Final Report

VALUATIONOFREDUCTIONSINHUMANHEALTH SYMPTOMSANDRISKS 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 1986DISCLAIMER
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.VALUATIONOFREDUCTIONSINHUMANHEALTHSYMPTOMSANDRISKS

Abstractof 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 illnessand 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 abouttheir 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 i11ne sse s 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 ChicagoWilliam Webb Economics University of Chicago Wallace Wilson Public Health University of Illinois at Chicago Martin Zelder Economics University of ChicagoCONTENTS 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 1-21Listof 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.

FrameworkForValuingHealthRisks(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.
HealthEconometrics: AnAssessment(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).

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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.

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1-4 Costof IllnessApproach(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.

Reviewof ContingentValuationStudiesof 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.
ComparingCostsof IllnessandContinigentValuation(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

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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.

HouseholdProductionof HealthandAvertingBehavior(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.

HousingValuesandtheValueof 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 2ppm 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: InterimValuesfortheHealthEffectsof 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.

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1-9 

### Table 1-1 Framework for Health Values HealthEffectsValuedValuereflects 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 Aggravationof Previously ExistingChronicMorbidity --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 IncreasedIncidenceof Non-fatal ChronicMorbidity --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 ofemphysema 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

1-12 Table 1-2 Interim Values for Morbidity and Mortality Effects of Air Pollution Value Estimate CategoryLow MediumHigh 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

1-13 Table 1-2 Interim Values for Morbidity and Mortality Effects of Air Pollution Value Estimate CategoryLow MediumHigh

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 (perstatistical 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

1-15 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.

Structureof 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.

HouseholdSampling(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 ResultsforHouseholdSurvey(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

1-17 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

1-18 

### Table 1-3 Seven Light Symptom One Day Regression Results
Bids to Relieve One Additional Day of: VariableCoughingSinus ProblemsThroatItchyEyes 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

1-19 

### 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

1-20 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.

HealthDefinitionandMeasurement(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.

TheQuantityandQualityof LifeandtheRelationBetweenMorbidityand MortalityBenefits(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.

AModel of UncertainPreferencesforExplainingInidividual BehaviorToward 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.
Designof ContingentValuationApproachestoSeriousIllness (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. USEPAGrant #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 1986DISCLAIMER 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- 702.5 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 2-1312.9.3 Interim Values for the Health Effects of Air Pollution 2-136List 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 Crackeret 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

2-161VALUATION 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 arriveat 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 2-1172. 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-lSection 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.

2-22.2. 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 To Valuing Health Risks

------A -- ____-- ------ ----- 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 Mushkin1962. 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
2-3time 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

2-4she 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.

2-5Theoretical 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),

2-6where 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-'nconsumption 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.vesexpected 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.

2-8The 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
2-10derivative 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. Valuation Of Changes In Risks To Human Health

---e----B

-- ---- -- -- 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)) -(UP 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.

2-11The numerator of the first term is the difference in expected

utility when healthy and when ill. This is div.idedby 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

2-12empirical 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

2-13for 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.
2-14TABLE 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 20.

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. 2-15Preventive 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 HEis larger in absolute value than H dX/dE; the sign of dH/dE is also negative if dX/dE >_

0. In ot E 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). .Theupshot 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

2-16improvement 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 nonworktime.

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:

2-17U(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

2-18can 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

2-19appropriately 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 Concluding Remarks

--e-e---- ------- 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
2-20willingness 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.

2-212.2.5 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

2-22from 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 Uwith 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 CO1studies 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.
2-237.

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 RegionalBenefits 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." Workplanfor 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.'andRice, 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.

2-252.3. 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 Qlwhich is less than Qo. The supply of health from such conditions is now Hl which is less than Hoyet the difference in health status c n be offset by additional avoidance procedures at a cost of C (H 8

- 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 Q Y toQ 8 would be C x (Ho

-H ).* On the other hand, in a stochastic setting, regression of H (or m*orerealistically, 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’ -_ Hspecfication 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), Crackeret 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 for Assessing Air Pollution Control Benefits, ------ ---- v-s -------- --- _----_--- __----- 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,

2-28cold 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. Chappieand 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.

2-292.3.3. Assessment

---------- 2.3.3.1. Pollutant Effect Comparison

Table 2-2 shows the effects of a 1 microgram/meter 3 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 SO4are 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
2-30correlation 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 occuringin 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.

2-31Table 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 ILave and1 Chappin andI. Crockerlsohm andland 

### I a I b I c I d I Pollutant1 Seskin ISeskin 1and 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'1microgram 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).

2-32Table 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)

2-332.3.4. 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 inenvironmental 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

2-34purposes 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.

2-352.4. 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 CO1approach 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 CO1approach 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 CO1approach 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 CO1approach 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

2-36illness 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 CO1approach 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

2-37conceptual issues, section 2.4.4is 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 CO1approach 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 CO1approach 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
2-38will 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'llowingthe 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 CO1studies 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 CO1estimates: 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.morbidityare 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 CO1measure 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 CO1measure 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 CO1measure 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
2-40individuals' 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 CO1benefit 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&ra 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.

2-412.4.3. 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 CO1measures 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
2-42health 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
2-43incurs. 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 .insurancepremiums. Even if the individual does not perceive the total savings in medical expenditures, though, as a first approximation the CO1benefit 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.

2-44Thus, 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 CO1approach 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,

2-45The 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 CO1benefit 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 Paringerand 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 Paringerand 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
2-46necessitated by disease j.in each of the n service categories.

The principle advantage of th.ismethodology is that double counting is avoided, since total expenditures are simply distributed to the different disease categories. For the purpose of benefit estimation, itis 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

2-47make 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

2-48incorrectly 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 Paringerand 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 Paringerand 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, vnwhere 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
2-49conditions, 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.

2-502.4.4.2. 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, CO1estimates 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 Paringerand 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

2-51respondents.

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, Paringerand 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 Paringerand 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

2-52characteristics as housewives". Finally, the value of'time spent

by all indiv'iduals keeping house, not just women, should be estimated. While Paringerand 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

2-53likely 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

2-54illnesses. 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 Paringerand 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 4 an 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.

2-55TABLE 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) Paringerand Berk (1977) Infective and --------- --- Parisitic Diseases --------- -------- Hodgson and Kopstein (1984) Paringerand Berk (1977) Neoplasms lcancerl --- ----- ------ Hodgson and Kopstein (1984) Paringerand Berk (1977) Hartunian, et al. (1980) Diseases of the Circulatory -------- -- --- ------m--m System

---- All

--- Hodgson and

Kopstein (1984) Paringerand 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

2-56TABLE 2-4 (continued)

Disease Medical Foregone Category Expenditures Earnings -----,---,--~--------------------------------------------------- Cerebreovascular -_-------------- Disease jStroke1 ------- ------ Hodgson and Kopstein (1984) Paringerand 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) Paringerand 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

2-572.4.5.2.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.
2-58An 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
2-59dividing 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, Actonputs 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 Actonattempts 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, Actonestimates 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, Actonuses a lower estimate of the number of cases in

2-60expressing his results on a per case baiss, which implies that if

the Actonand 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.

2-61TABLE 2-5: PER CASE MEDICAL EXPENDITURES AND FOREGONE EARNINGS (in $, August 1984
_________--_------------------------------------------- Medical Foregone Expenditures Earninings Disease Category Per Case Per Case _____-____-____----_-------------------------------------------- Infective and --------- --- Parasitic Diseases -------me -------- Hodgson and Kopstein (1984) Paringerand Berk (1977) 123

NeoPlasms --- ----_ All

--- Hodgson and

Kopstein (1984) Paringerand 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) Paringerand Berk (1977) Cerebreovascular -m-m------------ Disease LStrokel -e-s--- ------ Hodgson and Kopstein (1984) Paringerand 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

2-62TABLE 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) Paringerand 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

2-63TABLE 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 --------- --- Parasitic Diseases e-e------ -------- 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

2-64TABLE 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 RespiratoryDiseases -- ------ _------- 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

2-65TABLE 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)

_ ______---__--__------------------------------------- Infective and ---w-s--- --- Parasitic Diseases --------- -----_-_ Paringerand 1,559 Berk (1977)
NeoElasms --- ---__ Paringerand 1,105 Berk (1977)
Diseases of the -------- -- --- Circulatory System

---------- ---_ All

--- Paringerand 8,744

Berk (1977)
Stroke

------ Paringerand Berk (1977) NHLI (1975) Coronary Heart Disease ------- ----- ------- NHLI (1975) Respiratory Diseases --- ------ -------- 353 421

370

All

--- Paringerand 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

2-66Emphysema

-- - ---- 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 thevarious 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 costsexpressed 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.

2-672.4.5.3. 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 condtionvaries 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.

2-68TABLE 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) Paringerand 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) Paringerand Berk (1977) NHLI (1967)
Emphysema -- ----- NHLI (1967) Freeman, et al. (1976)
Pneumonia m-----e-- (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. -------I- ------- --- ---- ------- -----

Concluding 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.

2-70All 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 Paringerand 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.

2-712.2.11. References

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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. Paringerand 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. Onthe 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.

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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.
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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. HealthEconomics 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, series 10, no. 115. U.S. Health Interview Survey. Prevalence of Chronic Conditions of the Genitourinary, Nervous, Endocrine, Metabolic, and Blood and Blood-Forming Systems, and of Other Selected Chronic Diseases. Vital and Health Statistics 1973 and 1977, serices 10; no,. 109.

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2-752.5: 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. Overview and Assessment of Contingent Valuation

--s----s --- ---------- -- -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
2-76bias, 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 respondentsees 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, ,ChapterIII).

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, "themethod 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.

2-782.5.3. Qplications of Contingent Valuation to Health ------mm- -- ------ --_ --------- -- -_____
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 airpollution, 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

2-79health 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
2-80symptom 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'yet 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.
2-81Results 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

2-82values 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
2-83than 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.

2-84Table' 2-8 m-s-- --- Contingent Values of Health (1984 $) w-e--- --- ------ -- ------ 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)

2-85Table 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

2-862.5.3.4. 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 "badasthma 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
2-87mentioning the 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.

2-882.5.3.5. 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 frommildand 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

2-89familiar 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

2-90responses 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

2-91range 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.

2-92Symptom

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)

2-93Table 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)

2-94Table 2-9: Part 3

Survey 3 Relief from angina, given endowment of angina

--1mild day given 1 mild day given 10 mild days --1severe day given 1 severe day given 10 severe days --5mild 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)

2-95Survey 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 --lomild 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

2-962.5.4. Conclusions and Summary

-------w--e --- --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

2-97Control 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.

2-982.6. 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
2-99CV 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'andCV 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.ion2.6.4 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 CO1values. 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 CO1is 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 CO1is the respondents' rankings
2-100of 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 CO1value. 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 CO1and 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.
2-1012.6.3. CornParing CO1and CV

-New Results

-mm -e-v --- --- -- - --- ------- 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 CO1is 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 .05level 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.

2-102Symptom 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.

2-103There 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 orditaryleast 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 CO1is 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

2-104test 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
2-105results 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. Conclusions

--------e-s 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.

2-106The 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

2-107tests 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

2-1082.6.6. References

-_------es
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.

2-1092.7. 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. Gerking and Stanley 119841

-e---s --- ------ ---- 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)/dAusing a cross2-110sectional survey of 2,594 households in St. Louis, Missouri, over

the years 1977-1980, which is combined with air quality data from th.eRegional 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

2-111the 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.

2-112Cropper illustrates her analysis by calculating CO1and 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.
2-1135. Portney, P.R. and J. Mullahy. "Urban Air Quality and Acute

Respiratory Illness." Journal of Urban Economics, forthcoming.

2-1142.8. PROPERTY VALUES AND THE VALUE OF HEALTH

2.8.1. Introduction

--m--m------ 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.
2-1152.8.2. 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.

2-116FIGURE 2-2 BENEFITS OF AIR QUALITY IMPROVEMENT

BENfFITS 2.

- 8 b

\ COMPENSATED

DEMAND FOR 

### AIR QUALITY

-, AIR QUALITY L t

2-117TABLE 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.

2-118In 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.

2-119It 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 utl 9. 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 Ylrepresents 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 thtderivatives 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,
2-120since 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 aninstrumental 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 fsimmediately apparent in Rosen's suggested empirical technique. That is, if Pi is linear in Z and oiis 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 oiis a special case. In other words, with a single market area at a particular point in time,

2-121all 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.

2-122TABLE 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

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

2-1232.8.3. 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

2-124in 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-125point 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.

2-1262.8.4. 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

2-12712.

13.

14.

15. for the Proper .Estimationof 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

2-128Science, 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.

2-129B. 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-1302.9. 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 .whathealth effects it would be desirable to have values for, and what a complete value estimate would include. Rather than being.anideal, 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!e2lthEffects Of 412 Pollution ------m-w 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.
2-131Health Effects Valued

------ ------- ------ TABLE 2-13 FRAMEWORK FOR HEALTH VALUES

Acute 05Short-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 ---_---- ----_---_ Existing Chronic Morbidity ---e-e- ------- --------

__ 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

2-1322.9.2.1. 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
2-133still 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 inhishealth 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

2-134components of the value of acute morbidity remain relevant. Of

course, the discomfort may be *moresevere, 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.
2-135Another 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.
2-1362.9.3.2. 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 ACUTE MORBIDITY VALUES OF 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

X severe

2-138Approach, 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

2-139TABLE 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

2-140TABLE 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 XTABLE 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: --1mild 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

2-142Approach, study,

and health effect

--5 mild days --5severe 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

2-1432.9.3.3. 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 Paringerand 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.

2-144It 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.

2-145Estimates 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.

2-146Symptom 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

2-147respiratory 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

2-148pollution 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 ,weekor 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

2-149of 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

2-150average 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 atthemargin. 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 mildorsevere 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

2-151values 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

2-152days 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.eredfrom 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 conditonper 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,denceon 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

2-153too 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.

2-154Additional 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

2-155values 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
2-156approach" 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 morbidityvalues 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.
2-157TABLE 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.

2-158TABLE 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__________-------

2-159More 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).

2-160TABLE 2-17

INTERIM 'VALUES FOR MORBIDITY AND MORTALITY EFFECTS OF AIR POLLUTION
Category ---- -- Value Estimate Low Medium

--- m-m--- High -- Acute 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

190TABLE 2-17

INTERIM VALUES FOR MORBIDITY AND MORTALITY EFFECTS OF AIR POLLUTION (continued)
Category ---- -- Value Estimate Low Medium

--- ------ High -- Increased Incidence of Non-fatal Chronic Morbidity

--------- ------- -------- lpercase 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 .54m 3 m 7 m

.58m 3.8 m 9.4 m

2-1622.9.3.7. 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. Amediumor 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

2-163from 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.

2-164Final 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 1986DISCLAIMER 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 containsacomparative 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 3-383.4 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

3-97List 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 3-943.1. 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

3-1method 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.

3-2These 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

3-3introduced 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

3-4preparation 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

3-5survey 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.

3-63.2. 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 ofconditions, 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

3-8One 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 S02and 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 S02combines with water vapor to form sulfates, which are more harmful to health than S02alone. 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
3-9years 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 andastudy by Kuller et al., in Baltimore discussed by the National Research Council, 1977, p. 113). When

3-10the 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%, thereis 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

3-11these 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).

3-123.2.2.3. 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

3-13number 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

3-14et 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.

3-15TABLE 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.

3-163.2.2.4. 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 S02reach .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 S02concentrations and health. At S02levels greater
3-17than 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 S02is an average concentration of 0.03 ppm.There is little information on the percentage of the population likely to experience symptoms from high ambient S02concentrations. 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.

3-18TABLE 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).

3-193.2.2.5. 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
3-20We 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/m 5 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/mfor 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/m3at 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.

3-21Residents 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.

3-22TABLE 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).

3-233.2.2.6. 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 N02concentration 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 N02reach 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 N02concentrations. 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.

3-24People 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.

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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).

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3-333.3. 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
3-34interpretable 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

3-35concentrating 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.

3-36Various 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 orderbids 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.

3-383.4. 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

3-39shorter 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

3-40for 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 theactual 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

3-42consists 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 productbeing 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

3-43demographic 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

3-44they 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

3-45were 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.

3-463.5. 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

3-47would 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.

3-483.6. 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

3-49these 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.

3-50Thus 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

3-51discusses 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.

3-52Table 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

3-53Table 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

3-543.6.2.2. 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 Y lna 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

3-55Table 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

3-56Table 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

3-57Table 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 0.21 0.70
Note: t values in parentheses

3-58health 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.

3-59Table 3-7

Means and Standard Deviations ForSeven LightSymptoms 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

3-60Table 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

3-61Most 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.

3-62Table 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

3-63Intercept

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

3-64Intercept

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

3-653.6.4. 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.

3-66Table 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

3-67Table 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

3-683.6.4.2. 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.

3-69Intercept

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

3-70Table 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

3-713.6.5. 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.

3-72Table 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

3-73Table 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

3-743.6.5.2. 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.

3-75Intercept

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

3-76Table 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

3-773.6.6. 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 seenas 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.
3-783.7. 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
3-79information 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.

3-80Table 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

3-81Table 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.

3-83All 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.

3-84Table 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.

3-85Table 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

3-86Question 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.
3-87Table 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.
3-88Headaches 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.

3-89Table 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

3-90Table 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

3-91The 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.

3-92Table 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

3-93Table 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

3-943.7.6. 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

3-95exceeded 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. ____ ___ _________ _______ ___ _____

______

3-96APPENDIX 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.

3-97A.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.

3-987 - 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

3-997 - 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.]

3-1007 - 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

____ ____ ____ ____

3-1017 - 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

____ ____ ____

3-1027-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? $

_______ _______ ________ ________

$

_______ $

________ $

_______

_______ _______ _______

_______ $ $ $

_______ $ $ $

_______

3-1037 - 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? $ $ $

_______ _______ _______

3-1047 - 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

________________________

3-1057 - SYMPTOM HEALTH QUESTIONNAIRE: ONE DAY

M. DEFENSIVE MEASURESNow 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?

___________________

3-1067 - 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]

3-1077 - 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.
3-1087 - 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.

3-1097 - 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.]
3-1107 - 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.

3-1117 - 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 bidto 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.]
3-1127 - 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

3-1147 - 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

________

3-1157 - 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

____________________

3-1167 - 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]

3-1177 - 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.]

3-1187 - 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]

3-1197 - 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 _____________

______________

_____________

______________

_____________

3-1207 - 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.]

3-1217 - SYMPTOM HEALTH QUESTIONNAIRE: ONE DAY

ANSWERS TO S-7

3-1227 - 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

---------

3-1237-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]

-----------
3-1247-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.]

3-1257-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.

3-126A.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]

3-1277-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.

3-1287-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]

3-1297-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

3-1307-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.

3-1317-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 bidto 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.]

3-1327-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.

3-1337-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

3-1347-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

-----------

3-1357-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

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

3-136A.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.

3-137ANGINA 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

3-138ANGINA 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

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

3-139ANGINA 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? $

------
3-140ANGINA 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.

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

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

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

3-141ANGINA HEALTH QUESTIONNAIRE: 10 DAY

M. DEFENSIVE MEASURESNow 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?

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

3-142ANGINA 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.

3-143ANGINA 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

--------

3-144ANGINA 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.

3-145ANGINA 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.]

3-146ANGINA 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].

3-147ANGINA HEALTH QUESTIONNAIRE: 10 DAY

SOCIOECONOMIC QUESTIONS
(Same as in 7-Symptom Health Questionnaire: One Day)

3-148A.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.

3-149ANGINA 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

Valueof 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

------—

3-150ANGINA 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.

3-151ANGINA 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 .OFREDUCTIONS IN HUMAN HEALTH

--------- -- -------w-e WV ----- ------ SYMPTOMS AND RISKS -------- a-- -----

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. USEPAGrant #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 1986DISCLAIMER 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

------em- -- ---------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'cmeasures 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 valuationstudies. 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 modelledwithin the life cycle framework. Section 4.4 develops a model of choice under uncertainpreferences, 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 4-434.3.5

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 4-914.5 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

4-123List 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 WithNeoplasms 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 4-1114.1. 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 theestimation 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-lSection 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.pleair 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.

4-24.2. 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 ,functionis 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 dimen4-3FIGURE 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

Behavioral and environmental 

# >JJj

I Use for ‘health
- risk valuations I

4-4sions 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 beemphasized. 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 considerdin 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,

4-5other more recent definitions of health also stress life functioning, mental state and self fulfillment. Hoyman (1965) explains that "health is a process of continouschange 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 "...tofunction 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
4-6by 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 therelative 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:

4-71. 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 ofhuman 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-aFIGURE 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).

4-9TABLE 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.

4-10behavioral factors,, which may be preventable;

3. Lifestyle pattern is the major behavioral risk factor .involvedin 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).

4-11Figure 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;

4-12FIGURE 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

4-13The 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

4-14widespread 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,

4-15pulmonary 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,
4-16convulsions, 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, PCBsaccumulate 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

4-17conditions. Damage to other environmental systems (acid

deposition) ,maybe 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. Health Measurement

--mm-- -----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, notthose 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,medits "natural history' or "clinical course." In
4-18relation 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. Stags of susceptibility: B-m 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-symptomaticstage: ----- - ------- --- - Pathogenetic changes begin to occur, but the changes are not manifested in symptoms or signs which can be diagnosed. Clinical stags: ---B---B--- 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.

4-19efforts;

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.,.anabnormal chest x-ray); 5. When symptoms appear (severe coughing, chest pains, blood in sputum) and the individual, who knows that something is wrong, m.aytell 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 ,expandedinto 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

4-20considerations 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

4-21bathe 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-specificrisk 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

4-22suggested. 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 thepresent 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,

4-23one 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 symptomdescriptions 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

4-24account of individual cjrcumstances in a life cycle context with

certainty and uncertainty scenarios.

4.2.6 References

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; 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 ------- ------------ ------- United States --,-------m--p 2nd ed.: ed. Steven Jones; New York: Springer Publishing Company, 1981. Berkman, L. F. and L. Breslow; Health and Ways of Living; London: ------------- ------mm-- 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 LowBirth----------------------------------------------------- ------m-e- Weight Infants; Hamilton, Ont.: --- ---------- McMaster University, 1982. Breslow, L.; "Prospects for Improving Health Through Reducing Risk Factors;" Preventive Medicine 7:449-458, 1978.

--------a---------- 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;" Advances in Nursing Science, April 5, 1983. ----------w---e--- -------- Carlyon, W. H.; "Disease Prevention/Health Promotion--Bridging the Gap to Wellness;" Health Values: Achieving High-Level -------_-------w-----w-- --- ------- Wellness; -w-v---- May-June 1984.

4-25Carroll, C., D. Miller, and J. C. Nash; Health ----,-A the Science of

------------B-B Human Adaptation; Dubuque, IA: Wm. C. Brown Co., 1976. --------- ------ .Centers for Disease Contro,l. Health Risk Appraisal User Manual. Council on Environmental Quality; Environmental Quality Thirteen ---m---------w ---me--------- Annual RePorts; Washington, DC: U.S. ----m---w ---- Government Printing Office, 1970-1982. Cox, B. G., D. T. Carr, and R. E. Lee; Living with Lung Cancer; -e--m e-e------ ------- Rochester, MN: Mayo Foundation, 1977. Culyer, A. J.; Measuring Health: Lessons for Ontario. -m----v- --a------------,------,,,,,( 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;" Promoting Health;

----a--- -e--e-- American Hospital Association, July-August, 1981. Fielding J.; "Reducing the Risk of Risk Appraisals;" Promoting Health; ------me ------- 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.; Public Health Administration ----------------------m----m and Practice ,-eme--m---- 8th ed.; St. Louis: College Publishing, 1984. Hettler, B.; Description Analysis and Assessment of Health

------ ,--,A----- ---A---------,--,-,---,,-------- HazardLHealthRisk Appraisal Programs ------ ------------- ------a--- we -- Executive Summary!, Final A----,------,---,- RePort; Chapel Hill: Health Services Research Center, University o? Nirth Carolina, 1981. Hettler, B.; "Wellness Promotion on a University Campus, Family

----- and Community Health; 1981. ------me---- a------ Howard, R. A. and J. E. Matheson; The Principles' and Applications -e-w------ ------m-w --m---v-- of Decision Analysis Volume II* -m--------d----- ---A---------- ' Menlo Park, CA: Professtonal Collection, Strategic Decisions Group, 1984. Hoyman, H. S.; "An Ecological View of Health and Higher

4-26Education;" Journal of School Health 35. March 1965. ------,-------------,,,_,,_) Kane, R. L. and R. A. Kane; Values and Long-Term Care. Lexington, -------------- ---------a' MA: Lexington Books, D. C. Heath and Co., 1982. Kaplan, R. M.; "Human Preference Measurement for Health Decisions and the Evaluation of Long-Term Care;" Term Care; R. L. Kane and R. A. Kane, in Values and Long-

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---------------------e-----e --A------,,--,,,,- Explanations; St. Louis: -- -----a--- C. V. Mosby, 1981. Mausner, J. K. and S. Kramer; Qidemiology--An Introductory Text. -----m-e ---------------- -we--' Philadelphia: W. B. Saunders, 1984. Mechanic, D. and P. D. Cleary; "Factors Associated with the Maintenance of Positive Health Behavior;" Preventive Medicine 9:805-814, 1980. ------------------- Murray, R. J. Zenthel; Nursing ConcaRts ------ ------ for Health Promotion* Englewood Cliffs, NJ: ~---~~~-~~~~----~~~~---' Prentice-Hall, 1975. National Cancer Institute; Cancer of the Lung; USA Public Health ----------em----- Service, National Institutes of Health, August 1980. National Center for Health Statistics; General Mortality --------we------ Statistics 1979 Vol. II, Part A; USA Department of Health and ----------A----- 9 Human Services, 1979a. National Center for Health Statistics; Vital Statistics of the ----we----------------- United States 1979 Vol. II, Part B, Section 6; USA Department -------------A-----, of Health and Human Services, 1979b. National Center for Health Statistics; Current Estimates from the National Health Interview surve~1979--~~~~~~-iZr,-No,-i~~-(PHS) ------------------------------- ----' 81-1564; USA Department of Health and Human Services, April 1981. Pattfi Industrial Hygiene and Toxicology, Third Revised Edition,

---- vol. 1;-N~~-Y--~oh~-~~i~~-~-~~~~~-i978. Pliskin, J. S., D. S. Shepard, and M. C. Weinstein: "Utility Functions for Life Years and Health Status;" ORerations Research -----------------I
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Preston, S. H., N. Keyfitz, and R. Schoen; Causes of Death: Life --a------------------ Tables for National Populations; New York: 1972. ---------------------- -------a Ratcliff,.L.; Health Hazard ARRraisal: Clues to a Healthier

--------------- ---------a------------------- Lifestyle; ------ -- Public Affairs Pamphlet 558; New York, 1978. Robbins, L. and J. Hall; How to Practice Prospective Medicine; ------------------a- --------------- Indianapolis: Methodist Hospital of Indiana, 1970. Robinson, K.; "What is Health?"; Community Health; J. Clark and -------- ------- J. Henderson, eds.; pp. 11-18; Churchill Livingston Press, 1983. Rosen, S.; "Valuing Health Risk;" AEA PaRers and Proceedings ---me- ----------m--e--- 71(2):241-245, May 1981. Sacks, J. J., W. M. Krushot, and J. Newman; "Reliability of the Health HazardAppraisal;" American Journal of Public Health

--------------------------------- 70:730-732, 1980. Schoenbach, V. J., E. H. Wagner, and J. M. Karon; "The Use of Epidemiologic Data for Personal Risk Assessment in Health Hazard/Health Risk Appraisal Programs;" Journal of-Chronic ------------m---m- Diseases 36:627-638, 1983.

-------- Schultz, D. M. S.; "Lifestyle Assessment: A Tool for Practice;" Nursing Clinics of North America --w-w- Me--me--w--------------m-' June 1984. Somers, A. R.; "Life-Style and Health;"inMaxcy-Rosenau Public ---- ---*------------ Health and Preventive Medicine ----,---------,--,--_,,,,_,,,,) 11th ed.; J. M. Last, ed.; New York: Appleton-Century-Crofts, 1980. Surgeon General's Report on Health Promotion and Disease Prevention; Healthy People; Washington: USA Public Health

--m--e -w-w me Service, 1979. Sutherland, H. J., V. Dunn, and N. F. Boyd; "Measurement of Values for States of Health with Linear Analog Scales;" MedLcal

------- Decision Making, Vol. 3, No. 4, 1983. -----m----B--- Task Force on Environmental Cancer and Heart andslungDisease; Environmental Cancer and Heart and Lung Disease, Fifth Annual -------------------------------------- m--T---- Report to Congress; Washington: USA EPA, August 1982. Torrance, G. W., M. H. Boyle, and S. P. Horwood; "Application of Multi-attribute Utility Theory to Measure Social Preferences for Health Status;" ORerationResearch; November-December 1982. -M-------------e Toxic Substances Strategy Committee; Toxic Chemicals and Public -------_------------------ Protection 4 Report ~2 t&President; Washington: May 1980. ---,,-,,,,A -- --- ------w-v Travis, J.,

-Wellness Workbook for Health Professionals; Mill

-------------__---_----------------------- Valley, CA: Wellness Resource Center, 1977.

4-28USA Department of Health and Human Services; First Report on w---B--- ------ Carcinogens; Washington: July 1980. ------- -me Waldbott, G. L.; Health Effects of Environmental Pollutants* St. ---------,,,--------,,,,,,,,,,,,,,,,,,_,--' Louis: c. V. Mosby Co., 1978. Wolinsky, F. D.,. R. M. Coe, D. K. Miller, and J. M. Prendergast; "Measurement of the Global and Functional Dimensions of Health Status in the Elderly;" Journal of Gerontology 39(l), 1984. -----w-------e------

4-294.3. 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.

4-30Therefore 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

4-31point 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/dtbe 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. rWis 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) isconsistent 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 calculate the value of

-me-- e---e--- 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

4-32To 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 ssimply 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:

4-33vW -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 5E 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 tothe question of intertemporal substitution possibilities in consumption. To see this most clearly, let us examine some limiting

4-34cases. 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 isprepared 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 islarger. The second effect dominates if T is short enough, but if T is sufficiently long
4-35then 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 speriods 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 2onward 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 sforward. 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)Bis 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 1nthe 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

4-36have 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-w E (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 -aTf(Wb ),

4-38where 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/dTwere 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

4-39to 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 5L 51. 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 /uas 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

4-41the 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 vin (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 vof the form

V- c2 [(1-g)&]A',

4-42which 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,esecond is that the adjustment factor--the elasticity term Ris 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 cifalls 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 vis 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))emrtdt

+ 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 .

4-43Of 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

4-44term 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 lffechances, 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

4-45function 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 orilylooking 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

4-46for 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 2T. 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

4-47order 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 tof c(z)eerzdzdt

-integral from 0 to t of (1-F(t))c(t)eert dt,

4-48where 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.

4-49v' 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. vis 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 tybecomes 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 constratntin (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

4-51appear 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.enthe 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 acceptrisks 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 h2permanently, 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.

4-53Nonetheless, 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 inthe 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

4-54preference, 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. Itis 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 regretedactions 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 .theeffects 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 inhis 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

4-55equal 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 45-year-old --e--w- (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 "onthe 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

4-56threshold 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 'orvarying degrees of probability. Focus group explorations of hypothetical life path experiences showed graphically that people in their twenties havelittle 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
4-57wants 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; The Utilization of Health m-m ----------- -- ------ Services- Indices and Correlates, DHEW Publication No. --------A

------- --- ---------- (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;" Medical Core 17 (Supp): 1-131, --e--e- ---- 1979. Chestnut; L.C. and D.M. Violette; Estimates of Willingness --------- -- -_---- --_- to Pay for Pollution-Induced Changes in Morbidity: h

------w------e--- ---- -- -- -------- - ?Tit?&ue?gr Benefit-Cost Analysis of Pollution Regulation e-w-- -- --a------------ ---- --- -- --------- -- -------' 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; Health Status Medical Care Utilization ------ ------A ---m--e and Outcome: an -_-- -,,-------,A --- -e----e- -- Annotated Bibliographyof 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.

4-58London, 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 19:473-488, 1981.

------- --we 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 for ----- ----------- --- ----------- -- --a--- ---a-- --- Adults in the Health Insurance Study: Volume 1, General ------ -- --- ------ --------- ---- - w--w-- ------- 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

4-594.4. 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.inthe 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. AREroachTaken in This Section

-Be-- ----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 1sto ask individuals directly

4-60about 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.

4-614.4.3. ExpectedUtility 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. .Theindependence 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 AllaLscan 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

4-62Figure 4-4. INDEPENDENCE AXIOM

4-63Figure 4-5. ALLAIS PARADOX (A)

4-64Figure 4-6. ALLAISPARADOX (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 Allaisparadox, 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
4-66phenomenon" 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 .002percent 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 choicesbased not on the distribution of outcomes, but on the distribution of the dif'ferencebetween the chosen outcome and the outcome not chosen. This approach, based in minimaxstrategy game theory, was a popular early rival to expected utility theory, and it has recently been advocated by Loomes and Sugden. A major

4-67difficulty 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

4-68upon 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 carfullyto 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

4-69problems 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 should be. ---a-- 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 prferencesis 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.

4-704.4.5. Psychological Studies -- -e--w---- ------- Cognitive psychologists have not been concerned with the ethical/public policy question of which statements of preferences should be taken into account in the determination of public -----a 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
4-71common 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.licatedsituations. 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 .OOlas 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

4-72dropping 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 ?l random variables whit are estimates of Uiand U which we call Viand V jrespectively. 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).

4-73Given 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 U1is 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

4-74our 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:

Theorem 4-1: -----a- 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,evariance 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

4-75the 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:

Theorem 4-3: -w----e 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
4-76various alternatives akeno 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 2Series 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 "DOyou 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.

4-77Theorem 4-5:

---w--s 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:

Theorem 4-6: -v---w- 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-gerhold 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 Viand 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:
Theorem 4-8: ---m-w- 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 ,U2is preferred to U3
4-78than 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 U2is 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 Ulis 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

4-79greater 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:

Theorem 4-9: -e---e- 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 decisonmaker'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.

4-804.4.10. 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,iorof 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:
4-81ei -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 'swith 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 2 ternat ve 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 Ugand

is a good predictor of U % while U3 is independent of either. Suppose furthermore that t e error structures for U2and U3 are highly correlated, while.the error structure for Ul is uncorrelated with the other two. Then if the correlation between U1and U2 is sufficiently high, it is optimal for the individual to decide between U1 and U3 by introspecting on U2and 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.

4-824.4.11. 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. Theorem 4-11: -m---e- 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
4-83technique.

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

4-84are 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.econdway 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 e1and 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 hisa factor
4-85structure 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 Ulor 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 Ulis 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 Ulwith 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

4-86biases 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 ofrational 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
4-87information 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 .closerthe 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 fsdependence 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 decideon the number of contingent valuation questions to ask. Expertsnce reveals that there is a

4-88tradeoff 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

4-89repeated 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. 1This 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,smemory 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.
4-90A 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 andgradually 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 onvarious 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. References

---d-----e


### 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

4-914.

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 Contingenr Valuation Encountered With

m---w-------- -- ----a- --------- ----------- ---- Serious Illness --m---m-- ----- 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

4-92completely 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

4-93outlays 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

4-94It 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.fyears 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

4-95four 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 frompreliminary 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 thebasis 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 withthe 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
4-96the 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

4-97path 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. First Module-

----- --,--,I 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

4-98present 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 theprospective 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
Belief concerning control over health: -w--m- --------- -----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 No ------a-- --------- Questions about sick dayz: -------- e---e ---a VW 7. What conditions (such as specific illness and injuries) caused you to'stayinbed?

4-998.

9.

10 How many of the days that you lost from market work did you stay in he'dall 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 usesina 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.

4-100Referring 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 No ---------a -__-_-----' 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 certain of improving your prospects to thehealth ----e-m 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

4-101doctor'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. Third Module- Risk Perception and Risk Behavior

-e--m ------A --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

4-102markets 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 relative to past: ---- ---- ----A ----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 1to 10 going from least risky to most risky, enter the number you feel best describes the risk.

4-103Swimming Nuclear Alcoholic Pesticides Home Air

Crime Pools Power Beverages and Gas Pollution Herbicides Furnace 

### [1 [I [1 [1 [1 [1 11 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 1,2,3,4or 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.

4-1044.5.6. Fourth Module, 'Contingent Valuation Questions ------ -,-,-,A _-_--- --- ------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
4-105pollution 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+lto T. Equation (4-44) indicates that a change in life expectancy is ambiguous in the sense that there are many sets of changes in

'sconsistent 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 

# ,..’ I

50 55 60 65 70 75 80 85 90 95 100 Age

4-107The 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 isshown 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

4-108it 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 andchestpain. 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.

4-109Figure 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
..2.x
............- ..F<<.x.:.:.:. .*.:.~..~~..:.::~:.:.. :~<.:.>:.>..:.:.: <.~yp.V.V.%~.
...Av,?xfi::.:
... .I..>i...
..... ......5’...:.,._ 85 

# Age

4-110Figure 4-9 PIE CHART FOR MORTALITY LOTTERY WHEEL



# Age 80

-

85 ,

55 %

4-111How 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

4-112will 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 inthis 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
4-113Table 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)

4-114Table 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)

4-115offered. 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 howwe 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.

4-1164.5.7. 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 workindirected 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 .understandingof 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

4-117only 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 Lscounterproductive. 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)

4-118Level 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.

4-1194.6 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 modelledthe 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 contingentmarkets 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

4-120unfolds 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

4-121perceptions 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.

4-122APPENDIX. 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-yearold 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 iscalculated by dividing the number of survi.vors to age 55 by the number of living 20-year

4-123olds: 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 ateachage 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.

4-124Table 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.+ fillOther 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 1296

l 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-125TABLE 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 0.6000 1 0.7Sm32 1.09909

4-126TABLE A-3. PROBABILITY OF SURVIVAL FROM ONE AGE (x) TO ANOTHER AGE (Y)

. Nlmr Agk lx) g’(y) Entwinq fnterwl0 10 to so 40 so 60 70 80 90 --w .- - m m-- - - 100000 Loo00 0 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 089816

ei 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 0.3213 OJisa 0.6102 27183 0.2718 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

97900 l-4.9 s-9.9 97593 

### 10-14.9 97444 is-t?. 9 97322 20-24.9 25-29.9 so-s4.0 97088

96781 9642S ..‘,.,.’

- 95951 

### 35.39.9 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

4-128TABLE 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 5040 SO 60 70 80 90

- -m -.-m m- 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 0.7m0.7937 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 0.04n0.0448 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
4-129TABLE 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 23 4 306 351 475 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

4-130TABLE 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

4-131TABLE 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) Intuwi0 IO 20 30 40 30 60. 7080 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 0.m 0.9466 o.mz 0.9268 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.lszl0.1326 0.13Jb o.rm PS 3J3a 0.0354 o.oss 0.036s Odz67 o.on2 100 0 o:oooo 0.0000 0. oooo o.oooo0.0000 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

4-132TABLE 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 Neoplasmsvascular OtherViol. +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 z3 6 221508 233 122S J&7 2104

32 4 166 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-133TABLE 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

4-134TABLE 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 0.016s0.0170 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

4-135TABLE 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 362 7 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 152 9

4

-L I ‘: