an individual versus a societal

point of view. In addition, the existence of paid sick leave

allows the possibility of a difference between individual and

societal valuations of foregone earnings due to morbidity.

Finally, pure altruism plays a part when considering how society

in general values an individual's health risks. Each of these

problem areas is discussed below, but not at the length or with

the rigorous analysis they deserve. It should also be noted that

in keeping with the general purpose of this section, only the

case of morbidity is considered.

The role of medical expenditures in benefit estimation would

be much clearer if the market for medical care were the textbook

ideal of a competitive market in the absence of distortions. In

this situation, Harberger's basic postulates for benefit cost

analysis would apply; in particular it could be assumed that:

"(a) the competitive demand price for a given unit measures the

value of that unit to the demanders;" and "(b) the competitive

supply price for a given unit measures the value of that unit to

the supplier" (Harberger (1974)). For the last unit bought and

sold, the price observed in the market will be the demand price

and the supply price, in this ideal setting. So for a marginal

change in the quantity of medical care, the market price

represents the value both demanders and suppliers place on that

unit, and the change in medical expenditures (price times

quantity) is the value of that change appropriate for use in

benefit cost analysis, from either an individual or the societal

point of view. However, the medical care sector is far from the

ideal non-distorted competitive market: there are reasons to

believe the market price will not be a good approximation of the

value of the last unit to demanders; and there are also reasons

to believe that the market price of medical care may diverge from

the value of the last unit to the supplier, i.e., the value of

the next best alternative use of the resources involved in the

production of medical care.

The most obvious reason that the market price of medical

care may not reflect the value demanders place on the last unit

consumed is the existence of third party payments. Recent

figures show that over two thirds of all personal health care

expenses are paid for by third parties, including private health

insurers, governments, private charities, and industry (Gibson,

et al., (1983)). Third party payments drive a wedge between the

demand price (the price the demander or consumer sees) and the

market price. With third party payments, the value the consumer

of medical care places on the last unit may be fairly low,

depending upon the portion of the cost he pays. The benefits of

an improvement in health to the individual demander will relate

only to the possibly small reductions in medical expenses he

actually sees in the presence of third party payments. Following

the CO1 approach to measuring benefits, however, all medical

expenditures are counted, not just those expenses the individual

2-43
incurs. This means that a CO1 measure may not be comparable to a

measure based on individual willingness to pay, unless the

savings to a third party payer resulting from an individual's

reduced health risks are somehow passed on to the individual, as

could be the case if healthier individuals receive reductions in

their health .insurance premiums. Even if the individual does not

perceive the total savings in medical expenditures, though, as a

first approximation the CO1 benefit measure may represent the

societal viewpoint, since the third pary payer, or whoever does

realize the savings in costs (such as other purchasers of health

insurance), do benefit. The sum of the savings to the individual

directly involved and the savings to these others will equal the

total medical expenditures estimated in the CO1 approach. This

first approximation misses the more subtle effects of the wedge

third party payments drive between the demand price and the

market price involving optimizing b.ehavior on the part of the

demanders. These effects can not be successfully evaluated

without developing a more rigorous analytical model of the demand

and supply of medical care.

Other ways in which the medical care sector deviates from

the ideal competitive market are the importance of non-profit

organizations in providing hospital services, and the complicated

role the physician plays as both a supplier of medical care, and

one who has a possible influence on the quantity of medical care

demanded by the patient. In the absence of the profit motive,

hospital administrators may pursue other goals, such as a

reputation for high quality medical care. If this is the case,

hospitals may provide a higher quality, and higher priced, good

than the demanders would prefer. The role of the physician could

similarly result in the patient consuming more medical care than

he would judge optimal if he had full information. So both of

these aspects of the medical care sector may drive further wedges

between the value of the medical care to the demander, and the

market price. Again, a more rigorous analysis is required to

make any conclusions about the importance of these possible

effects.

A fairly standard analysis can be used in evaluating the

importance of one final aspect of the medical care sector: the

possible lack of competition in the supply of physician services.

Various features of the market for physician services suggest

that physicians may have a substantial degree of market power:

the effective restriction of entry through the American Medical

Association's control of the supply of medical students; the

increases over time in the incomes of physicians relative to the

incomes of what seem to be comparable professionals; and so

forth. In this situation, the market price of medical care will

be above the value of the next best alternative use of the

resources used in the production of medical care. The difference

is an economic rent, or monopoly profit, that is gained by the

physicians. Now, a reduction in medical expenditures due to an

improvement in health will release resources (physicians) that go

to a use valued at less than the market price of medical care.

The result is a reduction of the rents received by physicians.

2-44
Thus, the decrease in medical expenditures is partly a transfer

from physicians to patients. That this tranfer is not a welfare

gain for society as whole using the criterion of a potential

Pareto improvement described earlier is clear: the gains by the

demanders of health care are offset by the losses suffered by

physicians. Distributional effects could be relevant, however.

To summarize the preceding discussion of the medical care

sector, aspects of the demand and supply of medical care suggest

that there may be differences in how the individual and how

society value reductions in medical expenditures. Many of the

effects are unclear, in the absence of a rigorous analytical

model. The clearest result is that if physicians do have some

degree of market power, part of the reduction in medical

expenditures will represent a transfer of income, and not a gain

to society as a whole.

Another case for which the value of a health improvement may

be different depending upon the individual or societal viewpoint

is the analysis of lost time due to illness if the individual

receives paid sick leave. This case has been analyzed by

Harrington and Portney (1983) as a variant of their general

model. As they note, as a first approximation it might seem that

lost time due to illness, though no longer a cost to the

individual, still represents a cost to society as a whole: with

paid sick leave the employers would perceive the costs associated

with a worker's illness. Then if the CO1 approach estimates

foregone earnings without allowing for paid sick leave, the CO1

benefit measure will diverge from the individual WTP measure, but

it will still approximate society's willingness to pay for a

health improvement. However, the presence of paid sick leave

changes the individual's optimizing behavior, in particular it

changes his optimal choice of defensive expenditures, and his

ability to trade off leisure time and time spent working. As a

result, the formal analysis of Harrington and Portney concludes

that with paid sick leave, the CO1 measure is no longer

necessarily a lower bound to the WTP measure. (This is the type

of subtle effect that must be considered in a complete analysis

of the issues raised earlier involving third party payments and

other distortions in the medical care sector.)

The final difference between individual and societal

willingness to pay for a reduction in morbidity that will be

considered is the possibility of pure altruism. In this case,

other members of society are willing to pay for an improvement in

an individual's health, and these amounts should be added to the

individual WTP measure. Altruistic motives are clearly

important, and in particular family members may be willing to pay

a great deal to improve the morbidity risks of other members of

the family. This explanation may relate to the values placed on

improving the morbidity risks to children, infant mortality

risks, and even pre-natal care,

2-45
The analysis of sections 2.4.2 and 2.4.3 suggests there may

be conceptual problems with the cost of illness approach, because

costs of illness may not be closely related to either individual

or societal willingness to pay for improved health. Despite

these objections, the cost of illness approach remains widely

accepted as a standard approach to valuing health. Often, this

acceptance is justified by the argument that theoretical

considerations aside, the CO1 benefit measures are easily and

reliably estimated in practice. This section addresses directly

the issue of the quality of cost of illness estimates, as usually

implemented.

The most recent attempt to make a comprehensive estimate of

the total costs of illness in the U.S. is the study by Paringer

and Berk (1977), for the Fiscal Year 1975. In addition, a

comprehensive estimate of personal health expenditures by disease

category has been completed by Hodgson and Kopstein (1984), for

the year 1980. The health care expenditure estimates of the

Hodgson and Kopstein study, combined with the estimates of

foregone earnings due to morbidity from the Paringer and Berk

study will be an important source of estimates for possible use

in benefit cost analysis. (see section 2.2.5, below). For this

reason, a review of the quality of these estimates is in order.

In addition, since these studies use a standard methodology,

their weaknesse

9

and'strengths will be shared by a majority of

the CO1 studies.

First, the quality of the estimates of health or medical

expenditures due to different diseases is reviewed. Following

this is a discussion of the estimates of foregone earnings due to

morbidity.

2.4.4.1. Estimates of Health Expenditures

0

To evaluate the quality of the CO1 estimates of health

expenditures by disease category, it is necessary to review the

methodology behind these estimates. The comprehensive studies

such as that of Paringer and Berk follow fairly closely the

methodology developed by Rice (1966). The starting point is a

measure of total health sector expenditures for a given year, E.

Then, expenditures are broken down by type of service purchased,

i.e. hospital care, physicians' services, etc.

in the ith

Letting Ei

represent expenditures service category, where

i-l,...,n, note that the sum of the Ei equals E. Estimates of

the E- available from the Health Care Financing

Adminiist:iFion (HCFA). (Before 1978 these estimates were

prepared by the Social Security Administration.) Next, the CO1

studies must estimate a series of weights, v~i, which represents

the percentage of expenditures in service category i accounted

for by disease j. A variety of sources is used to estimate the

different V.Ji. Finally, the expenditures necessitated by

disease j, EJ, can be computed as the sum of the expenditures

2-46
necessitated by disease j.in each of the n service categories.

The principle advantage of th.is methodology is that double

counting is avoided, since total expenditures are simply

distributed to the different disease categories.

For the purpose of benefit estimation, it is the

expenditures necessitated by a particular disease, Ej that are

of interest. Since in general the weights for the j th disease

will vary across the service categories, proper estimation of the

expenditures by service category and the weights is required. In ---

a recent review, Scitovsky (1982) finds problems in both parts of

the estimation process.

A serious problem exists in the HCFA definitions of the

service categories. The major categories of expenditures are:

1) hospital care, 2) physicians' and other health professionals'

services, 3) drugs and medical sundries, 4) nursing home care,

and 5) nonpersonal health care services, such as the prepayment

and administrative expenses of insurance, medical construction,

etc. Currently, the HCFA estimates of hospital expenditures

include salaries and other payments to health professionals on

hospital staffs, and the expense of drugs dispensed in hospitals.

So expenditures for hospital care are overstated, while

expenditures for health care professionals' services and for

drugs and medical sundries are understated. A similar problem

arises in estimating expenditures on nursing home care: these

estimates include the costs of drugs dispensed in nursing homes.

Redefining the service categories to correct for these problems,

Scitovsky presents conservative estimates of the errors in the

1978 HCFA estimates of health care expenditures by service

category. She finds that expenditures for hospital services were

overstated by 12.4 percent, and expenditures for nursing home

care were overstated by 3.5 percent. Expenditures for dentists'

services were understated by 1.8 percent, expenditures for

physicians' services were understated by 9 percent, and

expenditures for drugs and medical sundries were understated by

50 percent.

Scitovsky mentions other problems with the estimation of the

size of the service categories, but could not estimate the

magnitude of these problems. For instance, expenditures for

physicians' services may be further understated, since the

estimates are based on tax returns of physicians. Particularly

for physicians in private practice, both the opportunity and a

strong incentive to underreport income are present, so this is a

source of potentially serious error. Another problem is that

Scitovsky feels the quality of the data used to estimate

expenditures for nursing home care is poor. Hodgson and Meiners

(1982) point out a third problem: double-counting of costs may

be included in the estimates of expenditures for non-personal

health care services. As an example, the costs of construction

of new hospital facilities should be reflected in the prices

charged for hospital care, so counting these costs in both

categories is incorrect. This type of error is necessarily

small, however, since expenditures for nonpersonal health care

2-47
make up only a small percentage of total expenditures.

One category of expenditures is typically omitted:

expenditures in the nonhealth sector necessitated by illness,

such as transportation to and from medical providers, special

diets, and so forth. These expenditures are conceptually medical

expenses, not preventive expenditures, because they follow the

incurrence of a disease and do not prevent or lessen the

probability of illness. It would be quite difficult to make a

comprehensive estimate of these expenditures, since

different types

so many

of goods and services could be involved. In an

admittedly incomplete attempt to estimate some of these costs,

Mushkin (1979, pp. 384-5) has estimated that including the

nonhealth sector costs of illness would increase total

expenditure estimates by 10 to 16 percent.

The problems encountered in th.e estimation of the

expenditures by service categories (the Ei) are probably not as

serious as the problems of estimating the weights used to assign

expenditures to specific illnesses. Based on the criticisms of

Scitovsky (1982) and others, the most important problems seem to

be those concerning the allocation of the two largest expenditure

categories: hospital services and physicians' services.

Most hospital expenditures are for community hospitals.

These expenditures are distributed by days of care for each

diagnostic group, as estimated from the Hospital Discharge

Survey, weighted by expense per patient day. However, several

studies by the Institute of Medicine (1977) show that the

hospital diagnosis data are imprecise, so the estimate of the

days of care by diagnostic group will be imprecise. Another

problem is that the inpatient/outpatient mix is not accounted for

in the allocation of expenditures. All expenditures are

allocated on the basis of days of inpatient care, but these

expenditures include a substantial amount of outpatient care. To

the extent that the case mix of outpatient care differs from that

of inpatient care, costs will be misallocated:

where 1 - hospital expenditures,

the weights vl,

will be estimated incorrectly.

Computing the weights for allocating expenditures for

physicians' services is also problematic. These weights are

based on the distribution of physician visits by diagnosis, based

on the National Disease and Therapeutic Index, a continuing

survey of private medical practice in the U.S. The quality of

these diagnostic data is questionable. Scitovsky feels that

these data are even less reliable than the similar data for

hospitals, while the Institute of Medicine (1981, p. 89)

describes the data as more reliable, but less precise due to the

smaller sample used in the survey.

A larger problem is that the studies implicitly assume

equal charges for all types of physician services. Since in fact

a routine office visit is much less expensive than a visit

requiring more extensive services or surgery, the weights will be

incorrectly computed, and thus the costs of different illnessess

2-48
incorrectly estimated. That this is a potentially serious

problem can be seen by comparing several estimates of the

expenditures due to cancer. Rice and Hodgson (1978) modify

Paringer and Berk's assumption of constant costs by breaking down

physicians' services into four types with four different costs.

Using this procedure, they reach an estimate 85 percent higher

than Paringer and Berk's, and they feel that their result is

still an understatement. Based on actual observation of

patients, Scitovsky and McCall (1976) estimate physicians'

services for breast cancer as costing three times more than the

Rice and Hodgson estimate, While it is not clear which is the

best estimate, there is certainly a very large range in this

case. In general, it must be concluded that the estimation of

this set of weights, the v, where m - physicians' services, is

also qu.ite imprecise.

Problems also exist in the allocation of expenditures in the

remaining smaller service categories: drugs and medical

sundries, nursing home care, and nonpersonal health care

services. Early studies' treatment of the expenditures for drugs

and sundries is poor. The original Rice (1966) study does not

allocate these expenditures at all, and the Cooper and Rice

(1976) update allocates expenditures without distinguishing

between prescription and non-prescription drugs. However, the

Paringer and Berk study does make this distinction (see Berk,

et al., 1978). Without knowledge of the detailed methodology

used in the Hodgson and Kopstein study, it is impossible to

assess the accuracy of their estimates of the weights used in the

allocation of expenditures for drugs and medical sundries.

Scitovsky (1982) found no evaluation of the data in general, and

so could not express an opinion regarding its reliability. On

the other hand, Scitovsky does judge the data used in allocating

expenditures for nursing home care as poor, so the estimates of

that set of weights are suspect. Finally, some remaining

personal health care expenditures may not be allocated at all;

Hodgson and Kopstein were able to allocate all but 5.6 percent of

these expenditures. However, no attempt is made to allocate

expenditures for nonpersonal health care to specific disease

categories. For 1980, this means that an additional 16 percent

of total health care expenditures are left unallocated. In

effect, this final set of weights, - nonpersonal

health care,

vn where n

have been arbitrarily set to zero. Hodgson and

Meiners (1982) in particular emphasize that these expenditures

are a cost of illness and should be allocated by disease category

(to the extent they do not represent double-counting, see above).

A serious problem that affects the estimation of all of the

weights is the treatment of multiple conditions. The procedure

is to allocate all of a patient's expenditures to his primary

diagnosis, even though multiple conditions may be present.

Multiple conditions seem fairly common. Scitovsky (p. 479)

reports studies that 52 percent of hospital patients has multiple

conditions, 85.7 p.ercent of all residents in nursing homes has

more than one chronic condition, amd 49.5 percent of the civili,an

noninstitutionalized population reported one or more chronic

2-49
conditions, and the average number of conditions per person with

a chronic condition was 2.2.

In the context of benefit cost analysis, the proper

treatment of multiple conditions will depend upon the exogeneous

change being-considered.' For example, Rice (1966) finds that

cardiovascular conditions are often secondary causes of

disability, and as such increase the costs of treating other

illnesses by necessitating longer hospital stays, etc. Counting

these extra expenditures as part of the costs of cardiovascular

disease would add around 5 percent to Rice's original estimate.

For a program that prevented or cured cardiovascular conditions,

the savings of the expenditures due to cardiovascular

complications would be a legitimate part of the benefit measure.

However, a program that prevented the primary illness might also

prevent some of the secondary expense, so the expenditures saved

could be counted as part of the benefit of that program also.

Careful consideration of each program is necessary, to capture

all the relevant benefits, but to avoid double-counting of

benefits.

Proper treatment of the problem of multiple conditions is

also necessary in the estimation of the lost wages caused by

illness, since these are commonly assigned only to the primary

diagnosis as well.

Taken together, the above criticisms imply that the

estimates of health expenditures by disease category are subject

to numerous, possibly large, errors. Many of the different

categories of expenditures, the Eil are estimated incorrectly, as

are the weights placed on the categories. The fact that several

categories are omitted form the final estimate of expenditures by

disease might be taken to implythatthe estimates as awhole are

conservative lower bounds. It is true that the estimates will

sum to less than a true estimate of total expenditures..

However, this does not imply anything about how the individual Ej

as estimated will compare to the ideal true value. It is

impossible to make any general statements even about the sign of

the errors, much less estimate the magnitudes. Consider as an

example the estimate of health expenditures created by a chronic

illness, that requires a great deal of routine care, but little

hospitalization or surgery. Expenditures will be understated,

since such a condition would require relatively large non-health

sector costs, such as transportation. On the other hand, since

the care would be routine, the cost of each office visitwouldbe

overstated by the assumption of constant costs for all office

visits. Considering the presence or absence of multiple

conditions, whether or not the disease necessitates expenditures

drugs, nursing home care, and so on further complicates the the

issue. ~11 that can be concluded is that the estimate of the

expenditures due to such an illness may be incorrect, but by how

much or in what direction would be difficult to guess.

2-50
2.4.4.2. Estimates of Foregone Earnings

The estimation of foregone earnings due to different

diseases is somewhat more straightforward than that of medical

expenditures. The methodology of the Paringer and Berk (1977)

study is fairly typical. First, the population is broken down

into four groups losing wages due to illness: 1) currently

employed individuals; 2) individuals keeping house; 3) noninstitutionalized individuals unable to work because of ill

health; and 4) the institutional population. Within each group,

detailed information is used to estimate the amount of earnings

foregone, and to allocate these losses to specific diseases.

A general problem of the foregone earnings estimates is

that, following the human capital approach, the CO1 studies focus

on output or production lost, be it market, or non-market

household production. Thus,

lost from work,

the studies attempt to measure days

or days lost from house-keeping, as a result of

illness. This measurement does not capture all the costs that an

individual would be willing to pay to avoid. As in the models

disucssed above, an individual can be thought of spending his

time working, at leisure, or ill. Utility maximizing behavior

implies that work and leisure will be traded off until at the

margin leisure time is just as

Additional time spent ill,

valuable as working time.

whether it comes out of leisure time

or is lost from work, is valued at the wage rate by the

individual. 'By only 'valuing the time actually lost from work or

housekeeping, the CO1 measure of foregone earnings implicitly

values leisure time at zero. Compared to the conceptually

correct measure, CO1 estimates like Paringer and Berk's are

incomplete.

There are also problems specific to the estimation of the

foregone earnings of each of the four groups. The estimation of

the foregone earnings due to illness of those currently in the

work force is probably the most problem free. The Paringer and

Berk study uses unpublished National Center for Health Statistics

(NCHS) data on the number of work-loss condition days by age,

sex, and diagnosis for individuals in this group. As the NCHS

data is based on the the National Health Survey, a household

survey, the first set of problems involves the accuracy of these

estimates. In their general comments on the quality of data from

the Survey, NCHS cautions that the estimates are based on a

sample, and not the entire population, so they are subject to

sampling error, but adds that sampling errors for most of the

estimates are small (see Vital and Health Statistics ----- --- ------ --s----B--) various

issues).. Another problem is that the results of the Survey

depend, of course, on how the respondents report their health

status. While the National Health Survey is undoubtedly welldesigned, this type of problem is to some extent impossible to

eliminate. Cooper and Rice (1976) conclude that the use of

Survey data in estimating foregone earnings due to morbidity

"undoubtedly results in conservative estimates for some diseases

and overstatements for others," because of incorrect

identification of the conditions actually present in the

2-51
respondents.

A second set of problems encountered in the estimates of the

foregone earnings of the currently employed is that it is the

number of "condition days" that is reported. A condition day of

work-loss is a day of work loss associated with a certain

condition, so if an individual reports that he missed a day for

two conditions, this would be reported as two condition days of

work-loss. In general, the sum of condition days of work-loss

may exceed the total number of person days of work-loss. To

avoid double counting of work-loss days, Paringer and Berk scale

down all work-loss condition days by a constant, so the sum of

adjusted work-loss condition days equals the total of person days

of work-loss. As they note, "this procedure may create a bias in

the estimates of morbidity costs by disease class, since certain

classes are more likely to be primary causes of work-loss or beddisability than others." (Paringer and Berk, 1977, p. 9).

A final source of error in the esimation of the foregone

earnings of the currently employed is the specificity of the data

used. While the data is age- and sex- specific, the Institute of

Medicine (1981, p 91) argues that even more specific data would

be desireable. Consider their example that the better educated,

who generally have higher earnings, may be healthier than the

less well educated, and less likely to fall ill from an

exogeneous threat such as pollution. Failure to control for

education will result in an overstatement of the foregone

earnings due to an increase in illness, since the poorly educated

with below average earnings for their age/race/sex group will be

affected disproportionately. Variables other than education may

also be important, so additional bias may be present in the

estimates of the earnings lost by those currently employed.

The estimation of the "foregone earnings" of individuals

keeping house is less precise than the estimation for the

currently employed. The Paringer and Berk study uses unpublished

NCHS data on the number of bed-disability condition days for

women keeping house, by age groups. Again, problems may be

encountered because of the possible inaccuracies of the Survey

data. In addition, the bed-disability condition days are scaled

down, so the estimates may be biased as with the work-loss

condition days discussed above. Finally, the same biases may

result because education and other possibly important variables

are not controlled for.

There are further problems with the estimates of the value

of housekeeping services. First, the procedure used to value

these services is questionable. The values are based on what the

Institute of Medicine (1981, p. 91) describes as a "relatively

small outdated sample." In addition, time spent housekeeping is

valued according to the wage rates of workers in the marketplace

performing similar services. What is relevant to the individual

keeping house, however, is the wage rate she is giving up by

staying out of the market. The IOM suggests that this might be

estimated "based on the earnings of working women with similar

2-52
characteristics as housewives". Finally, the value of'time spent

by all indiv'iduals keeping house, not just women, should be

estimated. While Paringer and Berk (pp. 11-12) make a strong

case that this should be done, they only estimate the value of

men's housekeeping services (or household production in general)

for the case-of mortality. Estimates of the loss of household

production due to morbidity are limited to estimates of women's

loss.

There is less to say about the estimation of the foregone

earnings of those unable to work because of illness and the

institutional population. The key assumption made is that these

groups would have had the same work and housekeeping experiences

as the currently employed, controlling for sex and age. Whether

this is a good approximation is not clear, but it is also not

clear if any better assumption could be made. This assumption

does imply that any biases in the estimation of the foregone

earnings of the currently employed and of those keeping house

will aslo. exist in the estimates of the foregone earnings of

those unable to work and the institutional population.

A recent study by Salkever (1985) includes several

methodological refinements in the estimation of foregone earnings

due to morbidity and so avoids some of the problems outlined

above. Salkever develops estimates for foregone earnings for

non-institutionalized males age 17 to 64 by combining data from

the Health Interview Survey (HIS) and the 1976 Survey of Income

and Education (SIE). To compute the earnings loss for each work

loss day reported in the HIS, a synthetic estimate of the

respondent's hourly wage was computed. This entailed inserting

data on the respondent's personal character-istics from the HIS

into an hourly wage regression estimated with SIE data. The

independent variables included measures of the individual's

education, presence or absence of a chronic condition, region and

urban or rural character of residence, industry where person was

employed and average earnings for the occupation in which the

person was employed. Using such specific data on the individuals

who suffer work loss days implies that Salkever's estimates of

foregone earnings are much less likely to suffer the bias

problems the Institute of Medicine described. To return to the

IOM example, since education differences are controlled for in

Salkever's estimates, foregone earnings will not be. overstated

even if the better educated earn more and are less likely to be

sick, as the IOM suggests.

Salkever also estimates the earnings losses for persons

unable to work because of illness. As in earlier studies, he

assumes these persons lose income equal to the earnings of

similar individuals without chronic health problems.

Specifically, these foregone earnings were computed as the

average earnings by persons in the SIE data, without chronic

health problems, classified by age group, education level, race

and region of residence. Just as for valuing work loss days,

using more specific data on the individuals unable to work

because of illness means that Salkever's estimates are less

2-53
likely to be biased.

Salkever's estimates of foregone earnings due to morbidity

represent important improvements in methodology, which should be

relfected in improved accuracy. However, since Salkever only

develops estimates for males age 17 to 64 for certain conditions,

his estimates are not directly comparable to the more

comprehensive estimates of earlier studies reported below. As a

result, it is difficult to judge the empirical importance of

either Salkever's refinements or the inaccuracies implied by the

earlier methodology.

In conclusion, the estimation of the foregone earnings due

to illness may be straightforward, but the estimates still are

not necessarily very close to the ideal true values. Most of the

errors tend to understate foregone earnings due to morbidity, so

in this case, unlike the health expenditures estimates, the

existing estimates can be considered as conservative lower bounds

to the true values.

2.4.5. --Empirical Estimates of the Cost of Illness __---- --------- -- --- ---- -- ---_---

In this section, estimates of medical expenditures and

foregone earnings due to illness are presented, to be used as a

measure of the value of improved morbidity risks. Particular

emphasis is placed on the cost of illness estimates for diseases

and disease categories that might be related to environmental

quality. In section 2.4.5.1, some estimates from existing CO1

studies of the total medical expenditures and foregone earnings

to morbidity related to different disease categories are

presented. In section 2.4.5.2, these estimates are put on a per

case basis, and additional per case estimates are presented. In

section 2.4.5.3, for certain conditions, the costs are also

expressed on a per day of illness basis.

2.4.5.1. Total Medical Expenditures and Foregone Earnings

Due to Morbidity

Reported in Table 2-4 are total figures for medical

expenditures and foregone earnings due to morbidity caused by

various diseases or disease groups. The totals have all been

updated to August 1984 dollars, using the medical care component

of the CPI to adjust the medical expenditures, and the general

CPI to adjust foregone earnings. It is recognized that this

procedure may introduce errors in the estimates, due to relative

price changes in health care services and relative wage changes

for different age/sex/race groups.

In addition to the comprehensive estimates of the cost of

all illnesses of the Paringer and Berk and the Hodgson and

Kopstein studies, Table 2-4 also reports the results of studies

that estimate the costs of a specific illness or group of

2-54
illnesses. 2 These studies are useful in two ways. First, the

expenditures and earnings lost. due to a specific illness (e.g.

emphysema) can be found. Comprehensive studies only provide

estimates relating to more general categ0rie.s (e.g., all

respiratory diseases). Second, the specific illness studies may

employ a dif.ferent methodology. This is particularly relevant

for the estimates of health expenditures. While some studies use

the same methods and data sources as the comprehensive studies,

others estimate expenditures based on more disaggregated data,

such as the observation of actual cases. For a review of the

methodology and quality of over 200 studies that estimate the

costs of illness, see Hu and Sandifer (1981). Briefly, the

studies by the National Heart and Lung Institute (NHLI (1972,

1975)) and the Acton (1975) study follow essentially the same

methodology as the Paringer and Berk (1975) and the Hodgson and

Kopstein (1984) studies, as reviewed above in Section 2.4.4. The

study by Freeman, et al., (1975) represents a slightly different

methodology (and it is thus notable the close correspondence of

the Freeman estimates and the NHLI (1972) estimates of the cost

of emphysema). The Hartunian, et al., (1980) follows a

methodology followin 4an incidence-based approach to measuring

medical expenditures.

It is difficult to make many general statements concerning

the range of estimates presented in Table 2-4. It is clear that

the estimates from the Paringer and Berk and the Hodgson and

Kopstein studies are much higher than comparable estimates from

other studies. This seems to be part of a general trend that the

more recent estimates are higher than estimates based on an

earlier time period and scaled up for inflation. Two influences

seem important. First, the use of the medical care component of

the CPI and the general CPI in adjusting for inflation may

somehow be biasing the earlier estimates downward. Second, the

more recent studies may be a more complete accounting of costs,

reflecting improvements in methodology and data sources. For

instance, more expenditures are allocated by disease in the more

recent studies, and more allowance is made for household

production in the estimation of foregone earnings. For these

reasons, .it is likely that the more recent estimates are more

accurate, and whenever possible that most recent study should be

used to provide estimates for use in benefit cost analysis.

2-55
TABLE 2-4: TOTAL MEDICAL EXPENDITURES AND FOREGONE EARNINGS

DUE TO SELECTED ILLNESSES

(in million $, August 1984)

_____-----------------------------------------------------------

Disease Medical

Category Expenditures

Foregone

Earnings

__-_-------_--__------------------------------------------------

--- -------- All diseases

Hodgson and

Kopstein (1984)

Paringer and

Berk (1977)

--------- --- Infective and

--------- -------- Parisitic Diseases

Hodgson and

Kopstein (1984)

Paringer and

Berk (1977)

--- ----- ------ Neoplasms lcancerl

Hodgson and

Kopstein (1984)

Paringer and

Berk (1977)

Hartunian, et al.

(1980)

-------- -- --- Diseases of the Circulatory ------m--m

System ----

All ---

Hodgson and

Kopstein (1984)

Paringer and

Berk (1977)

Acton (1975)

315,058

112,319

6,459

3.024

19,563

2,144

14,522

47,652

14,557

16,963

10,557

2-56
TABLE 2-4 (continued)

Disease Medical Foregone

Category Expenditures Earnings

-----,---,--~---------------------------------------------------

-_-------------- Cerebreovascular

------- ------ Disease jStroke1

Hodgson and

Kopstein (1984)

Paringer and

Berk (1977)

Hartunian, et al.

(1980)

Acton (1975)

NHLI (1975)

------- ----- ------- Coronary Heart Disease

Hartunian, et al.

(1980)

Acton (1975)

NHLI (1975)

Respiratory Diseases --- ------ --------

All ---

Hodgson and

Kopstein (1984)

Paringer and

Berk (1977)

NHLI (1972) 6,385 4,284

-- Emphysema - ----

NHLI (1972)

Freeman, et al.

(1976)

7,324

685

5,364

2,201

3,789

5,642

5,871

7,912

1,132

735

5,416

1,157

24,850

16,572

652 1,414

579 3,610

2-57
2.4.5.2.Per Case Estimates of Medical Expenditures and' Foregone

Earnings Due to Morbidity

Table 2-5 reports per case estimates of medical

expenditures are foregone.earnings due to various illnesses. The

estimates are based on the same sources as the totals of Table 2-

4. In addition, independent per case estimates by Scitovsky and

McCall (1976) and Acton (1975) are presented. All estimates are

updated to August 1984 dollars (See Notes to Table 2-6 for

details).

In putting the total figures on a per case basis, the basic

procedure is simply to divide the total cost figure for ayearby

the appropriate number of cases of that illness in that year.

The proper measurement of the appropriate number of cases is not

simple, however. In defining what constitutes a "case" of an

illness, the specific use of the per case estimates in benefit

cost analysis must be considered. For instance, it might be

known from epidemiologic or health econometric studies that a

reduction in pollution will reduce the number of serious cases of

a particular disease, i.e. only those cases that involve medical

expenditures and foregone earnings. In this situation, in

preparing per case estimates it would thus be desirable to define

a case as only a case of the disease that does involve medical

expenditures and foregone earnings. Instead, it might be known

only that the reduction in pollution will reduce the number of

cases of a particular disease, without specifying if the cases

are serious or not. Under these circumstances, a more general

definition of case is desirable, allowing for cases involving

varying amounts of medical expenditures and foregone earnings to

be included. Essentially, the per case estimates of medical

expenditures and foregone earnings represent the average cost of

a case of disease, but what population over which to average is

somewhat ambiguous. The per case estimates of Table 2-5 are

prepared using a broad definition of the number of cases, so the

average medical expenditures and foregone earnings due to a case

of illness are conservative estimates.

The source of the data for the number of cases of acute and

chronic illnesses (except neoplasms) is the National Health

Survey, as reported by the National Center for Health.Statistics

(NCHS) in various issues of Vital and Health Statistics As ----- --- ------ ----------*

described above, the estimates from the survey are subject to

possible inaccuracies. Estimates of the number of cases of the

different illnesses may understate the actual number of cases,

in general. For acute cases, the estimates exclude all conditons

involving neither restricted activity nor medical attention. For

chronic cases, data is available on the degree of impact the

illness had, so the number of cases could be adjusted downward so

that only more severe cases are counted. However, the fact that

chronic illnesses are generally under-reported in surveys, and

the likely use of' the per case estimates in benefit cost analysis

of changes in all types of cases of illness argue forthebroader

measure of chronic cases to be used.

2-58
An additional problem encountered in estimating the number

of cases of chronic illnesses is encountered in that the

prevalence of chronic conditions is not estimated for every year.

The prevalence estimates used in preparing Table 2-5 are

estimates from the survey for the closest year to the year used

as a base for the different studies that report total medical

expenditures and foregone earnings due to morbidity.

Estimating the number of cases of neoplasms (cancer)

presents several special problems. Three different measurements

are possible candidates. First, the incidence of cancer, that

is, the number of new cases of cancer diagnosed in a given year,

could be used, Second, the number of individuals under medical

care for cancer is a possible measure of the number of cases of

cancer existing in a given year. Third, by combining incidence

and survival data, it is possible to estimate the number of

people alive in a given year with a history of cancer. The

incidence measurement is an understatement of the number of cases

of cancer, since in any given year there will be individuals with

cancer that was incurred and diagnosed in an earlier year. The

number of people alive with a history of cancer is an

overstatement, because it includes individuals who for all

practical purposes have been totally cured of cancer. So the

figure used in preparing Table 2-5 is the number of individuals

under medical care for cancer, for 1974 (Cancer Facts and

Figures, 1974),

-s---B ----- ---

---- though the measure is not exactly comparable to

the broader definitions of cases used for other illnesses. Added

to this figure is an estimate of the prevalence of neoplasms of

the skin, from NCHS estimates. It should be pointed out that

adding neoplasms of the skin doubles the number of cases of

cancer, and biases the per case estimates of the medical

expenditures and foregone earnings due to cancer downwards, since

neoplasms of the- skin are likely to involve lower medical

expenditures and foregone earnings than other cancers. This is

an example of the inaccuracies involved in using estimates of the

costs of broad groups of illness, such as cancer, as opposed to

an estimate of the cost due to a more specific illness, such as a

particular type of cancer<

The basic procedure for deriving per case estimates

described above is not applied to the totals from the study by

Hartunian et a1.(1981). This study follows an incidence based

approach to estimating the costs of illness, while the other

studies cited follow a prevalence based approach. A problem of

comparability results. On an aggregate basis, incidence based

estimates and prevalence based estimates may be approximately the

same; in fact, Hartunian et a1.(1980) find relatively small

differences between the two approaches for some conditions.

However, putting the prevalence based estimates on a per case

basis yields estimates of the average yearly costs of a case of

illness. In contrast, expressing incidence based estimates on

this same basis would yield estimates of the average lifetime

costs of a case of illness. A secondproblemis that expressing

the total incidence based estimates of costs would entail

2-59
dividing total costs b,y the incidence of the different

condition f2

and estimates of incidence are limited in scope and

accuracy.

The per case estimates due to Hartunian et al. reported in

Table 2-5 are estimates of the average first year costs of

several conditions. The estimates are derived from the details

given of the calculation of the total costs in Hartunian etal.

(1981, various chapters). Since detailed descriptions of the

calculations were only given for selected conditions to be

illustrative of the methodology, the number of conditions for

which first year costs can be estimated is limited.

In addition to the per case estimates derived from studies

estimating total medical expenditures and foregone earnings,

Table 2-5 includes per case estimates from two independent

sources. Scitovsky and McCall (1976, as cited in Mushkin (1979))

report average medical expenditures due to several conditions,

based on the cost of care in the Palo Alto Medical Clinic in

1971 actually incurred by patients. Estimates of per case

medical expenditures and foregone earnings derived from Acton

(1975, tables 7 and 9) are also presented. In what is described

as an illustrative exercise, Acton puts his total estimates of

the costs of various diseases of the circulatory system on a per

case basis using a procedure similar to that described above.

The important difference is that Acton attempts to estimate the

medical expenses and foregone earnings of an average person

actively suffering the consequences of a disease. That is, Acton

uses a narrower definition of a "case" of a disease than is used

in the preparation of the other per case estimates of Table 2-5.

While Table 2-5 may seem to include a very wide range of

estimates, considering truly comparable diseases shows some

agreement between the studies. The lowest estimates of medical

expenditures and foregone earnings per case are for all

respiratory diseases ($87 and $56, respectively), and for all

infective and parasitic diseases ($123 and $63). However, the

per case figures for all respiratory diseases are influenced by

the very large number of cases of upper respiratory tract

infections that presumably involve relatively low medical

expenditures and foregone earnings. The estimates of the medical

expenditures and foregone earnings due to a more serious

respiratory disease such as emphysema are substantially higher

($497 and $1,078 from NHLI, or $441 and $2,753 from Freeman,

et al.). A similar result holds when comparing the cost of cases

of diseases of the circulatory system. The per case estimates

for all diseases of the circulatory system are much smaller than

the per case estimates for specific, more serious diseases, such

as cerebreovascular disease (stroke), coronary heart disease, and

myocardial infarction. The different estimates for these

specific diseases show more agreement between studies, but there

is still a fairly wide range. For instance, Acton estimates the

medical expenditures due to a stroke as $1,561, while the per

case estimate based on Hodgson and Kopstein is $4,210. As noted

above, Acton uses a lower estimate of the number of cases in

2-60
expressing his results on a per case baiss, which implies that if

the Acton and the Hodgson and Kopstein estimates were computed in

exactly the same manner, the difference would be even greater.

This difference in the medical expenditures due to a case of

stroke is the most extreme difference found in Table 2-5 for a

specific dis.ease; in general the per case estimates based on

different studies' estimates of the medical expenditures and

foregone earnings for a specific illness are much closer

together.

To sum up, in using the per case estimates of Table 2-5 in

benefit cost analysis, two considerations should be kept in mind.

First, just as for the estimates of the totals in Table 2-4, the

per case estimates in Table 2-5 based on the most recent studies

are judged as generally superior in quality. Second, the

estimates of the costs of a specific disease should be used

rather than the estimates of the costs of a group of diseases,

whenever possible.

2-61
TABLE 2-5: PER CASE MEDICAL EXPENDITURES AND FOREGONE EARNINGS

(in $, August 1984

_________--_-------------------------------------------

Medical Foregone

Expenditures Earninings

Disease Category Per Case Per Case

_____-____-____----_--------------------------------------------

--------- --- Infective and

-------me Parasitic Diseases --------

Hodgson and

Kopstein (1984)

Paringer and

Berk (1977)

123

--- NeoPlasms ----_

All ---

Hodgson and

Kopstein (1984)

Paringer and

Berk (1977)

--- ------ Lung Cancer

Hartunian, et al.

(1981)

------ -- --- ------ Cancer of the Breast

Scitovsky and

McCall (1976)

-------- -- --- Diseases of the

---------- Circulatory System ----

All ---

Hodgson and

Kopstein (1984)

Paringer and

Berk (1977)

-m-m------------ Cerebreovascular

-e-s--- Disease ------ LStrokel

Hodgson and

Kopstein (1984)

Paringer and

Berk (1977)

NHLI (1975)

Acton (1975)

63

8,780

962

15,687 13,404

7,605

773

275

4,210

394

3,708

1,561

1,318

803

2-62
TABLE 2-5 (continued)

Medical Foregone

Expenditures

Disease Category

Earninings

Per Case Per Case

------------~--------,------~--------------------------------------

------- ----- ------- Coronary Heart Disease

NHLI (1975) 2,393

Acton (1975) 1,406

Angina Pectoris -- --- --------

Hartunian, et al.

(1980)

Myocardial -----___

----_---__ Infarction

Scitovsky and

McCall (1976)

Respiratory Diseases --- ------ --------

All ---

Hodgson and

Kopstein (1984)

Paringer and

Berk (1977)

NHLI (1967)

-- Emphysema - ----

NHLI (1967)

Freeman, et al.

(1976)

------___ Pneumonia

(non-hospital care)

Scitovsky and

McCall (1976)

246 0

11,242

87

25

497 1,078

441 2,753

253

350

1,297

56

17

2-63
TABLE 2-6: PART 1

PER CASE MEDICAL EXPENDITURES

(background for Table 2-5)

Total Costs Number of Per Case Per Case

(in mil- Cases costs costs

Disease Category lions) (in thou- (year (August

and Study sands) varies) 1984)

_____-----------------------------------------------------------

--------- --- Infective and

e-e------ Parasitic Diseases --------

Hodgson and 4,498

Kopstein

(1984)

--- ----- Neoplasms

Hodgson and 13,623

Kopstein

(1984)

-------- -- --- Diseases of the

---------- Circulatory System ----

All ---

Hodgson and 33,184

Kopstein

(1984)

------ Stroke

Hodgson and 5,100

Kopstein

(1984)

NHLI (1975) 971

52,691 85.37 123

2,228 6114.5 8,780

61,652 538 773

1,740

1,534

2,931 4,210

633 3,708

2-64
TABLE 2-6; PART 1 (continued)

Total Costs Number of Per Case Per Case

(in mil- Cases costs costs

Disease Category lions) (in thou- (year (August

and Study sands) varies) 1984)

-_--------__----------------------------------------------------

------- ----- Coronary Heart

------- Disease

NHLI (1975) 2,072 3,307 627 2,393

-- ------ Respiratory Diseases _-------

All ---

Hodgson and 17,305 285,323 60.65

Kopstein

(1984)

NHLI (1967) 1,672 258,473 6.47

-- Emphysema - s--e

87

25

NHLI (1967)

Freeman,

et al.

(1976)

171 1,313 130.24 497

183 1,313 139.5 441

2-65
TABLE 2-6: PART 2

PER CASE FOREGONE EARNINGS

Total Costs Number of Per Case Per Case

(in mil- Cases costs costs

Disease Category lions) (in thou- (year (August

and Study sands) varies) 1984)

______---__--__------------------------------------- _

---w-s--- Infective and ---

--------- Parasitic Diseases -----_-_

Paringer and 1,559

Berk (1977)

--- NeoElasms ---__

Paringer and 1,105

Berk (1977)

-------- -- --- Diseases of the

---------- Circulatory System ---_

All ---

Paringer and 8,744

Berk (1977)

------ Stroke

Paringer and

Berk (1977)

NHLI (1975)

------- ----- ------- Coronary Heart Disease

NHLI (1975)

--- ------ -------- Respiratory Diseases

353

421

370

All ---

Paringer and 8,542

Berk (1977)

NHLI (1967) 1,370

48,206 32.34 63

2,228 496 962

61,652 141.8 275

1,740 203 394

1,534 274 1,318

3,307

285,323

258,473

112

28.75

5.3

350

56

17

2-66
-- Emphysema - ----

NHLI (1967) 452

Freeman, 1,343

et al.

(1976)

Explanatory Notes For Table 2-6 --B-B-- ----- --- ----- ---

1.

2.

3.

4.

1,313

1,313

344.25 1,078

1,023 2,753

Total costs (in millions) are the original estimates of the

various studies of the total medical expenditures and foregone earnings. These estimates are for various years.

Number of cases (in thousands) is the sum of the incidence

of acute cases and the prevalence of chronic cases, for the

year closest to the year the studies estimated that could

be found. Source: Vital and Health Statistics ----_ --- ---- -- ---------- 9 various

issues.

Per case costs = total costs divided by number of cases.

These per case costs are for the years of the original

studies.

Per case costs (Aug. 1984) are the previous per case costs

expressed in current (Aug. 1984) dollars; medical expenditures are adjusted using the medical care component of

the CPI; foregone earnings are adjusted using the general CPI.

2-67
2.4.5.3. Estimates of the Costs of Illness per Day Spent Ill

The third column of Table 2-7 presents estimates of the

costs of various illnesses per day spent ill. These estimates

are derived by dividing the per case costs developed above by the

average number of days spent ill per case of illness per year.

In the first column of Table 2-7 are per case costs of illness

(medical expenditures plus foregone earnings) from Table 2-6.

Estimates of the average number of Restricted Activity Days

(RADs) are available from the Health Interview Survey for most

acute conditions and certain chronic conditions. These estimates

are presented in column two of Table 2-7.

Costs of different illnesses per day spent ill present a

fairly narrow range, from $10 to $81. This reflects the fact

that a great deal of the difference between aminor and a serious

illness is simply the average number of days spent ill: the

number of days per condtion varies from about 4 for an average

case of acute infective and parasitic disease or for an acute

respiratory disease, to over 40 days spent ill due to heart

disease. Another possible difference is the degree of disability

on the day spent ill. A Restricted Activity Day is defined as

"one on which a person substantially reduces his normal activity

for the whole day due to an illness or injury" (Vital and Health

Statistics), this can range from reduced activity alone to a day

of work loss to a day of bed disability. The RADs for the more

serious conditions may reflect a greater restriction of activity

than the RADs for the minor conditions.

2-68
TABLE 2-7: COSTS OF ILLNESS PER DAY SPENT ILL

(in $. August 1984)

______-_-__-----------------------------------------------------

RADs

costs Per Case costs

Disease Category Per Case Per Year Per RAD

__-__-----------------------------------------------------------

----_---- Infective and ---

--------- Parasitic Diseases m------B

Hodgson and

Kopstein (1984)

Paringer and

Berk (1977)

186 4.06 46

----_--- Diseases of the -- ---

--------_- Circulatory System ----

------- ----- Coronary Heart Disease ___----

NHLI (1975) 2743 43.1 64

Acton (1975) 2703 43.1 63

--- ------ -------- Respiratory Diseases

--- All

Hodgson and

Kopstein (1984)

Paringer and

Berk (1977)

NHLI (1967)

-- Emphysema - ----

NHLI (1967)

Freeman, et al.

(1976)

m-----e-- Pneumonia

(non-hospital care)

Scitovsky and

McCall (1976)

143

42 4.1 10

1575 35.8 44

3194 35.8 89

253 18 14

4.1 35

2-69
2.4.6. Concluding -------I- Remarks.og ------- the Cost --- ----of Illness -------Approach -----

Section 2.4 is concerned with the problems of valuing

changes in health risks as reduction in health expenditures and

foregone earnings, i.e., the cost of illness approach. A

contribution of the present project has been to put aggregate

costs of illness on an individual per case and per day spent ill

basis. Results indicate that a typical case of acute respiratory

disease involves $87 of medical expenditures, and $56 of foregone

earnings. A case of emphysema involves $441 of medical

expenditures, and $2,753 of foregone earnings. A day spent ill

due to a typical case of acute respiratory illness costs $35,

while a day spent ill due to emphysema implies costs of $89.

Estimates of this kind on an individual basis needed to evaluate

environmental policy changes have not been available heretofore.

The cost of illness approach is an important source of

estimates for the value of health, because it is commonly

accepted by many researchers in the health care fields, and it

provides estimates for the value of a wide range of health

effects. Therefore, section 2.4 includes a careful evaluation

of the approach to assess its usefulness and accuracy.

This evaluation reveals that the approach suffers from

conceptual and methodological shortcomings, which limit its

usefulness. One set of issues essentially raises the problem

that the cost of illness benefit measure is not well-related to

the conceptually correct willingness to pay measure. The

discussion of this problem (section 2.4.2) suggests that a cost

of illness measure may be a lower bound to a willingness to pay

measure. It is not necessarily a good approximation to the

willingness to Pay measure, however. In addition, the

distinction between individual and societal willingness to pay

has.been treated unevenly in the cost of illness approach, and

deserves further consideration.

The review of the methodology of the cost of illness

approach in section 2.4.4 leads to the conclusion that the

estimates.of medical expenditures and foregone earnings due to

morbidity are not particularly precise or reliable. This is

especially significant since it is the presumed practical

advantages of calculating medical expenditures and foregone

earnings, instead of calculating willingness to pay, that is

often the stated reason for preferring the cost of illness

approach.

2.2.10. --.------- Footnotes

1. The Paringer and Berk (1977) study is cited by Mushkin

(1979) 9 and is part of a series of estimates of the cost of

illness for the years 1900, 1930, 1975, and projected for

the year 2000, prepared at Georgetown University Public

Services Laboratory.

2-70
All details of the methodology of Hodgson and Kopstein

(1984) study are not described in the published article.

They state that their "methodology follows closely that

originally devised by Cooper and Rice (1976) to allocate

expenditures among diagnoses, amended to include several

additional sources of data." My discussion and criticism of

the quality of the estimation of health care expenditures is

based on the Cooper and Rice methodology, so most of it

should apply to the Hodgson and Kopstein study. Since

Hodgson and Kopstein do use new sources of data, it is

expected that their estimates will be superior to earlier

estimates, and some of the criticisms below may not apply.

2. As explained earlier, the Paringer and Berk and Hodgson and

Kopstein studies are used because they represent the most

recent estimates o f foregone earnings and medical

expenditures due to illness that could be found.

3. The Hartunian et al. study reports foregone earnings due to

morbidity and mortality combined, so the foregone earnings

due to morbidity alone could not be derived easily. For

this reason, only the estimates of medical expenditures from

this study are reported in Table 2-4.

4. For a more complete discussion of the difference between

prevalence based and incidence based estimates of the cost

of illness, a report is available upon request.

2-71
2.2.11. ---------- References

1.

2.

3.

4.

5.

6.

7.

8.

9.

10.

11.

12.

13.

Acton, J.P. Measuring the Social Impact of Heart and Circulatory Disease Programs: Preliminary Framework and Estimates. The Rand Corporation, Santa Monica, California,

April 1975. pp. 35-57.

Bailey, M.J. Reducing Risks to Life: Measurement of the

Benefits, American Enterprise Institute, Washington, DC,

1980.

Berk, A., L. Paringer and S.J. Mushkin. The Economic Cost

of Illness, Fiscal 1975. Medical Care, 16, 1978, pp. 785-

790.

Blomquist, G. The Value of Human Life: An Empirical Perspective, Economic Inquiry, 19, January 1981. pp.157-164.

Conley, B.C. The Value of Human Life in the Demand for

Safety, American Economic Review, 66,1976. pp. 45-SS.,

Cooper, B. and Rice, D. The Economic Costs of Illness

Revisited. Social Security Bulletin, 39, 1976. pp. 21-36.

Courant, P. and Porter, R. Averting Expenditures and the

Cost of Pollution. Journal of Environmental Economics and

Management, 8, 1981. pp. 321-329.

Cracker, T.D., Schulze, W., Ben-David, S., and Kneese, A.V.

Methods Development for Assessing Air Pollution Control

Benefits. Experiments in the Economics of Air Pollution

Epidemiology, Volume 1, U.S. EPA Grant #R805059010, U.S.

Environmental Protection Agency, Washington, DC 1979.

Feldstein, P.J. Health Care Economics. John Wiley and

Sons, New York, 1979, 1982 (second edition).

\

Freeman, R.A. et al. Economic Cost of Pulmonary Emphysema:

Implications for Policy on Smoking and Health. Inquiry 13,

March, 1976. pp. 15-22.

Gibson, R.M., Waldo, D.R., and Levit, K.R. National Health

Expenditures, 1982. Health Care Financing Review 5, Fall,

1983. pp. l-31.

Grossman, M. On the Concept of Health Capital and the Demand

Health. Journal of Political Economy 80, March/April 1972.

pp.223-225.

Harberger, A.C. Survey of Literature on Cost-Benefit

Analysis for Industrial Project Evaluation, in his Project

Evaluation, The University of Chicago Press, Chicago, 1972.

2-72
14.

15.

16.

17.

18.

19.

20.

21.

22.

23.

24.

25.

26.

Harberger, A.C. Three Basic Postulates for Applied Welfare

Economics: An Interpretive Essay", in his Taxation and

Welfare. The University of Chicago Press, Chicago, 1974.

Harrington, W. and Portnoy, P.R. Valuing the Benefits of

Improved Human Health". Mimeo, Resources for the Future,

Washington, D.C., 1982.

Hartunian, N.S., et al. The Incidence and Economic Costs of

Cancer, Motor Vehicle Injuries, Coronary Heart Disease and

Stroke: A Comparative Analysis. American Journal of Public

Health 70, December 1980, pp. 1249-1260; and The Incidence

and Economic Costs of Major Health Impairments, Lexington

Books, 1981.

Hodgson, T. and Kopstein, A. Health Care Expenditures for

Major Diseases in 1980. Health Care Financing Reviews 5, l12, Summer 1984.

Hodgson, T. and Meiners, M. Cost-of-Illness Methodology: A

Guide to Current Practices and Procedures. Milbank Memorial

Fund Quarterly/Health and Society 60: 2, 1982. pp. 429-462.

Hu, T. and Sandifer, F.H. Synthesis of Cost of Illness

Methodology. Prepared for the National Center for Health

Services Research, Department of Health and Human Services,

Washington, DC, 1981.

Institute of Medicine. Reliability of Hospital Discharge

Abstracts, Reliability of Medicare Hospital Discharge

Records, Reliability of National Hospital Discharge Survey

Data, National Academy of Sciences, Washington, DC, 1977.

Institute of Medicine. Costs of Environment-Related Health

Effects: A Plan for Continuing Study, National Academy

Press, Washington, DC, January 1981.

Landefeld, J.S. and Seskin, E.P. The Economic Value of

Life: Linking Theory to Practice. American Journal of

Public Health 72, June 1982. pp. 555-566.

Lave, L.B. and Seskin, E.P. Air Pollution and Human Health.

The Johns Hopkins University Press, Baltimore, 1977.

Liu, B. and Yu, E. Physical and Economic Damage Functions

for Air Pollutants by Receptor. EPA Publication No. 660/S76-011, Socioeconomic Environmental Studies Series. NTIS

Publication No. PB 262 340. 1976.

Linnerooth, J. The Value of Human Life: A Review of the

Models, Economic Inquiry 17, January 1979. pp. 52-74

Mishan, E.J. Evaluation of Life and Limb: A Theoretical

Approach. Journal of Political Economy 79, July/August

1971. pp. 687-705.

2-73
27.

28.

29.

30.

31.

32.

33.

34.

35.

36.

37.

38.

39.

Mushkin, S.J. Biomedical Research: Costs and Benefits.

Ballinger, Cambridge, MA., 1979.

Paringer, L. and Berk, A. Costs of Illness and Disease

Fiscal Year 1975, Georgetown University Public Services

Laboratory, Washington, DC, January 1977.

Rice, D.P. Estimating the Cost of Illness. Health

Economics Series Number 6, U.S. Department of Health, Education and Welfare, Public Health Service, Washington, DC,

1966.

Rice, D.P. and Hodgson, T.A. Social and Economic Implications of Cancer in the United States. National Center for

Health Statistics, Washington, DC. Department of Health,

Education, and Welfare, 1978.

Rosen, Sherwin. Valuing Health Risks. American Economic

Review 71:241-245. 1981.

Salkever, D.S. Morbidity Costs: National Estimates and

Economic Determinants, NCHSR Research Summary Series,

DHHS Publication No. (PHS) 86-3393, October 1985.

Scitovsky, A. Changes in the Costs of Treatment of Selected

Illnesses, 1951-65. American Economic Review, 1967. Vol.

57, PP. 1182-95.

Scitovsky, A. Costs of Medical Treatment, Reply, American

Economic Review, 1968. Vol. 58, pp. 939-940.

Scitovsky, A.A. Estimating the Direct Costs of Illness.

Milbank Memorial Fund Quarterly/Health and Society 60:3,

1982, pp. 463-489.

Scitovsky, A.A. and N. McCall. Changes in the Costs of

Treatment of Selected Illness. 1954-1964-1971 NCHSR,

Research Digest Series, DHEW Publication No. (HRH) 77-3161,

July 1976.

Smith, V.K. and Desvouges, W.H. Averting Behavior: Does it

Exist? Vanderbilt University Department of Economics

Working Paper, September 1985.

U.S. Health Interview Survey. Current Estimates from the

Health Interview Survey. Vital and Health Statistics 1975,

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U.S. Health Interview Survey. Prevalence of Chronic

Conditions of the Genitourinary, Nervous, Endocrine,

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and 1977, serices 10; no,. 109.

2-74
40.

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44.

45.

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1975, series 10, no 123.

U.S. Health Interview Survey. Prevalence of Selected

Reported Chronic Conditions. Vital and Health Statistics

1979, series 10, no 99.

U.S. National Heart and Lung Institute (NHLI) Task Force in

Arteriosclerosis. Economic Impact of Arteriosclerosis.

Appendix D. Report by NHLI, Vol. 2, G.P.O. Washington, DC,

June 1971.

U.S. National Heart and Lung Institute (HNLI). Economic

Costs of Respiratory Diseases. Respiratory Disease Task

Force Report on Problems, Research Approaches, Needs. DHEW

Publication No. (NIH) 76-432, pp. 205-243. U.S. National

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Usher, D. An Imputation to the Measure of Economic Growth

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Income and Wealth, National Bureau of Economic Research, New

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Violette, D.M., and Chestnut, L.G. Valuing Reductions in

Risks. A Review of the Empirical Estimates. Energy and

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79, May/June 1971. pp. 527-544.

2-75
2.5: CONTINGENT VALUATION OF HEALTH

2.5.1. Introduction _-----------

One approach to valuing anon- marketgoodis to conduct a

survey and ask people what they would pay for the good,

hypothetically assuming (contingent upon) the existence of a

market for the good. This approach is termed the contingent

valuation method (CVM), and has been applied to a variety of

environmental goods, including air quality and health. The

purpose of this section is to review the applications of the CVM

to the problem of valuing health. Since the goal is to find

useful empirical evidence, discussion of both methodological

issues and of actual results is required.

Section 2.5.2 is a brief overview and assessment of the

contingent valuation method, drawing heavily upon the recent

review by Cummings, et.al. Section 2.5.3 concerns the

application of contingent valuation to health. It critiques

three studies that apply the method to health effects possibly

related to air pollution: Loehman, et al. (19791, Rowe and

Chestnut (1984) and Tolley et al. (1985, Volume 3 of this

report). Section 2.5.4 is a conclusion and summary of the

empirical results, with emphasis on explaining the differences

between the studies.

2.5.2. --s----s Overview and Assessment of Contingent Valuation --- ---------- -- -m---B --- -e----m--

Contingent valuation is an established, though still

controversial, research method for valuing non-market goods.

Since it is a fairly flexible approach providing a conceptually

correct and complete measure of willingness to pay, it has been

applied to a wide variety of non-market goods, especially in the

area of environmental economics. Studies have also compared the

results to indirect market methods for valuing such goods. Many

methodological issues concerning the CVM have been addressed as

well. Reviews of the literature exist elsewhere, notable is the

review by Cummings, et al. (forthcoming). In addition, Volume 3

of this report addresses methodological problems from the

practical perspective of designing a survey instrument for

contingent valuation of health. Therefore, the discussion that

follows of some of the important issues in CVM is quite brief.

The focus is on the accuracythatcan be expected for values from

contingent valuation studies.

2.5.2.1. Biases and Contingent Valuation

The basic reason contingent valuation results may be

inaccurate is the possibility that the responses are biased away

from the unobservable true maximum willingness to pay (or

accept). Types of bias often mentioned include hypothetical

2-76
bias, strategic bias, starting point bias, vehicle bias, and

information bias, though these categories can overlap.

Hypothetical bias and strategic bias can be understood as a

dilemma for contingent valuation. On the one hand, if a

respondent be-lieves the questions to be entirely hypothetical, he

has little incentive to give accurate information concerning his

maximum willingness to pay. On the other hand, if the respondent

sees the exercise as playing an important role in future policymaking and not hypothetical, he may have incentives to

strategically misrepresent his values.

Other biases stem from the structure of the CV

questionnaire. If a bidding process is used that begins by

asking ,whether the respondent is willing to pay a certain amount,

respondents may view this figure as appropriate and so bids would

be biased- towards the starting point. Another problem is the

vehicle by which the contingent payment is made. If it is

suggested that the payment will occur through a concrete vehicle

such as an increase in taxes, respondents who dislike taxes may

under-report their values, or protest the exercise by giving zero

bids. Finally, the values reported by respondents in a CV

experiment may be sensitive to the information provided them

during the questioning, and even the order of questions asked may

be important.

Various studies shed light on the importance of the possible

biases the CVM may be subject to. The fundamental problem that

contingent valuation is hypothetical has been investigated by

conducting experiments that include both hypothetical payments

and actual cash payments. Bishop and Heberlein conducted

surveys of hunters who had received free early season goose

hunting permits. For actual cash payments, the mean willingness

to sell was $63, while for hypothetical payments the mean

willingness to sell was $101. Carson and Mitchell dispute

this finding: in a re-analysis of Bishop and Heberlein's data

they find no statistically significant difference between the

hypothetical and actual values. However, Bishop and Heberlein

defend their original methodology, and present preliminary

results from a new survey that supports the finding that

hypothetical bias exists. For a discussion of this debate, see

Bishop and Heberlein in Cummings, et al. (forthcoming), and the

Appendix to Cummings et al. by Carson and Mitchell.

Other sources of bias can also be more or less directly

tested, by varying the starting point, payment vehicle, or

information given, or by changing the incentives for strategic

behavior. Results to date are somewhat inconclusive, though

Cummings et al. tend to minimize the importance of strategic bias

and starting point bias, while noting that payment vehicle and

information may be more important sources of bias. No strong

consensus seems to have been reached in this area, and in

particular a number of researchers believe starting point bias

may be quite significant. For a discussion of the various

studies' results that relate to these biases, see Cummings et al.

2-77
(forthcoming, ,Chapter III).

In short, existing reviews of the CVM suggest that bias

problems are not insurmountable, and that careful design of the

survey can minimize them in many cases. This points to the need

to carefully.consider the design of the survey that produces any

contingent valuation results. Of particular concern are the

tradeoffs faced in survey design. For instance, it may be

possible to reduce hypothetical bias by using more concrete

payment and delivery vehicles, but only at the cost of increasing

the chances of strategic behavior. The tradeoffs chosen in

designing a particular survey need to be explicitly recognized

and discussed.

2.5.2.2. Accuracy of Contingent Valuation

Aside from issues of bias, the basic question remains,

however: in a properly designed contingent valuation study, how

accurate are the values reported? In a sense, the question is

unanswerable, since the true values are unobservable. Several

types of evidence can suggest a range of accuracy.

First, as Tolley, Randall, et al. (p.63) point. out,

studies have found that contingent values are systematically

related to income, availability of substitute goods, and other

variables that economic theory suggests should be important.

This implies that the contingent market is to some extent similar

to an actual market and that the values reported are not random

but are reasonable subjects for economic analysis.

Second, a number of studies have compared the CVM to

alternative indirect market methods of valuing non-market goods.

Cummings et al. review these studies and stress that the results

can not establish the accuracy of the CVM. But: "Assuming that,

within the range of plus or minus SO%, value estimates derived

from indirect market methods include 'true' valuations by

individuals, these results suggest that CVM values may yield

'accurate' estimates of value in cases where individuals have had

some opportunity to make actual previous choices over that

commodity in a market framework."

Based on their comprehensive review of the methodology and

practice of contingent valuation, Cummings et al. suggest a range

of accuracy for carefully designed contingent valuation studies.

(These suggestions are linked to a set of Reference Operating

Conditions that the study must meet for the accuracy range to

apply.) At the least, "the method produces order of magnitude ----- -- -- ----se

estimates --but we think one can argue that error ranges are much

smaller." (p.279) At the best, "one might tentatively conclude

that, given the current state of the arts, the CVM is not likely

to be more accurate than plus or minus 50 percentofthe measured

valued." (p.123) This plus or minus 50 percent range is a

suggested reference accuracy, and though it is a somewhat

arbitrary figure it does seem reasonable.

2-78
2.5.3. Qplications ------mm- -- ------ of Contingent Valuation to Health --_ --------- -- -_____

2.5.3.1. Introduction

This section critiques three studies that use the

contingent valuation method to value health symptoms related to

air pollution. The first study by Loehman et al. (1979) values

symptoms linked to air pollution using a mail questionnaire of

the general public. The second study reviewed is Rowe and

Chestnut (1984). This study values a reduction in asthma

symptoms, using personal interviews of a group of individuals

suffering asthma. The third study is the contingent valuation

experiment described in Volume 3 of this report (Tolley, et al.

(1985)). This study includes four separate surveys valuing

different types and quantities of air pollution related symptoms,

using personal interviews of the general public.

2.5.3.2. Scope of the Review

At the outset, the limited scope of this section shouldbe

explained. In line with the overall purpose of Volume 2, the

focus is on empirical estimates of the value uf health. As a

result, no attempt is made to report and review all of the

findings of the studies in question. In particular, for our

purposes the values of health are best summarized by a simple

statistic such as a mean value for the sample. Other statistical

analysis, including the estimation of bid functions based on the

contingent valuation responses, are not reviewed, though they are

important parts of these studies. In addition, questions of

methodology and survey design are only addressed in the context

of evaluating the usefulness and accuracy of the value estimates

produced.

A second limitation in the scope of this review is that

several studies that use the contingent valuation method to value

changes inlair quality, including the health effects, are not

considered. These studies do not yield usable values of health

for various reasons. In two of them (Brookshire, et al. (1979),

and Loehman et al. (1981))., respondents were asked separately

about their values for the visibility and health effects of air

pollution, but it is not clear if people can meaningfully disentangle these effects. The values of health alone may be

overstated, reflecting part of the value of visibility, or

understated if part of the value of health is included in the

reported value of visibility.

A third study by Schulze et al. (1983) concentrates on

2-79
health effects of ozone, so it may not share the above problem.

It does share with the two studies previously mentioned another

problem of the definition of the product purchased in the

contingent market. In all three studies respondents were

provided with descriptions of the health effects likely to result

from air pollution levels, and then asked for their values for a

change in pollution levels. The descriptions are of the general

form: for a given level of pollution, some people (or a certain

percentage of people) experience these effects. Such a

description has multiple interpretations. A respondent could

identify the general population risk as his individual risk. So

if he is told that 50% of people will experience a symptom, he

views this as a 50% chance he will experience the symptom.

Another interpretation is that the information provided helps

remind the respondent of his experiences with air pollution. In

this case, the respondent will bid for a change based on his

prior subjective probability estimates of experiencing a symptom

given varying levels of pollution. Or, he may adjust his prior

beliefs on the basis of the information given. In either case,

the commodity the respondent is valuing is a change in risks

(probabilities of symptoms) that is unobservable to the

researcher.

These different interpretations of the effects of the

information provided mean that it is not clear if all respondents

were valuing the same good in these studies. More to the point

for the purposes of this section, it means that values of health

can not be inferred from these studies. To do so would require

numerous arbitrary assumptions concerning what we think the

respondents were thinking when they answered the questions.

2.5.3.3. Loehman,et al. (1979)

Study Design

The study by Loehman et al. (1979) concerns the benefits

of contro,lling sulfur oxides in Florida. A mail contingent

valuation survey was sent to 1,977 residents in that Tampa Bay

area, resulting in 432 returns. Willingness to pay questions

were asked about the following three groups of symptoms:

shortness of breath/chest pains; coughing/sneezing; head

congestion/eye/ear/throat irritations. Values were elicited for

minor and severe symptom days, which were defined briefly.

Respondents were asked to value one day, seven days, and ninety

days of relief. No mention was made of any specific underlying

disease, nor were causes such as air pollution mentioned. No

specific delivery vehicle, such as a pill, was employed, and a

simple, abstract payment vehicle-- "tell us how much you would

pay"--was chosen. The means of payment was a checklist, or

payment card, ranging from $0 to $1000 per year in ten

increments.

The Loehman et al. study design is similar to our seven

2-80
symptom survey described in Volume 3. In both cases a pure

health attribute approach was used.

carefully avoided

The Loehman et al. study

the introduction of redundant information in

its introductory letter, its symptom narrative and in its

delivery and payment vehicles.

of the Tolle'y et al. (1985)

One difference between the design

survey and the Loehman et al survey

is the large number (24) of similar willingness to pay questions

on the latter survey. The Tolley et al. surveys employed fewer

questions on any survey instrument in order to avoid taxing the

respondents' concentration and the extent of their information

and preference review. This problem might account for the

relatively low return rate (22 per cent) encountered by Loehman

et al. It also could imply a reduction in the accuracy of their

estimates of the value of health.

The major difference between Loehman et al. and the other

two contingent valuation studies reviewed below is that the

Loehman et al study used a mail questionnaire. The advantage to

using this approach is that the lower cost per survey completed

allows a larger sample size. There are several disadvantages.

An obvious question is whether the respondents are representative

of the general population. Loehman et al. test for this, and

find that the sample seems to be more or less representative, at

least in terms of standard demographic characteristics.

Another problem with using a mail survey is that in a

contingent valuation experiment there will be some protestors, or

people who either refuse to participate in the contingent market

or do not understand the nature of the exercise. In a personal

interview, follow-up questions and interviewer comments can help

identify respondents who are protestors. A mail questionnaire

gives no indication of the identity of protestors, except for the

bids themselves. Loehman et al. note the presence of bids from

respondents who gave values of $1000 (the highest amount on the

payment card). These bids were statistically outlyers, and the

respondents exhibited intransitivity of preferences. It seems

reasonable that these respondents were protestors. However, it

is also possible that these individuals simply had high values

for health. The limited information from a mail questionnaire

means this problem is difficult to resolve.

A final disadvantage of using a mail questionnaire is

that it requires the use of a payment card. Such a card lists

the possible amounts of people might be willing to pay, and the

respondents choose among the different amounts. Designing a card

that covers a wide range of low to high values and allows small

but important differences between values to be reported is

difficult. In addition, some have questioned whether such a card

elicits maximum willingness to pay responses. -------

Cummings et al.

(forthcoming) suggest that if a payment card is used, it should

be followed with iterative bidding, but this is not feasible in

the context of a mail questionnaire. These problems indicate

that the values from the Loehman et al. study may be inaccurate,

and in particular they may be under-estimates of the maximum

willingness to pay for health.

2-81
Results

Table 2-8 lists the median and mean bids found by

Loehman, et al. All bids are expressedinterms of 1984 dollars,

to insure comparability with other estimates of the value of

health discussed in this report. The bids were adjusted using

the Consumer Price Index, and were rounded to the nearest dollar.

The bids cover a fairly wide range. For one day of

relief, the lowest median bid is $4 for mild coughing/sneezing,

and the highest median bid is $18 for severe shortness of

breath/chest pains. However, the mean bids for 1 day of symptoms

are often an order of magnitude larger, ranging from $42 for mild

coughing/sneezing to $127 for severe shortness of breath/chest

pains. There is generally a smaller difference between median

and mean bids for 7 days of relief and 90 days of relief.

The large difference between median and mean bids results

from properties of the distribution of bids. As Loehman et al

describe it, the distribution is clearly not normal, but includes

a large number of relatively low bids, with a few bids in the

upper tail of the distribution. These bids were for $1000, the

highest bid possible, and represent the possible protestors

discussed above. The mean bids are much more sensitive to these

outlyers than are the medians, and so the means are much larger

than the medians.

In their analysis, Loehman et al use only the median

bids. One justification for this use is normative. They argue

that the median is "indicative of majority voting since it

indicates the bid which at least 50% of the population would

agree to pay..." (Loehman et al, 1979, p.232). Though this

majority voting criterion is certainly reasonable, it represents

an alternative to the standard methodology of applied welfare

economics, where programs are evaluated using the criterion of a

potential Pareto improvement. Using this criterion all

individuals' values are given equal weight, including the very

high values. It is possible that a program that represents a

potential Pareto improvement would not be favored by over 50% of

the population. Potentially, though, payments by gainers could

compensate the losers by enough that all would favor (or at worst

be indifferent to) the program. If this standard of applied

welfare economics is accepted, the correct summary statistic is

the mean, which puts equal weights on all, and not the median.

Loehman et al. also justify their use of median bids by

noting that the median is less likely to be biased due to the

outlyers. V.K. Smith explains how this problem could justify use

of median bids even if the potential Pareto improvement criterion

is accepted as relevant. If a distribution of individuals' true

2-82
values of health in a population is known, the mean value is the

correct summary statistic as explained above. Applying this

reasoning to a distribution of values resulting from a contingent

valuation experiment is not necessarily correct. To do so

requires the assumption that all contingent valuation responses

are judged as equally'good estimates of each individual's

willingness to pay. Arguments that have been made in the

contingent valuation literature for the use of the median

implicitly assume that not all responses to contingent valuation

questions are equally good estimates of each individual's

willingness to pay. In particular, there is a presumption that

very large or very small responses are more likely to have large

errors associated with them. Since the mean value is more

affected than the median, the mean would be a less robust

estimate of the "average person's" willingness to pay. In this

case, if outlyers are a problem, the median bid may be preferred.

Accepting the criterion of a potential Pareto improvement as

the relevant welfare guideline, the choice of using median or

mean values from a contingent valuation study depends upon the

informational content assumed for different responses. Reporting

median bids avoids overstating values due to the effect of very

high bids which may be inaccurate in the sense that they are not

a true reflection of willingness to pay. At the same .time,

legitimately high bids are also given little weight. In

addition, though the very high bids may be inaccurate, they

probably do indicate that these individuals are actually willing

to pay an amount higher than average. Finally, the argument is

symmetric with respect to low bids. While very low bids probably

do indicate that these individuals have lower than average

willingness to pay values, the true values may not be as low as

the values reported in the contingent valuation experiment.

To rigourously account for all of the considerations

discussed above requires a model of how people respond to

contingent valuation questions. In section 4.3 there is the

beginnings of such a model, but it does not allow any definite

conclusions to be made regarding the mean versus median question.

In practice, both mean and median values are important pieces of

evidence. Inferences of the informational content of very high

and very low bids can be drawn from careful consideration of the

study design and the distribution of bids found. For 'the Loehman

et al. results, the problems inherent in a mail survey and the

distribution of bids suggest that the high bids are not accurate

reflections ofwillingness to pay. Thus the medianmay be a more

robust summary statistic.

It is interesting to note the relationships between the

bids for 1 day, 7 days, and 90 days of relief found by Loehman et

al. Using mild coughing/sneezing as an example, bid for 1 day is

$4, while the bid for 7 days is $13. roughly three times as

large. The bid for 90 days is $37, about nine times as large as

the bid for 1 day. Roughly similar results are found for other

median bids. For mean bids the ratios are even smaller; the bid

for 7 days of relief from mild coughing/sneezing ($71) is less

2-83
than twice the bid for 1 day ($42), and the bid for 90 days

($138) is only about three times the 1 day bid.

Two explanations for these relationships are possible. The

marginal disutility from sickness (symptoms) could be diminishing

rapidly, so.that extra days of symptoms do not matter much and

the individual is-willing to pay increasingly less for relief

from the symptoms. This does not seem very plausible, especially

since decreasing marginal disutility from sickness implies

increasing marginal utility from health, which is not consistent

with the assumptions of economic theory. A second possibility is

that the respondents had trouble valuing large changes in health

because these changes were outside of their experiences. That

bids for unfamiliar commodities may be inaccurate has been

suggested by users of the contingent valuation method (see

Cummings, et al). This explanation seems to be more powerful in

explaining why bids for 90 days of relief (an unfamiliar

commodity to most people) are so smallcomparedto the bids for 1

day of relief(amore familiar commoditywithinthe range of most

people's experiences). It is less powerful in explaining the

ratio of bids for 1 day and 7 days of relief, since both seem to

be familiar experiences to most people.

2-84
m-s-- Table' 2-8 ---

w-e--- Contingent Values of Health (1984 $) --- ------ -- ------

Source: Loehman, et al (1979)

Sample Size - 432

Symptom Median Bid Mean Bid

-------_--------________________________-----.------------------~

1 day of:

--shortness of breath/

chest pains

mild 8 78

severe 18 127

-_ coughing/sneezing

mild 4 42

severe 11 73

--head congestion,

eye, ear, throat

irritation

mild 6 52

severe 13 85

7 days of:

--shortness of breath/

chest pains

mild 22 118

severe 57 218

--coughing/sneezing

mild 13 71

severe 32 116

--head congestion,

eye, ear, throat

irritation

mild 15

severe' . 33

66

129

(Table 'continued on next page)

2-85
Table 2-8 (Continued)

Symptom Median Bid Mean Bid

___------------_------------------------------------------------

90 days of

--Shortness of breath/

Chest pains

mild 56 233

severe 156 403

--Coughing/Sneezing

mild 37 138

severe 81 236

--Head Congestion,

Eye, Ear, Throat

Irritation

mild 40 145

severe 99 288

2-86
2.5.3.4. Rowe and Chestnut (1984)

Study Design

The study by Rowe and Chestnut(1984) provides estimates

of the value of a reduction in asthma days for people with

asthma. The economic research supplemented research underway at

the UCLA School of Medicine concerning the effects of air

pollution on asthmatics. The UCLA project included over 90

subjects from Glendora, California (in 1983); the general

questionnaire that included the contingent valuation questions

was completed by 64 adults, and 18 parents of children under 16

years of age. Of this total sample of 82, there was only one

refusal. After evaluation of the bids, including checking for

protestors and other respondents whose bids were judged to be

inaccurate on the bias of consistency checks, 65 bids were

retained. This relatively small sample is clearly not

representative of the general population since it involves only

asthmatics. This is arguably a strength, not a weakness, since

people with asthma are a group likely to be affected by pollution

who may value the change differently than the general population.

Unfortunately, the sample was not chosen so as to be

representative of asthmatics in general.

Contingent valuation bids were obtained by asking the

respondents: "If federal, state, or local governments set up

programs that could reduce pollens, dusts, air pollutants, and

other factors throughout this area that might reduce your (and

your household's) bad asthma days by half, but would cost you

increased tax dollars, what would be the maximum increase in --s---s --------

taxes each year that you and your household would be willing to

pay and still support such a program?" A number of aspects of

this contingent market deserve comment. First, the good or

commodity being bid on is a reduction by half of the respondent's

and his household's bad asthma days. Given the respondent's

experience with asthma and the earlier questions in the

questionnaire, it seems reasonable that the respondents

understood the commodity and by this point in the experiment had

prior valuation and choice experience with respect to consumption

levels of it. The major drawback of this definition of the

commodity is that it is different for each respondent. What

constitutes a "bad asthma day" is subjective, and since the

number of bad days varies across respondents, so does the number

of bad days removed implied by the 50 percent reduction.

Second, it was made clear that the reduction in asthma

days would be the result of a governmental program, and paid for

by an increase taxes. That is, relatively concrete vehicles for

the delivery of and payment for the good are used. Though this

makes the contingent market more realistic, the added realism is

purchased at the cost of increasing the possibility of problems

such as strategic bias or protestors (either at the idea of

increased taxes, or the impossibility of such a program). In

addition, experience in focus groups in Chicago showed that

2-87
mentioningthe environment as a cause of health .seemed to

distract the respondents from providing reasoned bids. This

problem may not have existed for the asthma patients, however,

since other results of the project showed that they had a good

understanding and accurate perceptions of the effects of

pollution on their conditions.

Third, an element of uncertainty is introduced into the

market, since it is stated that the program improving air quality

"might" reduce bad days by half. This wording raises

difficulties in interpreting the bids. Is one respondent bidding

a small amount because the reduction in asthma days is not worth

much to him, or because his subjective probability that the

program will work is relatively low? The extensive analysis of

the bids supports the former interpretation, but the issue can

not be entirely resolved.

Two more general problems of the structure of the

contingent market should be mentioned. First, there is the

problem of the bidding format. The Rowe and Chestnut study used

a payment card format. It was designed to eliminate some of the

problems associated with this format; they note that problems may

remain, however.

The second problem is the treatment of protest bids and

extreme values (either 0 bids or very large bids). The ideal is

to retain all bids that reflect the true value, no matter how

extreme, and to remove bids that do not. To be a useful bid, the

respondent must be willing to participate in the contingent

market, and fully understand the nature of the exercise. Rowe

and Chestnut carefully examine the zero bids, and subject bids to

a consistency check. This process necessarily involves some

rather ad hoc procedures, and is to a certain extent subjective.

It would be interesting to know how sensitive the bid results are

to the editing process. As mentioned earlier, this process

results in 17 of 82 bids being rejected, or roughly 20%.

Results

The results of the Rowe and Chestnut study relevant for

this review canbe very easily summarized. They found a meanbid

for a 50% reduction in bad asthma days (for 65 observations) of

$401 per year, with a standard deviation of $85. This is for an

average number of bad days reduced equal to 19. Thus, on average

a bad asthma day is worth about $21. Of course, this average

value can not in general be used to value a marginal change of 1

bad asthma day.

2-88
2.5.3.5. Tolley, et al (1985)

Study Design

Volume 3 of this report contains a detailed description of

the design of the Tolley et al. contingent valuation experiment,

and the considerations involved in this design. To summarize, the

experiment consist of four surveys valuing: 1) 1 day of relief

from 7 light symptoms such as coughing, etc.; 2) 30 days of

relief from these same 7 symptoms; 3) relief from mild and severe

angina (chest pain) given that the respondent already suffered

from 10 days of this symptoms; and4) relief frommild and severe

angina given that the respondent already suffered from 20 days of

this symptom. Separate surveys were used to keep the length of

the survey at a level where reasoned responses could be reached,

but respondents' patience and concentration were not over-taxed.

A total of 199 interviews were completed, roughly equally

divided between the four types of surveys. The surveys were

personal interviews of a randomly selected sample from Chicago

and Denver,

Of the total of 199 completed surveys, 23 surveys were

removed from the sample. Several criteria were used to determine

which responses to remove. First, protestors who refused to give

any bids were removed from the sample. Protestors are

distinguished from those who wished to bid zero. Zero bidders

were left in the sample on the grounds that the bids were felt to

be legitimate. A second group excluded from the sample were

those respondents who indicated that they would pay any amount

for the improvement in health, or exorbitantly high amounts (two

or three times their yearly income). The last group of

respondents removed from the sample were random bidders whose

bids bore no logical relationship to each other. Interviewer

comments were used in all cases to help identify individuals

unwilling or unable to participate in the contingent market. For

a more complete description of and rationale for the editing

process, see section 3.5.2 in Volume 3.

As described in Volume 3, a great deal of care was taken

in the creation of the contingent market. The contingent

commodities were described to the respondents, and the structure

of the survey encouraged respondents to think about the

commodities before bidding began. A form of iterative bidding

was used. Abstract payment vehicles and delivery vehicles were

chosen,. to avoid protests and to avoid distracting respondents

from giving reasoned values. Finally, interviewer comments and

analysis of the bids were used to identify protestors.

For the two surveys concerning the seven light symptoms, the

structure of the survey instrument first helps the respondent to

recall his own experience with these common symptoms, and then

establishes a standardized hypothetical product (relief from

symptoms) to be valued. As a result the respondent should be

2-89
familiar with the commodity of the contingent market, an

important prerequisite to obta.ining accurate value estimates.

The procedure described above could not be exactly followed.

for the two surveys concerning angina, since most respondents had

little or no-experience with this symptom. Standard questions on

health status help the respondent to begin to think about his or

her health and its importance. The contingent valuation section

begins with a general two paragraph introduction that asks the

respondent to imagine having mild or severe angina, and includes

a brief statement about the extent of an.gina in the United

States. The actual contingent valuation includes a description

by the interviewer of the specific symptoms to be valued, and a

card summarizing of this description is then handed to the

respondent. The complete survey instruments are reproduced in the

Appendix of Volume 3. This approach to survey structure was used

to minimize the problems associated with respondents being

unfamiliar with angina. While the value estimates resulting may

not be as accurate as for the more familiar seven symptoms, it is

felt that most respondents did give reasoned bids:

Results

Table 2-9 presents the values for symptoms, from the four

surveys conducted by Tolley et al. Part 1 of Table 2-9 presents

median and mean bids for relief from one additional day of seven

individual light symptomes, and two combinations of symptoms.

Part 2 of Table 2-9 presents the same statistics for relief from

thirty additional days of the same individual and combined

symptoms. Parts 3 and 4 of Table 2-9 present bids for relief

from angina. The number of additional days of angina, the

severity of the angina, and the endowment that respondents were

asked to assume described their situation are varied to provide a

range of values.

The median bids for relief from one additional day of the

seven light symptoms range from $11 for relief from a day of

coughing .to $20 for headaches. Mean bids are roughly two to

three times larger, ranging from $25.20 for a coughing day to

$50.28 for relief from a day of nausea. Relief from

combinations of three symptoms is more highly valued than relief

from one symptom alone, but is not the simple sum of the values

of the individual symptoms. For instance, a day of cough, throat

and sinus symptoms combined is valued at $65.60 The sum of the

bids for relief from these symptoms indvidually is $89.22.

For the Tolley et al. results the difference between the

median bids and the mean bids is substantially less than that

found for the Loehman et al. results. As described above, the

excessively large bids resulting from respondents who explicitly

or implicitly protested the contingent market were removed from

the Tolley et al. sample. This shows one advantage of the

personal interview structure compared to mail surveys:

interviewer comments can help identify protestors. Since all

2-90
responses were subject to the editing process, and the

distribution of bids shows'a smaller impact of the largest bids,

the mean seems to be the most robust summary statistic for this

sample. In other words, the assumption seems justified that all

responses, even the very large and very small bids, have roughly

equivalent informational content.

For relief from 30 days of the seven light symptoms, the

median bids range from $95 for 30 days of coughing to $135 for 30

days of sinus problems. Again, mean bids are usually about two

or three times larger than the medians, ranging from $166.50 for

30 days of coughing to $488.20 for 30 days of headaches. The

same relationship between the bids for combinations of symptoms

and the sum of the bids for relief from the individual symptoms

is found as in the one day survey. A combination of three

symptoms is valued more than any one symptom alone, but not as

much as the sum of the bids for the three individual symptoms.

Just as in the Loehman et al results, a somewhat surprising

relationship is found between the bids for different days of

relief. The mean bids for 30 days of relief from the light

symptoms are not 30 times larger than the mean bids for one day

of relief. The 30 day bids are closer to ten times the size of

the one day bids. Though these bids result from two different

samples of individuals, in terms of observable characteristics

the samples seemed similar. Another possible explanation is that

the results reflect diminishing marginal disutility from

sickness, but this explanation implies increasing marginal

utility from health which seems implausible. In addition, other

results from these surveys reported in Volume 3 support the more

standard relationship of increasing marginal disutility from

sickness. Finally, it could be argued that 30 days of sickness

are a more unfamiliar commodity to most individuals, so they are

under-valuing it. This possibility points to the continued need

for a formal model of how respondents react to contingent

valuation questions, since it is not obvious why bids for an

unfamiliar commodity would be systematically biased downwards.

The third survey conducted by Tolley et al. concerns the

value of relief from angina (chest pain), given an endowment of

up to 10 days of severe angina. Median bids range from $50 for

relief from 1 mild day given an endowment of 10 mild days, to

$200 for relief from 10 severe days given 10 severe days. The

mean bids are fairly close to the median bids, ranging from

$66.08 for relief from 1 mild day given 1 mild day, to $261.84

for 10 severe days given 10 severe days. For comparable

endowments, median and mean bids for mild days are always less

than bids for severe days, as would be expected. Comparing

across endowments, it is generally true that relief from a given

number of days of angina is valued more highly as the endowment

increases. This is consistent with increasing marginal

disutility of illness, and is the expected relationship.

The fourth survey also concerns angina, but the endowment

ranges up to 20 days of mild and severe angina. Median bids

2-91
range from $40 for relief from 1 mild day given 20 mild days, to

$200 for relief from 20 severe days given 20 severe days. Mean

bids show a larger difference between the value of 1 day and 20

days of angina. The mean bid for relief from 1 mild day given 1

mild day is $90.24, while the mean bid for 20 severe days given

20 severe days is $844.38. Again, as expected relief from severe

days of angina are valued more highly than relief from mild days.

However, comparing bids across endowments, the results do not

always support that increasing the endowment increases the bid

for a given number of days of relief. For example, the mean bid

for relief fromlsevere day givenlsevere day is $278.88, while

the meanbid for relief fromlsevere day given 20 severe days is

only 208.78 This difference may not be highly significant.

Closer examination of the bids reveals that some respondents bid

a large amount to be completely free of angina, while placing a

small value on a day at the margin given a large endowment.

Though this behavior is not consistent with increasing marginal

disutility of illness, it is not necessarily irrational.

Whether individuals with actual experience of angina would bid in

this way is an interesting and open question.

It is possible to compare the results of the two surveys on

angina in a few cases where identical commodities were valued by

the different samples of individuals. The mean bid for relief

from 1 mild day given 1 mild day is $66.08 for Survey 3 and

somewhat larger for Survey 4 at $90.24. A larger difference is

found for the only other case in which the surveys are directly

comparable. In Survey 3, the mean bid for relief from 1 severe

day given 1 severe day is $123.59, while in Survey 4 the meanbid

is $278.88. This larger mean bid in Survey 4 reflects the

influence of a few very high bidders who bida large amount to be

completely free of angina. In fact, the median bid from Survey 4

for relief from 1 severe day of angina given 1 severe day ($75)

is less than the median bid from Survey 3 ($100). These results

show the effect a few bids can have on the summary statistics,

and suggest that the values reported for relief from angina may

not be highly accurate.

2-92
Symptom

0

------a--

1 day of:

-- cough

-- sinus

-- throat

-- eyes

--

Table 2-9: Part 1

Contingent Values of Health

Source: Tolley, et al (1985)

Median

Bid

-- drowsiness

-- headaches

-- nausea

-- cough, throat,

and sinus

-- drowsiness,

headaches and

nausea

11

14

13

12.50

15

20

17.50

30.50

25 95.08

25.20

35.05

28.97

27.73

31.49

40.10

50.28

65.60

(Table continued on the next page)

2-93
Table 2-9: Part 2

Survey 2

Symptom Median

Bid

30 days of

-- cough

-w sinus

-- throat

-- eyes

-- drowsiness

-- headaches

-- nausea

-- cough, throat,

and sinus

-- drowsiness,

headaches and

nausea

95

135

100

100

100

132.50

100

200

300

Mean Bid

166.50

265.62

206.26

235.53

317.98

488.20

186.02

624.98

868.89

(Table continued on the next page)

2-94
Table 2-9: Part 3

Survey 3

Relief from

angina, given

endowment of

angina

--1 mild day

given 1 mild day

given 10 mild days

--1 severe day

given 1 severe day

given 10 severe days

--5 mild days

given 10 mild days

--5 severe days

given 10 severe days

--lo mild days

given 10 mild days

--lo severe days

given 10 severe days

Median

Bid

53 66.08

50 83.95

100

100

55

150

100

200

__

Mean Bid

123.59

144.74

96.18

192.90

154.36

261.84

(Table continued on next page)

2-95
Survey 4

Table 2-9: Part 4

Relief from Median Mean Bid

angina, given Bid

endowment of

angina

____--__--____-___--____________________--------------------

--1 mild day

given 1 mild day

given 20 mild days

--1 severe day

given 1 severe day

given 20 severe days

--lo mild days

given 20 mild days 100 287.63

--lo severe days

given 20 severe days 125 506.25

--20 mild days

given 20 mild days

--20 severe days

given 20 severe days

53

40

75

60

100

200

90.24

99.05

278.88

208.78

486.25

844.38

2-96
2.5.4. -------w--e Conclusions and Summary --- --we--

An assessment of the contingent valuation method suggests

that with careful design the resulting value estimates may be

fairly accurate. With this in mind, this section reviewed three

studies that applied the CVM to the problem of valuing health

effects related to air pollution: Loehman et al. (1979), Rowe

and Chestnut (1984), and Tolley et al. (1985). Each of these

studies seems to be carefully designed, though certain problems

are noted. As a result, the value estimates are probably as

accurate as any estimates based on contingent valuation; similar

to Cummings et al. (forthcoming), the reference accuracy may be

set at plus or minus 50 percent.

Wh.ile the health effects valued are not exactly the same,

certain comparisons can be made between the results of the three

studies. For instance, each of the studies implies a value for

one day of respiratory symptoms, though not always of the same

symptoms. From the Loehman et al. study, one day of of

coughing/sneezing has a mean value of $138 (mild day) or $236

(severe day). The Rowe and Chestnut study implies that relief

from one day of asthma symptoms is worth on average about $20.

The Tolley et al. study finds that relief from one day of

coughing, throat, and sinus problems has a mean value of $65.60.

These different values can be reconciled, to some extent.

First, the Rowe and Chestnut value is not a value for a marginal

day of relief, but an average value for one day, given an average

of 19 days of symptoms relieved. Thus, it is not really

comparable to the other estimates. The Loehman et al. and Tolley

et al. studies are more directly comparable. In general,

somewhat different values result. But comparing median bids

across the two studies, or comparing mean bids across the two

studies, the values do not seem to be necessarily inconsistent.

2.5.6. ----- Notes

1. For a review of these and other contingent valuation studies

concerned with the value of morbidity, see Chestnut and

Violette (1984).

2.5.7. --_------- References

1. Bishop, R..C. and Heberlein, T.A. Does Contingent Valuation

Work? in Cummings, et al. Valuing Public Goods: An

Assessment of the Contingent Valuation Method, pp. 149-179,

forthcoming.

2. Brookshire, D.S., R.C. d'Arge, W.D. Schulze, and M.A.

Thayer, Methods Development for Assessing Air Pollution

2-97
Control Benefits, Vol. II: Experiments in Valuing NonMarket Goods: A Case Study of Alternative Benefit Measures

of Air Pollution Control in the South Coast Air Basin of

Southern California. Prepared for U.S. Environmental

Protection Agency, Wash. D.C., 1979.

3. Chestnut, L.G., and D.M. Violette, Estimates of Willingness

to Pay for Pollution-Induced Changes in Morbidity: A

Critique for Benefit-Cost Analysis of Pollution Regulation.

Prepared for U.S. Environmental Protection Agency, Wash.

D.C.,September, 1984.

4. Cummings, R.G., D.S. Brookshire, and W.D. Schulze, Valuing

Environmental Goods: A State of the Arts Assessment of the

Contingent Valuation Method. (forthcoming)

5. Loehman, E.T., S.V. Berg, A.A. Arroyo, R.A. Hedinger, J.M.

Schwartz, M.E. Shaw, R.W. Fahien, V.H. De, R.P. Fishe,

D.E.Rio, W.F. Rossley, and A.E.S. Green, "Distribution

Analysis of Regional Benefits and Cost of Air Quality

Control,'" Journal of Environmental Economics and Management

6 (1979): 222-243.

6. Loehman, E.T., D. Boldt, and K. Chaikin, Measuring the

Benefits of Air Qualtity Improvements in the San Francisco

Bay Area. Draft Final Report prepared for the U.S.

Environmental Protection Agency, Wash. D.C., 1981.

7. Rowe, R.D. and L.G. Chestnut, Valuing Changes in Morbidity:

WTP versus CO1 Measures, Energy and Resources Consultants,

Inc., December 1984.

8. Tolley, G.S., A. Randall, et al, Establishing and Valuing the

Effects of Improved Visibility in the Eastern United States,

Report prepared for the U.S. Environmental Protection Agency,

Wash. D.C., 1984.

2-98
2.6. COMPARING COST OF ILLNESS AND CONTINGENT VALUATION

2.6.1. ------------ Introduction

The cost of illness (COI) approach and contingent

valuation (CV) are two important methods that allow a dollar

value to be placed on a change in morbidity or sickness. A

direct comparison of values based on these methods is undertaken

in this section. This comparison is especially interesting

because the methods are in some sense complementary. The cost of

illness approach, focusing on medical expenditures and foregone

earnings, uses widely available data and straight-forward

empirical techniques, so it is generally accepted on a practical

level. However, there is no strong theoretical basis for using

CO1 values in benefit cost analysis. That is, there are serious

questions whether a CO1 value associated with a given change in

morbidity will be close to what an individual would be willing to

pay for that change. In contrast, contingent valuation

experiments can be designed to directly estimate what an

individual would be willing to pay for a certain change in

morbidity. So CV values are estimates of the conceptually

correct benefit measures for benefit-cost analysis under

certainty. Unfortunately, the proper design of CV experiments is

difficult and still Controversial, and many economists tend to be

skeptical of the actual values given by individuals in a CV

experiment. On a practical level, CO1 values are often judged

superior to CV values, while on a theoretical or conceptual

level, CV values are preferred.

Due to the perceived practical advantages of the cost of

illness approach, recent theoretical work has investigated the

relationship between CO1 values and an individual's true

willingness to pay (WTP) for changes in morbidity. Harrington

and Portney's (forthcoming) theoretical analysis supports the

conclusion that a CO1 value is a lower boundtothe true WTP, for

the certainty case. The more general model presented in section

2.2 also implies that under plausible conditions, CO1 < WTP under

certainty; the model also allows the analysis to be extended to

the case of uncertainty.

CV studies of the value of morbidity have considered changes

in health status that occur with certainty. This seems justified

since the costs of adding uncertainty seem large in light of the

problems encountered in surveys that deal with concepts of

uncertainty, and the benefits of adding uncertainty in the

context of non-serious morbidity may be small. In this section

only the relationship between willingness to pay and cost of

illness for certain changes can be directly addressed.

The empirical evidence presented in this section is used to

test the hypothesis that'the cost of illness values are lower

bounds to the true willingness to pay values. Values reported in

2-99
CV experiments are used to represent the true WTP values for a

change from being certainly sick to being certainly well. On the

assumption that the CV values are reasonable proxies for true

WTP, the empirical results support the hypothesis that CO1 < WTP.

Alternatively, the fact that this reasonable relationship holds

between COI'and CV reported WTP can be seen as additional

evidence on the usefulness and reliability of contingent

valuation methods.

In section 2.6.2, previous work comparing cost of illness

and contingent valuation is reviewed. In'section 2.6.3, the

results of a new contingent valuation experiment are presented,

to test the hypothesized relationship. The analysis is extended

to a preliminary discussion of the relationship of CO1 and WTP

values under certainty, and the amount an individual would be

willing to pay for a change in health risks. No direct evidence

is available on willingness to pay for morbidity risks, but the

analysis of Section 2.2 suggests an approximation from the

evidence on certainty values is possible. Sect.ion 2.6.4 is a

conclusion.

2.6.2. -------- Previous Work Comparing ---- --- ---- CO1 --- and CV --- --

Two contingent valuation studies on the value of morbidity

contain some evidence on the relationship between cost of illness

values and CV values. 1 The first study, reported in Loehman, et

al. (19791, estimated median willingness to pay bids for

reductions in air pollution-related symptoms. They note that the

bids "are probably low compared to out-of-pocket costs of

illness." As an example, the income loss per day for a person

with an average income would be $65, while the highest median

reported for 1 day of relief from severe symptoms (shortness of

breath) is $10.92. Including the value of medical expenditures

would cause CO1 to exceed the CV bid by a larger amount. The

differnce may be in part due to paid sick leave and medical

insurance causing out-of-pocket expenses to be low. Another

problem i.+ the use of median CV bids. In order to avoid overstating WTP because of the influence of a few very large bids on

the means, they instead used the much smaller medians. This

might have resulted in an under-statement of WTP, however, which

might explain why the CV bids are small relative to reasonable

CO1 values. At least, the median CV bids should be compared to

median CO1 values. In any case, Loehman, et ai do not collect

the data that would allow a direct comparison of individual's CV

bids and their experienced or expected costs of illness. Thus,

their results seem to be only a weak indication that WTP is less

than COI; i.e. this is weak evidence against the hypothesis that

CO1 is a lower bound to WTP.

A second CV study, by Rowe and Chestnut (1984) on the

value of asthma, is more suitable to a direct comparison of CV

bids representing WTP, and the cost of illness. The first body

of evidence on WTP compared to CO1 is the respondents' rankings

2-100
of the importance of the benefits they might receive from reduced

asthma. Based on statistical analysis of the rankings, Rowe and

Chestnut conclude that discomfort and effects on leisure and

recreation activities, which are part of WTP but not part of COI,

clearly ranked above medical costs and work lost, which are the

only components of WTP that a CO1 value includes. So according

to these rankings, CO1 estimates do not include the most

important benefits of reduced morbidity. This indicates that WTP

should therefore exceed COI.

The second body of evidence from the Rowe and Chestnut

study is a comparison of the total WTP bid and a constructed CO1

value. This method reported yields a ratio of WTP/COI of 1.6,

supporting the hypothesis that WTP is greater than COI. Other

approaches to measuring this ratio examined in their larger study

suggest a ratio as high as 3.7.

Unfortunately, the data collected do not include foregone

earnings, so to construct the CO1 value Rowe and Chestnut had to

assume that the earnings foregone were equal to the medical

costs. The assumption is justified on the grounds that the

respondents' rankings of the importance of foregone earnings and

medical expenditures were nearly identical. The comparison of

WTP to CO1 does not seen sensitive to any inaccuracies inherent

in this assumption.

Another problem in the construction of the CO1 value is

that it includes only variable medical expenditures, such as on

medicines or doctor visits. The asthmatics interviewed also had

significant fixed cost expenses on one-time goods such as

Intermittent Positive Pressure Breathing Machines. From Rowe and

Chestnut's Table 1, the total (household) fixed cost expenses

were $713, compared to total (household) variable expenses per

year of $528. Clearly, the entire sum of fixed costs

expenditures should not be compared to the willingness to pay for

an improvement in morbidity. However, since the improvement

would change individuals' marginal decisions on the purchase of a

one-time good, ideally some (unknown) portion of the fixed

expenses would be included in a CO1 value. It does not seem

likely that doing so would change the result that WTP is greater

than COI.

In general, while the Rowe and Chestnut study is not the

ideal test of the hypothesis that WTP exceeds COI, it does offer

strong support of that relationship. The final caveat is that

the study involved only a relatively small sample of individuals

with a chronic condition, asthma, and may not be relevant for the

general population.

Comparisons of CO1 and CV values from the Loehman et al.

(1979) and Rowe and Chestnut (1984) studies are thus somewhat

inconclusive. The first study contains very weak evidence

against the hypothesis that WTP exceeds COI. The second study

contains much stronger evidence that supports the hypothesis, but

problems with the study may limit its applicability.

2-101
2.6.3. -mmCornParing -e-v ---CO1 and CV --- -- -- New Results --- -------

The contingent valuation study described in detail

elsewhere in-this report was designed to collect the necessary

data for a direct comparison of CV willingness to pay bids for

changes in health status with certainty and experienced cost of

illness. Only the surveys on seven light symptoms (coughing

spells, stuffed up sinuses, throat congestion, itching eyes,

drowsiness, headaches and nausea) are used for this comparative

analysis. The surveys on angina couldnotbe usedbecause few if

any of the respondents had experience with angina and its related

cost of illness.

The total sample of the seven light symptom surveys used

in the analysis was 131, using door- to-door and mall-intercept

interview methods. Out of this sample, 9 observations were

unusuable because they were incomplete. Because of the limited

scope of the sample, we view this empirical study as

illustrative.

Table 2-10 compares the mean WTP and private CO1 for each

of the seven symptoms in the contingent valuation survey. The

comparison is made among those who have experienced the symptom

in the previous year, i.e., those for whom we have CO1 data. The

private CO1 is calculated consistent with the prevailing measure

in the CO1 literature. It is the expenditures on medicine and

doctor visits less any insurance payments plus any lost earnings.

Both the individual WTP and CO1 measures are expressed on a daily

2 basis.

Out of the entire sample of 122 individuals, the

subsamples of those who had experienced the various symptoms in

the previous year ranged in size from 6 for drowsiness to 48 for

headaches. Within each of these subsamples, the mean WTP always

exceeded the mean cost of illness. The last column of Table 2-10

indicates that in 5 of the 7 cases, the dif.ferences were

significant at the .05 level in a one tailed test.

Another way to test the equality of the private CO1 and

the WTP is through the use of a nonparametric sign test (see Hoe1

(1971, pp.310-315)). This type of test is less sensitive to

extreme WTP or CO1 values than is the t-test. For the sign test

the 192 WTP-CO1 pairs across all seven symptoms are compared. In

174 cases, the WTP exceeds private COI. If the WTP-CO1 pairs had

in fact come from the same distribution, we would expect that in

only 96 cases would WTP exceed COI. We can then test whether 174

is significantly greater than 96 by3 using the binomial

approximation to the normal distribution. The resulting value

of the test statistic is 11.26 which is significantly different

from zero at a .OOl level of significance, further adding to the

empirical evidence that WTP exceeds COI.

2-102
Symptom

TABLE 2-10

Willingness to Pay and Private Cost

of Illness Comparisons of Means

Sample Mean Daily Mean Daily tsize (a) Willingness Private Costs value(d)

to pay (b) of Illness (c)

Coughing Spells 27 $105.34

Stuff Up Sinuses 43 38.84

Throat Congestion 24 43.93

Itching Eyes 16 172.23

Heavy Drowsiness 6 173.89

Headaches 48 173.21

Nausea 18 91.24

$11.29 2.12*

6.79 2.22*

14.27 1.59

14.56 1.24

21.50 2.57*

3.33 2.07*

2.36 2.03*

a

Only those experiencing the symptom are included

b

Willingness to pay to avoid one extra day of the symptom.

C

Calculated as expenditures on doctor visits and medicine net of

insurance reimbursements plus lost earnings, expressed on a daily

basis.

d

Test of the null hypothesis that willfngness to pay is less than

or equal to private costs of illness. *Indicates hypothesis

rejected at 0.05 level of significance in a one-tailed test.

2-103
There are two types of additional evidence which support

the finding that WTP exceeds COI. First, we asked individuals to

rank the reasons for their values for symptom relief. Focus

group feedback led to development of a five-item list which

covered most reasons. The reasons and the percentage of the 122

respondents who ranked the reason as the most important are:

comfort (67%), loss of work at home (6%), loss of work away from

home (12%), loss of recreation (2%), reduce medical expenses

(11%) and other (2%). So as in the Rowe and Chestnut (1984)

study, the components of the value of health included in CO1 are

ranked as less important than the components CO1 omits.

We also estimated simple

regressions of WTP on the private

orditary least squares

COI. In each case the

intercept is positive, and in most cases is

different from zero.

significantly

different from zero.

The slope term is never significantly

However, in the cases in which it

approaches significance, it is positive. Thus, the regression

results are consistent with the above finding that in general WTP

exceeds COI, although there does not appear to be any strong

tendency for the two to move together. This suggests it is not

possible to predict WTP based on COI. So while WTP/COI ratios

could be computed based on the means reported in Table 2-22,

yielding ratios of about 3 to over 50, the regression results

suggest that these ratios are not particularly meaningful.

Implicit in our WTP-CO1 comparison is the assumption that

the symptoms which people experienced in the previous year are

the same as those which they are bidding on in the contingent

valuation experiments. For the light symptoms included in the

survey the differences are rather inconsequential. When the

samples are limited to those who reported that their symptoms

were the same, not worse or less severe than the contingent

symptoms, the mean of WTP is still greater than the mean of CO1

for each symptom and although the dollar differences are greater

for four of the seven symptoms only two of the t-values are

significant at the .05 level due to the smaller sample sizes.

The nonparametric sign test yielded a test statistic of 8.73 and

the regression results are similar to those described above.

Our empirical evidence suggests that the private COI,

defined excluding time lost from consumption is less than WTP.

Is it the exclusion of these time expenditures which is driving

the result? In order to investigate this question we use other

information available from our contingent valuation survey to

construct an expanded CO1 measure which can then be compared to

the WTP values. This measure is the cost of medicine and doctor

visits net of insurance reimbursements plus the value of time

lost

%

rom any activity (e.g. market, work, school, work at

home). This increases the measured CO1 is more compatible with

theoretical models of COI. A comparison of the mean CO1 and WTP

for the various symptoms indicates that WTP is greater than CO1

in six of seven cases (the exception is throat congestion),

although the significance .levels of the t-statistics are lower

than before (they range from -.165 to 2.08). The nonparametric

2-104
test produces a test statistics of 5.48, which is again

significant at the .OOl level, indicating WTP > COI. Regressions

explaining WTP again produce positive (although smaller) and

mostly significant constant terms and insignificant CO1

coefficients. So overall, the exclusion of lost consumption time

does not appear to be the reason for our earlier result. Our

empirical results are consistent with the hypothesis that

consumer surplus exceeds the private COI, whether or not the

value of lost consumption time is included. It should be noted,

though, that our earlier measure, excluding the value of lost

consumption time, is more consistent with that used in CO1

studies.

The next step is to generalize our results to the

relationship between willingness to pay for a change in morbidity

risks and the expected COI. From the theoretical model of

Section 2.2, if an exogenous change which lowers the probability

of contracting an illness causes individuals to reduce their

preventive expenditures (that is, if dX/dE is negative), then

willingness to pay for a change in risks exceed's expected CS.

This is true since individuals would also be willing to pay their

preventive expenditure savings to avoid increases in health

risks. While our survey contains no direct evidence on the sign

of dX/dE fortunately

Individual; are

it contains some indirect evidence.

asked whether they have made various defensive

expenditures for health reasons: whether they have purchased air

conditioners, air purifiers, humidifiers for their home or car or

made other preventive expenditures. Nontrivial proportions of

the full sample have made some type of preventive expenditure.

But more interesting are the differences between those who have

and have not experienced at

symptoms. 7

least one of the seven light

While the percentages of the two groups are almost

equal for the purchase of humidifiers, those who have experienced

at least one of the seven symptoms are more likely to have made

expenditures in the other three categories than those who have

not. The difference is most pronounced for air conditioners. No

one in the group not experiencing any symptoms purchased an air

conditioner for health reasons but 19 of those having at least

one of the, seven symptoms did so.

What does this pattern of preventive expenditures tell us

about the sign of dX/dE? The pattern is consistent with a

negative dX/dE in the following way. Assume that those having

experienced the symptoms also experience worse exogenous

environmental conditions. This results in a higher probability

of experiencing the symptom. In looking across the sample, we

observe an increase in the quality of the environment(dE > 0)in

moving from those who have experienced at last one of the

symptoms to those who have not. The resulting change in

preventive expenditures then appears to be negative. It should

be stressed that the above explanation is only consistent with

dX/dE < 0. The data in the survey do not allow for a strict test

of hypothesis.

However, if it is true that dX/dE < 0, then our empirical

2-105
results are also consistent with willingness to pay for a change

in morbidity risks being greater than the expected COI. This

allows us to make statements about our theoretical model with

uncertainty from our empirical results, which by practical

necessity are couched in terms of certainty, and yield only

estimates of,willingness to pay under certainty, in other words,

an estimate of consumer surplus (CS).

One final illustration will help show the usefulness of

our empirical consumer surplus estimates. From the theoretical

model, it is plausible that the expected change in consumer

surplus is a lower bound on willingness to pay for a change in

health risks. Since the contingent valuation experiment measures

cs, if we assume some value for the change in probabilities of

becoming sick, we canestimate a lower bound for the value of the

reduction of health risks. For example, in Table 2-10 we report

that among those having experienced coughing spells in the

previous year, the mean CS for avoiding one extra day of cough

with certainty is $105.34. These individuals had on average

approximately 48 days of coughing spells in the previous year.

If we assume that the probability of having a coughing spell on

any given day is constant throughout the year, the mean

individual faces approximately a . 13 probability of having a

coughing spell each day. A lower bound estimate of the

willingness to pay for a 10% reduction in the risk of a coughing

spell on any given day for the mean individual is simply

- CS dH/dE or $105.34 x .013 - $1.37. The willingness to pay for

a whole year's worth of 10% reductions is $1.37 x 365 - $500.05.

Lower bounds on the values of changes in the risks of the other

symptoms can be similarly calculated. It should be stressed,

however, that our lower bound estimates, while useful for

comparisons among approaches, should be used for policy purposes

with caution. Our small sample is probably not representative of

the entire U.S. population. In addition, it should be recalled

that the contingent valuation experiment contained no direct

evidence on the value of morbidity risks, and the lower bound

estimates depend upon the theoretical model used in section 2.2.

2.6.4. --------e-s Conclusions

Our empirical work provides evidence on WTP and CO1 for

seven light symptoms in the certainty case: coughing spells,

stuffed up sinuses, throat congestion, itching eyes, heavy

drowsiness, headache, and nausea. The WTP values that are

obtained are equivalent to consumer surpluses. The results

suggest that WTP exceeds COI, but there is no strong indication

that WTP and CO1 move together in any systematic fashion.

Assuming that exogenous changes affecting health risks reduce

preventive expenditures, our results also imply that the WTP for

reduction in health risks which arises from our uncertainty based

model exceeds expected COI. We then provide an illustrative

lower bound estimate of the value of a change in health risks

from our contingent valuation survey.

2-106
The results of the new empirical work thus tend to confirm

Rowe and Chestnut's (1984) preliminary results that WTP exceeds

COI. It should be noted that this relationship is also found in

the experimental mail survey completed (see Section 3.7); but the

results are for a very small sample. So there is a growing body

of evidence that suggests contingent valuation responses on WTP

exceed COI, as predicted by several theoretical models. The

major limitation is the small sample sizes of the studies.

2.6.5. --------- Footnotes

1. Th.ese studies are described in greater detail in section 2.5.

2. The contingent valuation experiments were conducted for both

one-day and thirty-day changes in the experience of the various

systems. Implicit in the normalization to one-day changes is the

assumption of constant marginal costs in the case of cost of

illness and constant marginal utility in the case of willingness

to pay.

3. The standard deviation for calculating the normal

distribution test statistic is constructed under the null

hypothesis that the WTP - CO1 pairs come from the same

distribution. In this case the probability that WTP > CO1 is l/2

and the standard deviation for the binomial approximation to the

normal distribution is 192 x l/2 x l/2 - 6.93.

4. These and other results not reported in the paper are

available upon request.

5. A final piece of corroborating evidence is contained in the

survey. Individuals were asked how much they would be willing to

pay to avoid all of the symptoms they had experienced in the

previous year, Of the 46 individuals who did not experience

symptoms in combinations with one another, 41 had WTP > COI,

yielding a nonparametric sign test statistic of 5.3, which is

highly significant. The mean WTP greatly exceeded the mean CO1

and a simple regression yielded results similar to those

described previously.

6. The value of time lost from market or nonmarket activity is

measured by multiplying the number of days lost by the daily wage

(hourly wage x 8). This reduces the sample somewhat since not

everyone in the sample worked in the previous year and thus

reported a wage rate. We also expanded the definition of cost of

illness even further to include days of market and nonmarket

activity "hindered." This cost of illness measure is the same as

above except that'it also includes the number of days hindered

multiplied by one-half the daily wage. The means test, sign

2-107
tests and regressions were all recalculated and the results are

very similar to those described for the first expanded cost of

illness measure.

7. The proportions of the full sample having made various

preventive expenditures, and the proportions among those who have

and have not experienced at least one of the seven light symptoms

are as follows:

Preventive

Expenditure

Air Conditioner

Air Purifier

Humidifier .311 .318

Other .074 .056 .078

Full

Sample

.151

No

Symptoms

.ooo

.llO .044 .126

One or more

Symptoms

.188

.309

2-108
2.6.6. -_------es References

1. Harrington, W. and P.R. Portney, "Valuing the Benefits of

Improved Human Health," Journal of Urban Economics,

forthcoming.

Hoel, Paul G. Introduction to Mathematical Statistics, 4th

ed. (New York: John Wiley and Sons, Inc), 1971.

Loehman, E.T., S.V. Berg, A.A. Arroyo, R.A. Hedinger, J.M.

Schwartz, M.E. Shaw, R.W. Fahien, V.H. De, R.P. Fishe,

D.E.Rio, W.F. Rossley, and A.E.S. Green, "Distribution

Analysis of Regional Benefits and Cost of Air Quality

Control," Journal of Environmental Economics and Management

6 (1979): 222-243.

Rowe, R.D. and L.G. Chestnut, Valuing Changes in Morbidity:

WTP versus CO1 Measures, Energy and Resources Consultants,

Inc., December 1984.

2-109
2.7. HOUSEHOLD PRODUCTION OF HEALTH AND AVERTING BEHAVIOR

2.7.1. Introduction

Following Grossman (1972), economic analyis of health has

usually taken place in the context of household production

models. In these models, the individual produces the commodity

health by combining his own time and effort with purchased goods

such as medical care, diet, and so on. So in effect, health is

partially under the control of the individual, that is, it is

partly endogeneous. It may also be affected by exogeneous

factors the individual can not control, including environmental

quality.

Some recent theoretical and empirical work has used this

framework to derive expressions for what an individual would be

willing to pay for an exogeneous improvement in environmental

quality. The theoretical studies, such as the model developed in

section 2.2 and the references therein, investigate how the

conceptually correct willingness to pay measure will be related

to observable quantities namely the cost of illness

preventive expenditures (averting behavior).

and

Two empirical studies have taken the analyis further and

attempt to estimate willingness to pay directly. Gerking and

Stanley (1984) estimate willingness to pay for health risks

related to ozone exposure, and Cropper (1981) estimates

willingness to pay for health risks related to an index of air

pollutants. In sections 2.7.2 and 2.7.3 below these studies are

reviewed to investigate the usefulness and comparability of their

empirical estimates of the value of health. Section 2.7.4 is a

conclusion.

2.7.2. -e---s Gerking and Stanley --- ------ ---- 119841

The Gerking and Stanley study formulates a household

production model where environmental quality enters as a factor

in the production of health - which is in preferences, and which

affects the number of days sick. Thus the willingness to pay

(WTP) for an environmental quality imporvement can be derived:

WTP-dY/dAl(dU=O) - -Ha(S,A,D)/Hs(S,A,D)

where H is a multidimensionsl health production function, S is

averting activity -- in this case visits to a doctor -- and D

represents individual characteristics which parameterize individual productivities of S and A in producing H; for example, D

will include the existence and length of a chronic health

condition. Given that the assumptions of the implicit function

theorem hold, H-H(S,A,D) may be expressed as F(H,A,D), and thus:

Sa - -Fa/Fs - -(Fa/Fh)/(Fs/Fh) - -Ha/Hs.

Gerking and Stanley measure dS(A,D)/dA using a cross2-110
sectional survey of 2,594 households in St. Louis, Missouri, over

the years 1977-1980, which is combined with air quality data from

th.e Regional Air Pollution Study matched to each data point.

Because two of the independent variables in the regression - -

the existence and length of the chronic condition - - are

determined under the formulations of the model simultaneously

with the health decision, a two-stage logit procedure is

followed; the health variables are regressed on the other

explanatory variables, and from this, predicted values are

entered into the final logit regression.

Of the four pollutants considered in the model--ozone,

sulfur dioxides, total suspended particulates, and nitrous

oxides-- only ozone has a coefficient significantly different from

0, at the 1 percent level of significance. None of the other

pollutants are significant at the 10 percent level. By

multiplying this coefficient by the mean cost of a medical visit

and by a posited change in ozone levels, Gerking and Stanley

calculate the change in new first medical visit expenses due to a

30 percent reduction in ambient ozone levels. The reduction in

expenditures range from $18.45 to $24.45 per capita, annually.

As a result of the' order of their two stage estimation

process Gerking and Stanley do not directly estimate the effects

of ozone onhealth, so it is impossible to specifywhatchange in

health results from a given ozone reduction. Thus, these values

of WTP for an ozone reduction do not unambiguously imply a value

for WTP for health. However, Gerking and Stanley do suggest that

it might be reasonable to assume that each medical visit is

associated with a day of restricted activity due to illness. If

this is true, the value of preventing a restricted activity day

is equal to the full price of the medical visit, which they

estimated at about $40.

Another approach is to use an independent estimate of the

effect of ozone on health, and calculate what change in health

individuals are purchasing when they purchase a given change in

ozone. Portney and Mullahy (forthcoming) present a range of

estimated effects of ozone on health. When combined with the

Gerking and Stanley values for a 30 percent reduction in ozone,

these estimates imply values not inconsistent with the $40 per

restricted activity day value above.

Two problems noted by Gerking and Stanley that may affect

the robustness of this study are the choice of the dependent

variable, and the possible sample selection bias created by the

use of a relatively small subset of the entire sample. First,

whether or not an individual has ever visited a doctor within a

year just does not seem very sensitive to the particular health

care needs created by high ozone levles. It does not capture

additional medical trips made by those already visiting doctors

for other reasons, and similarly, does not reflect the intensity

of care related to a particulate ozone- related health problem.

Second, because the model is formulated using the full price of

medical care - which equals the direct price of medical care plus

2-111
the time cost of receiving such care,

information to value time suggests

the need for wage

that only the 824 households

who list their primary occupation as employed, and who had

reported wage date, be included in the regressions. If employees

experience different exposures to air pollution levels than those

not employed.- they may live in an air-conditioned office, or if

employees face different medical cost structures - they have

company-provided insurance, the WTP calculated from an employee

regression may not be generalizable to the population at large.

Gerking and Stanley do report, however, that regression results

run on the full sample do not differ much from the subsample

regression.

2.7.3. --- -- Cropper 119811 --__

Cropper postulates a dynamic health capital model in which

pollutants affect health expenditures only through wealth

maximization. Pollution increases the rate of health capital

decay - changing the margin between the net rate of return on

health capital and other investment goods, and increases the

number of days ill. But because neither the pollutant nor health

is in preferences, the consumer optimization problem can be

formulated as a two stage maximum; the individual first chooses a

schedule of health to maximize the present value of life-time

wealth, and then uses capital markets to shift consumption over

time so a s to maximize utility.

pollutant level in some period t,

For a small change in the

Cropper defines the WTP as:

WTP - (w(dS/dP)p + b(dI/dP>P)e-rt

where w is the wage rate, S the number of sick days, P the level

of pollution, b the costs of a unit of health investment, I the

extent of health investment, and 1: the discount rate. The first

term represents costs of illness(COI), the second the change in

health investment expenditures.

In the course of working through the dynamic wealth

maximization, Cropper makes three restrictive assumptions which

allow the WTP expression to be simplified considerably; the

relationships between the pollutant level and the depreciation

rate, and between health status and days ill, are assumed to be

of constant elasticity, and the health production function is

defined as constant returns to scale. Given these assumptions,

it can be shown that the change in averting expenditures exactly

equals the CO1 costs; the first order conditions for the wealth

maximization insure that the marginal costs of sickness and

health investment be equated, but, given the constant returns-toscale-- which insures constant prices- -and the constant elasticity

relationships, the equilibrium margins are constant irrespective

of the scale, and hence total costs are also equated. Thus to

calculate the WTP one merely needs to calculate CO1 and multiply

by two, or, to calculate the change in averting expenditures, one

just needs to measure the COI.

2-112
Cropper illustrates her analysis by calculating CO1 and WTP

from Michigan Panel Study of Income Dynamics data. Given the

estimated elasticity of sick time with respect to pollution, an

average personinthe1976 sample earning $6.00perhourwouldbe

willing to pay $7.20 annually for a 10 percent reduction in the

mean of sulfur dioxide.

Since WTP is always twice the foregone earnings in this

model, it is also possible to say that this average individual

would be willing to pay $96 to avoid the loss of an eight hour

work day. Putting this in 1984 dollars implies a value of $176

per work loss day.

2.7.4. ----------- Conclusions

In this section, studies by Gerking and Stanley (1984) and

Cropper (1981) are reviewed. These studies attempt to estimate

what an individual would be willing to pay for an improvement in

air quality related to health effects only. The implied values

for health are about $40 for a day of restricted activity from

the Gerking and Stanley study, and $176 for a work loss day in

the Cropper study. Since a work loss day is a more severe effect

than a day of restricted activity (as defined in these studies),

it is notunexpectedthatthe Cropper estimate is larger than the

Gerking and Stanley estimate. The magnitude of the difference

does seem large. However, due to the limitations of these

studies noted by the authors, these value estimates are probably

best described as illustrative of the order of magnitude of the

value of health. In this context, the two studies do not produce

inconsistent results.

2.7.5. --_------- References

1.

2.

3.

4.

Cropper, M. Measuring the Benefits from Reduced Morbidity.

American Economic Review, 71:235-240, 1981.

Gerking, Shelby, and Linda Stanley. "An Economic Analysis

of Air Pollution and Health: The Case of St. Louis."

(Mimeographed). University of Wyoming, May 1984.

Gerking, Shelby, L. Stanley and W. Weirick. AnEconomic

Analysis of Air Pollution and Health: The Case of St. Louis.

U.S. Environmental Protection Agency, Office of Policy and

Resource Management, Washington, D.C., 1983.

Grossman, M. "On the Concept of Health Capital and the

Demand for Health", Journal of Political Economy, 80 (March/

April 1972): 223-255.

2-113
5. Portney, P.R. and J. Mullahy. "Urban Air Quality and Acute

Respiratory Illness." Journal of Urban Economics,

forthcoming.

2-114
2.8. PROPERTY VALUES AND THE VALUE OF HEALTH

2.8.1. --m--m------ Introduction

Hedonic.analysis of housing markets frequently has been

employed in an effort to estimate the benefits of improved air

quality. Presumably, individuals reveal their willingness to pay

for environmental quality through their location choices in

housing markets and the corresponding housing premiums for

various locational attributes, including air quality. The

benefit estimates thus obtained, if accurately measured,

represent the total benefits to individuals of improvements in

air quality, including improvements in health status, reduced

property damage (soiling costs), as well as less tangible psychic

benefits such as improved visibility. As such, estimates of the

aggregate benefits of improved air quality obtained from hedonic

analysis of housing markets may be viewed as upper bound

estimates of the benefits of improved health status attributable

to improved air quality.

This section explores the possibility of deriving meaningful

information about the value of health risks from the literature

relating property values and air pollution. In section 2.8.2 the

hedonic analysis of housing markets is considered in detail.

After noting a number of econometric problems that have not been

fully resolved in the literature, some estimates of willingness

to pay for air quality implied by a number of studies are

presented. It should be noted that the review does not attempt to

attack or defend the basic methodology of applying hedonic

analysis to the problem of property values and environmental

quality. Given the existing state of knowledge it seems

premature to attempt to make judgements about the appropriateness

of housing market hedonic studies, or to attempt the derivation

of a consensus or best estimate of the value of air quality as

revealed in housing markets. Instead, a number of methodological

concerns and a range of empirical values are presented, to

explore the robustness of the method.

In section 2.8.3, the estimates of willingness to pay for

air quality are combined with estimates of the effects of air

quality on health, to imply upper bounds for the value of

mortality risks. The extensive literature on the value of

mortality risks as revealed in various indirect and contingent

markets has been reviewed elsewhere (see Blomquist (1982),

Violette and Chestnut (1984) and Jones-Lee (1985)). The upper

bound values of mortality risks as revealed in the housing market

can be compared to the range other studies have found. The main

benefit of examining the housing market results is that this

market directly reflects air quality. Other approaches to

valuing mortality risks consider other types of risks, such as

the risk of accidents while on the job, or traffic accidents. On

the other hand, the link between the value of air quality as

reflected in housing markets and the value of mortality risks is

fairly tenuous and depends crucially upon the validity of various

assumptions made.

2-115
2.8.2. Hedonic Analysis of Housing Markets ----__- ---- --- -- ------ -------

2.8.2.1. Introduction

Ideally, we need estimates of the parameters of the demand

function for improved air quality, and an estimate of the initial

height of the demand curve. The benefits of a given improvement

in air quality can be measured as the integral under the

compensated demand curve, from the initial level of air quality

to the level of air quality that is attained with the

improvement. In Figure 2-2, the initial level of air quality is

shown by Al, and the augmented level A2. The initial level of

marginal benefits as perceived by the consumer are shown as Bl,

and the level of marginal benefits corresponding to level A2 are

shown as B2. The value of the improvement to the consumer is

shown as the shaded area BlB2AlA2, and corresponds to the

equivalent .variation of income of the change. This is a measure

of the dollar equivalent of the welfare improvement (Hicks,

1968).

The earliest hedonic analysis of housing markets concerns

the construction of housing price indices. This literature is

motivated by an interest in accurately estimating changes in

housing price. Following Gorman (1956) and Adelman and Griliches

(19611, the primary emphasis in the housing price index

literature is the development of a time-series (or cross-SMSA)

housing price index holding housing "quality" constant. In some

of these studies, the sales price of a particular house at

different points in time is used to estimate a price index

(Dobson, 1970; Chinloy, 1977; Palmquist, 1980). In most of the

remaining studies, such as Musgrave (1969), Follain (1978), and

Palmquist (1980), the sale price is regressed on the

characteristics of the house, with the housing price index

computed as the change over time (or across areas) in the

predicted sales price of a typical housing bundle (that is, a

bundle with the sample mean level of each attribute).

Related to the housing price index literature is the early

hedonic demand literature. Studies of this type were primarily

interested in estimating the "shadow prices" of housing

characteristics, that is, the contribution of particular

characteristics to total value, rather than an overall housing

price. Studies concentrating on the impact of air quality on

housing values include Ridker and Henning (1967), Anderson and

Cracker (1971), Smith (1978), and Wieand (1973). A summary of

the results from these studies and others are provided in

Table 2-11. The marginal price estimates vary considerably

across studies, ranging from zero to $422.

2-116
FIGURE 2-2

BENEFITS OF AIR QUALITY IMPROVEMENT

BENfFITS2.

-

8 b

\

COMPENSATED

DEMAND FOR

AIR QUALITY

-, AIR QUALITY

L t

2-117
TABLE 2-11 ESTIMATES OF MARGINAL PRICES OF AIR POLLUTION

(Suspended Particulates)

____--------------------------------------------------------------

Estimated Marginal Price

Study Location Year (1980 Dollars/mm3)

____________------__-----------------------------------------

Diamond (1980) Chicago 1969-71 $422

Li and Brown (1980) Boston 1971 2-Ba

Smith (1978) Chicago 1971 91-108

Smith and Ohsfeldt Houston 1970 4-21

(1979) Houston 1976 14-68

Wieand (1973) Census 1960 o.- ga

________________________________________---------------------------

a Not statistically different from zero.

2-118
In many of these studies, marginal prices are assumed to

reveal the consumer's willingness to pay for various units of a

particular characteristic. However, these are not estimates of

the consumer's entire willingness to pay schedule, and may not

reveal the .marginal evaluations of different classes of

consumers, except as an overall average. Instead, these

estimates are measures of the average market price of a marginal

change in a particular locational amenity--clean air. At most,

the shadow prices determine only the height of the demand for

this characterisitic, but do not throw any light on the shape of

the demand function.

An additional problem of using single state hedonic

regression concerns the implicit nature of housing

characteristics. Consider an ordinary good that is supplied in a

competitive market. A consumer faces a constant marketdetermined price, and adjusts quantity purchased to the point

where the person's marginal evaluation of the good (demand) is

equal to the market price. If the good is sold in such a way

that the price facing the consumer varies with the quantity

purchased, the single hedonic estimate of the marginal benefit to

the consumer will be a weighted average of marginal evaluations

of consumers in different cicumstances. If air quality is a

normal good, higher income consumers will have a higher demand

for it, and their demand curves will intersect the non-constant

price schedule at different points. It is still true that

consumers equate marginal evaluation with price, and measures of

benefits to improved air quality can be estimated as the area

under the compensated demand curve, but these measures will vary

with consumers. One may conclude that a proper measure of

benefits should segment consumers by different income levels and

other characteristics, or alternatively one may accept that the

average marginal evaluation, shown by the hedonic estimate, might

be used for an overall estimate of benefits to the typical

consumer. The single-stage hedonic estimate still will not

provide evidence as to the shape of the demand curve, however.

2.8.2.2. Hedonic Prices and the Demand for Characteristics

There have been many attempts to estimate the demand for

housing characteristics directly, either as a system of demand

equations or with each equation treated separately. Among the

earliest studies of this type are Kain and Quigley (1975),

Straszheim (1975), and King (1976). Unlike Kain and Quigley,

both Straszheim and King include price information in their

estimating equations (specifically, the "hedonic" price of the

attribute). Since both studies assume a linear housing price

structure (that is, a constant marginal price of the attribute),

it is necessary to invoke a "segmented markets" assumption to

insure variation of the hedonic prices within an urban area at a

single point in time. That is, a separate hedonic regression is

estimated for each market segment, and the resulting coefficient

estimates are used as the price variable in the demand function.

2-119
It is important to note that the segmented markets

hypothesis arose from the observation that point estimates of

marginal price differ across areas within an urban area. If

markets were not segmented (or separated), it was (implicitly)

assumed that arbitrage between markets would insure price

equality across the urban area. Although this argument may be

applicable to the literature on racial discrimination in housing,

the segmented markets hypothesis, in general, represents a

failure to recognize the implicit nature of characteristics

markets. The fact that characteristics are purchased jointly in

indivisible bundles limits arbitrage possibilities,

a nonlinear price

resulting in

structure. Differences in point estimates of

marginal price are to be expected, and do not constitute evidence

of segmented markets.

2.8.2.3 Rosen's Model of Implicit Markets

A general model of implicit markets for characteristics was

developed by Rosen (1974). In this model, the interaction of

supply and demand produces a market clearing price function,

P(Z) 9 which relates the price of a heterogeneous good to 2, the

characteristics of the good. Rosen defined equilibrium as the

state at which the marginal bid price for Zi, oil equals the

marginal offer price for Zi, oi, for all i in Z. The bid curve

relates the maximum price a consumer is willing to pay for an

additional unit of Z.,

variables) and utl9.

holding income (and other exogenous demand

1tY constant (UO). The offer price curve

relates the minimum price a producer is willing to accept for an

additional unit of

5

holding exogenous supply variables and

profits constant (Pi f.' Notationally, an implicit market is in

equilibrium when

9iCz* Y~B U"> - Pi = Cpl(Z, Y2, Pi')

for all i, where Yl represents income and other exogenous demand

variables, Y2 represents exogenous supply variables, and Pi is

the equilibrium implicit marginal price of Zi.

In Rosen's model, the derivatives of 0. form a set of

compensated (inverse) demand functions, and tht derivatives of

9i a set of profit-compensated supply functions. The

intersections of the demand and supply functions trace out the

price function Pi, which will not in general be linear, and will

not imply a constant marginal price. (The usual hedonic

technique and the competitive model for an ordinary good both

imply constant marginal prices.) If the price function P

f

can be

determined, then taking its derivative at various leve s of Zi

will yield a set of implicit marginal prices, which in turn may

be used to estimate the compensated demand function needed in the

estimation of benefits to improved air quality. In essence,

2-120
since the price function relating the marginal price and the

quantity of an attribute is composed of intersections of demand

and supply, it is neither demand nor supply itself. What results

is an identification problem.

Rosen suggested a two-step estimation procedure, where an

hedonic market equation, P(Z), is estimated in the first step

using the best fitting functional form, and omitting Yl and Y2.

In the second step, the derivatives of the equation estimated in

the first step, evaluated at each observation's level of Z, are

used in the estimation of a system of supply and demand

equations:

'i * QiG, q> [demand]

[suPPlYI

where P.

each obierved Z.

- the partial derivative of P(Z) w.r.t. Zi, evaluated at

2.8.2.4. Rosen's Model: Applications to Demand for Air Quality

Studies that apply Rosen's technique to the analysis of the

demand for air quality are Harrison and Rubinfeld (1978), Nelson

(1978), Bender et al. (1980), and Ohsfeldt (1983). Harrison and

Rubinfeld are primarily interested in a single characteristic,

air quality. They estimate a single demand equation (1) using

OLS and (2) with an instrumental variable for air quality.

Nelson estimates a supply and demand function for clean air using

two-stage least squares. In both cases, the variation in P- in

the system is entirely attributable to the nonlinearity ofithe

price structure and the subsequent differences in point estimates

of marginal price. Bender, et al. estimate the demand for air

quality giving special attention to the choice of functional form

for both the demand function and the hedonic price equation.

Ohsfeldt estimates the demand for three housing neighborhood

characteristics including quality (of which air quality is a

major component) for three cities using the longitudinal Annual

Housing Survey for the years 1974 through 1979.

In all of these studies, with the exception of Ohsfeldt

(1983)s the market price function, P(Z), contains a greater

number of characteristics variables than the demand (or supply)

equations. One reason why the empirical models have this

structure, although it is never explicitly stated as such, is to

reduce the severity of a problem that fs immediately apparent in

Rosen's suggested empirical technique. That is, if Pi is linear

in Z and oi is linear in Z, then in the second step of the

estimating procedure, Z will explain all of the variance in Pi

and the coefficients of Yl will be zero. The only way to avoid

this result using Rosen's technique is to assume that Pi and Qi

have different functional forms with respect to Z, of which

including linear fewer Zi's in oi is a special case. In other

words, with a single market area at a particular point in time,

2-121
all of the variation in the estimated marginal price, Pi, can be

attributed to the nonlinearity of the price structure, P(Z). In

estimating demand (or supply), restrictions on the functional

forms must be imposed to avoid duplicating the marginal price

function. Even with multiple market data, substantial exogenous

price variation is necessary to avoid the effects of spurious

correlation (see Ohsfeldt and Smith, 1985). It seems likely that

all of these studies suffer, to some degree, from inadequate

exogenous price variation. Thus, the benefit estimates obtained

from these analyses are not very reliable.

Another basic flaw in most of these studies is that they

accept Rosen's view of the identification problem. The object of

an implicit market analysis is the individual consumer (or

producer). Since the market price structure P(Z), is exogenous

to the individual, there is no direct interaction between

---------- individual supply and individual demand. -_-------- The relevant

simultaneity problem in an implicit market analysis results from

the quantity dependence of marginal prices.

With these limitations in mind a summary of demand

elasticity estimates from these empirical studies is provided in

Table 2-12.

These estimates, to the extent they are accurate, indicate

that the demand for clean air is probably price inelastic, and

that clean air is a normal good.

In terms of benefit estimates, Bender et al. suggest a

permanent 10 percent reduction in suspended particulates would

result in a $700-1800 benefit (present value) per household. A

permanent reduction of 20 percent would create $1500-3000 in

benefits (present value) per household. Similarly, Harrison and

Rubinfeld estimate. that a 2 pphm reduction in nitrogen oxides

would create benefit of $800 per middle-income household, while a

9 pphm reduction would result in benefits of $2200 per

middle-income household. But, because of the econometric

problems outlined earlier, these estimates should be used

cautiously.

2-122
TABLE 2-12 ESTIMATES OF ELASTICITIES OF DEMAND FOR CLEAN AIR

________-----------------------------------------------------------

Date Price Income

Study Location Year Elasticity Elasticity

------__---_---_---------------------------------------------------

Bender, et al. (1980) Chicago 1972 - .516 .609

Harrison and Rubinfeld Boston 1970 - .850 .957

(1978)

Nelson (1970) D.C. 1970 -1.250 1.000

Ohsfeldt (1983) Houston 74-79 -1.111 .081

Chicago 74-79 - .113 .139

Philadelphia 74-79 - .382 .123

-------------------------------------------------------------------

2-123
2.8.3. implied _--- Values ------ gf Mortality Risks ------__ -----

In this section, we consider the problem of deriving a value

for the risks to human health associated with air pollution,

based on the-values implied in property value studies. This

exercise follows the proposal made by Portney (1981). A similar

exercise has also been carried out by Smith and Gilbert (1984)

for values derived from a hedonic wage function that incorporates

both job related risks and implicitly the mortality risks

associated with air pollution.

As discussed above in section 2.8.2, individuals may reveal

their willingness to pay for air quality through their location

choices, and so housing prices will relflect this value. From

some early studies in this field, estimates of the marginal price

of air pollution (suspended particulates) range from zero to $422

per microgram per cubic meter. For the present exercise, we will

use this average marginal evaluation as an estimate of the

benefits to the typical consumer. For illustrative purposes,

assume the true value is somewhere in the middle of this range,

say at $100.

Knowing the marginal price of air pollution as revealed in

housing markets does not directly lead to estimates of the value

of risks to health. What is necessary is additional information

linking air pollution to health risks, which can be found from

the health econometrics literature (see Section 2.3). Using the

same notation as Portney (1981), if the marginal value of risk is

vRp it can be approximated by the ratio of the marginal value of

air pollution (dV/dQ) and the marginal effect of air pollution on

risks (dR/dQ), i.e.

vR - (dV/dQ)/(dR/dQ).

Using the estimates from housing hedonics leads to a value of

(dV/dQ) ; using estimates from a health econometrics study allows

the estimation of (dR/dQ). In particular, a "typical" health

econometrics estimate (see Section 2.3) suggests that a marginal

change in the mean level of suspended particulates results in a

change in the average mortality rate of 0.45 (deaths per

100,000).

To actually complete the calculation of the value of

health risks, the basic pieces of information must be adjusted to

take into account exactly what is revealed in the housing market.

First, the marginal prices of 'air pollution, reflecting the

difference air pollution makes in housing prices, must be put on

an annual cost basis. Using a typical discount rate of 10

percent (again, see Portney (1981)), our assumed value of $100

implies a $10 annual cost. Second, it should be recognized that

the choice of location improves health for all members of the

household. So if a typical household is made up of 3

individuals, the risk reduction the household "buys" when it buys

a house with a marginal reduction of air pollution is a reduction

2-124
in mortality risks for 3 individuals, or 3 times .45 - 1.35

deaths per 100,000. With these figures, then, the implied value

of a risk reduction is

vR = (dV./dQ)/(dR/dQ) - ($10)/(1.35 x lo-5)- $7.4~ 10~.

That is, the value of a marginal change in risks, or the value of

life in a statistical sense, is $740,000.

There are numerous caveats concerning this value of risk.

First, for the calculation to be approximately correct, two

assumptions must be approximately met: 1) the only reason

households value cleaner air (as revealed in the housing market)

is for the change in health risks; and 2) households "correctly"

perceive the change

pollution.

in health risks associated with changing air

Since households probably value cleaner air for reasons

unassociated with health, the estimate of the marginal value of

risk, VR, will be upwardly biased, or an upper bound to the

correct measure. Smith and Gilbert (1984) attempt to at least

partially correct for this problem by reducing the implied values

of mortality risks by 30 percent. This correction used the

results of a contingent valuation study by Brookshire et al.

(1979) that asked respondents to allocate their total willingness

to pay for air pollution reductions between aesthetic and health

motivations. This study indicated that 30 percent of the total

willingness to pay was due to aesthetic motives. To use this

adjustment, Gilbert and Smith have to maintain the assumption

that the same proportion can be applied to willingness to pay

estimates from the wage model. Making the same assumption for

willingness to pay estimates from property value studies, the

value of mortality risks derived above could be similarly

adjusted. However, depending upon the individual's exposure to

pollution at work and at home, the relative importance of health

versus aesthetic motives may differ. Maureen Cropper suggests,

for instance, that most of the observed housing price premiums

may be due to aesthetic and not health motives. Since working

persons spend a large portion of their time away from their

homes, willingness to pay for cleaner air at home cannot capture

the total willingness to pay for cleaner air for health reasons.

This implies that the derived value of mortality risks overstates

the true value because of the inclusion of aesthetic and other

benefits, but understates the true value because it excludes the

value of clean air on the job.

If households underestimate the effect of air pollution on

health (i.e. households' estimates are smaller than the health

econometric studies' estimates of dR/dQ), then the estimate of VR

will be biased downwards. The converse is of course true if

households overestimate the effect of air pollution on health.

The effect of air pollution on health as perceived by households

is the required, but unkown, value. Smith and Gilbert (1984)

Z-125
point out that given the range of estimates existing in the

technical literature, it is plausible that the relationship as

perceived by individuals' could fall anywhere within this range.

Finally, even if the formula for calculating the value of

risk is approximately correct, the values plugged into the

formula are only possible candidates from a wide range of

estimates for both the value of air pollution and the effect of

air pollution on human health. Using different estimates could

change the value of risk by at least an order of magnitude. In

particular, since some property value studies show no premiums

for air quality, the lower bound for the value estimated is zero.

This could imply that there is no relationship between air

quality and health, or that individuals do not perceive any

relationship, or that the relationship simply is not discovered

by hedonic analysis of housing markets.

With the above caveats in mind, whatcanbe said about the

value of risk of $740,000 that was found? In very broad terms,

this value does not seem inconsistent with the values derived

from the hedonic analysis of labor markets, or from the analysis

of risk-related consumption activity. Blomquist (1982) reports a

range of implicit values from labor market studies from $378,000

to $2,820,000; and a range of implicit values from consump.tion

activity from $180,000 to $466,000. Further mention should be

made of the comparison of Portney's (1981) results to ours, since

by following almost exactly the same procedure as used above, he

arrives at a value of $180,000. The difference can be explained

mainly by the marginal value of air pollution Portney uses. He

begins with a value of $335 for 18 micrograms/cubic meter of

suspended particulates, which implies a value of (roughly) $18.60

for 1 microgram/cubic meter. This compares to the value of $100

used in the above calculations, and thus accounts for most of the

difference in the final value of risk. The estimate Portney used

is well within the range of estimates reported in section 2.8.2.

Also note that Portney's estimated relationship between air

pollution and mortality risks (.5 per 100,000) is very close to

that used above (.45 per 100,000).

So the various implicit market values for health risks,

where the markets are labor, housing, and certain consumption

goods, seem to result in what again is best termed not

inconsistent results. The $740,000 estimate can also be compared

to the cost of illness approach estimates of the value of

mortality risks, which are given by the present value of future

foregone earnings. Landefeld and Seskin (1982) report a standard

estimate for a male 40-44 years old of $180,352, or their

adjusted estimate (to more closely approximate willingness to

pay) of $660,193. Again, no large inconsistencies are seen in

the estimates. In addition, due to the existence of averting

behavior, it has been suggested that the cost of illness approach

underestimates willingness to pay (see Section 2.2). This can

help explain in particular the relatively low estimate of the

standard cost of illness approach.

2-126
2.8.4. BibliogyaEhy

PROPERTY VALUE STUDIES

A. Theory and Methodology

__--- First Stage Hedonics --- - --------

1. Freeman, A.M. Air Pollution and Property Values: A

Methodological Comment. Review of Economics and

Statistics, 53:414-415, 1979.

2. Lancaster, K. A New Approach to Consumer Theory.

Journal of Political Economy, 74:133-155, 1966.

3. Lucas, R.E.B. Hedonic Wage Equations and Psychic Wages

in the Return to Schooling. American Economic Review,

67:549-588, 1977.

4. McDougall, G. S. and C. Wright. A Proposal for

Improving Measurement of the Benefits from Pollution

Abatement. Journal of Environmental Economics and

Management, 7:20-29, 1980.

5. Murray, M. P. Prices and Composite Commodities. Journal

of Urban Ec'onomics, 5:188-197,1978.

------ --- Second Stage Hedonics - --------

6. Brown, J. N. and H. Rosen . On the Estimation of

Structural Hedonic Price Models. Econometrica,

50:765 - 768, 1982.

7. Diamond, D. and B. Smith. Simultaneity in the Market

for Housing Characteristics. Journal of Urban

Economics, forthcoming.

8. Epple, D. Hedonic Prices and Implicit Markets:

Estimating Demand and SUPPlY Functions for

Differentiated Products, unpublished paper. Carnegie -

Mellon University, April, 1984.

9. Freeman, A. M. The Hedonic Price Approach to Measuring

Demand for Neighborhood Characteristics. In: D. Segal

. led.), The Economics of Neighborhood. Academic Press,

New York, 1979a.

10. Freeman, A. M. The Hedonic Prices, Property Values, and

Measuring Environmental Benefits: A Survey of the

Issues, Scandinavian Journal of Economics, 81:154-173,

1979b.

11. Murray, M. P. Mythical Demand and Mythical Supplies

2-127
12.

13.

14.

15.

for the Proper .Estimation of Rosen's Hedonic Price

Model, Journal of Urban Economics, 14:327-33, 1983.

Ohsfeldt, R. L. and B. Smith. Estimating the Demand

for Heterogeneous Goods. Review of Economics and

Statistics, forthcoming.

Polinsky, A. M. and S. Shavell. Amenities and Property

Values in a Model of an Urban Area. Journal of Public

Economics, 5:119-129, 1976.

Rosen, S. Hedonic Prices and Implicit Markets:

Product Differentiation in Pure Competition. Journal of

Political Economy, 82:34-55, 1974.

Van Lierop, J. House Price Structure and Market

Equilibrium. Journal of Urban Economics, 11:272-289,

1982.

B. Application to Value of Air Quality

--__- First Stage __- - Hedonics ---_---_

16.

17.

18.

19.

20

21

22

23

Anderson, R. and T. Cracker. Air Pollution and

Residential Property Values. Urban Studies, 8:171-180,

1971.

Diamond, D. B. The Relationship Between Amenities and

Urban Land Prices. Land Economics, .56:21-32, 1980.

Li, M. M. and H. Brown. Micro -Neighborhood

Externalities and Hedonic Housing Prices. Land

Economics, 56:125-41,198O.

Polinsky, A. M. and D. Rubinfeld. Property Values and

the Benefits of Environmental Improvement. In: L. Wingo

and A. Evans (eds.), Public Economics and the Quality

of Life. Johns Hopkins University Press, Baltimore,

1977.

Ridker, R. G. and J. Henning. The Determinants of

Residential Property Values with Special Reference to

Air Pollution. Review of Economics and Statistics,

44:246-255, 1967.

Smith, B. A. Measuring the Value of Urban Amenities.

Journal of Urban Economics, 5:370-387, 1978.

Smith, B. A. and R. Ohsfeldt. Housing Prices Inflation

in Houston: 1970-1976. Policy Studies Journal, 8:257-

276, 1979.

Wieand, K. F. Air Pollution and Property Values: A

Study of the St. Louis Area. Journal of Regional

2-128
Science, 13:91-95, 1973.

------ Second Stage --- -------- Hedonics

24.

25.

26.

27.

28.

29.

30.

Bender, B. T, Gronberg, and H. S. Hwang. Choice of

Functional Form and the Demand for Air Quality. Review

of Economics and Statistics, 62:638-643, 1980.

Freeman, A. M. The Benefits of Environmental

Improvements: Theory and Evidence. Johns Hopkins

University Press, Baltimore, 1979.

Harrison, D. and D. L. Rubinfeld. Hedonic Housing

Prices and the Demand for Clean Air. Journal of

Environmental Economics and Management, 5:81-102, 1978.

McMillan, M. L. Estimates of Households' Preferences

for Environmental Quality and Other Housing

Characteristics from a System of Demand Equations.

Scandinavian Journal of Economics, 81: 174-187, 1979.

Nelson, J. P. Residential Choice, Hedonic Prices and

the Demand for Urban Air Quality. Journal of Urban

Economics, 5:357-369, 1978.

Ohsfeldt, R. L. Implicit Markets and the Demand for

Housing Characteristics, unpublished dissertation.

Department of Economics, University of Houston, 1983.

Palmquist, R. B. Estimating the Demand for the

Characteristics of Housing. Review of Economics and

Statistics, 46:394-404, 1984.

HEDONIC WAGE STUDIES

A. Theory and Methodology

31. Eberts, R. W. An Empirical Investigation of Intraurban

Wage Gradients. Journal of Urban Economics, 10:50-60,

1981.

32. Eberts, R. W. and T. Granbert. Wage Gradients, Rent

.Gradients, and the Demand for Housing: An Empirical

Investigation. Journal of Urban Economics, 12:168-176,

1982.

33. Muth, R. F. Cities and Housing. University of

Chicago Press, Chicago, 1969.

2-129
B. Applications to Value of Air Quality

34. Bayless, M. Measuring the Benefits of Air Quality

Improvements: A Hedonic Salary Approach. Journal of

Environmental Economics and Management, 9:81-99, 1982.

35. Cropper, M. L. and A. S. Arriage-Salinas. Intercity

Wage Differentials and the Value of Air Quality.

Journal of Urban Economics, 8:236-254. 1980.

36. Roback, J. Wages, Rents, and the Quality of Life.

Journal of Political Economy, 90:1257-1278, 1982.

--___----_ References (for Section 2.8.3)

1. Blomquist, Glenn. Estimating the Value of Life and Safety:

Recent Developments. In:

Michael Jones-Lee, ed.

The Value of Life and Safety,

North-Holland Publishing Company,

Amsterdam, 1982.

2. Cropper, M.L. Measuring the Benefits from Reduced

Morbidity. American Economic Review, 71:235-240, 1981.

3. Landefeld, J.S. and E.P. Seskin. The Economic Value of

Life: Linking Theory to Practice. American Journal of

Public Health. 72(6):555-566, 1982.

4. Portney, P. Housing Prices, Health Effects, and Valuing

Reductions in Risk of Death. Journal of Environmental

Economics and Management, 8:72-78, 1981.

Z-130
2.9. CONCLUSIONS: INTERIM VALUES FOR THE HEALTH EFFECTS

OF AIR POLLUTION

2.9.1. -_---------- Introduction

The strengths, weaknesses and major results of the various

approaches to solving the problem of valuing health effects

likely to result from an air quality change are discussed in the

earlier parts of Volume 2. A synthesis of these results is the

goal of this concluding section. The task seems formidable,

since the studies reviewed often value different aspects of

health, using different methodologies. As a result of the

methodology used, the studies' results will vary in quality, in

terms of accuracy and in how complete a value estimate can be

reached.

To organize the issues involved, in section 2.9.2 a

framework for value estimates is discussed. This section

describes .what health effects it would be desirable to have

values for, and what a complete value estimate would include.

Rather than being.an ideal, the goal is to develop a framework

that can be implemented with data already available or likely to

be available in the near future.

In section 2.9.3 the available evidence on the value of health

effects is reviewed. The available evidence is compared to the

framework, in terms of which health effects are valued, and how

complete these values will be. In light of this discussion,

reasonable ranges and interim values are developed. To

illustrate the usefulness of these values, the section concludes

with an illustrative calculation of the benefits of an

hypothetical change in air quality.

2.9.2. A Framework for Valuing _________ --- -----_ the k!e2lth Effects Of 412

------m-w Pollution

There are two questions involved in forming a set of values

for the health effects related to air pollution. First, what

types and ranges of health effects would we like to have values

for? Second, for the health effects we would like to value, what

would constitute a complete and conceptually correct value

estimate? Answers to these questions are discussed below, and

this discussion is summarized in Table 2-13.

Other sections of this report contain a more complete

discussion of the issues involved in answering these questions.

The types and ranges of health effects related to air pollution

are discussed in section 2.3 on health econometrics, and in

section 3.2 of Volume 3 on dose response relationships. What is

involved in a complete value estimate is developed on a rigorous

theoretical basis in section 2.2. A preliminary investigation of

valuing serious or life-threatening illness is the focus of

Volume 4, though the framework developed has yet to be

implemented.

2-131
------ ------- ------ Health Effects Valued

TABLE 2-13

FRAMEWORK FOR HEALTH VALUES

----- Acute 05 Short-term Morbidity --e------m --------

--light symptoms

--marginal change in

time spent ill

Value reflects ----- --------

--physical and mental

discomfort

--work time lost

--other time lost

-- medical expenditures

--costs of averting

behavior or preventive

measures

Aggravation ---_---- gf Previously ----_---_

---e-e- Existing Chronic Morbidity ------- --------

__ chronic lung conditions

__ chronic heart conditions

--marginal and non-marginal

changes in time spent ill

--------- --------- -- Increased Incidence" of

--__----_ Non-fatal Chronic Morbidity ------- --------

-- chronic lung conditions

em chronic heart conditions

--cancer

Mortality m-s-----

__ unforseen instant death

-- chronic lung conditions

_ _ chronic heart conditions

--cancer

-- a larger degree of

all of the above

--individuals' health

status is already low

- - all of the above

--lifestyle and work

changes due to the

existence of chronic

illness

- - mortality risks

--morbidity preceding

mortality valued as

above

--psychic costs of

imminent death

2-132
2.9.2.1. Health Effects to be Valued

Based on the health econometrics literature and what is

known about dose-response relationships, the health effects

relevant to.a change in air quality levels fall into three

groups: 1) acute morbidity; 2) chronic morbidity; and 3)

mortality. This classification is necessarily somewhat

arbitrary. Particularly troublesome is the separation of

morbidity and mortality. Almost all morbidity involves some risk

of mortality, and conversely almost all mortality is preceded by

a period of morbidity. In what follows, morbidity is treated as

not involving any risk of death; that morbidity related to death

is termed "morbidity preceding mortality."

Most individuals affected by air pollution at all probably

experience only acute effects. These include symptoms such as

eye irritation, cough and headache stemming directly from the

pollutants, and the possibility of increased sucesptibility to

acute illnesses such as upper respiratory infections. Reasonable

changes in air quality could change the experience of these

individuals marginally-- a fraction of a day to a few days of this

type of health effects more or less. So value estimates should

value marginal changes for a range of light symptoms.

Health changes related to chronic morbidity will affect a

smaller number of people, but each will suffer more serious

effects. Most evidence supports the relationship between air

pollution and the aggravation of existing chronic lung

conditions. There is also some evidence that those individuals

with existing heart conditions may be affected. In general, the

dose-response literature seems to suggest that a reasonable

change in air pollution levels may provide a significant change

in health status for those with chronic conditions, both in the

severity of the symptoms and in the change in the number of days

the symptoms are experienced. However, at levels of air

pollution relevant to the U.S., from the health econometrics

literature little evidence has been found of a link between air

pollution.and any large changes in time spent ill. To value the

possible effects of air pollution on the chronically ill, it is

thus necessary to address the symptoms the chronically ill

experience, and be applicable to both marginal changes in time

spent ill, and possibly non-marginal changes as well.

The possibility that air pollution causes (or is one

possible cause of) new cases of chronic lung conditions or heart

conditions also can not be ruled out. To date, evidence on this

possibility is virtually non-existent. There is some evidence

linking increases in mortality rates for chronic and serious

illnesses to air pollution. If air pollution is increasing the

incidence of eventually fatal condtions, it seems reasonable that

it increases the incidence of non-fatal conditions as well. On

the other hand, air pollution may not be causing new cases at

all, but instead aggravate existing cases to the extreme of

increasing death rates. While this is an unresolved issue, it is

2-133
still useful to value a change in the incidence of non-fatal

chronic morbidity. Aside from valuing an important possible

effect of air pollution, valuing non-fatal conditions is a first

step towards valuing the morbidity preceding mortality.

The most serious health effect related to air pollution is

of course mortality. Evidence supports a link between general

mortality rates and air pollution levels, possibly stemming from

increased mortality due to chronic lung conditions, heart

conditions, and cancer. The ideal measure of the value of

mortality would include a value of the change in mortality risks,

plus a value for the change in morbidity preceding mortality.

2.9.2.2. Components of a Complete Value Estimate

The development of a conceptually correct and complete

estimate of the value of animprovementinhealth due to a change

in environmental quality can be thought of involving several

steps. First, for morbidity, an estimate of what an individual

wouldbe willing to pay for a certain change inhis health status

could be prepared. This estimate will reflect the different

reasons an individual values his health. Second, it is necessary

to estimate what an individual would be willing to pay for a

change in the risks of mortality he faces. This estimate will

reflect the value of the morbidity preceding mortality, as well

as the value of the mortality risks alone. Each of these steps

is discussed briefly below. Following this discussion is a brief

discussion of the limitations of the framework that are

necessitated by the limitations of the available data. It should

also be noted at the outset that the value estimates are being

prepared for use in an ex ante evaluation of whether a project is

a potential Pareto improvement. This criterion relfects

normative judgements, but it is not the purpose of this Report to

discuss and defend the general methodology of applied welfare

economics.

To analyze why and how much an individual values his health,

first consider why an individual would value a reduction in acute

morbidity. First, there is the value of discomfort: the direct

disutility of illness or symptoms, which in more severe cases

might be termed pain and suffering. Second, there is the value

of work time lost due to illness or symptoms. This can be

measured directly as the value of the foregone earnings the

individual actually incurs (allowing for the possibility of paid

sick leave). Third, there is the value of other time lost. This

includes the value of time devoted to housework, leisure time,

and so on. Fourth, there are the direct costs of medical

expenditures incurred because of the illness or symptoms.

Finally, there are the costs of averting behavior, or preventive

actions taken to offset the impact of bad health or the

environment.

For the value of chronic morbidity, all of the above

2-134
components of the value of acute morbidity remain relevant. Of

course, the discomfort may be *more severe,

earnings, lost time,

and the foregone

medical expenditures, and averting behavior

may be more significant. In addition, there seem to be special

considerations required for chronic conditions. Since the

condition may restrict activity and cause discomfort for a much

longer period of time,

changes

the individual may be forced to make large

in his lifestyle and occupation. For instance, certain

strenuous leisure activities or occupations may not be possible.

So evenifthe individual has not lostworktime or leisure time,

he also may not earn as much or enjoy his leisure as much as he

would if the chronic condition were not present. (The influence

of chronic conditions on earnings

et al (1979).)

has been explored by Cracker,

Valuing mortality risks due to air pollution involves

valuing the morbidity that precedes death, and finding the amount

individuals are willing to pay to

risks.

avoid increased mortality

Valuing morbidity preceding mortality involves the same

considerations discussed in valuing chronic morbidity. Valuing

mortality risks results in what has been termed the value of a

statistical life.

The framework discussed above for developing a complete

estimate of the value of health is feasible to implement (though

not necessarily perfectly) given existing data, but still falls

short of being ideal. Several further steps would need to be

taken before the value of health would be ideally estimated.

First, since health and the effects of environmental quality

on health are goods involving a high degree of uncertainty, the

analysis must take this into account. Graham (1981) addresses

the general problem of benefit cost analysis under uncertainty,

and investigates how what an individual would pay for a change

in risk may be related to what an individual would pay for a

certain change. An expression for what an individual would be

willing to pay for a change inhealth risks is derivedin section

2.2. However, in the discussion above of the value of morbidity,

health is treated as a certain good, and the complete value

measure developed corresponds to a standard consumers surplus

measure under certainty. This simplification is necessary

because most of the existing empirical work values certain

changes. In general, for small changes in the incidence of common

illnesses or symptoms (e.g. coughing), treating uncertain changes

as if they occur with certainty does not seem very misleading.

At the other extreme, valuing mortality risks by the amount an

individual would be willing to pay to avoid certain death is

clearly inappropriate, and so the value of mortality risks, or

the so-called value of a statistical life, is used. In between

these extremes, the change involved if an individual develops a

new chronic condition is probably large enough that recognition

of the inherent uncertainty is necessary. What would be ideal is

the value of a change in risks of incurring a chronic condition,

but since the only data available apply to certain changes, value

estimates must reflect this.

2-135
Another conceptual shortcoming of the framework developed

above is that it applies mainly to the values individuals place

on their own health. That is, individual willingness to pay is

the focus, while for benefit cost analysis these measures must be

adjusted to reflect societal willingness to pay. This problem is

discussed in section 2.4.3, and a preliminary attempt to value

some of the differences between individual and willingness to pay

is made in the contingent valuation experiment discussed in

Volume 3. It is not entirely clear in which direction and to

what extent individual willingness to pay is biased away from

societal willingness to pay, but it seems likely that in general

individual willingness to pay will understate societal.

2.9.3. ------- Interim Values for the Health Effects of Air Pollution ------ --- --- ------ ------- -- --- -------__

2.9.3.1. Introduction

Based on the framework developed above (summarized in Table

Z-13), and the studies reviewed in Volume 2, this section

develops a set of interim values for the morbidity and mortality

effects due to air pollution. Given that there exists a-good

deal o,f controversy regarding the proper estimation of the value

of health, this exercise might seem premature. There are two

reasons the development of the interim values is justified at

this time. First, a reasonably large body of work already exists

on the value of health. Since the studies often use different

methodologies and do not always yield easily comparable values,

this body of work is not accessible to many policy-makers. So

one advantage of developing the set of interim values is that it

makes the results of this body of work available for applied

benefit-cost analysis. The second reason that the development of

interim values is a useful exercise is that it helps indicate

where further work is needed.

In section 2.9.3.2, the evidence from which the interim

values are developed is briefly discussed. The main criteria

used in judging the usefulness of this evidence are presented.

s.ections 2.9.3.3, 2.9.3.4, and 2.9.3.5 detail the actual

development of the interim values. Since so many obj.ective and

subjective judgements are involved, these sections attempt to

spell out in as much detail as possible the considerations

involved. It is hoped that the details will show the values

presented are reasonable, but providing the details will also

show where different judgements could be made, and how these

differences would affect the conclusions. To allow for some

differences, low, medium, and high estimates are presented. This

range is not determined by the range of estimates from the

separate studies, but instead is fntended to include all

plausible values, given the existing data. Thus, it may narrower

or wider than the range of individual estimates. Finally, in

section 2.9.3.6 an example of using the interim values in

practice is given.

2-136
2.9.3.2. Available Evidence on the Value of Health

The available evidence on the value of morbidity and

mortality is summarized in Table 2-14 (acute or short-term

morbidity),. and Table 2-15 (chronic morbidity). The value of

mortality risks has been reviewed elsewhere, most recently by

Jones-Lee (1985). The estimates presented are limited to the

health effects likely to be related to air pollution, as

discussed above and summarized in Table 2-13. All values are

expressed in terms of 1984 prices. For details of the derivation

of the values, see earlier sections of Volume 2.

In judging the usefulness of the evidence presented in

Tables 2-14 and 2-15, the most important criterion is how

complete the value estimates are, in relation to the framework

developed above. An incomplete value, no matter how precisely

estimated, yields limited information on the true value of the

health effect. The completeness of the different estimates is

summarized in Tables 2-14 and 2-15. In general, the most

complete estimates come from the contingent valuation studies.

The health production studies may or may not be complete,

depending upon the specifics of the derivation. The cost of

illness studies are always only partial measures of the value of

health. Since the relationship between these partial values of

health and the complete value is unclear, the partial values

provide only corrobsrative evidence. A detailed discussion of

the estimates and the differences between them is presented below

as a partofthe developmentofthe interim values.

Two important criteria concerning the validity of the

contingent valuation studies are survey design and sample size.

Other factors held constant, an improved survey design or a

larger sample size should improve the accuracy of the contingent

valuation estimates. The existing studies represent a tradeoff

between survey design and sample size. The study by Loehman et

al. reflects the largest sample of respondents, but at the cost

of using a mail survey. This design may decrease the validity of

the results for various reasons as discussed in section 2.5, the

most important problem being the inability to identify

unrealistic values or protest bids. The other contingent

valuation studies are based on personal interviews and may be

more accurate as a result, but also represent smaller sample

sizes. This tradeoff between survey design and sample size means

that no simple rule favoring the largest sample or the best

design can be applied in judging the validity of the different

estimates.

Finally, some mention should be made of the criteria used in

judging the results of the health production function approach.

As discussed in section 2.7, shortcomings in the methodology and

data are seen as limiting these results to being accurate only

within an order of magnitude.

2-137
.TABLE 2-14

VALUES OF ACUTE MORBIDITY

Value

(S/day)

Approach, study,

and health effect

Value Components Included

dis- work time medi- prevencomfort lost lost cal tion

-------- ---- w-m- --__ -------

---- -- ------- Cost of Illness

Hodson & Kopstein

(1984), Paringer

& Berk (1977) X X

--respiratory

illness 35

------ Contingent Valuation -__ ----__-__

Tolley, et a1.(1985)

25

35

29

28

31

40

50

--cough X

X

X

X

X

X

X

--sinus

--throat

--eyes

--drowsiness

--headaches

--nausea

--cough, throat

and sinus 66 X X X X X

--drowsiness,

headaches and

nausea 95 X X X X X

Loehman, et a1.(1979)

--shortness of breath/

chest pains:

mild 8

18

X X

X X

X X

X X

X

severe X

2-138
Approach, study,

and health effect

Value

(S/day)

_--_--

--coughing/sneezing:

mild

severe

4

11

--head congestion,

eye,ear,throat

irritation:

mild 6

severe 13

Health Production ------ ----------

Cropper (1981)

-- acute illness

Gerking,et al. (1984)

-- acute illness

TABLE 2-14

VALUES OF ACUTE MORBIDITY

(continued)

176 X X

40

Value Components Included

dis- work time medi- prevencomfort lost lost cal tion

____--- ---- ---- -_-_ ---e-me

X X X X X

X X X X X

X X

X X

X X

X X

X X

X X

X

X

X

2-139
TABLE 2-15

VALUES OF CHRONIC MORBIDITY

Approach, study, Value Value Components Included

and health effect ($> dis- work time medi- prevencomfort lost lost cal tion

--m-s---mm-m------ w-m--- m------w --a- --mm mm-- --mm--s

-_____- CHRONIC LUNG CONDITIONS ___- ----------

---_ Cost of Illness -- --_----

Freeman, et al. (1976)

--average case of:

emphysema 3194 X

Scitovsky &

McCall(1976)

--average case of

pneumonia

(non-hospital care)

253 X

----_- Contingent Valuation --- -----__--

Tolley, et a1.(1985)

predicted value of 1

day of relief for

person usually sick

(experienced 36 days of

symptom) for:

__ cough

--sinus

--throat

X X X X

--eyes

--cough, throat

and sinus

107

82

163

334

X X X X

X X X X

X X X X

297 X X X X

30 days of:

(given normal health)

-- cough 167 X X X X

--sinus 266 X X X X

--throat 206 X X X X

X

2-140
TABLE 2-15

VALUES OF CHRONIC MORBIDITY (continued)

Approach, study, Value Value Components Included

and health effect ($1 dis- work time medi- prevencomfort lost lost cal tion

__~-~~~~-~~~-~~--~ _-_-__ __------ ---- ---- -*-- -------

--eyes 236 X X X X X

--cough, throat

and sinus 625 X X X X X

Rowe and Chestnut(1984)

--average of 38

bad asthma days

Loehman, et a1.(1979)

one week of:

--shortness of breath/

chest pains:

401

mild 22

severe 57

--coughing/sneezing:

mild

severe 32

--head congestion,

eye,ear,throat

irritation:

mild

severe

90 days of:

--shortness of breath/

chest pains:

13

15

33

X

X

X

X

X

X

X

mild 56 X

severe 156 . . 'i

2-14

X X

X X

X X

X X

X X

X X

X X

X X

X X

X X

X x . x

X

X X X X

X X X X

X X X X
TABLE 2-15

VALUES OF CHRONIC MORBIDITY (continued)

Approach, study, Value

and health effect ($1

--~~---~--~~~~-~~~

--coughing/sneezing:

mild

severe

37

81

--head congestion,

eye,ear,throat

irritation:

mild

severe

40

99

-___--- CHRONIC HEART CONDITIONS ----- ----------

Value Components Included

---- -- Cost of Illness ----___

Acton(1975)

--average case of

coronary heart

disease

2703 X X

Hartunian, et al.(1'981)

--average case of

angina 604

Sctivosky & McCall(1976)

--myocardial

infarction 11,254

------ --- --------- Contingent Valuation

X

X

dis- work

comfort lost

-------- ---_

X X

X X

X X

X X

Tolley, et a1.(1985)

angina, various

endowments:

--1 mild day 66-99 X X

--1 severe day 124-279 x X

time medi- prevenlost cal

me-- ----

X X

X X

X X

X X

X X

X X

tion

------_

X

X

2-142
Approach, study,

and health effect

--5 mild days

--5 severe days 192 X X X X X

--lo mild days 154-288 X X X X X

--lo severe days

--20 mild days

--20 severe days

CANCER

---- -- Cost of Illness m---m--

Hodson & Kopstein

(1984)s Paringer

& Berk (1977)

TABLE 2-15

VALUES OF CHRONIC MORBIDITY (continued)

Value Value Components Included

($1 dis- work time medi- prevencomfort lost lost cal tion

____-_ mmme---m ---- ..--- ---- -------

96 X X X X X

262-506 X X X X X

486 X X X' x X

844 X X X X X

--average case of

cancer 9742

Hartunian, et a1.(1981)

_- average first year

of lung cancer 29,924

2-143
2.9.3.3. Value of Acute or Short-term Morbidity

Severity of Symptoms Valued

The least serious health effects possibly associated with

air pollution are various acute or short-term symptoms. Five

separate sources of estimates for the value of a day of acute

morbidity are reported in Table 2-14. A brief description of the

estimates follows, with emphasis on how the severity of the day

of morbidity valued differs. 1) The combination of the Hodgson

and Kopstein (1984) and Paringer and Berk (1977) studies provides

a cost of illness value for an average respiratory illness. The

value is expressed in terms of an average or Restricted Activity

Day (RAD). (See Section 2.4 for details). 2) The Tolley, et al.

(1985) contingent valuation study provides values for a day of a

range of light symptoms, alone and in certain combinations.

Based on the descriptions of a "symptom day" given as part of the

contingent valuation experiment, it seems reasonable to interpret

these days as average RADS. 3) The Loehman, et al. (1979)

contingent valuation study provides values for mild and severe

days of several combinations of light symptoms. Since only a

short description of what is meant by mild and severe was given

as part of this experiment, it is somewhat difficult to interpret

these values. A mild day probably corresponds to a day of

discomfort, without any major restriction of activity. A severe

day can either be interpreted as an average RAD, or a more

serious day involving work loss and/or confinement to bed. 4)

The Cropper (1981) health production study can be used to derive

a value for a severe or work loss day (WLD), in theory due to the

actual experienced acute illness or symptoms caused by air

pollution. 5) The study by Gerking and Stanley (1984) also

implies a value for a day of experienced acute illness due to air

pollution. In this case, it is not clear what severity of a day

is relevant, though Gerking and Stanley (p.24) suggest that

interpreting it as an average RAD may be appropriate.

The severity of day valued in the above studies can be

broken down into three classes: a severe work loss day, an

average restricted activity day, and a mild day of discomfort

alone. Interim values for each level of severity are presented

in Table 2-17. A consideration in reporting this range of values

is the information available or likely to be available linking

air pollution to acute morbidity. For example, the study by

Ostro (1981) relates air pollution to WLDs, so a value of a WLD

is required to use this study in benefit cost analysis. On the

other hand, the study by Portney and Mullahy (forthcoming)

relates air pollution to RADs, so a different set of values is

needed. Future work, such as that by the Rand Corporation using

data from the National Health Insurance Experiment, may link air

pollution to still different severity of days, such as a mild day

involving discomfort, or allow the linking of air pollution to a

specific symptom. The range of days valued is limited, however,

by the existing data.

2-144
It is useful to make a preliminary judgement as to how the

values of different severities of days may compare. This

comparison allows a more efficient use of the available evidence:

if we know how the value of a WLD is related to a value of a RAD,

we can use an estimate of the value a WLD as corroborative

evidence on the value of a RAD, and vice versa. While the

relationship cannot be specified exactly, useful evidence

comparing different severities of symptom days comes from

Loehman, et a1.(1979). Respondents placed values on one day,

seven days, and ninety days of mild and severe symptoms; the

median value for severe is always between two and three times the

median value for mild. Unfortunately, as noted above, it is not

clear if a severe day should be interpreted as a an average RAD

or a WLD. As a compromise, it can be assumed that a severe day

as defined by Loehman et al. is intermediate in severity between

an average RAD and a WLD.

In the preparation of interim values, the rule of thumb

roughly applied is that relief from an average day (a RAD) should

be valued about twice as much as a mild day (discomfort); and

relief from a severe day (a WLD) is twice as valuable as relief

from an average day. This allows for a slightly larger variation

in values from mild to severe than found by Loehman et al. It

should be re-emphasized that this rule of thumb is not used to

derive the values for different severities, but used to allow

some sort of meaningful comparisons between the different

studies, for corroborative purposes.

Independent Symptoms-Average Severity

In the interim values presented in Table 2-17, six different

sets of estimates are provided for the values of an average day

(RAD) of acute morbidity due to air pollution. The first five

sets are for fairly specific symptoms. These estimates are

derived principally from the Tolley, et al. (1985) contingent

valuation experiment, with corroboration from Loehman et al.

(1979) when possible. As can be seen in Table 2-14, these

estimates from contingent valuation are complete measures of the

value of health.

The values from Tolley, et al. are used as follows. The

mean values based on the sample including all plausible nonprotest bids are presented in Table 2-14: $35 for a day of sinus

problems, $29 for throat, $25 for a day of coughing or

respiratory problems, $28 for a day of eye irritation, and $40

for a day of headaches. These means are seen as medium

estimates. Examination of the median values, the range of

values, and other aspects of the distribution of values from the

Tolley et al. study is also taken into consideration in the

general process of forming the range of values. These

considerations suggest that for the Tolley et al. results the

mean value is the most robust estimate of an average individual's

willingness to pay.

2-145
Estimates from the Loehman et al. (1979) contingent

valuation study can be used as corrobarative evidence. They are

not exactly comparable, however, for several reasons. First, the

average day valued in Tolley et al. may be somewhere between the

mild days and the severe days valued in Loehman et al., in terms

of severity. Also, the Loehman et al. values are for

combinations of symptoms, none of which are exactly the same as

what is valued in Tolley et al., though several are similar. For

instance, a mild day of coughing/sneezing is valued at $4, a

severe day at $11; and a day of shortness of breath is valued at

$8 for mild, and $18 for severe.

These values can be compared to the Tolley et al. values for

a day of coughing, at $25 from above. The difference in the

values stems from Loehman et al. 's use of median values. Using

median values is generally not appropriate, given the methodology

of benefit cost analysis. It should be recognized that in a

random sample or the entire population, it is reasonable that

some individuals will place very high values on their health. In

standard benefit cost analysis, justified by the potential Pareto

improvement criterion, all individuals' values should be given

equal weight, even if the values are far above the average. If

median values are used, however, the values of people with high

values are implicitly given very little weight. So though

reporting median bids avoids overstating values due to the effect

of very high bids which may be inaccurate (i.e., not a true

reflection of willingness to pay), legitimately high bids are

also given little weight.

If it seems likely that high bids have less informational

content than lower bids, as seems to be the case for the Loehman

et al. study, the median may be a more robust measure of an

average person's willingness to pay than the mean. However,

since legitimately high bids may also exist, medians are judged

as likely to be underestimates of the values desirable for

benefit cost analysis.

The median bids from Loehman et al. are used principally in

the development of the low range of estimates, though some small

weight is placed on these values in the (subjective) calculation

of medium estimates. Some weight is also placed on the mean

values from Loehman etal., which are much closer inmagnitude to

the Tolley et al. estimates. The outlier problem Loehman et al.

describes indicates these means are overestimates, so only a

small weight is placed on them as well.

The interim values, based on the above considerations, for

average days of specific symptoms are as follows: sinus at

$2O(low), $35(medium), or $60 (high); throat at $10, $25 or $40;

respiratory symptoms at $15, $30, or $50; eye irritation at $20,

$40, or $100; and headache at $30. S50, or $110. The low,

medium, and high estimates reflect the considerations described

above, as well as some feedback from the development of

additional values that follow.

2-146
Symptom Combinations-Average Severity

In addition to valuing a day of specific symptoms, the

evidence in Table 2-14 supports estimates for an average RAD due

a likely combination of symptoms that could result from air

pollution. In this case, relevant estimates come from the cost

of illness approach, health production studies, as well as

contingent valuation studies. For a RAD due to an average case

of acute respiratory illness, the cost of illness approach

suggests a value of $35. This may be an overestimate of the

medical expenditures and foregone earnings due to an air

pollution related illness, since this average includes the

influence of severe acute respiratory illnesses (e.g.,

pneumonia). However, the average is dominated by a large number

of upper respiratory infections, which are presumably similar to

air pollution related symptoms.

In addition, the cost of illness estimate is not a complete

measure of the value of morbidity, since it fails to value

discomfort, time lost from non-paid activities, and preventive or

averting expenditures. The $35 estimate is used as a lower

bound, or low value estimate. It has been suggested that a cost

of illness (COI) value can be multiplied by a rough adjustment

factor to approximate a conceptually complete willingness to pay

(WTP) value. Rowe and Chestnut (1984) find WTP/COI ratios of 1.6

to 3.7, for asthma symptoms; Tolley et al. find much larger

ratios from about 3 up to 50, depending on the symptom (some

ratios based on very small sample sizes). Using a fairly

conservative ratio of 2 suggests that a true value would be $70

per average day of respiratory illness. This value is used as

one input in the development of the medium estimate.

Willingness to pay estimates from health production models

in principle value the health effects actually due to existing

levels of air pollution. Theoretically, the Gerking and Stanley

(1984) estimate of $40 includes all aspects of the value of

health, but due to data limitations this figure is probably more

illustrative of the order of magnitude than of the exact value.

The Cropper (1981) estimate of $176 is derived from a theoretical

model that assumes discomfort and medical expenses were

negligible, and in addition relied on the use of specific

functional forms. Thus it also is probably more indicative of

the order of magnitude. It applies to a severe work loss day,

but if it is scaled down by one-half to none-third, it yields a

value of $50 to $80 per restricted activity day. These values

serve a's additional inputs in the development of the medium

estimates.

The final estimates relevant to the value of an average day

of a likely combination of symptoms come from the contingent

valuation studies. In using these values, it is necessary to

make a judgem'ent as to which symptoms are most likely. Based

mainly on the dose-response literature, sinus, throat, and

2-147
respiratory symptoms seem likely, with some possibility of

headache and eye irritation. Since it seems relatively unlikely

that all five symptoms would occur in combination is a single

day, the value of sinus, throat, and cough combined from the

Tolley et al. study is used as proxy for any two or three likely

symptoms. The mean bid is $66, which is used as an input in

forming the medium value. Medians and other information on the

distribution of values are taken into consideration. The values

from Loehman et al. serve as inputs in forming the low estimates.

The interim values for an average RAD due to a likely combination

of acute symptoms are $35 (low), $50 (medium), and $100 (high).

Severe Symptoms

There is relatively little information from which to develop

interim values for a severe or work loss day of acute symptoms.

As a definite lower bound, such a day should be valued at the

earnings foregone, which on average would be roughly $80 a day.

The health production model developed by Cropper (1981) indicates

that this figure should be doubled to include the value of

preventive or averting expenditures, implying a value of $176 for

the typical wage rate she uses in her illustrative example (in

1984 $). The rough rule of thumb that a severe WLD should be

valued at twice the value of an average RAD supports this range.

So the interim values of a severe WLD due to a likely combination

of symptoms are $80 (low), $125 (medium), and $175 (high).

Mild Symptoms

To form interim values for a mild day of a likely

combination of symptoms is also difficult. The only direct

evidence is from the contingent valuation study by Loehman et al

(1979). The value estimates should be relatively complete, but

are of somewhat questionable reliability. For combinations of

mild symptoms, the median values reported by Loehman et al range

from $4 to $8. The mean values for these combinations range from

about $40 to about $80. As mentioned above, it is felt that the

medians are probably underestimates, but the means may be

overestimates, so the medium value for a mild day of a likely

combination of symptoms should fall in the middle of this range.

Applying the rough rule of thumb that a mild day should be valued

at about one-half an average RAD indicates this range is

reasonable. So the interim values for a mild day of discomfort

due to a likely combination of symptoms are $10 (low), $25

(medium), and $50 (high).

2.9.3.4. Aggravation of Previously Existing Chronic Morbidity

To move on from acute or short-term health effects, the

second major class of health effects to be valued is the

aggravation of previously existing chronic morbidity. Air

2-148
pollution may have its most significant impacts on those already

with certain chronic conditions, so a change in air pollution

could cause either a marginal change in time spent ill (e.g., one

day), or possibly a non-marginal change (e.g., a ,week or more).

However, due to fact that very little support has been found for

a link between air pollution and a large change in time spent

ill, and due to the limited information on the value of such

time, interim values are only developed for an additional day of

morbidity for those with previously existing chronic conditions.

Two types of chronic conditions are considered: lung and heart.

Lung Conditions

Chronic lung conditions likely to be aggravated by air

pollution include the very serious illness emphysema (or chronic

obstructive pulmonary disease), and the less serious

asthma/bronchitis. To value an additional day of symptoms due to

these conditions, the evidence on the value of acute respiratory

illness is clearly relevant. The per day values for the chronic

lung conditions should be higher than the per day values for

acute respiratory symptoms, for two reasons. First, a symptom day

is likely to be more severe for a person with a chonic illness.

Thus, only the values of an average RAD and the values of a

severe WLD from the acute values are likely to relevant for

valuing chronic illness. Second, economic theory suggests that

the marginal utility of health should be diminishing, so the

marginal disutility of sickness should be increasing. The

implication is that an individual who already experiences many

sick days should value a change at the margin higher than an

individual who experiences few. Support for this relationship is

found in Tolley et a1.(1985) and other contingent valuation

studies. So even the values for a severe day of symptoms for a

healthy individual may be too low compared to how an individual

with a chronic condition would value the same change.

The available evidence on the value of chronic morbidity is

presented in Table 2-15, and will be referred to in the ensuing

discussion.

Emphysema

For the value of an additional day of emphysema, there are

several pieces of evidence. From the results of the Tolley et

al. (1985) contingent valuation study, regressions were estimated

that relate the bids (values for a day of relief) to various

explanatory variables, including overall health status and the

individual's experience with the symptom. Though these results

are based on a sample of people with normal health, predicted

values for a chronically ill individual can be calculated by

evaluating the regression equation to correspond to someone with

a chronic condition. Thus the dummy variables were set to

indicate that the overall health status is low, and the

experience with the symptom is set at 36 days, the average number

2-149
of RADs for an individual with emphysema, according to the Health

Interview Survey. This exercise results in predicted values from

$80 to $330 for single symptoms, and about $300 for a combination

of symptoms. That the predicted value for the combination of

symptoms is lower than the predicted value for relief from eye

irritation is not expected, and is indicative of the degree of

confidence that can be attached to these results. Nevertheless,

they do give some indication of the value a chronically ill

person might place on relief from an additional day of illness,

and help to quantify the degree to which the values a day of

acute illness understate the values of an additional day of

emphysema.

Another piece of evidence on the value of an additional day

of emphysem symptoms comes from the Freeman et a1.(1975) cost of

illness study. This study implies that an average case of

emphysema involves $3194 of medical expenditures and foregone

earnings, or an average of about $88 per restricted activity day

due to emphysema. It is impossible to determine how this average

cost of illness compares to marginal cost of illness, or what is

actually relevant, willingness to pay for a marginal change in

days spent ill. Assuming average and marginal cost of illness

are similar, this average figure should be an underestimate of

the willingness to pay, and applying the adjustment factor of two

suggests that relief from a day of emphysema may be worth about

$180.

The values for an additional day of emphysema available

produce a rather wide range. On the low side, the value should

be bounded by the value of an average or severe day of acute

respiratory symptoms (medium interim values for these are $60 and

$125, respectively). On the high side, the predicted values from

Tolley et al. exceed $300. The interim values for the

aggravation of emphysema (per day) are $50 (low), $100 (medium),

and $300 (high).

Asthma/Bronchitis

To value an additional day of asthma/bronchitis, it is again

possible to use the values of a day of acute respiratory illness.

In this case, since asthma/bronchitis are less serious chronic

conditions than emphysema in general, the values for acute

illness may be more useful. For the same reason, however, it was

not possible to use the Tolley et al. (1985) estimated bid

function to predict values for a day of asthma/bronchitis

symptoms different than the values for acute symptoms.

Direct evidence on the value of relief from asthma is

available from the Rowe and Chestnut (1984) contingent valuation

study. In this study, about 80 asthmatics were asked their

maximum willingness to pay to have the number of "bad" days they

actually experienced reduced by 50 percent. The average bid is

$401, for an average reduction of about 19 days. On average,

then, a bad day of asthma is valued at about $20. How this

2-150
average value compares to the willingness to pay to avoid a

marginal change can not be determined. Based on the results for

the value of a day of acute respiratory symptoms, this $20 amount

seems low, perhaps because it is an average for 19 days rather

than a bid by a person with chronic asthma/bronchitis for a day

of relief atthe margin.

The interim values for an additional day of

asthma/bronchitis symptoms are set at $35 (low), $60 (medium),

and $100 (high).

Heart Conditions

Some evidence suggests that air pollution may aggravate

existing chronic heart conditions, perhaps causing an individual

with heart disease to experience angina pectoris (chest pains).

The main evidence on the value of this type of symptom is found

in the Tolley et a1.(1985) contingent valuation study on angina.

In this experiment, individuals who on the whole had little

experience with heart conditions were asked to value relief from

additional days of angina, given that they already experienced

(were endowed with) various numbers of days of the condition.

For a day of mild angina, the means ranged from $66 to $99,

depending upon the endowment. For a day of severe angina., the

means ranged from $124 to $279. It is not clear if air pollution

would cause mildor severe angina. It is also notclearwhatthe

average experience of angina would be for the individuals

affected by air pollution, so it is not possible to narrow the

range of values much.

Potentially useful additional evidence is found in the

Hartunian et a1.(1981) cost of illness study. Their calculations

suggest that an average case of uncomplicated angina pectoris

involves about $600 of medical expenditures and foregone

earnings. It is not possible to discover how many symptom days

this average case involves, though, so this figure can not be

directly compared to the per day values from Tolley, et al.

With relatively little evidence available, a fairly wide

range of interim values for an additional day of angina are

developed: $75 (low), $150 (medium), and $400 (high).

Likely Combination of Lung and Heart Conditions

Depending on the data linking air pollution to health, it

may be known only that air pollution has aggravated chronic

illness, without specifying which illnesses. Thus, values for

the aggravation of a likely combination of chronic lung and heart

conditions are also needed. To form these values, the basic

inputs are the interim values for the separate conditions. These

are combined with the judgement that the majority of chronic

conditions aggravated will be asthma/bronchitis, with emphysema

being the next most likely chronic conditfon affected, and only a

small number of heart conditions relevant. Thus the interim

2-151
values for an additional day of a likely combination of symptoms

due to chronic lung and heart conditions are $45 (low), $80

(medium) and $190 (high).

2.9.3.5. Inc,reased Incidence of Non-fatal Chronic Morbidity

In addition to the aggravation of previously existing

chronic conditions, it is possible that air pollution will cause

new cases of chronic conditions. This is an explanation as to

why air pollution is linked with higher mortality rates, and if

air pollution is causing fatalities associated with chronic

illness, it presumably accounts for an increased incidence of

non-fatal chronic conditions. Of course, ex ante it is

impossible to distinguish conditions

fatal from those that will not,

that will eventually be

but it is useful analytically to

first consider the value of the morbidity alone, and then

consider the morbidity that precedes mortality. So this section

focuses on valuing one year of a case of non-fatal chronic or

serious illness. First respiratory conditions are discussed, and

then heart conditions.

Lung Conditions

Emphysema

The main piece of evidence on the value of a case of

emphysema is the estimate from Freeman et al. (1975) that on

average a case involves $3194 of medical expenditures and

foregone earnings a year. Using the adjustment that a complete

willingness to pay measure is at least twice the cost of illness

measure of medical expenditures and foregone earnings suggests

that a a case of emphysema may be valued at around $6500 a year.

Evidence to corroborate the cost of illness value is slim.

Since a case of emphysema will involve on average at least 30

days of restricted activity (see NCHS estimates), the values for

30 days of symptoms from the Tolley et al (1985) contingent

valuation study may be relevant. This study found mean values of

$166 to almost $500 for 30 days of a single symptom, and a mean

value for 30 days of coughing, throat, and sinus symptoms

combined is $625. That these values are considerably below even

the pure cost of illness estimate for a case of emphysema

probably stems from two factors. First, 30 days of symptoms were

beyond the experience of most of the respondents in the Tolley et

al. study, and a general result found in contingent valuation

experiments is that the values for unfamiliar goods may be

inaccurately reported. Second, the symptoms in the Tolley et al.

experiment are probably much less serious symptoms than those

experienced by an individual with emphysema, particularly one at

an advanced stage of the disease. Not much weight can be

attached to the Tolley et al. results, then, in forming a value

of a case of emphysema. The same problems apply to the Loehman

et al. (1979) contingent valuation results on the value of ninety

2-152
days of symptoms.

The interim values for one year of a case of emphysema thus

mainly come from the cost of illness estimate, with the range

developed considering what reasonable adjustment factors might

be: $3200 (low), $7000 (medium), and $10,000 (high).

Asthma/Bronchitis

Direct evidence on the yearly value of a case of

asthma/bronchitis is found in the Rowe and Chestnut (1984)

contingent valuation study. As described above, the mean bid for

a 50 percent reduction in the number of "bad" days a group of

asthmatics actually experienced is about $400. As a very rough

approximation, then, elimination of a case of asthma for a year

could be valued at $800 or above, since elimination would involve

a 100 percent reduction in the number of bad days as well as

reducing the number of days the individuals suff.ered from less

serious asthma symptoms. Clearly, this extrapolation can not be

rigourously justified. In addition, the Rowe and Chestnut study

may not be typical for asthma in general. In this study, the

participants evidently suffered from fairly severe cases of

asthma; for instance, the average number of bad days of asthma is

76. The NCHS estimates on the basis of the Health Interview

Survey that asthma involves only 15 restricted activity days per

conditon per year, and only 0.8 work-loss days per condition per

year. So the estimate of $800 a year for a case of asthma based

on the sample of individuals in the Rowe and Chestnut study may

overstate the value of an average case of asthma.

Additional evi,dence on the value of a case of

asthma/bronchitis is available from a comparison with the value

of a day of acute illness. Since asthma/bronchitis are

relatively less serious chronic conditions (compared to emphysem,

for example), these values may be fairly appropriate. As above,

the NCHS estimates that an average case of asthma involves 15

RADs, it also estimates that an average case of chronic

bronchitis' involves 7.5 RADs. Using the medium interim value for

a day of a likely combination of respiratory symptoms ($60), and

multiplying by 7.5 to 15 yields a range of $450 to $900. This

range may be low since a chronic illness is generally more severe

and relief valued more highly than an acute illness. The results

from the contingent valuation studies of Loehman et al. and

Tolley et al. are also of interest. The median values reported

by Loehman et al. for a week of symptoms are all well under $100

dollars, and even doubling these values to approximate the value

of 15 days of symptoms yields at most a value of $114. Judging

that these median values are too low, the mean values from this

study can also be examined, yielding much higher values. The

Tolley et al. study values 30 days of symptoms alone and in

combination from $167 to over $800. This implies that 15 days

(to correspond to asthma) might be valued at $80 to $400, or 7.5

days (to correspond to bronchitis) at $40 to $200. Again, since

these values correspond to acute illness, they may in general be

2-153
too low.

Based on consideration of the above evidence, the interim

yearly values for a case of asthma are $200 (low), $900 (medium),

and $1200 (high).

Lung Cancer

In addition to increasing the incidence of chronic lung

conditions such as emphysema and asthma/bronchitis, it is

possible that air pollution may increase the incidence of lung

cancer. Valuing the small percentage of these cases that will be

non-fatal rests largely on cost of illness estimates. Hartunian

etaL(1981)estimate that the first year of lung cancer involves

almost $30,000 of medical expenditures and foregone earnings.

From separate cost of illness studies (Hodgson and Kopstein

(1984) and Paringer and Berk (1977)) an average case of any

cancer implies costs of almost $10,000. Since lung cancer is

more serious and thus more costly than an average of all cancers

(including a large number of relatively non-serious neoplasms of

the skin), the $30,000 seems quite reasonable. Doubling this

estimate to $60,000 may approximate a complete willingness to pay

avoid a case of lung cancer.

Additional evidence that relief from cancer is highly valued

is found in Jones-Lee (1985). As shown in Table 2-16, given a

choice of preventing 100 deaths from either cancer, heart

disease, or motor vehicle accidents, most respondents preferred

to prevent the cancer deaths, and were willing to pay

correspondingly higher amounts to do so on the average. As

Jones-Lee (p.68) concludes, the results suggest that people

"would be willing to. pay very substantial sums to avoid the

protracted period of physical and psychological pain prior to

cancer death." Similarly, the results seem to also imply that

relief from the morbidity associated with even non-fatal cancer

is valued highly. So doubling or even tripling the cost of

illness estimate may be conservative.

The interim values for a case of non-fatal lung cancer are

$30,000 (low), $60,000 (medium), and $100,000 (high).

Heart Conditions

The incidence of non-fatal chronic heart disease may also be

related to air pollution. The least serious condition considered

is "angina pectoris uncomplicated," defined as a case of angina

that does not include more serious aspects of heart disease. On

average, Hartunian et al. estimate that such a condition involves

about $600 of medical expenditures and foregone earnings, which

doubled implies a $1200 willingness to pay estimate of the

complete value of angina.

2-154
Additional evidence comes from the Tolley et al. contingent

valuation study. Mean values range from under $100 for relief

from one day of mild angina, to over $800 for relief from 20 days

of severe angina. The values also depend on the initial

endowment the respondents were asked to imagine they experienced.

For instance, the meanbidto relieve 10 mild days whentheywere

endowed with 10 mild days is about $154. Since the respondents

to this question are "buying" relief from their entire endowment,

this value is in effect the value of a case of angina that

involves 10 mild days. Similarly, this study also implies that a

case of angina involving 10 severe days is worth $262; a case

involving 20 mild days is worth almost $500; and a case involving

20 severe days is worth $844. Without knowing the number and

severity of days a case of air pollution-induced angina involves,

this range can not be narrowed. It should be noted that these

contingent valuation estimates are complete measures of value,

but they may be inaccurate since respondents were relatively

unfamiliar with angina before the experiment.

The interim values for a case of angina pectoris

uncomplicated are $500 (low), $800 (medium), and $2000 (high).

More serious heart disease, involving angina as well as

other complications, may also be caused by air pollution. Again,

evidence on the value of a case of such an illness comes from

cost of illness and contingent valuation estimates. Acton (1975)

estimates that a case of heart disease on average implies $2700

of medical expenditures and foregone earnings. Scitovsky and

McCall (1976) estimate the medical expenditures alone for a

myocardial infarction (a "heart attack") at over $11,000, but

clearly this is one of the most serious outcomes of heart

disease. Acton's estimate is judged to be more representative

for the costs of an average condition. This incomplete value may

be doubled to approximate a complete value measure at around

$5500. Alternatively, Acton's estimate can be combined wtih the

Tolley et al. results on the value of angina. Since angina will

often be one aspect of a serious heart condition, the values

reported above are again relevant, ranging from under $100 to

over $800. These values mainly reflect the value of comfort, and

are little influenced by the costs of illness. So it may be

ap?ropriate to simply add the estimates of the value of angina to

the cost of illness value, suggesting a total value of over $3000

for an average case of heart disease. Prevention of more serious

cases may have amuchhigher value.

Thus the estimates suggest a range of interim values of

$2500 (low), $4000 (medium), and $10,000 (high).

Likely Combination of Lung and Heart Condtions

In case it is known that air pollution increases the

incidence of chronic conditions, but the conditions involved can

not be specified (possibly because of data limitations), interim

2-155
values for an increased incidence of a likely combination of

chronic lung and heart conditions are useful. To develop this

range, the interim values for the specific chronic conditions are

combined with judgements as to which chronic conditions are most

likely to result from air pollution. It seems that the

likelihood of non-fatal conditions is probably inversely related

to the seriousness of the condition: asthma/bronchitis being

least serious and most likely to be caused by air pollution;

emphysema being next most likely; heart disease is judged as

relatively unlikely, with most conditions only involving angina

pectoris uncomplicated; and finally non-fatal lung cancer is

judged as being extremely unlikely. These judgements and the

interim values developed above imply interim values for a likely

combination of lung and heart conditions of $1700 (low), $3800

(medium), and $5900 (high).

2.9.3.6. Increased Mortality Risks

A good deal of evidence suggests that air pollution is

associated with increased mortality rates. Valuing these risks

involves two steps. First, the value of what might be termed

" p u r e '1 mortality risks is estimated. This value corresponds to

the value of an unforseen instant death often estimated in the

"value of life" literature, with no significant morbidity

preceding the death. However, air pollution at the levels found

in the U.S. could not cause such instant death, but instead must

influence mortality rates by increasing the incidence or

aggravating the severity of chronic conditions. So the second

step in valuing the increased mortality risks due to air

pollution is to value different causes of death differently, to

reflect the differences in the morbidity preceding mortality.

A large number of studies, based on revealed preference as

discovered through the hedonic analysis of labor markets or

analysis of consumption activities, and contingent valuation

methods estimate the value of more or less pure mortality risks

or the value of an unforseen instant death (in a statistical

sense). These estimates are reviewed by Blomquist (1982),

Violette and Chestnut (1983), and Jones-Lee (forthcoming).

Updated to 1983 or 1984 prices, all reviews suggest a range from

several hundred thousand dollars per statistical life, to

estimates of over five million dollars per statistical life.

Jones-Lee finds an overall mean of the revealed preference

studies of $2.06 million, and an overall mean of the contingent

valuation studies of $2.35 million. Support for a value of

around $2 million also is found in the Gegax, et al study that

incorporates both wage hedonic analyis and contingent valuation.

So the interim values for an unforseen instant death are $0.5

million (low), $2 million (medium), and $5 million (high).

The low interim values for mortality from specific illnesses

are developed using calculations similar to the "prevalence-based

2-156
approach" to estimating costs of illness. The calculations are

based on the fact that every current death due to a condition is

associated with a much larger prevalence of cases that eventually

will be fatal. For instance, if the average life expectancy with

a certain condition is 10 years, in a given year there will be

one death and 10 person-years of morbidity preceding mortality.

To develop the low interim value for such a death, the value of

10 person-years of morbidity is added to the low value for an

unforseen instant death ($0.5 million). The yearly morbidity

values used are the medium estimates developed for valuing nonfatal chronic conditions. These are conservative values for the

value of morbidity preceding mortality, since eventually fatal

conditions are obviously more serious and thus more costly than

non-fatal conditions. In addition, no allowance ismade for the

psychic costs of imminent death. With these caveats in mind, the

low interim values are $0.64 million for emphysema, $0.53 million

for asthma/bronchitis, $0.58 million for lung cancer, and $0.54

million for heart disease.

In developing the medium and high interim values, the

procedure used to estimate the low values is considered as one

input. However, a major attempt is made to more completely value

the morbidity preceding mortality, Significant evidence are

responses to a questionarre given by Jones-Lee et al (1985),

reported in Table 2-16. One question related to the seriousness

of different types of injury, from losing an eye to being

confined to a wheelchair for life or being permanently bedridden.

Since the study focused on motor vehicle safety, most of the

injuries described are not relevant to the value of chronic lung

and heart conditions. However, as these conditions get

progressively worse (ending in death), they will generally

involve prolonged periods of severe limitations of activity,

possibly to the point of confinement to bed. This type of

outcome is probably most likely with lung cancer and emphysema,

and to a lesser extent heart disease. How people rate being

confined to a wheelchair for life or being permanently bedridden

in the Jones-Lee et al survey is therefore relevant to the

morbidity preceding mortality associated with lung cancer,

emphysema, and heart disease. Jones-Lee et al found that about

one-half of the sample of about 1000 individuals felt that being

confined to a wheelchair was as bad or worse than death. Over

one-half felt that being permanently bed-ridden was as bad or

worse than death, with almost one-third (30%) ranking it worse

than death. If these outcomes are viewed as at least as bad as

death, it seems reasonable that an individual would be willing to

pay to change the risks of these outcomes approximately the same

amount .he would be willing to pay to change mortality risks.

This implies that the total value of a death from lung cancer of

emphysema may be twice the value of an unforseen instant death.

The value of a death from heart disease, possibly involving a

smaller but still significant degree of restriction of activity,

should also be valued a great deal higher than an instant death.

A death from asthma/bronchitis may involve much less restricition

of activity, so its value may be much lower than that of the

other conditions.

2-157
TABLE 2-16

VALUES OF DIFFERENT KINDS OF MORTALITY

Comparing Causes of Mortality

(Source: Jones-Lee (1985)

Cause of Death Prefer to have

Reduced (%)

Mean WTP

For reduction in

(British pounds)*

Deemme--a-e--e- _------------- -------------------

Motor Accidents 11 7.35 million

Heart Disease 13 13.23 million

Cancer 76 23.12 million

*Value is a single payment to reduce the number of deaths from

these causes by 100 next year. Value is not a value of

statistical life.

2-158
TABLE 2-16

(Continued)

SERIOUSNESS OF DIFFERENT TYPES OF INJURY

Type

Lose an eye 92.1 5.0 2.8

Badly scarred

for life, and in

a hospital for

. a year

87.5 7.7 4.7

Confined to

a wheelchair

for the rest

of your life

48.6 27.7 23.8

Permanently

bedridden

36.7 33.4 30.0

(source: Jones-Lee (1985))

Not as bad As bad Worse than

as death (%) as death death

_-_--__-___-_-_-----_________c__________-------

2-159
More evidence from Jones-Lee et al is available on the

relative values of deaths from cancer, heart disease, and

unforseen instant death (specifically, death from motor vehicle

accidents, which are assumed to be instant). As described above,

when asked to choose between preventing 100 deaths from these

causes, a large majority (76%) chose to prevent the deaths from

cancer, indicating that relief from the morbidity associated with

cancer is valued highly. The differences can be quantified to

some extent by examining the amounts people were willing to pay

to prevent the 100 deaths from the different causes. While the

question is not worded so as to elicit the value of a statistical

life, the amounts should indicate the relative values for the

three causes. The means of the responses indicate that

preventing 100 deaths from heart disease may be worth almost

twice what preventing 100 instant deaths is. Preventing 100

cancer deaths is valued at about three times the value of 100

instant deaths. This is additional evidence that doubling or

even tripling the value of an instant death may approximate the

value of a death from cancer or heart disease.

The medium and high interim values for a death from

emphysema, asthma/bronchitis, lung cancer, and heart disease are

based on considering the value of a similar non-fatal condition,

and the evidence from Jones-Lee et al suggesting how the value of

an instant death may relate to the value of a deathprecededby a

prolonged period of morbidity. The low interim values are

prepared as described above, using a "prevalence-based" approach.

The interim values are: a death from emphysema at $0.64 million

(low), $3.5 million (medium), and $9 million (high); a death from

asthma/bronchitis at $0.53 million, $2.5 million, and $5.5

million; a death from lung cancer at $0.58 million, $4 million,

and $10 million; and a death from heart disease at $0.54 million,

$3 million, and $7 million.

It is particularly important to have a value for an

"average" death due to air pollution, since most studies linking

air pollution and mortality rates do not specify the diseases

responsible for the increased mortality. Thus we derive a value

that is a weighted average of the value of all causes of death

likely to be related to air pollution. In this case, the weights

attached are directly related to the seriousness of the

condition. Lung cancer is judged as causing the majority of the

increase in mortality, with heart disease and emphysema also

being signficant. A low weight is attached to asthma/bronchitis,

since fatalities from these conditions seem unlikely, and no

weight is placed on the value of an unforseeninstantdeath. The

interim values for a weighted average of all causes of death are

$0.58 million (low), $3.8 million (medium), and $9.4 million

(high).

2-160
TABLE 2-17

INTERIM 'VALUES FOR MORBIDITY AND MORTALITY EFFECTS

OF AIR POLLUTION

---- -- Category

Value Estimate

--- Low Medium m-m--- -- HighAcute or short-term

-------- morbidity

average day (restricted

activity day):

--sinus

--throat

--respiratory symptoms

--eye irritation

--headache

--likely combination 35 60 100

severe day (work loss

day):

--likely combination 80 125 175

mild day (discomfort):

--likely combination 1 0 25 50

Aggravation of previously

existing chronic morbidity

her-- --day1

lung conditions:

-- emphysema

__ asthma/bronchitis

heart conditions:

--angina, possibly with

other heart disease

--likely combination of

lung and heart

$20 $35 $60

1 0 25 40

15 30 50

20 40 100

30 50 110

50

35

75

45 80

2-161

100 300

60 100

150 400

190
TABLE 2-17

INTERIM VALUES FOR MORBIDITY AND MORTALITY EFFECTS

OF AIR POLLUTION

(continued)

---- -- Category

Value Estimate

--- Low Medium ------ -- HighIncreased Incidence of

--------- Non-fatal Chronic Morbidity ------- --------

lper-- ---- case per -- --- year1

lung conditions:

--emphysema

-- asthma/bronchitis

--lung cancer

heart conditions:

--angina uncomplicated

-- other heart disease

--likely combination of

lung and heart

--unforseen instant death

-- emphysema

__ asthma/bronchitis

--lung cancer

--heart disease

--weighted average of

all causes

$3,200 $7,000 $10,000

200 900 1,200

30,000 60,000 100,000

500 800 2,000

2,500 4,000 10,000

1,700 3,800 5,900

.5 mill. 2 mill. 5 mill.

.64 m 3.5 m 9m

.53 m 2.5 m 5.5 m

.58 m 4 m 10 m

.54 m 3 m 7 m

.58 m 3.8 m 9.4 m

2-162
2.9.3.7. Using the Interim Values in Practice

To illustrate the usefulness of the interim.values, this

section calculates the benefits of a hypothetical program

improving air quality in some certain area. To focus on the

problem of valuation, suppose the health effects of the program

are know (either from health econometrics estimates or doseresponse relationships), and the question that remains is how the

value the effects. Amedium or best estimate of the value of the

effects uses the medium interim values from.Table 2-17 for the

relevant categories. For acute or short-term illness, it is

estimated that the program will reduce the number of restricted

activity days experienced by the general population by 1000

person-days. Using the medium interim value for a likely

combination of symptoms, each of these days is worth $60, so the

total value of the change in acute illness is $60,000. The

program will also improve the health of sensitive populations by

reducing the extent to which air pollution aggravates existing

chronic lung and heart conditions. Some of those with emphysema

will experience fewer symptom days, for a total of 200 person

days of relief. Each of these days is given a medium value of

$100. For those with asthma/bronchitis, 300 person days of

relief result from the program, and each of these days are valued

at $60. Finally, those with existing heart conditions experience

a total of 100 fewer days of angina, valued at $80 each. Thus

the total value of the reduced aggravation of existing chronic

conditions is: (200 x $100) + (300 x $60) + (100 x $80) -

$46.000. In addition, the incidence of chronic lung conditions

is reduced as a result of the program. In one year, with the

program, there are 10 fewer new non-fatal cases of emphysema than

there would have been without the program. Valuing each case at

the medium value from Table 2-17 gives that this change is worth

10 times $7000, or $70,000. The program also results in a

reduction of 20 non-fatal cases of asthma/bronchitis, valued at

$900 each for a total of $18,000. Finally, in a given year the

mortality due to lung cancer is reduced by two deaths, each

valued at $4 million.

The value of the health effects from this hypothetical

program can be summarized as follows. The reduction in acute

morbidity that results from the program is valued at $60,000.

The reduction in aggravated chronic morbidity is valued at

$46,000. The reduction in the incidence of non-fatal chronic

conditions is valued at $88,000. The two statistical lives saved

are valued at a total of $8 million. So the total value of the

program, using the medium interim values, is $8.134 million.

In a benefit cost analysis of the hypothetical program, then

the health effects resulting imply benefits of over $8 million.

Any other benefits should be added to this value, and then the

costs can be compared to the benefits to see if the program is

justified. To check the sensitivity of the decision to the

health benefits estimate, alternative estimates of the health

effects could be computed using the low and high interim values

2-163
from Table 2-17. In practice the health effects would not be

known with certainty so a range of health effects possible could

be given a range of values for the sensitivity analysis.

Though the above exercise is entirely hypothetical, it does

illustrate the use of the interim values. In addition, it is

interesting that the change in mortality risk dominates the total

of the value of health effects, even though only two deaths were

prevented. This is likely to be a fairly general result, because

the value of mortality risks is so many orders of magnitude above

the values of morbidity. This suggests that the emphasis that

has been placed on linking air pollution to mortality may not be

inappropriate, because of the importance of mortality, in both

dollars amounts and in human terms.

2-164
Final Report

VALUATION OF REDUCTIONS IN HUMAN HEALTH

SYMPTOMS AND RISKS

Volume 3

CONTINGENT VALUATION STUDY OF LIGHT SYMPTOMS AND ANGINA

George Tolley

Lyndon Babcock

and

Mark Berger

Anthony Bilotti

Glenn Blomquist

Michael Brien

Robert Fabian

Gideon Fishelson

Charles Kahn

Austin Kelly

Don Kenkel

Ronald Krumm

Tracy Miller

Robert Ohsfeldt

Sherwin Rosen

William Webb

Wallace Wilson

Martin Zelder

The University of Chicago

Cooperative agreement between the University of Chicago and the

U.S. Environmental Protection Agency with participation by University

of Illinois at Chicago, University of Kentucky and University of

Wyoming.

USEPA Grant #CR-811053-01-0

PROJECT OFFICER: Dr. Alan Carlin

Office of Policy Analysis

Office of Policy, Planning and Evaluation

U.S. Environmental Protection Agency

Washington, D.C. 20460

January 1986
DISCLAIMER

Although prepared with EPA funding, this

report has neither been reviewed nor

approved by the U.S. Environmental

Protection Agency for publication as an EPA

report. The contents do not necessarily

reflect the views or policies of the U.S.

Environmental Protection Agency, nor does

mention of trade names or commercial

products constitute endorsement or

recommendation for use.
VALUATION OF REDUCTIONS IN HUMAN HEALTH SYMPTOMS AND RISKS

This is Volume 3 of a four volume report. The total project

undertakes an assessment and reconciliation of attempts to value

reductions in human health risks, and it develops new methods and

estimates for these values. Volume 1 is the executive summmary.

Volume 2 contains a comparative assessment of work on valuing

health risks. Based on the assessment, a set of interim

morbidity and mortality values applicable to effects of criteria

air pollutants is developed. Volume 3 reports on a study

developing and applying contingent valuation techniques to the

types of light symptoms often attributed to air pollution.

Volume 4 reports on the design of approaches for valuing serious

or life threatening illnesses.

Abstract of Volume 3

CONTINGENT VALUATION STUDY OF LIGHT SYMPTOMS AND ANGINA

Volume 3 reports on a contingent valuation study conducted

as part of this project to estimate the benefits of light symptom

reductions and angina relief. The approach is based on focus

group experimentation followed by systematic household sampling.

Section 3.2 addresses the problem of quantifying reductions

in symptoms. To cover the range of conditions encountered in

environmental assessments, respondents needed to be asked about a

variety of situations, but the variety had to be manageable.

Four survey instruments were used. Two of the instruments were

for relief from seven light symptoms, with one instrument pertaining to one day of relief and the other to thirty days of

relief. Two of the instruments were for relief of angina, with

one of these pertaining to ten days of relief and the other to

twenty days.

Sections 3.3 and 3.4 explain the structure of the contingent valuation instrument. Section 3.5 explains the household

sampling procedure, which was carried out in Chicago and Denver.

In Section 3.6 the empirical results are presented. A relationship was found between the number of days a symptom is

experienced and the bid per day, indicating the existence of

increasing marginal disutility of symptoms. Independent variables in regressions explaining bids included age, education and

income, and these generally had postive coefficients.

Section 3.7 reports the results of an experimental mail

survey where a response rate of 48 percent was achieved. Results

were corroborative of the household surveys.
TABLE OF CONTENTS

Volume 3: Contingent Valuation Study of Light Symptoms

and Angina

List of Tables

3.1 Introduction 3-1

3.1.1 Purpose 3-1

3.1.2 Major Issues in Contingent Valuation 3-2

3.1.3 Previous Contingent Valuation Work on

Morbidity 3-5

3.1.4 Outline of Remainder of this Section 3-6

3.2 The Dose-Response Problem and the Definition of

Symptom Relief 3-7

3.2.1 Implications of Dose-Response

Relationships for Benefit Estimation 3-7

3.2.2 Effects of Criteria Pollutants on Health 3-8

3.2.3 Light Symptom Relief in the Present

Study 3-24

3.2.4 Angina Relief in the Present Study 3-25

3.3 Design of Questionnaire in Light of Focus Group

Experience 3-34

3.3.1 Overview 3-34

3.3.2 Contingent Valuation Product 3-34

3.3.3 Bidding Framework 3-35

3.3.4 Health Status 3-37

3.3.5 Respondent-Interviewer Interaction 3-37

3.3.6 Length of Interview 3-38
3.4 Structure of CV Instrument 3-39

3.4.1 Seven Symptom Health Questionnaire: 1

Day

3.4.2 Seven Symptom Health Questionnaire: 30

Days

3.4.3 Angina Health Questionnaire: 10 Days

3.4.4 Angina Health Questionnaire: 20 Days

3.5 Household Sampling

3.5.1 Sampling Procedures

3.5.2 Sample Size and Editing

3.6 Empirical Results From Household Personal

Interviews

3.6.1. Introduction

3.6.2 Seven Symptoms: One Day Relief

3.6.3 Seven Symptoms: Thirty Days Relief

3.6.4 Angina: Ten Days Relief

3.6.5 Angina: Twenty Days Relief

3.6.6 Summary and Implications

3.7 Mail Questionnaire

3.7.1 Background

3.7.2 Design of the Mail Survey

3.7.3 Sample and Response Rate

3.7.4 Results of the Survey

3.7.5 Demographics

3.7.6 Summary of Results

3.8 Appendix. Field Questionnaires for Light

Symptoms and Angina

3-39

3-44

3-44

3-45

3-47

3-47

3-47

3-49

3-49

3-52

3-59

3-66

3-72

3-78

3-79

3-79

3-79

3-80

3-80

3-89

3-95

3-97
List of Tables

Table 3-1

Table 3-2

Table 3-3

Table 3-4

Table 3-5

Table 3-6

Table 3-7

Table 3-8

Table 3-9

Table 3-10

Table 3-11

Table 3-12

Table 3-13

Table 3-14

Table 3-15

Table 3-16

Table 3-17

Table 3-18

Table 3-19

Table 3-20

Table 3-21

Dose-Response Relationships for CO

Dose-Response Relationships for Ozone

Dose-Response Relationships for

Dose-Response Relationships for Particulates

Means and Standard Deviations for Seven

Light Symptom One Day Survey

Seven Light Symptom One Day Survey Regression

Results, Parameter Estimates

Means and Standard Deviations for Seven

Light Symptom Thirty Day Survey

Seven Light Symptom Thirty Day Survey

Regression Results, Parameter Estimates

Means and Standard Deviations for Angina

Ten Day Survey

Angina Ten Day Survey Regression Results,

Parameter Estimates

Means and Standard Deviations for Angina

Twenty Day Survey

Angina Twenty Day Survey Regression Results,

Parameter Estimates

Whether Ever Experienced Symptom

How Much Symptom Bothers the Respondent

Willingness to Pay per Month to Eliminate

3 Symptom Days per Month

Reasons for Willingness to Pay Amounts

Mean Incidence of Symptom Days, Mean

Days Lost, Mean Earnings Lost, and Mean

Medical Care Expense, Last 12 Months

Age Distribution of Respondents

Education of Respondents

Number of Persons Living in Household

Household Income in 1983

3-12

3-16

3-19

3-23

3-53

3-56

3-60

3-63

3-67

3-70

3-73

3-76

3-81

3-82

3-85

3-86

3-88

3-90

3-91

3-93

3-94
3.1. INTRODUCTION

3.1.1. Purpose

The purpose of this section is to describe and explain the

methods that were developed to estimate the value of reducing

light symptoms attributable to air pollution. Intensive study of

the effects of air pollution on human health has been underway

for a number of years. Epidemiological and econometric studies

are amassing evidence on the mortality effects of sulfur oxides

and particulate. Much less attention has been paid to morbidity

effects of air pollution and the economic value of avoiding these

effects. Progress is being made, however, in establishing the

health effects of pollutant exposures regularly experienced by

large population groups, and economists have begun to turn their

attention to estimating the achievable benefits of reduced

illness. This is an important development, because knowledge of

the value of symptom reduction is a major missing element of

environmental policy analysis. Mortality benefits, while large

for affected persons, are somewhat isolated instances. It is

important to know the value of smaller benefits received by large

numbers of people. This knowledge would greatly reduce the

uncertainty of health benefits from cleaner air.

While the value of life literature has provided analytic

constructs for valuing mortality benefits, economic analysis has

offered no such ready construct for measuring the benefits of

reduced illness. Most morbidity analyses have measured benefits

in terms of reduced work loss days and reduced medical

expenditures. Those measures, however, do not provide a

conceptually satisfactory measure of morbidity benefits because

they neglect the value of comfort and other benefits of health

such as leisure and productivity of non-market work.

The purpose of this section is to describe a theoretically

sound approach to empirically estimating the benefits of symptom

reduction resulting from improvements in ambient air quality.

Contingent valuation is the research method used to accomplish

this objective.

Contingent valuation offers a technique capable of getting

at values that are extraordinarily difficult to measure by other

means, such as property value or revealed behavior methods.

Health and aesthetic values of air and water quality, recreation

and power plant siting are among the topics that have been

addressed by contingent valuation. Our objective is to establish

a contingent market in symptom reduction that encompasses all

essential aspects of symptom disutility. Expressions of

willingness to pay are designed to reflect the total value of

symptom reduction, unlike payments in existing markets, which

provide only partial measures of value.

Contingent valuation has become an established research

3-1
method during the last 10 or 15 years. Considerable advances

have been made in overcoming methodological shortcomings and

eliciting high quality information. The present study builds on

this progress by applying contingent valuation to a neglected

area of empirical economics.

3.1.2. Major Issues in Contingent Valuation

Several studies have summarized the analytic development of

the contingent valuation method. Among these are Randall [1985]

and Carson [1985]. Cummings et al. [1984] provides an extended

critique of the present role and state of development of

contingent valuation. In building upon this work, we have given

greatest attention to three methodological areas. These are the

information and preference context of contingent valuation, which

frames the problem for the respondent and helps him research his

preferences; the structure of the contingent market, which

defines the good to be valued in a clear, concise and

quantitative manner; and the bidding game process, which assists

the respondent in arriving at carefully thought-out, unbiased

values. This study builds on progress in dealing with those

issues, and it considers the new problems they raise when dealing

with morbidity.

3.1.2.1. Information and Preference Context

The quality of answers is affected by the fact that

information is imperfect and thinking requires effort. If a

person is asked out of the blue how he values a hypothetical

situation, his answer may be nearly random unless considerable

thought is given. Contingent valuation must give effort to

helping the respondent invest in information and exploration of

his preferences. Questions need to be asked related to

background information on the subject matter--for example the

respondent’s health status and the various health costs and

disutilities he has borne, such as loss of work, doctor bills and

discomfort. In this way the respondent is helped to invest in

thinking about considerations that go into a reasoned answer.

Questions arise as to the optimum degree of investment and as to

the content of the investment. Tedium is a major limit on the

amount of time that can be taken. Attempts to help the

respondent think about the problem will be counterproductive if

he becomes bored. Manageable total length of the questionnaire

becomes an extremely important consideration.

Questions of optimum content involve first, focusing on most

important matters in view of the limited time available, and

second, avoiding imparting bias by overstressing certain effects

and understressing others. Helping the respondent invest in

information raises unique problems in the case of morbidity

because of the variety of ways that health affects a person.

Guidance from economic theory is needed that sorts out the roles

of work, medical costs, discomfort, and defensive measures.

3-2
These subjects must be introduced in common sense terms but still

be consistent with the economic theory of utility maximization

and consumer surplus. The theoretical framework for the

information and preference context is given in section 4.3.

3.1.2.2. Structuring the Contingent Market

It is essential that the contingent market good be presented 

to respondents in a natural, believable way so that they can

reach a valid judgement about it. It is equally important,

however, that the good be defined in a precise way that is

amenable to quantitative analysis. Reconciling these objectives

required much experimentation.

Everyday language is an important part of the description of

symptoms. Descriptions of the frequency, duration, and severity

of symptoms must be included in a natural way that assures as

much as possible that all respondents are thinking about the same

thing when they express their willingness to pay.

In the case of light symptoms, the problem is simplified by

the fact that most people have first-hand experience. This makes

it possible to keep the description of the contingent market good

fairly short and still fulfill both major objectives.

For severe symptoms, out of range of ordinary experience,

more difficult problems are raised. The angina questionnaires

posed these problems. A special effort must be made to help the

respondent imagine what it would be like to live with extreme and

recurrent pain-- in the case of severe angina--or recurrent pain

of less intensity in the case of mild angina.

Every respondent is asked to imagine having a specific

angina health problem, in contrast to the light symptoms surveys,

in which each respondent simply recalls his own endowment from

his information and preference context.

After the contingent market good has been established, it is

necessary to devise a vehicle for delivery of the good to the

respondent, and a vehicle of payment. The payment vehicle

problem has received much discussion in the literature. The

vehicle for delivery has received less discussion, but will be

important in future contingent valuation studies of health.

Much experimentation was devoted to devising an effective

method of conveying the good--better health--to the respondent.

An example is to attribute all light symptoms to allergy and

postulating a new prescription drug, easy to take with no side

effects, that would deliver a specified amount of relief. This

delivery vehicle is expressed in tangible, concrete terms in the

interest of achieving realism. But its realism proves to be a

drawback because numerous respondents were found to object to the

idea of taking medicine, they didn’t accept the allergy, and the

necessary specification of ease of use and no side effects

3-3
introduced abstractions that caused respondents to balk. Because

efforts to achieve tangibility in the vehicle of delivery

introduce distractions of this sort, use of pure willingness to

pay questions is regarded as an advantageous approach.

The payment vehicle presents similar problems. Tangibility

can be achieved by making payment come though higher prices or

taxes. Public goods have been paid for through higher utility

bills. Tangibility, however, is often found to be accompanied by

suggestions of other matters of concern to respondents that

distract them from making bids that reflect the true value of the

contingent market good. As in the case of the vehicle for

delivery of the good, there are strong reasons for using an

abstract payment vehicle that simply asks “How much would you be

willing to pay for this good?”

3.1.2.3. Bidding Game

Bidding formats have received extensive analysis in the

literature. Drawing upon this literature, as well as extensive

previous experimentation with alternative formats, the iterative

bidding procedure was chosen. A major virtue of iterative

bidding is the focusing of attention it demands of respondents.

No bidding format is perfect, however, and several problem areas

must always receive special attention. Strategic bidding and

limited investment in information needed to bid serves as a

convenient two-way classification of concerns.

Because normal precautions were taken, strategic bidding did

not pose difficult problems, although one problem is worth

mentioning. It is very important that the interviewer not

suggest in any way what answer is being sought. There is a

tendency among some respondents to try to please the interviewer

with their answers, or to demonstrate their wisdom by giving the

answer they believe the interviewer thinks correct.

The information-investment problem was much greater,

however, and considerable research was devoted to it. Anchoring

is a frequently encountered problem in bidding behavior with

insufficient information.

Anchoring means that people seize upon a convenient, easy

bid amount and stick to it across bids because they have little

information based incentive to do otherwise. Starting point

bias, often seen as a weakness of iterative bidding, is probably

more fundamentally a problem of limited investment in information

and inadequate researching of preferences on the part of the

bidder. Focus group experience teaches that as questionnaires

are enriched in their information and preference review aspects,

anchoring at or near the starting point ceases to be a problem.

As more and more bid questions are asked about similar

contingent market goods, it becomes increasingly difficult for

respondents to recognize meaningful variations in value. Careful

3-4
preparation enchances the respondents’ ability to handle more

questions, but experience teaches that splitting the

questionnaire or sacrificing information becomes a necessity.

At the opposite extreme from insufficient variation across

questions for a respondent is excessive variation across

respondents to a question. This too comes to be recognized as an

information-investment problem. Variation is expected because

respondents do not have perfect information about the good or

their preferences. Problems arise when the respondents’

understanding of the good and the market and of their own

preferences is so limited that extraneous information

predominates in determining bids. This problem is addressed in

the theoretical framework of section 4.3 in Volume 4.

There are two important cases- -extremely high bids and

extremely low bids. Take the high bid case. A respondent may be

thinking of the increase of his well being due to greater comfort

without thinking of the food, clothing, housing, and other goods

he must give up if he bids high, or he may simply forget about

his budget constraint. With regard to respondents who bid too

low, there may be a high threshold of perception due to the cost

of thinking. For example, eliminating a cough will really be

worth something to him but he bids zero because he has relegated

coughs to an unimportant category where he does not bother to

make comparisons.

3.1.3. Previous Contingent Valuation Work Morbidity

Some previous work has included morbidity as a part of other

effects, as for example the study by Schulze et al. [1984], where

air pollution effects, including both morbidity and visibility,

were asked about. We are aware of only two pervious contingent 

valuation studies concerned with morbidity as such. One is an

asthema study by Rowe, Chestnut and Shaw (1984), reported in a

paper by Rowe and Chestnut (1984).

Another research project, by Loehman and associates (1978,

1979, 1982), concerns the benefits of controlling sulfur oxides

in Florida. In the 1979 study, a mail contingent valuation

survey was sent to 1,977 residents in the Tampa Bay area,

resulting in 432 returns. Willingness to pay questions were

asked about the following three groups of symptoms: shortness of

breath/chest pains; coughing/sneezing; head

congestion/eye/ear/throat irritations. Values were elicited for

minor and severe symptom days, which were defined briefly. No

mention was made of any specific underlying disease, nor were

causes such as air pollution mentioned. No specific delivery

vehicle, such as a pill, was employed, and a simple, abstract

payment vehicle--” tell us how much you would pay’’--was chosen.

The means of payment was a checklist, ranging from $0 to $1000

per year in ten increments.

The Loehman et al. study is similar to our seven symptom

3-5
survey in a number of respects. First of all there is a close

correspondence between the symptom lists. In both cases a pure

health attribute approach was used. The Loehman et al. study

carefully avoided the introduction of redundant information in

its introductory letter, its symptom narrative and in its

delivery and payment vehicles. (Our mail survey, unlike the much

more extensive door-to-door versions, used a medication to

deliver the contingent market good). The Loehman et al. return

rate-- 22 per cent- -is much lower than our 48 per cent, which

reflects the effectiveness of the Dillman procedures followed in

our mail survey. A major difference between the two approaches

is the large number (24) of similar willingness to pay questions

in the Loehman et al. survey. Our surveys employed much fewer

questions on any survey instrument in order to avoid taxing the

respondents’ concentration and the extent of their information

and preference review.

3.1.4. Outline of the Remainder of This Section

Section 3.2 deals with quantifying symptom relief to be

asked about in contingent valuation exercises. The basic problem

is to cover a range of symptoms that is realistic in light of

possible environmental control programs and their effects on

people through dose-response relationships. Evidence is reviewed

giving attention to normal and sensitive populations.

The design of other facets of the contingent valuation

instrument is considered in section 3.3. Focus group experience

leading to the instrument chosen is reviewed.

Section 3.4 presents the structure of the contingent

valuation instrument used in this study. There are four

instruments. Two of the instruments pertain to seven light

symptoms, with the first asking about one-day relief and the

second about 30-day relief. The other two instruments pertain to

angina, one asking about 10-day and the other about 20-day

relief.

After a discussion of the sampling approach in section 3.5,

section 3.6 presents the empirical results from household

personal surveys conducted in two cities in 1985. Summary

statistics on bids and characteristics of respondents are given.

Regression results explaining other bids are presented.

Finally, in section 3.7, the results from a corroborative

mail questionnaire are discussed.

3-6
3.2. THE DOSE-RESPONSE PROBLEM AND THE DEFINITION OF

SYMPTOM RELIEF

3.2.1. Implications of Dose-Response Relationships

for Benefit Estimation

The values that respondents place on improvements in ambient

air quality levels depend on the degree of pollution reduction

and the time pattern of reduction, e.g. whether pollution is

reduced on many days or only a few days. The value of an extra

day of relief may depend on the level of symptoms prevailing

before the relief. People might value an extra day of relief

from symptoms differently if they were already experiencing

several weeks of symptoms than if they were only experiencing one

or two days.

The degree of relief cannot be specified before specific

policy scenarios are known. Some policies could have only a

small effect on pollution levels, while others could have a large

effect. A complication is that any one policy will reduce

pollution levels by different amounts in different places,

depending for example on how far above a standard different areas

are when the standard is imposed. Furthermore, a full analysis

should not necessarily assume that standards are met absolutely.

There may be days of exceedences, which will vary among areas.

The situation is further complicated by sensitive groups in

the population. A large number of people in the population may

experience only a small change in symptoms from a given reduction

in pollution levels, whereas the same reduction may grant many

days of relief to sensitive persons, including those whose

allergic balance may be upset.

The general problem is to develop a way of valuing

reductions in symptoms from pollution depending on the amount of

relief from symptoms, where the relief may vary among areas and

different types of people in amounts that are not known

beforehand. In short, the problem is to estimate, not a single

value, but a function that specifies value depending on amount of

relief and symptom level prevailing in the absence of the policy

being evaluated. This function provides a tool that can be used

to value the variety of symptom reductions among areas and types

of people.

The amount of relief and symptoms prevailing in the absence

of relief must be applicable to the variety of conditions that

will be encountered in reality. Respondents thus need to be

asked about a variety of symptom situations. However, it would

have done no good to query respondents about degrees of relief

that are orders of magnitude greater than would be encountered.

This consideration is important because

attention available from any respondent.

Respondents had to be asked about

3-7

of the limited time and

a sufficient variety of
conditions, but the variety had to be in the realm of reality.

These considerations guided the choice of symptom situations in

the questionnaires. The choice of symptom situation had to take

account of the imperfect state of knowledge about pollutant

reduction. The basic strategy was to choose a range of symptom

levels and symptom relief sufficient to capture the small effects

which many policies would have on a large number of people and

the substantial effects that could occur for sensitive persons

especially in the presence of exceedences.

3.2.2. Effects of Criteria Pollutants on Health

To provide a basis for deciding on degree of symptom relief

to be used in structuring contingent markets, this section brings

together presently known information on health effects of

criteria pollutants. Based on the results, light symptom relief

and angina relief used in the questionnaires of the present study

are described in sections 3.2.3 and 3.2.4.

3.2.2.1. Background

In considering the health benefits of policy to reduce air

pollution, it is necessary to collect data on dose-response

relationships. There are a number of symptoms and physiological

responses that have been observed to occur with increasing doses

of criteria pollutants. Some studies have shown increased

mortality in areas where there have been relatively high

concentrations of certain pollutants (see Lave & Seskin 1979).

It is widely accepted that there is higher mortality among

sensitive groups during acute pollution episodes (Carnow, 1979).

There is considerable evidence to show that criteria pollutants,

especially sulfur oxides, particulate and ozone are associated

with respiratory irritation. Coughing, shortness of breath,

throat and chest irritation and sinus problems appear to increase

with higher levels of pollution. More serious damage to the

lungs and respiratory tract have been known to occur in extreme

cases.

The criteria pollutants that concern us include sulfur

dioxide, particulate matter, carbon monoxide and nitrogen

dioxide. Headaches, shortness of breath, chest discomfort and

coughing are observed to occur when ozone concentrations are

above 0.15-0.30 ppm, levels which occur frequently in the Los

Angeles area and several other cities. Respiratory irritation

with shortness of breath and a probable increase in coughing has

been observed with concentrations of S02 and particulates that

are experienced in cities like New York and Chicago.

Strong evidence for effects on mortality from

epidemiological studies has been provided for sulfur dioxide and

particulate

consistently

ambient air.

matter. Other pollutants have not been shown to

affect mortality at concentrations observed in the

3-8
One important consideration in looking at the effect of

criteria pollutants on morbidity is the interaction among the

various criteria pollutants. Sulfur dioxide has a greater effect

the higher the concentration of particulate (Graves and Krumm,

1981). At least one study demonstrates synergism between S02 and

ozone (Bates et al., 1974).

Weather conditions are also important in determining the

effects of certain pollutants. Sulfur dioxide has a greater

effect on health when the air temperature is below 40-50 degrees

F. Higher humidity increases the rate at which S02 combines with

water vapor to form sulfates, which are more harmful to health

than S02 alone.

Another important consideration in analyzing the effects of

pollution on health is to consider susceptible population groups.

Those with chronic bronchitis or asthma are particularly

susceptible to sulfur dioxide, particulates and ozone. Angina

sufferers are sensitive to levels of carbon monoxide that are

sometimes observed in the ambient air. Elderly persons with

heart trouble may also be more susceptible to carbon monoxide and

pollutants that affect the respiratory system. Children and

pregnant women are more susceptible to respiratory infections,

which may be aggravated by sulfur oxides, ozone and nitrogen

oxides. Others with various genetic diseases or nutritional

deficiencies may be more susceptible to certain pollutants.

Sulfur dioxide, particulates and ozone have a number of

harmful health consequences which are possible at ambient levels.

Carbon monoxide, which is especially high at certain locations,

may affect the health of exposed occupational groups. Nitrogen

oxides are of lesser concern to health, but will be mentioned

briefly.

3.2.2.2. Effects of Carbon Monoxide on Health

Carbon monoxide has a number of effects on health which have

been demonstrated both in the laboratory and in the ambient

environment. There is plenty of information on the effects of

acute exposures to carbon monoxide. Since CO comes primarily

from automobile emissions, its ambient concentration varies with

traffic volume, average speed and the subject’s proximity to busy

streets and highways. The effect of exposure to high levels of

ambient CO depends on both the concentration and the length of

exposure, which determines the level of carboxyhemoglobin (COHb)

in the blood.

The U.S. ambient air quality standard for CO is 9 ppm

(10,000 mg/m3) 8-hour -- average not to be exceeded more than

once per year. The one hour standard is 35 ppm (40,000mg/m3) --

not to be exceeded more than once per year. (Stern et al., 1984)

Observed maximum levels of CO in major cities in recent

3-9
years are usually in the range of 10-20 ppm for the 8-hour

average and 30-40 ppm for the one-hour average. (EPA, 1979,

based on data from Los Angeles, Baltimore and Denver). Ambient

concentrations as high as 40 ppm (8-hour average) and 50 ppm (1-

hour average) are possible in busy streets and intersections

(McMullen, 1975). One-hour averages ranging from 100-200 ppm

have been measured in unventilated parking garages and tunnels

(Wright et al., 1975).

In the Chicago area in 1982, there were 3 excursions of the

8-hour standard of 9 ppm. The highest 8-hour average

concentration was 15.5 ppm and the highest observed 1-hour

concentration was 21.4 ppm. (Annual Air Quality Report.,

Illinois, 1982). Concentrations tend to be the highest in the

winter with highest winter concentrations 2-3 times as large as

maximum summer concentrations (EPA, 1979 based on data from LA,

Baltimore and Denver).

Carbon monoxide exposure can be measured in terms of COHb

formation, which is the basis for the EPA CO standards. The

standards are “intended to protect against the occurrence of COHb

levels above 2 percent” (Federal Register, 1971 cited in

Calabrese, 1978). This level was based largely on a study by 

Beard and Wertheim (1967). For the COHb level to exceed 2%, most

people must be exposed to CO concentrations of at least 12 ppm

for 8 hours or 35 ppm for one hour. (Based on the Coburn

equation discussed in Coburn et al., 1964). Beard and Wertheim

observed impairment of time interval discrimination when the COHb

concentration increases by 2%. Another study of smokers (Aronow,

1978) finds some aggravation of angina pectoris symptoms at this

level. The findings of both of these studies have been sharply

criticized.

In most studies, the first symptoms are not observed until

the COHb level is 2.5-3% or above. At this level, several

laboratory studies find an earlier onset of angina symptoms among

susceptible persons (Aronow and Isbell, 1973; Anderson et al.,

1973). There is also a possibility of aggravation of

intermittent claudication (exercise-induced leg pain) in patients

with cardiovascular problems (Aronow et al., 1974). This level

of blood COHb can be reached when the 8-hr average concentration

is 10-20 ppm or more, or when the one-hour average exceeds 40

ppm.

Effects on patients with coronary artery disease may be the

most serious problem associated with exposure to low

concentrations of CO. The stress this causes, which could

ultimately lead to heart attacks, is difficult to measure

(Stewart, 1976). Upwards of 25% of males over 45 years old may

have preexisting coronary disease (Calabrese 1978, p. 61) There

is not yet conclusive evidence that links CO exposure to higher

mortality, but there is good reason to think that it has some

effects on heart patients (based on a study by Goldsmith and

Landaw, in Los Angeles and a study by Kuller et al., in Baltimore

discussed by the National Research Council, 1977, p. 113). When

3-10
the COHb level in the blood reaches 4%, there is evidence for a

decrease in exercise performance in healthy persons and those

with chronic obstructive pulmonary disease (Aronow and Cassidy,

1975 and Aronow et al., 1977 cited in the EPA criteria document,

1979). This level can be reached when the ambient CO

concentration is above 25 ppm (8-hour average). For the same

effect from a one-hour exposure, the ambient concentration must

be about 70-100 ppm or above. Eight-hour average CO

concentrations often exceed 25 ppm in busy streets and

intersections and toll booths. Concentrations above 25 ppm (8-

hour average) or 50 ppm (one-hour average) are likely to affect

primarily those who are occupationally exposed such as traffic

officers, toll collectors, tunnel workers and parking garage

attendants. When the blood COHb concentration reaches 5%, there

is additional evidence for reduced time to the onset of exerciseinduced angina and probably also increased duration of angina

attacks (Aronow et al., 1972). At COHb levels of 4-6%,various

studies have shown effects on vigilance tasks, visual perceptions

and manual dexterity (Bender et al., 1972, Putz et al., 1976,

Salvatore, 1974, Rummo and Salarnis, 1974). Winneke, however,

found no effects on vigilance or manual dexterity when COHb

concentrations were 5 and 10%. Effects such as headaches and

drowsiness are not likely to occur until COHb levels reach 30%,

well above anything expected even in tunnel and parking garage

workers (Stern et al., 1984).

It is possible that susceptible individuals, such as those

who suffer from angina pectoris, peripheral vascular disease and

other types of heart problems, may be affected by ambient levels

of CO on the worst days in major U.S. cities, if they are

nonsmokers. Levels between 10 and 20 ppm occur on a few days in

many cities. On these days, perhaps 10% of of the nonsmoking

population in. a given city will be exposed for long enough to

have COHb concentrations higher than 2.5%. No more than 5% of

the adult population suffers from coronary heart disease and/or

angina pectoris (Gordon, 1964). Of this susceptible population,

it is doubtful that even 10% would experience noticeable symptoms

as a result of elevated COHb and most of these would be quite

minor. Hence, it is reasonable to conclude that no more than

few additional days per year of mild angina symptoms because of

ambient CO concentrations typical of U.S. cities. Possible

effects on the frequency and severity of heart attacks are

potentially a more serious problem, but there are no data to

demonstrate the existence or magnitude of such effects.

Those who are occupationally exposed or smokers have a

greater likelihood of experiencing symptoms such as aggravation

of angina, reduced time to exhaustion during exercise, possible

increased risk of heart attacks and effects on the performance of

vigilance tasks. This may include traffic policemen,

firefighters, parking garage attendants, tunnel workers and some

industrial workers. Even among these groups, most symptoms are

likely to be minor, affecting a relatively small number who are

the most susceptible. There is no epidemiological evidence to

show serious health problems from CO exposure among members of

3-11
these occupational groups, except in the most extreme

circumstances.

TABLE 3-1

DOSE-RESPONSE RELATIONSHIPS FOR CO

Percent

COHb

2

2.5

3

4

5

7

Possible aggravation of angina in smokers (Aronow, 1978);

Possible impairment of time interval discrimination (Beard

and Wertheim, 1967);

Earlier onset of angina in laboratory studies (possible)

(Aronow & Isabell, 1973; Anderson et al., 1973);

Critical level for cardiovascular disease patients (EPA,

1979);

Aggravation of symptoms of intermittent claudication

possible (Aronow et al., 1974);

Reduced time to exhaustion in treadmill exercise in normal

subjects (Aronow & Cassidy, 1975);

Decrease in exercise performance in those with chronic

obstructive pulmonary (Aronow et al., 1977);

Reduced precision of hand-eye coordination (Bender et al.,

1972);

Likelihood of earlier onset of angina symptoms (Aronow et

al.,1972);

Increased reaction time (Rummo and Sularnis, 1974).

3-12
3.2.2.3. Health Effects of High Ozone Concentrations

Some of the most serious symptoms are associated with high

ozone concentrations. Because a number of other photochemical

oxidants normally occur along with ozone, it isn’t always clear

whether a symptom is caused by ozone or some other associated

pollutant.

Most ozone problems occur in California. The highest

concentrations of photochemical oxidants occur in the Los Angeles

area. In a typical year, it is likely that the second highest

one-hour average concentration will be close to 0.40 ppm at a

station in the Los Angeles area. During the 1960s, one-hour

average concentrations above 0.5 ppm were sometimes recorded

(EPA, 1978).

Many other urbanized areas record levels of ozone above the

national ambient standard which is 0.12 ppm one-hour average not

to be exceeded more than once in any given year. San Diego,

Denver and Philadelphia have each recorded 1-hour average

concentrations of photochemical oxidants exceeding 0.3 ppm.

Other eastern U.S. cities have almost never recorded

concentrations above 0.3 ppm. Most, like Chicago, do not report.

maximum 1-hour average concentrations much above 0.2 ppm in a

typical year. Since ozone is 65-100% of photochemical oxidants,

ozone levels of 0.3-0.4 ppm may occur each year in Los Angeles,

Denver and San Diego. Most other cities can expect maximum ozone

levels of 0.15 to 0.25 ppm one-hour average.

Table 3-2 gives some idea of the concentrations of ambient

ozone or photochemical oxidants at which various symptoms are

observed. Typical symptoms include headaches, chest discomfort,

coughing, throat irritation, increased susceptibility to acute

respiratory diseases, impaired athletic performance and shortness

of breath. Eye irritation is often observed, probably due to

high levels of PAN, which is usually associated with ozone.

Some studies have found that ozone begins to have effects on

airway resistance at concentrations of 0.10 ppm or below (Von

Nieding and Wagner; Goldsmith and Nadel, 1969). The results of

both studies are of uncertain reliability (EPA, 1978). Studies

by Wayne et al., (1965) and Herman (1972), which the EPA

considers more reliable, show a negative relationship between

improvements in running time and oxidant concentration, when

oxidant levels exceed 0.10-0.15 ppm. In several epidemiological

studies, eye irritation has been shown to occur when oxidant

concentrations approach 0.15 ppm (Mizoguchi, 1977; Hammer, 1974).

At least one laboratory study (Delucia and Adams, 1977)

shows a reduction in lung function among exercising subjects when

ozone concentrations reach 0.15 ppm. Mizoguchi finds increased

sore throats and shortness of breath when the ambient oxidant

level is above 0.15 ppm.

When the ambient ozone level is between 0.2 and 0.3 ppm, a

3-13
number of investigators observe symptoms particularly among

susceptible groups such as asthmatics and others with chronic

lung diseases. Young (1963), in a study of occupational exposure

to ozone at this level, notes that 1 out of 7 smokers could

detect irritating odors and noticed soreness of eyes and dryness

of mouth, throat, and trachea, while 2-3 subjects experienced

changes in lung function. Mizoguchi observed large increases in

the number of high school students experiencing eye irritation,

sore throat, shortness of breath, coughing, headaches, and

watering eyes when oxidant levels exceed 0.23 ppm. Asthmatics

and others with chronic lung disease experience aggravated

symptoms when ozone exceeds 0.25 ppm (Schoettlin et al., 1961,

Remmers and Balchum, 1965, Hackney, 1975). Several investigators

have observed no effects when the ozone concentration is below

0.3 ppm. This is true for several studies of occupational

exposure (Challen et al., 1958, Kleinfeld et al., 1957 and

Bennet, 1962). Hackney, in one study of normal subjects at rest,

found no symptoms even when concentrations reached 0.5 ppm.

Many studies have shown that when the ozone concentration

exceeds 0.3 ppm, there will be effects in normal subjects at

rest. These include headaches, chest discomfort and respiratory

tract irritation (Hammer et al., 1974 Knelson et al., 1976

Kleinfeld et al.,. 1957 Hazucha and Bates, 1973).

Another way to look at ozone dose-response is to consider

the results of regression studies of the relationship between

increases in average daily maximum 1-hour ozone concentrations

and days when people will restrict their activities (minor

restricted activity days). Portney and Mullahy (1983) find that

an increase of .01 ppm in the average daily maximum ozone

concentration will result in 0.39-0.64 additional minor

restricted activity days per capita in the course of a year. If

this result is assumed to affect the population of all SMSAs,

then a 0.01 ppm increase in the average daily maximum ozone

concentration will result in between 40 and 75 million additional

minor-restricted activity person-days per year in the United

States.

The existence of symptoms resulting from exposure to high

concentrations of ozone depends partly on the history of

exposure. Typically, symptoms will be the worst on the second or

third day of an ozone episode but will decline by the fourth or

fifth day (Hackney, 1977 (2)). Those who have lived in areas

where high ozone levels are common may experience fewer symptoms

than others when exposed to a given high concentration (Hackney,

1977 (l)). Usually symptoms are present, only on days when the

ozone concentration is high. Effects on asthmatics may persist

for several days after the end of a period of high ozone

concentrations (Golden, 1978).

The only groups which appear to be especially susceptible to

ozone are asthmatics and others with chronic lung diseases. Age

does not appear to matter. Persons over 70 have shown no

effects even when concentrations are as high as 0.4 ppm (Gerking

3-14
et al., 1984).

In Illinois in recent years, the highest recorded ozone

concentration has generally been below 0.20 ppm. In 1983, a year

in which the weather was conducive to high ozone accumulation,

the highest recorded concentration in Illinois (one-hour average)

was . 214 ppm in Alton, near St. Louis. The worst station

recorded 13 days when the ozone concentrations exceeded the

standard. The worst station in the Chicago area recorded six

exceedances of the one-hour standard of 0.12 ppm. We can

therefore predict that even in the worst years there will be

fewer than 10 days when ozone concentrations will be high enough

to affect athletic performance. Some individuals may experience

some throat irritation and coughing on these days, though

probably very minor. On the very worst days (no more than 3 days

in 1983) as much as 5% of the population may experience eye

irritation, 2% may experience some throat and/or shortness of

breath, and less than 1% may experience coughing as a consequence

of exposure to high concentrations of ozone. These estimates are

based on one study of 515 school children in Tokyo. (Mizoguchi

et al.) Other studies show no effects in resting subjects at

levels that are likely on the worst days in Illinois. There may

be some changes in lung function and minor symptoms in active

individuals on the worst days in the Chicago area and in the St.

Louis suburbs (Illinois EPA, Annual Air Quality Report, ______ ___ _______ _______ 1981,

1982, and 1983 - 3 volumes).

In some of the areas around Los Angeles, the ozone standard

is violated more than 50 days per year (Gerking et al. 1984).

There are probably several days each year in the Los Angeles area

where the ozone concentration is high enough to result in

aggravation of asthma symptoms in some subjects. On the worst

days in a typical year, many exercising subjects will probably

experience some coughing, eye irritation, shortness of breath,

reduced endurance and headaches. At the very worst, there might

be a few days in the Los Angeles area when 10% or more of the

population experience some throat irratation, and more than 5%

experience shortness of breath, cough or headache.

3-15
TABLE 3-2

DOSE-RESPONSE RELATIONSHIPS FOR OZONE

PPM

0.10 Possible increased airway resistance;

Effects on athletic performance; Possible eye irritation;

0.15 Beginning of possible symptoms in active individuals;

Possible sore throat, shortness of breath, cough, headache,

Possible changes in lung function;

0.20 Likely changes in lung function and other symptoms in

continuously exercising subjects;

Some evidence for no symptoms in subjects during and after

intermittent exercise;

0.25 No effects observed in resting subjects according to one

study;

First symptoms observed (probably) in subjects with

intermittent exercise regime;

Aggravation of asthma symptoms in some subjects;

Likely increased frequency of headaches, eye irritation,

sore throat, cough and shortness of breath in school

children (epidemiological study);

0.30 Increased frequency of headache, cough and chest

constriction (epidemiological study);

Reduced endurance in exercising subjects;

Changes in lung function in resting subjects;

No effects found in at least one study;

0.37 Level at which there is a broad consensus for the existence

of symptoms including cough, substernal pain, wheezing and

malaise.

3-16
3.2.2.4. Health Consequences of High S02 Concentrations

Until recently, sulfur dioxide was one of the most

troublesome pollutants, especially in industrialized areas or

near electric power plants. Sulfur dioxide, sulfates and related

particulate matter have been implicated as the causes of excess

mortality during acute pollution episodes in London, New York and

Donara, Pa. At levels as low as 0.19 ppm (24-hour average),

which were relatively common in London in the 1950s, and somewhat

less common in Chicago and New York in the early 1960s, at least

one study has shown increased mortality associated with high

ambient concentrations of S02 (Wilkins, 1954). At

concentrations above 0.4 ppm (24-hour average), which have been

observed during some past episodes, there is a great deal of

evidence for increased daily mortality, especially among the

elderly, bronchitis patients and others with chronic lung

diseases (Martin and Bradley, 1960). These effects are more

likely when particulate concentrations are also high.

Sulfur dioxide emissions near major cities have been reduced

by 50-80% since the 1960s so that it is unlikely that even the

worst day of the year in Chicago will have concentrations high

enough to involve increases in mortality. There is some

possibility of respiratory effects from S02 or associated

sulfates on the worst days in Madison county near St. Louis and a

few other locations in other states. It is more difficult to

demonstrate such effects at levels observed in the Chicago area

in recent years.

Sulfur dioxide in high concentrations has been observed to

cause decreased maximum expiratory flow, greater pulmonary flow

resistance, airway resistance and reduced vital capacity (Snell

and Luchsinger, 1969; Frank, 1961; Lawther, 1975). Any of these

physiological effects may be associated with difficulty

breathing. An increase in airway resistance may lead to

coughing.

At ambient S02 concentrations as low as 0.10 ppm (24-hour

average), some asthmatics showed increased airway resistance in a

laboratory study (Sheppard, 1981). At concentrations ranging

from .11 to .19 ppm Brasser et al. (1967) show increased hospital

admissions and absenteeism from work for older persons. Likely

worsening of health among chronic bronchitis patients occurs when

daily average concentrations of S02 reach .20-.25 ppm accompanied

by particulate matter (Lawther, 1970; Carnow, 1968).

Accentuation of symptoms in patients with chronic lung disease

has been observed in London when S02 concentrations are about

0.21 ppm accompanied by smoke concentrations of 300mg/m

(Lawther, 1958). This compares with the 24-hour primary standard

which is 0.14 ppm S02 not to be exceeded more than once a year

(Stern et al., 1984).

A number of other studies show the relationship between

annual mean S02 concentrations and health. At S02 levels greater

3-17
than 100 mg/m3 annual average (about 0.04 ppm) with smoke of at

Y least 160 mg/m , studies have shown greater frequency of

respiratory symptoms and lung disease (Petrilli, 1966, Italian

data), and greater frequency and severity of respiratory diseases

in school children (Lunn et al., 1967). At about this same

level, Wicken and Buck (1964) observed increased mortality. The

annual primary standard for S02 is an average concentration of

0.03 ppm.

There is little information on the percentage of the population likely to experience symptoms from high ambient S02 concentrations. At levels commonly observed in the ambient air, most

laboratory studies find that between 10 and 25 percent of the

subjects experience symptoms. Because of the small sample size

of most studies and the existence of other studies that show no

effects at similar S02 concentrations, any statement about

frequencies is open to question. Lave and Seskin (1977, p. 203)

show an elasticity of daily mortality with respect to daily S02

concentrations of about 0.1 in a cross section of U.S. cities.

Graves and Krumm (1982) show a similar elasticity of hospital

admissions for respiratory disease with respect to S02 levels

when particulates are high in Chicago.

In recent years, neither the annual standard nor the 24-hour

standard have been exceeded in the Chicago area. The number of

symptom days as a result of high S02 levels has fallen from

perhaps as high as 100 in the early 1960s for those with chronic

bronchitis, to none in recent years. There may be a few days in

a year when the most susceptible older persons experience

increased respiratory disease symptoms because of high S02 and

when asthmatics experience greater airway resistance with

possible coughing, wheezing or shortness of breath (see Graves

and Krumm for some evidence from Chicago).

There has recently been some discussion of implementing a

one-hour standard for S02. There are about 100 locations in the

U.S. where hourly maximum SO.2 concentrations exceed 0.4 ppm

during a typical year. In some of these locations there may be

several days where there are one or two hours where asthmatics

may experience wheezing and shortness of breath. There are also

some locations near large smelters where short-term S02

concentrations exceed 1 ppm so that normal individuals may

experience short periods of coughing and possible shortness of

breath.

3-18
TABLE 3-3

DOSE-RESPONSE RELATIONSHIPS FOR so*

24-Hour Concentration

0.10 Increased airway resistance in asthmatics -- possible

increase (Sheppard,1981);

0.14 EPA 24-hour standard

increased hospital admission and absenteeism from work for

older persons possible (Brasser et al., 1967);

0.19 Possibility of increased mortality (Wilkins, 1954);

0.20 Likely worsening of health among chronic bronchitis patients

(Lawther, 1970; Carnow, 1968);

Accentuation of symptoms in patients with chronic lung

disease (Lawther, 1958);

0.4 Likely increases in mortality, especially among elderly,

bronchitis patients and others with chronic lung diseases

(Martin and Bradley, 1960).

3-19
3.2.2.5. Dose-Response Relationships for Particulates

Particulates are probably the most difficult category of

pollutants for dose-response estimation. A wide variety of solid

and liquid particles of various sizes fall into this category.

The human health effects will depend upon the type of particle as

well as the size of the particle. Most of the adverse health

effects of particulate are observed in association with high

concentrations of SO (U.S. Office of Air Quality Planning and

Standards (OAQPS) 1982, Graves & Krumm). Some of the health

effects may be due to high concentrations of sulfates, which are

more likely to form when S02 is combined with droplets of water

and other particulate matter.

Particulates can have several types of effects on the human

system. They can cause chemical or mechanical irritation to

tissue or nerve receptors at the site of deposition (Widdicombe

et al., 1962; Nadel, 1973). By altering host defense systems,

such as the body’s mechanism for the clearance of bacteria,

particles may be associated with increased susceptibility to

infection and the potential for the development of chronic lung

diseases (Douglas and Wailer, 1966; Lunn et al., 1967;

Kalpazanov et al., 1976). Particles can also cause reduced lung

function or tissue damage (Alarie et al., 1975; Martin, 1964).

In extreme cases, particles may have direct toxic effects on the

human body (EPA, 1977; Winkelstein and Kantor, 1967).

Because most health effects are associated with small

particles, it is difficult to speak of dose-response using total

suspended particulates (TSP) as the standard. Another standard,

currently being considered, would use the concentration of

particles smaller than 10 micrometers (um) in diameter (EPA,

1982). Various studies have shown that about half (45-55%) of

suspended particulates fall within this size range.

In dose-response studies of short-term concentrations, there

is little evidence for health risks of consequence below the 24-

hour standard of 260 TSP, equivalent to about 150

smoke or particles smaller than 10 um (U.S. OAQPS, 1982). There

is a possibility of increased mortality when TSP rises above 260

based on the results of several studies conducted in

London and New York in the 1950s and 60s (Mazumdar et al., 1981;

Schimell, 1978). Some studies show aggravation of bronchitis,

(Lawther et al., 1970). A few studies show aggravation of

but not generally until TSP concentrations reach at least 350

bronchitis in London when smoke concentrations are below 250

At smoke concentrations above 500 (equivalent to

TSP above 600 most epidemiological studies show a

significant positive relationship between particulate levels and

mortality.

One study (Lambert and Reid, 1970) found increased cough and

phlegm, and possible changes in lung function when 24-hour smoke

concentrations exceed 100 equivalent to TSP levels of 150-

200

3-20
We can also consider the likelihood of symptoms given

different levels of long-term average particulate levels. The

U.S. annual standard is 75 mg/m average TSP concentration. Few

effects have been observed when long-term TSP concentrations are

below 130 mg/m3

(Ferris et al., 1973, 1976). One study found

some increased respiratory symptoms when the TSP concentration

rises from 60-150 mg/m5

annual average (Bouhuys et al., 1973).

According to at least one study, increased respiratory disease

symptoms accompanied by a small reduction in lung function in

adults are likely when measured TSP levels exceed 180 mg/m for a

long period of time (Ferris et al., 1973). An increase in the

frequency of respiratory diseases and reduced lung function has

been shown from a study in England when long-term average smoke

levels are between 230 and 300 mg/m (Lunn et al., 1967).

In recent years, annual average concentrations of

particulates have exceeded the primary standard of 75 mg/m3 at

only a few monitoring stations. Fewer than 10 percent of the

stations in the Chicago area had average TSP levels which

violated the standards in 1983. In Illinois, the highest annual

average TSP level recorded in recent years has been about 134

mg/m3at Granite City, near St. Louis. The highest average level

recorded in the Chi ago area in recent years has not been much

3 greater than 80 mg/m . Only a few sites in the Chicago area have

recorded more than one exceedance of the 24-hour TSP standard in

any given year. With the exception of 1983, there have been

almost no sites in the Chicago area which have exceeded the

standard more than once in a given year.

In 1981 and 1982, the highest 24-hour TSP concentration

recorded in Illinois was about 460 mg/m . In a typical year,

about half of the stations report one or more days when the 24-

hour TSP concentration exceeds 150 mg/m , the EPA secondary

standard. The worst monitoring station in Illinois, located in

Granite City, recorded 22 days when the average TSP concentration 9

exceeded 150 mg/m3 and 7 days when it exceeded 260 mg/m in 1983

(Illinois EPA, Annual Air Quality Report 1981, 1982, 1983).

Historically, annual particulate

3

levels in the late 1950s

averaged 200-300 mg/m 5

or more in London and over 200mg/m in New

York (Commins and Waller, 1967; Eisenbud, 1980). Chicago and

other U.S. cities had similarly high levels during the early

1960s (U.S. HEW, 1969).

At present levels, persons living in or near heavily

industrialized areas such as Granite City, Illinois experience

possible increased respiratory symptoms on as many as 20 days per

year because of high concentrations of particulates. In the

worst years, there may be five or more days when high

concentrations of particulates in Granite City result in possible

increased mortality and aggravation of bronchitis symptoms. The

evidence to support even these relatively minor effects is not

very strong.

3-21
Residents of the Chicago area experience no more than 10

days when there is a possibility that they will experience

increased respiratory disease symptoms, even in the worst

locations. Only at a few locations on the one or two worst days

a year is there a possibility of significant mortality effects or

aggravation of bronchitis symptoms.

3-22
TABLE 3-4

DOSE-RESPONSE RELATIONSHIPS FOR PARTICULATES

Concentration

75

130

150

180

260

350

600

U.S. annual standard for total suspended particulate (TSP)

Possible increased respiratory symptoms when annual average

60-150 (Bouhuys et al., 1973);

Possible respiratory symptoms above this level (annual

averge) (Ferris et al., 1973, 1976);

24-hour secondary standard for TSP

Possible coughing and phlegm along with changes in lung

function after 24-hour exposure (Lambert and Reid);

Likely increased respiratory symptoms with reduction in lung

function after long-term exposure (Ferris et al.);

Little evidence for short-term health risks (OAQPS, 1979);

U.S. 24-hour primary standard for TSP

Possible increased mortality after 24 hours (Mazumdar

et al., 1981; Schimmel, 1978);

Possible aggravation of bronchitis;

Likely aggravation of bronchitis after short-term exposure

(Lawter et al., 1970);

Significant positive effect on mortality likely at this

level and above (QAQPS, 1979).

3-23
3.2.2.6. Effects of Exposure To High Concentrations of N02

The ambient standard for nitrogen dioxide is 0.05 ppm annual

average concentration (Stern et al., 1984). Most effects on

human health are the result of short-term exposure to

concentrations of N02 greater than 0.5 ppm (EPA, 1982). Some

studies have shown evidence of increased respiratory illness in

children living in homes with gas stoves, where N02 concentration

reaches almost 0.2 ppm in bedrooms and may have frequent peaks of

0.6 ppm (Florey et al., 1979; Speizer et al., 1980; Spengler

et al., 1979; Melia et al. 1979, Goldstein et al., 1979). Single

exposures for periods of a few hours or less often result in no

effects even when the N02 concentration is 1.0 ppm or above

(Hackney et al., 1978; Beiland, Ulmer, 1976). Asthmatics and

those afflicted with chronic bronchitis are the most likely to

experience symptoms including possible chest discomfort, dyspnea,

headache and/or slight nasal discharge following 2 hours of

exposure to 0.5 ppm N02 (Kerr et al., 1979).

Peak 1-hour ambient concentrations of N02 reach 0.4 ppm or

above only in California and a few other locations (EPA, 1982).

A larger number of cities including Phoenix, St. Louis and New

York have reported peak hourly concentrations above 0.25 ppm for

the period from 1975 to 1980.

Based on this information we conclude that it is possible

that there could be a few days per year in California when

asthmatics may be affected by high N02 concentrations. It could

be that in some years there will be a few days when children

experience increased risk of respiratory disease because of N02

concentrations repeatedly above 0.2 ppm. Otherwise the health

.

effects of N02 are not very significant for those exposed to

ambient concentrations.

3.2.3. Light Symptom Relief i n the Present Study

From the above review, it is clear that a great range of

uncertainty still attaches to the health effects of certain

pollutants, particularly the light symptom effects. However, two

conclusions stand out. First, realistic pollution control

policies will give a fractional day or at most a few days of

relief to the majority of people. Second, evidence is more

tenuous regarding sensitive risk populations. The possibility

needs to be allowed for that these persons would obtain greater

relief.

Based on these conclusions the following strategy was

chosen. For the light symptoms, one version of the questionnaire

asked about one day of relief to establish values per day

attaching to fractional-day relief or at most a few days of

relief applicable to large numbers of people under many policies.

3-24
People were asked about their prevailing symptoms to see how

symptom level affects the value per day of the small number of

days of relief. A second version of the questionnaire asked

about relief of thirty days to encompass sensitive groups whose

allergic balance could be affected by ambient air quality

changes.

3.2.4. Angina Relief i n the Present Study

A basically similar strategy was followed in the

questionnaires on the one heavy symptom considered--namely

angina. However, the questionnaire strategy was modified to

allow for the fact that angina is outside the realm of most

people’s experience. To find out how the value of varying

degrees of relief are related to a prevailing level of symptoms,

people were asked to suppose alternatively that they started from

levels of one, ten and twenty symptom days of angina.

Furthermore, angina being a more serious symptom found in

different degrees of severity in the population, requires

attention to the quality of the symptoms relieved. To retain

manageability, the variety of starting endowments of angina were

limited within each questionnaire. One version of the angina

questionnaire asked about relief from one, five, and ten days of

mild and severe angina. The other questionnaire asked about

relief from one, ten, and twenty days of mild and severe angina.

3.2.5. References

The references for the above findings on the effects of

criteria pollutants on health are as follows.

1.

2.

3.

4.

Air Quality Criteria for Ozone and Other Photochemical

Oxidants. USEPA, Office of Research and Development, Wash.,

D.C. EPA-600/8-78-004, April 1978.

Alarie, Y. C., A. A. Krumm, W. M. Busey, C. E. Ulrich, and

R. J. Kantz (1975). Long-term exposure to Sulfur Dioxide,

Sulfuric Dioxide, Sulfuric Acid Mist, Fly Ash, and Their

Mixtures. Results of studies in monkeys and guinea pigs.

Arch Environ. Health 30:254-262.

Anderson, E. W., R. J. Andelman, J. M. Strauch, N. J.

Fortuin, and J. H. Knelson. Effect of Low-level Carbon

Monoxide Exposure on Onset and Duration of Angina Pectoris:

A study on 10 patients with ischemic heart disease. Ann.

Intern. Med. 79:46-50, 1973.

Annual Air Quality Report, Illinois Ambient Air Monitoring

Section State of Illinois EPA, Springfield, 1981, 1982, 1983

(1 volume for each year should be citations).

3-25
5.

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Aronow, W. S. Effect of Passive Smoking on Angina Pectoris.

N. Engl. J. Med. 299:21-24, 1978.

Aronow, W. S., and J. Cassidy. Effect of Carbon Monoxide on

Maximal Treadmill Exercise: A Study on Normal Persons.

Ann. Inter. Med. 83:496-499, 1975.

Aronow, W. S., J. Ferlinz, and F. Glauser. Effect of Carbon

Monoxide on Exercise Performance in Chronic Obstructive

Pulmonary Disease. Am. J. Med. 63:904-908, 1977.

Aronow, W. S., and M. W. Isbell. Carbon Monoxide Effect on

Exercise-Induced Angina Pectoris. Ann. Intern. Med 79:392-

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Aronow, W. S., C. N. Harris, M. W. Isbell, S. N. Rokaw, and

B. Imparato. Effect of Freeway Travel on Angina Pectoris.

Ann. Intern. Med. 77:669-676, 1972.

Aronow, W. S., E. A. Stemmer, and M. W. Isbell. Effect of

Carbon Monoxide Exposure on Intermittent Claudication.

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Beard, R. R., and G. A. Wertheim. Behavioral Impairment

Associated with Small Doses of Carbon Monoxide. Am. J.

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auf Atemmechanik und Acelytcholinempfindlichkeit bei

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on respiratory mechanics and bronchial susceptibility to

acetylcholine in normal persons.) INT. Arch Occup. Environ.

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Staub Reinharlt. LUFT 32:54-60, 1972.

Bennett, G. Ozone Contamination of High Altitude Aircraft

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Environmental and Occupational Health Standards. Wiley &

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S02 and Sulfate. INR, Chicago, 1979.

3-26
18. Carnow, B. W., Lepper, M. H., Shekelle, R. B., and Stamler

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1958.

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Commins, B. T., and R. E. Waller (1967). Observations From a

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During Exercise on Pulmonary Function and Blood

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Ferris, B. G., Jr., H. Chen, S. Puleo, and R. L. H. Murphy,

Jr. (1976). Chronic non-specific respiratory disease in

Berlin, New Hampshire, 1967-1973. A further follow-up study.

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Ferris, B. G., Jr., I. T. T. Higgins, M. W. Higgins, and J.

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Florey, C. duV., R. J. W. Melia, S. Chinn, B. D. Goldstein,

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Webster. The relation between respiratory illness i n

primary school children and the use of gas for cooking. III

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29.

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Folinsbee, L. J., F. Silverman, and R. J. Shepard. Exercise

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Whittenberger, J. L.: Effects of acute controlled exposure

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Anderson, D., Dickie, M., Brookshire, D., Estimating

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report, 1984.

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human subjects to ozone. J. Air Pollut. Control Assoc.

19:329-330, 1969.

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human health. Science 162:1352-1359, 1968.

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illness in primary schoolchildren and the use of gas for

cooking. II - Factors affecting nitrogen dioxide levels in

the home. Int. J. of Epid. 8:339, 1979

Goldstein, J. R., S. N. Rokaw, and L. A. Shearer.

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in California. Inter. J. Epidemiol. 4: 207-212, 1975.

Gordon, T. Heart Disease in Adults, United States--1960-

1962. U.S. Department of Health, Education, and Welfare,

Public Health Service, National Center for Health

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43pp.

Hackney, J. D., W. S. Linn, S. K. Karuza, R. D. Buckley, D.

C. Law, D. V. Bates, M. Hazucha, L. D. Pengelly, and F.

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Southern Californians. Evidence for adaptation? Arch.

Environ. Health 32:110-116, 1977.

3-28
40.

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E. Spier, D. C. Law, and D. A. Fisher. Experimental studies

on human health effects on air pollutants. IV. Short-term

physiological and clinical effects. Arch. Environ. Health

33(4): 176-181, 1978.

Hackney, J. D., W. S. Linn, D. C. Law, S. K. Karuza, H.

Greenberg, R. D. Buckley, and E. E. Pedersen. Experimental

studies on human health effects of air pollutants. Ill.

Two-hour exposure to ozone alone and in combination with

other pollutant gases. Arch. Environ. Health 30: 385-390,

1975.

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Adaptation to short-term respiratory effects of ozone in men

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Hackney, J. D., W. S. Linn, J.G. Mohler, E.E. Pedersen, P.

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health effects of air pollutants. II. Four-hour exposure

to ozone alone and in combination with other pollutant

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Hammer, D. I., V. Hasselbald, B. Portnoy, and P. F. Wehrle.

The Los Angeles student nurse study: Daily symptom reporting

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Hazucha, M., F. Silverman, C. Parent, S. Field, and D. V.

Bates. Pulmonary function in man after short-term exposure

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Herman, D. R. The Effect of oxidant Air Pollution on

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Knelson, J. H., M. L. Peterson, G. M. Goldstein, D. E.

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3.3. DESIGN OF QUESTIONNAIRES IN LIGHT OF FOCUS GROUP EXPERIENCE

3.3.1. Overview

Focus groups were the basic research tool employed in the

development of the seven symptom and angina questionnaires. Many

alternative versions of the questionnaires were administered to

participants during the first half of focus group sessions,

followed during the second half by discussions among participants

and researchers. These sessions were followed by weekly meetings

of the research team devoted to discussing strengths and

shortcomings of the test questionnaires, discussing problems and

new insights derived from the sessions, and formulating revised

versions for testing with the next focus group.

Two seven light symptom questionnaires and two angina

questionnaires resulted from this process. The following

discussion outlines the major issues that received the greatest

clarification and development as a result of the focus group

process.

3.3.2. Contingent Valuation Product

Establishing a standard contingent market good to be

purchased (in various quantities) by all respondents was a basic

requirement. For analytic purposes, a well defined regressor is

essential. Realism or concreteness was a complimentary

objective, because respondents feel more comfortable bidding on

tangible goods.

Early focus group experience confirmed a prior hypothesis

that any mention of environmental pollution as a cause o f

symptoms would distract respondents from expressing their values.

No mention of pollution is made in the final versions.

Early versions of single light symptom questionnaires achieved

concreteness by postulating the existence of an allergy that

caused the symptom, and a new prescription medicine that relieved

it. The medicine was declared safe by the doctor, and the

allergy was declared to pose no underlying threats to health.

Use of variants of this approach with several focus groups,

however, eventually convinced the research team that concreteness

was purchased at the expense of distraction from the nature of

the values being sought. Some respondents expressed disbelief in

allergy as a source of some symptoms. They thought in terms of

more serious disease as the source of difficulty, suggesting that

people were not bidding purely for symptom relief. Some

respondents related the cost of symptom discomfort to the price

they spend on medicines to obtain relief. Maximum willingness to

pay was thus confused with market price, causing misstatement of

the correct values. In several focus groups, a frequent

explanation for zero bids was that the experience is a common

event in everyday life and that it is best simply to live with it

until it passes. The zero bids of these respondents are thus

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interpretable as “I usually don’t spend money on medicines in

these situations.”

Introducing the judge merit of the doctor into the CV

narrative appeared to have a similar unintended effect. Its

purpose was to help the respondent accept the narrative as

authentic and bid on the basis of best available information.

One apparent result, however, was to increase the number of zero

bids, because people took account of the fact that they usually

don’t visit the doctor because of these symptoms. The CV

narrative implied a visit to the doctor, which would be costly in

terms of both time and money.

Thus the attempt to construct a tangible, real-life

situation in terms of allergy, medicine and implied doctor visit

created an information overload that biased responses away from

true willingness to pay for symptom relief. The solution to the

problem was to use a more abstract narrative that abandoned these

devices. In the final version of the questionnaire, the respondent was reminded of the various ways he might deal with the

symptoms --buy medicine, go to the doctor or simply wait for them

to go away. Then he was asked to notice that a cure might be

worth even more than the price he had to pay for medicine or

doctor’s assistance, and might be valuable to him even if he just

waited for relief to come on its own accord. The CV questions

that follow this general introduction are of the form “If you

were faced with 30 additional days of coughing in the next 12

months, would it be worth $100 to completely get rid of these

coughing days?”

This version of the light symptom questionnaire was field

tested before being adopted, and was found to be effective. The

relatively abstract nature of the contingent market good proved

to be acceptable to respondents.

3.3.3. Bidding Framework

3.3.3.1. Symptom Selection: Light Symptoms

Because policy application was the research objective, a

set of individual symptoms and symptom combinations had to be

selected that would be affected by environmental policy. At the

same time, contingent markets in symptom reduction had to be

established in a managable bidding framework. At the outset, the

choice was between restricting each questionnaire to one or two

symptoms on the one hand, or on the other hand, constructing more

inclusive questionnaires that spanned the set of policy

consequences.

The former route initially appeared to permit more

intensive iterative bidding and the attainment of more points on

the bid functions of each of the symptoms. Accordingly, one

symptom questionnaires were developed and tested in focus groups.

The result, however, was that respondents quickly tired of

3-35
concentrating at length on the symptom problems. Iterative

bidding, while helpful in getting the bidding process focused on

reasonable values, proved to be redundant after several

applications.

The final seven symptom questionnaires contained the

solutions to these problems. Tedium was reduced by introducing a

variety of symptoms. Before money bids for symptom reduction

were asked, respondents ranked the symptoms in order of

bothersomeness to them. This led them to establish relative

values among the symptoms before bidding and to think at length

about their own preferences first. Iterative bids were obtained

on the least -and most- bothersome symptoms. Bids for each of

the intermediate symptoms were then directly obtained without

iteration.

3.3.3.2. Symptom Selection: Angina

Angina symptoms were included in the light symptom surveys

during early focus groups. It was decided to use them in a

separate set of surveys to reduce the length and complexity of

these exploratory survey forms. Angina symptoms were seen as

being qualitatively different from the light symptoms.

Consequently they required individually tailored sections to

prepare the respondent for bidding. First, a longer, more

detailed set of symptom descriptions was necessary because most

people are unfamiliar with angina. Secondly, the health status

part of the questionnaire had to be related to angina in order to

establish the appropriate health endowment and serve as effective

respondent warm-up.

The angina questionnaires represent a step in the direction

of the study of life threatening health problems. Severe angina

introduces anxiety and extreme pain. The narrative carefully

excludes danger of death, however, and is thus purely symptom

oriented. A risk of death question was included in early

versions of the angina questionnaires, but was dropped when it

was recognized that careful preparation of respondents in

probability interpretation was necessary. It is expected that

the angina responses will be useful in understanding health

problems involving the anxiety and response of risk bearing

associated with serious illness and death.

3.3.3.3. Frequency of Symptom Occurrence in Questionnaires

Much focus group experimentation was devoted to determining

the proper number of bids to elicit from respondents. Progress

in the solution of this problem complimented work in determining

the number of symptoms it was feasible to investigate in one

questionnaire. Several issues were involved. A purely practical

problem was how many bids could a respondent make before losing

concentration and giving mechanical answers. This question was

discussed in numerous meetings following focus group sessions.

3-36
Various devices were

Another issue

normal and sensitive

and large symptom

necessary in order

developed to discourage mechanical bidding.

was the necessity of respresenting both

populations. Bids representing both small

responses to environmental change were

to estimate benefits among all affected

groups. Getting people to take small symptom changes seriously

required major experimentation. A third issue was the

desirability of having an adequate manner of points to

econometrically estimate bid or demand functions for symptom

reduction.

As described in section 3.4, both the angina and the seven

symptom surveys were split into two versions -- identical except

for frequency of symptom occurrence and number of symtom days

reduction to be valued.

3.3.4. Health Status

The health status

underwent considerable

experience. The basic

module of the seven symptom survey

evolution as a result of focus group

challenge was to obtain a substantial

amount of detailed information about the background and

experience of the respondent with each of the seven symptoms, and

information about expenditures for medicine and professional care

on the symptoms. Early attempts proved to be cumbersome and time

consuming, and much of the individual symptom detail was removed.

When it became evident that too much analytically valuable

information was being lost, further attempts were made to include

it, and an efficient format, originally developed for an

experimental mail survey, was successfully adopted.

3.3.5. Respondent-Interviewer Interaction

determined the order of bidding.

The tally sheet was filled

track of bids. The respondent was

3-37

out by the respondent to keep

given an opportunity to revise

As expected, some respondents had difficulty concentrating

on the survey for more than a few minutes. To combat this

problem, a number of handout cards were developed for use

throughout the interview. Some of these cards simply list the

respondent’s choices of answers. Others play a more active role

in the survey. Ranking of symptoms was introduced into the

seven-symptom survey primarily to avoid mechanical or

inadequately thought-out bidding. People tended to bid the same

amount for several symptoms without too much thought in early

focus groups. The ranking approach required them to consider

carefully which symptoms were more or less bothersome. (Ties

were allowed.) Greater variation in bids resulted in later focus

groups. The respondent arranged the symptom cards from least to

most bothersome. He was asked to think carefully about the role

of these symptoms in his own life. The resulting card order
bids and symptom rankings, in case he had second thoughts about

these judgments as the contingent valuation was carried out.

3.3.6. Length of Interview

Experience indicated that respondents could be kept

involved in the interviews for up to about 40 minutes. All final

questionnaires fall within that time limit.

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3.4. STRUCTURE OF CV INSTRUMENT

The structure of the health survey is reflected partly in

the organization of the questionnaires, and partly in the

relationship of the questionnaires to each other. Internally,

the four questionnaires have essentially the same organization.

Their major features are questions on health endowment in the

beginning, followed by contingent valuation questions and ending

with questions on socioeconomic characteristics. A major

structural feature of all questionnaires is that they contain a

high degree of interaction throughout between interviewer and

respondent. Pairs of angina and seven symptom questionnaires

were used in the field in order to obtain responses on a range of

symptom severities. This contributed greater precision to

econometric estimation and assured that contingent market symptom

avoidance spanned an adequately wide range of experience to be

useful in policy analysis. Pairs of questionnaires were used

rather than single versions in order to keep interview time

within acceptable bounds. Responses were pooled during analysis

into single data sets for the seven symptom and for angina.

Details of the questionnaire structure are given in the

remainder of this section, using the one symptom day version of

the seven symptom questionnaire for discussion. Differences in

the other questionnaires are then described briefly.

3.4.1. Seven Symptom Health Questionnaire: 1 Day

3.4.1.1. Introduction

The first page of the questionnaire introduces the

interviewer, briefly explains the purpose of the visit and seeks

an eligible respondent. Some general respondent and interview

identification is recorded.

3.4.1.2. Health Evaluation

The respondent is asked to subjectively rate his own health.

This is followed by questions on perceived degree of control over

own health, and frequency of illness or physical discomfort

during the last month.

These three questions orient the respondent to thinking

about the subject of health, about which detailed hypothetical

and experience-based questions will be asked. They are also

intended for use as explanatory variables in the analysis.

3.4.1.3. Health Status

This section focuses on the respondent’s experience with the

seven symptoms during the previous twelve months. It is

difficult to get accurate recall over a year long period, but a

3-39
shorter period was ruled out because responses would likely be

unrepresentative because of seasonal effects.

In the first question, people are simply asked if they have

experienced any of the seven health probelms during the last

year. They are handed a card that lists the problems. A series

of questions is then asked concerning the problems experienced by

respondents. First, they are asked to recall about how many

times they have experienced each problem. Next, respondents rank

problems from most to least bothersome. These three initial

questions are increasingly specific-- eliciting more and more

recall and thought.

The next questions quantify symptom severity in physical

terms. They obtain information on the numbers of days of

activities of various kinds that were lost or interfered with by

each of the symptoms. If work days were lost, they are asked how

much earnings fell as a result.

The following questions pertain to purchase of medicine or

use of professional health care related to the symptoms. First,

respondents are asked if they have purchased medicine or visited

a health professional. Then they are asked how many times and

lastly, how much it cost (net of insurance payments). Lastly,

respondents are asked if they have experienced any of the

symptoms in combination. If so, they are asked to name the

combination of symptoms they have experienced most frequently.

Health status was one of the most extensive and timeconsuming sections of the questionnaire. The principal reason

for obtaining such extensive health status information is to

provide the data base for the comparison of the health

expenditures and contingent valuation analyses. Less detailed

data bases originally considered would have greatly restricted

the comparative analysis.

The other purpose of the health status data is that it,

together with the health evaluation responses, determined the

health endowment of the respondent. It is important to know the

initial health condition of the respondent because initial health

is hypothesized to be an important influence on willingness to

pay for additional symptom avoidance.

3.4.1.4. Defensive Measures

Respondents are asked if they have purchased any air quality

control equipment for their home or car for health reasons. They

are asked if they avoid smoking and if they have changed location

of residence for health reasons.

Money spent on equipment to reduce the risk of health

problems is an important part of what some people are willing to

pay to avoid the seven questionnaire symptoms. Avoiding smoking

is not money expenditure, but represents an expenditure of effort

3-40
for many people that is probably equivalent to a large monetary

expenditure. Moving for health reasons reflects willingness to

pay both in terms of dollar amount and effort.

The role of defensive measures, or averting behavior, was

given considerable theoretical attention during the time that the

survey was being prepared and administered in the field. That

work is reported in sections 2.2 and 2.7. The abridged list of

defensive measures included in the questionnaires had the purpose

of giving a preliminary indication of the direction and extent of

their influence on willingness to pay for symptom avoidance.

3.4.1.5. Ranking of Symptoms

This section is a preparation for the bidding of the

contingent valuation section. It establishes the standardized

hypothetical product to be valued. Each symptom is described in

a brief statement read by the interviewer. Cards are handed to

the respondent, summarizing the main points of each symptom

description. The respondent is asked to suppose that his health

endowment during the next twelve months will be exactly as it was

in the past twelve months, except for one additional day of each

of seven symptoms in turn. Thus, while the additional symptom

day is the same for all, nevertheless the situation for each is

unique because it is based on own individual experience. Several

objectives are accomplished by this approach. First, a standard

product is established, making it clear for purposes of

quantitive analysis what is being valued by the bids. Second,

realism is achieved by relating the contingent valuation problem

to the respondent’s personal experience. (The respondent has, of

course, just spent quite a bit of time recalling that

experience.) Third, it permits analytic exploration of the

entire demand surface of the population by giving measures of

willingness to substitute symptom free days for other goods over

a wide range of health endowments.

The ranking procedure accomplishes the additional objective

of establishing relative valuations among the symptoms in

physical terms. It requires the respondent to think carefully

about the symptoms in personal terms before bidding. Symptoms

and symptom cards are presented to the respondent one by one, as

described above. After each card is presented, the respondent is

asked to arrange the cards in a stack with the more bothersome

symptoms towards the bottom. Ties are permitted. The

interviewer records the rankings on a tally sheet, in the order

determined by the respondent.

3.4.1.6. Contingent Valuation

3-41

To further prepare the respondent for bidding, a household

spending card is presented. This card lists six categories of

household spending together with amounts and percentages spent by

a typical family. The respondent is urged to think about the
actual amounts pertaining to his own family, and think

specifically where symptom bids would affect the family budget.

After discussing the spending card, a paragraph is read to

the respondent that gives some instructions about how to think of

the contingent markets about to be examined. The problem

addressed is that people often think about willingness to pay in

terms of what they actually pay in the market for remedies. In

cases where they are accustomed to suffering through a problem

until it goes away without buying medicine or going to the

doctor, people often declare their willingness to pay to be zero.

Respondents are asked to set aside their actual behavior in these

situations and enter a simplier kind of hypothetical market in

which a monetary payment could exchanged for a cure. The

contingent market is structured this way in order to avoid the

larger number of zero bids that were found to result from alternative structures. An important feature of the contingent market

structure is that it abstracts from visits to the doctor,

purchases of medicine or similar activities usually associated

with curing health problems. A straightforward, abstract market

involving a simple expression of willingness to pay was adopted

and found, with suitable preparation, to be acceptable to

respondents. The advantage of this approach over more tangibly

constructed markets is that it avoids the equation of “I usually

do nothing to treat this symptom” with “I am willing to pay

zero.“

Bidding then proceeds for each of the seven symptoms. For

each symptom, the respondent is asked to suppose that his health

will be the same during the next year as last, except for one

additional day of the symptom in question. Bidding begins with

the least bothersome problem identified by the symptom card at

the top of the stock. The second contingent valuation is given

for the most bothersome problem, corresponding to the bottom

card.

These two bids are obtained by means of iterative bidding.

An arbitrary starting period of 100 dollars is used. Bidding

proceeds up -- doubled --or down -- halved -- depending on

whether the respondent says yes or no to the opening offer. Once

a no answer is received after an opening yes bid, half the

difference between the last no answer and to most recent yes

answer is asked. Bidding concludes with the last yes answer or

zero. Answers are recorded on the tally sheet.

Having bracketed the dollar values on the least and most

bothersome symptoms, the respondent is asked to decide the values

for avoiding symptoms of intermediate bothersomeness. No bidding

game is utilized; the respondent simply enters the values on the

tally sheet. The respondent is encouraged to change bids, or

even alter the original rankings if desired.

The next part of the contingent valuation section is

devoted to combinations of symptoms. One combination consists of

an extra day of cough, sinus and throat problems. Another

3-42
consists of an extra day of headache, nausea, and drowniness

symptoms. As an approach to valuing the avoidance of a day of

these symptoms, the respondent is asked to add respective

individual bids and compare the sum with the value of avoiding

all three together.

The next contingent valuation question asks willingness to

pay for a day of symptom relief for the respondent’s entire

household, using the first three symptom combination: cough,

sinus and throat problems. The last question extends the day of

relief from the three symptoms to everyone in the entire United

States. The bid is for relief over and above that already bid

for the respondent’s own family.

3.4.1.7. Reasons

In this section, the respondent distinguishes loss of

activity in the market (work away from home; medical expenses)

and activities outside the market (comfort, work at home,

recreation). Respondents rank as many of the six categories

(including "other," which they are asked to specify) as pertain

to them. One intended use of the rankings is a descriptive

tabulation that provides a qualitative summary of the importance

of the symptoms to the general population. Another use is to

provide additional information for the comparative analysis of

willingness to pay vs. health expenditures in valuing symptom

reduction.

The second reasons question asks respondents to compare the

severity of the hypothetical symptoms described to them in the

contingent market with the severity of corresponding symptoms

they actually experienced. Then respondents are asked how much

they would pay to completely get rid of the symptoms they have

actually experienced. The question helps to quantify the product

being offered by linking it to the hypothetical symptom descriptions in terms of severity. Information on frequency has already

been gathered in the health status section.

While the contingent value question on actual symptom

experience logically belongs in the previous section, including

it here gives the respondent a little relief and variety, and

permits proper preparatory questioning.

Finally, an opportunity is given to change many of the bids

and rankings about which the respondent may have had second

thoughts.

3.4.1.8. Socioeconomic Questions

Socioeconomic information, together with the health

endowment data collected at the beginning of the survey,

quantifies the explanatory variables in the willingness to pay

regressions. Socioeconomic questions comprise general

3-43
demographic household information, various measures of household

market activity and general measures of human capital. The

health endowment information is complementary in that it

quantifies important specific human capital variables.

The first three questions deal with past and expected

change of residence. The next question identifies the

respondent’s occupation. A question on respondent aptitudes is

included partly as a general human capital measure, and partly

for the purpose of gauging ability to respond to the

questionnaire. The remainder of the socioeconomic section

gathers household data on age, race, education, family size and

structure, current and permanent income, wealth and saving.

3.4.1.9. Interviewer Evaluation

At the end of the questionnaire, the interviewer records

comments that may be helpful in identifying problems that call

into question the quality of the responses.

3.4.2. Seven Symptom Health Questionnaire: 30 Days.

This version of the seven light sypmtom survey is identical

to the one day version except that avoidance of thirty additional

days of symptoms, instead of one additional day, are ranked and

valued in the ranking and CV sections.

3.4.3. Angina Health Questionnaire: 10 Days.

The angina questionnaires are identical to the seven symptom

questionnaires in the following sections: introduction, health

evaluation, defensive measures, reasons, socioeconomic questions

and interviewer evaluation. The content of the remaining

sections is modified as described below.

3.4.3.1. Health Status

The first group of questions pertains to respondents who

have been diagnosed as having a heart condition of any kind.

First, they are asked if they know the name of their condition.

Next, they are asked to list the symptoms they have experienced

and to rank them according to how bad they were. Frequency of

occurrence is then recorded. For those respondents who

experienced some curtailment of normal activity, information

similar to that in the seven symptom survey is obtained.

Respondents are then asked about types and extent of health care

they have received for their condition during the past year, and

associated expenses. The health status section concludes by

asking all respondents, including those without heart condition,

if they are familiar with the subject of the survey--angina

pectoris; whether they know. anyone with the condition; and how

3-44
they are related to these people.

As in the seven symptom surveys, the health status section

establishes the respondent’s health endowment most closely

related to the concern of the questionnaire, as well relevent

health expenditure data. The questions about familiarity with

the health problem are an important addition to the angina

questionnaire, because they address the question of the

importance of familiarity and semantic efforts.

3.4.3.2. Contingent Valuation

The contingent valuation sections of the ten day and twenty

day angina questionnaires are structured identically. The ten

day questionnaire is described in detail here, followed by a

brief comparison with the twenty day version.

The section begins with a general two paragraph

introduction that asks the respondent to imagine having the

angina problems about to be described -- first a relatively mild

problem; then a severe one. The introduction concludes with a

brief statement about the extent of angina pectoris in the United

States.

Contingent valuation begins

mild angina symptoms a month on

described by the interviewer and

the respondent. Willingness to

with an endowment of one day of

the average. The problem is

summarized on a card handed to

pay to avoid the problem is

elicited by means of an iterative bid with a starting point of

$53.00. The odd number was chosen to avoid tempting the

respondent to settle for a round number at the beginning.

The next question supposes an endowment of ten mild symptom

days a month. Willingness to pay pertains to eliminating one of

these days. Iterative bidding is again employed, starting at

twice the value determined by the respondent on the previous

answer. The third question pertains to eliminating all ten

symptom days. The fourth question eliminates five of the ten

symptom days. No iteration is employed in the third and fourth

questions.

The second half of the contingent valuation section

pertains to severe angina, which is described by the interviewer

and by the summary card handed to the respondent. Endowments,

levels of avoidance and bidding strategy are the same as for mild

angina. The starting bid for avoidance of the one day per month

of severe angina is twice the corresponding bid for mild angina.

Twice this bid is the starting point for eliminating one day out

of ten severe angina days.

3.4.4. Angina Health Questionnaire: 20 Days

This version of the angina survey is identical to the ten

day survey, except that the endowment of angina the respondents

3-45
were asked to imagine they experienced, and the number of days of

relief bid for, ranged from one day to ten days to twenty days of

mild and severe angina.

3-46
3.5. HOUSEHOLD SAMPLING

3.5.1. Sampling Procedures

The basic objective of the sample design was to obtain a

representative cross section of households on which to base

inferences about health behavior. Two metropolitan areas were

sampled- -Chicago and Denver. Two different cities were chosen to

test for possible regional differences in responses.

Random sampling was employed. Census tracts within each

metropolitan area, and starting points within each tract, were

chosen randomly. The sample in each metropolitan area was drawn

using 1980 census tract maps and census statistical tables.

First, all of the n census tracts in the urban portion of the

metropolitan area were assigned numbers one through n. Then

about thirty numbers between one and n were drawn from a table of

random numbers and matched with the corresponding census tracts.

Eight interviews were to be taken within each tract, in the order

drawn, until an adequate city sample was obtained. Extra tracts

were drawn in case eight interviews could not be obtained in some

of the tracts. The sampling order of the random draw had to be

followed, however; no interviewer discretion was allowed in tract

choice.

Random selection of households within each tract was

achieved in a similar way. Every block within each selected

tract was assigned a number between one and m, which was

determined by counting the blocks shown on the census tract maps.

A random number between one and m was chosen to determine the

block where interviewing started. Additional blocks were

determined by going to the next-higher numbered block as

indicated in the tract maps (returning to the lowest-numbered

block if necessary).

The interviewer’s starting point on each block and the

direction to proceed around the block were uniformly specified in

advance for all interviewers. The procedure continued until

eight interviews were obtained within a tract.

Copies of census tract maps were provided to all

interviewers, with starting blocks clearly indicated. Field

supervisors in each city worked closely with interviewers, and

monitored their work. Contact between the field supervisors and

the University of Chicago survey coordinator was maintained

throughout.

3.5.2. Sample Size and Editing

One-hundred-ninety-nine interviews were completed,

approximately equally divided between two cities. Twenty three

of these interviews had to be removed from the sample. The

reasons for removal were infinite bids (respondents who said they

3-47
would pay any amount), random bidders, whose bids bore no

logical relationship to each other, and protectors.

Similar to other personal interviewer surveys employed in

the past, a few incomplete and inconsistent responses were a

problem in the analysis. It was occasionally necessary to

extrapolate existing information to fill the gaps left by

respondents who were unwilling or unable to provide consistent or

thorough information. In the present surveys, two areas required

particular attention: willingness to pay bids and values of

household income.

The bids are crucial to the CV framework and it was

necessary to assure their validity. “Protectors,” respondents

who refused to give any bids, were removed from the sample. The

protectors were determined by the lack of any CV bids and/or an

interviewer comment, and were distinguished from those who wished

to bid zero. Zero bidders were left in the sample on the grounds

that the bids were felt to be legitimate by the interviewer and

by the consistency of other information provided.

Equally important to being willing to participate in the

experiment (i.e. not be a protestor) is that the respondent fully

understood the nature of the exercise. A lack of understanding of

the willingness to pay concept led to the exclusion or editing of

two other groups of respondents. First are random bidders, the

several respondents who bid dollar amounts that were grossly out

of sequence for the manner in which they had ranked the symptoms.

They were entirely excluded. As should be clear by the

description of the survey instruments, this was a problem only in

the seven light symptom versions. A second and somewhat more

important group was the few respondents who bid infinite

amounts(a willingness to pay “any amount”) or exorbitantly high

amounts (two or three times their yearly income) for the relief

of the symptoms. As was stressed in the survey, it is important

for a CV experiment to have bids that are consistent with the

household budget constraint. In most cases, respondents offered

unrealistic bids for only one or two endowments. The various

combinations of symptoms, the additional amount to relieve the

entire United States and twenty days of severe angina were the

questions that occasionally induced unrealistic bids. Allowing

those respondents’ other, more reasonable. bids to be included,

the questionable bids were set equal to missing values.

Exclusion of the very high bidders may have produced some

downward bias on the summary statistics and the regression

results because the actual, although unknown, values of these

bidders may have been higher than others in the sample.

The final determination of household income also needed

additional work. To gather this figure, the survey used a direct

question on yearly income and a variety of questions concerning

hours, weeks and months worked, and hourly, weekly, and monthly

wages of all members of the household. If income was still

undetermined, a default mechanism allowed the respondent’s median

census tract income to be used.

3-48
3.6. EMPIRICAL RESULTS FROM HOUSEHOLD PERSONAL INTERVIEWS

3.6.1. Introduction

The four versions of the personal interviews were

administered throughout the Chicago and Denver metropolitan areas

in the winter of 1984/85. The data were collected from the field

interviewers by an area supervisor and returned to the University

of Chicago for coding, inputting and analysis. This section

presents the summary statistics and gives the results of the

regression analyses.

Multiple regression analysis was used to investigate the

relationship between the contingent valuation bids for improved

health and various socioeconomic and health status measures. The

goal was to determine how much of the variation in individuals’

bids could be explained by differences in observed

characteristics. Since the four versions of the surveys ask

respondents to value quite different changes in health, each

version is analyzed separately.

The socioeconomic measures used as explanatory variables in

the regressions are income, education, race (white/non-white),

age and sex. Assuming health is a normal good, it is expected

that higher income respondents would bid larger amounts. Since

wealth or permanent income may be more relevant to the

inividual’s willingness to pay than his current income, a

variable indicating whether the respondent owns or rents was

included in an earlier set of regressions as a proxy for wealth.

However, this variable had an unexpected sign, and is not

included in the regressions reported below. There is no obvious

explanation for the anomalous results, except that the own/rent

variable may be a poor proxy for wealth, perhaps because door to

door sampling may result in an atypical mixture of owners and

renters .

The remaining socioeconomic measures used as explanatory

variables are motivated by the literature on the demand for

health and medical care. For a review of this literature, see

Feldstein (1982); a standard reference is Grossman (1972a,b).

Studies have found systematic differences in demand for medical

care and health according to education, race, age, and sex.

These same patterns may appear in the contingent markets for

health defined in the four surveys. If so, the better educated

individuals are expected to bid more for improvements in health.

Whites are expected to bid more than nonwhites, older individuals

are expected to bid more than the young, and females are expected

to bid more than males.

Differences in the expected cost of illness (out of pocket

medical expenses and foregone earnings) might also help explain

differences in bids to avoid illness. Measurement of these

expected costs is difficult, however. For those individuals who

had experience with the light symptoms, past costs may be used as

an estimate of expected costs, but this limits the sample. For

3-49
these smaller samples, willingness to pay bids were regressed on

experienced cost of illness, as described in section 2.6 of

Volume 2. The cost of illness were measured as the sum of

medical expenses and foregone earnings, adjusted for health

insurance coverage and paid sick leave. The coefficients on the

cost of illness terms were not significantly different from zero,

indicating that in these small samples the willingness to pay

bids and cost of illness show no strong tendency to move together

in a systematic fashion. Cost of illness measures were not used

in the regressions using the full samples reported below.

A set of health status measures were included in the

regressions as explanatory variables for the willingness to pay

bids. For all four surveys, a measure of general health status

was included, indicating whether the respondent judged his own

health to be excellent, or other, that is, to be only good, fair

or poor. For the seven symptom surveys, the individual’s

previous experience with the symptom was included. For the

angina surveys, a dummy variable indicating whether the

individual had a heart condition or not was included.

Individuals in bad health, as indicated by these measures, are

expected to bid higher amounts for improvements in their health,

reflecting increasing marginal disutility of bad health.

The concept of increasing marginal disutility can be seen

to be the converse of the more familiar idea of decreasing

marginal utility. Equation (3.1) represents an ordinary utility

function,

(3.1) U = u(H),

where H = symptom free days. The utility of the individual is

simplified to be a function of only symptom free days. It is

assumed that the utility function exhibits traditional properties

of a positive marginal (du)/(dH) > 0, and diminishing

marginal utility, The second assumption

implies that the more healthy days an individual experiences, the

less he is willing to pay to obtain an additional good day.

The case at hand does not deal directly with healthy days,

but rather with the change in symptom days experienced and the

indirect effect on individual utility. The amount of symptom

free days can be expressed as

(3.2) H = T - S,

where T = Total number of days available;

S = Days were a symptom is experienced.

3-50
Thus the amount that people are willing to pay to rid themselves

of a particular symptom is a measure of marginal disutility, not

marginal utility.

The marginal utility of a symptom day is expressed as

follows and is negative:

(3.3) (dU)/(dS) = ((dU)/(dH)) ((dH)/(dS)) .

However, from equation (3.2), (dH)/(dS) = -1; therefore

(3.4) (dU)/(dS) = - (dU)/(dH) < 0,

since (dU)/(dH) is assumed to be positive.

Marginal disutility, M, is the negative of the marginal

utility expression in equation (3.4):

(3.5) M = (dU(H))/(dH) .

The CV experiment considers the change in the marginal disutility

as the number of symptom days increases. From equatiom (3.5), we

get

(3.6) (dM)/(dS) = (d2U(H) )/dH2(dH)/(d S) .

Recalling that (dH)/(dS) = - 1, we find

(3.7) (dM)/(dS) = - (d2U(H)/(dH2) > 0 .

This follows from the original assumption that the utility

function exhibits increasing marginal utility.

The analysis has shown that the hypothesis of diminishing

marginal utility of good, a commodity that is enjoyed by an

individual, implies increasing marginal disutility of a bad, a

commodity that is not enjoyed by an individual. Thus , the result

that people are willing to pay more for an extra day of relief

the more symptom days that they have already experienced, is

consistent with received utility theory.

Summary statistics and the results of the regression

analyses are reported in sections 3.6.2 through 3.6.5. These

sections also discuss in greater detail the regression techniques

used. Section 3.6.6 summarizes the results of the analyses adn

3-51
discusses the implications for valuing health.

3.6.2. Seven Symptoms: One Day Relief

3.6.2.1. Summary Statistics

Reported in Table 3-5 are the means and standard

deviations for all variables that were included in the regression

analysis of the seven symptoms, one day relief questionnaire.

Presented first are the bids to relieve one day of each of

the seven light symptoms. The mean values range from $50.28 to

relieve one day of nausea to $25.20 to relieve one day of

coughing. The ranking of the symptoms from most bothersome to

least bothersome, according to mean bid values, is: nausea,

headaches, sinus problems, drowsiness, throat congestion, itchy

eyes, and coughing. The next set of variables presented are the

bids to relieve a combination of the symptoms for the individual

and the United States, and to relieve the symptoms that are

actually experienced by the respondents.

Following the bids are the independent variables used in

the analysis. The central tendencies for income and education

are high for a random sample, but not very different from those

obtained in other door-to-door surveys. There is a substantial

spread in these variables.

The “white,” "own-rent,”

status variable are zero-one

Seventy-three percent of those

the race question. The health

“sex,” and the various health

dummy variables as indicated.

interviewed amswered "white” to

status variables disclose the

respondents’ general perception of their personal health.

The last set of variables used in the analysis indicates

the respondents’ experience with each of the seven symptoms over

a twelve month period, The mean symptom days range from 19.75

days of itchy eyes to 1.3 days with nausea. The mean values may

appear slightly large. This is primarily due to the respondents

who claim to have experienced a symptom extremely frequently. The

two largest values, for example, headaches and itchy eyes, each

had one respondent who claimed to have experienced the symptom

virtually every day of the year in question.

3-52
Table 3-5

Means and Standard Deviations for Seven Light Symptom

One Day Survey

Standard

Variable Label Mean Deviation

BIDCGH1

BIDSNS1

BIDTHT1

BIDEYE1

BIDDRW1

BIDHED1

BINAS1

BID1231

BID5671

BIDCOMB1

BIDUS1

PERSBID1

Bid to relieve 1 additional

day in coughing

Bid to relieve 1 additional

day of sinus problems

Bid to relieve 1 additional

day of throat congestion

Bid to relieve 1 additional

day of itchy eyes

Bid to relieve 1 additional

day of drowsiness

Bid to relieve 1 additional

day of headaches

Bid to relieve 1 additional

day of nausea

Bid to relieve 1 additional

day of coughing, throat

congestion, and sinus problems

Bid to relieve 1 additional

day of drowsiness, headaches,

and nausea

Bid to relieve 1 additional

day of coughing, congestion

and sinus symptoms for entire

household

Bid to relieve 1 additional

day of coughing, sinus and

congestion for entire United

States

Bid to relieve own actual

25.20

35.05

28.97

27.73

31.41

40.10

50.28

65.60

95.08

113.65

137.97

38.66

42.32

42.29

33.01

45.69

61.23

102.41

77.13

158.84

148.48

297.96

614.09 1356.96

3-53
Table 3-5 (continued)

Standard

Variable Label Mean Deviation

INCOME 1983 income of household

(dollars)

EDUC1 Education of person 1 (years)

AGE1 Age of person 1 (years)

WHITE 1 if white, 0 otherwise

SEX 1 if female, 0 if male

NOEXHLTH lif not excellent overall

health, 0 otherwise

DAYSSYM1 number of days of coughing

DAYSSYM2 number of days of sinus

problems

DAYSSYM3 number of days of throat

congestion

DAYSSYM4 number of days of itchy eyes

DAYSSYM5 number of days of drowsiness

DAYSSYM6 number of days of headaches

DAYSSYM7 number of days of nausea

28583.30

14.25

44.49

0.73

0.55

0.65

7.65

14.08

6.83

19.75

2.50

15.88

1.30

24371.50

4.57

15.77

0.45

0.50

0.48

20.94

32.75

20.94

69.93

10.50

62.88

4.98

3-54
3.6.2.2. Regression Analysis

Using the one day relief data, ordinary least squares

regressions were performed. Household income, age, sex, education

and race of the respondent, as well as home ownership, various

measures of health status and experience with the seven symptoms

were used as the explanatory variables. Equation (3.8) is the

equation that was estimated.

(3.8)

where Ylna

i

b

ij

‘j n

U

in

Bid i of person n (i refers to a symptom or

combination of symptoms and n refers to the

respondent)

= Intercept

th

= Effect of independent variables j on the i bid

= Independent variable j for person n

th

= Stochastic error on bid for person n on the i

bid.

The results of the ordinary least squares regressions are

presented in Table 3-6. In general, the results offer little

support for the expected relationships between the different

socioeconomic variables and the amounts bid. The effects of

income on bids tended to be small or even negative, and the

estimated coefficient is never statistically significantly

different from zero. As expected, the more educated did tend to

bid more. The coefficient on education is positive in nearly all

of the regressions, but is only significantly different from zero

at the 95 percent confidence level in one case. It approaches

statistical significance in several other cases. In most cases

whites bid more than non-whites, as expected, but the effect is

never statistically significant. In general, older individuals

bid more than the young, but of the estimated coefficients that

are positive only one is significantly so. In addition, in the

regression explaining the bids to relieve a day of headaches, age

had a negative and significant coefficient. Finally, no

systematic relationship between the sex of the respondent and the

amount bid is found. In about half of the regressions females

tended to bid more and in about half females bid less; most of

the time these coefficients are not significant in the

statistical sense.

More support is found for the expected positive relationship

between poor health and amount bid, reflecting increasing

marginal disutility of illness. Being in other than excellent

3-55
Table 3-6

Seven Light Symptom One Day Survey Regression Results

Intercept

Income

Education1

White

Age1

Sex

Noexhlth

Parameter Estimates

Sinus Throat

Coughing Problems Congestion

-103.79 -56.73 -46.75

(-2.84) (-1.48) -(1.00)

-0.000026 0.000036 -0.00051

(-0.10) (0.14) (-1.57)

2.85 2.72 2.51

(1.91) (1.71) (1.33)

22.41 -3.47 21.21

(1.47) (-0.21) (1.13)

1.56 0.74 0.46

(3.23) (1.46) (0.83)

-20.77 10.57 -10.98

(-1.62) (0.77) (-0.69)

4.58 8.95 31.53

(0.30) (0.59) (1.86)

Days of Depen- 1.43 0.71 1.12

dent Variable (3.43) (3.23) (2.14)

F Value 3.23 2.83 2.00

R-Square 0.48 0.45 0.37

Note: t values in parentheses

Itchy

Eyes

-95.05

(-2.69)

-0.000023

(-0.11)

4.22

(2.79)

19.02

(1.42)

0.64

(1.65)

4.91

(0.42)

20.36

(1.65)

0.15

(1.79)

2.07

0.38

3-56
Table 3-6 (continued)

Intercept

Income

Education1

White

Age1

Sex

NoExhlth

Drowsiness

45.40

(0.93)

-0.00018

(-0.54)

-2.24

(-1.10)

3.62

(0.18)

0.74

(1.16)

-28.63

(-1.61)

-2.22

(-0.11)

Days of Depen- 3.25

dent Variable (2.93)

F Value 2.11

R-Square 0.38

Headaches

47.84

(0.74)

-0.00081

(-1.82)

1.21

(0.45)

39.18

(1.46)

-1.88

(-2.15)

29.87

(1.27)

73.32

(2.83)

-0.006

(-0.03)

2.84

0.45

Nausea

-101.20

(-1.62)

-0.00019

(-0.45)

3.53

(1.38)

43.93

(1.77)

0.77

(1.06)

-4.24

(-0.20)

47.05

(2.08)

16.91

(8.23)

18.22

0.84

Note: t values in parentheses

3-57
Table 3-6 (continued)

BID1231

BID5671

BIDCOMB1

-73.16

(-0.45)

0.00046

(0.42)

9.74

(1.41)

17.42

(0.25)

-2.13

(-1.07)

135.96

(2.29)

94.24

(1.49)

2.28

0.35

BIDUS1

- 369.45

(-1.01)

0.0039

(1.57)

14.36

(0.92)

56.94

(0.36)

1.56

(0.35)

66.80

(0.50)

83.11

(0.58)

1.09

0.21

PERSBID1

172.38

(0.11)

0.0081

(0.75)

-19.91

(-0.30)

1178.75

(1.73)

-17.08

(-0.88)

-447.45

(-0.77)

1135.23

(1.84)

Intercept

Income

Education1

White

Age1

Sex

NoExh1th

Dayssym1

Dayssym2

Dayssym3

Dayssym5

Dayssym6

Dayssym7

F Value

R-Square

-15.64

(-0.21)

-80.74

(-0.52)

0.000062

(0.12)

-0.00066

(-0.67)

3.77

(1.33)

3.46

(0.61)

-21.98

(-0.77)

75.34

(1.37)

-0.21

(-0.2288)

0.06

(0.03)

45.21

(1.87)

-2.22

(-0.04)

3.99

(0.14)

85.52

(1.60)

0.91

(0.57)

1.14

(1.49)

1.04

(1.31)

-18.01

(-1.27)

2.59

(1.38)

23.24

(4.98)

4.28

0.64

5.82 1.10

0.70 0.21

Note: t values in parentheses

3-58
health had a positive effect on the amount bid in all but one

regression. The estimated coefficients are significant at the 95

percent confidence level in two cases, and significant at the 90

percent level in two more instances. In addition, a strong

relationship exists between the respondents' actual experiences,

with a symptom and their bids to relieve that symptom. The

parameter estimate is usually positive and significantly

different from zero. This result holds better for the

individual symptom bids than for the bids to relieve combinations

of symptoms.

Bids to relieve one symptom day of each of the seven

symptoms were also estimated using Zellner’s seemingly unrelated

regression technique. This procedure will account for any

correlation across the bids by individuals. Beginning with the

ordinary least squares equation (3.8), this method allows for a

correlation in the error terms, giving more efficient

estimates. The results (not presented) were parameter estimates

that are consistent with the ordinary least squares method. In

addition, this technique shows the relationship that exists

between the regressions for each of the seven symptoms. It

should be noted that all values are positive and occasionally

quite close to one. There appears to be a strong correlation

between the bids for headaches and nausea, and a lesser but still

strong relationship between itching eyes, and both nausea and

headaches.

3.6.3. Seven Symptoms Thirty Days Relief

3.6.3.1. Summary Statistics

Table 3-7 shows the means and standard deviations for the

variables in the thirty days relief surveys.

As before, the means and standard deviations of the bids

for each of the seven symptoms and combinations of symptoms are

presented first. The mean bids for each of the seven symptoms

range from $488.20 to relieve thirty days of headaches to $166.50

to relieve thirty days of coughing. Drowsiness, sinus problems,

itching eyes, throat congestion amd nausea is the order of the

remaining middle symptoms. This ranking is different from that

in the one day version, with only sinus problems, coughing and

throat congestion occupying the same position.

The thirty day results are also not thirty times larger than

the one day even though the added endowment is thirty times

larger. The differences between the one day and thirty day bid

values appear to be on the order of ten. Comparison of the bids

from the two difference survey instruments thus does not support

the hypothesis of increasing marginal disutility of symptom days.

This is in contrast to the results of the regressions explaining

the one day bids.

3-59
Table 3-7

Means and Standard Deviations For Seven Light Symptoms

Thirty Day Survey

Standard

Variable Label Mean Deviaton

BIDCGH3

BIDSNS3

BIDTHT3

BIDEYE3

BIDDRW3

BIDHED3

BIDNAS3

BID I233

BID 5673

BIDCOMB3

BIDUS3

PERSBID3

Bid to relieve 30 additional

days of coughing

Bid to relieve 30 additional

days of sinus problems

Bid to relieve 30 days

additional of throat congestion

Bid to relieve 30 additional

days of itching eyes

Bid to relieve 30 additional

days of drowiness

Bid to relieve 30 additional

days of headaches

Bid to relieve 30 additional

days of nausea

Bid to relieve 30 additional

days of coughing, throat

congestion and sinus problems

Bid to relieve 30 additional

days of drowsiness, headaches

and nausea

Bid to relieve 30 additional

days of coughing, congestion

and sinus symptoms for entire

household

Bid to relieve 30 additional

days of coughing, sinus and

congestion for entire United

States

Bid to relieve own actual

166.50

265.62

206.26

235.53

317.98

488.20

186.02

624.98

868.89

1250.00

230.27

359.82

284.88

458.94

593.00

833.21

256.02

879.87

1343.36

2165.51

483.46 1013.62

1169.07 2369.27

3-60
Table 3-7 (continued)

Standard

Variable Label Mean Deviation

Income 1983 income of household (dollars)

EDUC1 Education of person 1 (years)

AGE1 Age of person 1 (years)

WHITE 1 if respondent is white,

0 otherwise

SEX 1 if female, 0 if male

NOEXHLTH 1 if excellent overall health,

0 otherwise

DAYSSYM 1 number of days

DAYSSYM 2 number of days

DAYSSYM 3 number of days

congestion

DAYSSYM 4 number of days

DAYSSYM 5 number of days

DAYSSYM 6 number of days

DAYSSYM 7 number of days

of coughing

of sinus problems

of throat

of itchy eyes

of drowsiness

of headaches

of nausea

30109.70

13.83

42.15

0.81

0.49

0.70

4.96

9.64

1.89

33.15

6.74

24.23

1.96

18359.90

4.10

15.72

0.40

0.51

0.46

14.05

28.39

4.82

112.74

43.75

62.54

4.52

3-61
Most of the independent variables that follow in Table 3-7

are consistent with those found in the one day experiment.

3.6.3.2. Regression Analysis

The analysis of bids for thirty days of symptom relief is

similar to the analysis of the one day bids already discussed.

The results of the ordinary least squares regressions are

presented in Table 3-8. The results are not supportive of the

expected relationships between the socioeconomic variables and

the amount bid. Income had a generally positive effect on bids,

but the estimated coefficients were never significantly different

from zero. In fact, virtually none of the estimated coefficients

on the socioeconomic variables differed significantly from zero

in the statistical sense. In addition, for many of the variables

the signs of the coefficients were not consistent across

regressions explaining bids for different symtpoms.

The results of the regressions explaining the thirty day

bids are also not supportive of a positive relationship between

poor health as indicated by a general health status variable or

the number of days of a symtpom the individual acually

experienced. There was some tendency for the individuals who 

had experienced more days of a symptom to bid more for thirty

days of relief. However, the estimated coefficients were not

significant, and the signs of the coefficients were not always

consistent across regressions.

The seemingly unrelated regressions (not reported) again

yielded comparable, but more efficient parameter estimates than

the ordinary least squares regressions. The correlation across

models is considerably stronger than was found in the one day

results. A correlation greater than .9 is found across the same

models as in the one day sample as well as across many other

models.

3-62
Table 3-8

Seven Light Symptom Thirty Day Survey Regression Results

Parameter Estimates

Intercept

Income

Education1

White

Age1

Sex

NoExh1th

Coughing

365.02

(1.45)

0.0007

(0.31)

-3.98

(-0.37)

-197.72

(-1.74)

-0.10

(-0.03)

-15.11

(-0.19)

-19.17

Sinus

Problems

258.35

(0.59)

0.0002

(0.05)

2.93

(0.15)

-133.96

(-0.66)

1.56

(0.32)

-20.76

(-0.15)

-26.44

(-0.22) (0.18)

Days of Depen- 6.93 0.08

dent Variable (1.79) (0.01)

F Value 1.51 0.14

R-Square 0.28 0.04

Note: t values in parentheses

Throat

Congestion

322.28

(0.96)

0.00095

(0.30)

6.91

(0.48)

-324.37

(-2.22)

1.07

(0.29)

49.26

(0.47)

-52.72

(-0.22)

-2.22

(-0.22)

0.84

0.18

Itchy

Eyes

135.52

(0.23)

0.062

(1.16)

29.50

(1.20)

-723.34

(-2.39)

5.61

(0.88)

-85.52

(-0.47)

-71.30

(-0.78)

-0.74

(-0.78)

1.37

0.26

3-63
Intercept

Income

Education1

White

Age1

Sex

NoExhlth

Days of Dependent Variable

F Value

R-Square

Table 3-8 (continued)

Drowsiness Headaches

449.52 615.88

(0.60) (0.57)

0.0072 0.007

(0.99) (0.73)

-18.35 55.30

(-0.56) (1.23)

5.85 -1027.00

(0.02) (-2.13)

5.48 -2.65

(0.65) (-0.23)

-194.53 -375.92

(-0.82) (-1.11)

-377.89 56.40

(-1.46) (0.16) 

3.07 1.17

(1.11) (0.38)

0.92 1.27

0.19 0.25

Nausea

159.09

(0.59)

-0.00013

(-0.05)

7.91

(0.61)

-100.50

(-0.88)

0.24

(0.08)

-187.54

(-1.98)

56.48

(0.58)

10.42

(1.03)

0.90

0.19

Note: t values in parentheses

3-64
Intercept

Income

Education1

White

Age1

Sex

NoExhlth

Dayssym1

Dayssym2

Dayssym3

Dayssym5

Dayssym6

Dayssym7

F Value

R-Square

Table 3-8 (continued)

BID- BID- BID- BID- PERS -

1233 5673 COMB3 US3 BID3

147,26 1057.77 -52.83 1051.17 -1267.41

(0.14) (0.32) (-0.02) (0.81) (-0.55)

0.0014 0.0051 0.017 -0.009 0.03

(0.14) (0.32) (0.72) (-0.75) (1.34)

52.42 33.55

(1.15) (0.42)

-500.35 -789.38

(-0.99)(-0.92)

6.90

(0.58)

-211.81

(-0.62)

21.16

(-0.62)

40.23

(1.46)

-18.57

(-0.84)

-57.01

(-1.29)

-

-

-

-

-

-

0.67

0.19

0.20

(0.01)

-810.01

(-1.32)

53.06

(0.09)

-

-

-

-

11.53

(1.95)

0.80

(0.17)

62.32

(1.02)

1.40

0.33

180.75 0.10 30.27

(1.62) (0.002) (0.30)

-2670.97 -118.13

(-2.37)(-0.21)

27.80

(0.97)

-574.83

(-0.71)

-465.29

(-0.52)

-

-

-

-

-

-

-

1.53

0.25

-9.37

(-0.66)

-235.54

(-0.58)

495.77

(1.11)

-

-

-

-

-

0.46

0.09

-210.71

(-0.21)

30.57

(1.19)

207.12

(0.29)

-324.67

(-0.41)

-

-

-

-

-

0.67

0.12

Note: t values in parentheses

3-65
3.6.4. Angina: Ten Day Endowment

3.6.4.1. Summary Statistics

Table 3-9 presents the means and standard deviations for

the data collected in the angina ten day surveys. The first

eight values are the dependent variables used in the regression

analysis. The bids vary from $261.84 to relieve ten days of

severe angina when the respondent is endowed with ten severe days

to $66.08 to relieve one mild day when only afflicted with one

mild day. The bids can be seen to vary according to the severity

and duration of the endowment, and according to level of relief

provided.

The relationships found between different bids are

supportive of the hypothesis of increasing marginal disutility of

illness. In general, the more severe or the greater duration of

the angina the respondent was asked to suppose he was endowed

with, the greater the amount bid. The mean bid for one day of

relief from mild angina when the respondent was endowed with ten

mild days is greater than the mean bid for the same amount of

relief when the respondent was endowed with only one day ($83.95

and $66.08 respectively). The same holds true for the bids for

relief from one severe day when endowed with either ten or one

days.

The independent variables that follow are similar to those

found in the light symptom surveys. A major difference is the

replacement of symptom days experienced with the variable,

HEARTCON, that indicates whether or not an individual respondent

has experienced a heart condition. This new variable should

permit similar explanatory effects on the magnitude of the bids

as well as allow for testing the existence of increasing marginal

disutility of this symptom. About one quarter of this sample had

ever experienced a heart condition.

The other independent variables are equivalent in nature

to those found in the earlier tables. It should be noted that a

slightly lower income figure and a higher average age are found

in this version.

3-66
Table 3-9

Means and Standard Deviations for

Angina Ten Day Survey

Standard

Variable Label Mean Deviation

BIDTEN1

BIDTEN2

BIDTEN3

BIDTEN4

BIDTEN5

BIDTEN6

BIDTEN7

BIDTEN8

Bid relieve 1 mild day when

have 1 mild day

Bid relieve 1 mild day when

have 10 mild days

Bid relieve 10 mild days when

have 10 mild days

Bid relieve 5 mild days when

have 10 mild days

Bid relieve 1 severe day when

have 1 severe day

Bid relieve 1 severe day when

have 10 severe days

Bid relieve 10 severe days when

have 10 severe days

Bid relieve 5 severe days when

have 10 severe days

66.08

83.95

154.36

96.18

123.59

144.74

261.84

192.90

55.68

102.30

165.21

103.87

101.63

145.72

244.80

195.03

3-67
Table 3-9 (Continued)

Standard

Variable Label Mean Deviation

INCOME

EDUC1

AGE1

WHITE

SEX

NOEXHLTH

HEARTCON

1983 income of household 25531.00 18842.70

(dollars)

Education of person 1 13.20 3.43

(years)

Age of person 1 (years) 50.33 17.79

1 if respondent is white, 0.85 0.36

0 otherwise

1 if female, 0 if male 0.50 0.51

1 if not excellent overall 0.70 0.46

health, 0 otherwise

1 if has heart condition, 0.25 0.44

0 otherwise

3-68
3.6.4.2. Regression Results

For both angina surveys, ordinary least squares and

seemingly unrelated regressions were performed to estimate

equation (3.8). Results for the ten day survey are presented in

Table 3-10. As in the seven light symptom results, there is

little support for the expected relationships between the

socioeconomic variables and the amounts bid for relief from

angina. Income always has a positive coefficient, but it is

never significantly different from zero. The signs of the

coefficients on other variables tend to vary. None of the

estimated coefficients is significantly different from zero.

The angina regression results do not provide support for

the existence of increasing marginal disutility of symptom days.

Neither the measure of general poor health status or the heart

condition experience variable had a significant positive effect

on the willingness to pay bids.

The insignificant effect of having a heart condition on

willingness to pay for angina relief may be partially due to the

definition of the variable. Unlike the symptom variables in the

seven symptom analysis, HEARTCON stems from a general question

concerning the respondent’s experience with any heart condition.

The endowments that are suggested here may be out of the range of

experience of most respondents. Therefore, even those who do

indicate having a heart condition may have never experienced

symptoms similar to those described. On the whole, experience

with the seven light symptoms is expected to explain bids better

than experience with a heart condition. The reason is that the

light symptom experience pertains exactly to the light symptom

bids, whereas heart condition experience at best bears only a

partial relationship to the angina bids.

The results of the seemingly unrelated regressions (not

reported) are extremely similar to the ordinary least square

results, but may be considered a more efficient estimate. A

strong correlation between models was found, with correlation

values consistently in the range of .8 or .9.

3-69
Intercept

Income

Education1

White

Age1

Sex

NoExhlth

Heartcon

F Value

R-Square

Table 3-10

Angina Ten Day Survey Regression Results

Parameter Estimates

BIDTEN1

114.32

(1.43)

0.00023

(0.30)

-2.37

(-0.55)

-5.07

(-0.15)

-0.69

(-0.85)

12.41

(0.55)

14.03

(0.53)

6.99

(0.23)

0.25

0.06

BIDTEN2

8.71

(0.08)

0.00026

(0.25)

0.85

(0.15)

3.90

(0.09)

0.10

(0.09)

39.19

(1.28)

23.17

(0.64)

23.17

(0.57)

0.48

0.11

BIDTEN3

153.69

(0.85)

0.00078

(0.45)

-5.01

(-0.51)

57.70

(0.77)

-1.21

(-0.66)

23.88

(0.46)

55.75

(0.92)

-21.65

(-0.32)

0.36

0.08

BIDTEN4

37.34

(0.26)

0.00017

(0.12)

-1.14

(-0.14)

45.16

(0.75)

-0.51

(-0.35)

38.67

(0.94)

62.38

(1.28)

-10.17

(-0.19)

0.45

0.10

Note: t values in parentheses

3-70
Table 3-10 (continued)

Intercept

Income

Education1

White

Age1

Sex

NoExhlth

Heartcon

F Value

R-Square

BIDTEN5

171.14

(1.16)

0.00046

(0.33)

-1.42

(-0.18)

-18.85

(-0.31)

-0.50

(-0.33)

-5.34

(-0.13)

13.37

(0.27)

-17.04

(-0.31)

0.12

0.03

BIDTEN6

260.26

(1.29)

0.0015

(0.79)

-8.11

(-0.74)

-17.09

(-0.20)

-0.007

(-0.004)

17.11

(0.30)

-63.43

(-0.94)

-1.26

(-0.02)

0.22

0.05

BIDTEN7

455.45

(1.56)

0.0038

(1.31)

-21.11

(-1.33)

60.69

(0.50)

-2.00

(-0.68)

28.99

(0.35)

16.88

(0.17)

-22.32

(-0.20)

0.66

0.14

BIDTEN8

321.29

(1.24)

0.0044

(1.79)

-18.19

(-1.29)

1.04

(0.01)

-0.0086

(-0.003)

54.97

(0.75)

-30.08

(-0.35)

-57.80

(-0.59)

0.68

0.15

Note: t values in parentheses

3-71
3.6.5. Angina: Twenty Day Endowment

3.6.5.1. Summary Statistics

Table 3-11 presents the means and standard deviations for

all variables used in the analysis of the survey that

incorporated an endowment of twenty days of angina. In this

version, the bids ranged from $844.38 to relieve twenty days of

severe angina to $90.24 for eliminating one day of mild angina a

month.

For a given number of days of relief from angina, the mean

bids tend to vary directly with the severity and duration of the

endowment. As explained above, this is seen as evidence of an

increasing marginal disutility of illness.

Two points should be raised concerning the size of the

bids. First, and most notably, is the difference between BIDTEN1

and BIDTWT1 as well as between BIDTEN5 and BIDTWT5. As described

above, the first and fifth bid requests are the same for each

survey. While BIDTEN1 and BIDTWT1 are relatively close, $66.08

and $90.24 respectively, BIDTEN5 and BIDTWT5 are quite far apart,

$123.59 and $278.88 respectively. A small part of the difference

may be explained by the differences in income in the two samples.

The ten day sample mean income was $25,531.00 while the twenty

day was higher at $29,950.10. This explanation assumes that

income has a strong positive effect on bid values. The

regression analysis presented below adds some support to this

proposition The difference in value can also be explained by

the outliers in the bids. Some respondents bid considerably

higher than others, but offered no grounds for removing them from

the sample. The importance of these bids can be seen by

observing the large standard deviation for BIDTWT5.

It should be noted that the twenty day results represent

more than a two-fold increase in bid values over the ten day

results. This point is consistent with increasing marginal

disutility since respondents on average are willing to pay

proportionately larger amounts for relief when confronted with

larger endowments.

3-72
Table 3-11

Means and Standard Deviations For

Angina Twenty Day Survey

Standard

Variable Label Mean Deviation

BIDTWT1

BIDTWT2

BIDTWT3

BIDTWT4

BIDTWT5

BIDTWT6

BIDTWT7

BIDTWT8

Bid relieve one mild day when

have one mild day

Bid relieve one mild day when

have twenty mild days

Bid relieve twenty mild days

when have twenty mild days

Bid relieve ten mild days

when have twenty mild days

Bid relieve one severe day

when have one severe day

Bid relieve one severe day

when have twenty severe days

Bid relieve twenty severe days

when have twenty severe days

Bid relieve ten severe days when

have twenty severe days

90.24

99.05

486.25

287.63

278.88

208.78

844.38

506.25

103.56

179.78

923.90

506.59

776.35

339.09

1609.94

1000.27

3-73
Table 3-11 (continued)

Standard

Variable Label Mean Deviation

INCOME 1983 income of household 29950.10

(dollars)

EDUC1 Education of person 1 14.15

(years)

AGE1 Age of person 1 (years) 48.13

WHITE 1 if respondent is white, 0.74

0 otherwise

SEX 1 if female, 0 if male 0.69

NOEXHLTH 1 if not excellent overall 0.67

health, 0 otherwise

HEARTCON 1 if has heart condition, 0.14

0 otherwise

23723.70

3.02

18.46

0.44

0.47

0.48

0.35

3-74
3.6.5.2. Regression Analysis

The ordinary least squares results are presented in

Table 3-12. Income tends to be a significant factor in the

determination of the bids. The estimated coefficient is positive

in all regressions, and significant at at least the 95 percent

confidence level in all but two of the regressions. No strong

relationships are found between the bids and the other

socioeconomic variables or health status measures.

The seemingly unrelated regressions (not reported) behaved

in a manner similar to that found in the ten day version and gave

results equivalent to the ordinary least squares method. The

correlation across models tended not to be as strong as the

angina ten day results. While many values were in the range of

0.8 and 0.9, there were also many values considerably lower or

even negative.

3-75
Intercept

Income

Educ1

White

Age1

Sex

NoExhlth

Heartcon

F Value

R-Square

Table 3-12

Angina Twenty Day Survey Regression Results

Parameter Estimates

BIDTWT1

-3.11

(-0.03)

0.0027

(3.48)

-2.45

(-0.40)

40.40

(1.02)

0.02

(0.02)

-26.75

(-0.71)

24.80

(0.72)

92.80

(1.82)

2.56

0.39

BIDTWT2 BIDTWT3

487.85 -873.41

(2.30) (-1.06)

0.00029 0.012

(0.19)

-11.77

(-0.98)

-114.07

(-1.47)

-1.53

(-0.79)

-150.99

(-2.03)

37.89

(0.56)

29.20

(0.29)

1.44

0.27

(2.06)

54.70

(1.17)

77.97

(0.26)

6.81

(0.90)

-212.20

(-0.73)

-185.22

(-0.70)

98.89

(0.25)

1.66

0.29

BIDTWT4

-130.71

(-0.28)

0.0082

(2.44)

10.36

(0.39)

2.40

(0.01)

2.55

(0.59)

-218.65

(-1.31)

8.36

(0.05)

22.75

(0.10)

1.81

0.32

Note: t values in parentheses

3-76
Table 3-12 (continued)

Intercept

Income

Educ1

White

Age1

Sex

NoExhlth

Heartcon

F Value

R-Square

BIDTWT5

-430.43

(-0.50)

0.023

(3.76)

-34.23

(-0.70)

212.08

(0.67)

-1.86

(-0.24)

407.64

(1.35)

176.86

(0.64)

-785.21

(0.96)

2.22

0.36

BIDTWT6

710.20

(1.77)

0.0049

(1.73)

-24.92

(-1.09)

95.36

(0.65)

-6.64

(-1.81)

-58.57

(-0.42)

-94.12

(-0.73)

-688.51

(1.73)

1.37

0.25

BIDTWT7

-1031.89

(-1.13)

0.03

(3.80)

25.14

(0.39)

447.37

(1.06)

5.88

(0.56)

125.71

(0.31)

-133.95

(-0.36)

2534.89

(0.77)

2.73

0.41

BIDTWT8

-581.14

(-0.76)

0.03

(5.28)

-30.14

(-0.70)

293.35

(1.05)

2.83

(0.41)

78.58

(0.29)

189.73

(0.78)

906.58

(0.81)

4.62

0.54

Note: t values in parentheses

3-77
3.6.6. _______ Summary and Implications ___ ___________

Two conclusions can be drawn from the empirical investigation of the willingness to pay bids for relief from light symptoms and angina. The first finding is that various pieces of

evidence support the hypothesis of increasing marginal disutility

of illness. As shown in section 3.6.1 this hypothesis follows

from the more standard assumption of decreasing marginal utility

from health. In the one day and thirty days light symptom surveys, respondents were asked to bid for one day or thirty days of

relief given their previous experience with the symptom. It was

notable in the one day survey that those respondents who had

experienced more days of a symptom tended to bid more for the

marginal day of relief. This offers support for the hypothesis

of increasing marginal disutility, though support was not found

in the regression analyses of the thirty day surveys. However,

considerable additional support was found for the hypothesis in

the angina surveys. In these surveys the respondents were asked

to suppose they experienced different endowments of angina, and

were then asked to bid for relief. Again, the results are seen

as consistent with the hypothesis of increasing marginal disutility of illness: respondents tended to bid more when they were

given endowments of increased severity or duration.

Second, the regression analyses yielded little support for

any strong relationships between various socioeconomic variables

and the willingness to pay bids. In a number of regressions

certain socioeconomic variables were significantly related to

willingness to pay; a case in point is the consistent and

significant positive impact of income on the bids for angina

relief in the twenty day survey. However, income was not always

an important explanatory variable in other sets of regressions.

As described in section 2.6 of Volume 2, one further finding

of the surveys was that the most important reason given as

explanation of the willingness to pay bids was to avoid the

discomfort of illness. This suggests that a respondent’s taste

for health, or his distaste for illness, will dominate the amount

he is willing to bid. In this situation it is not surprising

that no strong relationship was found between the socioeconomic

variables and the willingness to pay bids. There is no reason to

expect that a person’s taste for health will systematically vary

with these observable quantities. This pertains to a final

point on the methodology of contingent valuation. Some

researchers have argued that evidence that contingent values are

systematically related to socioeconomic variables such as income

tends to support the validity of the method. The converse is not

necessarily true: failure to find systematic relationships is

not necessarily indicative that contingent valuation methods are

faulty. The empirical analyses of the results of the four

surveys is entirely consistent with individuals making rational

choices over the value of health and reporting those values

accurately in a contingent valuation experiment. Unobservable

differences between individuals accounted for much of the

variation in bids.

3-78
3.7. MAIL QUESTIONNAIRE

3.7.1. __________ Background

It is clear that the personal interviews on which contingent

valuation was based produced the most complete and highest

quality data. It is also the case that personal interviews are

much more expensive than telephone and mail interviews.

Realizing that greater accuracy in estimation of willingness to

pay could be obtained through a larger number of interviews,

these less costly modes of survey research were considered.

Telephone interviews, which are intermediate in cost

between personal and mail interviews, were not chosen because the

relatively brief interviews required for telephone surveys would

not allow adequate time for thoughtful bidding. Also, a strong

possibility was seen that advance mailing of the tally sheet, use

of which by the respondent was essential to generation of a

reasoned set of bids, would significantly lower the response

rate. Instead, it was decided that an experimental mail survey

would be considered.

3.7.2. Design of the Mail Survey. ______ __ ___ ____ _______

The experimental mail survey was based on six common air

pollution induced symptoms. The pollutants that could cause such

symptoms included sulfur dioxide, nitrogen dioxide, ozone and

carbon monoxide. The mail survey was based on two questionnaires.

One included a set of comparative questions concerning earnings

lost and expenditures for physician visits, medicines, and other

medical expenses for each symptom. The second questionnaire was

identical to the first except for omission of these comparative

questions. This was done because it was anticipated that the

additional time and effort required to answer these memory based

comparative questions might significantly lower the response rate

to the mail survey.

The symptoms included in the mail questionnaires include

painful headache, coughing spells, stuffed up sinuses, itching

eyes, and heavy drowiness when driving. Respondents were asked

about their willingness to make monthly payments for an excellent

medicine that would eliminate a certain endowment of three

symptom days each month of each symptom. The medicine would only

have to be taken once a month, and it would be safe and have no

side effects. Respondents were also told that their bids for the

different symptoms would not be added to any multiple symptom

monthly total, that each symptom and the bid associated with it

would occur separately, without the other symptoms.

The common questions in the two mail surveys asked whether

the respondents had ever experienced each symptom (to establish

interest and focus, Q.1); the degree to which each symptom

bothers them (to encourage thoughtful variation in bids, Q.2);

reasons for choosing the amounts of the bids, Q.4). Demographic

3-79
information was also collected. The demographic variables

included sex and age of respondents, highest level of education,

number of persons in the household, and household income in 1983.

It was decided that the mail survey methodology would be

that known as the “Dillman Method.” This method indicates that

an approximately 70 percent response rate of the general public

could be achieved in a mail survey (Dillman, 1978).

3.7.3. ______ Sample and Response Rate ___ ________ ____

Reverse telephone directories for the Chicago metropolitan

area were used to draw a sample of 103 names and addresses, using

interval sampling with a random start. Business addresses were

excluded. Addresses without the name of the resident and those

with unlisted telephone numbers were included and addressed to

“Resident.” Questionnaire types A and B were alternated,

producing an almost equal number of mailings. Of the 103 mailed

questionnaires, 15 were returned to sender, indicating that the

subject had moved since publication of the reverse directories.

This yielded 88 possible mail interviews. Of this number, 42

completed questionnaires were returned, a response rate of 48

percent. This is a reasonably high response rate but below that

suggested by Dillman. Forty-two questionnaires is not a large

sample, but it is adequate for an exploratory survey and

analysis. The response rates for the two questionnaires were

exactly equal. The addition of the comparative expense questions

did not lower the response rate of the longer questionnaire.

3.7.4. Results of the Survey

The first question asked whether the respondent had ever

experienced each symptom. The results are shown in Table 3-13.

A majority of the respondents reported having experienced

every symptom except drowsiness when driving, which was reported

by 43 percent. The most commonly experienced symptom was stuffed

up sinuses.

Question 2 asked the degree to which each symptom bothered

the respondent. Only those who had experienced a symptom were

asked how much it bothered them. The results are shown in Table

3-14.

3-80
Table 3-13

WHETHEREVER EXPERIENCED SYMPTOM

Symptom Percent Ever Experienced

in the Symptom

Painful headache 71%

Coughing spells 55%

Stuffed up sinuses 81%

Irritated throat 69%

Itching and smarting 50%

of your eyes

Heavy drowsiness 43%

when driving

-----------

Number of cases 42

3-81
Table 3-14

HOW MUCH SYMPTOM BOTHERS THE RESPONDENT

Does Not Bothers Bothers Me

Symptom Bother Me Me Some A Lot

____________________________________________________

Painful headaches 30% 47 17

Coughing spells 35% 48 13

Stuffed up sinuses 22% 40 19

Irritated throat 20% 57 20

Itching eyes 22% 56 22

3-82

Heavy drowsiness 35% 40 10

when driving

_______________________________________________________
Table 3-14 (continued)

Bothers Me Total Mean Number of

Symptom A Great Deal Score% Cases

--------------------------------------------------------------

Painful headache 6 100% 3.8 30

Coughing spells 4 100% 2.9 23

Stuffed up sinuses 19 100% 3.4 37

Irritated throat 3 100% 3.1 30

Itching eyes *% 100% 3.0 23

Heavy drowsiness 15 100% 3.1 20

when driving

a . The mean score is based on Does not bother me = 2, Bothers me

some = 3, Bothers me a lot = 4, and Bothers me a great deal

= 5.

b . * = less than one percent.

3-83
All of the symptoms centered on “Bothers me some,” but both

the percentage distributions and the mean scores based on the

percentage distributions showed stuffed up sinuses to be the

symptom which bothered the respondents the most, averaging about

midway between “Bothers me some” and “Bothers me a lot.”

Question 3 asked about willingness to pay each month to

eliminate three symptom days of each symptom per month through

purchase of a safe, effective, side-effect-free medicine. The

results are shown in Table 3-15.

Personal discomfort symptoms mean bids were in the $8 to $9

per month range, representing yearly bids of about $100 to $115.

The average willingness to pay to eliminate heavy drowniness when

driving was about $5.40 per month, or $65 per year. The highest

willingness to pay was expressed for two symptoms: stuffed up

sinuses ($116 per year), which is consistent with the answers to

Question 2, in which stuffed up sinuses were reported to be the

most bothersome symptom, and to eliminate headache days ($113 per

year).

About 20 percent of the respondents did not bid on each

symptom because they had never experienced the symptom. The

question was not structured to exclude those who had never

experienced each symptom. Instead, most of those respondents who

had reported never having experienced a symptom spontaneously

decided not to bid on elimination of the symptom. A few of those

who had never experienced each symptom did make a bid, typically

zero.

Question 4 asked about the reasons for willingness to pay in

Question 3. The data on reasons are shown in Table 3-16.

The most common basis for willingness to pay bids was

personal comfort. About 84 percent of all respondents who bid

listed personal comfort as a reason for their bids. To avoid

loss of work or other usual activity was the next most frequently

mentioned reason, it was reported by 32 percent of the

respondents. The other reasons ranged between 10 and 20 percent

of the total.

The fact that only 14 percent of the respondents mentioned

the amount of their monthly income as being a basis for their

bids might suggest lack of realism in bidding. However, the

modest level of the bids, typically less than 10 dollars per

month, suggests that the budget constraint was taken into

consideration when bidding.

3-84
Table 3-15

WILLINGNESS TO PAY PER MONTH

TO ELIMINATE 3 SYMPTOM DAYS PER MONTH

Mean Amount Mean Amount Number of

Willing To Willing To Cases

Symptom Pay Per Mo. Pay Per Yeara

---------------------------------------------------------------------------

Painful headache $9.39 $113 33

Coughing spells 8.87 106 30

Stuffed up sinuses 9.68 116 34

Irritated throat 8.42 101 31

Itching eyes 8.63 104 27

Heavy drowsiness

when driving 5.41 65 27

a Calculated by multiplying the mean monthly bid by 12.

3-85
Table 3-16

REASONS FOR WILLINGNESS TO PAY AMOUNTS

Reasons Percent Mentioning

------------------------------------------------------------------

Comfort 84%

To avoid loss of work or 32%

other usual activity

Amount of monthly income 14%

Spend less for other medicines 16%

Spend less for doctor bills 11%

and other medical care

To not have to take other 19%

medicines

Other 11%

Number of cases 37

3-86
Question 5 in questionnaire B, which appeared only in the

Type B questionnaire, asked about symptom days experienced in the

last 12 months for each symptoms; days of work or other usual

activity lost; earnings lost, and medical-care expenses induced

by the symptom. Although 12 months may be too long a period for

accurate recall, it is also true that the symptoms included in

this question and elsewhere in the questionnaire are quite

seasonal in their incidence. This would imply that the use of a

time period of less than one year would have produced

considerable variation according to the month of the year in

which the survey was conducted. On balance, the data produced by

this question should be viewed as being approximate in accuracy.

The question about medical care expenses did not ask for

expenses net of any health insurance reimbursement. The phrasing

of the question suggests out-of-pocket expenditure. It should be

noted, however, that important, the relatively low costs of overthe-counter medications, doctor office visits and prescription

drugs measured here are not covered by most health insurance

policies.

The findings from question 5 are shown in Table 3-17. Mean

data are presented both for those who experienced each symptom

and across all respondents, to show aggregate personal and

financial impact.

Of the 21 Type B questionnaires, one was not completely

ascertained with respect to question 5, leaving 20 useable cases.

This is not a large number of cases, but a sample worthy of

explanatory analysis. The number of cases of the last three

symptoms--irritated throat, itching eyes, and drowsiness--was

quite small. The data for these symptoms should be viewed as

being merely suggestive.

The most frequently reported symptom was stuffed up sinuses,

reported by 80 percent of the respondents. The least frequently

reported symptoms were itching eyes (35 percent) and heavy

drowsiness when driving (20 percent). Stuffed up sinuses also

had the highest average number of symptom days--34 days per year

for those experiencing the symptom and 27 days averaged across

all respondents. Headaches were next most frequently reported,

averaging 28 days for those experiencing headaches and 17 days

averaged across all respondents. Itching eyes and heavy

drowsiness when driving were the least frequently reported

symptom days.

In terms of days of work or other work usual activity lost,

headaches produced the greatest mean number of days lost--1.9

days per year for those experiencing headaches and 1.1 days

averaged across all respondents. Stuffed up sinuses produced the

next greatest number of average days lost--0.9 days for those

experiencing stuffed up sinuses and 0.8 days averaged over all

respondents. No days of work or other usual activity lost were

reported for itching eyes and heavy drowsiness when driving.

3-87
Table 3-17

MEAN INCIDENCE OF SYMPTOM DAYS,

MEAN DAYS LOST, MEAN EARNINGS LOST,

AND MEAN MEDICAL CARE EXPENSE, LAST 12 MONTHS

Mean Mean Days

Had Symptom Symptom Work or

Symptom Last 12 Mos. Days Other Lost

------------------------------------------------------------------------------

Symptoma Allb Symptom All

-----------------------------------------------------------------------------------

Painful headache 60% 28 17 1.9 1.1

Coughing spells 50 9 4 0.6 0.3

Stuffed up sinuses 80 34 27 0.9 0.8

Irritated throat 60 8 5 0.3 0.2

Itching eyes 35 9 3 0.3 0.8

Heavy drowsiness

when driving 20 7 1 * *

-----------------------------------------------------------------------

Table 3-17 (continued)

Mean Mean Number

Earnings Medical o f

Symptom Lost Expense Cases

Symptoma Allb Symptom All

---------------------------------------------------------------------

Painful headache $179 $108 $100 $60 12

Coughing spells 67 31 4 2 10

Stuffed up sinuses 22 18 15 12 16

Irritated throat 8 5 5 3 12

Itching eyes * * * * 7

Heavy drowsiness

when driving * * * * 4

----------------------------------------------------------------------------

b : Symptom = all those reporting the symptom in the last 12 months.

a: All = mean across all 20 Type B questionnaire respondents.

3-88
Headaches also produced the greatest mean loss of earnings--

averaging $179 per year for those experiencing headaches and an

average of $108 for all respondents. Coughing caused the next

highest average loss of earnings - - $67 per year for those

experiencing coughing and an average of $31 for all respondents.

Stuffed up sinuses produced an average of $22 in earnings lost

for those experiencing this symptom and $18 for all respondent.

Headaches similarly produced the highest average medical expenses

averaged across all respondents. The next highest mean medical

expense was for stuffed up sinuses- -averaging $22 per year for

those experiencing stuffed up sinuses and an average of $17 per

year for all respondents.

In terms of comparison of willingness to pay with earnings

lost and medical care expenses, for those respondents reporting

each symptom it is clear that mean willingness to pay, shown in

Table 3-15, greatly exceeded both mean earnings lost and mean

medical expense, both separately and in combination, for all

symptoms except headache, where both mean earnings lost and mean

medical expense were of the same general magnitude as mean

willingness to pay. For headaches the mean earnings loss was

$179, the mean medical expense $100, and the mean willingness to

pay $113.

3.7.5. ------------

Demographics

Respondents were almost evenly divided between male (56

percent) and female (44 percent) respondents. The cover letter

asked that the adult who usually pays the bills complete the

questionnaire.

The age distribution of the respondents is shown in Table 3-

18.

The distribution of respondents according to age appears to

be reasonably representative of the age distribution among

adults.

The distribution of respondents by highest level of

education is shown in Table 3-19.

The distribution of respondents according to highest level

of formal education achieved shows the distribution to be broadly

representative, but showing a somewhat higher rate of

representation among those with higher education.

3-89
Table 3-18

AGE DISTRIBUTION OF RESPONDENTS

Age of Percentage

Respondent Distribution

----------------------------------------------------------

18-24 *%

25-34 29

35-44 19

45-54 15

55-64 17

65-74 15

75 and over 5

------------

Total 100%

Number of cases 41

3-90
Table 3-19

EDUCATION OF RESPONDENTS

Highest Level Percent

of Education Distribution

-------------------------------------------------------

Some grade school 5%

Completed grade school 5

Some high school *

Completed high school 20

Some college 25

Table 3-19 (continued)

Highest Level Percent

of Education Distribution

-----------------------------------------------------------------------------------------

Completed college 17

Some graduate work 13

A graduate degree 15

------------

Total 100%

Number of cases 40

3-91
The distribution of respondents by number of persons living

in the household is shown in Table 3-20.

The distribution of respondents according to size of

household shows that about half (51 percent) of the respondents

lived in a two member household, 15 percent in single member

households, and about one-third (34 percent) in households of

three or more persons.

The distribution of respondents by level of household income

in 1983 is shown in Table 3-21.

Although the household incomes of the respondents ranged

broadly across income levels, overrepresentation of those with

higher levels of income is evident.

3-92
Table 3-20

NUMBER OF PERSONS LIVING IN HOUSEHOLD

Number of Persons in Household Percent Distribution

One 15%

Two 51

Three 5

Four 22

Five 7

Six or more *

--------------

Total

Number of cases

100%

41

3-93
Table 3-21

HOUSEHOLD INCOME IN 1983

Household Income Percent Distribution

------------------------------------------------------------

Less than $3,000 *%

$3,000-4,999 3

$5,000-9,999 3

$10,000-14,999 14

$15,000-19,999 5

$20,000-24,999 8

$25,000-29,999 16

$30,000-39,999 16

$30,000-49,999 11

$50,000 and over 24

---------

Total 100%

Number of cases 37

3-94
3.7.6. _______ Summary of Results _ _ _______

An experimental mail survey was conducted to, determine

whether it would be feasible to greatly expand the number of

cases on which the contingent valuation estimates could be based.

As in the personal interview questionnaires, the indirect,

symptom based approach to willingness to pay was adopted, using

six common air pollution caused symptoms, including those caused

by general air pollution, ozone, and carbon monoxide. Two

questionnaires were developed, identical except that one

questionnaire, Type B, added a set of comparative questions which

measure, earnings lost and medical care expense occasioned by the

symptoms. The Dillman mail survey method was employed for this

survey.

An equal probability sample of 103 names and addresses

representing the Chicago metropolitan area adult resident

population was drawn from reverse telephone directories.

Discounting 15 addresses which had changed, a response rate of 48

percent of the 88 possible interviews was achieved, forming a

data based of 42 cases.

The symptom which was reported to be both most commonly ever

experienced and most bothersome was stuffed up sinuses.

The willingness to pay question was based on a certain

endowment of 3 symptom days per month for each symptom. The bids

were for an effective, safe, side-effect-free medication which

would have to be taken only once a month. The mean bids to

eliminate the personal discomfort symptoms of headache, coughing,

stuffed up sinuses, irritated throat, and itching eyes ranged

between $8.42 and $9.68 per month, or $101 and $116 per year.

The mean willingness to pay to eliminate heavy drowsiness when

driving was $5.41 per month, or $65 per year.

By far the most common reason underlying the amount of the

bids was personal comfort. Next most frequently mentioned was to

avoid loss of work or other usual activity.

The comparative set of questions again showed stuffed up

sinuses to be the most commonly experienced symptom, followed by

headaches, irritated throat, and coughing, which also were

common. Stuffed up sinuses showed the highest mean number of

symptom days per year--27 averaged across all respondents, with

headaches showing a mean 17 symptom days per year. However, in

terms of days of work or other usual activity lost, headaches

produced the largest mean number of days lost, 1.1 per year

averaged over all respondents. Earnings lost because of headache

was by far the largest--averaging $108 per year across all

respondents. Medical care expenses were also by far the largest

for headaches--averaging $60 per year over all respondents.

Coughing caused the next highest mean level of earnings loss and

stuffed up sinuses the next highest mean medical expenses. In

terms of comparative analysis, mean willingness to pay greatly

3-95
exceeded both mean earnings loss and medical expense and the

total of these two means for all symptoms except headaches, for

which mean willingness to pay, mean earnings lost and mean

medical expense all were of the same approximate magnitude.

Analysis of the demographic characteristics of the

respondents showed male respondents to be slightly more common

than female respondents, the age distribution to be approximately

respresentative, and the educational distribution to be somewhat

skewed toward those among those with higher levels of education.

Size of household proved to be mostly two-person households, with

a third of the households having three or more persons. The

distribution of household incomes showed overrepresentation of

those with higher levels of income.

As a final note, the results from the mail survey can be

compared to the data gathered through the presonal interviews.

The most direct comparison involves the seven light symptom one

day and thirty days surveys. The mean bids for the mail survey,

which considers the relief of three symptoms days per month, are

mostly intermediate in value between the one day and thirty day

means for comparable symptom. They are not however, three times

the one day mean bids nor one tenth of the thirty day means.

When examining the mail data, one also finds a positive

relationship between the mean bid for a symptom and the number of

days the symptom was actually experienced. The same relationship

was also clearly observed within the seven symptom one day data.

This observation adds further evidence to the proposition of an

increasing marginal disutility for experiencing a particular

symptom.

3.7.7. __________ References

1. Don A. Dillman, Mail and Telephone Survey: The Total

Design(New York: Wiley and Sons, 1978). In the Dillman method

the first mailing is followed three weeks later by a second

mailing and by a registered mail or special delivery third

mailing in the seventh week after the first meeting. In this

study the final meeting was via special delivery mail.

____ ___ _________ _______ ___ _____

______

3-96
APPENDIX

FIELD QUESTIONNAIRES FOR LIGHT SYMPTOM AND ANGINA

This appendix synthesizes the form field questionnaires

used in the contingent valuation studies of light symptoms and

angina. The form questionnaires pertain to:

1. Relief from one day of light symptoms;

2. Relief from 30 days of light symptoms;

3. Relief from up to 10 days of angina symptoms; and

4 . Relief from up to 20 days of angina symptoms.

3-97
A.1 7 - SYMPTOM HEALTH QUESTIONAIRE: ONE DAY

November 15, 1984 Version

Format _____________ City

Interviewer#

_______________

________ | Respondent#

Date [Check One]--

_________

__________________ | Center City

Time Started

__________

__________ | Suburban

Time Ended

___________

_____________ | Rural _____________

Hello. I’m ____________________ from the University of Illinois

School of Public Health. We are visiting with people in your

area as part of a research project about risks to your health. We

have scientifically selected a sample of households to represent

your area and your household has been chosen as part of the

sample.

Are you the [male/female] head of the household?

[If not, ask to speak to the head and start over.]

Your opinions are very important and we hope you will help

us. Please be assured that this is purely a research project and

we do not represent any business or product. No sales call will

result by your participation in this study. The information you

provide us will remain confidential.

The questionnaire will take about 30 minutes.

3-98
7 - SYMPTOM HEALTH QUESTIONNAIRE: ONE DAY

A. HEALTH EVALUATION

[Interviewer circle numbers.]

A-1. Would you describe your overall health as being

1 Excellent 2 Good 3 Fair 4 Poor

A-2. Please look at this card and tell me which statement best

describes the control you have over your health.

[Interviewer hand out card on ABILITY TO CONTROL HEALTH.]

1 There is little I can do because it is beyond my

control.

2 I can do some things, but they have little effect.

3 My actions have a moderate effect.

4 My actions have a great effect.

[Interviewer take card from respondent. ]

A-3. How often were you bothered by any illness, bodily

disorders, aches or pains, during the last month?

Every day 1

Almost every day 2

About half of the time 3

Now and then, but less than

half of the time 4

Rarely 5

None of the time 6

3-99
7 - SYMPTOM HEALTH QUESTIONNAIRE: ONE DAY

H. HEALTH STATUS

Now we are going to talk about whether you have certain

health problems and how they have occurred. Most people have

difficulty remembering how many times they have experienced these

problems, but it is important that you try to remember about how

often you have had them. The health problems are listed on this

card.

[Hand respondent Health Problem card.]

H-1. Which of the health problems on the card have you experienced in the last 12 months?

[For any health problem named, circle the number at the top of

the column corresponding to the symptom. Remember to turn the

page to complete each question.]

3-100
7 - SYMPTOM HEALTH QUESTIONNAIRE: ONE DAY

(Questions) 1 2 3 4

___________

I

I

H-2. About how I

many days have \ /

you had this in the

last 12 months? ____days ____ days ____ days ____ days

H-3. Which of

these bothered

you the most?

1-most, 7-least ____ ____ ____ ____

H-4. During the last year

did this health problem

cause you to miss one

or more days of usual

activity such as work,

school, or work at home?

Write H for housework,

N for no activity missed,

S for school, W for

work away from home. ____ ______ ______ ______

H-5. About how many days

of work or other

usual activity did

you lose because of

this? days days days days ____ ____ ____ ____

H-6. Were there one or

more days during the last

year when this health problem

caused you to greatly reduce

your normal activities?

Enter number

of days. days days days days ____ ____ ____ ____

3-101
7 - SYMPTOM HEALTH QUESTIONNAIRE: ONE DAY

___________

(Questions)

H-2. About how

many days have

you had this in the

last 12 months? days days days ____ ____ ____

H-3. Which of

these bothered

you the most?

1-most, 7-least ______ ______ ______

H-4. During the last year

did this health problem

cause you to miss one

or more days of usual

activity such as work,

school, or work at home?

Write H for housework,

N for no activity missed,

S for school, W for

work away from home. ______ ______ ______

H-5. About how many days

of work or other

usual activity did

you lose because of

this?

H-6. Were there one or

more days during the last

year when this health problem

caused you to greatly reduce

your normal activities?

Enter number

of days.

days days days ____ ____ ____

days days days ____ ____ ____

3-102
7-SYMPTOM HEALTH QUESTIONNAIRE: ONE DAY

_________________________________________

STUFFED

COUGHING UP THROAT ITCHING

SPELLS SINUSES CONGESTION EYES

------------------------------------

1 2 3 4

H-7. During the last year

did you purchase any

medicine for this health

problem, either over the

counter or with a

prescription?

Check for yes.

H-8. About how much did

you spend for this

medicine?

H-9. How much of this

cost (if any) was paid

by insurance or

any other health

plan?

________ ________ ________ ________

$ ________$ ________ $ ________ $ ________

$ ________ $ ________ $ ________ $ ________

H-10. During the last year

did you visit a doctor,

clinic, hospital, or

other source of professional

medical care for this

problem?

Enter number of

visits. _______

H-11. About how

much did these

visits cost

during the last

year? $ _______

H-12. About how much of

this cost was paid by

insurance or any

other plan? $ _______

H-13. [If Work Days Lost in H-5]

About how much earnings

were lost because of

work days missed? $ _______

_______ ________ ________

$ _______ $ ________ $_______

_______ _______ _______

_______

$ $ $

$_______ $ _______ $

3-103
7 - SYMPTOM HEALTH QUESTIONNAIRE: ONE DAY

H-7. During the last year

did you purchase any

medicine for this health

problem, either over the

counter or with a

prescription?

Check for yes.

H-8. About how much did

you spend for this

medicine?

H-9. How much of this

cost (if any) was paid

by insurance or

any other health

plan?

________ ________ ________

$ ________ $ ________ $ ________

$ ________ $________ $ ________

H-10. During the last year

did you visit a doctor,

clinic, hospital, or

other source of professional

medical care for this

problem?

Enter number of

visits. _______ _______ _______

H-11. About how

much did these

visits cost

during the last

year? $_______ $_______ $_______

H-12. About how much of

this cost was paid by

insurance or any

other plan? $_______ $ _______ $_______

H-13. [If Work Days Lost in H-5]

About how much earnings

were lost because of

work days missed? $ _______ $ _______ $ _______

3-104
7 - SYMPTOM HEALTH QUESTIONNAIRE: ONE DAY

H-14 Did you have any of the symptoms in combination? [Check

one]

Yes ________ No ________ [Skip to Section M.]

H-15 What combination did you have most often? [1 = Coughing

spells. 2 = Stuffed up sinuses. 3 = Throat congestion. 4 =

Itching eyes. 5 = Headache. 6 = Heavy drowsiness. 7 = Nausea.

For example, a combination of stuffed up sinuses, itching eyes

and headache should be recorded as 2,4,5.]

Combination ________________________

3-105
7 - SYMPTOM HEALTH QUESTIONNAIRE: ONE DAY

M. DEFENSIVE MEASURES

Now I would like to ask you some questions about your day-today living that are related to the symptoms we have been

discussing.

M-1 Do you have any of the following in your home or car,

purchased for health reasons?

Air Conditioner YES ______ NO_______

Air Purifier YES ______ NO_______

Humidifier YES ______ NO_______

Other ( ____________ )

M-2 Do you smoke?

YES ______ NO_______

Yes ______ [Skip to M-3]

No _______

(a) Did you ever smoke? Yes ______ No [Skip to M-2(c)] _______

(b) Did you quit for

health reasons? Yes ______ No ______

(c) Would you smoke if

smoking were not

damaging to your health? Yes ______ No ______

M-3 Have you ever changed to location of your residence for

health reasons?

Yes __________

No________ [Skip to Section R]

M-4 Where did you move from? _________________

M-5 To? ___________________

M-6 What health problem prompted the move? ___________________

3-106
7 - SYMPTOM HEALTH QUESTIONNAIRE: ONE DAY

R. RANKING OF SYMPTOMS

In this next set of questions, I’m going to describe several

symptoms of discomfort that are common to many people. The

symptoms will not necessarily describe what you experience. I

would like you to put yourself in the position of having these

symptoms, however.

I want you to suppose that your health in the next 12

months is going to be like it was in the past 12 months, except

that you will experience an additional day of a given symptom.

First we’re going to talk about which of the symptoms you

consider to be worst, and which you would be bothered by the

least.

Everyone has experienced coughing. Please look at this

card, which describes a particular coughing experience.

[Hand respondent Coughing Days card]

The card describes the one additional day on which coughing

occurs. You will cough about twice an hour in spells that last 10

to 20 seconds. You will feel the cough in your chest, but it is

not severe enough to make you red in the face.

I am going to pause briefly to let you think about how much

you would mind the one additional day of coughing.

[Interviewer pause for 15 seconds]

Now suppose that, instead of having the one additional day

of coughing, you will have one additional day of sinus problems

in the next 12 months. In other respects, your health will be

exactly as it has been in the last 12 months.

A day of sinus problems is described on this card.

[Interviewer hand respondent Days of Sinus Problems card]

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7 - SYMPTOM HEALTH QUESTIONNAIRE: ONE DAY

You will have congestion and pain in your sinuses and

forehead all day. You will be bothered by a feeling of stuffiness

in your head, accompanied by sinus drainage in your throat. You

will need to blow your nose every few minutes. You will have to

breathe through your mouth most of the time.

Please think over how much you would be bothered by the one

additional day of sinus problems, and compare it to the day of

coughing. Think about which symptom you mind the least and which

the most.

When you have decided, please tell me which bothers you

more.

[Check one]

__________ One Coughing day

__________ One Day of sinus problems

Place that card under the other card.

[Wait for respondent to arrange cards]

Another problem that bothers people is throat congestion.

Here is a card describing a day of throat congestion.

[Hand respondent card on Day of Throat Congestion]

On this day, you will have congestion in your throat and

upper respiratory tract. You will make repeated efforts to clear

your throat. The throat clearing is annoying to you and those

around you. Your throat will be scratchy. Your voice will be

hoarse, and you will have some difficulty speaking.

Suppose that instead of either the coughing or the sinus

problems, you will have one additional day of throat congestion,

as described on the card.

Please rank the 3 symptoms. The question is which day

bothers you the least, which the next least, and which bothers

you the most.

Take your time.

Place the three cards in the order you have decided on.

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7 - SYMPTOM HEALTH QUESTIONNAIRE: ONE DAY

[Interviewer check to see cards are in proper order. If

respondent has difficulty in ranking the days, read the following

three indented paragraphs. If respondent has difficulty in

ranking later on in the questionnaire, return and read these

paragraphs, Otherwise, do not read the indented paragraphs to

the respondent]

If there are symptoms that bother you the same,

cards for those days should be next

to each other in the deck. It does not matter

which comes before the other.

For example, if you don’t care whether you have

coughing or sinus problems, either of the two

cards may be on top.

[Interviewer be sure that the cards for any group within which

there is indifference are in their proper place in the deck,

showing how this group ranks relative to the other days.]

Symptoms that you mind less than coughing and

sinus problems should be on the

top, symptoms that mind more should be on the

bottom.

[Resume text if indented paragraphs were not read]

Let’s go on to eye irritation. Here is a card describing a

day with this type of problem.

[Hand respondent card on Days of Itching and Smarting of Eyes]

Watering and smarting of your eyes on this day forces you to

interrupt what you are doing every 15 minutes or so. You rub your

eyes and close them. Stinging of your eyes brings tears three

times during the day--bad enough to cause you to use a

handkerchief or kleenex around your eyes.

We want to proceed as before. Please think about how much

you mind one additional day of this sypmtom and how you rank it

with the others.

[Wait until respondent has finished arranging cards]

Next we consider a day on which you have headaches. Here is

the card that describes the headache experience.

3-109
7 - SYMPTOM HEALTH QUESTIONNAIRE: ONE DAY

[Hand respondent Headache Day card]

Two rather painful, splitting headaches will strike some

time during the day. Each period of headache will last 2 hours.

Please proceed as before. Think about how much you mind

the additional day of headaches. After you have decided, put the

card in its proper place in the deck.

[Wait until respondent is through]

We have a couple of more symptoms to consider. The next one

is drowsiness. Here is a card describing a day when you are

bothered by heavy drowsiness.

[Hand respondent Heavy Drowsiness card]

You will have extreme difficulty staying awake during 6

of the hours when you are normally awake. Sometimes your eyelids

will flutter. You will doze off for an instant now and then.

The drowsiness will interfere

other leisure. You will find

comes over you while you are

appliances or other machinery.

After thinking about one

with your social activities and

the drowsiness dangerous if it

driving or working with tools,

additional day when you have

drowsiness, add the card to the deck to reflect where it comes in

your ranking.

[Wait for respondent to finish, and then proceed]

The last symptom is nausea. Here is a card about it.

[Hand respondent Nausea card]

Throughout the day, you will have a lingering urge to vomit,

but you will not be able to do so. Stomach distress will be

strong. There will be no actual pain.

As before, think about how you rank one additional day of

nausea, and place it in the deck.

Thank you. I’m going to record your answers for use later.

Let’s keep the deck sitting there. We’ll use it in a minute.

[Interviewer record rankings on Tally Sheet.]

3-110
7 - SYMPTOM HEALTH QUESTIONNAIRE: ONE DAY

CV. CONTINGENT VALUATION

In this next set of questions, I’m going to ask you how much

it would be worth to you to avoid the symptoms we’ve been talking

about.

The answers in this part are for yourself alone and not for

any other members of your household.

Before we start, please look at this card showing how a

typical family spends its take-home income.

[Hand respondent Household Spending card]

When you pay to avoid symptoms, the money will have to come

out of one of the categories shown. We’ll leave the card here so

that you can think about where the money comes from that you

would spend to avoid the symptoms. Keep in mind, however, that

your situation is probably different from this one.

Let's think about ways we normally deal with health

problems. One way is to go to the doctor, another way is to buy

medicine at the drugstore. Oftentimes we don’t do anything at

all --we just suffer through the problem until it goes away. It

might be that the price of a bottle of medicine or a visit to the

doctor measures the value of a cure. But if we stop to think

about it, the cure might be worth much more to us than that--if

we really had to pay it. A cure might be valuable to us even

when we just suffer with the problem until it goes away. In such

cases we might ask ourselves “How much would I be willing to pay

to get rid of this problem right now, even if I don’t want to

take medicine or visist the doctor?”

With these thoughts in mind, please try to give the largest

dollar value a cure would be worth to you when answering the next

few questions.

Now look at the card at the top of the deck--[symptom]--

which is the symptom you mind least.

3-111
7 - SYMPTOM HEALTH QUESTIONNAIRE: ONE DAY

CV-1. If your health symptoms in the next 12 months were the

same as in the last 12 months, except that you would also be

faced with one additional day of [symptom], would it be worth

$100 to you to completely get rid of these days of symptoms?

[Circle one]

Yes No

CV-2. [If answer to CV-1 is Yes, ask if getting rid of the day

would be be worth $200, $400--doubling each time until a No

response is obtained. Then subtract half the difference between

the two previous answers. Continue adding or subtracting half

the difference between the last two answers until respondent no

longer wants to change.]

[If answer to CV-1 is No, ask $50, $25--decreasing by half

until a Yes response is obtained. Then add half the difference

between the two previous answers, continuing with the half

difference procedure until respondent no longer wants to change.]

[Record final bid at top of tally sheet.]

Next look at the card at the bottom of the deck which is the

symptom you mind the most.

[Interviewer: For the following two questions, you will need a

calculated bid for CV-3. The calculated bid for CV-3 is the bid

to get rid of the least bothersome day given in the answer to CV2, multiplied by two.]

CV-3. If your health symptoms were the same in the next 12 months

as in the last 12 months, except that you would also be faced

with one day of the symptom you mind the most, would you be

willing to pay [calculated bid for CV-5] to completely get rid of

the symptoms on that day? [Circle one]

Yes No

CV-4. [If the answer to CV- is Yes, ask if respondent would be

willing to pay double the calculated bid for CV-3. Proceed by

further doubling until a No answer is obtained. Then subtract

half the difference between the first No amount and the last Yes

amount. Continue increasing or decreasing by half the difference

until a final bid is obtained.]

3-112
7 - SYMPTOM HEALTH QUESTIONNAIRE: ONE DAY

[If the answer to CV-3 is No, ask if respondent would be

willing to pay half the calculated bid for CV-3. Proceed by

halving until a Yes answer is obtained. Then add half the difference between the first Yes amount and the last No amount.

Continue increasing or decreasing by half the difference until a

final bid is obtained]

[Record Final bid at bottom at tally sheet.]

I have here a tally sheet for you to keep track of your

answers. [Interviewer hand respondent Tally Sheet]

Here is a pencil. [Interviewer hand respondent pencil]

The first column of the Tally Sheet is called “Symptom Days

Ranked from Least to Most Bothersome”. In this column, I have

written the symptoms in the correct order from the deck of cards

you have arranged.

The second column of the Tally Sheet is your Bid to avoid

additional symptom day. The dollar amounts you have given are

for the first and last lines in this column.

At this point, think about how much you would be willing to

pay to avoid one additional day of the other five symptoms that

you placed between the least and most bothersome,

Take as much time as you need to decide on the amounts you

would be willing to pay to avoid each symptom day. As you decide

on the amounts, record them.

People often find that they want to change the bids

originally given for the least and most bothersome days. They

often take several tries at each entry in the column.

3-113

Feel free to change any of the amounts as much as you want.

In this part, people find themselves using the eraser a lot.
7 - SYMPTOM HEALTH QUESTIONNAIRE: ONE DAY

Tally Sheet

RANKING OF SYMPTOMS

FROM LEAST TO MOST

BOTHERSOME

1) ___________

2) __________

3) ___________

4 ) ___________

5) ___________

6) ___________

7) ___________

BID FOR ONE DAY OF

RELIEF IN THE NEXT

12 MONTHS

$ ___________ per year

$ ___________per year

$ ___________ per year

$ ___________per year

$ ___________ per year

$ ___________per year

$ ___________per year

3-114
7 - SYMPTOM HEALTH QUESTIONNAIRE: ONE DAY

[Interviewer wait for respondent to complete the column. Avoid

any appearance of impatience]

CV-5. So far we have been considering the symptoms individually. Sometimes, however, they occur together.

Suppose you faced one day in the coming year in which you

had the three following symptoms on a single day. [Interviewer

hand respondent cough, sinus, throat card.] You would have

coughing, stuffed up sinuses and throat congestion on that day.

Look at your bids for these three individual symptoms on the

Tally Sheet. Let’s add them up.

[Interviewer compare sum with respondent. Record sum]

Sum of individual bids:

_________ dollars

Think about whether you would be willing to pay more or less

than this sum to get rid of one day on which all 5 of the

symptoms occur together. When you are ready, please tell me how

much are you willing to pay to get rid of the one day of combined

symptoms.

Bid to get rid of one day of combined cough,

sinus and throat symptoms:

_______________ dollars

CV-6 Now suppose that you faced 1 day in the coming year of

these three symptoms. [Interviewer hand respondent Headache,

Nausea, Drowsiness card.] You would have headache, nausea, and

drowsiness.

Once again, let’s add up your bids for the individual

symptoms.

[Interviewer compare sum with respondent. Record sum.]

Sum of Individual bids:

________ dollars

3-115
7 - SYMPTOM HEALTH QUESTIONNAIRE: ONE DAY

How much would you be willing to pay to get rid of 1 day on

which all 3 of the symptoms occur together?

Bid to get rid of 1 day of headache,

nausea and drowsiness:

--------dollars

CV-7. Your answers so far have been about how much you would

pay for relief of yourself alone.

Look again at the card for combined coughing, sinus and

ingestion symptioms. How much would your household be willing to

pay to relieve the one day of combined symptoms for yourself and

every other member of your household.

Bid for relieving household of

one day of combined symptoms

___________________ dollars

CV-8. I have one final question on amounts you are willing to

pay. Suppose that everybody in the United States faced one additional day of combined coughing, sinus and congestion symptoms.

How much extra would your household be willing to pay for

everybody’s symptoms to be eliminated on this day? This is in

addition to the amount you just stated for your household alone.

Addition to household payment to get rid of day of

combined symptoms for everybody in the United States:

____________________ dollars

3-116
7 - SYMPTOM HEALTH QUESTIONNAIRE: ONE DAY

RE. REASONS

The value questions are now complete, but before we move on,

would you tell me what the major reasons were for your answers.

Here is a card that list some reasons.

[Interviewer hand respondent Reasons card]

[Interviewer: The following list will be needed to record the

ranking of reasons in question RE-1]

-----------

-----------

-----------

-----------

-----------

-----------

RE-1. Please look at the card and

Comfort

Loss of work at home

Loss of work away from home

Loss of recreation

Reduce medical expenses

Other (Specify)

tell me the most important

reason for the amounts you were willing to pay.

[Interviewer enter “1” beside the reason given as answer]

Please continue with the next most important reason, the one after

that, and so forth for all the reasons that influenced your bid.

[Interviewer enter “2” beside the next most important reason, “3”

beside the one after that, and so forth for all reasons mentioned

by respondent]

3-117
7 - SYMPTOM HEALTH QUESTIONNAIRE: ONE DAY

RE-2. [This question is for respondents who have experienced

one or more of the health problems as reported in H-1. For

respondents who didn’t experience any of the health problems,

skip to RE-4.]

Could you tell me how the symptoms you actually experienced

during the last 12 months compared with the symptom days

described in this questionnaire. Please indicate whetheryour

symptoms were worse than, about the same, or less severe than

those described.

[W=worse. S=same. L=less

dent did not have the symptom]

severe. Make no entry if responCoughing

Sinuses

Throat Congestion

Itching Eyes

Headaches

Heavy Drowsiness

Nausea

RE-3. Concerning the seven symptoms

how much would you be willing to pay to

symptoms you have actually experienced?

___________

we have been discussing,

completely get rid of the

dollars

RE-4: Because we want your best answers, I am asking you once

again whether you would like to go back and change any of your

bids or rankings given in your responses to previous questions.

Do you want to change any of your answers? [Circle one]

Yes No

[Allow respondent to change any answers. Record all changes

made by respondent in appropriate places on questionaire.]

3-118
7 - SYMPTOM HEALTH QUESTIONNAIRE: ONE DAY

Please give me back all the cards you have. These include

the symptom cards, the family spending card and the reasons card.

Also please give me the Tally Sheet you have filled out.

[Interviewer take back cards and Tally Sheet. INSERT TALLY SHEET

INSIDE THIS QUESTIONNAIRE IMMEDIATELY AFTER THE FIRST PAGE]

3-119
7 - SYMPTOM HEALTH QUESTIONNAIRE: ONE DAY

S. SOCIOECONOMIC QUESTIONS

So that we can analyze the responses we get from different

people, we need to ask you a few questions about your household.

Your answers will be completely confidential.

S-1. Have you moved during the last 5 years? ___________

S-2. What is the farthest you moved? ______________

S-3. Do you expect to move in the next 3 years? ___________

S-4. What is your occupation? _______________________

[Hand respondent Skills card.]

S-5. Among the items on this list, tell me which you like to

do or are good at, and which you dislike or feel you’re not very

good at. If you have no particular feeling about the item, tell

me “no opinion.”

[Mark 1 for like/good at; O for dislike/not good at; No for no

opinion.]

A. Arithmetic/Mathematics

B. Foreign languages

C. Reading newspapers/magazines/books

D. Interpreting blueprints/diagrams for

assembling kits or models

E. Interpreting financial/tax statements

_____________

______________

_____________

______________

_____________

3-120
7 - SYMPTOM HEALTH QUESTIONNAIRE: ONE DAY

S-6 Use the instructions on this page to complete the table on

the next page.

Number: Each person is assigned a number, 1, 2, 3, etc. Circle

the number which represents the respondent.

Relationship: Indicate the customary family relationships

(spouse, son, grandmother, etc.). For non-family relationships,

just write “friend.”

Education: What is the highest grade or year in school

completed?

None

Elementary

High School

College

Some Graduate School

Graduate or Professional Degree

School: Is ------ currently attending a school, college or

university full-time?

Work: Does------ usually work [or seek employment] outside the

household?

If No, go to next person.

If Yes, continue .

Months : How many months did work in 1983?

Hours :

------

How many hours/week did usually work in 1983?

Wage :

------

[Record either hourly, weekly or monthly wage.]

3-121
7 - SYMPTOM HEALTH QUESTIONNAIRE: ONE DAY

ANSWERS TO S-7

3-122
7 - SYMPTOM HEALTH QUESTIONNAIRE: ONE DAY

S-7. [Race/ethnic group, of respondent. Interviewer Check One].

Asian _________

Black_________

Hispanic ----——

White _________

Other ________

S-8. In your household, do you: [Check One]

a. ---- share or pool your incomes, as a family or couple might

do.

b. ----– live alone, or keep your personal incomes separate, as

friends sharing a house/apartment might do.

S-9. [Present Income Card] Please look at this card. Tell me

which letter best describes your [household if S-8a; or personal

if S-8b] income before taxes in 1983. Include income from all

sources, including work, investments, business profits, interest

on savings, pensions, social security, support from relatives,

and any other benefits.

----- [Letter]

----- [Refused, or didn’t know and refused

to guess].

S-10. Was your personal income in 1983 [Check One]

a. about the same as other recent years?

b. much higher than in other recent years? ----

c. much lower than in other recent years? ----

S-11. In 5 years time, do you expect your income to be:

a. about the same as in 1983? ----

b. much higher than in 1983? ----

c. much lower than in 1983? ----

S-12. Do you lose pay when you miss a day of work because of

sickness?

Yes --------

No ---------

3-123
7-SYMPTOM HEALTH QUESTIONNAIRE: ONE DAY

S-13. [Does your household if S-8a; Do you if S-8b]

[Check One]

a. manage to save or invest a little? -----

b. just get by on current income? -----

c. have to dip into savings or

investments just to make ends meet? -----

S-14. If you wanted to work a few more [or “a few” for non-income

earners] hours a week, do you think you could find work?

Yes ------- No-------

S-15. [If Yes] How much do you think you’d be paid?

S-16. Do

$ -----/HOUR 

you own your residence or do you rent it?

Own-------

Rent ------ [Skip to S-16c.]

[If own]

a) About what fraction of the value of your

house is the outstanding balance on the

mortgage?

For example if the house value is

$10,000, then the mortgage balance

is a fraction of the house value is 1/5.

b) If you had to pay off all of your debts,

except your mortgage, would you be able to do

so without borrowing any money or selling your

home?

Yes --—-—-—-- [Go to S-27]

No ---------- [End Interview]

[If rent]

If you had to pay off all of your debts, would you

be able to do so without borrowing any money?

Yes ---------- [Go to S-27]

No ----------- [End Interview]

3-124
7-SYMPTOM HEALTH QUESTIONNAIRE: ONE DAY

S-17. Would the amount left be as much as your yearly income?

Yes ---------

No ----------

S-18. Do you have any other comments about the subject we

discussed? [Interviewer enter answers on last page, along with

your own comments.]

3-125
7-SYMPTOM HEALTH QUESTIONNAIRE: ONE DAY

I.E. INTERVIEWER EVALUATION

Record any comments which might help us understand the

answers given by the respondent, especially those who protest

during the bidding questions.

3-126
A.2 7-SYMPTOM HEALTH QUESTIONNAIRE: 30 DAYS

(Same in all respects as one day version of 7-Symptom Health

Questionnaire, except for R. and CV sections reproduced here.

R. RANKING OF SYMPTOMS

In this next set of questions, I’m going to describe several

symptoms of discomfort that are common to many people. The

symptoms will not necessarily describe what you experience. I

would like you to put yourself in the position of having these

symptoms, however.

I want you to suppose that your health in the next 12

months is going to be like it was in the past 12 months, except

that you will experience an additional 30 days of a given symptom.

First we’re going to talk about which of the symptoms you

consider to be worst, and which you would be bothered by the

least.

Everyone has experienced coughing. Please look at this

card, which describes a particular coughing experience.

[Hand respondent Coughing Days card]

The card describes the 30 additional days on which coughing

occurs. You will cough about twice an hour in spells that last 10

to 20 seconds. You will feel the cough in your chest, but it is

not severe enough to make you red in the face.

I am going to pause briefly to let you think about how much

you would mind the 30 additional days of coughing.

[Interviewer pause for 15 seconds]

Now suppose that, instead of having the 30 additional days

of coughing, you will have 30 additional days of sinus problems

in the next 12 months. In other respects, your health will be

exactly as it has been in the last 12 months.

A day of sinus problems is described on this card.

[Interviewer hand respondent Days of Sinus Problems card]

3-127
7-SYMPTOM HEALTH QUESTIONNAIRE: 30 DAYS

You will have congestion and pain in your sinuses and

forehead all day. You will be bothered by a feeling of stuffiness

in your head, accompanied by sinus drainage in your throat. You

will need to blow your nose every few minutes, You will have to

breathe through your mouth most of the time.

Please think over how much you would be bothered by the 30

additional days of sinus problems, and compare it to the 30 days

of coughing. Think about which symptom you mind the least and

which the most.

When you have decided, please tell me which bothers you

more.

[Check one]

--------- 30 Coughing days

---------- 30 Days of sinus problems

Place that card, under the other card.

[Wait for respondent to arrange cards]

Another problem that bothers people is throat congestion.

Here is a card describing a day of throat congestion.

[Hand respondent card on Day of Throat Congestion]

On these days, you will have congestion in your throat and

upper respiratory tract. You will make repeated efforts to clear

your throat. The throat clearing is annoying to you and those

around you. Your throat will be scratchy. Your voice will be

hoarse, and you will have some difficulty speaking.

Suppose that instead of either the coughing or the sinus

problems, you will have 30 additional days of throat congestion,

as described on the card.

Please rank the 3 symptoms. The question is which day

bothers you the least, which the next least, and which bothers

you the most.

Take your time.

Place the three cards in the order you have decided on.

3-128
7-SYMPTOM HEALTH QUESTIONNAIRE: 30 DAYS

[Interviewer check to see cards are in proper order. If

respondent has difficulty in ranking the days, read the following

three indented paragraphs. If respondent has difficulty in

ranking later on in the questionnaire, return and read these

paragraphs. Otherwise, do not read the indented paragraphs to

the respondent]

If there are symptoms that bother you the same,

cards for those days should be next

to each other in the deck. It does not matter

which comes before the other.

For example, if you don’t care whether you have

coughing or sinus problems, either of the two

cards may be on top.

[Interviewer be sure that the cards for any group within which

there is indifference are in their proper place in the deck,

showing how this group ranks relative to the other days.]

Symptoms that you mind less than coughing and

sinus problems should be on the top, symptoms that

mind more should be on thebottom.

[Resume text if indented paragraphs were not read]

Let’s go on to eye irritation. Here is a card describing a

day with this type of problem.

[Hand respondent card on Days of Itching and Smarting of Eyes]

Watering and smarting of your eyes on these days forces you

to interrupt what you are doing every 15 minutes or so. You rub

your eyes and close them. Stinging of your eyes brings tears

three times during the day- --bad enough to cause you to use a

handkerchief or kleenex around your eyes.

We want to proceed as before. Please think about how much

you mind 30 additional days of this sypmtom and how you rank it

with the others.

[Wait until respondent has finished arranging cards]

Next we consider days on which you have headaches. Here is

the card that describes the headache experience.

[Hand respondent Headache Day card]

3-129
7-SYMPTOM HEALTH QUESTIONNAIRE: 30 DAYS

Two rather painful, splitting headaches will strike some

time during the day. Each period of headache will last 2 hours.

Please proceed as before, Think about how much you mind

the 30 additional days of headaches. After you have decided, put

the card in its proper place in the deck.

[Wait until respondent is through]

We have a couple of more symptoms to consider. The next one

is drowsiness. Here is a card describing a day when you are

bothered by heavy drowsiness.

[Hand respondent Heavy Drowsiness card]

You will have extreme difficulty staying awake during 6

of the hours when you are normally awake. Sometimes your eyelids

will flutter. You will doze off for an instant now and then.

The drowsiness will interfere with your social activities and

other leisure. You will find the drowsiness dangerous if it

comes over you while you are driving or working with tools,

appliances or other machinery.

After thinking about the 30 additional days when you have

drowsiness, add the card to the deck to reflect where it comes in

your ranking.

[Wait for respondent to finish, and then proceed]

The last symptom is nausea. Here is a card about it.

[Hand respondent Nausea card]

Throughout the day, you will have a lingering urge to vomit,

but you will not be able to do so. Stomach distress will be

strong. There will be no actual pain.

As before, think about how you rank the 30 additional days

of nausea, and place it in the deck.

Thank you. I’m going to record your answers for use later.

Let’s keep the deck sitting there. We’ll use it in a minute.

[Interviewer record rankings on Tally Sheet.]

CV. CONTINGENT VALUATION

3-130
7-SYMPTOM HEALTH QUESTIONNAIRE: 30 DAYS

In this next set of questions, I’m going to ask you how much

it would be worth to you to avoid the symptoms we’ve been talking

about.

The answers in this part are for yourself alone and not for

any other members of your household.

Before we start, please look at this card showing how a

typical family spends its take-home income.

[Hand respondent Household Spending card]

When you pay to avoid symptoms, the money will have to come

out of one of the categories shown. We’ll leave the card here so

that you can think about where the money comes from that you

would spend to avoid the symptoms. Keep in mind, however, that

your situation is probably different from this one.

Let’s think about ways we normally deal with health

problems. One way is to go to the doctor, another way is to buy

medicine at the drugstore. Oftentimes we don’t do any thing at.

all- -we just suffer through the problem until it goes away. It

might be that the price of a bottle of medicine or a visit to the

doctor measures the value of a cure. But if we stop to think

about it, the cure might be worth much more to us than that--if

we really had to pay it. A cure might be valuable to us even

when we just suffer with the problem until it goes away. In such

cases we might ask ourselves “How much would I be willing to pay

to get rid of this problem right now, even if I don’t want to

take medicine or visist the doctor?”

With these thoughts in mind, please try to give the largest

dollar value a cure would be worth to you when answering the next

few questions.

Now look at the card at the top of the deck--[symptom]--

which is the symptom you mind least.

3-131
7-SYMPTOM HEALTH QUESTIONNAIRE: 30 DAYS

CV-1. If your health symptoms in the next

same as in the last 12 months, except that

faced with 30 additional days of [symptom],

$100 to you to completely get rid of these

[Circle one]

12 months were the

you would also be

would it be worth

days of symptoms?

Yes No

CV-2. [If answer to CV-1 is Yes, ask if getting rid of the day

would be be worth $200, $400 --doubling each time until a No

response is obtained. Then subtract half the difference between

the two previous answers. Continue adding or subtracting half

the difference between the last two answers until respondent no

longer wants to change.]

[If answer to CV-1 is No, ask $50, $25--decreasing by half

until a Yes response is obtained. Then add half the difference

between the two previous answers, continuing with the half

difference procedure until respondent no longer wants to change.]

[Record final bid at top of tally sheet.]

Next look at the card at the bottom of the deck, which is

the symptom you mind the most.

[Interviewer: For the following two questions, you will need a

calculated bid for CV-3. The calculated bid for CV-3 is the bid

to get rid of the least bothersome day given in the answer to CV2, multiplied by two.]

CV-3. If your health symptoms were the same in the next 12 months

as in the last 12 months, except that you would also be faced

with 30 days of the symptom you mind the most, would you be

willing to pay [calculated bid for CV-5] to completely get rid of

the symptoms on that day? [Circle one]

Yes No

CV-4. [If the answer to CV- is Yes, ask if respondent would be

willing to pay double the calculated bid for CV-3. Proceed by

further doubling until a No answer is obtained. Then subtract

half the difference between the first No amount and the last Yes

amount. Continue increasing or decreasing by half the difference

a until a final bid is obtained.]

3-132
7-SYMPTOM HEALTH QUESTIONNAIRE: 30 DAYS

[If the answer to CV-3 is No, ask if respondent would be

willing to pay half the calculated bid for CV-3. Proceed by

halving until a Yes answer is obtained. Then add half the difference between the first Yes amount and the last No amount.

Continue increasing or decreasing by half the difference until a

final bid is obtained]

[Record Final bid at bottom at tally sheet.]

I have here a tally sheet for you to keep track of your

answers. [Interviewer hand respondent Tally Sheet]

Here is a pencil. [Interviewer hand respondent pencil]

The first column of the Tally Sheet is called “Symptom Days

Ranked from Least to Most Bothersome”. In this column, I have

written the symptoms in the correct order from the deck of cards

you have arranged.

The second column of the Tally Sheet is your Bid to avoid

additional symptom days. The dollar amounts you have given are

for the first and last lines in this column.

At this point, think about how much you would be willing to

pay to avoid 30 additional days of the other five symptoms that

you placed between the least and most bothersome.

Take as much time as you need to decide on the amounts you

would be willing to pay to avoid each symptom day. As you decide

on the amounts, record them.

People often find that they want to change the bids

originally given for the least and most bothersome days. They

often take several tries at each entry in the column.

Feel free to change any of the amounts as much as you want.

In this part, people find themselves using the eraser a lot.

3-133
7-SYMPTOM HEALTH QUESTIONNAIRE: 30 DAYS

Tally Sheet

RANKING OF SYMPTOMS

FROM LEAST TO MOST

BOTHERSOME

1) -----------

2) -----------

3) -----------

4) -----------

5) -----------

6) -----------

7) -----------

BID FOR 30 DAYS OF

RELIEF IN THE NEXT

12 MONTHS

$ ----------- per year

$ ----------- per year

$ ----------- per year

$ ----------- per year

$ ----------- per year

$ ----------- per year

$ ----------- per year

3-134
7-SYMPTOM HEALTH QUESTIONNAIRE: 30 DAYS

[Interviewer wait for respondent to complete the column. Avoid

any appearance of impatience]

CV-5. So far we have been considering the symptoms individually. Sometimes, however, they occur together.

Suppose you faced 30 days in the coming year in which you

had the three following symptoms on each day. [Interviewer hand

respondent Cough, Sinus, Throat card.] You would have coughing,

stuffed up sinuses and throat congestion on each of the 30 days.

Look at your bids for these three individual symptoms on the

Tally Sheet. Let’s add them up.

[Interviewer compare sum with respondent. Record sum]

Sum of individual bids:

---------------- dollars

Think about whether you would be willing to pay more or less

than this sum to get rid of 30 days on which all 3 of the

symptoms occur together. When you are ready, please tell me how

much are you willing to pay to get rid of the 30 days of combined

symptoms.

Bid to get rid of 30 days of combined cough, sinus and throat

symptoms:

------------------ dollars

CV-6 Now suppose that you faced 30 days in the coming year of

these three symptoms. [Interviewer hand respondent Headache,

Nausea, Drowsiness card.] You would have headache, nausea, and

drowsiness.

Once again, let’s add up your bids for the individual

symptoms.

[Interviewer compare sum with respondent. Record sum.]

Sum of Individual bids:

----------- dollars

3-135
7-SYMPTOM HEALTH QUESTIONNAIRE: 30 DAYS

How much would you be willing to pay to get rid of 30 days

on which all 3 of the symptoms occur together?

Bid to get rid of 30 days of headache,

nausea and drowsiness:

--------dollars

CV-7. Your answers so far have been about how much you would

pay for relief of yourself alone.

Look again at the card for combined coughing, sinus and

congestion symptoms. How much would your household be willing to

pay to relieve the 30 days of combined symptoms for yourself and

every other member of your household.

Bid for relieving household of

30 days of combined symptoms

------------------- dollars

CV-8. I have one final question on amounts you are willing to

pay. Suppose that everybody in the United States faced 30 additional days of combined coughing, sinus and congestion symptoms.

How much extra would your household be willing to pay for

everybody’s symptoms to be eliminated on these days? This is in

addition to the amount you just stated for your household alone.

Addition to household payment to get rid of day of

combined symptoms for everybody in the United States:

-------------------- dollars

3-136
A.3 ANGINA HEALTH QUESTIONNAIRE: 10 DAY

Nov. 18,1984 Version

Hello. I’m ---------------- from the University of Illinois

School of Public Health. We are visiting with people in your

area as part of a research project about health and risks to

health. We have scientifically selected a sample of households to

represent your area and your household has been chosen as part of

the sample.

Are you the [male/female] head of the household?

[If not, ask to speak to the head and start over.]

Your opinions are very important and we hope you will help

us. Please be assured that this is purely a research project and

we do not represent any business or product. No sales call will

result by your participation in this study. The information you

provide us will remain confidential.

The questionnaire will take about 30 minutes.

3-137
ANGINA HEALTH QUESTIONNAIRE: 10 DAY

A. HEALTH EVALUATION

[Interviewer circle numbers.]

Self-assessment of own health status.

A-1. Would you describe your overall health as being

1 Excellent 2 Good 3 Fair 4 Poor

[Interviewer hand out Contol card.]

A-2. Please look at this card and tell me which statement best

describes the control you have over your health.

1. There is little I can do because it is beyond my

control

2. I can do some things, but they have little effect.

3. My actions have a moderate effect.

4. My actions have a great effect.

A-3. How often were you bothered by any illness, bodily

disorders, aches or pains, during the last month?

(Circle one)

Every day 1

Almost every day 2

About half of the time 3

Now and then, but less than

half of the time 4

Rarely 5

None of the time 6

3-138
ANGINA HEALTH QUESTIONNAIRE: 10 DAY

HEALTH STATUS

H-1. Have you been diagnosed by your doctor as having a heart

condition of any kind?

No ----- [Skip to H17]

Yes -----

H-2. Do you know the name of your heart condition?

NAME(S) -------------

-------------

DON’T KNOW ------

H-3. List the symptoms that you experience because of your heart

condition. [Enter the sumptoms in the first column]

NUMBER OF DAYS

SYMPTOM RANK PER YEAR

-------------------- -------- --------

------------------- -------- ----------

----------------- -------- ----------

-------------------- --------- ---------

H-4. Which of these symptoms bother you the most. [Number the

symptoms in the Rank column. 1=worst]

H-5. On about how many days did you experience these symptoms in

the last 12 months? [Put number in Number Per Year column.]

H-6. During the last year did this health problem cause you to

miss one or more days of usual activity, such as work, school, or

work at home?

No ------- [Skip to H-9] Yes --------

3-139
ANGINA HEALTH QUESTIONNAIRE: 10 DAY

H-7. How many days did you lose of:

Work School Housework —------- ------- -------

Other (Specify) None [Skip to H-9.] -------------- ---------------

H-8. About how much earnings were lost because of work days

missed?

$ -------------

H-9. During the last year did you purchase any medicine for your

heart condition?

No--------- [skip to H-13. ] Yes ---------

H-10. About how much did you spend for medicine for this during

the last year?

$ ----------

H-11. Was any of this cost paid by insurance or any other health

plan?

No --------- [Skip to H-13.] Yes

H-12 How much was paid?

H-13. During the last year did

other source of professional

problem?

No ------ [Skip to H-17]

Visit mainly for this

$ ---------

you visit a doctor, clinic, hospital, or

medical care for this health

Part of visit for other purpose --------—

H-14. About how many visits were there? visits ---------

H-15. About how much did these visits cost during the last year?

$------

3-140
ANGINA HEALTH QUESTIONNAIRE: 10 DAY

H-16. About how much of this cost was paid by insurance or any

other plan?

$ ______

[If Angina not mentioned in H-3]

H-17. Are you familiar with the condition called "angina

pectoris”?

No -------- [Skip to Defensive Measures] Yes --------

H-18. Have you ever known anyone with this condition?

No ________ [Skip to Defensive Measures]

Yes --------

H-19. State their relationship to you, such as father, aunt or

friend.

------------------

------------------

------------------

3-141
ANGINA HEALTH QUESTIONNAIRE: 10 DAY

M. DEFENSIVE MEASURES

Now I would like to ask you some questions about your day-today living that are related to the symptoms we have been

discussing,

M-1 Do you have any of the following in your home or car,

purchased for health reasons?

Air Conditioner YES ------ NO------

Air Purifier YES ------ NO------

Humidifier YES ------ NO ------

Other (____________)

M-2 Do you smoke?

YES ------ NO---—---

Yes ------ [Skip to M-3]

No------

(a) Did you ever smoke? Yes ------ No ------ [Skip to M-2(c)]

(b) Did you quit for

health reasons? Yes ------ No ------

(c) Would you smoke if

smoking were not

damaging to your health? Yes ------ No ------

M-3 Have you ever changed to location of your residence for

health reasons?

Yes -------

No ----—--- [Skip to Section CV]

M-4 Where did you move from? ----------------

M-5 To? --------------------

M-6 What health problem prompted the move? ---------------------

3-142
ANGINA HEALTH QUESTIONNAIRE: 10 DAY

CV. CONTINGENT VALUATION--ANGINA

In this next set of questions, I’m going to ask you how much

it would be worth to you to reduce or avoid angina pectoris--a

painful condition that can occur with different frequencies and

different levels of severity. The description I will read to you

almost certainly won’t describe your own circumstances. I would

like you to put yourself in the position of having these

symptoms, however, and tell me what it would be worth to you to

remove them.

Angina is a painful condition of the chest that afflicts

about 500,000 people in the United States. It can occur in

people of any age, although most sufferers are 50 years of age or

older. Symptoms can be of varying degrees of severity. Even the

severest instances however, hardly ever result in death.

Mild Angina: One Day

First let’s consider mild angina. Here is a card describing

it. [Hand respondent card on Mild Angina.]

An attack lasts anywhere from 10 minutes to 3 hours. You

experience stiffness in the shoulders, backache and numbness in

the hands and feet. Often, these symptoms are accompanied by

difficulty breathing with any exertion and dull persistent chest

pain like a band is tightening around your chest.

Suppose that in an average month, you can expect 1 of these

symptom days.

3-143
ANGINA HEALTH QUESTIONNAIRE: 10 DAY

Frequency

Angina Tally Sheet

MILD ANGINA:

You have one day of mild angina each month

Value of eliminating one day a month

You have 10 days of mild angina each

Value of eliminating one day a month

Value of eliminating 10 days a month

Value of eliminating 5 days a month

month

1.

2.

3.

4.

SEVERE ANGINA:

You have one day of severe angina each month

Value of eliminating one day a month 5.

You have 10 days of severe angina each month

Value of eliminating one day a month 6.

Value of eliminating 10 days a month 7.

Value of eliminating 5 days a month 8.

Value

$ -------- /month

$ -------- /month

$ -------- /month

$ ---------/month

$ -------- /month

$ -------- /month

$ -------- /month

$ -------- /month

3-144
ANGINA HEALTH QUESTIONNAIRE: 10 DAY

CV-1 Would it be worth $53 a month to completely avoid the day

of symptoms?

Yes --------

No --------

[If Yes, ask $100, $200, etc. until Reject. Then work back to

highest previous Accept (but no further).

If No, ask $20, $10, etc. until Accept. Then work back if

necessary. Record final answer on Tally Sheet, Value 1.]

Mild Angina:10 days

Next suppose you have the angina condition 10 days a month on

the average. Would it be worth [Double Value 1] per month to

completely avoid one of those days each month?

Yes ---------- No --------

[Iterate as in Value 1 instructions. Record on Tally Sheet,

Value 2.]

Again let’s suppose you have the angina condition 10 days a

month, just as described on the card you have. This time I’d

like you

completely

[Record on

Suppose

10 symptom

to tell me how much you’d be willing to pay to

eliminate all ten symptom days each month.

Tally Sheet, Value 3.]

you had the opportunity to eliminate half of these

days. How much would it be worth to you to be free of

the five symptom days each month?

[Record on Tally Sheet, Value 4.]

Severe Angina:One Day

Now let’s look at a more severe angina problem. Here is a

card about it. [Hand respondent card on Severe Angina.] Severe

angina has all the symptoms we have just discussed, but some of

them are considerably worse. There is a feeling of suffocation.

Chest pain is now almost unbearable. The experience can be

terrifying because one feels as though one were dying. After

having some experience with these attacks, however, and with

assurances from the doctor, one learns that they do not pose a

risk of death. The symptoms last 10 minutes to 3 hours and occur

one day a month.

3-145
ANGINA HEALTH QUESTIONNAIRE: 10 DAY

Suppose you had the severe angina condition one day a month.

Would it be worth [Double Value 1] a month to completely avoid

the day of symptoms?

Yes --------- No ---------

[Iterate as in Value 1 instructions. Record on Tally Sheet,

Value 5.]

Next suppose you have the severe angina condition 10 days a

month. Would it be worth [Double Value 5] a month to completely

avoid one of those days each month?

Yes ----------- No ---------

[Iterate as in Value 1 instructions. Record on Tally Sheet,

Value 6.]

Again let’s suppose you have the severe angina condition 10

days a month, as described on the card. This time, tell me how

much it would be worth to you to completely eliminate all ten

days of severe angina each month.

[Record on Tally Sheet, Value 7.]

One last question. Once again you experience the severe

angina symptoms ten days a month. Suppose you could eliminate

half the symptom days each month. How much would you be willing

to pay to be free of 5 of the 10 symptom days each month?

[Record on Tally Sheet, Value 8.]

Now I’d like to show you a summary of your answers, [Hand

Tally Sheet to respondent.]

[If any of the Severe Angina values are smaller than the

corresponding Mild Angina values, point it out on the Tally Sheet

and say]

Value --—---- for Severe Angina is smaller than Value

for Mild Angina,

--------

even though the situations are the same in other

respects. Would you like to make a change that takes this into

account?

[If there are no inconsistencies, say]

Tell me if they look o.k. to you, or if any answers need to be

changed.

[Record any changes. Take back Tally Sheet and Symptom cards.]

3-146
ANGINA HEALTH QUESTIONNAIRE: 10 DAY

RE. REASONS

The value questions are now complete, but before we move on,

would you tell me what the major reasons were for your answers,

Here is a card that list some reasons.

[Interviewer hand respondent Reasons card]

[Interviewer: The following list will be needed to record the

ranking of reasons in question RE-1]

Comfort

Loss of work at home

Loss of work away from home

Loss of recreation

Reduce medical expenses

Other (Specify)

RE-1. Please look at the card and tell me the most important

reason for the amounts you were willing to pay.

[Interviewer enter “1” beside the reason given as answer]

Please continue with the next most important reason, the one after

that, and so forth for all the reasons that influenced your bid.

[Interviewer enter “2” beside the next most important reason, “3”

beside the one after that, and so forth for all reasons mentioned

by respondent].

3-147
ANGINA HEALTH QUESTIONNAIRE: 10 DAY

SOCIOECONOMIC QUESTIONS

(Same as in 7-Symptom Health Questionnaire: One Day)

3-148
A.4 ANGINA HEALTH QUESTIONNAIRE: 20 DAY

(Same in all respects as Angina Health Questionnaire: 10 Day,

except for CV section reproduced here).

CV. CONTINGENT VALUATION--ANGINA

In this next set of questions, I’m going to ask you how much

it would be worth to you in order to reduce or avoid angina

pectoris--a painful condition that can occur with different

frequencies and different levels of severity. The description I

will read to you almost certainly won’t describe your own

circumstances. I would like you to put yourself in the position

of having these symptoms, however, and tell me what it would be

worth to you to remove them.

Angina is a painful condition of the chest that afflicts

about 500,000 people in the United States. It can occur in

people of any age, although most sufferers are 50 years of age or

older. Symptoms can be of varying degrees of severity. Even the

severest instances however, hardly ever result in death.

Mild Angina:One Day

First let’s consider mild angina. Here is a card describing

it. [Hand respondent card on Mild Angina.]

An attack lasts anywhere from 10 minutes to 3 hours. You

experience stiffness in the shoulders, backache and numbness in

the hands and feet. Often, these symptoms are accompanied by

difficulty breathing with any exertion and dull persistent chest

pain like a band is tightening around your chest.

Suppose that in an average month, you can expect 1 of these

symptom days.

3-149
ANGINA HEALTH QUESTIONNAIRE: 20 DAY

Angina Tally Sheet

Frequency

MILD ANGINA:

You have one day of mild angina each month

Value of eliminating one day a month

You have 20 days of mild angina each month

Value of eliminating one day a month

Value of eliminating 20 days a month

 Value of eliminating 10 days a month

SEVERE ANGINA:

You have one day of severe angina each month

1.

2.

3.

4.

Value of eliminating one day a month 5.

You have 20 days of severe angina each month

Value of eliminating one day a month 6.

Value of eliminating 20 days a month 7.

Value of eliminating 10 days a month 8.

Value

$ -------- /month

$ -------- /month

$-------- /month

$-—------/month

$ -------- /month

$ month

$ -—----—- /month

$------— /month

3-150
ANGINA HEALTH QUESTIONNAIRE: 20 DAY

CV-1 Would it be worth $53 a month to completely avoid the day

of symptoms?

Yes --------

No --------

[If Yes, ask $100, $200, etc. until Reject. Then work back to

highest previous Accept (but no further).

If No, ask $20, $10, etc. until Accept. Then work back if

necessary. Record final answer on tally sheet, Value 1.]

Mild Angina:20 days

Next suppose you have the angina condition 20 days a month on

the average. Would it be worth [Double Value 1] per month to

completely avoid one of those days each month?

Yes----------- No------------

[Iterate as in Value 1 instructions. Record on Tally Sheet,

Value 2.]

Again let’s suppose you have the angina condition 20 days a

month, just as described on the card you have. This time I’d

like you to tell me how much you’d be willing to pay to

completely eliminate all 20 symptom days each month.

[Record on Tally Sheet, Value 3.]

Suppose you had the opportunity to eliminate half of these 20

symptom days. How much would it be worth to you to be free of

the ten symptom days each month?

[Record on Tally Sheet, Value 4.]

Severe Angina-One Day

Now let’s look at a more severe angina problem. Here is a

card about it. [Hand respondent card on Severe Angina.] Severe

angina has all the symptoms we have just discussed, but some of

them are considerably worse. There is a feeling of suffocation.

Chest pain is now almost unbearable. The experience can be

terrifying because one feels as though one were dying. After

having some experience with these attacks, however, and with

assurances from the doctor, one learns that they do not pose a

risk of death. The symptoms last 10 minutes to 3 hours and occur

one day a month.

3-151
ANGINA HEALTH QUESTIONNAIRE: 20 DAY

Suppose you had the severe angina condition one day a month.

Would it be worth [Double Value 1] a month to completely avoid

the day of symptoms?

Yes ---------- No----------

[Iterate as in Value 1 instructions. Record on Tally Sheet,

Value 5.]

Next suppose you have the severe angina condition 20 days a

month. Would it be worth [Double Value 5] a month to completely

avoid one of those days each month?

Yes ---------- No------------

[Iterate as in Value 1 instructions. Record on Tally Sheet,

Value 6.]

Again let’s suppose you have the severe angina condition 20

days a month, as

much it would be

of severe angina

[Record on Tally

described on the card. This time, tell me how

worth to you to completely eliminate all 20 days

each month.

Sheet, Value 7.]

One last question. Once again you experience the severe

angina symptoms 20 days a month. Suppose you could eliminate

half the symptom days each month. How much would you be willing

to pay to be free of 10 of the 20 symptom days each month?

[Record on Tally Sheet, Value 8.]

Now I’d like to show you a summary of your answers. [Hand

Tally Sheet to respondent.]

[If any of the Severe Angina values are smaller than the

corresponding Mild Angina values, point it out on the Tally Sheet

and say]

Value ------- for Severe Angina is smaller than Value

for Mild Angina,

--—----

even though the situations are the same in other

respects. Would you like to make a change that takes this into

account?

[If there are no inconsistencies, say]

Tell me if they look o.k. to you, or if any answers need to be

changed.

[Record any changes. Take back Tally Sheet and Symptom cards.]

3-152
,

Final Report

--------- VALUATION .OF -- REDUCTIONS IN HUMAN HEALTH -------w-e WV ----- ------

-------- a-- ----- SYMPTOMS AND RISKS

Voiume 4

CONCEPTS AND APPROACHES TO THE VALUATION

OF SERIOUS ILLNESS

George Tolley

Lyndon Babcock

and

Mark Berger

Anthony Bilotti

Glenn Blomquist

Michael Brien

Robert Fabian

Gideon Fishelson

Charles Kahn

Austin Kelly

Don Kenkel

Ronald Krumm

Tracy Miller

Robert Ohsfeldt

Sherwin Rosen

William Webb

Wallace Wilson

Martin Zelder

The University of Chicago

Cooperative agreement between the University of Chicago and

the U.S. Environmental Protection Agency with participation by

University of Illinois at Chicago, University of Kentucky and

University of Wyoming.

USEPA Grant #CR-811053-01-O

PROJECT OFFICER: Dr. Alan Carlin

Office of Policy Analysis

Office of Policy, Planning and Evaluation

U.S. Environmental Protection Agency

Washington, D.C. 20460

January 1986
DISCLAIMER

Although prepared with EPA funding, this

report has neither been reviewed nor

approved by the U.S. Environmental

Protection Agency for publication as an

EPA report. The contents do not

necessarily reflect the views or policies

of the U.S. Environmental Protection

Agency, nor does mention of trade names or

commercial products constitute endorsement

or recommendation for use.
------em- VALUATION OF REDUCTIONS IN HUMAN HEALTH SYMPTOMS AND RISKS -- ---------a -- ----- ------ -------- --- a----

This is Volume 4 of a four volume report. The project

undertakes an assessment and reconciliation of attempts to value

reductions in human health risks,' and it develops new methods and

estimates for these values. Volume 1, is the executive summmary.

Volume 2 contains a comparative assessment of work on valuing

health risks. Based on the assessment, a set of interim

morbidity and mortality values applicable to effects of criteria

air pollutants is developed. Volume 3 reports on a study

developing and applying contingent valuation techniques to the

types of light symptoms often attributed to air pollution.

Volume 4 reports on the design of approaches for valuing serious

or life threatening illnesses.

Abstract of Volume 4 -------- -- ------ -

CONCEPTS AND APPROACHES TO THE VALUATION OF SERIOUS ILLNESS

Volume 4 extends the analysis of health valuation to life

threatening illness.

Section 4.2 considers alterna‘tive definitions of health

and, for the study of serious illnesses resulting from environmental causes, concludes that a definition in terms of absence of

symptoms should be used. The potential contributions of various

pollutants to the risks of serious illnesses are reviewed, in

order to choose which diseases should be studied and what ranges

of risks are relevant. Specifi'c measures of health status are

evaluated including symptom description, self-assessment, health

risk appraisal, health indexes and multi-attribute utility

functions. The first three of these are recommended for

contingent valuation studies.

Section 4.3 develops a life cycle explanatory framework

for valuing reductions in life-threatening illness that guides

the remainder of the study. Within this framework, longevity

(i.e. mortality) and quality of life (as affected by morbidity)

are considered together in a unified context. Young people, presented with improved prospects for greater health and longevity

only after a long period of time, will heavily discount the

benefits and will pay little, even though aware that their preferences many years hence will be different. Policies that

promise a near-term benefit will be valued much more highly by

people of any age. If people can easily substitute near term

consumption for deferred consumption, they will place less value

on additions to life expectancy. The capacity for consumption

changes over the life cycle. An added year of life accompanied

by high income or accumulated wealth, together with a high quality of leisure time, will be valued relatively highly. Latency is

modelled within the life cycle framework.

Section 4.4 develops a model of choice under uncertain
preferences, bringing utility theory to bear on the problem of

valuing small changes in events that are thought of only infrequently and may involve low probabilities of occurrence. The

model is applicable to eontingent valuation approaches to serious

illness. The model assumes environmental health risks are unfamiliar to most people, and that because people seldom have

occasion to think carefully about them they are uncertain about

their preferences concerning them. The model leads to twelve

theorems for stimulating people to obtain improved knowledge

about their preferences and to state valid, consistent risk

reduction values.

Section 4.5 applies the preceding sections to contingent

valuation of life threatening illness. A structure for an intensive interviewing process is developed, based on techniques of

in-depth interviewing.

The proposed interview structure contains four modules. The

first module concerns the repsondent's health experiences. The

defensive measures module is the second module:The third module

pertains to risk perception and risk behavior. This module

teaches respondents basic notions of probability and conveys

information about probabilities involved in health. Information

is obtained about repsondent perceptions and attitudes towards

risks.

Contingent valuation questions form the fourth module. The

module begins with simple questions involving certainty scenarios

and mortality only, after which serious illnesses are introduced.

Then life path scenarios are introduced that combine morbidity

and mortality in a life cycle setting. Respondents are asked to

choose among and value the scenarios, first in a certainty and

then an uncertainty setting.
----- Table of Contents em m-------

Volume 4: Concepts and Approaches to the Valuation of

Serious Illness

4.1 Overview

4.2 Defining

4.2.1

4.2.2

4.2.3

4.2.4 Health Measurement 4-18

4.2.5

4.2.6

and Measuring Health Over Life

Overview

Alternative Health Definitions

Role of Causal Factors

Background

Role of Behavior or Lifestyle

Role of Environment

Measurement in Terms of 111 Health

Health Indices

Multi-attribute Utility Functions

Health Risk Appraisal

Implications for Valuing Serious Illness

References

4.3 The Quantity and Quality of Life: Conceptual Framework

4.3.1 Introduction

4.3.2 The Value of Longevity: Deterministic Model

4.3.3 Extensions of Deterministic Model

Nonconstant Consumption

Age-dependent Preferences and the

Quality of Life

B'equests

Labor market Activities

Retirement

4-1

4-3

4-3

4-5

4-7

4-23

4-25

4-30

4-30

4-31

4-37

4.3.4 The Value of Morbidity 4-43
4.3.5

4.3.6

4.3.7

4.4 Modelling

4.4.1

4.4.2

4.4.3

4.4.4

4.4.5

4.4.6

4.4.7

4.4.8

4.4.9

4.4.10

4.4.11

4.4.12

4.4.13

4.4.14

4.4.15

Value of Life Expectancy: Stochastic Model 4-45

Preliminaries

Optimal Choices

Valuation Formulas

Valuations of Workers

Interpretation and Applications 4-54

Major Results from The Life Cycle Model

Life Experiences and Willingness to Pay to Avoid

Serious Illness

References

of Choices With Uncertain Preferences

Background

Approach Taken in This Section

Expected Utility Theory and Its Critics

Conceptual Problems With Welfare Analysis

When Tastes Are Uncertain

Psychological Studies

Components of an Economic Model

Formal Model Statement

Answering a Series of Questions

Comparison Versus Scaling Questions

More General Distribution of .Priors

The Effect of Limited Memory

Biases

Example of Biased Priors Generating Preference

Reversals

Summary and Implications

References

4-58

4-60

4-60

4-60

4-62

4-68

4-71

4-72

4-73

4-77

4-79

4-81

4-83

4-84

4-85

4.87

4-91
4.5 Design of Contingent Valuation Approaches to Ser.ious

Illness

4.5.1 Special Problems of Contingent Valuation

Encountered With Serious Illness

4.5.2 Rationale and Overview of Four Module Approach

Health Experience

Health Costs and Defensive Measures

Risk Perception and Risk Behavior

Conginent Valuation Questions

4.5.3 First Module: Health Experience

4.5.4 Second Module: Health Costs and Defensive

Measures

4.5.5 Third Module: Risk Perception and Risk

Behavior

4.5.6

4.5.7

Contingent Valuation Questions

Mortality

Morbidity

Life Path Approaches Combining Morbidity and

Mortality

Implications and Further Work

4.6 Summary and Conclusions on Serious Illness

Appendix. Manipulation of Life Tables: Cancer Illustration

4-92

4-93

4-96

4-98

4-100

4-102

4-105

4-117

4-120

4-123
List of Tables ---- -- ------

Table 4-l Death Rates: Leading Causes of Death,

United States, 1979

Table 4-2 Life Path Scenarios

Table A-l Number of Persons Dying (Out of 100,000 At

Birth) From All Causes U.S. Females, 1964

Table A-2

Table A-3

Probability of Dying From Selected Causes

Probability of Survival From One Age (x)

To Another Age (y)

Table A-4 Probability of Death With Neoplasms

Eliminated

Table A-5 Probability of Survival From One Age (x)

To Another Age (y) With Neoplasms

Eliminated

Table A-6 Number of Person Dying (Out of 100,000

At Birth) From All Causes With Neoplasms

Eliminated

Table A-7 Probabilities of Death With Neoplasms

Reduced by 50%

Table A-8 Probability of Survival From One Age (x)

To Another Age (y) With Neoplasms Reduced

by 50%

4-10

4-114

4-125

4-126

4- 128

4-129

4-130

4-131

4-132

4-133

Table A-9 Number of Persons Dying (Out of 100,000 At

Birth) From All Causes With Neoplasms Reduced

By 50% G-133

Table A-10 Probabilities of Death With Neoplasms Increased

by 100% 4-13.L

Table A-11 Probability of Survival From One Age (x) To

Another Age (y) With Neoplasms Increased

By 100%

Table A-12 Number of Persons Dying (Out of 100,000 At

Birth) From All Causes With Neoplasms

Increased.by 100%
---- -- -- List of Figures ----

Figure 4-l Health Definition: Steps Toward Quantification 4-l

Figure 4-2 Effects of Intervention 4-9

Figure 4-3 Pollution-Health Relationship 4-13

Figure 4-4 Independence Axiom 4-63

Figure 4-5 Allais Paradox (A) 4-64

Figure 4-6 Allais Paradox (B) 4-65

Figure 4-7 Probability of Survival With and Without

Threat of Cancer 4-107

Figure 4-S Remaining Years of Life at Various Ages 4-110

Figure 4-9 Pie Chart for Mortality Lottery Wheel 4-111
4.1. OVERVIEW

Volume 4 extends the analysis of health valuation to the

domain of life threatening illness. It provides an original

framework that can be used to obtain values of increased

longevity and reduced risks of death from serious illness.

Section 4.2 provides a discussion of approaches to the

measurement of health status. This section is a pre-requisite to

determining how to measure health attributes whose value is to be

estimated. Simple self-rating of health, definition of health as

a good or a bad, broadness of definition extending to mental well

being, disease specific definitions and symptom specific definitions are among the appraoches to health measurement that are

considered. A central purpose is to consider which measures

should be used in estimating values connected with life

threatening illness, giving particular attention to health risks

due to environmental pollutants. Extensions of previous approaches to health measurement are suggested.

Section 4.3 develops an explanatory framework to guide the

estimation of values that result from reductions in life-threatening illness. This framework brings out how people's decisions

regarding health and longevity depend on their life situations

and streams of experiences that have developed over long periods

of time. An important implication is that the quality of life

and longevity are part of a single decision making process, and

that they must be considered together in a unified context taking

account of a peron's life cycle situation. The life cycle

framework is at the heart of the remainder of the study. One of

the challenges brought out by the framework is how to measure

the value people place-on the reduction of threats to health that

have their effects only after a latency period that may be many

years in duration. Analysis of this problem is one of the contributions of section 4.3.

Section 4.4 provides the theoretical underpinnings to

another aspect of the problem of valuing life threatening illness. It brings economic theory to bear on the problem of how

people think about and value small changes in small probabilities

of large damages to health or risk to life. A clear understanding of this process is essential to determining the benefits of

environmental policies if a contingent valuation approach is to

be used to estimate values. The problem has been widely recognized, but heretofore procedures to deal with it have been

largely ad hoc. The theoretical perspective of the present study

is that environmental health risks are unfamiliar to most people,

and that because people seldom have occasion to think carefully

about them they are uncertain about their preferences concerning

them. Section 4.4 contains a series of theorems that have implications about efficient ways of stimulating people to obtain

improved knowledge about their own risk preferences and to state

valid, consistent risk reduction values.

4-l
Section 4.5 brings together and applies all of section 4

research on life threatening illness. A structure for an indepth intensive interviewing process is developed, embodying

refinements based on focus group experiments. The structure is

composed of four modules.

The first module concerns the repsondents' health

experiences. It establishes the health endowmment and prepares

respondents to give detailed thought to their health preferences

and values.

The defensive measures module is the second module of the indepth interview framework. Defensive measures, or averting

behavior, are an important part of many people's efforts to

increase the probability of good health over the life cycle.

They are evidence of a willingness to pay for improved life

prospects. Reductions in defensive measures are a part of the

benefits of reducing health risks. In some cases .averting behavior entails increased expenditures (for exam.ple air conditio,ning), while in other cases reduced expenditures occur (for

example reduced smoking).

The third module pertains to risk perception and risk

behavior. The first part of this module addresses the problem of

teaching people to grasp the concept of probability as it is

manifested in environmental health problems. In the second part

of this module, respondents are asked questions about their

behavior toward risk and how they perceive the riskiness of a

variety of life situations.

Contingent valuation questions form the fourth module.

The contingent valuation questions increase in complexity,

beginning with simple questions involving certainty scenarios and

mortality only. Next, serious illnesses are introduced, and

respondents are asked their willingness to pay to eliminate the

risks of getting diseases. These questions are followed by life

path scenarios that combine morbidity and mortality in a life

cycle setting. Alternative life path possibilities are

presented, and respondents are asked to choose among and value

them, first in a certainty and then an uncertainty setting.

It is believed that the approach developed in section 4,

and the extensive preparation for obtaining expressions of willingness to pay described in the modules, constitute an advance

in survey research on the values of health improvements, and that

intensive empirical applications are needed.

4-2
4.2. DEFINING AND MEASURING HEALTH OVER LIFE

4.2.1 Overview ------em

Health measurement is an essential part of any analysis of

the values that people derive from policies affecting health.

Several different methods of health measurement have been employed in the literature. Self:assessment is the most widely

used measure of health status. People are asked to rate their

own health as excellent, good, fair or poor. This approach has

been used in the Center for Health Administration Studies

national surveys and in many smaller household surveys.

Other frequently used approaches include reports of restricted activity days, bed disability days, number and severity

of symptoms experienced, number of chronic conditions, and the

amount of pain experienced by the respondent during the past

year. A variety of attitude questions have also been used, such

as perceived effectiveness of health care [Fuchs, 1982, pp.144-

1451. Studies of the demand for health care have utilized these

measures of health status. These studies have included nonmarket health related activities as well as expenditures on

medical care consumption. They have focused on such topics as

price and income elasticities of demand and the effects of

insurance on medical care consumption. Health status is often an

important variable in explaining the demand for health care.

Recent work has emphasized that health is a multidimensional condition whose complexity should be represented in

health studies in order to avoid bias in the measurment of price

and income elasticities and other important variables. The

multi-attribute utility ,function is an example of the multidimensional approach. A study of Torrence et al. [i9a2]

represents health according to four dimensions: morbidity and

physical activity; self care and role activity; emotional wellbeing and social activity; and health problems [Chestnut and

Violette, 19841.

In studying values associated with life threatening illness

in this study, it is necessary to define and measure health,

choosing among the previous approaches and building on them where

necessary. Figure 4-l depicts the progression from health

definition to use of morbidity and mortality data and knowledge

about influences on health, to measurements for health risk

valuations. Drawing on this schema, the present section provides

a critique of previous approaches and suggests extensions, giving

attention to conceptual adequacy and practical considerations in

valuing serious illness.

Section 4.2.2 considers alternative health definitions.

Attention is given first to definitions that consider the dimen4-3
FIGURE 4-1. HEALTH DEFINITION: STEPS TOWARD QUANTIFICATION

General definitions of health

I

Variables invoived in definition of health

I

Health measuremsnt [indexes and indicators)

I

Morbidity and

mortality data

1 Quantitative health path(s) 1

>JJj Behavioral and environmental

I Use for ‘health - risk valuations I

4-4
sions of health in terms of various attributes which may be good

and desired or alternatively may be bad and undesired.

Definitions of varying broadness are examined. Attention is

given second to definitions of health that focus in detail on

symptoms or departures from good health, rather than desired

attributes.

Section 4.2.3 considers the relevance to the measurment

problem of causal factors affecting health. Attention to heredity* lifestyle and environment as causes of disease helps to

arrive at judgments as to which health attributes should be

emphasized. The view taken here is that definition and measurement should depend on the purpose at hand. In this study, the

major purpose is to consider serious illnesses associated with

environmental causes.

Section 4.2.4 turns to health measurement per se. Selfrating of health, the health risk appraisal approach and various

approaches to measuring specific symptoms are considerd in

detail.

Section 4.2.5 considers the implications of the preceding

sections for empirical work on values associated with serious

illness. A critique of approaches to health measurement from the

point of view of their adequacy for the valuation of serious

illness is given. Criteria include familiarity of respondents

with symptoms, ability to encompass risk, adequacy in terms of

the effects of serious illness on life cycle experiences, brevity

and simplicity. Refinements and extensions to previous approaches to health measurement are suggested.

4-2.2. ----------- Alternative Health Definitions ------ -----------

Health is a key determinant of the quality of life. Central

to the valuation of health is an understanding of the nature of

health and the forces that influence it. Essential to this effort

is the definition of human health such that deviations from the

conditions it describes can be quantitatively described.

While most people have an instinctive comprehension of what

constitutes "health," few explicit working definitions are in

common use. A multitude of biological, behavioral, cultural and

social factors combine to shape human health--factors which act

in both favorable and unfavorable ways to determine the level of

well-being of a person at any point in time. "Death" is easily

and explicitly defined as the end or extinction of'life. "Morbid" indicates diseased, sick, or unhealthy. But the definition

of health itself is much more elusive, particularly when quantification is desired. Webster defines health as "physical and

mental well-being," "soundness," and as "vitality," "prosperity,"

and "flourishing condition." Health is thought of also as simply

the absence of illness or morbidity, i.e., a biological state

dependent upon biological factors. AS Banta (1981) points out,

4-5
other more recent definitions of health also stress life functioning, mental state and self fulfillment. Hoyman (1965) explains that "health is a process of continous change or adaptationthroughout the human life cycle. In fact there is no single

definition of health, although many definitions have been developed and are currently in use."

Carroll, Miller and Nash (1976) push the definition beyond

absence of disease or discomfort to the ability "...to function

effectively, happily, and as long as possible in a particular

environment." A statement issued by the World Health

Organization describes health as a "state of complete physical,

mental and social well-being, and not merely an absence of

disease" though this may be a statement of goals rather than a

definition (Hanlon and Pickett, 1984). Great Britain's Royal

Commission on the National Health Service aptly summed up the

debate by declaring that "health itself is not a simple concept."

Clearly,healthis muchmore thanmere absence of disease, and it

has extremely great value.

Another related concept which is undergoing a change in

meaning is that of "medical care," which traditionally has meant

the provision of medical services by, or under the direction of,

physicians. In recent years, the emphasis of such care has

broadened to include preventive, as well as strictly curative,

measures to preventive actions -- albeit still provided by the

physician in a clinical setting.

Broader still is the term "health care," no longer the

exclusive, province of the clinical physician. The term "health

care" has come to replace "medical care" in many instances.

Other new terms such as "health promotion," "health maintenance,"

and "disease prevention" have come into use (often

interchangeably) to characterize the new preventive focus of

health care which includes measures to be undertaken by

individuals themselves. The Surgeon General's Report (1979)

describes disease prevention as the protection of people from the

harmful effects of health threats (diseases, environmental

hazards). Health promotion measures are aimed, at well, as well

as ill, people (promotion of activities to improve lifestyles).

Perhaps the most far-reaching of the new health concepts are

"wellness" and "high-level wellness" (Ardell, 1977; Travis,

1977), which can be defined as "active processes through which

the individual becomes aware of and makes choices toward a more

successsful existence" (Hettler, 1981). Indeed, individuals are

becoming increasingly aware of the merits of promoting their own

health; sizable investments in time and other resources are being

made.

Given the array of similar terms and definitions introduced

above, an attempt to visualize these conceptual relationships

suggests a health continuum described by Brubaker (1983). From

this point of view, illness and death lie atone end, wellness at

the other, while an individual's state of health is characterized

4-6
by any degree of illness or wellness. Hettler offers a somewhat

exapanded representation of the health continuum, adding terms to

describe social well-being and ability to function within a

society.

4.2.3. ---- -- Role of Causal Factors e----e -w---m4.2.3.1 Background

Causal factors in health include hereditary, lifestyle and

envionrmental factors. The causal factors are relevant to the

definition and measurement of health, primarily because they

determine the strength of various health attributes, which helps

to distinguish the important from the unimportant. For example,

if environmental change affects the incidence of cancer, then

cancer symptoms and not the entire range of health attributes

will be a principal focus in a study related to the environment.

Among cancer symptoms, the degree of refinement of measurement of

physical pain versus mental anguish will be determined by the

relative strength of these attributes among cancer victims. Furthermore the causal factors determine how greatly a policy will

affect health attributes, which in turn determines the range of

change in health attributes that need to be studied.

As noted, health is influenced by a great number of forces,

which can be described as hereditary, lifestyle, and environmental. Health can be seen a$ a process of continuous adaptation to

the effects of these forces (Carroll, Miller, and Nash,). The

nature of these influences and their relative importance to human

health have been described by Hettler and by Blum . Health is

described as an indivisible whole comprised of somatic

(physical), social, and psychic (mental) well-being: illness in

any one of the three facets affects the other two.

Of primary concern to the valuation of risk reduction are

the environmental and- behavioral influences on health, and, to a

limited extent, medical or health care. Heredity, though important, will not be given further attention here. Furthermore, the

definition of environment outlined by Blum encompasses education,

culture, and politics, factors beyond the scope of this study.

For our purposes, environment consists of the interaction between

human health and physical factors, such as air and water quality

stressors, toxic substances present in the ambient environment,

workplace hazards, radiation exposure and accidents. We assume

that these aspects of the physical environment are partly under

the control of an individual. Behavioral factors are under even

greater control of the individual, and demonstrably influence

personal health (Somers, 1980).

Some generally accepted conclusions are:

4-7
1. Everyone is endowed with certain health assets at

birth. These may be above or below averages for the

population in general. Regardless of initial birth

endowment, however, the health of an individual is

subject to change.

2.

3.

4.

5.

4.2.3.2.

The

Interventions can influence the health of each

individual either positively or negatively. Some

interventions will have an immediate effect on health

level (e.g., an automobile accident); the effects of

other interventions may not manifest themselves until

years after the intervention (latent effects of

cigarette smoking, for example). These examples are

,illustrated in figure 4-2.

Health changes can be temporary and reversible, such as

those associated with a common cold or exercise, or the

.health change can be permanent such as loss of a limb

or contraction of emphysema.

Interventions may be voluntary, involuntary, or

something in between. Cigarette smoking clearly is

voluntary, but subjecting oneself to the risks of

living near a hazardous chemical facility may be either

voluntary or involuntary, depending on the amount of

information available to the risk taker.

The health path will, at some point, terminate in

death. For an individual, this termination can occur at

any aget regardless of health.

Role of Behavior or Lifestyle

influence that behavior can have on health has been long

recognized, but systematic study and measurement of the

implications of human actions on health are recent developments.

Behavior patterns, or lifestyles, are at least partly under

individual control. Lifestyle is intimately tied to social class

and culture -- complex concepts describing characteristics of

human interactions whose effect on health is not easily quantified. Nonetheless, it is clear that intervention against lifestyle-induced risk factors can reduce the probability of dying

from the major causes of death (Berkman and Breslow, 1983; Klein,

1980; Mausner and Shira, 1984; Somers, 1980).

As Somers affirms, the links between behavior and health can

be summarized in three statements:

1. The major causes of death, serious illness, and

disability in the United States today are chronic

disease and violence (see table 4-l):

2. Most chronic disease, disabilities, and premature

d,eaths are related to a variety of environmental and

4-a
FIGURE 4-2. EFFECTS OF INTERVENTION

\

I I I I

0 20 40 60 80 100 .

Age

CA1 is a short - term intervention which has an immediate

short-term positive temporary effect on health (such as exercise).

(81 is another short-term intervention, but it has a latent but

substantial permanent deleterious effect [such as exposure.

to a carcinogen).

4-9
TABLE 4-1. DEATH RATES: Leading Causes of Death, United States, 1979*

-------v-w---------------------~--------------------------------

Cause Rate/lOO,OOO Percent of

Population All Deaths

Diseases of heart 333 38

Malignant neoplasma 183 21

Cerebrovascular disease 77 9

Miscellaneous chronic diseases** 56 7

Accidents, including motor vehicle,

suicide, and homicide 70 8

Other 151 17

All causes 870 100

* Figures Rounded

** Diabetes, cirrhosis of liver, arteriosclerosis, bronchitis,

emphysema and asthma, nephritis and nephrosis, peptic ulcer

From National Center for Health Statistics: General Mortality

Statistics, 1979, Volume II, Part A.

4-10
behavioral factors,, which may be preventable;

3. Lifestyle pattern is the major behavioral risk factor

.involved in chronic disease contraction and disability

(Somers).

No matter how comprehensive a nation's programs of

enviornmental monitoring, or how extensive its health care

services, the individual is ultimately responsible for minimizing

threats to his health (Mechanic and Cleary, 1980). Factors such

as smoking, alcohol and drug abuse, lack of exercise, reckless

driving and failure to use seat belts can have considerable

effects on health status and life expectancy (Breslow, 1978;

Breslow and Enstrom, 1980; Mechanic and Cleary, 1980). This is

not to say that people can easily correct negative behavior,

because they are a part of the larger society and influenced by

its institutions, which offer ambiguous messages about what is

advisable behavior (Blum,; Surgeon General's Report,). Nonetheless, a willing individual can take steps which will measurably

affect health status.

4.2.3.3. Role of Environment

Nature of Cause-Effect Relationships

Several approaches that relate environmental stressors'to

health effects have been considered. While the present research

is concerned with valuing health consequences, and not with

environmental cause-effect relations as such, some attention to

cause-effect relations is needed.

In the following sections, the source-receptor-effects

system is described. Inventories of some of the pollutants

receiving considerable study and public attention during the past

15 years are presented. The extreme uncertainty of cause-effect

relationships is indicated. The relationship between the present

section and section 3.2 on cause relations may be noted. Section

3.2 contributes to the study of light symptoms. It is more

quantitative and has greater depth on a narrower range of

pollutants than the present section. The present section serves

as an introduction to a wider range of pollutants needed for the

study of serious illness.

With few exceptions, the existence of causal relationships

between pollution in the ambient environment and disease is

difficult to quantify. Problems arise in attempting to relate

exposure to a suspected agent with the development of illness,

particularly if the illness is preceded by a long latency period

(Task Force, 1982).

4-11
Figure 4-3 summarizes the complex path between a source of

pollution and a variety of possible health effects including

death. Moving down the diagram, the source of pollution may be

industrial, residential, natural, etc. The emission may be from

air, water, land, or a combination of media. The pollutants are

likely to be diluted, transformed, and partially decayed before

reaching exposed human receptors.

Note that defensive measures may be applied at the source to

reduce the amount of, or entirely eliminate, the emission; other

personal defensive measures may be applied prior to exposure

(migration, air conditioning, etc.).

After or during continuous exposure it is likely there will

be a finite latency period before adverse health effects, if any,

appear. Uncertain and often lengthy latency periods make

exposure-effect determinations very difficult.

The adverse effects, by definition, include any departure

from optimal health. They range from almost imperceptible

discomfort to terminal lung cancer. These adverse effects might

be defined either as groupings of symptoms or as a clearly

identified disease. Defensive and/or curative measures may

reduce the effect of disease, but the adverse environmental

effects may still be present. Adverse effects are not discretely

divided into morbidity and mortality, but rather, the effects are

seen to influence a health continuum which begins with optimal

health (that existing in the absence of pollution) and ending

with death.

Even prior to exposure, however, health can be adversely

influenced by factors other than pollution, such as age and

previous medical history. Each person exposed, at a different

point on a different route, will die. The ch-allenge is to define

the environmental influence on each path of mortality.

There is uncertainty at each linkage. Rosen (1981)

concludes, "The most pressing need is for better estimates of

risk valuations. That 'pressing need' would require much better

data than currently are available." .

In,summary, the complexities involved in establishing direct

cause-effect relationships include:

Exposure to a toxic substance which may occur through

direct contact with contaminated soil, water, air,

food, or in the workplace;

The substance may be absorbed through the skin,

ingested, inhaled;

Contact may be brief, prolonged, on single, multiple or

continuous occasions;

4-12
FIGURE 4-3. POLLUTION-HEALTH RELATIONSHIP

c

Source

Dispersion

Ttansf ormation Defensive

Decay measures

.

,

Latency

period I 4

Y

Effects

4

?

Symptoms Definable

I P

I

disease I

I

Eventual death

4-13
The effects may be manifest very shortly after exposure

or, as in the case of carcinogens, many years later;

The substance may act synergistically with other agents

to produce illness, such as asbestos exposure combined

with cigarette smoke;

The existing health status of the exposed person may affect

the development of illness.

Of the harzards to human health arising from toxic

substances, cancer is the target of most concern. It is the only

major cause of death that has continued to rise since 1900, and

is responsible for the loss of 400,000 lives each year. Some of

the increase in cancer mortality since 1900 is a function of the

greater average age of the population and the medical progress

made against infectious diseases. But even after correcting for

age, both mortality rates and incidence of cancer are increasing.

It is extremely difficult to assess the role that

environmental factors play in causing human cancer because

people are exposed to multiple stressors of both physical and

chemical natures, some of which are related to their own

behavior. Some early estimates of the proportion of cancers

directly attributable to environmental agents were as high as 85-

90 percent, but more recent analyses suggest that the role of

environmental health pollutants is minimal (Task Force, 1982).

This finding is supported by Doll and Peto (1981) who compare

environmental and behavioral risks and conclude that the

environmental and occuptional risks are relatively minor.

Much of what is known about the acute and chronic health

effects of chemical substances has come from studies of workplace

exposure. Many workers die each year as a resultofphysical and

chemical hazards at work, but the exact magnitude of the longterm health effects of occupational conditions is unknown (Toxic

Substances Strategy Committee, 1980).

Complex human epidemiology over a lifetime seems essential

if progress at unravelling the cause- effect complexities is to be

made. Animal studies are a poor substitute for human study

because of the low ambient concentrations of toxics and long

latency periods. In addition, animal studies cannot be used for

annoyance symptoms (e.g., cough, headache).

The kinds of research needed to define environmental health

risks are described in-depth in a report for U.S. EPA (Babcock

and Allen, 1982).

Health Effects of Selected Environmental Contaminants

The following is a l&St of some of the most persistent and

4-14
widespread pollutants which are of continuing concern to public

health. The list resulted, from a review of (1) the first

thirteen annual "status" reports of the Council on Environmental

Quality, which examine the environmental issues of greatest

concern to the government and public, (2) recent summary reports

and literature of governmental agencies and other researchers in

the field of environmental health, and (3) current toxicology

references. (See Council on Environmental Quality, 1970-82; Duffus,1978; First Report on Carcinogens, 1980; Hamilton and Hardy's

Industrial Toxicology, 1983; Handbook of Hazardous Materials,

Fire-Safety- Health, 1983; Patty's Industri.al Hygiene and Toxicology, 1978; Toxic Substance Strategy Committee, 1980; Waldbott,

1978). The inventory includes some substances which are ubiquitous in environment, but the health effects of which are

uncertain, particularly with regard to long-term, low-level exposures. It must be stressed that the health effects listed below

are associated primarily with chronic or acute exposure levels

found in the workplace, and usually not in the ambient

environment.

Asbestos is the generic name for several varieties of

naturally occurring fibrous minerals which are heat, friction,

and acid resistant, and are flexible and strong. They are used

primarily in cement, fire-proofing, in formation of pipes and

ducts for air, water and chemicals, brake pads and linings,

roofing, garden ornaments, and furniture. Exposure can lead to

pulmonary fibrosis (asbestosis), cancer of the lung, and the

chest or abdominal cavity, and gastrointestinal carcinoma.

Symptoms of respiratory illness include unexplained

breathlessness upon exertion, cough, tightness of the chest, skin

discoloration, enlargement of fingertips.

Arsenic is released in the combustion of coal, the

manufacture of insecticides, herbicides and fungicides. It is

present in the ores of copper and iron, and is oxidized during

smelting. It is inhaled, ingested, and absorbed through the

skin. It has been associated with cancers of the skin, lungs, and

liver, as well as birth defects, nausea, diarrhea, stomach pain

and constipation.

Benzene is the basic chemical of the group called aromatic

hydrocarbons. It is used in the fabrication of paints,

.

adhesives, dyes, plastics, chemicals, detergents, and pesticides,

as an additive to gasoline, and in synthetic rubber manufacture.

Benezene accumulates in the bones and fatty tissue of humans, and

is a cause of leukemia, blood cell deformations, and is a

depressant to the central nervous system. Drowsiness, headache,

vertigo and nausea are associated symptoms.

Beryllium is a' metal that is resistant to heat, mechanical

stress. It is both light and hard, has high conductivity, and is

non-magnetic. It is used in a variety of industrial processes,

aircraft engines, electric heaters, copper products, steel,

cobalt, and nuclear power production. It has been associated with

bronchitis, bronchiolitis, berylliosis, fibrosis, heart damage,

4-15
pulmonary edema, and death. Symptoms include irritation of the

upper respiratory tract, fever, chills, cough, sputum, shortness

of breath, and weight loss.

Cadmium is a soft, ductile metal resistant to corrosion, and

is used inelectroplating, manufacture of polyvinyl chloride,

jewelry, soldering, batteries, aircraft engines, and automobiles.

It is a contaminant of the soil, air, water and food. Symptoms

include vomiting, diarrhea, colitis, hypertension preceding heart

disease, chromosomal abnormalties, and death.

Motor-vehicle emissions are the largest source of carbon

monoxide. Cigarette smokers experience extremely high'levels

during smoking periods. Regardless of source, the exposures

usually are temporary, with temporary displacement of oxygen in

the blood stream as the primary health effect. Symptoms include

headache, dizziness, nausea, impaired judgment, fatigue, and

unconsciousness. Effects appear to reverse quickly at levels

found in the ambient environment.

DDT is one of the group of persistent chlorinated

hydrocarbon insecticides. It accumulates in the tissues of

aquatic organisms, birds and other animals and plants which are

part of the human food chain. It is present in soil, water, air,

and food supplies. The long-term health effects of DDT on humans

are uncertain, although it acts as a potent neurotoxin on

insects and other animals. It is fat-soluble, and accumulates in

the fatty tissue of humans, degrading very slowly over many

years.

Dioxin, or 2,3,7,8 tetrachlorodibenzo-p-dioxide (TCDD), is a

by-product which appears during the manufact.ure of herbicides.

Again, its low-dose long-term effects on humans have not been

established, but it is known to cause birth defects,

miscarriages, fetal death and other reproductive disorders in

animals. Agent Orange, the defoliant used extensively during the

Vietnam War, contained TCDD. Chloracne is a skin condition

resulting from acute exposure which is characterized by swollen

eyelids, fingertips, and mucous membranes of the eyes and mouth.

Sources of ionizing radiation are both natural (sun, soil),

and human induced (nuclear energy, weapons, isotopes from

medicine and research). Exposure can result from internal or

external s‘ources, and through inhalation or ingestion. The

various radionuclides can cause genetic mutation, chromosomal

damage, impaired cell division, leukemia, cancers of the skin,

lung, bones and genitals, cataracts, shortened life span, and

death. Symptoms of radiation poisoning include loss of hair, skin

ulcers, diarrhea, purpura, and skin hemorrhages.

Lead is an ubiquitous metal found formerly in paints and

currently in batteries, gasoline, insecticides, pottery glaze,

metal cans, and numerous industrial commercial products. It is

found in the air, water, soil, and food. Lead contamination can

lead to kidney disease, jaundice, gout, neurological disorders,

4-16
convulsions, brain damage, sterility, premature birth of

children, and death. Symptoms range from fatigue, weakness,

headaches, and restlessness, to stomach and abdominal pain,

lethargy, sleeplessness, vomiting, diarrhea, and hallucinations.

Mercury is found in medicine, dental fillings, fungicides,

paint and paper manufacture, diapers, coal combustion, asphalt

production, municipal incineration, electrical apparatus, and

plastics. Health effects include visual impairment, brain damage,

and fetal poisoning; symptoms such as tremors, skin eruptions,

abdominal and muscle pains, and visual disturbances occur.

The principal anthropogenic sources of nitrogen dioxide are

the combustion of coal, oil, natural gas, and motor vehicle fuel.

Exposure can cause lung irritation, increased susceptibility to

respfratory infections, pulmonary edema and death in extreme

cases.

Organochlorine compounds (other than DDT) include aldrin,

dieldrin, chlordane, and heptachlor, and have been used for many

years in agriculture and malaria control programs. They are

persistent in the environment, are biomagnified in the food

chain, and are mutagenic and toxic to animal, life. The acute

effects include liver damage and convulsions, with manifestations

similar to those of DDT. The long-term effects of low-level

exposures are not well known.

Ozone is an important constituent of photochemical smog,

resulting from the reaction of nitrogen oxides and hydrocarbons

in the presence of sunlight. It acts as an irritant to the mucous

membranes of respiratory organs, and aggravates existing

respiratory illness. Other effects include eye irriatation,

impairment of cardiopulmonary function, and headaches.

PCBs (polychlorinated biphenyls) are chemical compounds

which are nonflammable and highly plasticizing. They are used as

heat transfer fluids and insulators, and in paints, adhesives,

sealants, brake linings, flourescent lamps, electrical

transformers, and capacitors. Like DDT, PCBs accumulate in fatty

tissue and are slow to degrade: consequently, the long-term

effects on humans are uncertain. The acute health effects

include chloracne. Other symptoms include loss of hair and sexual

power, headaches, numbness, abdominal pain and vomiting, deformed

nails, joints and bones.

soot, tar, and oil are the products of coal mining and

combustion, and of the asphalt, tar and pitch industries. They

usually contain polycyclic hydrocarbons and are associated with

cancers of the lung, larynx, skin, scrotum, and bladder.

Anthropogenic sulfur dioxide is almost entirely a'result of

combustion of coal, wood, and petroleum products. In the

atmosphere, this pollutant can cause bronchial constriction,

irritation of. the upper respiratory tract, eyes and ears,

tightness in the chest, and can aggravate existing bronchial

4-17
conditions. Damage to other environmental systems (acid

deposition) ,may be the primary adverse impact.

Vinyl chloride is the main constituent of polyvinyl

chloride, which is used in a variety of plastic products such as

pipes, ducts, floor tiles, toys, waterproof upholstery, wrapping

paper, film, records, boots, and sporting goods. Exposure to the

gas can lead to liver cancer, acre-oteolysis, pulmonary

teratogenic, mutagenic and chromosomal effects.

4.2.4. --mm-- Health Measurement -----e---e4.2.4.1. Measurements in Terms of Ill Health

Levels of morbidity are commonly classified as a series of

five "D's": disability, discomfort, discontent, disease, and

death. Available evidence argues that trace environmental

pollutants have their greatest impact on the first four "D's,"

although they may contribute to premature death as

well.

Nationwide surveys of Americans provide information on

prevalence of diseases and various health indicators. For

example, the National Health and Nutrition Examination Survey

(NHANES) clinically examines 20,000 different people every four

years. A variety of health, nutritional, and disease prevalence

information is obtained.

The National Health Information Survey (NHIS) provides data

concerning the prevalence of disease. NHIS surveys more than

100,000 people per year, but the survey is restricted to

question-answer interviews rather than examinations. These

tabulations don't specifically indicate numbers of people who

suffer from more than one malady or from the same malady more

than once in a year. Likewise, there is no information about

numbers of people who escape all the diseases. These surveys are

cross sectional; they do not follow individuals through life.

However, such information is useful for construction of likely

scenarios which exhibit certain diseases during a lifetime.

In practice, many health status measurements are based on

functional classification or therapeutic considerations involving

diseased or disabled persons, not those who are well. That is,

the definition is in terms of ill health, notgoodhealth.

Mausner and Kramer (1984) point out that "the development of

disease is an irregularly evolving process, and the point at

which a person should be labeled 'diseased' rather than 'not

diseased* may be arbitrary." Left untreated, a disease may

extend over time with.symptoms changing in stages. This pattern

may be ter,med its "natural history' or "clinical course." In

4-18
relation to age, II... factors favoring the development of chronic

disease are often present early in life, antedating the

appearance of clinical disease by many years." The Mausner and

Kramer framework for analysis of disease history follows.

B-m Stags of susceptibility:

disease,-

----- ------- Prior to the presence of a

factors which may increase the probability of

its development may be pr-esent. These are termed risk

factors. Age, sex, and race are examples which are not

susceptible to human intervention, but alcohol or

tobacco use can be subject to change. The presenc'e of

risk factors does not ensure disease development nor

does their absence ensure freedom from disease.

----- Pre-symptomatic - ------- --- stage:- Pathogenetic changes begin to

occur, but the changes are not manifested in symptoms

or signs which can be diagnosed.

---B---B Clinical stags: --- Recognizable signs and symptoms occur.

It is at this point that classifications of health

status based on functional or therapeutic

considerations are made. Examples for categorization

of cardiac disease appear below.

. Functional Classification:

Class I No limitation of physical activity because of

discomfort;

Class II Slight limitation of physical activity; patient

.comfortable at rest but ordinary activity produces discomfort;

Class III Marked limitation of physical activity; comfortable at rest but less than ordinary activity

causes discomfort;

Class IV Inability to carry out physical activity without

discomfort.

Therapeutic Classification:

_

Class A Physical activity need not be restricted in any

way;

Class B Ordinary physical activity need not be restricted, but patient is advised against sever.

4-19
efforts;

Class C Ordinary physical activity should be moderately

restricted;

Class. D Ordinary physical activity should be markedly

restricted;

Class E Complete bed rest advised; patient confined to

bed or chair.

Descriptions of the natural history of the disease can be

incorporated into indicated health effects. Lung cancer provides

an example as follows:

1. The time when an individual is at no risk: either has

not been exposed to the disease-causing agent (e.g., does not

smoke or work with asbestos), or has been exposed the agent but

is not vulnerable to it (e.g., even in the presence of smoke,

newborn infants are noi vulnerable to, and will not develop, lung

cancer);

2. When one is vulnerable due to genetic propensities or a

change in age or environment and therefore does not have an

immune status;

3. When the damaging agent is present, at which time the

exposed individual is in danger of acquiring the disease (e.g.,

anyone who smokes);

4. When an actual sign of disease is observable by a

physician though not apparent to the victim (e.g.,.an abnormal

chest x-ray);

5. When symptoms appear (severe coughing, chest pains,

blood in sputum) and the individual, who knows that something is

wrong, m.ay tell a physician or other health worker; or

6. When disability, partial or complete, occurs.

The natural histories of many diseases are still unknown.

In addition, some people never develop a disease despite the

presence of a number of risk factors.

The listed functional classifications might be ,expanded into

health indexes by defining various levels of minor discomfort and

pain, and minor limitations of physical activity. Some health

problems attributed to environmental interventions include

learning impairment, peripheral neuropathy, and birth defects.

More simply, however, the history of the diseases provides

descriptions of symptoms and consequences which could be

quantified to a more or less exact degree depending on

4-20
considerations of measurement feasibility in view of a particular

study purpose.

4.2.4.2. Health Indexes

The health definitions discussed in Section 4.2.2 above

suggested that a person has neither absolute health nor absolute illness (except death) but is in an ever-changing state and

that one can be at any point on.the continuum at any point in

life (Murray and Zenthel, 1975). For some purposes it would be

useful to quantify a health continuum, first numerically and then

in terms of economic valuation of small increments of change.

Initially efforts would focus on the simpler Brubaker health

continuum, but the expansions by Hettler into risks and education

might also possibly be useful in contingent valuation studies.

Howard (1984) defines morbidity as a fraction of death.

This principle might be applied to a health index. Some of his

methods involve trading years of life for improved health. He

argues that there are no fates worse than death. Kane and Kane

(1982) disagree.

Pulmonary function tests are used to measure lung

capabilities (Babcock and Nagda, 1976). These and other

physiological tests (exercise, work level, physical education

performance, etc.) might provide another type of index.

4.2.4.3. Multi-Attribute Utility Functions

Researchers in the field of decision analysis have devised

techniques for the characterizati.on or prediction of health

status (Katz et al., 1983; Wolinsky, et al., 1984), usually for

the evaluation and comparison of health care treatment

alternatives or medical policy decisions. Quantitative methods

such as multiattribute utility functions (Keeney and Raiffa,

1976), or linear analog scales (Sutherland, Dunn and Boyd, 1983),

are employed to evaluate the nature of trade-offs between quality

of life and longevity (Pliskin, Shepard and Weinstein, 1980) or

to measure a patient's preference for certain health states

(Torrance, Boyle and Horwood, 1982). Such analytical methods may

involve complex, lottery-based measurement techniques to

determine probabilistic outcomes.

Boyle et al. (1982) employ a multiattribute health state

classification system for use in a cost- effectiveness analysis of

neonatal intensive care. Health status is defined by physical

function, using measures of mobility and physical- activity; role

function, or self-care, such as the ability to eat, dress or

4-21
bathe with or without help; social-emotional function, measures

of emotional well-being and social activity; and health problems,

such as the presence or absence of a disability.

4.2.4.4. Self-rating of Health

As noted in Section 4.2.1, self-assessment is the most

widely used measure of health status. The simple ranking of

one's health (excellent, good, fair or poor) is crude in terms of

being amenable to dollar quantification. However, the measure is

simple, which makes it attractive especially for contingent

valuation studies. While self-rating may not be useable for

obtaining a value measure, it may be useable as a shifter in a

function explaining health values, since the state of one's

health is an influence onhowmuch one is willing to pay to avoid

various specific symptoms or diseases.

4.2.4.5. Health Risk Appraisal

Health Risk Appraisal (HRA) is a tool for assessing the

potential impact of individual behavior on the probability of

dying from selected causes. In the course of an HRA, information

about an individual's lifestyle and personal and family health

history is elicited. This information is then compared with age,

race and sex-specific mortality data and epidemiologic statistics

to determine whether or not a person is a greater or less than

average risk of dying from a selected cause, usually within the

next ten years. Most HRAs are based on the work of Robbins and

Hall and the statistical tables of Geller and Gesner (cited in

Robbins and Hall). The objectives of the appraisal are to estimate individual risk with some degree of accuracy, and, by

identifying risky behavior, help individuals modify or eliminate

negative habits before the development of disease or disability

(Dunton, 1981; Goetz, Duff and Bernstein, 1979; Hettler, 1981;

Schultz, 1984).

The appraisal begins with a self-administered q,uestionnaire.

Each response is assigned a numerical "risk factor" which is then

multiplied with the average risk of dying from each major cause

of death. In the case of multiple risk factors for a single

cause of death, a "composite risk factor" is calculated and then

multiplied by average risk. The resulting disease-specific risk

projections are then summed to form a "total projected risk."

This is then compared to average risk to yield a new term "risk

age" or "appraised age," i.e., the age of an average person with

the same mortality risk as the respondent (Hettler).

This appraised age can be readily compared with actual age.

If the total risk is greater than average (appraised age greater

than the actual age), appropriate behavior modifications are

4-22
suggested. If the suggestions are followed, the individual can

hope to lower the overall risk projection, as expressed by the

value of the "achievable age" (Hettler,). For example, a 34-

year old may have the risk characteristics of a 30-year old

(appraised age) but an achievable age of 29.

It is important to recognize that HRA instruments are,

despite widespread use, still in an early stage of development.

Concern has been expressed about the quality of the data elicited

by a self-administered questionnaire and the accuracy of the risk

(Fielding, 1981; Hettler, 1981, pp. 7-16; Sacks, Krushot, and

Newman, 1980; Schoenbahh, Wagner and Karon, 1983.)

4.2.5. --Implications --------- --- for Valuing Serious Illness ------ ------- ---we--

The approaches to the definition and measurement of health

that have been reviewed in this section serve to bring out the

complex nature of this subject matter. The question becomes: How

are we to measure health in the present study in view of the

complexities?

A first implication that stands out is that measurement in

terms of ill health is appropriate in view of the concern of the

present study with values of eliminating undesirable environmental effects. As reviewed in Section 4.2.3, the possible

diseases and symptoms caused by environmental pollutants can be

described rather definitely in terms of ill health effects.

A second implication is that a broad definition of health

effects is needed, extending beyond physical pain to mental well

being and beyond this to the functioning of the individual.

Conceptually one wants to value all the significant deleterious

effects of the illnesses being studied.

Third, the fact that broad classes of illness are to be

studied among many people in the population means that a

basically simple approach must be followed. People must be able

to think meaningfully about the measures, and it must be feasible

to take the measurements and analyze them operationally as they

pertain to large numbers of people. While the first and second

implications go in the direction of detail and complexity, the

third implication indicates that compromises with the first two

implications will have to be struck.

.

If we look ahead to ensuing sections of this study,

additional implications are obtainod. Thus a fourth implication

is that the present state of health may affect values attached to

contracting particular diseases. It is important to relate

changes in health status to existing levels of health. A fifth

implication is that a person's entire stream of life experiences

with and without a disease affects hov the disease is valued. A

person's age is particularly relevant, as is his expectation as

to the course of events in his life without the disease. Sixth,

4-23
one must look beyond health effects encountered with certainty to

situations of uncertainty. Most people will never contract the

diseases being considered. Environmental improvements will reduce the probability of contracting the disease. Health measurement must give attention, not only to certainty scenarios, but

also to risk reduction in the context of uncertainty scenarios.

The first, second and third implications help in choosing

between existing health measurement approaches. The third,

fourth and fifth implications indicate needs for extensions and

refinements of these approaches. Finally, the fact that the

present study gives particular emphasis to devising contingent

valuation approaches to serious illness affects choice of health

measures.

One of the clearest conclusions from these implications Ls

that measurement in terms of ill health effects is called for in

the present study. In view of the need for operational

simplicity, symptom descriptions in terms of average conditions

brought about by a disease are the basic approach recommended here

for studying values connected with serious illness. The symptom

descriptions need to be supplemented by allowance for full effects of the symptoms on mental well being and functioning of

individuals. In a contingent valuation approach, this can be

done by making the respondent aware of a wide range of effects of

the symptoms.

For getting at the effects of existing health levels on

valuations, self rating of health has much to offer. It is more

readily available than more sophisticated measures, and the need

for precision is less great for measuring the existing health

level than the specific effects of the disease being valued.

The health risk appraisal approach, which takes the trouble

to relate highly specific individual characteristics, including

age and lifestyle factors to health prospects, is highly

congenial to the framework of the present study which stresses

the importance of life experiences and alternative future life

path scenarios. It plays a prominent role in some of the

approaches to health valuation developed later in this study.

The multi-attribute utility function approach has much to

recommenditconeptually for some purposes, but it is not used in

this study, largely because it apears operationally too complex

for this study. Respondents in contingent valuation experiments

can and should be encouraged to take account of the multi-faceted

nature of health effects in framing responses, which is consistent with multi-attribute utility functions. But to quantify the

utility function as such is not attempted in this study, which

is concerned with going directly to dollar valuations of the sum

of all the effects of an illness.

The later parts of this study build on the choices among

existing health measures implied by the above remarks. Refinoments to the health measurement approaches are developed takfng

4-24
account of individual cjrcumstances in a life cycle context with

certainty and uncertainty scenarios.

4.2.6 References ----------

Alliance of American Insurers ) -----------------------~~~~~~~A Handbook of Hazardous Materials

---------- Fire-Safety-Health -------' 2nd edition; 1983.

American Cancer Society, Inc.; "Answering Your Questions About

Cancer;" New York: 1984 (pamphlet).

Ardell, D.; High-Level Wellness ; Emmaus, __ PA: Rodale Press,

1977.

Babcock, L.R. and R.J. Allen; "Cost Effectiveness of Emission

Control:" APCA Journal ------------ 28(3):173-179, 1973.

Babcock, L. R. and R.J. Allen; "Methodologies for Environmental

Assessment;" Unpublished report submitted to the Industrial

Environmental Research Laboratory; USA EPA, 1976.

Babcock, L. R. and N. L. Nagda; "Popex Ranking of Air Pollution

Sources by Population Exposure;" EPA-600/2-72-063, USA EPA,1976.

Banta, D.; "What is Health Care;" Health ------- ------------ ------- Care Delivery in the

--,-------m--p United States 2nd ed.: ed. Steven Jones; New York: Springer

Publishing Company, 1981.

Berkman, L. F. and L. Breslow; ------------- ------mm-- Health and Ways of Living; London:

Oxford University Press, 1983.

Blum, H. L.; "Social Perspective on Risk Reduction;"

----- Family and Community Health -a----------- -------' Vol. 3, No. 1, 1980.

Boyle, M. H;, G. W. Torrance, J.C. Sinclair, and S. P. Horwood;

----------------------------------------------------- Economic, Evaluation of Neonatal Intensive Care of Very ------m-e- LowBirthWeight Infants; Hamilton, Ont.: --- ---------- McMaster University, 1982.

Breslow, L.; "Prospects for Improving Health Through Reducing

Risk Factors;" --------a---------- Preventive Medicine 7:449-458, 1978.

Breslow, L. and J; E. Enstrom; "Persistence of Health Habits and

Their Relationship to Mortality;" Preventive Medicine ------------------- 9:469-483,

1980.

Brubaker, B. H.; "Health Promotion: A Linguistic Analysis;"

----------w---e--- Advances in Nursing Science, April 5, 1983. --------

Carlyon, W. H.; "Disease Prevention/Health Promotion--Bridging

the Gap to Wellness;" -------_-------w-----w-- Health Values: Achieving --- ------- High-Level

Wellness; -w-v---- May-June 1984.

4-25
Carroll, C., D. Miller, and J. C. Nash; Health ----,-A------------B-B the Science of

--------- ------ Human Adaptation; Dubuque, IA: Wm. C. Brown Co., 1976.

.Centers for Disease Contro,l. Health Risk Appraisal User Manual.

Council on Environmental Quality; ---m---------w Environmental Quality ---me --------- Thirteen

----m---w Annual RePorts; ---- Washington, DC: U.S. Government Printing Office,

1970-1982.

Cox, B. G., D. T. Carr, and R. E. Lee; -e--m Living with Lung Cancer; e-e------ -------

Rochester, MN: Mayo Foundation, 1977.

Culyer, A. J.; Measuring Health: -m----v- --a------------,------,,,,,( Lessons for Ontario. Toronto:

University of Toronto Press, 1978.

Doll, R. and R. Peto; The Causes of Cancer: New York: Oxford --------------------

University Press, 1981.

Duffus, J.; ---------------------- Environmental Toxicology; New York: Wiley & Sons,

1978.

Dunton, S.; "A Basic Introduction to the Health Hazard

Appraisal;" ----a--- Promoting Health; -e--e-- American Hospital Association,

July-August, 1981.

Fielding J.; "Reducing the Risk of Risk Appraisals;"

------me Promoting Health; ------- American Hospital Association, July-August,

1981.

Finkel, A. J., ed.; --------------- Hamilton and Hardy's Industrial Toxicology, ------------------

4th ed.; Littleton, MA: John Wright-PSG, Inc., 1983.

Fuchs, V., ed.; --------- Economics -- ---- Aspects --of ------ Health; Chicago: University

of Chicago Press, 1982.

Goetz, A. A., J. F. Duff, and J. E. Bernstein; "Health Risk

Appraisal: The Estimation of Risk; ------------------- --- State-of-the-Art PaPers;

Programs in Occupational Settings, National Conference on Health

Promotion, 1979.

Hanlon, J. and G. E. Pickett, eds.; ----------------------m----m Public Health Administration

,-eme--m---- and Practice 8th ed.; St. Louis: College Publishing, 1984.

Hettler, B.; ------ ,--,A----- Description Analysis ---A---------,--,-,---,,-------- and Assessment of Health

------ ------------- HazardLHealth Risk Appraisal ------a--- Programs we--A----,------,---,- Executive Summary!, Final

RePort; Chapel Hill: Health Services Research Center, University

o? Nirth Carolina, 1981.

Hettler, B.; "Wellness Promotion on a University Campus, Family -----

------me---- and Community Health; 1981. a------

Howard, R. A. and J. E. Matheson; -e-w------ The Principles' ------m-w and Applications --m---v--

-m--------d----- of Decision Analysis ---A---------- Volume II*' Menlo Park, CA: Professtonal

Collection, Strategic Decisions Group, 1984.

Hoyman, H. S.; "An Ecological View of Health and Higher

4-26
Education;" ------,-------------,,,_,,_) Journal of School Health 35. March 1965.

Kane, R. L. and R. A. Kane; Values and Long-Term -------------- ---------a' Care. Lexington,

MA: Lexington Books, D. C. Heath and Co., 1982.

Kaplan, R. M.; "Human Preference Measurement for Health Decisions

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4-28
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4-29
4.3. THE QUANTITY AND QUALITY OF LIFE: CONCEPTUAL FRAMEWORK

4.3.1. Introduction

Serious professional interest in cost benefit analysis of

projects involving safety, illness and death probabilities has

its origins in environmental concerns beginning in the 1960s as a

practical policy matter, and in the work of Schelling and Mishan

as an intellectual one. These authors showed how to put the

problem into the "willingness to pay" framework of applied

welfare economics, which has been the guiding principle in

economic research in this area ever since. Subsequent research

has followed two distinct conceptual lines. Beginning with the

important paper by Usher, one line has followed a strictly life

cycle framework. Building on the paper by Yaarf, work by

Cropper, Conley, Ehrlich and Chuma, and Arthur (this the only

general equilibrium paper in the literature) have built

increasingly elaborate models of life-cycle valuation criteria.

Another line, and one which has tended to guide most empirical

work, uses a simplified single period model without explicit

regard for life cycle considerations (e.g., Jones-Lee, Rosen,

Thaler and Rosen). The single period.models are conceptually

simpler than life cycle models, but may miss some important

considerations that arise in the fully dynamic life-cycle setting

which the problem obviously requires.

This section is concerned with life cycle models of safety

and health evaluation. One of its goals, at least by

implication, is to show the close relationship between life cycle

and single period models. This is achieved by stripping away

many of the detailed complexities of life cycle dynamics to

reveal the internal structure of the problem most clearly and in

the most elementary manner. In fact this is most easily done in

a deterministic setting, in which a person has a fixed 1ongevLty

and is allowed to optimize consumption and labor supply decisions

. over his fixed length of life. The solution to the optimal

program naturally leads to a simple formula for putting dollar

values on suitably small increments of longevity, using the

principles of duality theory. Models of this type are discussed

in the following two sections. First a simple consumption

allocation problem is analyzed and the valuation equation

exhibited. Then the model is complicated in a number of ways.

It is shown that most of the principles underlying the simplest

model carry through for all variations on the theme. This model

may be extended to include valuation of morbidity as well as of

longevity.

While deterministic models are useful in their great

simplicity, they suffer obvious defects in terms of realism.

4-30
Therefore the remainder of the paper turns to stochastic models

using actuarial calculus and the insured-consumption-loans device

for dealing with intertemporal budget constraints introduced by

Yaari. The insurance features of these schemes allow the

analysis to separate allocation decisions regarding consumption

and labor supply from uncertainty regarding length of life. The

exposition brings out the intimate connection between

deterministic and stochastic models and shows that the same types

of parameters are relevant for both. Chief among these is a

parameter which is naturally interpreted as reflecting the

inherent substitution between "quantity" (or longevity) and

"quality" of life. It is closely related to the economic concept

of intertemporal substitution. Estimates of the "values of life"

from existing empirical studies allow rough imputations of this

parameter, which ultimately relate to the question of how much of

the economy's wealth should be spent on safety, health and

longevity concerns. Other relevant factors are shown to include

the rates of interest and time preference, the level of wealth

and the person's stage in the lifecycle.

An interesting implication of this analysis is that personal

valuations of life expectancy inevitably vary over the life

cycle. This important point is the inevitable consequence of the

finiteness of life itself and the effect of discounting. Hence a

person who chooses an action when young that affects subsequent

mortality may life to regret it-later, in the sense that in the

circumstances he finds himself in later he would have somehow

"preferred" not having taken the earlier action. However, there

is nothing either inconsistent or irrational in this type of

behavior, since by hypothesis, the full future consequences of

current actions are foreseen when they are chosen. It does mean,

however, that the benefit side of any cost-benefit calculation on

these matters must take account of the life cycle structure of

valuations and will be sensitive to the age and demographic

composition of the population and how it changes over time.

4.3.2. --- ----- -- The Value of Longevity: Deterministic Model --a ---- - ------------- -----

In this section we consider a deterministic problem which

sets many of the essential ideas for the valuation of life

expectancy. Consider a person with time- seperable preferences

for consumption over a lifetime of length T:

(4-l).

-at

U- Integral from 0 to T of U(c(t))e dt,

where the concave function u(c) evaluates the utility of consuoption c at time t and a is a fixed and constant rate of tima

preference. The person is endowed with a fixed wealth W at the

beginning of life and has a fixed investment opportunity which

yields a return of r. The problem to be considered is how the

person would allqcate his fixed wealth over consumption at each

4-31
point in the life cycle. The solution to this problem yields the

valuation we seek.

Let W(t) represent remaining wealth at time t and let

dW/dt be the change in wealth at time t. Then the budget

constraintfacing this person may be written in flow terms as

(4-2) dW/dt - rW - c,

which has a ready interpretation. rW is the income from

investing current wealth at rate of return r and c is the amount

that is consumed out of this income. If consumption falls short

of current income the person's wealth must be increasing, while

if current consumption exceeds current income his wealth must be

decreasing.

.

The formulation of preferences in (4-l) is consistent with

the situation of an unattached individual who has no heirs and

therefore no bequest motive. We impose the condition that the

person cannot die in debt, and since he does not wish to leave

wealth (there are no heirs), we have a boundary condition for the

differential equation in (4-2) that W(T) - 0. The- person will

obviously wish to consume all endowed wealth over the entire life

cycle. Using this boundary condition and integrating (4-2) yields

an equivalent budget constraint in terms of stocks:

(4-3) w * Integral from 0 to T c(t)ewrt dt

Initial wealth equals discounted lifetime consumption.

Consider the problem of maximizing U in (4-l) subject to

constraint (4-3). Let V(T,W;r,a) denote the maximum of U given

that the sequence c(t) is optimally chosen. Clearly V is a

function of the parameters of the problem, which are T, W, r and

a. This value function allows us to -me-- e---e--- calculate the value of

longevity. Let L denote the value of longevity, defined as the

maximum amount of wealth a person would willingly give up to

extend his life by a small increment dT. In exchange for an

increment dT, the person would be willing to pay as much wealth

as would keep V at its initial level. This is therefore nothing

more than the marginal rate of substitution between T and W

implicit in V. Totally differentiating V and setting the result

equal to zero, we have

(4-4) v * - dW/dT - partial of V w.r.t./

partial of V w.r.t. W

4-32
To evaluate this expression it is necessary to first solve the

maximum problem.

Associating a Lagrange multiplier m with constraint (4-3),

first order conditions for maximization of (1) subject to (3) are

(4-5) u'(c)eSat - meert for all t.

The marginal utility of consumption is proportional to the

positive multiplier m, suitably discounted by' the difference

betweem r and a. To simplify even further, let us analyze the

leading case where r - a. Then (4-5) implies u'(c) - m, which in

turn implies c(t) - c, a constant for all t on [O,T]. That is,

lifecycle consumption is "flat" and the same at all ages, an

especially pure form of the permanent income hypothesis. Using

this result and substituting into (4-l) defines V as (since r -

a>.

-rt

(4-6) V - Integral from 0 to T u(c)e dt - u(c) integral from 0 to

-rt -rT

- u(c) integral from 0 to T e dt - u(c)(l/r)(l-e )

- (by definition) u(c)A(T),

where A(T) - (l/r)(l-emrT) i s simply the value of an annunity

received for T periods at rate of interest r. A(T) is the

"correction factor" for finite life.

Now from the budget constraint, after substituting

c(t) - c, we have

(4-7) W- rT (c/r)(l-e' ) - CA(T) .

Therefore c - W/A, which is just the finite life-corrected level

income which exhausts the endowment W at T exactly. Putting (4-

6) and (4-7) together, we have

(4-a) V - u(W/A(T))A(T) .

There are two immediate consequences of (4-8). First, V is

strictly increasing in W:

4-33
vW - partial of V w.r.t. W - u'(W/A) > 0;

greater wealth makes a person better off. Second, the effect of

T is confined to its influence through A. Now A is increasing in

T, since an annunitythat lasts longer has a larger value. But A

has two effects on V. It has a negative effect through its

influence on the first term in u(.> in (4-8) but it also has a

direct positive effect through the multiplicative second term in

(4-8). Concavity of u(c) implies that the second direct effect

dominates and that V is increasing in A:

(b-9) vA - partial of V w.r.t A

I - (W/A)u'(W/A) + u(W/A) - u(W/A)(l-E)

where E - cu'(c)/u(c) is the elasticity of the function u(c). We

require 0 5 E 11 for the problem to be well conditioned and for

the marginal condition (4-5) to characterize the optimum. Therefore VA > 0. Though there is no direct value of length of

lifetime T in preferences in this problem, its value is induced

by its effe

?

t on A.

A'(T) - esr

From the definition of A(T), we have

> 0.

We are now prepared to evaluate v. Totally

differentiating (4-8),

(4-10) dV - u(W/A)A((E)dW/W + (l-E)(A'/A)dT) .

Sett%ng (4-10) equal to zero, the value of longevity is

(4-11) v- -dW/dT - A'(T)[(l-E)/E](W/A) - emrT [(l-E)/E](W/A)

(4-11) displays some interesting properties:

(i) v is increasing in wealth (given E). Longer life is more

valuable to wealthier persons and they are willing to pay more to

extend it. This is one reason why life expectancy is longer in

societies with greater wealth, which spend some of it on safety

devices and living styles that promote longevity. Notice

however, that in this formulation -dlogW/dT is independent of W: --e- ----we

all individuals are prepared to pay the same percentage of their

wealth to extend life when preferences are of this form.

(ii) An especially interesting and unusual implication of (4-11)

is the role of the term in E, which relates to the curvature

properties of the function of u(c). This in turn is related to

the question of intertemporal substitution possibilities in consumption. To see this most clearly, let us examine some limiting

4-34
cases. First, look at what happens in the limit.as E goes to

unity, so that u(c) goes to a linear function of c. Then according to (4-l), we have that U is essentially summable in c(t) and

all that matters to the person is total consumption over the life

cycle, andnotatallhowa given total is distributed over ages.

One big consumption bash at some time is equivalent to many

periods of much smaller consumption levels, for example. Here we

have VA - 0, so v goes to zero as well. A person is not willing

to pay to extend life when E -1 because the increasedhorizonis

completely offset by lower per period consumption: V - W in this

case, which is independent of T. This is a case of perfect

substitution between the "quantity" and "quality" of life, equivalent to perfect intertemporal substitution in consumption

across periods.

At the opposite extreme, consider what happens when E goes

to zero. Here the indifference curves in the c(t) hyperplane

exhibit "elbows" and fixed proportions (in the E - 1 case they

are stra.ight lines), so intertemporal substitution possibilities

are nil. Now the person is willing to pay large amounts for

greater life expectancy, since each year of life becomes

"essential." The main point is that limited substitution of

consumption across years of life implies that quantity and

quality of life are imperfect substitutes for each other. There

is an inverse relation between the value of longevity and the

degree of intertemporal substitution in consumption in lifecycle

preferences.

(iii) Substituting for the definition of A(T) in (4-11) we have

v-e -rT / (l-e-rT )[(l-E)/E]Wr,

and it follows that partial of v w.r.t. T C 0. Hence a person

with a smaller horizon is prepared to pay more to extend life

than a person with longer horizon. In particular, this result

implies that other things equal, younger persons are willing to

pay less to extend their life than older persons are prepared to

pay. That L itself changes over the lifecycle may cause a person

to, in some sense, regret past decisions. However, there is

nothing inconsistent with this when preferences are timeseparable and discount rates are constant over age.

(iv) v is not necessarily decreasing in r (given that a

adjusts conformably). This experiment applies to a comparison of

two societies, one in which persons are impatient and have high

rates of time preferences, and one in which they have more

foresight. In both, however, the interest rate adjusts to the

rate of time preference. There are two effects: On the one hand

the term in the exponential9 in the expression under (iii) is

decreased by an increase in r. On this account the value of

longevity tends to fall. But on the other hand, the term in Wr

is increased and real income is larger. The second effect

dominates if T is short enough, but if T is sufficiently long

4-35
then v will fall. It is surprising that the effect of a change

in time preference and interest rates (together) cannot be

signed.

Let us now examine the internal consistency of the solution.

Suppose that the program derived above has proceeded for s

periods. From that point on the person has T'- T-s years of life

of life left and has already consumed a fraction of initial

endowed wealth. Let W' denote current wealth (after s periods

have passed by). Then

W’ - integral from 0 to T' of (W/A)e'rt dt - (W/A)B,

where B - (l/r)(l-e "rT') is the value of the remaining annuity

for T' periods. Now it is clear that the optimal program from

time 2 onward remains the same as before, because the budget

constraint becomes, from point;s onward, integral from 0 to T of

c(t)e dt - cB - (W/A)B and we have already determined c to be

equal to W/A. Another way of saying this is that the new budget

constraint becomes W' - cB, so c - W/A also solves the "new

problem" from s forward. The person doesn't change his plan.

However, the value function changes as the person ages:

V' - integral.from 0 to T' of u(W/A)e'rt dt - u(W/A)B

so the value V' when there are T-s periods left is smaller than

the value V when there are T periods remaining because B < A.

That the value function is decreasing with age (reaching its

minimum at the age of death T) is due to the fact that terms are

continually lopped off the sum of discounted utilities of further

consumption as the person ages. Now in terms of remaining

wealth, we have c - W/A - W'/B, so V' - u(W'/B)B is precisely of

the same form as (4-8) above, with B replacing A. Substituting

from the above, we find

V' - vers,

so the value of life grows exponentially with age (2) in this

case.

The relationship between v' and v 1n the expression immediately above makes clear the economic rationale for increasing

value of life with age. In this deterministic problem, the

the experiment tacks on extra years at the end of the program,

and these terms are necessarily discounted-to present value.

Something might have very large value at the time it occurs (as

it does, for example, for a person at death's door, so to speak.

in this problem). However, if the event will only occur sometioo

in the future, its current value is greatly reduced by

discounting. Even though a young person and an old person will

4-36
have the same value of longevity when they actually reach age T,

at their current ages, this is discounted by a different amount

due to horizon differences.

This simple point has some important practical

implications, and even survives to stochastic models where the

length of life is random rather than deterministic. It means

that risks and actions which have long latency periods and which

are long deferred can have small value to many people, especially

young people. The young may appear "reckless" on this account,

but such "recklessness" is rational. To illustrate the point

further, suppose there is an opportunity to extend life by dT

which costs a fixed amount independent of age. Then, since L is

increasing in age, there is a threshold age, call its* such that

people who are younger than s* do not purchase the opportunity,

while those whose age exceeds s* purchase it. Similarly, if the

market provides an opportunity to trade money and wealth for

shortened life expectancy (as in risky jobs, for example) there

is another threshold age s**, such that people who are younger

than s** voluntarily make the trade and undertake the risk,

whereas those who are older than s** do not do so.

4.3.3. ---------- Extensions of Deterministic Model -- ------------- -----

4.3.3.1. Nonconstant Consumption

The strong result that c(t) -c in the model above derives

from the assumption that r - a. It is well known that when these

two parameters are unequal then c(t) is either decreasing or

increasing. To illustrate, consider an example in which r

exceeds a. Then application of (4-5) shows that c(t)

is increasing. To make further progress we need to be more

specific about u(c),

u(c) - cE,

so assume the constant elasticity case where

with 0 < E < 1. Detailed analysis reveals that the

relevant discount facto in this case is q - (a -Er)/(l-E).

Defining A* -

f (l/q)(l-e'q ) we obtain the following expressions

for V.

In the case where q - 0, V becomes

V I WE +Ee .

In this case there is direct valuation on T itself, because the

effective discount rate is zero (and only sums matter, not

discounted sums). Here we find

v- [Cl-E/El(W/T),

which is increasing in W and decreasing in E and T, much as

before. In the more probable cases where q RO, we find

4-37
v-wE (A+ E - (W/A*)E A* - u(W/A*)A*,

which has a form very similar to the simpler case where r - m

in all cases therefore the conclusions are very similar to the

analysis above and need not be repeated.

4.3.3.2. Age-Dependent Preferences and the Quality of Life

The model so far has assumed that the utility function

u(c) is constant over life and has no age-dependent factors built

into it. However, it is intuitively clear how the presence of

such factors would affect the analysis. Suppose for example that

the quality of life deteriorated with age, so the utility

function u(c) is decreasing over time. Then the value function

would be adjusted conformably and the value of life calculation

would take this into account, e.g., if life got progressively

worse with age then a person would not pay as much to extend it,

obviously.

For example, introduce the age-dependent factor in a

multiplicative way as follows:

u- integral from 0 to T of u(B(t))c(t))e'at.

Here the term in B(t) represents a consumption correction

factor to make "real" consumption equivalent across ages. For

example, if B(t) is decreasing in age, it takes an ever

increasing amount of consumption to make up for the lower

"efficiepcy" of consumption as a person ages. In this case the

marginal condition, in (4-5) above is simply altered by

multiplicatipnB;f the left hand side by B(t). If we also assume

that B(t) - e then the analysis is virtually identical to

that of section) 4.3.3.1 (where the discount rate of time

preference does not necessarily equal the rate of interest).

Again, the refinement is a minor one.

4.3.3.3. Bequests

Suppose now that the person has heirs and that at the time

of death all remaining wealth is transferred to these heirs. The

standard way to incorporate a bequest motive into a life cycle

problem is to introduce a bequest function into the utility

function. Thus write

U - integral from 0 to T of u(c(t))e"at dt + e -aT f(Wb ),

4-38
where the first term is identical to that above, and the second

term reflects the person's utility of bequests. The amount of

bequests artTWb which yield utility (discounted to present

value) of e f(W), >. Now the wealth constraint becomes

W- integral from 0 to T of c(t)e'rt + wb e"rT

and the necessary conditions to the maximum problem are

u’(c)e’at - m e"rt,

f'(Wb)e" aT * m e"rT.

Assuming r - a again for simplicity, we have

u'(c) * f'(Wb) * m

and the constraint becomes

w- CA + Wb A'

where A and A' - dA/dT were defined above.

Using these conditions and applying the envelope theorem

to v, we find

partial of V w.r.t. W - m

partial of V w.r.t.

- [u(c) - m]e -rT " re'rT [f(Wb) " mWb].

Using the simplified first order conditions and simplifying

yields

V- -dW/dT - e"rT [c(l-E)/E - rWb (1-E*)/E*],

where E *

- f'(wb>wb /f(w,) i= the elasticity of the bequest

function. Thus the presence of bequests and bequest motives

reduces the value of life in and of itself,.because of the

offsetting benefit to heirs of the person's demise. Of course

this strong conclusion is built on some special assumptions, of

which two are particularly important. One is that the utility of

own consumption may itself be affected by the presence of heirs

and children in the household. People tend to have children

because they want to and because it increases their own utility

over and above any affect of bequests. Hence the presence of

heirs may make life itself worth more to the person, which tends

4-39
to increase the value of longer life rather than to reduce it.

Second, the. heirs may suffer a loss of utility from the person's

death, and this utility loss should be valued by the person

himself if he is altruistic (really, a form of reciprocal

altruism). This factor would also tend to increase the value of

longer life.

4.3.3.4. Labor Market Activities

Let us now consider a person who has endowed wealth W, as

before, but who also has the opportunity to work at an hourly

wage rate w. It is necessary to alter the utility function to

handle this case because some valuation must be placed on

leisure. Let L be leisure and normalize so that 0 5 L 5 1. Then

(1-L) is the amount of time devoted to work. Maintaining time

seperable preferences as before, write the utility function as

(4-12) u- integral from 0 to T of u(c(t),L(t)e'at dt,

where the utility function u(c,L) has conventional properties.

The person has two sources of income in this problem. One is

endowed wealth and the other is (endogenously chosen) earnings

w(l-L). .The intertemporal budget constraint equates the present

discounted value of earnings plus endowed wealth to the present

discounted value of consumption over the life cycle:

(4-13) u - integral from 0 to T of w(t)(l-L(t)e'rt)dt

- integral from 0 to T of c(t)e'rt dt.

Optimality conditions for choice of c(t) and L(t) which maxLmize

(4-12) subject to (4-13) are

(4-14) U,(c,L)e'at - me'rt,

UL(c,L)e"at - mwe'rt.

Solving these two equations along with the budget constraint

yields the optimal traj-ectories for L and c.

We can place this problem in the context above by making

the simplifying assumption that r - a and that w(t) - w. Then

(4-14) implies

(4-15) UL (cm/u, (c,L) - we

4-40
u, (c,L) - m,

which imply that c(t) - c and L(t) - L are constants over the

life cycle. Therefore, we may write

(4-16) V - max {u(c,L)A + m (W + w(l-L)A - CA)),

c,L

where again A is the present value of an annuity that lasts for T

periods. Using the envelope property of a maximum., we find

(4-17)

VW - m,

vw -

m(l-L)A,

vT - [u(c,L) + m(w(l-L) - c)]A',

- [u(c,L) - m (W/A)JA', _

where the second equality in the last expression follows from the

budget constraint.. Therefore

(4-18) v- 'T/'W - [u(c,L)/uc (c,L) - (W/A)lA',

since m - uc from the marginal conditions, Defining the

elasticity E - cut /u as before, (4-18) becomes

(4-19) v- [c/E - (W/A) IA'.

This may be written in yet another way: solving for c from the

budget, we have c - W/A + w(l-L). Substitute this into (4-18)

and rearrange:

(4-20) v- [(W/A)(l-E) + w(l-L)] e'rt/E .

Look at (4-19) first.

posit'ive and negative

The value of longevity has both a

A' - e"rT).

term (of course suitably discounted--

The positive term is the level of consumption

adjusted by the inverse of E, and since E cannot exceed unity.

the actual value of consumption is a lower bound for this term

The negative term in W/A, which is just the level incooo

available from an endowment of nonhuman wealth W available at

interest rate r from T periods. This must be subtracted from tha

adjusted consumption level because an increment of life T lowers

4-41
the annuity value of income available from W because it must be

spread over a longer interval and consumption in earlier periods

is lowered on that account.

The second form of v in (4-20) shows that the value of

longevity has a relationship with observed income as well as with

observed consumption. The first term in this expression is

W/A)WE)e Irt/E, precisely the same as when leisure is not

considered in the problem. To this we need to add the extra

income available from work when the person lives longer.

However, it is not the extra earnings alone that must be added,

but that amount divided by E. That is, observed earnings is a

lower bound to the extra adjustment and is only an unbiased

estimate when E is very close to unity. Again, this adjustment

reflects imperfect substitution between quantity and quality of

life when consumption and leisure are not perfect substitutes

intertemporally.

4.3.3.5. Retirement

The model in section 4.2.3.4 assumed that the person worked

over his whole life, and would be relevant for a situation of

"early" death. However, for most people work patterns over the

life cycle follows a systematic course of full time work up to a

certain age followed by a full time retirement. The model above

may be extended to cover this case most easily be assuming that

the wage w is available up to some retirment age, say T*, at

which time w drops to zero and the person consumes full time

leisure. 'The the utility function must be written

u * integral from 0 to T* of u(cl(t),L(t))eeat dt

+ integral from T* to T of u(c2(t),l)eeat dt,

where cl denotes consumption during the years in which a person

,works and c2 denotes consumption when the person is retired and

leisure is fully consumed ( L - 1). The budget constraint is

conformably altered to

w + integral from 0 to T* of w(t)(l-L(t))ewrt dt

= integral from T* to T of cl(t)eert dt

+ integral from T* to T of c2(t)eSrt dt

and the optimal program chooses L(t), cl(t) and c2(t) to maximize

U subject to the budget constraint as before. Omitting details

and making the same simplifying assumptions as above yields an

expression for v of the form

V- c2 [(1-g)&]A',

4-42
which looks very much like the first problem considered here.

There are two minor differences. First, the relevant consumption

level is that applicable to retirement rather than to preretirement. Th,e second is that the adjustment factor--the

elasticity term R is calculated at the retirement utility level

of leisure where L - 1: a - c2 uc (c2,1)/u(c2,1). It is not at

all obvious whether or not ci falls short of or- exceeds the

corresponding elasticity calculated at the preretirement optimum

utility: this would depend on the precise form of preferences.

Nor is it entirely obvious, without more structure on

preferences, whether c2 exceeds or falls short of cl. This would

depend on the nature of complementarities and substitution

between consumption and leisure, about which little can be said

in general. However, the budget constraint does imply

c2 - [(W/A*) + w(l-L) - cl] / (A - A*)/A*,

where A* is the annuity formula for T* periods and A is the

formula for T periods. It is clearthatthe longer the period of

retirement, the smaller is c2 and the lower the value of v,

ceteris paribus. It is also clear that v is larger for people

with greater nonhuman and human wealth, because retirement

consumption will be larger in these cases.

4.3.4. --- ----- -- The Value Of Morbidity ----m--m

The ideas in the last two extensions provide a basis for

beginning to evaluate morbidity. Imagine the following

situation: The person is ill for exactly S periods, after which

time he becomes "whole." During the period of illness, utility

is G(clJIL while during the normal (well) period utility is

u(c2,L2) as before. Here the subscript 1 refers to these

variables in the well-state. For the demarcation of illness to

make any sense, we must have that G(c,L) < u(c,L) when both

functions are evaluated at the same arguments. Then illness

makes the person worse off. In addition, a person who is ill

cannot work on the same terms as one who is well. Represent this

by a drop in the wage: if the wage in state 2 is w, then the wage

in state 1 is aw, where a < 1. In addition, medical and other

expenses may be required if the person is ill. Denote these, as

a flow, by D.

The budget constraint for this problem is

(4-21) W + integral from 0 to S of aw(l-Ll (t))emrt dt

+ integral from S to T of w(l-L2(t))ewrt dt

- integral from 0 to S of (cl(t>+D)eert dt

+ integral from S to T of / c2(t)eert dt .

4-43
Of course it may turn out that the person chooses not to work in

state 1, in which case the first earnings expression in (4-21) is

zero. Again, maintaining seperability for analytical

convenience, lifetime utility is

(4-22) U - integral from 0 to S of G(cl(t),Ll(t))ematdt

+ integral from S to T of u(c2 (t),L2 (t))eeat dt.

If we assume that r - a and that w is independent of t, we again

find that the c's and L's are constant in the optimum program, so

that

(4-23) V - maxtG(cl,Ll)AS + U(C+~)(AT-AS)

+ m [W+(aw(l-Ll) - cl - D)A,

+ (~(142) - C~)(AT - +)I),

where At is the annunity formula for t periods. We are

interested in how much wealth a person would be prepared to pay

to reduce the period of illness by an increment dS. This again

is a marginal rate of substitution calculation comparable to the

definition of v. Hence define M as the corresponding value of

morbidity:

(4-24) M- (dW/dS) - Vs/Vw.

From (4-23) and the envelope theorem'it follows that

vS - (G - u)AS + 1~1 - 3’2 - (cl + D - c2)1A’ss

VW -m,

where yl - aw(l-Ll) and y2 - w(l-L2) are earnings in states 1 and

2 respectively. Applying the definition (4-24),

(4-25) M - ([u(c2,L2) - G(cl,Ll)l/m + (~2 - ~1) + cl+ D-c~))A's.

This expression shows that the value of morbidity

reduction is composed of three distinct parts. One part is the

difference in earnings between the two states, or “foregone

earnings" commonly found in practical work. To this must be

added the cost of medical care and related expenses (D), which is

also commonly incorporated in empirical measures. However, these

measures usually excluded two other components which are more

difficult to mea.sure. The first of these is the dollar value of

the utility loss of illness, reflected in the first bracketed

4-44
term in the expression for M- -division by the marginal utility of

wealth converts the utility difference to an equivalent dollar

magnitude. This term would be related to the concept of "pain

and suffering" associated with personal injury litigation. Its

magnitude obviously varies with the degree of debilitation, and

also with the extent to which the relative marginal utilities of

consumption and leisure are affected by the illness and the

extent to which "leisure" and consumption in the ill state are

complements or substitutes. Little can be said about this in

general, and it must be analyzed on a case-by-case basis. The.

third term is the difference in consumption between the two

states, and this is almost always ignored in empirical work. To

the extent that consumption in the ill-state falls short of

consumption in the well. state, that difference should be

subtracted from a willingness-to-pay measure. To the extent that

was true, the "pain and'suffering" term would be offset.

To understand this last adjustment a little better, write

the two components combined:

(u(cpL2> - G(clJl))/m - 9 + cl

- ([u(c~,L~) - m ~21 - [G(cl,Ll) - m cl])/m.

Now m equals the marginal utility of consumption in each state,

by the first order conditions of the maximum problem, and can be

thought of as the shadow price of consumption in each state.

Then each of the terms in square brackets above is total utility

in the state minus the utility cost of consumption in that state,

or a measure of "rent" in that state. It is the difference in

these rents between states that must be imputed to the valuation

of morbidity. It seems clear that the rent in the well-state

would exceed that in the ill-state, so foregone earnings and

medical bills would understate the true cost of morbidity. The

extent to which it would understate the truth, however, would

depend on the precise properties of preferences and how the

illness affects G(c,L).

4.3.5. Value Of Life Expectaqcyi Stochastic Model

4.3.5.1. Preliminaries

In this section we examine a stochastic decision problem in

which life expectancy is uncertain. While this changes some of

the details of analysis, the main thrust of the deterministic

model carries through with minor alternations.

Analysis of the stochastic case requires some attention to

the statistical description of lffe chances, and a brief review

of some actuarial concepts for describing probability

distributions over length of life. Let F(t) be the probability

of surviving until age t at most. Then 1 - F(t) is the survivor

function, the probability of surviving to at least age t, or

more. Define f(t) - dF(t)/dt - -d(l-F(t))/dt as the density

4-45
function of length of life; the probability of surviving to age t

exactly. The age specific death rate or hazard rate, is the

probability of death at age t given that one has survived up to

that age. It is a conditional probability: Denoting the hazard

or death rate at age t by h(t), it is h(t) - f(t)/(l-F(t)), or

from the relationship above:

(4-26) dlog(l-F(t))/dt - -h(t) .

Integrating (4-26) and using the boundary condition F(0) - 0 (we

are orily looking at survivors at birth), yields the fundamental

relationship between the hazard rate and the survival rate

(4-27) (1 - F(t)) - exp I- integral from 0 to t of h(z)dz),

where exp means the exponential 2.

The importance of equivalence (4-27) lies in its relation

to the problem at hand. The hazard h(t) is naturally associated

with the undertaking of risks to life and is the natural

primitive for studying the valuation of life-threatening actions.

However, the survivor function is the natural primitive for

studying expected utility and expected wealth. Equation (4-27)

shows precisely how the two are related.

At some cost of realism, great simplicity in understanding

the nature of the problem is achieved by studying some special

cases. In particular, assume h(t) - h, so the death rate is

constant at all ages (the case of constant hazard). Then it

follows directly from (4-27) that

(4-28) F(t).- 1 - emht,

1 - F(t) - eeht,

f(t) - heSht.

The probability density of length of life f(t) is exponential in

this case. Furthermore, life expectancy itself, call it E(t) is

simply related to the death rate as

E(t) - integral from 0 to infinity of tf(t)dt

- integral from 0 to infinity of hte.'ht - l/h.

- l/h.

Note that life expectancy is independent of current age in this

case. No matter howlon,g onehas lived there is always l/hyears

left! The system has no memory. This is of course highly

unrealistic, but the convenience of analysis more than makes up

4-46
for this defect. The more general case in analyzed by Arthur, to

which the reader to referred for details.

Suppose now that the hazard rate is a step function. That

is, it is h(t) - hl for t < T, but then jumps to a higher level

beyond some age T: h(t) - h2 for t 2 T. Then application of (4-

27) yields

(4-29) 1 - F(t) - exp(-h,t) for t < T

- exp ([(h2-hl)Tl-h2TI.

Now the survival function is exponentially declining at rate hl

for t < T, but its slope shows a point of discountinuity at T.

It declines at a larger rate for t > T than for t < T. Here we

would find that life expectancy is decreasing with age, so long

as t < T.

Any pattern of h(t) could be approximated in this way as a

sequence of step functions. Since the mechanics of this are

straightforward, they will be omitted here. Instead we turn to

the choice problem.

4.3.5.2. Optimal Choices

The fundamental method.follows the deterministic approach

above. Let us begin by ignoring work decisions and describe

tastes by an intertemporally separable utility function in the

sequence of consumption c(t). If a person lives exactly t years

then his utility is postulated to be

u(t) - integral from 0 to infinity u(C(z) east dz,

which follows precisely the form of the deterministic model.

However, in an uncertain world a person lives t years only with

probability f(t). Therefore apply the expected utility theorem

to U(t). A person's expected lifetime utility is

(4-30) EU - integral from 0 to infinity of U(t)f(t)dt

- integral from 0 to infinity of u(c(z))e'az dzdt

- integral from 0 to infinity of u(c(t)jewat

- integral from 0 to infinity of f(z)dzt

- integral from 0 to infinity of (l-F(t))u(c(t))e-a' dt,

where the second to last equality follows by a change in the

4-47
order of integration. We see that the relevant utility

expression incorporates the survival rate l-F(t) and that is why

it is a fundamental concept for the problem. Substituting from

above, preferences follow

(4-31) EU - integral from 0 to infinity of

u(c(t)exp(- at - integral from 0 to T h(z)dt) 1,

so the hazard rate works exactly like a discount rate. To make

this even more transparent, suppose h(t)

- integral - h-t:+~yJ;t- T$y from 0 to infinity of uc(t))e

"effective" discount rate is a + h. The force of mo'rtality h

makes a person act more "impatiently" and to weigh the future

less heavily.

Budget constraints in problems such as this create a host

of conceptual difficulties revolving around the question of how

to cope with the fact that the person might die in debt. These

issues have been thoroughly explored by Yaari and there is little

to add to that discussion here. Hence we adopt a natural

solution in which a person is not allowed to die in debt and can

borrow and lend on a perfect capital market at rate of interest

r. The constraint of budget balance at each possible point in

the life cycle is enforced by an actuarial insurance-debt system.

It amounts to the following. Whenever a person makes a loan he

is compelled to at the same time take out an insurance policy of

equivalent value such that if he dies at any time during the

course of the loan, the insurance indemnity is sufficient to pay

off the remaining balance. As is well known, this is basically

an actuarial annunity system in which a cohort of identical

individuals turn over their wealth to the insurance-finance

company and contract for their optimal consumption bundle c(t)

which persists as long as and for however long they live. Those

who di,e early effectively subsidize the fund ex post, since their

assets have exceeded their consumption claims. These subsidies

are used to pay the consumption claims of those individuals who

survive longer than average. We can represent this in a simple

manner as follows.

If a person lives for exactly t periods and contracts for

c(z), the present discounted value of his claims is integral

from 0 to t of c(z)e-rzdz. The probability of surviving for

exactly t periods is f(t), so the expected discounted value of

the claim c(z) is equated to the person's initial wealth W under

an actuarial, no-load system. The budget constraint is

(4-32) w * integral from 0 to infinity of f(t) times

integral from 0 to t of c(z)eerz dzdt

- integral from 0 to t of (1-F(t))c(t)eert dt,

4-48
where the second equality follows from the same change in order

of integration as above. Again, it follows that the influence of

the survival term (l-F(t)) in this expression is to increase the

effective discount rate. It is interesting to note that even if

r and a are zero, there is a well defined optimization problem,

something that isn't true in a deterministic problem with an

infinite horizon (because the objective function becomes

unbounded in that case).

The economic problem is to choose c(t) to maximize (4-30)

subject to the constraint in (4-32). Associating a multiplier m

with the constraint and noting that the term in (l-F(t)) is

common to both the objective function and the constraint and

therefore factors out of the optimality conditions, first order

conditions for the problem duplicate those of the deterministic

problem. We have

(4-33) ut(c(t))eSat - m eert for all. t.

The interpretation is straightforward. The life insurance

features of the annuity arrangement allow the person to do

whatever he would have done in the deterministic problem and to

insure the death risk over consumption streams by the law of

large numbers applied to his cohort. In particular, assume r -

a. Then (4-33) implies c(t) - c, a constant, and the person

contracts for a constant-consumption stream up to the point of

his death and no matter how long he lives. From the budget

constraint we have that c - W/integral

F(t))e'lct

from 0 to infinity of (ldt, so the amount of consumption available under this

scheme depends on the person's wealth, the rate of interest, and

the precise age-pattern of survival probabilities.

4.3.5.3. Valuation Formulas

Consider the case where h(t) - h. Then (4-32) implies

w- c/(r+h), just the formula for the value of a perpetuity of c

at discount rate (r+h). In this case (4-30) becomes EU - EU -

u(c>/(r+W, or instantaneous utility discounted at rate r+h

forever. Therefore

(4-34) V - EU - u(W(r+h))/r+h .

This looks very similar to the deterministic problem. Define v'

as the value of changing the probabtlity of death, h. Then

(4-35) v' - - (partial of V w.r.t h)

/.partial of V w.r.t. W - dW/'dh.

4-49
v' is amount of money the person would have to be paid to

increase the death rate confronting him by dh. From (4-34)

VW -

u’(c),

'h -

[(r+h)Wu"(c) - u(c)]/(r+h)2 .

Therefore, in the constant hazard case with r - a,

(4-36) V' - [u(c>/u'(c> - (r+h)Wl/(r+h) 2

- W/(r+h))(l-El/E,

where again E is the elasticity of u(c) with respect to c, and

O<ECl. Comparing this with equation (4-11) of the

deterministic model, we see that the term in h serves as the

correction factor for finite life, rather than the annuity term A

in (11). Otherwise, the expressions are identical and have

identical implications. v is increasing in W and decreasing in E

for the sa.me reasons as were spelled out above. In particular,

the role of quantity versus quality of life substitution as

reflected in E remains exactly the same as before. It is also

true that v' is decreasing in r, and is also decreasing in h.

We can find an equivalent expression in terms of the

expectation of life, t7 since t-0 l/h when the hazard is

constant. Then dh - - dt/t2 so

dW/dt - [(W)/?(rt+l)] [(l-E)/E].

A person with a longer life expectancy is willing to pay less to

extend it.

4.3.5.4. Valuations of Workers

Let us now extend the stochastic model to include choice

of work and earnings as well as consumption. Then, similarly to

the deterministic models, the one-period utility function must be

written u(c,L), where L is leisure. This function replaces u(c)

in the definition of expected utility in (4-30). A worker has a

source of earned income as,well as endowed wealth. If he can

earn w(t) per unit of time, earned income is w(t)(l-L(t)), which

when discounted to present value and including allowances for

mortalit

F(t))eer

ty becomes infinity of 0 to infinity of w(t)(l-L(t))(ldt and which must be added to the term in W on the left

hand side of the budget constratnt in (4-32). The first order

conditions for choice of c(t) and L(t) duplicate equation (4-14)

in the deterministic model. With r - a and w(t) - w, the value

function becomes

4-50
(4-39) V - max ([u(c,L) + m[w(l-L) - cl]

c,L

integral from 0 to infinity of (1-F(t))emrt dt + m W),

since c(t) - c and L(t) - L under these circumstances.

Assume h(t) - h. Then the integral term in (4-39) is

merely l/(r+h) and maximum expected utility is the perpetuity

value of u(c,L) held at its optimal values of c and L, at

discount rate r+h. In this case we find

(4-40) 'Vh / vW - [~(l-E)/E + w(l-L)]/(r+h)2

as the capital sum the person would be willing to give up to

reduce the death rate by dh. This expression is similar to (4-

36) with the addition of the earned income term; since the

opportunity to work has value.

Expression (4-40) does not closely relate to empirical

work in this area. Much of the empirical work on the value of

life uses labor market data and estimates the risk premium

necessary to induce a worker to undertake a risky job. For the

problem at hand, the relevant risk premium is nothing more than -

vh / v,~ which is, in this case

(4-41) -vh & - [c(l-E)/E + w(l-L) - c]/(l-L)(r+h).

From this expression we may infer something about the

intertemporal substitution parameter E.

As an example, consider the study of Thaler and Rosen

(Ippolito and Ippolito produce a similar estimate from much

different data.) Thaler and Rosen estimate - Vh /VW in terms of

the weekly wage as $3,520 in 1968 dollars. In their sample

average weeks worked are approximately 50 and the average worker

earned about $6,600. Since this is a low income population, the

bulk of consumption expenditure must have come from earnings, so

ignore savings and assume c - w(l-L) - $6,600. Substituting this

and (1-L) - 50 into (4-41) and rearranging, we have

E- (6,600/176,000) / (r+h) .

Hence the estimate of E depends on assumed values of r and h. In

the Thaler and Rosen sample, h is about 2.5 per 1,000, decomposed

into 1.5 per 1,000 normal life table experience plus an

additional 1.0 per 1,000 excess risk from working conditions

among people in hazardous jobs. Hence any realistic interest

rate swamps the,effect of h. For this population r - 10% would

4-51
appear to be a plausible lower bound. If so than E - .39. If r

- 15% the estimate of E drops,to .26. Presumably these are upper

bound estimates among the population at large, because most

workers are not found in risky jobs through selection: ceteris

paribus their value of E must be no greater and most probably

lower than indicated if they find it advantageous to work on

safer jobs at lower rates of pay. Hence from this evidence, we

get an upper bound of E in the .25-.40 range.

Now return'to equation (4-36) and convert it into logs:

(4-42) dlog W/dlog h - W(r+W(l-EWE.

Substituting the values above yields as estimate for dlog W/dlog

h in the range .04 to .05. That is, the people in this sample

would have been willing to give up one-half percent of their

wealth for a 10 percent reduction in the death rate. Presumably

the equivalent sum for the average person in the population is

larger than this because of the selection effect mentioned above.

Notice however, that the term inh/(r+h) is even smaller for such

persons (because their values of h are smaller) and this dampens

any effect of a smaller value of E. Notice also, as a rough and

ready approximation, the term in h would be much larger for older

persons, so they would be willing to pay a much larger fraction

of their wealth.

Now consider an experiment related to the specification in

(4-29). This is i.nteresting because it is closely related to

long term hazards with a latency period of length T. Thus, for

example, a person with a "normal" risk exposure hl may undertake

some action now which has no effect on death probabilities until

periods later, at which time the death rate jumps to h2. Exposure

to chemical substances may take this form. Again maintaining

r - a for simplicity, from (4-29) and (4-30) and (4-32) we have

(4-37) v - m.ax (u(c) integral from infinity of (1-F(t))ewrt dt

+ m[W - c / (1-F(t))e'= dtl

- max [u(c) - mc][(l/(r + hl))(l-exp-(r+hl)T)

(.Wr+hp)) (exp (-(r+hl)T),

from which it follows by the now familiar manipulations

(-vh >/VW - [c((l-E)/E)exp (-(r+hl)T)l/ [(r+h2>21

2

4-52
(4-38) vT/vW - [CW-EWUexp( -(r+hl)W WyhlM*r+h2)1

VT& -

2

(h2 - hl> (I: + h2) .

The first expression in (4-38) shows how much the person is

willing to pay to reduce the later hazard. This again depends on

the intertemporal substitution parameter E and the level of

consumption, as before. It also depends on how far away the

hazard is from the present- -the further away it is the smaller

the willingness to pay to reduce it-- and on the rate of interest.

The second expression in (4-38) shows how much the person would

be willing to pay to push the increased hazard a little bit

further away from now. This also depends on c and E, and is

decreasing in T and increasing in the difference h2 - hl. The

third expression, written for completeness, is the marginal rate

of substitution betwe.en the level of the new hazard and the time

of its occurrence.

The most important thing to notice about these valuations

is that they are time or age dependent. The willingness to accept

risks of this form is largest for younger people and the willingness to pay to avoid them is largest for older individuals (when

the person is old enough to have passed beyond t- T, the formulas

revert to the form of (4-36)). This is basically due to the force

of discounting, which includes not only the interest rate but the

hazard rate itself. Furthermore, these expressions make no allowance for pain and suffering and the manner of death, but

including such factors would have the effect of increasing their

absolute va.lues without affecting their intertemporal patterns.

Changing valuations over the lifecycle raises some tricky

issues for risks that are irreversible. Thus suppose the market

provides an opportunity for undertaking a risk exposure of the

type above which increases wealth or utility in other ways. Then

we would again find some critical age, beyond which a person

would not undertake the risk, but before which he would. Suppose

this action affects h2 permanently, so there is no going back on

the decision once it has been undertaken at the early age, and

the person is stuck inapermanentlyhigh risk class at some time

in the future. Then as the person ages, he would perhaps have ex

post regret about his earlier actions. However, there appear to

be no inconsistencies (in the sense of intertemporal

irrationalities) in this type of behavior, because, by

hypothesis, all these affects are foreseen in the first instance.

The point applies to any type of gambling behavior.

appear to be very favorable ex ante,

A gamble may

but ex post realizations

often lead to regret, about which nothing can be done and which

is already factored into the initial decision to undertake it.

The same is true in this case when all the information is on the

table.

4-53
Nonetheless, in evaluating such hazards for the purposes of

social policy and cost-benefit analysis, one would certainly like

to take account of different valuations by people of different

ages, since it is the sum of all valuations whichmatter. That a

person might have a different valuation at different points of

time and age is properly accounted for in these sums, and no

allowance need be made for the fact that the person will change

his valuation at some future time. This conclusion is of course

conditioned on the manner in which the problem has been set up,

which assumes perfect information and a perfect capital market.

If capital markets were imperfect and the insurance charge did

not fully reflect the increased future risk for any given person,

there would be a moral hazard effect and the social value of risk

would exceed the private value, because individuals would have a

tendency to shift risks excessively to the insurance fund. Too

many risks would be undertaken. And of course similar statements

apply if assessments of future hazards are biased (in either

direction) by the persons undertaking them.

4.3.6. ----- -------- --- Interpretation and ARRlications -------e4.3.6.1. Major Results From The Life Cycle Model

Section 4.3 has been motivated by the question "How much

of the economy's wealth should be spent on safety, health and

longevity concerns? " The answer depends on the way individuals

(or households) appraise their own life situations. and how they

make decisions they judge to be optimal in light of those situations. This section has provided a framework that identifies the

underlying decision variables and guides the valuation of policy

decisions designed to improve people's life prospects.

A life cycle frameworkhas been seen to be appropriate, and

the intimate relation between quality of life and longevity, or

quantity of life, has emerged in the developnent of the model.

Valuations of increases in life expectancy, in reductions in

periods of illness, and in reductions in risk of death have been

explored. Labor force participation and the value of increased

longevity are taken into account. Results derived from the model

include widely recognized effects such as foregone earnings and

medical expenditures, and also more frequently overlooked effects

such as the utility of consumption and leisure and differences in

the utility of consumption and leisure and differences in consumption between various states of wellness.

.

Several parameters play key roles throughout the

development of the model, and others are important to the

development of special parts of it. Perhaps of greatest interest

among the former is the elasticity of lifetime consumption. This

relates to intertemporal substitution and reflects the close

relationship between the quality and quantity of life. Other

parameters in this category are the rates of interest and time

4-54
preference, the level of wealth and the person's.stage in the

life cycle.. Of interest in the other category of parameters,

pertaining to special parts of the model, is a "consumption

correction factor," which takes into account the fact that

people's capacities change over their life cycles. This is

particularly important, in empirical work because it pertains to

people's endowments, which are important in explaining their

valuations. Another special parameter is the hazard function

parameter, which measures an individual's probability of dying at

any given age. This is another aspect of endowment. It is

central to the treatment of the effects of uncertainty on choice

and is of particular interest in valuing threats to health that

involve latency, which is represented by a discrete increase in

the hazard of death after a number of years elapse.

One of the results is that younger prople are willing to

pay less to extend their lives than older people. The primary

reason is that the return to a younger person is deferred so far

into the. future that its present value has been largely wiped out

by discounting. It is quite possible that the person when older

will regret actions taken earlier in life because extended longevity has become more important in the meantime. Nevertheless

the now regreted actions must be regarded as rational when preferences are time separable. A similar result is obtained in the

analysis of risks to health which change the probability of death

after an intervening period of latency. Once again the farther

into the future the increased risk is deferred the less a person

is willing to pay now for its reduction.

Maureen Cropper has added a comment regarding .the effects

of age on willingness to pay for risk reduction. One must

distingusih between the age of the respondent at the time the

question is asked and the age at which the risk occurs.

To illustrate, consider two men, one 18 and the other 45,

who have identical preferences and lifetime earnings streams. The

distribution of date of death conditional on reaching age

t (t-18 ,...) is the same for both persons. The only difference

between them is that the 45-year-old has followed for 27 years

the consumption path which the 18-year-old will eventually

follow. There are three willingness to pay to compare:

(1) The amount the 18-year-old will give up today to avoid

a marginal increase in his conditional probability of

death at age 18.

(2) The amount the 18-year-old will give up today to avoid

a marginal increase in his conditional probability of

death at age 45.

(3) The amount the 45-year-old will give up today to avoid

a marginal increase in his conditional probability of

death at age 45.

With perfect annuities markets and a rate of time preference

4-55
equal to the market rate of interest, (1) > (2) and (1) > (3).

The fact that (1) > (2) means that a reduction in risk of death

27 years hence is less valuable than a reduction in current risk

of death. This point is made in this section and has obvious

relevance for valuing risks with long latency periods.

The fact that (1) > (3), i.e., that the 18-year-old will

pay more to reducehis current risk of deaththanthe --e--w- 45-year-old

(at least according to the theoretical model) needs to be made

clearly. One can reverse this inequality by assuming imperfect

capital markets, which constrain the individual to consume no

more than his income when he is young, and a hump-shaped earnings

stream; however, under the assumptions of this section, (1) >

(3).

V. Kerry Smith comments "on the possibility of considering

a'changing framework,' that is, a framework which allowed the

individual to change his or her plans over time. The current

framework seems to assume there is one optimal plan which is in

not allowed to change with respect to changes in the parameters of

the individual's situation. The actual model is probably much

more like a situation in which the individual makes a plan and

then takes one step along that plan, updates, and utilizes a new

plan."

The elasticity of the life cycle consumption function,

which is closely'related to the intertemporal substitution of

consumption, has a strong bearing on both the value of extended

life and the value of reducing hazards that occur later in life.

The greater a person's ability to substitute present consumption

for future consumption the less interest that person has in

providing for the future. The value of the intertemporal

substitution parameter is a key importance in understanding

tradeoffs between the quantity and quality of life in this

framework.

Elasticity of consumption is estimated to have an upper

bound of 0.25 to 0.40. This rather low elasticity implies that

quantity and quality of life are poor substiutes for each other,

which in turn varies the value of extra years of life.

Allowing for reduced capacity for consumption during later

years of life requires a consumption correction factor. Tha

implication of diminishing capacity is that unless real

consumption can be maintained the value of longevity is reduced.

This is an important implication because people's consumptioncapacity prospects and expectations can be approximated

empirically.

The fact that people value extensions of life the oldor

they get has implications for labor market behavior. Supposing

that opportunities to extend life a given amount have a constant

cost independent of age, then there is a threshold age belov

which people are willing to accept shortened life expectancy fn

exchange for increased money return, whereas people above the

4-56
threshold will not accept the trade.

Application of the framework to some available sample

evidence yields the result that people would give up one-half

percent of their wealth for a ten percent reduction in the death

rate. The equivalent amount for an average person in the

population would probably be greater.

4.3.6.2. Life Experiences and the Willingness to Pay to Avoid

Serious Illness

The life cycle approach to serious illness was applied in

later parts of this study in experimental focus group sessions.

It was hypothesized and found to be the case that age makes a

great difference in the way a person perceives the consequences

of risks to health, either with certainty 'or varying degrees of

probability. Focus group explorations of hypothetical life path

experiences showed graphically that people in their twenties have

little or no interest in their health propsects for their seventies or even their fifties. A different picture emerges from the

responses of people in their fifties or sixties. The theoretical

contributions of this section provide the rationale for this

behavior and point the way to empirical solutions to the problems

raised by these focus group encqunters.

The contingent valuation questions to be considered in

Section 4.5, which grew out of the framework here and learning

from focus group experience, emphasize comparisons between life

paths. In some cases individuals are required to rank alternative paths which embody different tradeoffs between suffering and

life expectancy. Different kinds and durations of suffering are

considered. Finally, uncertainty is introduced and valuations of

risks are sought within streams of experience that embody both

sickness and death.

Perfect health is generally not the alternative to

symptoms, diseases or health risks that are reduced by successful

public policy. The value of improved prospects must be weighed

against alternatives that carry risks of their own. Thus a

person is generally trading one stream of illnesses for another,

less undesirable one. It is this change, rather than a

transition to perfect health, that constitutes the benefit of the

public policy.

The life path approach constitutes in a number of ways a

departure from conventional methods of valuing health benefits.

The distinguishing feature of the approach is its treatment of

the whole stream of experience as the focus of analysis. Good

health, illness and death are viewed as inseparable in analysis

as in life. As in other areas of life people make choices for

more or less health and longevity. To an important degree people

choose greater or lesser amounts of health and longevity depending on their ,values for these goods relative to their other

4-57
wants and needs. The life path approach is an appropriate means

of obtaining health values because it is based on willingness to

pay in view of the totality of substitutions that people make

over time in resonse to changes in health risks. Methods that

attempt to value health or longevity as one period events, and

especially methods that disregard age, run the danger of missing

important determinants of health values.

4.3.7. References a---------

1.

2.

3.

4.

5.

6.

7.

8.

9.

10.

11.

Aday, L.A..-, and R.L. Eichhorn; m-m The Utilization of Health ----------- -- ------

--------A Services- ------- --- ---------- Indices and Correlates, DHEW Publication No.

(HSM) 73-3003; Washington: U.S. Government Printing

Office, 1972.

Arthur, W.B., The Economics of Risks to Life. American

Economic Review, 1981.

Brook, R.H., J.E. Ware, and A. Davies-Avery; "Overview of

Adult Health Status Measures Fielded in Rand's

Health Insurance Study;" --e--e- Medical Core 17 (Supp): 1-131, ----

1979.

Chestnut; L.C. and D.M. Violette; --------- -- Estimates of Willingness -_---- --_-

to Pay for Pollution-Induced Changes in Morbidity: ------w------e--- ---- -- -- -------- - h

?Tit?&ue?gr e-w-- -- --a Benefit-Cost Analysis of Pollution Regulation ------------ ---- --- -- --------- -- -------'

U.S.E.P.A., Boulder, Colorado: Energy and Resource

Consultants, Inc., 1984.

Conley, B.C.; The Value of Human Life in the Demand for

Safety. American Economic Review, 1976.

Cropper,M.L.; Health, Investment in Health and Occupational

Choice. Journal of Political Economy, 1977.

Ehrlich, I. and H. Chuma. The Demand for Life: An Economic

Analysis. University of Buffalo, 1984

Freeburg, L.C., J.R. Lave, L.B. Lave, and S. Leinhardt;

------ ------A Health Status ---m--e Medical -_-- Care Utilization -,,-------,A --- and Outcome: an -e----e- --

Annotated Bibliography of Empirical Studies, DHEW -----a--- e--e-- --

Publication No. (PHS) 80-326?; WasKcrg?%:: tTS.-<overnrnent

Printing Office, 1979.

Fuchs, V.R., ed.; -------- Economic Aspects ---- of Health; ------ Chicago:

University of Chicago Press fc;Nationai Bureau of Economic

Research, 1982.

-

Ippolito, P.M. and R.A. Ippolito; Measuring the Value of

Life Saving from Consumer Reactions to New Information.

Journal of Public Economics, 1984.

Jones-Lee, M.W.; The Value of Life: An Economic Analysis.

4-58
London, 1976.

.

12. Jones-Lee, M.W.; The Value of Life and Safety: Proceedings

ofaconference Held by the Geneva Association, NorthHolland, Amsterdam, 1982.

13. Mishan, E.J.; Evaluation of Life and Limb: A Theoretical

Approach. Journal of Political Economy, 1971.

14. Rosen, S.; Valuing Health Risk. American Economic Review

(Proceedings), 1981.

15. Schelling, T.C.; The Life You Save May'be Your Own. In:

S.B. Chase (ed), Problems in Public Expenditure Analysis.

Brookings, 1968.

16. Stewart, A.L., J.E. Ware, and R.H. Brooks; Advances in the

Measurement of Functional Status: Construction of Aggregate

Indexes"; ------- Medical Core --we 19:473-488, 1981.

17. Thaler, R. and S. Rosen. The Value of Saving a Life:

. Evidence from the Labor Market. In: N.E. Terleckyj (ed),

Household Production and Consumption, NBER, New York, 1975.

18. Usher, D.; An Imputation to the Measure of Economic Growth

for Changes in Life Expectancy. In: M. Moss (ed), The

Measurement of Economic and Social Performance. NBER, New

York, 1973.

19. Ware, J.E. "Scales for Measuring General Health

Perceptions;" ------ Health -------- Services -------- Research 11:396-415, 1976.

20. Ware, J.D., A . Davies-Avery, and R.H. Brook;

Conceptualization and Measurement of Health Status for

Adults in the Health Insurance Study: Vol. VI, Analyses of ---- --- --

-m--------e RelationshiRq ---- among ------ Health ------ Status Measures, -------- R-1987/b-HEW;

Santa Monica, CA: The Rand Corporation, 1980.

21. Ware, J.E.. S.A. Johnson, and A. Davies-Avery;

----- ----------- --- ----------- -- Conce.Rtualization and Measurement of Health Status --a--- ---a-- --- for

Adults in the Health Insurance Study: Volume ------ -- --- ------ --------- ---- - w--w-- 1, General -------

------ ----- Health Perceptions --e-w ' R-1987/5-HEW; Santa Monica, CA: The Rand

Corporation, 1978.

22. Yaari, M.E.; Uncertain Lifetime, Life Insurance and the

Theory of the Consumer. ------ -- -------- Review of Economic Studies, 1965. --e---w

4-59
4.4. MODELLING OF CHOICES WITH UNCERTAIN PREFERENCES

4.4.1. ---- Backgrond w-wPeople have many occasions in their lives to take actions to

avoid or reduce risks. In order not to spend all their resources

on risk avoidance, they implicitly consider what the value of

risk reduction is, and they try with more or less success to

carry risk avoidance only to a point justified by the costs.

This point is often unconscious or subconscious. It is carried

out imperfectly and is beset by lack of information due to the

fact that, while the events to be avoided involve very great

values, the probabilities are small and outside the realm of

everyday experience. Knowledge about risks is important. This

is particularly the case for environmental risks. Thus people

tend not to know their own minds on the subject of risks. Section

4.4 addresses the problem of making choices about risky

alternatives in view of knowledge imperfections. Section 4.4.2

introduces the difficulties for benefit-cost analysis caused by

risk, and the approach taken to solve them. Section 4.4.3

discusses relevant issues.in the theory of expected utility.

Section 4.4.4. introduces the concept of uncertain preferences.

Section 4.4.5 critiques the literature on risk from psychology

and relates the concept of uncertain preferences to the economic

literature of behavior towards risk. Following introductory

comments in section 4.4.6, section 4.4.7 and 4.4.8 produce a

series of theorems that indicate how people process information

and make choices about low probability events on the basis of the

results. Section 4.4.9 compares the effects of using comparison

questions versus. realing questions. Section 4.4.10 introduces

the realistic assumption that respondents' answers to certain

questions are interrelated, and examines its implications.

Sections 4.4.11 through 4.4.13 discuss the effects of limited

memory and bias in the answering of questions about risky events.

Section 4.4.14 draws implications of the theorems for the study

of serious illness, giving particular attention to contingent

valuation.

4.4.2. AREroach -Be-- Taken in This Section ----m -- ---- -------

A major benefit of air pollution regulations is the

reduction in health risks. If the govenrment wishes responsibly

to decide on the correct level of standards to impose, it must

attempt to determine what value individuals place on health risk

reduction. Ultimately there are only two ways to gain this

information. One is to observe market behavior and, through the

logic of revealed preference, to make inferences about

individua,ls' tastes. The other 1s to ask individuals directly

4-60
about their preferences. In the case of most public goods,

including air quality, there are few markets in which individuals

can reveal their preferences--indeed, this scarcity of markets is

the reason government must be concerned with the problem in the

first place. Thus it appears that surveys and interviews are

likely to be necessary in any attempt to assess the public's

demand for reduction in health risks.

Researchers have, however, run into serious difficulties

when they have attempted to interpret individuals' responses to

questions about their preferences in risky situations. Many

economists are suspicious of survey responses about willingness

to pay, feeling that they are subject to strategic manipulation

by the respondents. In the case of survey data on risk

tolerance, there are much more immediate problems: Answers

elicited appear to be at odds with the standard economic theories

of risk aversion. Worse, they appear to be inconsistent with the

fundamental assumptions of rational decision making.

Therefore, to be able to use survey data to establish the

value of the benefits from risk reduction, we need a framework

that will enable us to interpret that data consistently in a

cost-benefit analysis. Section 4.4 will attempt to provide the

conceptual basis for such a framework. The framework we propose

is one in which it is costly for individuals to determine their

own preferences and therefore unlikely that their responses to

survey questions will reflect their true choices with absolute

accuracy. We will demonstrate how cost-benefit analysis can be

interpreted in such an environment and briefly indicate some

implications for the handling of surveys of individuals' risk

tolerance.

This approach is consistent with much recent work in

cognitive psychology, and can in fact be understood as a economic

reinterpretatidn of some of that field's analysis. It differs,

however, from the approach taken by much recent work in economic

theory. We will begin therefore by outlining the recent

theoretical alternatives to expected utility, the reasons why

they have been advocated, and the reasons why we feel these

approaches are not adequate to handle the problems inherent in

the use of surveys. Then we analyze the conceptual problems with

cost-benefit analysis when individuals are uncertain about their

own preferences, and the limitations of and uses of surveys in

those circumstances, Next we briefly review psychological models

of decision making of relevance to our problem. Finally, we

develop a model of uncertain preferences which translates the

psych.ological models into a cost-benefit framework. We use the

structure briefly to examine the methods by which surveys may

most effectively be used to gather information about the true

underlying preferences.

4-61
4.4.3. -- ----- ------ ----- --- --- Expected Utility Theory and Its Critics -------

For more than two decades expected utility theory has been

the dominant paradigm in economics for modeling individual

decision making under uncertainty. The main appeal of the

formulation has been theoretical; the axioms from which the

expected utility theorem is derived are simple, elegant, and for

the most part intuitively unobjectionable. The framework has

proved to be a solid foundation on which to develop both

macroeconomic and microeconomic theories, and to be a handy and

reliable maintained hypothesis in empirical work examining

markets in which uncertainty was a consideration.

While the theory has been dominant, it has not been without

objections and challenges, both on theoretical and empirical

grounds. The theoretical objections have centered on the socalled independence axiom. .The independence axiom, as illustrated in figure 4-4, says that lottery A is preferred to

lottery B if and only if a compound lottery in which A is the

prize with probability p and C is the prize with probability (lp) is preferred to a lottery in which B is the prize with probability p and C is the prize with probability (l-p), for all A, B,

C and p. Although this assumption seems a priori reasonable, it

is not as fundamental as the other axioms upon which expected

utility theory is based. The main objections to it have arisen

from empirical results in which individuals' stated preferences

appear to violate this axiom. Among the earliest examples of

this violation are those by Allais (1953).

A simple version of the phenomenon noted by AllaLs can be

described as follows.. In Figure 4-5 virtually all individuals of

moderate income prefer $10,000 with certainty (call this outcome

A) to a 50 percent chance at $30,000 (and a 50 percent chance of

receiving nothing. Call this lottery 8). On the other hand, as

illustrated in Figure 4-6, many individuals prefer a .OOl percent chance at $30,000 (call this X) to a .002 percent chance at

$10,000, (call this Y). Holding to both of these announced

preferences violates expected utility theory. To show this it is

only necessary to realize the the distribution of outcomes in

lottery X is equivalent to the distribution in a compound lottery

where at the first stage there is a .002 percent chance of winning, where the prize is a ticket to lottery B, while lottery Y

is a compound lottery in which there is a .002 percent chance of

winning the prize, which is a ticket to A.

Allais cited the independence axiom as the weak link in the

chain and called for its abondonment. Striking as examples of

this form were, they had little effect on-the mainstream of

economics, because Allais built no coherent theoretical structure

to set as a rival to expected utility theory. The first

completely developed analysis which dropped the independence

axiom is by Machine (1982), who also surveys the empirical

4-62
Figure 4-4. INDEPENDENCE AXIOM

4-63
Figure 4-5. ALLAIS PARADOX (A)

4-64
Figure 4-6. ALLAIS PARADOX (B)
objections to expected utility and indicates which of them his

extended theory can address.

Machina analyses the extension of expected utility theory

results when the independence axiom is replaced with the lessrestrictive assumption that preferences are smooth in changes in

gambles. He demonstrates that expected utility theory still

holds as a local approximation describing individuals' tastes for

relatively small changes in gambles around a (possibly random)

initial wealth level. Any properties which we wished to

attribute to expected utility functions, for example declining

risk aversion, or regions of relative risk loving, can now be

attributed to the so-called "local utility functions" at various

initial wealth levels. This is valuable for it permits us to

rationalize not only the Allais paradox, but also the observation

by Markowitz (1952), that individuals continue to buy both

insurance and lottery tickets as their wealth changes. Expected

utility theory can rationalize purchases of each by postulating

regions of risk aversion at levels of wealth below the initial

wealth, and regions of risklovingat levels ofwealthabove the

initial wealth. However, as the individual's wealth changes, and

he moves out of the initial boundary level between these two

regions, one sort of behavior or the other should be abandoned

according to the simple theory, and this does not appear to

happen. Machina resolves the problem by appeal to variations in

the local utility.function as the individual's wealth changes.

A similar type of analysis can rationalize the Allais

paradoxes: the local utility function is again not independent

of the entire set of outcomes available to the individual at the

time the decision is made. Thus there is nothing unexpected in

the fact that the existence of a chance at C affecting the

preferences for A versus B.

However, as Machina himself notes, there are several

observations in the experimental work on risk preferences that

cannot be squared with expected utility theory even when extended

in the Machina manner. Most of these are violations, not of the

independence axiom, but of the assumption that preferences are

dependent only on the distribution of outcomes that the lottery

yields, not the form in which the lotteries are presented. In

the language of psychology, stated preferences appear to depend

on the context in which the alternatives are "framed."

A striking example of this phenomenon appears in the work of

Kahneman and Tversky (1979). They build examples in which

preferences are altered when initial wealth is increased by a

fixed amount, and the outcome of the gambles offered is decreased

by the same amount in all realizations. Note therefore that the

assumption that is being violated is an extremely basic one.

namely, that preferences depend only on the final distribution of

outcomes. Another, equally basic situation of inconsistency of

preferences is described in the work by Grether and Plott (1979).

who trace the evidence of their particular "preference reversal

4-66
phenomenon" through several experimenters' works. This

phenomenon is the fact that individuals, when asked to state a

certainty equivalent for a 'gamble, will often choose a value

which is greater than the dollar value they will in fact choose

in preference to that same lottery. That is, given a lottery A,

an individual will claim that he is indifferent between A and

some dollar payoff D, and then in fact if offered a choice

between A and some lower payoff L, choose L. This observation

apparently violates no less an assumption than the transitivity

of preferences; no extension of "expected utility" theory can

adqequately handle it, and in their survey Grether and Plott

conclude that the explanation must lie in. some sort of

information processing problem.

However, once we have decided that it will be necessary to

include the difficulties of information processing as part of our

modeling of the decisions made by individuals facing risk, then

these same difficulties can be used to explain the other

phenomena which the dropping of the independence assumption was

intended to address (see below). Nor is the dropping of the

independence assumption without cost. Observers have generally

agreed as to the normative disirability of the independence

assumption. If we are trying to develop a framework for costbenefit analysis, these normative arguments carry considerable

weight. For if we drop the independence assumption we will be

faced with a certain time-inconsistency in our subjects'

preferences over lotteries. While there is nothing selfcontradictory in this fact, we will then discover that we can

change individuals' welfare simply by restricting their ability

to change their minds about which choices they will make,

.

For instance, suppose we use the lotteries described in

figure 4-6. Suppose we start by only allowing the individual

lottery B in the event that the .002 percent chance arises. Then

before the outcome of this chance, the individual's utility is

equal to the utility associated with lottery X. Now suppose we

expand the choices available to include the choice either of

lottery B or lottery A in the event that the chance arises. The

result is a decrease in the individual's current utility from X --------

to Y. The individual's reasoning against the i.ncrease in his

choice set is as follows: "Should the chance arise I know I will

pick lottery A, because as of that date I will prefer it to

lottery B, but in fact, from my current perspective I prefer

lottery A to lottery B, thus my utility has decreased by my not

being able to prevent myself from picking this currently-lessdesirable alternative."

Another recently revived alternative to expected utility--

regret theory--generates similar difficulties. This alternative

theory assumes that the individual decision maker makes choices

based not on the distribution of outcomes, but on the distribution of the dif'ference between the chosen outcome and the outcome

not chosen. This approach, based in minimax strategy game

theory, was a popular early rival to expected utility theory, and

it has recently been advocated by Loomes and Sugden. A major

4-67
difficulty with the theory is that it implies an intransitivity

of preferences, since individual preferences are not independent

of the set from which the choices are made. The authors of the

article argue eloquently that there is nothing "irrational" about

such a model of behavior, nor is there any logical inconsistency

in the structure. Although this is true, allowing this assumption does equal damage to the welfare analysis. For if we let

the government expand the set of available choices we again find

that utility can decrease, as individuals choose less preferred

alternatives because of the intrusion of seemingly irrelevant

alternatives.

In short, it appears to us that the price in terms of

difficulties with welfare analysis is too high to pay, especially

given the less drastic modifications that can be made to

rationalize the observed responses to risk surveys and still

maintain the fundamental welfare-economics structure intact.

4.4.4. ----- Conceptual ---- Problems with Welfare -------- ---- ------- ---- Analysi,s

When Tastes Are Uncertain ---- --mm-- --- ---------

Thus we conclude that the best way to procede in trying to

interpret surveys of individuals' attitudes towards risk is to

retain the independence axiom but admit that individuals do not

know their own tastes with certainty. There should be nothing

counterintuitive in this position: Most people do not deal

regular1.y with issues of risk; most people therefore are not

likely to be very expert in stating their preferences over risky

alternatives. Under the circumstances, it is not surprising that

when presented with a complicated set of alternatives among which

to choose, most people make choices thatseemto implythattheir

preferences are intransitive. However, we would expect the same

thing to happen if we presented real world consumers with multivariate bundles of goods and asked them to choose among them. As

long as we kept the bundles the same in most dimensions and only

varied a few at a time, we might have reasonable hope to obtain

a consistent ranking. But when we ask individuals to rank among

pairs of highly dissimilar bundles, we would not be surprised to

find apparent inconsistencies in their preferences. Individuals

are likely to make mistakes, and to be subject to the utilityequivalent of "optical illusions" when describing their

preferences.

The crucial test is the subject's reaction if confronted

with the apparent inconsistency of some set of preferences.

Suppose we say to a particular individual after an intervie,w "you

have said you prefer A to B, you prefer B to C and you prefer C

to A. Do you see any inconsistency in these statements?" If the

individual's answer is "yes, upon reflection I prefer A to C: we

are home free. If his answer is "yes, I see a problem there, but

I cannot tell which of my statements are incorrect." Then we too

have a problem, since the decision task is so difficult for the

individual that he cannot straighten out his preferences even

4-68
upon reflection. Nonetheless, our hypothesis of consistency of

preferences is still intact. Only if the individual says "no, I

see no problem at all with those statements" are we in deep

trouble, for then the individual must mean by the word

"preferences" something quite different from what we mean by the

word. In the case of Grether and Plott's preference reversal

phenomenon it is extremely likely that if confronted with the

apparent contradictions in their statements the subjects would

agree that their preferences would need revision. It is less

clear from the evidence that this is the case in the Allais

paradox cases. But at least in multiattribute problems,

descriptions of individuals' decison making processes seem to

indicate that transitivity of preferences are an underlying

assumption in their own actions (Payne et al.).

To summarize, our position is the following: if individuals

do not have consistent preferences and deny that their own

preferences need be consistent, we cannot do welfare economics.

If preferences are asserted by individuals to be consistent then

there is at least the possibility that progress can be made.

However, given we can no longer assume that individuals know

their preferences, the question remains, "what is the correct set

of criteria for making welfare judgments?"

One approach is to argue that the correct criterion is the

criterion that would be used by the politician hoping for

reelection. Voters make their decisions as to whom to reelect

without being forced carfully to think through their casually

stated preferences. If they do not know what their preferences

would be if they had thought through the situation sufficiently,

it is of no concern to the politician--those "true" preferences

must be irrelevant for reelection. If that means that different

preferences might be elicited by stating the decision problem in

different ways, then so be it; we must state the decison problem

in the form that the politician in power chooses to state it, and

then record the answers as accurately as possible.

The drawbacks of this point of view are obvious. Presumably

if the approach were explained to any voter, he would prefer that

alternative criteria be adopted by the investigator. One

alternative appraoch is the following: the problem stems from the

difficulty in eliciting individual preferences--this is always a

costly matter, as polling organizations insist. It is

particularly difficult if individuals themselves find it costly

to determine their own preferences. Under the circumstances, a

voter might prefer that the investigator use more extended

surveys, spending sufficient time and resources with each

indivdiual interviewed. Care should be exercised by going

through the initially stated preferences of the individual in

sufficient detail to determine if the,re are any inconsistencies

in them, by double checking those inconsistencies with the

individual, by presenting the decision problem in several

different formulations to double check that the individual is not

being swayed by illusions of the presentaiton, and finally by

giving the individual sufficient practice at answering decision

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problems of the sort we are dealing with to allow him to train

himself in ,determining his own preferences.

This approach, if explained to the average voter, would

presumably draw greater support than the initial one. Even if

the voter himself is not picked for the interview, if he regards

himself as sufficiently typical in his tastes, he will prefer

having a proxy go through this more extensive interview to get at

what his own true preferences are likely to be. Nonetheless the

average voter is still likely to have reservations about this

procedure. The extensive interviewing is largely a matter of

"education." From the investigator's point of view, it is the

individual educating himself about his own preferences. From the

point of view of a suspicious outsider, it could easily be the

interviewer educating the subject as to what his preferences

---a-- should be. These suspicions are likely to be particularly strong

if the conclusions of the investigation go against the surface

preference of the outside observer. In short, the procedure must

be carefully tailored to ensure that there is no presumption as

to what are the "right" or "wrong" preferences in the situation--

beyond the basic requirement of transitivity.

This is particularly difficult to achieve since people will

be dealing with questions to which moral strictures are .commonly

placed. Many people believe gambling to be morally wrong, and

maintenance of health at all costs morally correct. In assessing

the value to one individual of another individual's health, moral

perceptions will play even greater a role. One way of

characterizing the difficulty is to describe an individual as

having two sets of preferences--the preferences of his "selfish

self" and the preferences of his "socially conscious self"-- and

then trying to decide, not which preferences actually count in

individual decision making, but which should count for welfare ------

analysis. Another, probably more fruitful way of describing the

situation is to say that individuals' stated preferences depend

on their audience. Many of the causes of this dependence can be

reduced to a desire for various sorts of approval--desire to

appear to be a sophisticate, a moral individual, a member of the

team. Nonetheless, we do not need to distinguish between the

various reasons for stated preferences to vary. Our operational

definition of "true" preferences is those that would dominate in

the privacy of one's own home-- or in the privacy*of the voting

booth. It still then is an open question as to whether the

normative standard ought to be the sum of individuals' pri'vate

preferences but as a-Frs%<ical matter it should not be surprising

to find that indivdiuals will report different preferences to an

interviewer than they will declare to friends or through their

actions. Although this difficulty of moral overtones on

prferences is not a primary focus of this work, it is a problem

which will inevitably arise in the interviewing procedure.

Ultimately there is probably no resolution of the issue and the

only procedure open to the investigator will be an examinaton of

the extent to which individual preferences are influenced by the

groups in which they find themselves during the interview.

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4.4.5. -- Psychological Studies -e--w ---- -------

Cognitive psychologists have not been concerned with the

ethical/public policy question of which statements of preferences

-----a should be taken into account in the determination of public

policy. On the other hand, they have studied much more carefully

the question of what structures we can use to model preferences

which underlie the apparently inconsistent choices individuals

make.

An early version of a formulation which allows for

inconsistent answers to choice questions is the random utility

model (Thurstone), which in effect posits the existence of a

distribution over possible consistent underlying preferences, and

then assumes that each question is answered with respect to a

draw from one of the distributions. Note that the random utility

model is not, easily reconciled with economic models of decision

making. For instance, it is not equivalent to a model in which

the consumer has Bayesian priors about his own preferences. Such

an account would instead yield a more complicated, but still

perfectly consistent set of preferences over lotteries--indeed

the structure could be aggregated into a state preference model

in the ordinary way,

The assumption underlying the Thurstone model is that there

is a difference between the purely intellectual question "which

do you like better?" and the economic question, "which will you

take?" (compare Little). The random utility model simply assumes

that over time an individual's preferences change randomly so

that the answer can vary stochastically' to the question when

repeated. An alternative formulation, and one much more useful

from our point of view, is that the underlying preferences are

constant but the structure by which these preferences are

translated into ‘decisions is stochastic (Lute, Tversky). There

has been much concern in that literature with the equivalences or

non-equivalences between various formulations of the random

utility model. For our purposes, however, the issues are two:

what rational calculus can underly such a model and what

implications will it have for welfare economics? Our job as

economists is to delve through the stochastic portion to the

underlying preferences; our task in a survey then is to minimize

the noisiness of the response, and it therefore becomes important

to understand where the noisiness comes from.

This investigation belongs to the subfield of psychology

known as decision research. Its investigation involves several

methohologies not normally used in economics, including such

techniques as "verbal protocols" (the investigation of subjects'

reports of their own behavior) and records of subjects' use of

information in the decision process (Payne et al.). A useful

distinction made in this field is between decision making based

on alternative ranking versus decison making based on attribute

rankings. Alternative'ranking involves the process normallv

treated in economics--all alternatives are measured in some

4-71
common scaling and the highest of these scalings indicates the

preferred alternative1 In, attribute processes the various

attributes attached to the alternatives are ranked and then these

rankings in various dimensions are compared to determine an

overall ranking. The latter is useful when the tradeoffs between

the different attributes are difficult for the individual to

determine, but the cost is that such systems of decision making

easily result in intransitive rankings. Various authors in this

literature have focused on various procedures by which attribute

rankings are accomplished (a brief survey is included in

Aschenbrenner). Kahneman and Tversky .focus on the various

considerations that arise in the process of decision making in

comp.licated situations.

Among them are the "isolation" phenomenon and the

"anchoring" phenomenon. By "isolation" is meant the focusing on

the aspects that are perceived as the main contrasts between the

two available alternatives, treating as precisely equal the

aspects perceived as of smaller difference. Thus the Allais

paradox can be explained as an approximation'error due to the

decision maker's initial estimate that there is relatively little

difference between probabilities of .002 and .OOl as opposed to

differences between outcomes of $10,000 and $30,000. The

phenomenon of "anchoring" is a perceptual dependence on initial

conditions, a tendency to estimate values as closer to values

already examined. Grether and Plott's preference reversal can

then be rationalized as a tendency for certainty equivalents to

be anchored to the winning payoff in a gamble.

Thus it would appear that the phenomena most likely to pose

problems in interpreting surveys of risk preferences can be

understood without abandoning the independence assumption. Our

job is then to provide an economic basis which can rationalize

the use of such structures.

4.4-6. --_Components of an Economic Model ------ -- -- -------- -----

The basic component of the model is a set of prior preferences', which describe the individual's beliefs about his own

tastes in the event that he makes no expenditures to examine

those tastes.

The individual can also expend an amount of psychic costs to

improve the sample of his tastes. The expenditure gives him a

draw as to his own tastes, which in conjunction with his priors

can be used to derive new tastes. Each new draw can be added to

the set.

We then need memory to store the draws. The simplest story

is that memory is infinite, so that each draw is stored and we

can at any point find the set of consistent preferences representing an individual's beliefs at that point. The more

difficult, but possibly more interesting model, has finite memory, so that after some point more draws can only be added by

4-72
dropping the information in earlier draws.

The next step is to allow degrees of investment in reducing

the uncertainty over the prior preferences. Greater investment

entails a greater psychic cost, but allows a sharper prediction

as to preferences. Given previously learned information we can

imagine the individual as choosing to think more or less

carefully in attempting to answer the latest question. This is a

useful distinction for understanding the problems of "anchoring,"

since individuals' initial response will make it worthwhile not

to spend as much energy in attempting to answer subsequent

questions, relying instead on the initial answers to provide

clues. It also has testible implications in the case where

memory is limited, since the anchoring should diminish as the

length of time between related questions on the survey increases.

So far we have not discussed the role of the closeness of

one outcome to another. To do so requires the addition of a

metric to the problem, which metric describes the "similarity"

between outcomes, and therefore the degree to which the guess on

one outcome affects the likelihood of responses on other

outcomes. Once this metric is established it becomes useful to

describe the situation where different questions elicit different

sorts of investments in introspection, some being more useful to

anwering one, and some to answering another question.

Finally, we will drop the assumption of unbiased estimating

by the decision maker, and consider the effects of limited forms

of bias on the outcomes. This last modification will be

necessary to understand preference reversals due to "framing."

4.4.7. ------ ----- Formal Model Statement -----B-wSuppose that there are I alternatives being considered, each

with an unknown utility ui. Let U be the vector of these

utilities, and let F(U) be the joint probability distribution

over U. To begin with we will take the Ui to be i.i.d.

Throughout the the paper our examples will assume that the Ui's

vary normally and independently, with prior means m.1

and

precisions hi (i.e. l/variance).

The individual can, by spending a psychic cost of k, receive

extra information about his true preferences. We assume that the

extra information gal ed by this "introspection" is a draw of two

random variables whit?l are estimates of Ui and U which we call

Vi and V j respectively. We assume .I

where ei is measurement error which in our examples we will

assume is distributed as a normal with mean 0 and precision gi,

and independent of all other errors e and of all UI's (and

similarly for the distribution Vj).

4-73
Given any string of information (Vl , Vz,...) - S, we can

derive posterior distributions of the' utilities of the

alternatives F(UIS). In the case of normal distributions, a

simple application of Bayes's rule shows that, given a draw of

vi' the posterior distribution of U1 is normal with mean

y*(Q) - (mihi + vigi)/(hi + gi>

and precision

hi + gi’

If no draw is made, the individual's expected utility if

given a choice between Uland U2 is

max (ml, m2).

If the draw is made, utility is

max ( Iml*(VIL mg*(V2)) - k 1.

The first model we will consider is to solve the following

Bayesian decision problem: The individual is presented with a

series of alternatives, where each alternative is a pair of

outcomes, one of which he will receive. He is asked to make his

choice. For simplicity we will assume that at each instant he

treats the question being asked him as the last problem he will

face. (In fact, the problem is more complicated since an

individual might be expected to anticipate.that a series of

questions wi.11 occur and modify his introspection accordingly.

We will ignore this refinement. If the reader wishes, he can

assume that the survey is structured so that at each stage there

is an extremely low probability of any one participant's

receiving an additional question. This makes it possible to

ignore the likelihood of extra questions at every stage.)

The decision problem for the individual, namely how many

draws to invest in, can be formulated either sequentially or nonsequentially. These formulations mirror the strategies analyzed

in the research literature. The non-sequential formulation

(Stigler, 1961) has the individual precommit to a fixed number of

introspections. The sequential formulation (Kohn and Shavell.

1974) allows the individual at every step to consider further

expenditure on introspection based on the results he has learned

so far. Although the specific optimal strategies differ between

these two formulations, the general outlines are similar. Since

4-74
our problem is a specific version of the search problem, we will

consider ourselves free to switch back and forth between the two

formulations in the examples that follow, depending on which

yields the more tractable analysis in any specific application.

In this structure. it will not generally be optimal for the

individual to eliminate all uncertainty about his own tastes --

indeed it will not generally be possible. It can be shown that:

-----a- Theorem 4-1: Less information is acquired

l> The greater the difference between prior estimates

of the mi's.

2) The lower the variance of the prior estimate of

either Ui.

3) The greater the variance of the noise in any

estimate.

4) The greater the cost of information acquisition.

On the other hand, the posterior announced preferences are

more accurate

1) The greater the difference between prior estimates of

of the mi's.

2) The lower th,e variance of the prior estimate of either Ui.

3) The lower the variance of the noise of any estimate.

4) The lower the cost of the acquisition of information.

In actual experiments, it is often the case that instead of

receiving the payoff with certainty, the subject only receives it

with some probability less than one. For this modification we

have:

------- Theorem 4-2: When the probability of actually receiving the

payoff decreases, subjects

1) expend less effort in determining their own tastes, and

2) give less accurate ex post predictions of those tastes.

w These conclusions are immediate from the model, but they do

lead to some natural considerations for survey design: Difficult

questions will simply not be given much consideration. Questions

which yield potentially great payoffs in that it is costly to

answer incorrectly will be given more consideration, but ex post

are still likely to lead to inaccurate answers. Questions which

4-75
the individual considers easy to answer ex ante will not be given

much additional consideration by the individual.

Next we consider the effects of the answer to one question

on the answer to subsequent questions. Note that in this model,

repeating the same question several times in succession yields no

new information, since the individual has already optimized and

thus has no reason to make further introspections. However it

turns out that expending information on answers to one question

will, in general, yield information useful to answers to other

questions.

Suppose we ask the individual about a completely new pair of

alternatives. In the model in which all alternatives have

independent distributions, previous introspection has thrown no

light on his preferences with regard to these new alternatives.

Thus his behavior is the same as if the questions had never been

asked. However, consider the case where the second question

gives us as an alternative one of the options already considered

in the first question. Now previously gathered information

becomes useful and the subjects' responses will be affected.

There are two considerations. First, having answered one

question already means that the answer to the second question

will start from a more accurate assessment of the beliefs than

would otherwise be obtained. This decreases the likelihood of

extra investment but increases the expected accuracy of the ex

post announced choice.

The second consideration depends on the realizations

actually obtained in response to the first question. If the

realization causes expected values of the two alternatives in the

second question to move further apart, then the likelihood is

that there will be less investment in examining the second

question. However, if the realizations bring the values of the

two alternatives closer together, then investment in answering

the second question will tend to increase. On average, these two

possibilities balance and we have the first. consideration

dominating. Therefore although the presence of preceding related

questions on a survey may in any instance increase or decrease

the amount of investment used in determining the answer to

subsequent questions, we can nevertheless conclude that:

-w----e Theorem 4-3: Expenditure on introspection on average decreases

through the survey, while accuracy increases.

'Among other things, this result predicts a decline over time

in the attention paid by respondents to questions within a

survey-- a tendency often observed-- without needing to postulate a

fatigue factor.

More generally this interrelationship will be observed in

any model in which answers to one question help answer another

We will consider in more detail below the case where priors for

4-76
various alternatives ake no longer independent. But the

phenomenon can occur when priors are independent as long as there

is some dependency in the'sampling. The example of this

discussed above is the simplest one. Another case occurs when

introspection reveals information not about the 'two alternatives

independently, but only about the difference between their values

(We will call this the case of "Sampling of differences.") In

this case, whenever we find that an individual indicates that i

is preferred to j, it means that we can expect that i has a

higher value than initially anticipated, and therefore is more

likely to be preferred to other alternatives as well, and

conversely for j. Thus even in the case of independent

valuations, a primitive form of anchoring emerges.

4.4.8. Answering -------- 2 Series of Questions ------ -- --------

Given this structure,. there will be nothing paradoxical

about 'a sequence of answers to questions leading to apparent

intransitivities; it will simply be the case that between answers

additional information has been derived. It will also be

perfectly possible for individuals to reverse their answers on

subsequent repetitions of a question, provided that other

questions have intervened which have led the individual to seek

more information.

Suppose we now consider asking a third question and that

there are only the three alternatives Ul, U2, U3 under

consideration. If preferences are perfectly known, then the

entirety of the information can always be revealed with three

questions, and often with two. If preferences can only be

determined with a cost, there may be a gain from asking an

apparently redundant question. In our model we have:

------- Theorem 4-4: Suppose the first question determines that Ul is

preferred to U2 and the second question determines that U2 is

preferred to U3. Then

1) In response to the third question "Do you prefer U3 to

Ul?I' there is a finite possibility of the answer

exhibiting an apparent intransitivity.

2) In response to the third question "DO you prefer U2 to

Ul?" there is a finite probability of the answer exhibiting a reversal of preferences.

In any case, later answers are more likely to reflect true

preferences than are early answers in the list.

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---w--s Theorem 4-5: Suppose furthermore, that we continue to cycle

through the questions in the same order indefinitely. Then the

probability is zero that there is no number n such that for all

questions beyond the nth no further investment in introspection is

made. In order words, responses eventually settle down and

preference reversal ceases. Moreover, at the point where further

investment has ceased, there will be no intransitivities in the

response.

In short, this model with infinite capacity for recall

allows preference reversal and intransitivity, but only as

transient phenomena. Once further investment in introspection

ceases, preferences are stable and transitive. This result,

although useful as an insight, is not as strong as it might

appear, for it is not possible based solely on the responses to

determine whether investment in introspection has ceased. In our

normal distribution model we have the following result as well:

-v---w- Theorem 4-6: For any number n there is a finite probability

of obtaining unchanged results through n cycles with no intransitivities, and a preference reversal in the n+lst cycle. The proof of

this theorem depends on the fact that normal distributions are

unbounded. We conjecture that if the model is modified to deal

with bounded distributions, this last theorem will no ion-ger hold

and more positive results can be obtained.

So far none of our conclusions are altered if we use the

"comparison" formulation for introspection (recall that this is

the formulation in which draws give not two values Vi and V j' but

merely the difference between them). The following result

depends specifically on using the comparison formulation.

------- Theorem 4-7: Suppose that the initial question determines that

Ul is preferred to U

?l

and the second question determines that U

is preferred to U2. T en if investment yields only an estimate o 2

the difference between the valuations of alternatives, it cannot

be the case that a third question reverses the answer to the first

question.

----- Proof: There is no incentive for further investment in response

to the third question, since the second question only reduces the

estimate of Up.

If introspection gives estimates of both Ui and Us, the

conclusion of the theorem is weakened:

---m-w- Theorem 4-8: Suppose the initial question determines that Ul

is preferred to U2. Then preference reversal in question 3 is

more likely if question 2 determines that ,U2 is preferred to U3

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than if it determines the reverse.

In the case where two questions have already been asked, we

are now in a position to compare the relative usefulness of

various possible third questions. Here are the two relevant

cases to consider:

---- Case I:- Suppose the first question reveals Ul is preferred to U2

and the second question reveals that U2 is preferred to U3. Then

the most useful third question is to compare Ul with U2 again,

rather than to compare U

for the investigator to i

with U3. In.both cases it is optimal

ase his predictions of true underlying

preferences on the last two of the three responses; however,

these optimal predictions are more accurate when question 1 is

repeated than when the new comparison is made.

---- -- Case II:

U and the

Suppose the.first question reveals Ul is preferred to

i

second question reveals U3 is preferred to U2. Then

t e most useful third question is obviously to compare Ulwith

U3*

The resultant principles can be summarized quite neatly:

Redundancy in questions can be useful. If redundant questions

are used, it is more useful to doublecheck the earliest questions

and the ones which full ranking indicates represent the closest

calls. When redundant questions are used, rely on later rather

than earlier answers.

4.4.9. --- ------ ------ ------ -------- Comparison Versus Scaling Questions

For the purpose of this section, we will assume that

introspection yields an estimate of the value of only one ---

alternative. We now wish to consider the difference between the

effects of the following two questions: comparison questions

("Which alternative do you prefer?") and scaling questions ("How

much do you value alternative X?") Both are commonly used in

risk analysis and risk surveys and some of the difficulties with

the results stem from the non-comparabilities of the two sorts of

questions.

We need to establish some payoff associated with the answer

to the latter question. In actual surveys this is typically

accomplished by announcing to the individual that he will

participate in what is equivalent to a second-price auction

(Vickrey) with his announced valuation as his bid. Since truthtelling is a dominant strategy in such circumstances, in the case

where introspection is costless, this gives the individual an

incentive to answer correctly.

Giving the individual whichever alternative he says he

prefers is also an incentive to answer accurately. The issue

then is which format leads to greater introspection and therefore

4-79
greater accuracy in answering. In fact, comparison .questions are

special cases of scaling questions, since the second price

auction framework in effect chooses the value of the alternative

randomly and then presents the individual the realization, if the

individual's bid indicated he would prefer it, and the initial

alternative otherwise. A comparison question is thus a special

auction in which the bid which will win is known with certainty

beforehand.

Therefore the relative merits of the two forms of question

can be determined by resolving the following: Which random

distribution of alternative valuations induces the individual to

invest most in determining his valuation of a specific

alternative? The answer is the following:

-e---e- Theorem 4-9: Investment in introspection in evaluating a

propose offer is greatest when the value of the alternative to

receive-if the offer is refuse has a distribution with mass

concentrated at the expected prior utility of the proposed offer.

------ Proof: (Outline) By the results of the initial section, we

know that among offers with identical variance, the one giving the

closet mean utility to the proposed offer elicits the greatest

investment. Thus concentrating all mass at the mean is of greater

value than dissipating it across alternative possibilities.

If we know the individual's prior mean, then the best way to

elicit accurate preferences is to have the individual choose

between the alternative and the certain offer of the prior mean

utility. In any application, of course, we will not know the

decison maker's priors. Thus maki.ng a fixed alternative offer

will yield variable amounts of investment across individuals

depending on how close it matched each individual's prior mean.

One approach then is to ask casually what the mean valuation of

the individual is ("how much is this offer worth to you?") and

then to give.the offer or the estimated value to the individual,

whichever he prefers. The paradox of the difference between

estimates made in some of the preference reversal literature is

partially resolved then by the fact that greater investment is

made when the actual offers are in prospect. This framework

does, however, yield refutable propositions, since the initially

stated preferences should be reversed about half of the time. If

reversal occurs more than half the tfme, we must assume biases in

the individual's initial estimates. Analysis of this situation

must wait until the final section.

In any event, this analysis also gives a useful rule of

thumb for scaling the distribution of offers in the alternative

used in a scaling question: They should mirror the

investigator's estimate,of prior means in a population sample.

4-80
4.4.10. More General Distributions of Priors ---- ------- ------------- -a w----w

Thus far we have assumed a great degree of homogeneity: All

alternatives and all estimations have been assumed to have

independent distributions. In fact, much of the richness of a

real decision problem comes from the non- independence of these

distributions.

The structure we have developed allows for outcomes to be

"similar" in several senses. First, two outcomes may have the

same expected utility. Second, two outcomes may be considered

similar if it is relatively easy to tell which one is preferred

to the other. Finally, outcomes may be similar because there is

a correlation between information about one of them and

information about the other -- so that one becomes a useful

predictor of the other. Each of these notions is important in

describing the effects of learning about preferences and the

relationship between learning about one alternative and learning

about the next. In this section we begin to establish a

framework which will enable us to explore this relationship.

To consider the effects of non-independence, we will assume

that all alternatives have a factor representation, so that the

utility associated with any alternative is

Ui - Summation of biXi,

where the b's are weights and the X's are i.i.d. underlying

factors. If we make this assumption, then we will describe one

alternative Ui as a good predictor of another U if the two are

closely correlated. In this framework correlatio d is simply

Summation over i and j of bibj(Summation over i of bi2

summation over j of bj2)1'2.

In this framework, the answers to a question about an

alternative are affected similarly by having asked previous

questions about it or by having asked previous questions about a

good predictor of it. In either case, the variance of estimate

of the alternative is reduced, answers become more accurate, and

the likelihood of further investment in introspection declines.

In particular, any conclusion from preceding sections about the

behav,ior of multiple questions applies approximately when all the

alternatives in one of the questions in the sequence is replaced

by a good predictor of those questions with mean utilities scaled

up or down proportionately.

A second form of interdependence is attributable to

interrelations in the error structure in the sampling. Suppose

again that all the Ui's'are independent, but that the e's in the

various draws have a factor representation:

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ei - Summation aixi.

The closer th'e correlation for any two alternatives i, j,

the more can be learned from a given attempt to compare them. If

we identify the xi 's with various measurement errors associated

with the forms in which alternatives are presented, it is

apparent that we desire a presentation which is as consistent as

possible across alternatives. Moreover, if questions are

designed to give the individual aid in learning about the forms

of measurement error, then we can hope that associated errors may

disappear in subsequent questions,

are learned.

as values of particular xi's

So far we have assumed that the individual is passive in his

choice of alternatives upon which to make introspections, only

choosing the number of examinations to make of any given

alternative. As long as homogeneity assumptions are maintained,

there was little cost associated with this additional

simplification; in answering a question about preferences between

U and U it was always more useful to introspect on those two

a f ternat ve 2 than upon any other set. Once homogeneity is dropped

however this need no longer be the case, as the following example

demonstrates:

---- -- Example:

that Ul

Suppose there are three alternatives Ul, U2, and Ug and

is a good predictor of U

%

while U3 is independent of

either. Suppose furthermore that t e error structures for U2 and

U3 are highly correlated, while.the error structure for Ul is

uncorrelated with the other two. Then if the correlation between

U1 and U2 is sufficiently high, it is optimal for the individual

to decide between U1 and U3 by introspecting on U2 and U3.

In other words, the structure is now sufficiently rich to

rationalize the use of proxies and heuristics. If a decision is

to be made where the measurement problems are sufficiently

difficult, then the decison maker finds it advantageous in his

work to substitute for the initial decision a set of alternatives

which are good predictors but for which the measurement problems

are less acute -- for instance, to simplify a complex lottery by

substituting certainty equivalents for certain branches.

Note that although this structure can explain the use of

heuristics, it cannot explain any biases observed in the

heuristics used. For example suppose w.e structured a problem so

as to make one set of heuristics most natural in one instance and

a second set in a second instance. The model as it stands would

not predict that every individual's answer be identical in the

two instances, but it would predict that on average stated

preferences would be the same in either realization.

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4.4.11. T&z Effect of Limited Memory ------ -- ------- -----

It is important to realize that the framework as it has been

described so far still has a significant limitation. An

important simplifying assumption we have used is that of "perfect

recall." No experiment, once made, is ever forgotten.

Information becomes more and more precise as more and more

questions are asked. This simplifying assumption leads to

testable implications. As noted before, preference reversals and

intransitivities occur in the model, but as transient phenomena.

As more and more questions are asked, the number of reversals

becomes rarer and rarer, and the effects of anchoring to the

previous questions dies out.

If these predicitions are not upheld by the data, a natural

way to .keep preference reversals occurring is to allow for

imperfect memory. We simply need to assume a limited memory

capacity, so that records can only be kept for a fixed number of

experiments. If the number of examinations made exce-ads this

fixed limit then each new examination replaces an earlier result.

Beyond that point, we simply condition priors only by the last N

observations (where N is the capacity of memory) rather than by

the entire history.

Note in particular that this model is an extension of the

basic random utility model. In our new framework we would

interpret the random utility model as a special case in which

memory can only contain one experiment at a time. A limitation

of the simple random utility model is that responses cannot be

autocorrelated, as they can when memory is allowed. On the other

hand, in a finite memory model there is no tendency for

preference reversals to die away or expenditur.e on introspection

to cease. The following results are immediate:

------- Theorem 4-10: The smaller N, the more common are preference

reversals, and the more likely are observed intransitivites.

-m---e- Theorem 4-11: For a given question let R(n) be the fraction of the

times that the answer is reversed between instances of posing the

question, when the numbzr of intervening questions is n. Assume

that for some n, say n , there is no memory--i.e., none of thz

introspection that entered into

questions later.

answering any questi*on is left 2

Then any period n less than n , R(n)/R(n >

measures the extent to which memory endures n periods.

Again, these results, although useful conceptually, are of

less use in empirical implementations if the acutal capacity of

memory is large. For if it is, the interview session would have

to continue sufficiently long to gather a large amount of data

relative to the memory capacity. Some investigators have

attempted to overcome this limitation by posing some questions in

several sessions with large amounts of time intervening. The

theorems may serve as a basis of determining the success of this

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technique.

4.4.12. ------ Biases

In the previous sections we considered several cases where

inconsistencies resulted; however the Bayesian structure left as

an implication that the inconsistencies could not systematically

be weighted in one direction or another. In this final section

we develop models 'which will allow for systematic biases in

individuals* estimates.

It is extremely difficult to develop a Bayesian account in

which individuals are subject to bias. For example, consider a

problem in which an individual is paid a reward for correctly

estimating the length of a line. Suppose he has a measuring

stick which is biased, and suppose he has had previous

experiences with the biases of this measuring stick. Then his

estimates will be made so as to undo any such biases. The only

waythatthere will be abiased estimate is if the individual has

not yet learned the biases of his instruments; once learned,

rationality requires that they be compensated for.

In the case of estimating the utility of prospects, it is

easy to believe that individuals have not yet learned all of the

biases in their measurements. It is also easy to believe that

unless they experience the gambles they are estimating their

preferences over, they will not learn these biases during a

questioning session, except inasmuch as these biases lead them

into a logical contradiction.

On the other hand, we will wish to be extremely careful in

incorporating biases into the model. The difficulty with

assuming them is that they are too powerful. By assuming

sufficiently complicated forms of bias it is possible to

rationalize any sequence of preference announcements. Therefore

in this section we wi-11 content ourselves with modeling the

biases as occurring only in the priors and not anywhere else in

the description. At one point we will demonstrate that for a

certain class of examples this is informationally equivalent to

assuming that the biases occur elsewhere.

The introduction of biases imposes a conceptual problem: In

what sense can we obtain evidence of biases? We propose the

following interpretation: Biases can be evident from a

systematic set of information which influences tastes. For

instance, if the data show a systematic tendency for alternative

2 to be valued more highly than alternative 1 at the beginnning

of an interview than at the end, then this is evidence of some

bias; individuals in initial periods might be expected to take

advantage of this statistical regularity as a source of

exploi,table information about true preferences.

These biases can be incorporated by assuming bias In the

individual's priors. Let us suppose that individual preferences

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are drawn from a population with some given distribution. If

individuals' priors are unbiased, then their priors as to their

own tastes equal this population distribution. More generally,

in cases where not all individuals are identical a priori, prior

beliefs are defined as unbiased if for any particular prior, the

sample distribution of, true beliefs of individuals holding that

prior is identical with the prior.

We consider only the case of infinite memory. In this case

"true" preferences are simply the asymptotic distribution after

infinite numbers of samplings. Moreover, in this case, since the

influence of priors dies out with time, biases disapppear. The

existence of such biases can easily be tested, by comparing

distributions of preferences implicit in initial questions on a

survey with those implicit in final questions on a survey. The

result of such an investigation will be of use in adjusting the

results of short surveys to correct for prior biases.

A s.econd way of formulating the account is to assume the

biases are not in the priors but in the process of introspection.

For instance, imagine that in introspections about one outcome

Ul, the mean of measurment error e1 is not zero, while in the

corresponding outcome U2 the mean is zero. However suppose that

both e1 and e2 are treated by the decision maker as being zeromean variables. Then the greater the amount of introspection

that has occurred the more likely alternative 1 is to be

preferred to alternative 2. Of course identical results would be

obtained if priors were biased against alternative 1 and

introspection were unbaised. Thus we will .continue to use the

'formulation in which we ascribe all bias to the priors.

Similar, but more subtle forms of bias can be demonstrated

through over-dependence on initial introspections, over-valuation

of current information, and so forth. In all cases, the test of

bias boils down to a claim that statistically, the answer to a

question conditioned on any information set or a set of previous

questions should equal the answer to the question conditioned on

any additional information. If not, then, the earlier estimates

were not making use of the available information. To have

anchoring in this sense will require bias.

For our purposes, the most interesting example of bias is

the case where the conditioning event is the form in which an

alternative is presented. If there is no bias in the preference

priors then statistically about as many people should prefer an

alternative independent of the form of its presentation. In what

follows we will generate an account within which biased priors

can account for the inconsistencies and therefore can generate

preference reversals of the form described in Grether and Plott.

4.4.13. ---- -- -- Example of Biased Priors Generating Preference Reversals ------ ------ ------m-- ------w-m

Suppose Ul is a complicated l lcornative which his a factor

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structure

x1 + x2 + x3 .

Suppose U2 has the structure X1+X2; and, suppose U3 has the

structure X1+X3; also, suppose we wish to compare Ul with U4

which has the structure X4. All X's are 1.i.d. normal.

Suppose that the measurement error structure for the.U's is

vl - Ul + el

v2 - u2

v3 - U3

V4 - U4 + e4 .

Suppose that el is large compared to X2 or X3 so that it

makes sense to compare U4 with one of the predictors U2 or U3

rather than directly with Ul.

Suppose thatU2 and U3 are ex ante identical so that it does

not matter which the comparison is made with and finally suppose

that the costs k are sufficiently great that a single draw is

optimal.

Under these circumstances, without bias we would predict

that statistical results would pick Ul or U4 with frequencies

independent of whether V2 or V3 were used as the predictor. On

the other hand suppose the true distribution for U2 is

X1+X2+h

where h is positive. Then although the indivdiual treats the

predicting alternatives as equivalent to alternative Ul,

alternative 2 is likelytobe preferredtol. The result is that

Ul is announced as preferred to U4 more often if the comparison

is carried out by means of U2 than if it is carried out by means

of u3.

If the biases in individuals' estimations enter through the

priors as we have described them here, then we have a testable

implication. Questions asking the individual to compare Ul with

U

a 1

or U3 will cause the individual to invest in introspection

ong those dimensions, reducing the influence of the priors and

making it more likely that h is included in the measurement

Thus we have:

------- Theorem 4-12: If biases occur in the priors then they will be

reduced by questions which focus on the comparisons in which the

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biases occur.

In this example, if two presentations of the data apparently

lead to different preferences, then the biases might be reduced

bY asking directly for comparisons either of the two

presentations, or of each with the predictor which we expect has

been derived from it.

4.4.14. ------ Summary and --- --ImEliciations -------mm- --- for Contingent Valuation --a--- --- e--m-----

The model of uncertain preferencess in section 4.4 provides

a framework to guide the application of contingent market methods

to estimate the value of health risk reduction. Following a

critique of expected utility theory and a discussion of the

theory of individual values and behavior towards risk, a series

of theorems have been developed that resolve difficulties with

survey responses in terms of the behavior of a rational

respondent making a costly examination of his own preferences

when faced with questions that call them into play perhaps for

the first time.

The key to the problem of obtaining consistent, valid measures of risk values, according to the theory that has been

developed in section 4.4, is dealing with the fact that people

are often highly uncertain about what their risk preferences and

values actually are. This is to be expected because people

infrequently have occasion to think carefully about risky events.

They seldom have occasion to examine their own reactions to the

influences to opinion-molding surface events. Careful,

systematic reflection is required, just as is required before

deciding on an operation, a risky investment, or other difficult

decisions that arise from time to time in everyone's life. While

bias may enter into the valuation process, the economic approach

of section 4.4 postulates that people learn to correct for the

influence of their own biases when they become aware of them. A

model has been developed and a series of theorems derived that

have implications applicable to the task of eliciting consistent,

valid risk reduction values.

The propositions of this section coming from a model of

rational behavior replace assertions from the psychology literature that apparent preference reversals and sensitivity to

framing show that people are irrational. In the present section,

these phenomena are viewed as being due to the costliness of

information.

Theorem 4-l concerns reducing an individual's uncertainty

about his own preferences. The question posed is how an

individual can make the best choice when faced with a pair of

alternatives. The theorem says that less new information is

required the greater the difference in the value received from

each available choice. It also says that the more certain the

individual is about the values of the alternatives, the less new

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information is required to make the right choice. Finally, less

new information will be acquired the greater the cost of

acquisition.

The reminder of theorem 4-l contain several propositions

about the accuracy of preferences that are stated after an

individual has acquired additional information. The theorem

holds that announced preferences are more accurate the greater

the difference in value received from each available choice.

Preferences are stated more accurately the more certain

individuals are about the value of the alternatives they face.

Finally, announced preferences are more accurate the lower the

cost of acquiring new information.

An application of theorem 4-l is found in the use of the

floating starting point in sequence of iterative bids. Consider

the 7-symptom Health Questionnaire: One day, reproduced in

Appendix A.1 of section 3. The sequence proceeds from an

arbitrary startingbid of $100 to get rid of the least bothersome

symptom. The starting point for the next bid, concerning the

most bothersome symptom, is set at twice the first bid, based on

the guess that such a value might be a fairly close approximation

to the respondent's value. The theorem says that the respondent

will think more carefully about his preferences at the outset the

.closer the guess is to his value for the contingent market

product.

Theorem 4-2 concerns outcomes of risky situations in which

the values associated with alternatives may not actually be

received, but are received only with a probability less than one.

The theorem states that people expend less effort in getting to

know their own preferences the smaller the probability of

actually receiving the stated values of alternative choices

available to them. It also states that actual expressions of

their preferences are less accurate the more uncertain it is that

they will receive the payoff.

The fact that no actual transactions occur in the contingent

market surveys is a disincentive to careful thought on the part

of respondents. This has been recognized by researchers for a

long time. The disincentive is partially overcame in public

policy applications by appealing to respondents' w.illingness to

cooperate in accomplishing an important endeavor.

Theorem 4-3 pertains to the way people allocate their

efforts to know what their risk preferences are. If people

reflect on a series of alternatives, they will devote less and

less effort and attention to later alternatives to the extent

that they are related to alternatives previously considered. A

similar result occurs when there fs dependence in the sampling

and people discover the values they place on differences.

One of the most difficult dectstons in the construction of

the health surveys is to decide on the number of contingent

valuation questions to ask. Expertsnce reveals that there is a

4-88
tradeoff between the quality of responses and the volume of

information sought. Theorem 4-3 explains this experience. When

long' question sets are asked about similar contingent products,

people tend not to think independently about each of them. It

tends to be their reliance on previous introspections rather than

often-postutated fatigue that produces this result, according to

the theorem.

The theorem implies that a series of related questions can

lead people to think about the differences between contingent

goods rather than considering them as independent alternatives.

This behavior can be exploited by encouraging people to think

about differences as they express their values for programs. For

example in the '/-symptom health questionnaire of section 3,

people were asked to carefully consider each symptom in turn and

rank them from least to most bothersome. Bids were then obtained

for the two extreme symptoms; iteration was used to encourage as

much thought as possible. Bids for the five intermediate symptoms were then written down directly on the assumption that the

comparison exercise had made their values apparent.

Theorem 4-4 addresses the problems of preference reversal

and intransitivity that are frequently observed in expressed

valuations of risky outcomes. If preferences are uncertain and

information is costly to obtain, inconsistencies or outright

reversals may occur as individuals reflect upon their

preferences. True preferences are more likely to be stated

during later stages of reflection. A related theorem states that

if reflection on the same list of risky alternatives continues, a

point is reached where further reflection will not be attempted

and expressed inconsistencies are eliminated. This result

depends on several assumptions, among which is that the

individual does not forget any of the earlier steps in the

reasoning process. If the reflection process produces only

estimates of the 'differences in outcomes, then further probing of

preferences can not produce preferences reversals, simply because

there is no incentive for such further probing of these outcomes.

An effort was made in constructing the health questionnaires

to utilize apparent preference reversals as part of the process

of respondent introspection about preferences. For example, in

thinking about how much they would be willing to pay to relieve

symptoms respondents sometimes change their minds about thefr

beliefs when they were working out their rankings. Accordingly

they were encouraged to change their responses, several times if

necessary, until they arrived at a set of rankings and values

that satisfied them.

The following theorems suggest additional approaches to

stimulating introspection about preferences where preference

reversals and intransitivities are present in survey responses

These hold considerable promise for further work.

The practical content of theorems 4-5 through 4-8 is that

repeated questions concerning preferences are often useful. If

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repeated questions are used in the reflection process, it is most

useful to doublecheck 'the earliest questions and the ones in

which the earlier rankings suggest the closest calls.

Reflection about preferences frequently takes one of two

forms: comparison- -which alternative do I prefer?; and scaling--

how much do I value alternative X? The question that induces the

greater amount of investment in additional information is the

superior question to use in any given circumstances, Theorem 4-9

states a condition on the most effective way to stimulate effort

to get new information. Suppose one constructs an offer of

alternatives: one whose value is sought and another whose value

is fixed at some given stated value. The best given stated value

is that closest to the prior value of the alternative of

interest, i.e. the value before new information has been

acquired.

Theorem 4-9 has a very important lesson for the construction

of contingent market goods. It received careful application in

the 7- symptom questionnaires of section 3. 1 This was accomplished by framing willingness to pay questions in terms of the

respondents' endowments, with which they were familiar and presumably had clear ideas about in utility terms. Additional

amounts of symptoms were then added to those they already experienced. Thus respondents were presented with two alternatives: Alternative X- -their current situation; and alternative

Y- - the situation with added symptoms. They were then in affect

asked a scaling question- -how much do you prefer situation X.

Theorem 9 says that by relating the policy alternative (Y-X) to

the respondent's own endowment rather than some less familiar

reference point X', the respondent invests more effort in thinking about his own real preferences.

Further work needs to be done along these lines on the life

path scenarios on heavy symptoms reported in section 4.5. For

example, certainty scenarios begin with a person of age 50 and

present life path alternatives with later ages. Application of

theorem 4-9 suggests that people who are younger or older than 50

do not have strong prior beliefs about their health values at age

50, and will not invest much effort in making accurate WTP

statements about the alternatives. Investment in introspection

would be increased if these scenarios were tailored to each

respondent's actual situation.

The foregoing theorems assume that there are no memory

limitations that reduce the effects of information gathering

about preferences. Relaxing thi.s assumption yields a theorem

that says that the more limited i,s memory capacity the more

numerous will be instances of preference reversals and intransitivities.

Theorems 4-10 and 4-11, of limited empirical usefulness when

memory capacity is large, provide a method of measuring the

extent to which memory endures during a period of reflecting

about preferences.

4-90
A problem of importance in discovering the values of uncertain preferences is the presence of bias. The problem is for the

individual to learn the size and direction of his biases and

correct them in discovering his underlying preferences. Questions arise during reflection in which biases occur. Theorem 4-

12 states that biases will be reduced by questions that focus on

comparisons of alternatives in which the biases occur.

In conclusion, the framework we have built, although rudimentary, allows us to address several of the most vexing problems

which arise in researchers' attempts to make use of data from

risk surveys. It has been constructed as a series of nested

generalizations starting from expected utility theory and

gradually dropping or modifying assumptions that have been refuted in one or another examination of responses to survey questions.

Although the outlines of the model at every level are clear,

there remains much to be done. In particular when the

homogeneity assumptions are dropped there remain a great variety

of unexplored possibilities. Itwill be most useful to tailor

specifications of assumed structural relationships between the

priors on various alternatives or the measurement errors of

various acts of introspection to the specific description of the

alternatives in any particular experiment. Once this is done we

can begin to make useful inferences from watching individuals'

behavior in the face of specific complicated offers, and learn

which sorts of simplifications individuals actually make in

estimating preferences.

Similarly, there is much work to be done in specifying

particular biases to which we would wish to attach the priors.

Here previous psychology studies will be most useful for

providing insight as to the most reasonable specifications.

Tendencies to overestimate small probabilities and to

underestimate large quantities can be among those considerations

we capture in the biased priors. In short, although the

structure is now available, much work remains to be done in terms

of specific applications.

4.4.15. ---d-----e References

1. Aschenbrenner, K. Michael. Efficient Sets, Decision

Heuristics, and Single-Peaked Preferences. Journal of

Mathematical Psychology, 23: 227-256, 1981.

2. Allais, M. Le Comportement de 1'Homme Rationnel devant le

Risque, Critique des Postulats et Axiomes de 1'Ecole

Americaine. Econometrica, 21: 503-546, 1953.

3. Grether, D.M., and C.R. Plott. Economic theory of Choice

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4.

5.

6.

7.

8.

9.

10.

11.

12.

13.

14.

15.

4.5.

and the Preference Reversal Phenomenon. American Economic

Review, 69: 623-38, 1979.

Kahneman, D., and A. Tversky. Prospect Theory: An Analysis

of Decision Under Risk. Econometrica, 47: 263-92, 1979.

Kohn, Mier, and Steven Shavell. The Theory of Search.

Journal of Economic Theory, 9: 93-123, 1974.

Little, I.M.D. A Critique of Welfare Economics. Oxford

University Press, London, 1956.

Loomes, Graham, and Robert Sugden. Regret Theory: An

Alternative Theory of Rational Choice Under Uncertainty.

The Economic Journal, 92: 805-824, 1982.

Lute, R.D. Individual Choice Behavior. Wiley, New York,

1959.

Machina, M. 'Expected Utility' Analysis Without the

Independence Axiom. Econometrica, 50: 277-323, 1982.

Markowitz, H. The Utility of Wealth. Journal of Political

Economy, 60: 151-58, 1952.

Payne, J.W., M.L. Braunstein, J.S. Carroll. Exploring

Predecisional Behavior: An Alternative Approach to Decision

Research. Organizational Behavior and Human Performance,

22: 17-44, 1978

Stigler, George J. The Economics of Information. Journal of '

Political Economy, 69: 213-225, 1961.

Tversky, A. Choice by Elimination. Journal of Mathematical

Psychology, 9: 341-367, 1972

Thurstone, L.L. A Law of Comparative Judgment.

Psychological Review, 34: 273-286, 1927.

Vickrey, W. Counterspeculation and Competitive Sealed

Tender. Journal of Finance, 16: 8-37, 1971.

DESIGN OF CONTINGENT VALUATION APPROACHES TO SERIOUS ILLNESS

4.5.1. Special Problems of m---w -------- -- ----a- Contingenr Valuation Encountered --------- ----------- With ----

--m---m Serious Illness -- -----

The valuation of serious illness entails a number of

analytic problems that are fundamentally different from the

valuation of minor illness and light symptoms experienced

occasionally by everyone in relatively unpatterned ways

throughout their lives. Thus the analysis of section 4 requires

4-92
completely different analytic techniques from those employed in

section 3, even though it builds on the survey research knowledge

obtained there.

Two fundamental aspects of behavior, relatively unimportant

to the study of light symptoms, are introduced in section 4. The

first of these is risk. Serious illness, dreaded by people at

some stage of their lives, is a prospect they face with varying

degrees of probability. Because people have some control over

the probability of serious illness, their behavior in the face of

serious health risks is an important measure of the value they

attach to good health prospects. Hence it is important to

understand people's attitudes towards health risks.

The second fundamental aspects of health behavior is the

way prospects vary over a person's lifetime. In younger persons,

choice and consequence are often separated by many years. Over

time one's health prospects change, and behavior tends to be

modified.accordingly. At the same time, life expectancy becomes

a matter of conscious concern. How one responds to these

interrelated matters depends in large measure on the social and

economic circumstances of one's life, and on how one has cared

for his health in the past. Thus the focus of section 4 research

turns to an integrated view of serious illness and death in the

context of a person's overall lifecycle experience.

Accordingly+ section 4.2 explicitly introduces the concept

of health as a behavior-dependent condition of overall well

being. Operationally, a narrower version is adopted--health is

measured in terms of its absence, or in terms of the amount and

types of the person's ill health. This narrower operational

definition preserves the prespective of the broader, more

satisfactory definition by being embedded in a life cycle model

of quantity and quality of life, developed in section 4.3,

Section 4.4 addresses the difficult problem of eliciting

expressions of people's behavior towards risks to health.

Respondents will have thought about these matters to a greater or

lesser extent and adjusted their behavior accordingly. The

research challenge is to obtain quantitative equivalents to the

sometimes nebulous attitudes that govern health behavior in the

face of risks. The current state of utility theory leaves

unanswered the question how best to obtain these quantitative

equivalents in a form suitable for use in welfare analysis.

Section 4.4 provides the inquiry required to guide the

investigation along sound theoretical lines.

The empirical framework that resulted from this conceptual

investigation is presented in section 4.5. This empirical

framework takes the form of a four-module approach to the

valuation of health-risk reduction. The first module, health

experience, quantifies the respondent's health endowment

according to the operational definition of health established in

the conceptual work of section 4.2. Health costs and defensive

measures, the second module, quantfffes certain important money

4-93
outlays and nonmarket behavioral costs incurred on behalf of

health. The module on risk perception and risk behavior prepares

respondents to think carefully about the kinds of probabilites

involved in behavioral decisions about serious illness and

longevity. This involves a prepartory session to impart an

intuitive grasp of the elementary principles of probability. It

also obtains information about respondents' behavioral responses

to a variety of risky situations. The fourth module presents the

contingent valuation questions used to obtain values related to

longevity and reduction of risk of serious illness. The goal of

these questions was to integrate prospects for serious illness

and death into an integrated life cycle approach. The questions

progress from simple life experience situations to more

complicated life path situations involving various probabilities

of serious illness and death.

The four-module approach requires about three hours to

complete, including breaks for relaxation. Designing a survey of

this complexity and duration is a novel research enterprise.

Past economic survey experience suggests it to be too taxing of

respondents' patience and stamina. In view of this experience

the necessity of taking steps to avoid fatigue was apparent.

Taking several breaks at intervals defined by the modules is the

simpliest of these. Use of this Health Risk Appraisal also

serves this purpose by providing an interactive computer program

approach to obtaining information about the respondents' health

endowments. Respondents are aware that the program output gives

them information about their own health status, which is expected

to sustain their interest and energy while at the same time

providing information that will unable the contingent valuation

questions to be tailored to their own life situations.

Considerable thought has also been given to devising entertaining

probability teaching devices that can accomplish their task with

a minimum of effort. The contingent valuation questions

themselves are designed to capture the interest of respondents.

Path-of-life situations are presented with the assistance of such

devices as a type of roulette wheel that respondents manipulate,

and with various card-game analagies with which many are

familiar. Lastly, the incorporation of in-depth marketingresearch interview techniques will be employed in order to make

the exercise as effective as possible.

Much work on morbidity has pertained to non life-threatening

diseases, including section 3 of this report. At the other

extreme, there have been many studies of mortality, as reflected

in an extensive value of life literature. Serious illness has

been relatively neglected. Only the health expenditure approach

has given much attention to serious illness. As was brought out

in section 2 of this report, which concerned comparative analysfs

of approaches to valuing health, the health expenditure approach

suffers,from crucial conceptual problems, and at best it gives

lower bound estimates.

Serious illness involves valuation problems that combino

pure morbidity effects and value of life and mortality effects

4-94
It might be thought that serious illness could involve only

morbidity and not mortality., However there are two important

reasons why the valuation of serious illness must be concerned

with both morbidity and mortality. First, most serious illness

is life threatening. Increased risk of death b.ecomes a cost of

the illness along with more usually recognized morbidity effects

such as medical expenditures, lost work and discomfort. Second,

serious illness affects the quality of life in an extreme way.

The value of life is affected by the quality of life as well as

its quantity. That is, the value of life depends on well being

during life as well as the number o.f years lived. The

traditional value of life literature may be interpreted as

pertaining to duration, or number of years of life, assuming

cause of death does not affect the quality of life.

In this regard the usual value of life approach to death

from a disease like cancer, coming at the end of a lingering

illness, understates the costs of cancer. Cancer reduces the

number of years of life -- which is taken account of by the

traditional value of life approach, and it also reduces the

quality of life while living -- which is ignored in the

traditional value of life approach.

Recognizing that serious illness involves both the quality

and quantity of life leads to a reformulation where morbidity and

mortality are considered in a common framework. Cne of the most

important results of using this framework is to view values of

serious illness in terms of tradeoffs between the quantity and

quality of life. In this section we develop and apply this

framework.

In addition to raising questions about the relationships

between the quantity and quality of life, serious illness is more

complicated than non-serious illness because risk is an important

consideration. Perception of risk is a .prerequisite to

intelligent valuation of serious illness. Just as with death,

the value attached to serious illness with certainty is different

from the value attached to small changes in the probability of

the illness, which in the aggregate mount up to the same number

of deaths.

People's knowledge of risks and their abilities to verbalize

their attitudes toward risks are notoriously difficult areas,

which must be dealt with if the contingent valuation approach is

to have hope of yielding reliable results. In addition to perception and knowledge about risks, issues arise concerning behavior in the face of risk. The degree of a person's risk aversion will influence how greatly he values a reduction of the

probability of the problem of a serious illness.

The present section draws on the three previous sections in

devising a contingent valuation approach to serious illness.

Section 4.5.2 first states why in-depth interview techniques are

needed in the valuation of serious illness. Then the basic

structure of a four module interview approach is described. The

4-95
four modules pertain to 1) health experience, 2) health costs

including defensive measures, 3) risk and 4) contingent value

questions. Sections 4.5.3 through 4.5.6 describe the four modules in detail. Finally section 4.5.7 draws implications from

preliminary experimentation with the modules and makes recommendations 'for further work.

4.5.2. --------- --- -------- Rationale and Overview of Four Module Approach em de-- -e--m- - -----

Early focus group efforts indicated that respondents have

great difficulty in a short interview in forming quantitative

opinions on small risks and heavy health damages outside their

everyday experience. An in-depth four module approach was

therefore developed. The four module approach establishes the

basis for intensive interviewing for the study of life threatening illness..

4.5.2.1. Health Experience

The first module, health experience, establishes the

respondents' health endowment and health habits as part of the

explanation of willingness to pay survey responses. It also

helps respondents focus their attention on the subject of the

survey and prepares them to give carefully thought-out answers.

4.5.2.2. Health Costs And Defensive Measures

The second module deals with the costs of maintaining health

and treating illness. It considers defensive measures taken to

promote health and avoid illness as well as expenditures to treat

illness. Respondents are asked to recall the number of days of

work and recreation that were lost because of illness, and also

the number of such days that were partially impaired by illness.

Defensive measures include all behavior intended to avert risks

to health and life. They comprise actions identifiable by market

expenditures and also behavior that is costly to the individual

in a non-market sense. Non-market preventive measures include

both abstinence and health producing activities that in part, at

least, do not yield utility directly.

Measurement of these activities is part of the empirical

framework for studying behavior towards risk. They are an

important part of the behavior by which people reveal the values

they place on improved life and health prospects.

-

4.5.2.3. Risk Perception And Risk Behavior

The third module, risk perception and risk behavior, gives

the respondent an intuitive grasp of probability and discusses

4-96
the importance of the concept in everyday life. Fundamentals of

probability are discussed using everyday language supplemented by

physical devices such as urns from which drawings illustrating

randomness and chance are made. Following this grounding in

probability, the respondent's attitudes towards risk and perceptions of the danger of various activities are explored. Respondents are askedhow they attempt to keep risks downintheir life

at present. They are asked what they would do if exposed to

greater or less risks than at present.

4.5.2.4. Contingent Valuation Questions

The fourth module pertains to the construction of the

contingent market. The contingent valuation (CV) exercise provides the basic valuation data that permits estimation of the

benefits of health risk reduction. The CV module has been

designed in segments.

The first segment concerns mortality, for which alternative

approaches to presentation have been developed. The first is the

excess deaths approach, which pertains to the increases in death

rates in various age groups because of some particular cause of

death such as cancer. The second is the life expectancy approach, which states the average age of death in the U. S. POPulation, and establishes contingent market programs that would

increase life expectancy. Bar charts that illustrate the probability of living beyond age 50 with and without the program are

introduced. The third method is life shortening. This is similar to life expectancy, except that it can be presented without

mention of probabilities. A bar chart illustrates the average

remaining number of years at five-year age intervals beginning at

age 50. Program effects can be shown by changing the height of

the bars. The last two methods devised to present mortality are

a lottery wheel and a card game. The lottery wheel has a

spinning arm with a pointer that comes to rest in a zone of the

board that corresponds to a given life experience. It is useful

in conveying the probabilities of occurrence of many life-health

situations. The card game involves the chance occurence of

drawing a card indicating that a sickness such as a heart attack

will occur. The respondent is asked about willingness to pay to

reduce the number of sickness cards in the deck.

In the second segment of the CV module, questions about

several kinds of illness of varying degrees of seriousness are

asked. Two types of contingent markets are utilized. In the

first, a disease specific approach is used in which disease is

mentioned by name. In the second, a health attribute approach is

used in which only the symptoms are mentioned.

In the next section of the CV module several specific and

explicitly depicted comparative life paths are presented, with

symptoms and illnesses of varying severities and different life

expectancies. Respondents are asked first to rank alternative

life paths according to their preferences. A hypothetical life

4-97
path endowment is postulated, and willingness to pay and accept

questions are asked, based on respondent rankings. The questions

are constructed so as to reveal the strengths of preferences in

choices involving severity of symptoms and length of life. These

tradeoffs are offered in terms of certainty prospects.

The following section explores how health valuations are

affected by the existence of risk. The respondent is offered one

life path with certainty and pairs of alternative life paths --

one better and one worse -- with various probabilities.

Respondents are asked about their willingness to pay for the

scenarios.

Willingness to pay questions are asked based on the life

path preferences. A base life path endowment is established and

programs that would improve or prevent deterioration of the

environment are offered. The program effects are linked to the

life paths. Linkages are not established between dollar bids and

probability statements. It would be possible, however, to apply

this contingent valuation structure to obtain statements of

willingness to pay for risk reduction in future work.

Based on the four module formulation and facus group

experience, refinement and development of alternative approaches

for each of the modules was undertaken. The approaches are

illustrated in the next four subsections. They provide the basis

for possible future field work.

4.5.3. ----- --,--,I First Module- Health ------ -- ------- Experience

The first module, health experience, develops the

information and preference context of the questionnaire. It

serves two research purposes. The first is to focus the

respondents' attention and research their references on the

subject of the survey and prepare them to give carefully thoughtout answers. The second purpose is to establish the respondents' health endowment and health habits as part of the explanation of willingness to pay responses to survey questions. The

questions encourage the respondents to link health status to the

behavior and activities of daily living. Their perceptions about

psychological well being and degree of control over personal

health reinforce the connection between health and behavior,

which will be important later in reflecting on the value of

health preservation or improvement.

Obtaining detailed knowledge of respondents' experiences

with specific kinds of life threatening illness is an important

part of the health appraisal framework. Detailed information

about specific health problems of interest in the survey

supplement the more general health status information obtained

earlier. The empirical framework integrates mortality into the

study of behavior towards risks to health and life. Some recent

theoretical contrib.utions have recognized that death has

important endogenous elements in life cycle choices, but the

4-98
present study goes farther than others in empirically integrating

mortality into the investigation of the value of risk reduction

in a life cycle context. It accomplishes this by making the

prospective life path of the respondent the basis for the contingent market good. The following abridged set of health status

questions 'was developed to meet these ends.

--------------- -- ------ Self-assessment of health status: ------

1. In your own opinion, which one of the following best

describes your current health status:

1Excellent 2 Good 3 Fair 4 Poor

-w--m- Belief concerning control over health: --------- -----w- -a-- ------

2. Which one of the following best describes the control

you have over your health?

1 There is little I can do because it is beyond my

control.

2 I can do .some things, but they have little effect.

3 My actions have a moderate effect.

4 My actions have a great effect.

-------- Detailed questions on health status: -m--e--- -- -----a ------

3. Are you unable to do certain kinds or amounts of work,

housework, or schoolwork because of health?

Yes No ---7----- ---------

If "yes" then 4.

4. Have you been unable to do this work for more than

three months? Yes -------a- No ---------

5. Does health limit the kind of vigorous activities you

can do, such as running, lifting heavy objects, or

participating in strenous sports?

Yes --------- No ---------

If "yes" then 6.

6. Has health limited the kinds of vigorous activities you

can do for more,than.three months?

Yes ------a-- No ---------

Questions about sick -------- e---e ---a VWdayz:

7. What conditions (such as specific illness and injuries)

caused you to'stayinbed?

4-99
8.

9.

10

How many of the days that you lost from market work did

you stay in he'd all or most of the day?

-e---e--- days

During the last year, how many days did you cut down

for as much as a day?

-------me days

What condition caused you to cut down?

General questionsabouthealth perceptions:

Definitely Mostly Don't Mostly Definitely

true true know false false

According

to the 5 4 3 2 1

health

professionals,

my health is

now excellent

I try to avoid

letting illness 5

interfere with

my life

4 3

Focus group experience indicated that respondents are

willing to answer these questions. They served their intended

purpose well, but consumed too much time in a conventional

interview context. For usesin a half-day, in-depth interview,

however., their use is feasible and deserves further consideration.

4.5.4. ------ Second Module- ------I ------ Health Costs and Defensive Measures -_--- --- --------- ---e-e--

.Much of the material in this module is very similar to the

modules on health costs and defensive measures already presented

in section 3. The earlier material will not be repeated here.

In addition to the earlier material, defensive measures toward

serious illnesses that have low probability risk are explored.

An illustration will be presented here of questions about

willingness to undertake changes in lifestyle to reduce risk of

serious illness. The illustration centers on diet.

4-100
Referring again to cancer probabilities, imagine you were

told by your physicianthatthe cancer life path is what you

had to look forward to --because of some condition he had

just discovered. He offers you a program, however, which

will give you a 50% chance of avoiding the cancer scenario

and getting the health scenario instead. His terms are

this:. stop smoking, stop drinking, and immediately adopt a

Special diet (not shown Here). Would accept the doctor's

program?

Yes ---------a No -__-_-----'

If yes: Are you confident that you would be able to

adhere to these terms for the restofyour life?

Very confident ----------------

Somewhat confident ----------------

Doubtful ---------------

Virtually no chance --------------eIf no: Suppose the doctor told you that you could be

----e-m certain of improving your prospects to thehealth

scenario. Would you accept the doctor's program?

Yes --------e No ---------

If no: What is the most difficult part of the doctor's

program for you?

Rank them 1, 2, 3.

Diet ----m--e

Drinking ---------

Smoking ---------

If Diet: Would you accept the doctor's program if it

only required the Special Diet?

Yes --------- No ---------

If no: Would you accept the doctor's program if there

were no dietary restrictions at all?

If yes: Repeat above.

If no: [Eliminate second most difficult part of

4-101
doctor's program and repeat.]

Building on this illustration, iteration on defensive measures could be used as part of the contingent valuation modules

considered below in section 4.5.1.3. Hypothetical future life

experiences would be ranked from worst to most desirable. The

respondent wold then be endowed with the worst path and asked to

bid for more desirable alternatives. Bidding would be in terms

of defensive measures involving smoking, drinking, diet and

exercise. Iteration would be used to determine how much averting

behavior would be tolerated in order to improve life prospects by

various amounts. Some experimentation with uncertainty could be

introduced by setting the probability of payoff equal to 50

percent. The respondent would be asked how confident he is of

being able to stay on the various programs, and which parts of

the programs are the most difficult. The latter responses would

be used in further iterations by e.liminating the most difficult

parts of a rejected program and asking if it would then be an

acceptable price to pay for a preferred life path.

The rest of this iterate-on-defensive-measures approach

entails eliciting willingness to pay (WTP) in dollars for the

programs, based on their careful thought about sacrifices made

for measures they are already taking.

4.5.5. -e--m Third Module- ------A Risk Perception and Risk Behavior --me ----- ---- --- ---- --------

A major result of work with focus groups is recognition of

the need to carefully educate respondents in the basic concepts

of probability and risks. The procedures, whose principles are

discussed in detail in section 4.4, are necessary if respondents

are to be able to respond intelligently about low probability

environmental threats to life and health.

It is furthermore important to delve into people's general

risk perceptions because they underlie judgements and choices in

particular risky situations. The risk percetions help to explain

choices in contingent markets for health risk. Asking respondents to reflect on these attitudes brings them more clearly to

mind, improving the quality of contingent valuation responses.

Examination of people's actions in various risky situations

reveals attitudes towards risks, just as do their prior

perceptions of risk. These risk attitudes, formed over long

periods under innumerable influences, are important determinants

of behavior towards health risks, and are therefore likely to be

important to analysis. Responding to risk behavior questions

also helps prepare the respondent give well considered contingent

valuation answers.

It is thus apparent from the focus group experience that a

major experimental effort is required to develop teaching ,devices

that will permit the effective use of probabilistic contingent

4-102
markets in health. Basic drills for teaching probability are not

presented ,here. The defensive measures module contains some

information on risk behavior which could be extended. Building on

the present module, games have been devised using a lottery wheel

and cards directly in contingent valuation questions as will be

reported on in Section4.5.6.

The presentation in the present section is limited to

questions on risk perception, which are as follows.

---- ---- Risk perception ----A relative to past: ----m--e -- -al. Relative to your parents' experience, the risks to

health and safety you are faced with are:

1 Much less

2 Somewhat less

3 About the same

4 Somewhat greater

5 Much greater

------- --------- --- ------- General awareness and concern:

2. Risks to health and safety come from a variety of

activities, substances and technologies. Which causes

the greatest, second greatest and third greatest

concern to you? (Put appropriate number in each box.)

1 Crime 8 Power lawn mowers

2 Swimming pools 9 Smoking

3 Nuclear power 10 Motor vehicles

4 Alcoholic beverages 11 Food preservatives

5 Pesticides and 12 Asbestos

herbicides 13 Water pollution

6 Home furnaces gas 14 Job risks

7Airpollution 15 Other (specify) -----

[ ] Greatest concern

[ ] Second greatest concern

[ ] Third greatest concern

------ Ranking questions -_------ ---_- about causes of concern about risks and ------ _- ------- -w-w- --e-- ---

---- also about household ----- ---- ---_- Rroduction ----- -_-- -- of health and safety: ------ --- -----

3. Much has been said about various risks to health and

safety. Using a scale of 1 to 10 going from least

risky to most risky, enter the number you feel best

describes the risk.

4-103
Swimming Nuclear Alcoholic Pesticides Home Air

Crime Pools Power Beverages and Gas Pollution

Herbicides Furnace

[ 1 [ I [ 1 [ 1 [ 1 [ 1 1 1

Power Motor Food

Smoking .Vehicles

Water Job

Lawn Preser- Asbestos Pollution Risks

Mowers vatives

[ I [ 1 [ 1 [ 1 [ 1 [ 1 [ I

4. To what extent are the risks knownbypeople exposed to

the risk? Use the following scale.

risk level risk level

known precisely 12345 not known at all

Knowledge [ ] (Enter the number 1,2,3,4 or 5)

5. To what extent through your own actions can you control

exposure to the risk? Use the following scale.

exposure. can't be exposure can be

controlled at all 12345 completely controlled

by individuals by individual

Exposure control [ ] (Enter the number 1,2,3,4 or 5)

6. To what extent can you by personal efforts and use of

available resources control the outcome if you are

exposed to risk? Use the following scale.

outcome can't be outcome can be

controlled at all 1 2 3 4 5 completely controlled

by individuals by individual

Consequence Control [ ] (Enter the number 1,2,3,4 or 5)

This set of questions, while effective when used in a focus

group ,session, would be too long for a door to door survey. US8

of these questions in a half-day, in-depth interview settfng

would be effective, however.

4-104
4.5.6. ------ Fourth Module, -,-,-,A _-_--- 'Contingent Valuation Questions --- ------a-- -------_

4.5.6.1. Mortality

Several methods of presenting mortality risks were developed

and tested in focus groups. Five methods are-reported on here:

excess deaths, life expectancy, life shortening, use of a lottery

wheel, and use of a card game.

Excess Deaths

The following sample illustrates the excess deaths approach

-- possibly the most easily understood idea of mortality risk:

We have all used the term "epidemic" to describe

the outbreak of a disease. An epidemio is said to

exist when more people develop an illness -- measles,

flu, for example -- than is expected under normal

conditions. Similarly, the term "excess deaths" can be

used when more people die from a certain illness or

condition than is normally the case.

For example, suppose that on average, 1000 people

die every year in fires in the United States. If 5000

people were to die this year in fires, those additional

4000 deaths could be thought of as "excess," that is,

more than could normally be expected to occur. Some

scientists warn that pollution of the air and water

cause excess deaths in the population today.

Q* How much would you be willing to pay to eliminate one

excess death due to air pollution?

Life Expectancy

Various approaches were tested to present the idea of life

expectancy, changes in life expectancy, and people's willingness

to pay to get improvement or avoid decline. One type of life

expectancy question offered a rather elaborate contingent market

to the respondent. The following example contains explanatory

narrative that relates life expectancy to cancer, and illustrates

a life path for a person of age 50 by means of the bar charts.

Of all the possible consequences to human health

arising from pollution problems, the threat of cancer

may be the greatest source of concern. It is the only

major cause of death which has continued to rise since

1900. It is difficult to determine how great a role

4-105
pollution plays in causing cancer. People differ in

age, place of residence, occupation, health status, diet

and lifestyle, and all of these factors together

influence the probability of developing cancer.

Please look the first set of bars (see figure 4-7).

These bars illustrate the overall probability of a

person surviving from the age of 50 to the ages shown.

For example, the likelihood of living to age 80 is

about 48%, to age 85 about 308, and so on. (Of course,

it is impossible to predict how and when a person will

die; many factors will influence that event. The

probabilities shown here are national averages)

Now look at the second set of bars. They show the

probabilities of surviving to advanced age, but also

the changes in the percentages if cancer were

eliminated as a cause of death. Without cancer, the

chances of living to be 80 or 85 would increase to 55%

and 37%, respectively.

Suppose that it were possible to devise programs

that would eliminate all cancer.

Q- How much would you be willing to pay for the programs?

Maureen Cropper comments that asking a person to value

changes in life expectancy is somewhat ambiguous and does not

necessarily measure what one wants to measure.

represents conditional probability of death at age

Suppose Dj

j and

resents the probability of surviving to the beginning of qi!li:

year given that one is alive at age t. It follows that

(4-43) qj ,t * (l-Dt+l) .*.(l-Dj-1)' j > or - t.

Furthermore, life expectancy at age t can be shown to be

(4-44) Summation of qjt from j - t+l to T.

Equation (4-44) indicates that a change in life expectancy

is ambiguous in the sense that there are many sets of changes in

's consistent with a given change in life expectancy.

2FthSdrGore

She suggests

it seems that what one wants to value is the Dj's.

that it might be better to ask people to value a

change in the conditional probability of death at various ages.

Life Shortening

The life shortening method of presenting mortality risks

to respondents is similar to life expectancy except that it does

not require a discussion of probabilities.

4-106
% 100

90

80

70

60

.~.1

‘50

40

30

20

10

0

Figure 4-7

PROBABILITY OF SURVIVAL WITH AND WITHOUT THREAT

OF CANCER (FOR LIFE EXPECTANCY QUESTION)

I I

.

T ’

1 I Present conditions

Cancer eliminated ,..’

50 55 60 65 70 75 80

I

85 90 95 100

Age

4-107
The absence of probability from the discussion makes this

approach easier to understand than the life expectancy approach.

Also it is possible to use one chart to illustrate remaining life

for people in every age group. This makes it easy to tailor the

question to the endowment of each individual respondent. The

remoteness of the contingent market product for many respondents

remains a problem, however.

An example of the life shortening approach is as follows.

Consider how many more years you can expect to live once

live once you reach the age of 50. Of course, you

would hope to live as healthy and as long a life as is

possible. Please look now at Figure 4-8, which

depicts in graphic form the national averages

for remaining lifetime, expressed in years. Note for

example that a 50 year old can look forward to 16

more years, etc.

Q. How much would you be willing to pay for a program that

would extend your life by two years?

Lottery Wheel

The lottery wheel is the most graphic portrait of mortality

experience developed so far. It is a device that involves the

respondent in an activity that builds up an idea of a person's

risk of death under varying conditions.

The prototype wheel is two feet in diameter and consists of

a wooden arm spinning on a skate boardwheelbearing affixed to a

sheet of plywood. Nails, equally spaced at the periphery, divide

the circle into 90 segments. A piece of flexible plastic at the

end of the arm provides Las Vegas- type noise and forces the arm

to stop within a single segment (between two nails). Paper

overlays depict a wide variety of pie charts that show age of

de.ath and health-disease distributions. The pie charts depict

different size segments that correspond to different likelihoods

of being in good health, having heart disease, etc., at various

ages. The pie charts are constructed to reflect the probability

distribution, the population within five year intervals beginning

at each decade of life. A sample is shown in Figure 4-9.

Contingent market goods were constructed for testing in

focus groups by depicting the mortality expectation of a 50 year

old person with and without cancer rfsk. This is done by showing

the actual expectations of the person in one ring of a pie chart,

and the calculated expectations of death with cancer removed in

another ring. Repeated spinning of the "wheel of death" gives

the participant a sense of improved prospects in the absence of

cancer. When the participant is adequately prepared, willingness

to pay questions to get the without-cancer lottery are asked.

Testing of the lottery wheel in focus groups indicated that

4-108
it has a great deal of promise for future use in both mortality

and morbidity contingent-valuation work.

Card Game

As probabilities become smaller, the probabilities generally become more difficlt for resopndents to interpret. Some

people however have acquired a sense of small probabilities in

connection with work or leisure or activities. People who play

cards are examples of such people.

An example making a link between card games and

probabilities encountered in health risks follows. Unexpected

painless mortality from heart malfunction is a health risk that

carries quantifiable probabilities for persons of given age,

general health and personal characteristics. A contingent market

can be established by proposing a card game to persons in various

risk categories, with hands dealt from a deck in which the probability of heart malfunction corresponds to the propbability for

people of their category. Respondents are then asked how much

they would pay to reduce the number of heart malfunction cards in

the deck.

4.5.6.2. Morbidity

Several different approaches were developed for posing

contingent valuation questions on serious morbidilty. The

approaches are discussed in this section.

Specific Disease 'Approach

In the specific disease.approach, diseases are named, allowing for the possibility for semantic effects in the valuation

of risk reduction. A bronchitis question is illustrated in the

following question.

Chronic bronchitis is an illness affecting about

3 percent of all adults in the United States.

Bronchitis is an upper respiratory disease

which causes coughing andchest pain. In

addition to physical discomfort, many people

with chronic bronchitis become discouraged and

depressed about this illness. In addition to to

cigarette smoking, air pollution is acause of

chronicbronchitis and it also aggravates the

condition. Treatment of chronic bronchitis with

medicinesis helpful but tends to create side

effects.

4-109
Figure 4-8

REMAINING YEARS OF LIFE AT VARIOUS AGES

(FOR LIFE SHORTENING QUESTION)

Years

remaining 28

24

20

16

12

8

4

0

50 55 60 65 70 75 80

~:~~.~~:~<~~~~~~~~~~ :.:<.:.::::...:::.:.:.:: .:...:.: .~~..:~.:~~~~:~:. .-. . ..A.. ..........A.... ....... #$$.:+:.:.:

n

.,*:.y,.:.::w ..F<<.x.:.:.:. ..2.x .. . ... . .....- .*.:.~..~~..:.::~:.:.. :~<.:.>:.>..:.:.: <.~yp.V.V.%~. ...A...v,?xfi::.: .I..>...i... ...5’...: . . .,._. . .

85

Age

4-110
Figure 4-9

PIE CHART FOR MORTALITY LOTTERY WHEEL

Age 80 - 85 ,

55 %

4-111
How much would you be willing to pay per month in

to eliminate the risk of bronchitis?

Aside from the semantic effect of mentioning a specific

disease, a problem in this question is the precise amount of risk

that is being eliminated in the contingent market.

The following question, concerning cancer, combined illness

with substantial risk of death. The death risk was presented

implicitly to the respondent by revealing the overall experience

in the U.S. population.

Chemicals in the environment, in the air, in water, and

in some foods are believed to be significant cause of

cnacer in the United States. These cancers include

cancers of the lung,'kidney and liver. Today about half

of all cancer patients die of the disease and about

half survive. A great many cancer patients, both those

who die and thosewho survive, have to undergoradiation, chemotherapy, or surgery, often in combination, which formany is a highly uncomfortable and

emotionally trying experience.

How much per month would you be willing to pay to

eliminate the risk of getting cancer of the lung,

kidney, or liver or some other organ?

General references to the experiences of the entire U.S.

population are limited by the fact that they do not give

respondents the kind of graphic description of illness that

assists them in judging the value of removing or lowering the

risks they face. This health attribute and life path approaches,

which follow, add the desired element of realism to the

contingent market product.

Health Attribute Apporach

The health attribute approach focuses entirely on the

effects of diseases and avoids naming the underlying causes.

Semantic effects can be tested by listing the symptoms caused by

a disease in one survey and actually naming the disease in

another, comparable survey. An example of the health atrribute

approach follows.

Physical discomfort effects of illnesses include

coughing, pain with each breath, and other effects. I

4-112
will ask about each effect separately. Each.of these

effects would continue for many years, unless the

question says that is it for several months.

a. Frequent, persistent coughing $ --m--e-- per month

b. Chronic throat irritation $ -e--v--- per month

C . Gripping pain with each breath $ a------- per month

d. Itching and smarting of eyes $ -------- per month

e. Frequent nausea, feeling of need $ -------- per month

to vomit for several days each

week for several months

f. Whole body discomfort, feeling $ -------- per month

rotten all over for several

days each week for several months

It was discovered in focus group experiments that numerous

questions in quick succession are not conducive to carefully

considered answers. Instead, answers may become rather -mechanical unless broken up with intervening discussion and preparatory

thinking on the part of the respondent. This consideration limits

the number of bids that can accurately be obtained.

4.5.6.3. Life Path Approaches Combining Morbidity and Mortality

Life path approaches represent a progression towards the

creation of a realistic setting in which respondents can relate

to health problems that are either current, possible in the next

few years, or in the distant future. The approach is to

construct several parallel life paths with a number of common

elements and ask contingent valuation questions on each.

Respondents who might not be able to value an isolated event such

as dying two years earlier in 40 years may well be able to

express a preference for one life path over another and assign

dollar values to the preference.

Both morbidity and mortality considerations are embodied in

the life path scenarios. Consideration was given to measuring

interactions between them and valufng tradeoffs. Scenarios were

develo.ped in terms of certain alternatives and in terms of

uncertainty, as will be described in this section.

Certainty Scenarios

Table 4-2 shows three alternative life paths, characterized

by either cancer, emphysema or heart attack. They differ substantially in the overall quality and length of life that is

4-113
Table 4-2. LIFE PATH SCENARIOS

Age Cancer Scenario Emphysema Scenario

----------------------------------------------------------------

50 Good Health Good health

55 Symptoms (which probably

began. earlier) become

apparent: Loss of energy

(e.g., climbing stairs

tires you out; shortness

of breath, difficulty in

breathing. Breathing

difficulties result in

increasing work absences.

60 Relative good health but Symptoms become

Symptoms become noticeably increasingly severe.

reduced from that at 50. Health deteriorates to

the extent that early

retirement is necessary.

65 Health reductions continue Lung deterioration

both with no serious reaches point where you

illnesses. You continue intermittently must use a

able to do a full day's portable bottled oxygen

work, but you retire at age supply to reduce

65. breathing difficulties

while walking.

70 Cancer symptoms become You become bedridden and

apparent, and chemotherapy require continuous bottled

is initiated. Side effects oxygen to reduce

include nausea. You feel breathing difficulties.

the need to vomit several

days each week. There are

periods of improved well

being, but on other

occasions you feel rotten

for days at a time.

74 Chemotherapy and side

effects continue, but

otherwise you lead a

normal life.

Death due to heart

failure.

76

78

Cancer spreads throughout

your body and death occurs.

(Third scenario presented on next page)

4-114
Table 4-2 (continued)

Heart Attack

Age Scenario

__--___----__---__-----------------------------------------------

50 Good health

55

60 Relative good health but

noticeably reduced from

that at age 50.

65 Health reductions continue

but with no serious

illnesses. You continue

able to do a full day's

work, but retire at age 65.

70

74

76

78

Still no serious illnesses

Sudden and painless death

occurs due to heart

failure.

(End of Table 4-2)

4-115
offered. The example illustrates the certainty approach to life

path analysis.

Respondents are asked to rank the life paths in order of

desirability and express a willingness to pay to avoid the less

preferred life paths. Focus group experience indicates that this

is a promising method of obtaining values. It imparts reality to

the contingent market alternatives that are offered.

Possibilities exist to tailor the scenarios for special

purposes. Distinct symptom modules 'form the life path building

blocks. A set of life paths can be built from the symptom sets

and combined with different ages at death. The life paths can be

ranked and values expressed relative to a base case path. The

results could be used in policy analyses that detail the disease

effects of illness by symptom and age of death more completely

than at present, but they would also be useable in present state

of the art policy evaluations.

Uncertainty Scenarios

The following survey segment substituted probabilities of

obtaining the life paths for the certain alternatives of the

previous questionnaire. A simple probability display device was

used to convey the idea of risks and help the respondent make

probabilistic choices.

The example below illustrates the questionnaire approach.

Each of us faces an uncertain future concerning our

health and length of life. Knowledge about health is

increasing, however, and we are learning more about how

we can influence our own prospects. Public health officials, are learning more about what of government policies

can improve the health and life expectancy of the general

population.

We are very interested in your views about the

value of health improvements. I would like to ask you

some questions about a matter of importance to

people- -how you feel about the uncertainties and risks

to your future health.

The life path scenarios presented above in Table 4-2 would

then be combined with a probability analysis to see how much

people wold be willing to pay to reduce the risk of the more

undesirable scenarios.

4-116
4.5.7. -- --------- Implications

The proposal for the in-depth four module approach that has

been developed in this section grew out of findings from focus

group experiments. For example, early focus group work

indirected respondents had difficulty grappling with life threatening illness in a short interview. It became apparent that a

major experimental effort would be required to devise effective

probabilistic contingent markets in health. Several experimental

games were tested that may develop into useful approaches in

future work.

,Equally difficult was the task of getting respondents to

think seriously about contingent payoffs defined far into the

future. Younger respondents in particular found it was difficult

to place any value in an extra year of life or health at age 70

or 75. Because certain benefits of environmental improvement are

likely to be of this type, it will be particularly important to

address the problem of deferred benefits in future work.

The role of the participant's own health endowment became

the subject of thought during this early period. Two objectives

became apparent. One was to have a standard, well defined

contingent product for which all respondents would bid. The

second was to make the contingent market as realistic as possible

by relating it to the respondent's own experience. This

eliminates the need for the respondents to try to imagine having

a hypothetical endowment and then imagine hypothetical departures

from that endowment.

The first module of the four module approach, health

status, developed the methods required to establish the

respondent's endowment, to tailor contingent market goods to the

individual's own circumstances, and to start the respondent to

think about health preferences that have usually not received

much attention. The second module, defensive measures,

investigates and records the activities that people take to avert

illness or threats to life and health. These activities include

health practices, changes in life style and also expenditures on

market goods that contribute to health. Risk perception and risk

behavior in the third module. Its purpose is to convey an

.understanding of probability that is adequate to understand and

respond to questions that elicit the value of health improvements

that are plausible results of environmental policy. The work of

the first three modules is brought together in the fourth module,

contingent valuation. Contingent market health products,

realistically tailored to each respondent's health endowment, are

formulated. Respondents are assited in thinking carefully about

the value that these health products would have in their lives,

and to express their willingness to pay for them. Program

effects are presented in terms of alternatives that can be

obtained with certainty, and also as alternatives that will occur

4-117
only with various stated probabilities.

Risk age, life shortening, life expectancy, and lottery of

life approaches are used in constructing life path scenarios.

Further research is necessary before the most effective

approaches can be identified.

In life path scenarios, which are needed and promising,

methods and information for relating to environmental effects

needed to be developed. The visual approach is one effect on

death rates. Even apart from the latency problem, a person with

increased.exposure to pollutants faces a stream of altered life

path prospects from different points in the future depending on

when the disease is contracted. The problem exists when the

probability of contraction of disease is independent between time

periods and it also exists when there is a latency period, which

merely complicates slightly the estimation of probabilities of

when the disease will be contracted.

Future research needs to address two closely related

concepts, as follows.

Level of Discrimination

Intuitively one would expect that individuals could value

some risk reductions more meaningfully than others. For example

the probability or risk of death could increase from almost zero

to l/6 (if one should choose to play Russian Roulette) or it

could increase from 1.1/1,000,000 to 1.8/1,000,000 (odds perhaps

associated with an increase in an environmental trace

concentration of some toxic substance). Somewhere between these

extremes, an average respondent likely would lose the ability to

discriminate between one risk level and another. Future

research would attempt to approximate this discrimination treshold.

Level of Complexity

There are other complexities in addition to discrimination

which make it difficult to distinguish between and ultimately

value one risk versus another. Pertinent information is helpful

in this regard. Increased information beyond, some point,

however, has less value and eventually Ls counterproductive.

Pertinent variables include:

Age specificity

(present age and age of death)

Disease specificity

Cause of death

Cause of the cause of death

(risk factors such as alcohol, obesity, air pollution)

4-118
Level of health or morbidity

(physical status, level of disability)

Thus, at one extreme, a respondent might be given virtually

no information prior to being asked to value a change in health

or death risk. At the other end very explicit life paths,

tailored to the individual, could be provided. Future research

should identify minimum information levels needed to obtain

meaningful contingent valuations.

4-119
4.6 SUMMARY AND CONCLUSIONS ON SERIOUS ILLNESS

In section 4 attention has been directed towards serious

illness, including risks to life. The work builds on the investigation of the valuation of light symptom reduction, reported

in section 3.

Section 4.2 addressed the problem of health measurement.

It contained a discussion of different approaches to health

measurement. The importance of recognizing that health is a

state of mental as well as physical well being was emphasized.

Self assessed health status was found to be the most widely used

health status measurement technique. While this approach has

limitations, it was seen to have an important role to play in

health risk reduction benefit research. Its importance stems

primarily from the role that self-assessment plays in the

perception of benefits from improvements in health prospects.

Because health is a multi-dimensional condition, it is

necessary to supplement self-assessment with other measures of

health status. Further refinements in health status measurment

are needed, including the possible use of the health risk

assessment as an interactive health measurement tool.

It is in the valuation of serious illness and mortality

that the fragmentary nature of much of the existing literature

related to health values becomes most apparent. Progress has

been made in valuing aspects of these experiences that are often

more important than those that can be measured in terms of market

transactions. An important research result reported in section 4

is the integration of serious illness and death as a single life

experience. This integration is achieved by placing the experience in a life cycle setting.

Section 4.3 modelled the basic context in which people make

decisions regarding serious threats to health. A person's position in his own life cycle is seen to be the relevant decision

making context. People are seen to make decisions about health

over their lifetimes, and life is viewed as a stream of experiences involving widely varying degrees of healthiness and sickness and uncertainty concerning length of life. The major challenge that arose out of this approach was to construct contingent

markets that preserved the preference-formation and value-determining context. Isolating small parts of the context in the

interest of simplicity was seen to be theoreticaliy problematic

and led to emphasis on life path scenarios.

Section 4.4 is another source of theoretical guidance to the

development of the approach of this study. This section brings

utility theory to bear on the problem of valuing small changes in

events that are thought of only infrequently and involve low

probabilities of occurrence. The model developed in this section

4-120
unfolds in a series of theorems. Several theorems address the

problem of stimulating respondents to think carefully about their

preferences. One theorem states that the closer the sum of money

is to the (unknown) value of the program benefit, the harder the

respondent will think about the choice. Iterative bidding begins

with a rather arbitrary starting point. In subsequent bidding,

however, the theorem is applied by taking account of previous

completed bids on related programs. The starting point is made

identical or close to the final bid on the similar previous

program to encourage careful thinking from the beginning.

An important objective is to realistically rel'ate the

contingent market good to the respondent's own circumstances.

This means tailoring the good to the respondents's endowment. An

implication of the theorems is that introspection about preferences is much more effective when this is accomplished, Much

progress has been made in tailoring contingent market goods to

individual endowments. Nevertheless, more research is required

in this area.

Based on the results of the preceding sections, an intensive interview approach to contingent valuation work, reported in

section 4.5, proposed a four module interview scheme. The interview is designed to be conducted with from six to ten people and

to last about four hours including breaks. The intensive

encounter is necessary because of the great difficulty of

achieving its central task--obtaining values of events that

entall small changes in small probabilities.

The health status module is the first module. It establishes health endowments of respondents and begins the process of

careful scrutinizing of preferences. Self-assessment was judged

to be an appropriate method. Its brevity is a virtue in survey

work, and subjective perception of health is an important

determinant of willingness to pay. Detailed knowledge of respondents' symptoms or chronic ailments appropriate to the CV

framework were judged to be essential. These health status

questions served as explanatory variables as discussed in the

health status literature, but they had other functions as well.

The questions established the respondents' health endowments,

permitting tailoring of the contingent marke.t product to the

circumstances of the respondent and, as explained in section 4.4,

stimulating maximum reflection of the respondent on his preferences.

The second or defensive measures module examines averting

behavior to preserve health. Averting behavior includes expenditures and also activities not measured by market transactions.

Efforts people are willing to make to achieve better health

prospects are probed, with a view to placing a monetary value on

them.

The third or risk perception and risk behavior module begins

by teaching respondents basic notions of probability as related to

their everyday experiences. It then obtains information about their

4-121
perceptions of and attitudes towards risk in a variety of

situations. Next it conveys an idea of the kinds of probabilities

that are involved in matters that concern their health.

The fourth or contingent valuation module establishes contingent markets in health. Hypothetical life experiences involve

both quality and length of life that people are asked to evaluate

in comparison with their own prospects. Excess deaths, life

expectancy, life shortening, a lottery wheel and card games were

among the devices developed to present alternatives on which to

bid. The module features evaluation of alternative life path

scenarios values in a certainty and then in an uncertainty

context.

It is believed that the survey aproach developed in section

4, and the extensive preparation for obtaining expressions of

willingness to pay described in the four proposed modules,

constitute an advance in survey research on the value of heatlh

improvements, and that further empirical applications are needed.

4-122
APPENDIX. MANIPULATION OF LIFE TABLES: CANCER ILLUSTRATION

Numerous studies have estimated the effects of environmental

and behvforal stressors or interventions on life expectancy.

Limited results of uncertain epidemiological and other studies

are described in following sections. Results based on assumed

elimination of a specific reported disease or other reported

cause of death are more illustrative. The following discussion

describes results of mathematically changing the level of deathcausing cancer while allowing other competing health risks to

proceed at the same rates for each age interval. The results

indicate that total removal of cancer would increase the

percentage of the population reaching age 80 from 44.5 percent

to 52.9 percent, or increase life expectancy by 2.7 years. This

conclusion avoids all controversies regarding causes of cancer.

Further, this illustration utilizes available data for

female deaths in 1964. The approach could be applied as readily

to more recent results for another population category.

Table A-l presents the mortality experience of an imaginary

sample of 100,000 females subject to the death rates which prevailed in 1964. Column 1 lists.five-year age intervals, minus the

first five years of life. Columns 2 through 4 report deaths for

several of the major causes (neoplasms, cardiovasacular diseases,

motor vehicle accidents, and other violence). In column 5 all

other deaths are reported and total deaths appear in-column 6.

The final column contains the number of persons of an age period

who survive to enter the next age group. Thus, of 100,000 born, a

total of 2,107 do not survive the entire first year; the forces of

mortality then act on the remaining 97,893 one-year olds, of whom

340 additional females do not survive the fifth birthday.

In Table A-2 the numbers of deaths (from Table A-l) are

expressed as fractions of the total numbers of survivors who

entered the age interval. Out of 100,000 newborns, 7 die of some

neoplasm before the end of year one, for a probability of dying

of 0.00007. The probabilities of death for the causes shown are

then summed in column 7. The number entering the interval for

the 1.0-4.9 age bracket is then

100,000 - (100,000 x 0.02107) - 97,893.

Another way of portraying the life experience is to focus on

the chances of surviving from one age to another, rather than on

the prospects of dying. Table A-3 contains the probabilities of

surviving from one age (x) to another age (y) for selected ages.

To determine the chances of a 20-year old surviving to age 55,

for example, first look at column 1, the goal age, then read

across the table to the appropriate base age of 20. The probability is shown to be 0.9137. This is calculated by dividing the

number of survi.vors to age 55 by the number of living 20-year

4-123
olds: 88,583 by 96,954. By this formula, the likelihood that a

lo-year old will live to age 85 is 0.2792.

At this point it is possible to demonstrate the effect of

removal of a specific cause of death on survival probabilities,

while holding constant the death rates due to other causes. In

table A-4, when the probability of dying of cancer is reduced to

zero, the numbers of people surviving to an older age increases.

This is calculated in the same manner as in table A-2; i.e., the

number entering the 1.0-4.9 age interval is:

100,000 - (100,000 x 0.02100) - 97,900.

Compare this figure to the corresponding number in table A-2; it

represents an increase in survivors of 7 per 100,000. A comparison of the number of survivors to age 75 reveals an increase of

67,195 - 59,237 - 7,958.

Note that in the absence of information on disease

interaction, the technique used in these calculations probably

results in an incorrect estimate of the expected survivorship.

As Preston, Keyfitz and Schoen (1972) point out, pneumonia, for

example, may develop as a complication resulting from another

illness, and increase the probability of death from the original

illness. Eliminating pneumonia might result in 'an incorrect

decrease of deaths from other causes.

In table A-5, the new probabilities of survival, cancer

threat removed, are listed. In a comparison with table A-3, a

20-year old's chances of surviving to age 55 are increased from

0.9137 to 0.9402. In other words, the fraction of the population

surviving from age 20 to age 55 with the eliminationofcancer is

94 percent. In addition, the fraction of the population

surviving to age 80 increases from 44.5 percent to 52.9 percent.

Interpolation of these results indicates an increase in life

expectancy of 2.7 years.

In table A-6, the new probabilities of survival are con'-

verted back to the numbers of deaths that would occur ateach age

interval, as in table A-l.

In tables A-7 to A-9, a scenario of altered mortality

resulting from halving the cancer death rate is presented

tables A-10 to A-12 portray the "life experience" with a doubling

of the probability of dying of cancer. All six of these tables

employ the same mathematical technique used to represent total

elimination of cancer.

4-124
Table A-l. NUMBER OF PERSONS DYING (OUT OF 100,000 AT BIRTH) FROM

ALL CAUSES V.S. FEMALES, 1964

Age

0 - .9

1 - 4.9

- Number

Cudfo- Hato+ Vch.+ fill Other Entering

Neopl

-

arms vrsculu Other Viol. + Unknown Total Interval

_.---- &

t2 * 79 2009 2107

9

s - 9.9

IO - 14.9

is - 19.9

109 10s 340

17 7 5 182

51 60 IS0

130 -es 267

20 - 24.9

2s - 2X.9

7

33

33

28

33

42

67

.lqs

245

426

640

1017

1241

157

i935

2050

2oa3

1854

1086

7

.

l .21

19

,

.42

30 - 34.9.

3s - 39.9

.- ..I IlO-.

200

400 44.9

1so

140

152

163

166

114 348

1Sl 423

‘210 i. “a07

,377 885

ss4 l 1296

45 - 49.9

so - 54.9

5s - 59.9

60 - 64.9

350

.

59s

1067

.

1736

\

2967

177 471 1933

178 617 2879

197 786 3990

&S - 69.9

70 - 74.9

73 - 79.9

00 - 84.9

85 - 89.9

90 - 94.9

204 ' 1027‘ 5175

*z7 13s 8359

278 1719 11222

35s 2044 14690

.

47s 2301 17364

9s - 99.9

I

. 543

i81

4a34

717s

101/3

12734

i2s73

6287

2095

580 2071 16310

240 IOZS 8ZSS

97 345 2718

1OrX~OO

100000

97843

9755s

97z71

97931

9aqss

96606

96183

955j6

94691

4339s

91462

88583

8439s

78818

7OA59

c

59237

44547

27103

10873

/ 271e

b-125
TABLE A-2. PROBABILITY OF DYING FROM SELECTED CAUSES

Numbew

We Entering

Intemml Interval

O-.9

l-4.9

S-9.9

10-9l4.9

m-19.9

20-24.9

25-23.9 -

m--34,9-

35.39.9

40-44.9

45-49.9

SO-34.9

S-59.9

60-64.9

65-69.9

70-74.9

75-79.9

80-64.9

8sa9.9

90-94.9

95-99.9

1 OQOOO

?78?Z

97553

915irl

97221

96954

96606

96183

95576

94691

933%

91462

08583

84593

78818

704s9

39237

e

44547

27183

10873

2718

Neapl asms

0.00007

0.00034

0.00034

0.00029

0.00034-

'0.00043

0.00069

0.00140

0.00256

0: da4SO

0.0073?

0.01112

0.014s7

O.OlB64

0.02455

0.02909

0.03483

0.04162

0.03995 -

0.04994

0.06659

Mot or VeCl .

Cudi 0’ + Othap

VISCU1 ar Vi oi encm

0.00012

0.00009

0.00007

0.00011

0.00020

0.00043

0.00067

0.00114 *

0.00209

0. oos?o

O.OQ637

0.01167

0.0193f

0.03307

0.061S3

0.10183

0.17lis

0.29586

0,4&Ss

0.57822

0.71079

0.0007?

o.oo111

0.00069

0.00OS2

* 0.00134

0.04155

0.00245

o-. OQ 1 SE3

.

0.00171

0.0017s

0.00190

O.OQl%

0.001239

0.00241

0*0030 1

0.00395

0.00599

0.01066

0.02134

0.02667

0.03s69

All Other

+ Unknown

0.02009

0.00193

0.00077

0.00062

‘.

0.00087

0.00118

O.OOtS6

o.oo2la

. . . .

O.QO290~

o.oos74

0: 00504

0.00675

o:ame7

0.01214

0.01717

0.02440

0.03543

O.OSlbS

0.07619

0.09519

0.32693

.

.

Totri

0. OZlOi

0, m34i

~.00187

0.001s4

0 l 00275

0.003s9

0.,00438

0.00631

0.00?2&

0.01369

0.02070

0.03148

0.04504

0.06827

O.10605

0.15927

o,.z4799

0. x979

0.60001

0.7Sm32

1.09909

4-126
TABLE A-3. PROBABILITY OF SURVIVAL FROM ONE AGE (x) TO ANOTHER AGE

(Y)

.

Nlmr Agk lx)

g’(y)Entwinqfnterwl0 10 to so 40 so 60 70 80 90

--w .--m m-- - -

0 100000 Loo00

1

s

10

1s

20

2s

so

ss

44

IS

50

55

97371 1.0000

969%

96&a

96183

is37b

94491

0.97a9

0.97s

a.%7

0.9722

0.96%

0.9tif

0.9618

o.%sa

0.9469

0.9340

0.91u

o.is!n

0.9985

0.99s

0.992l

o.om LOOM -.

914&z

aim

04393

089816ei

0.972s -

0.992

0.93%

0.9w7

LOOOO’

0.9964

0.9920

0.9esa

oA7

0.9&B

0.9434

0.9ls7

0.9937

0.984s l.ooo0

0.9710 0.9863

0.9soo 0.9&T? 1.ooa0 .

o.mo 0.935s 0.9685

.

.

60

6s

70

73

a0

as

90

9s

100

0.4439 0.8648 0.m 0.4795 0.8934 0.9249 l.oooa

- ,

7118 0.7842 0.40% o.am

0.7267

0.6110

0.4s%

0.2ao4

0.112l

0.0200

0. OQOO

0.81%.

0.7326

OAls9

0.4631

0.2426

0.1130

0.0243

0.0000

0.4324

0.7441

0.62s6

0.4704

0.2871

0.1148

0.0247

0.8618

0.7704

O.MTI

0. (071

0.2972

0.1189

0.0297

0.0000

0.4317

0.4329 l.Oooo

0.7003 0.8447

70459 0.7046 Oimb

59237 0.5924 0.6004

44347 0.4453 0.4sR

)

0.2792

0.4266 od22 1.0000

27183 0.2718 0.3213 OJisa 0.6102

10873 0.1087 0.1117 0.128s 0.1543 0.2441 t.oooo

O.oszl 0.0386 0.0610 0.2soo

0.0000 0.0000 0.0000 0.0000

* nta 0.0272 0.0270

0 0.0000 0. oooo 0.0000

. - 127
TABLE A-4. PROBABILITY OF DEATH WITH NEOPLASMS ELIM.INATED

Number

Entering

Interval

Hotar Veh.

+ Other

Violence

0.00979

0.0011J,

0.00069

0. ooos2

0;00134

ioorss

0.00145

0.001s8

0.0017i

0.00175

0.00190

0.00195

0.00233

0.00241

'O.O,oZOl

0 l 003?5

o.oos99

O.OlO66

0.02lJ4

0.02667

-

0.02823

We

Inthrval

Cardiovasculv

0.00012

0.00009

0.0000T

0.00011

0.09020

0.00043

0.00067

0.00114

0.00209

0 ; 00&/o

0.00637

0.01167

a.01951

O.Os'sO7

0.06133

0.10183

.

O.1727z

0.28586

0.46253

0.57822

0 ..02S70

All Other New

‘+ Unknot Tot al

0.02009 9.02100

1

0.001?3 0.00314

0.00017 0.901s3

0.00062 0.00125

O.OOO%7 0.00241

0.00118 0.00316

O.OOlSb 0.00369'

0.002lB O.Oc349L ’

0.00290 O.O~X79

0.00374 0.00919

0.00504 O.O1szl

0.00673 0.02036‘

0. ooaei 0.03047

0.01214 0.049bs

0.01717 9.08lS~)

0.02440 0.13017

0. oza4q 9.21326

0.05165 0.34817

0.07619 0. S&Q96

0: O?S19 9. 70008

0.1 3539 1. 09000

N,eopl l sms

0.00000

0.00000

0.00000

0.0~000

0.00000

0.00000

0.00000

0.00000

.,. -,. *.

0.00000

0.00000

0.00000

0.00000

I

0.00000

0. ‘00000

0.00000

0.00000

0. 00000

0.00000

0.00000

0.00000

O-.9 100000

l-4.9 97900

s-9.9 97593

10-14.9 97444

is-t?. 9 97322

20-24.9

25-29.9

so-s4.0

97088

96781

9642S

..‘,.,.’ -

35.39.9 95951

40-44;9 95309

45-49.9 94433

30-54.9 93176

53-59.9 9 1279

60-64.9

65-69.9

70-74.9

88498

84106

772st

75-m. 9 67195

go-‘ao. 9 52872

85-W. 9 34463

30-94.9 15162

95-99.9 4547 0.00009

4-128
TABLE A-5. PROBABILITY OF SURVIVAL FROM ONE AGE (x) TO ANOTHER AGE

(y) WITH NEOPLASMS ELIMINATED

hm

kuiu I@ (xi -

6011 Eutnr II9

Aqe (II I&anal 0 10 20 50 40 SO 60 70 80 90

- -m -.-mm- m0 1ooooO

1 97900

s 97?93

10 97444

ls??3z!

2 0 m0a

23 9bfBl

so 9642s

35, 9s9sr

1.oooo

0.9790

0.973 -

.

0.9744 1.0008 .

0.9732 0.987

0.9709 0.9963 l.oaoe

0.9678 0.9’7S.Z 0.9W

0.9642 0.9893 0.99s l.oooo

0.93% 0.9847 o.iws 0.99% .

0.9231 0.m 049et7- 0.9w4 i.0000

0.9443 0.9691 0.9727 0.97% 0.9ha

,

.

40

IS

50

55

60

6s

70

75

80

0s

90

9s

100

9so9

‘94433

95176

91279

8849e

04146

7725;

6719-S

%a72

sub3

IS162

.

4147

0

0.9318 0.9562 0.9597 0.9663 0.9776 1.QOOO

.

0.912a 0.9367 0.9402 ‘0.9w 0.%77 o.ms

0.483 0.9oa2 0.9flS 0.9m 0.9as 0.9498 1.0000

0.4411 0.8631 O.&b3 0.4723 o.iaz 0.?027 o.m4

on23 0.7m 0.7937 0.4012 o.am omi 0.4727 1.0000

O.HlO 0.6896 0.6921 O.ic969 0.7OSO 0.7212 0.733 0.8698

o.stBt o.mh 0.5446 0.?1443 0347 o.zh74 o..w4 O.MU l.oooo

o.su4 0.m o.ssso 0.3374 0.3616 0.1699 0.194 0.44&l o.ma

.

O.lfl6 0.1s 0.1562 o.mz O.lJ91 0.1627 0.1713 0.1963 0.2868 l.Oooo

0.0455 0.0467 0.0468 0.0472 0.04n 0.0448 0.0514 O.OSB9 0.0860 0.2399

o.aooa o.oooa 0.0000 o.ooaa 0.0008 0.0000 0.0000 0.0000 0.0000 . 0.0000

4-129
TABLE A-6. NUMBER OF PERSONS DYING (OUT OF 100,000 AT BIRTH) FR&

ALL CAUSES WITH NEOPLASMS ELIMINATED

causes

Number

Cardio- Motor Vah.+ 411 Other Entering

Neoplarmr vascular Other Viol. + Unknown Total IntrrvaI

d- .9

1 - 4.9

s - 9.9

10 - 14.9

1s - 19.9

20 - 24.9

2s - 29.9

30 - 34.9

c 3s .?“,39.9..

40 - 44.9

4s - 49.9

50 - 54.9

s5 - 59.9

-60 - 64.9

65 - 69.9

70 - 74.9

7s - 79.9

00 - 84.9

85 - 89.9

90 - 94.9

95 - 99.9

0

0'

0

0

0

0

0

0

. 0

0

0

0

0

0

0

0

0

0

0

0

0

12 79 2009

9 109 189

7 67 7s

11 51 60

19 130 as

.

42 l.so 114

QS lk0 1Sl

110 157 211

.a 201 i.d .I&4 278

3s2 167 336

602 179 476

1087 181 629

1768 203 810

3104 213 1074

5158 255, 1444

7067 305 1885

,

11546 403 238 1

15114 . 564 2751

8767 404 1443

3155 L74 618

2100

307

149

122

234

306

351

475

as3

876

1257

1897

2781

4592

.

68ss

1OOSb

14323

18408

100000

97900

97595

97444

97322

97oqe

96781

96425

95951

x509

94433

93376

91279

88498

84106

7x51

6719s

52!372

334G

15162

4547

4-130
TABLE A-7. PROBABILITIES OF DEATH WITH NEOPLASMS REDUCED BY 50%

O-.9

14.9

s-9.9

10-14.9

15-19.9

20924,9

25-23.9

30-34.9

33139.9

4044.b

45-49.9

50-54.9

s-59.9

60-64.9

65-69.9

70-74.9

75-79.9

80-84.9

85-09.9

90-94.9

95-99.9

100000

97897

97373

* 97407

97271

97021

96694

9&a4.

9s764

9soqo

93913

92316

89924

86528

81428

73792

63112

483&O

. 30642

12869

3s30

Number

me Entering

Interval Interval Neoplasms

0.00004

0.00017

0.00017

0.000;4

.

0.00017

0.00022

0.0003s

0.00070

d.00128

O.OQ22S

-

0.00369

0.00ss6

0.00729

0.00932

0.01228

0.014535

0.01741

0.02081

0.01998

0.02497

0.03330

Crrdioviscul l r

O.OOQl2

0.00009

0.00007

0.00011

0.00020

0.00043

0.000&i

0.00114

0.0020?

.

0.00333

0.006a7'

.

0.01167

0.019n

0.05507

0.06133

0.10183

0.17273

0.28586

0.4&2,53

0.51822

0.77079

Motor Veh.

+ Other

Violence

0.00079

O.O<jlll

0.0006'9

0.00052

0.00134

.

0.00155

0.00145

0.00158

0.00171

0.0017s

0.001yw

0.0019s

0.00222

0.00241

0.00301

0.60395

0.00599

0.01066

0.02134

0.02667

0.03569

All Other

+ Unknown

0.02009

0.00193

0.00077

0.00062

0.00087

0.00118

O.OOlS6

0.00218 ’

0.00290

0.00374

0.00~04

0.00673

0.00887

0.01214

0.01717

0.02449

0.03s33

0.05163

0.,07619

0.09519

0.16023

New

Total

0.02104

0.oo;i.o

0.00170

0.00149

0.00258

0.0033?

0.00403

O.OOS61

0.00798

0.01144

0.01700

0.02592

0.04376

0.05895

O-09=8

0.14572

O.ZO27

0. s&a96

0.56003

0.7250!5

1 . 00000

4-131
TABLE A-8. PROBABILITY OF SURVIVAL FROM ONE AGE (x) TO ANOTHER AGE

(y) WITH NEOPLASMS REDUCED BY 50%

New

llwhf

ad Entning ’

Age kJ

aqe (y) Intuwi 0 IO 20 30 40 30 60. 70 80 90

m-------v mm0

!

3

1 0

1S

20

2s

30

3s

.44

41

50

51

60

bl

70

7s

a0

Naooo

97401

ml

?702l

96694

wo4

m64

9looo

9391s

72316

a9924

am

.

a1428

73792

bS112

4030

I.0000

0.9790

o.?m

0. ?741

0.7727

0.9102

0.9669

0.9630

o.?ln

0. Tll

0.9392

O.pm

0.8-m

0.8655

0.3243

0.7379

0.6312

0.40%

l.Oooo

0.9786

0.990 . l.oaoO

e

0.9927 0.9946

0.9881 0.m

0.9832 0.9870

l.oao

Lo944

‘P.ms. - 0.9792

0.9641 0.9600

O.P#?' o.n23

-aims -1;oooo

.

o.?rQ 0.9086

O.FS 0.9728

o.mz 0.9268 0.m 0.9466

0.8883 0.8929

0.8360 0.837s

0.890l 0.9108

i&b 0.7606

0.8455 0.8511

0.7b62 0.7768

o.ss 0.6&S

0.5042 0.5112

0.6479 o.bss

0.4985 0.500s

.

as 306)2 0.364 0.3146 0.3m 0.3102 0.3226

90 12869 0.1287 O.lszl 0.1326 0.13Jb o.rm

PS 3J3a 0.0354 o.oss 0.036s Odz67 o.on2

100 0 o:oooo 0.0000 0. oooo o.oooo 0.0000

1.0000

0.9741

o.?m

0.802l

0.7993

0.4l837

OAaO

0.3319

O.lS94

0.0385

0.0000

.

,.*.

l.oooo

0.0412

0.8528

0.7294

O.%fZ

0.3541

0.1407

0.0409

0. coo0

. .

.

.

1.0ooo

0.8s ’

0.6581 1.0000

0.41s o.mo

0.1744 o.ihso l.Oooo

0.0479 0.0729 0.2749

0.0000 0.0000 0.5000

4-132
TABLE A-9. NUMBER OF PERSONS DYING (OUT OF 100,000 AT BIRTH) FROM

ALL CAUSES WITH NEOPLASMS REDUCED BY 50%

ASP

0 -‘.9

1 - 4.9

s - 9.9

to - 14.9

1s - 19.9

20 - 24.9

2s - 23.9

30 - 34.9

.

3s - 39.9

40 - 44.9

4s - 49.5' .

so - 54.9

ss- sp.9

60 - 64.9

6S - 69.9

70 - 74.9

7s - 79.9

80 - 84.9

85 - 89.9

90 - 94.9

9s - 49.9

- . .-c-i Number

Cudi 0' Motor Veh:+ Al 1 Other

Neoplasms vascular Other Viol. + Unknown

-&I--III------ .

.4

17

17

14

1 7

21

24

6e

123

214

347

515

12

9

7

11

19

42

&S

110

200

331

.

598

1077

79

109

67

Sl

120

lS0

140

lS2

163

167

178

180

200

209

245

291

378

S18

6%

343

126

2009

189

7s

60

8s

114

1st

210

278

355

807

1000

1078

1099

lqtl

612

321

118

/ 1742

3033

4994

7514

10839

13881

1417s

7441

2727

474

622

738

lOS0

1398

1800

z36

221508

233

122S

J&7

2104

324

166

lJ&

251

-&I)- 3L/

390

s40

764

1087

lJ?7

-2395

339s

SlOl

7&J&

*10&7?

24582

17918

17774

9 2

TT"Y

3SJB

100000

97897

97873

97407

l

97271

97021

96694

96304

95764

95000

93913

92316

89924

86528

81428

m92

63112

40S60

30632

12969

3sz3

Entering

Total Interval

e-133
TABLE A-10. PROBABILITIES OF DEATH WITH NEOPLASMS INCREASED BY

100%

We

Interval

O-.9

l-4.9

s-9.9

10-14.9

15-19.9

20-24.9

25-23.9

30-34.9

3k39.9

49-44.9

4"4-4?.?

50-54.9

55-59.9

60-64.9

&S-b?. 9

70-74.9

x-79.9

80-84.9

85-a?. 9

k-94.9

95-49.9

NUltib~

Entering

Intsrvei

100000

97886

97st3

97298

97120

96821

96431

'-95942

SS?OZ

94076

92365

89771

8S947

80824

73799'

64161

5207s

37348

t-12ss

7646

2 SZ?

CardioNeopl asam vascular

0.40014 0.00012

0.00067 0.0000~

0.00068 0.00047

.

0.00058 0.00011

0.00068 0.00020

0.00087 0.00043

0.00133 0.00067

0.00281 ..' 0.00114

o.oosl~ 0.00209

0.00900 0.00370

0.01478 0.006~7

o-02224 0.01167

0.'0291s 0.01937

0.03728 0.03So7 .

0.04910 0.06133

O.OS819 0.10183

0.06965 0.17173

0.08324 0.28586

0.07990 0.462Sz

0.09988 0.57822

0. lssl? 0.77079

?lotur Veh.

+ Other

Violrnce

0.0007?

0.00111

0.00069

0.00052

0.00134

0.00155

.

0.0014s

0.00158

0.00171

0.00175

0.00190

0.0019s

0 . 002??

0.00241

0.00301

0.0039s

0.00599

0.01066

0.02134

0.02667

0.03S69

CIll Other New

+ Unknown Total

O.O2009

0.00195

0.00077

0.00062

0.00087

0.00118

0.00156 0.00507

"0.00-218 --- O~.‘Oijf71

0.. 00299 0.01182

.o.ooa74 0.01819

0.00504 0.02909

0.00675 0.04260

0.00887 0.05962

0.012l4 0.08691

0.01717 0.130~0

0.02430 o.lsezb

0.93s43 0 .2929 1

0.0SlbS 0.43141

0.07619 0. a3996

0. ws19 0.7-J96

0.06034 1. 000>0

0.02114

0.09381

0.00220

0.00183

0.00309

0.00402

4-134
TABLE A-11. PROBABILITY OF SURVIVAL FROM ONE AGE (x) TO ANOTHER

AGE (y) WITH NEOPLASMS INCREASED BY 100%

0

1

5

10

13

20

2l

so

n

rq

43

20

sl

60

6s

70

A

00

as

90

95

loo

1ouooa

On23

97298

97120

96821

96432

93942

95202

94476

1.oooo

0.?789

o.¶l;

0.m

0.9712

0.9682

0.964s

0.9594

0.9408

0.92n

a9771 0.8977

:

ii947 0.8lYs’

80924 0.8OP

0.7300

64161

32OA

3730

2ltJf

7646

1529

0

O&lb

0.5207

O.J13

0.2!24

.0.076s

O.Ols.3

o.oooo

l.oow

0.9982

0.9951

0.9911

0.9862

0.9ias

0.9613

0.949s

0.9226

.

0.8633

0.8saf

0.7las

o.hs94

.

o.ss2

o.san

0.2183

0.0786

o.om

0.0000

f.oooo

0.9960

0.9909

0.m

-

0.97l7

0.9l40

0.9272

0.8877

0.3348

0.76z

0.6627

0.3379

o.san

0.2193

0.0790

O.Olsa

0.0000

Loo00

0.9923

0.9806

0.9627

0.m

0.8959

0.8424

0.7692

0.6681

0.342a

0.1893~

0.22ls

0.0797

o.oll?

0.0000

.

1.0000

0.9818

0.9542 2.0000

0.915) 0.9574

0.8s92 0.9003

0.7845 0.8zl

0.6820 0.7147

o.sla O.zaoI O&43 0.8!16

0.39io 0.41&O

0.22s7 0.23hb

0.0813 O.OBft

0.016s 0.0170

0.0000 0.0000

f.ooo0

0.913;

0.79m l.OOoo

o.u2l 0.5821 l.Oooo

0.2h27 0.5310 0.5686

e

0.0944 0.1192 .0.2047 l.Oooa

.

0.0189 0.02S8 0.0410 O.?ooO

0.0000 o.oooo o.oooo o.oooa

4-135
TABLE A-12. NUMBER OF PERSONS DYING (OUT OF 100,000 AT BIRTH) FROM

ALL CAUSES WITH NEOPLASMS INCREASED BY 100%

. .

Rae

Cardio- Motor Veh. + Al I’ Other Glterfnq

Nedpl rsms vrscul l r Other Viol. + Un’knuwn Total Interval

I)-.9

1 - 4.9

s - 9.9 *

10 - 14.9

.

1s - 19.9

20 - 24.9

2s- 29.9

3o~-,su.?

3s’ - 39.9 j .

I

40 - 44.9

4s - 49.9

so - 54.9

ss- 39.1

60 - 64.9

65 - 69.9

70 - 74.9

7s. 79.9

80 - 84.9 .

8S - 69.9

90 - 44.9

9s - 99.9

14

66

Lb

SC,

64

84

134

269

488

846

13&S

ibY&

2505

3013

5624

am

3627

3109

1697

764

204

12 79 . 2009

9 . 109 189

7 67 7s

11 51 63

19 130 85

.

42 lS0 114

.&s 140 lS1

110 . . - -1. ,& _. . .." '..C 209 *.= . .

199

348

.

388 -

1047

1663

2asq

4S2i

6s34

8943

10676

9822

162

165

17s

1M

191

19s

22z

233

312

398

453

204

5s

276

332

4&6

606

76s

981

1267

1563

1845

1329

1618

728

92

2114 100000

373 97886

215 97513

178 9729e

500 97120

389 96021

489 46431

*- l -74Q 95442

1126 95202

1711 94076

2594 923&S

3824 89773

5124 85947

7024 a 80824

9639 75799

12086 64161

14727 52075

16112.. 3738

13590 21235

6116 7656

1 s29 1529

4 - L I ‘: