EPA-230-09-86-018

OXIDANTS AND ASTHMATICS IN LOS ANGELES:

A BENEFITS ANALYSIS

Robert D. Rowe

Lauraine G. Chestnut

Energy and Resource Consultants, Inc.

P.O. Drawer O

Boulder, CO 80306

(303) 449-5515

Prepared for:

U.S.

Ann Fisher

Office of Policy Analysis

Environmental Protection Agency

and

Sylvia Champomier

Research Division

California Air Resources Board

March 1986

The information in this document has been funded in part by the United States

Environmental Protection Agency

by the California Air Resources

subjected to the EPA's peer and

publication as an EPA document.

does not constitute endorsement

under Contracts 68-01-6543

Board Contract A2-118-32.

administrative review, and

Mention of trade names or

or recommendation for use.

and 68-01-7047, and

It has been

approved for

commercial products
1.0 “INTRODUCTION AND OBJECTIVES

This study examines changes in behavior, expenditures, and willingness to pay

as related to changes in air pollution and to changes in asthma symptoms. It

is based upon information for a panel of 82 asthmatics in Glendora,

California, gathered in the fall of 1983 and analyzed in 1984 and 1985. The

panel of asthmatics represents individuals of a population expected to be

sensitive to ambient oxidant levels. It was conducted in cooperation with the

U.S. EPA, the California Air Resources Board, and the UCLA Schools of Medicine

and Public Health. The UCLA study included a year long epidemiological

analysis relating air pollutants and other agents to asthma symptoms (Gong et

al. 1986). This summary covers the findings of the economics study conducted

by Energy and Resource Consultants, Inc. (ERC) as reported in Rowe and

Chestnut (1985, 1986).

The objectives of this study were:

o To examine the potential effect of mitigating behavior on epidemiological estimates of the relationship between oxidants and asthma

symptoms,

o To estimate conceptually correct willingness to pay

measures for changes in asthma severity and compare

to the cost of illness (COI) measures that are most

value changes in adverse health symptoms, and

(WTP) benefit

these WTP measures

frequently used to

o To provide economic data for use in calculating benefit estimates for a

sensitive population, in this case asthmatics, for changes in oxidant

levels.

In addition, refinements to the contingent valuation benefit estimation method

were developed and implemented.

The first two objectives of this study were meant to address two limitations

that often occur in economic studies aimed at valuing changes in health status

-1-
due to changes in environmental pollutants. Typically, economic studies use

epidemiology results to estimate changes in health status variables as a

function of changes in environmental quality. Such health status variables

often include changes in work loss and specific health effect measures. Next,

values are assigned to work loss, and medical expenditures are estimated for

the change in health status. The combination of work loss and medical

expenditures are referred to as the COI measure of damages. This economic

valuation approach may tend to understate the value of health impacts of

environmental pollutants for at least two reasons.

o If individuals perceive potential risks and undertake expenditures and

behavioral adjustments to avoid or mitigate exposure to environmental

pollutants, then benefits estimates based on observed epidemiological

relationships between pollutants and health status may be biased toward

zero unless such behavior adjustments are accounted for. Further, the

estimated epidemiological relationships may show a pollutant threshold

level at which statistically significant health and welfare effects are

observable that is higher than the true threshold that would be

estimated if mitigating behavior were considered.

o COI measures of damage for changes in health status may understate the

value of changes in health status. For example, any discomfort

experienced, or changes in activities undertaken to prevent or treat

illness, may be valued in addition to work loss and medical costs

incurred. To date, few studies have attempted to quantify the

importance of discomfort and activity effects associated with changes

in health status.

2.0 AN ECONOMIC MODEL OF VALUE AND LITIGATING BEHAVIOR

The economic analysis is based upon a health production function model derived

from those by Barrington and Portney (Forthcoming) and Gerking et al. (1983).

The model is used to illustrate the level of defensive expenditures and

activities the individual will choose to undertake, how epidemiological

-2-
analyses can be affected when defensive expenditures are ignored, “and the

components of willingness to pay. The primary conclusions of the model are:

1.

2.

3.

Individuals will engage in defensive efforts to minimize adverse

health effects to the point where marginal benefits equal marginal

costs in terms of time and money spent for defensive efforts.

An individual’s VTP to reduce risks of adverse health effects

associated with exposures to air pollution is expected to include

values related to the following damage categories.

i.

ii.

iii.

Medical expenditures for the prevention and treatment of

illness.

Foregone income due to time off work, and

lower productivity at work because of the

treatment of illness.

lover wages or

prevention and

Disutility of reduced ability to participate in desired

leisure activities, household chores, child care, choice of

where to live and recreate, and other activities because of

the prevention and treatment of illness.

iv. Disutility of discomfort due to illness.

COI estimates, based only upon medical costs and vork loss will

probably understate WTP to reduce health impacts by missing the value

of discomfort and by ignoring the value of preventive expenditures and

behavior changes to prevent and respond to illness. A willingness to

pay measure incorporates all of the relevant effects.

-3-
3.0 SURVEY DESIGN

Two sets of survey instruments were used: (1) The UCLA instruments, used for

the epidemiology analysis; and (2) the ERC daily diary questionnaire} and the

ERC general background and WTP questionnaire.

The UCLA Epidemiology Surveys and Analysis

UCLA researchers collected data on over 90 subjects with diagnosed asthma. The

data were collected over an eleven month period from January 1983 through

November 1983. All of the subjects lived in Glendora, California, a town in

the San Gabriel Valley east of Los Angeles, where state and federal standards

for ambient ozone and other pollutants are exceeded frequently. At the

beginning of the study each participant completed a general questionnaire on

medical history, asthma symptoms, household and socioeconomic characteristics

and other data.

During the study period, each subject kept a daily record of his or

her asthma symptoms. These were measured in three different ways: (1)

subjects rated their daytime and nighttime symptoms in several categories on

a 1 to 7 severity scale; (2) subjects took twice daily readings of their

pulmonary peak flow; and (3) subjects used, as needed, an inhaler that

recorded the amount of medication used. Every two weeks the subjects were

given more extensive tests and answered questions about any illnesses they may

have had or other things that may have affected their asthma during the two

week period. Air pollution

Management District Station

pollens, fungal spores, and

on-site facility. See Gong

levels were taken from the South Coast Air Quality

60. Weather conditions and the amount of

potential aeroallergens were measured at the

et al. (1986) for additional details.

The ERC Economic Surveys

The economic surveys were designed to obtain additional information from the

UCLA panel without interfering with the UCLA study. Subjects aged 16 and over

 (the adult group) were asked to complete a diary at home each day for four

weeks and to complete the general questionnaire during their last visit to the

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UCLA facility. The parents of subjects under sixteen years old were asked to

complete the general questionnaire only. Sixty-four of the then current

sixty-five adults, and parents of all eighteen of the panelists under sixteen

agreed to participate.

Several of the questions referred to "bad

the subject adjusts his or her activities

What is "bad" will be different for every

asthma days" so as to determine how

when his or her asthma is "bad”.

individual. Bach subject therefore

was asked to pick the highest rating on the seven point UCLA severity scale

that he or she would still consider to be a "good asthma day". The

respondents had been using the UCLA seven point severity scale to rate their

daily asthma for the past 8 to 10 months and were quite familiar with it. The

subject then was told that when the questions referred to a "bad asthma day"

it meant any day on which he would rate his asthma symptoms higher (worse)”

than the selected point.

The Daily Diary. During October and November 1983 respondents provided diary

information on perceptions and activities. The objectives were to determine

if these individuals perceive air pollution as affecting their asthma,

determine if their perceptions accuractly correlate with ambient conditions,

and examine whether they alter their behavior to reduce or minimize adverse

asthma symptoms when they anticipate having a bad day with air pollution as

possible cause.

Six questions were asked each day:

o When the day started, what did you think might affect your asthma

during the day?

a

o When the day started, did you think you might have asthma symptoms that

would result in a bad asthma

o How did your asthma symptoms

that day?

o How many hours were spent in

day?

affect your work, schoolwork or

different activity categories?

-5-

housework
o Did you change your leisure activities to avoid

asthma symptoms that you would consider to be a

having or worsening

bad asthma day?

o Did you change your sleep activities to avoid having or worsening

asthma symptoms that you would consider a bad asthma day?

The General Questionnaire. The general questionnaire identified ways in which

asthma affects the respondents’ well-being. It provided data for estimating

economic measures of changes in well-being associated with changes in the

frequency of asthma symptoms that result in a bad asthma day.

The questionnaire consisted of seven sections. The first six addressed asthma

effects on medical expenditures, vork and school, leisure and chores, and

residential choice. Part VII of the questionnaire asked respondents to rank

in importance five categories of benefits they might receive if their asthma

improved including lower medical expenditures, higher income or productivity,

more flexibility about where to live, better chance to participate in leisure

activities, and less pain and suffering or discomfort. After the ranking,

respondents were asked how much they would be willing to pay in additional

taxes each year for a program that would reduce their bad asthma days by

one-half. Evaluation of zero bids, the medical cost data, and ranking

responses were used to analyze the internal consistency of the individual’s

WTP responses. The final question was household income. Other socioeconomic

variables were available through the UCLA questionnaires.

4.0 RESULTS OF THE DAILY DIARY ANALYSIS

Each of 64 adult respondents completed the diary for an average 27.8 days

resulting in a total of 1779 observations (or person-days). Individuals

started the diary between October 12 and November 2, 1983, depending upon

their schedule of visits to the UCLA Glendora facility. Due to king late in

the fall of the year and the unusual amount of rain, there were only 13 days

with peak hourly ozone readings in excess of 12 pphm (the federal standard) in

Glendora during the study period, although peak hourly readings above 30 pphm

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are not uncommon in the

levels mean that it may

the diary results.

summer and early fall in this area. The 10V pollution

be more difficult to identify mitigating behavior in

For analysis purposes, the diary data were analyzed with both the "full

sample" of 64 individuals and a “reduced sample” of 32 individuals who checked

air pollution as a possible factor aggravating their asthma on one or more

days. It was felt that those individuals who never indicated air pollution as

a factor were, in their opinion, either not sensitive to air pollution or were

not aware of air pollution at the levels experienced during the study period,

and could not be expected to alter” their behavior in response to changes in

their perceptions about air pollution, which was the relationship of interest.

Perceptions About Air Pollution

If respondents accurately perceive air pollution and then act to mitigate any

possible adverse effects, this should be

and economic studies.

The respondents checked air pollution as

important to consider in epidemiology

a factor potentially aggravating

their asthma on only 292 person-days (16.4 percent of the total). The

infrequency of this response could have been the result of the unusually low

pollution levels. For those days when air pollution was checked, respondents

were more likely to check tension, stress, and anxiety; and animals, plants,

and pollens; as potentially aggravating their asthma. This suggests that

asthmatics perceive that air pollution is more likely to affect their asthma

when other factors are also present or vice versa.

Both ordinary least squares and logit regression analyses (See Table

1 for definition of variables and Table 2 for results of these analyses for

the reduced sample) demonstrate that the probability of checking air pollution

as a factor possibly aggravating asthma symptoms during the day is

significantly related to actual ambient oxidant levels (as well as to total

suspended particulate levels, which were highly correlated with oxidant

levels). Differences in asthma severity did not influence perceptions about

air pollution. The analysis suggests that for a day with a peak hourly O3

-7-
Table 1

Definition of Variables

Name Definition Source

AQI

AQ2

A2

A3

A4

A5

A6

A7

A8

EXP4

EXP5

EXP6

EXP7

TEMP

HUMID

PRECIP

AGN1 to

AGN10

SYMPTOM

HOA

WEEKEND

SEV

INC

AGE

SEX

Maximum hourly ozone reading (pphm)

Daily Average Ozone (pphm)

Concerned that illness might affect

asthma today = 1, 0 otherwise

Concerned that tension, stress might affect

asthma today = 1, 0 otherwise

Concerned that exercise might affect asthma

today = 1, 0 otherwise

Concerned that air pollution might affect

asthma today = 1, 0 otherwise

Concerned that allergies might affect asthma

today = 1, 0 otherwise

Concerned that weather might affect asthma

today = 1, 0 otherwise

Concerned that a bad day yesterday might affect

asthma today = 1, 0 otherwise

Expected a bad asthma day with exercise as a

concern

Expected a bad asthma day with air pollution

as a concern

Expected a bad asthma day with allergies as a

concern

Expected a bad asthma day with weather as a

concern

Daily temperature (F.) at 1 p.m. at El Monte

airport

Daily relative humidity at 1 p.m. at El Monte

airport

Daily precipitation (inches) at Glendora West

Fire Control

Ten daily allergen levels (trees, shrubs, molds,

etc.)

Summary of daily asthma symptoms reported by

the respondent over the entire UCLA study period;

used as an indicator of severity

Daily hours in outdoor active activities

1 if a non-work day for the individual, 0 otherwise

Severity of asthma based upon respondents reported

monthly frequency times intensity (reported

on UCLA instruments) summed over the calendar

year

Income

Age

Sex; 0 = male, 1 = female

Diary

Diary

Diary

Diary

Diary

Diary

Diary

Diary

Diary

Diary

Diary

UCLA

UCLA

UCLA

UCLA

UCLA

UCLA

UCLA

UCLA

General

UCLA

UCLA

-8-
Table 1 (continued)

MEDVHH

RTFM

GDAY

NBAD

NBADR

ADULT

TAXBID

NOBS

Variable medical costs/year paid by the household

for this asthmatic (doctors, hospitals, medicines,

etc.)

Respondent’s share of total household asthma

(0-100%)

Highest day rating on UCLA scale still

considered to be a good day

Number of bad days/year - number of days where the

day rating is greater than GDAY

1/2 NBAD = Number of days reduced in WTP scenarios

Is the respondent an adult (16+ years)

1 = yes, 0 = no

WTP response to reduce bad asthma days in half

through a tax vehicle

Number of observatories used in the analysis

General

General

Diary and

General

UCLA

--

General

General

--

Note: The prefix D is used to denote deviations from the mean, P to denote

percentage of the mean and LN to denote the natural log of the variable.

UCLA = UCLA Survey Instruments

Diary = ERC Daily Diary Survey Instrument

General = ERC General Questionnaire

CARE = California Air Resources Board

-9-
Table 2

Results of the OLS and Logit Estimation of the Perceptions

Equation for the Reduced Sample*

Dependent Variable A5 (Respondent felt air pollution might affect asthma

that day, mean = .318)

Explanatory Variable Logit OLS

Variable Mean Coefficients Coefficients

Constant

AQ1

SEV

INC

AGE

SEX

R2

F

Likelihood

Ratio Test

NOBS

-.572

(1.17)

8.3 .88 E-1

(5.61)

172.4 -.11 E-2

(.83)

32125 -.34 E-5

(.74)

38.5 -.49 E-2

(.83)

.52 -.93

(5.48)

76.38

866 866

.358

(3.7)

.18 E-1

(5.8)

-.18 E-3

(.69)

-.82 E-6

(.77)

-.89 E-3

(.78)

-.191

(5.65)

.086**

16.2

866

Source: Rowe and Chestnut (1985, 1986)

* t-staistics given in parentheses.

**The R2‘s reported in Rowe and Chestnut (1985) were in error. The multiple R was incorrectly reported. The correct R2‘s for previous Table 4.3 are:

Equation: 1 2 3 4

R2: .040 .043 .086 .088

-10-
level equal to the federal standard of 12 pphm, 41 percent of the males and 

percent of the females in the reduced sample will observe the air pollution

and expect it to affect their asthma. Looking at the “full sample,” the

percentages who will expect air pollution to affect their asthma are about

half the rate for the reduced sample.

Pollution and Daily Schedule

If asthmatics perceive that air pollution might aggravate their asthma, the

perceptions may cause them to take averting or responsive actions in terms 

altering their daily schedule to minimize adverse symptoms. For example, o

might spend less time in active outdoor activities, because pollution level

are typically higher outdoors on high pollution days and exercise can

aggravate asthma

hypothesis.

The first set of

symptoms. Three sets of models were analyzed to examine t

models used ordinary least squares (OLS) regressions to

relate changes in hours spent in seven activity categories to expectations

that a bad asthma day might occur and that air pollution was a potential

aggravating factor. To isolate substitution in time spent in different

activities as a result of differences in expectations about asthma that mig

be related to air pollution, these models were estimated for those individu

in the "reduced sample." The results indicate that when these asthmatics

expected a bad asthma day with air pollution as a possible factor, they

less time on chores and both active and inactive leisure, and more work

occurred. However, the statistical significance of these results was

generally weak.

The second set of models considered the potential simultaneity between

spe

los

expectations of a bad asthma day and hours spent in different activities. 

was hypothesized that the individual would spend less time in active outdoo

activities on days when he or she expected a bad asthma day and was concern

about air pollution. It was also hypothesized that on days when more activ

outdoor activities were planned, the individual might be more likely to exp

a bad asthma day related to air pollution. To the extent that this 

-11-
simultaneity exists, it could have biased toward zero the OLS coefficients

relating changes in activities to expectations about bad asthma days where ai

pollution was a concern.

To simplify this second analysis, all active outdoor leisure and work hours

were aggregated into a single variable for hours in active outdoor activities

Two stage least squares was used to estimate two equations:

active outdoor activities, and the other for whether or not

expected a bad asthma day with concerns about air pollution

aggravating factor. The results of this estimation suggest

simultaneity between hours in active outdoor activities and

one for hours in

the individual

as a potentially

that the

expectations abou

air pollution effects is not statistically significant for the sample group

and time period, although the coeffients on these variables” were of the

expected signs.

Given the lack of evidence of simultaneity, another OLS model was estimated

incorporating the refinements from the simultaneous modeling effort. These

results, reported in Table 3, indicate that expectations that air pollution

may contribute to a bad asthma day lead to an average 20 percent reduction in

active-outdoor activities for individuals in the "reduced sample." Contrary

to previous analyses, these results are statistically significant.

In summary, each of the modeling efforts indicated that if respondents who

are concerned about air pollution expect a bad asthma day with air pollution

as a contributing aggravating factor, they will substitute behavior in a

manner that may be expected to reduce adverse asthma symptoms. These changes

in behavior are potentially substantial, on the order of a 20 percent

reduction in time spent in active outdoor activities. This change in behavio

is likely to be a combination of mitigating and responsive actions. It shoul

be noted that during the study period, oxidant levels were generally quite lo

relative to levels experienced during the mid-summer. Had higher levels of

oxidants been experienced during the study period, even larger substitutions

in activities might have been observed.

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Table 3

Relationship Between Changes in Active Hours Spent Outdoors

end Expectations That a Bed Asthma nay Hay Occur

Dependent Variable = DHOA

Variable Coefficient t-Ratio

CONSTANT

EXP4

EXP5

EXP6

EXP7

WEEKEND

A2

A3

A8

PRECIP

TEMP

R 2 = .10,

F = 6.53

.222

.147

-.627

.579

-.317

1.647

-.315

.303

-.373

.199

-.0050

.27

.50

-2.52

1.92

-1.41

7.15

-1.31

1.70

-1.48

.45

-.44

Source: Rowe and Chestnut (1986)

-13-
Medical Expenditures

Expenditure data were collected on medical supplies, equipment, and special

treatment programs. These data were separated into fixed and variable costs

and adjusted by the number of asthmatics in the household and the amount paid

by insurance. Information on doctor and hospital visits was obtained from the

respondents and from UCLA. Sample averages are reported in Table 4.

Estimated variable medical costs paid by the household and attributed to the

respondent, including medications, treatments, doctors, and hospitals, were

regressed against asthma severity (SEV) and selected socioeconomic variables

(Table 5). Significant in the regression results is that” the elasticity of

variable medical costs with respect to severity is just less than one,

indicating that variable costs increase just less than proportionally to

severity. A variable for whether or not the respondent had insurance was

never significant when included and had minimal effect on the estimates of

other coefficients.

Effects of Asthma on Work, School, Non-Paid Chores, and Leisure

The survey results indicate that for the sample population, more severe asthma

is likely to affect short-term and long-term earnings potential. Of the 47

respondents employed full or part-time, 20 felt their choice of job was

affected by their asthma. Twelve respondents felt their asthma affected their

income. These respondents had, on average, higher asthma severity than the

rest of the sample.

Turning to students, nearly two of every three felt their asthma affected

their performance at school, particularly their extracurricular activities

(63%) and their grades (40%). (Recall that there are only 16 students in the

sample.)

Eighty percent of the adult asthmatics felt that their asthma affected their

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ability to perform chores that they routinely do, but do not get paid for.
Table 4

Average Medical Costs per Year for 82 Asthmatics in Glendora, California

Household For This

Total Asthmatic

Total Fixed Cost Expenses

Total Variable Expenses/Year

Household Paid Fixed Cost Expenses

Household Paid Variable Cost Expenses/Year

Insurance Paid Fixed Cost ExDenses

Insurance Paid Variable Cost

Fixed cost expenses refer to

Pressure Breathing Machines.

Expenses/Year

one-time goods

Variable costs refer to expenses repeatedly

doctors visits.

Insurance includes government programs.

$713 $573

528 435

619 486

268 208

94 87

260 227

such as Intermittent Positive

incurred such as for medicines or

-15
Table 5

Variable Medical Costs as a Function of Asthma Severity

Dependent Variable:Log of variable medical costs paid by the household; LN

(MEDVHH)

Explanatory

Variable (efficient t-ratio

Constant

LN (SEV)

LN (INC)

LN (RFTM)

ADULT

SEX

F

R2

NOBS

-1.13 -.49

.92 2.40

-.105 -.47

● 45 1.06

-.51 -1.33

.90 2.86

4.73

.24

82

Sample: Full General Questionnaire Sample

See Table 1 for variable definitions.

Source: Rowe and Chestnut (1985)

-16-
Nineteen percent (10 respondents) hired help on a regular basis to perform

chores that they would perform themselves if their asthma were less severe.

These individuals spent an average $1,478 per year for these services, and had

significantly higher average asthma severity relative to the remainder of the

sample. Analysis of-costs of chores hired and asthma severity for these

individuals indicates that a 10 percent increase in severity results in an 8.8

percent increase in expenditures for chores hired out in part due to asthma.

Asthma affects leisure activities for nearly 75 percent of the respondents.

The respondents indicated that most often they change their activities or

spend less time in leisure activities while occasionally doing the same

activities at a different time of day.

Rankings

Respondents ranked, in descending order of importance, five benefits they

might receive from reduced asthma. This question was a final step in

preparing respondents for the total willingness to pay question and, in

combination with estimated medical costs, provided a validation check on the

WTP responses. The rankings are summarized in Table 6a. Assigning values of

one when a category is ranked first and five when a category is ranked fifth,

and six if the category is not ranked, yields the overall mean ranking.

Table 6b presents t-test results for the hypothesis that the mean scores are

identical. The t-tests reject the hypothesis that the mean scores are

identical except for medical costs and work loss. Discomfort and asthma

effects on activities were clearly ranked above cost of illness measures of

medical costs and work loss, which were ranked very closely to each other.

The low ranking for the residential flexibility should be cautiously

interpreted because it is based upon the responses of a group of asthmatics

who live in a very high air pollution area. They have not moved in order to

reduce their exposure to air pollution, which may aggravate their asthma, and

they may not be representative of other asthmatics in this regard.

A discriminant analysis was also used to examine the relationships between the

rankings and the characteristics of the respondents. The results indicate

-17-
Results

a.

Table 6

of the Ranking

Rankings

Times Ranked

Over- SE of Times n

all Mean the

category Score Mean 1st 2nd 3rd 4th 5th (=6)

Discomfort 1 2.16 .16 40 19 11 1 4 7

Activities 2 2.89 .18 22 20 12 13 3 12

Effects

Medical 3 tie 3.63 .20 12 1 4 19 8 5 24

costs

Work Loss 3 tie 3.79 .20 7 20 14 11 2 28

Residential 5 4.88 .15 1 6 9 1 0 16 40

Choice

b. t-ratios* on Pairwise Comparisons of Average Scores

Discomfort Activities Had. costs Work Loss

Discomfort ---

Activities 3.0 ---

Medical Costs 5.7 2.7 ---

Work Loss 6.4 4.5 .6 ---

Residential Choice 12.4 8.5 5.0 4.4

* t-ratio of hypothesis that the ❑ ean rankings are equal.

Source: Rowe and Chestnut (1985)
that as age, family

were more likely to

size, and number of bad asthma days increased asthmatics

rank medical costs or work loss as the most important

benefit of reduced asthma. Higher income, being an adult (versus child), and

a greater share of total household asthma severity led to increased likelihood

of ranking a lifestyle category first.

The ranking results play an important role in subsequent analyses. In these

analyses it was assumed that in ranking the importance of each benefit, the

respondents considered the net effects of their asthma symptoms after

selecting a level of medical treatment. Based on this assumption, it was

presumed that willingness to pay for each of the benefits would follow the

same order as the rankings. This means, for example, that an individual who

is able to fully mitigate adverse effects of asthma with medication would be

expected to rank reductions in medical expenditures’as the most important

benefit of an improvement in asthma and would rank the other benefits as

unimportant.

Tax Bid Analysis

The following contingent valuation question was asked: "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 taxes each year that you and

your household would be willing to pay

A payment card with alternative dollar

question appeared generally to be well

and still support such a program?”

amounts accompanied the question. The

received with 69 non-zero responses, 12

zero responses and one refusal. Upon detailed evaluation of the responses

(discussed in more detail below), some zero observations were retained and a

few non-zero bids deleted, resulting in a mean bid for 65 observations, called

the tax bid sample, of $401 per year with a standard error of the mean of $85.

This estimate is for an average number of bad asthma days reduced of 37 per

year (50% of the average number of bad days). The mean estimated variable

medical costs paid by the household for this group of respondents was $272.00

with a standard error of the mean equal to $27.62.

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Models were derived from consumer utility maximization that related changes in

consumer’s surplus, measured by the tax bid, to changes in asthma severity.

Table 7 presents estimation results for one of the more simplistic, but

statistically most significant, models, The model suggests that WTP increases

at about one-half the rate of the number of bad asthma days reduced and

increases almost linearly with the level of asthma severity (on the 1 to 7

scale) that was viewed by the respondent as the highest severity that is still

a good asthma day. Predicted WTP values for alternative frequency and

intensity of bad asthma days using the results of Table 7 are reported in

Table 8.

Alternative tax bid specifications considered included variables representing

the number of bad asthma days at each intensity level from level 2, days with

very mild symptoms, to level 7, days with very severe symptoms. While the

coefficients were statistically significant on many of the variables

representing bad asthma days at each intensity level, the size and

significance of these coefficients were not stable across small changes in the

regression specifications. It was presumed this was the result of

multicollinearity across these variables.

WTP Response Consistency Checks

A major issue in contingent valuation (CV) studies has been the credibility of

the values received through hypothetical questions (Cummings et al., 1984).

This survey instrument was designed specifically to examine the plausibility

of the CV responses by examining zero and large bids and by comparing the tax

bid, medical costs, rankings and other responses. Of the 82 respondents, one

refused to respond to the tax bid question and one gave a bid exceeding his

stated income. These responses were deleted. Twelve zero responses were

given. Based upon a typical zero bid follow-up question eleven bids would

have been deleted, but subsequent analysis indicated that five of these bids

were probably valid because the individual’s asthma condition was such that he

or she had

Therefore,

zero. The

zero or one bad day in the last year and very low medical costs.

reducing bad asthma days by half could appropriately be valued at

remaining seven zero bids were by respondents with at least $150

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Table 7

Tax Bid Regression Model

Dependent Variable = LN (TAXBID)

Sample = Tax Bid Sample

Variable Constant LN (NBADR) LN (GOAT) AGE ADULT

Coefficient 4.28 .552 -.683 -.47 .77

t-ratio (2.78) (4.26) (::% (-1.21) (-1.09) (.98)

NOBS = 65 F Statistic = 5.26

R 2 = .308 ~2 = .250

* Source: Model version 2 Table 10a (revised Table 4.15a) Rowe and

Chestnut (1986)

Table 8

Predicted WTP Values ($’s)

Highest Asthma Severity Number of Bad Days Reduced

Considered by Respondent

to be a Good Day (GDAY) 1 5 15 50

1

2

3

4

(no symptoms) $ 9 $22 $40 $79

(very mild symptoms) 19 47 86 166

(mild symptoms) 30 133 258

(moderate symptoms) 41 K 181 353

Source: Table 10 (revised Table 4.15b), Rowe and Chestnut (1986) Value

predicted for male adults at the mean age.

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per year in variable medical costs, 18 or more bad asthma days and who gave a

rejection response to the zero bid follow-up questions. These were deleted

from further analysis. Four non-zero bids were also deleted from the tax bid

sample because for these individuals NBAD equalled zero, while the bid

exceeded $100 per year. For these individuals it was presumed that the NBAD

estimates, which were extrapolated from six months of data, may have been in

error, especially if their asthma symptoms were seasonal. In this case the

bids may be valid, but a possible significant error in the NBAD estimate could

bias the regression results.

The responses of sixty-eight respondents who gave non-zero bids less than

their income were analyzed using the following consistency check. It was

assumed that a 50 percent reduction in bad asthma days would yield a 46

percent reduction in variable medical costs (.92 from Table 5 times 50 percent

reduction in asthma severity). WTP should therefore exceed .46 of the

individual's variable medical costs. Further, if changes in medical costs are

ranked third, for example, total WTP should exceed .46 of variable medical

costs by at least a factor of three, if changes in each of the above ranked

categories are valued the same or more highly than changes in medical costs.

If changes in medical costs are ranked fifth then total WTP should exceed .46

of variable medical costs by a factor of five or more and so forth.

A limitation of the consistency check analysis is that while the individuals

may have attempted to give accurate and reasonable estimates for their ❑ edical

costs and underlying values for changes in asthma, measurement error may

result in failure of the consistency check.

Of the 68 individuals with responses analyzed with the

provided medical cost, tax bids and rankings that were

consistency check, 37

consistent with the

above assumptions, and another 16 were consistent using a reduction in medical

costs of 25 percent or allowing a 33 percent measurement error in either the

tax bid or medical cost estimates.

A second

are based

reduction

important limitation in the consistency check is that the WTP bids

upon a 50 percent change in bad asthma days, while the estimated

in medical costs is based upon a 50 percent change-in severity

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measured as the sum of monthly frequency times the intensity of asthma

symptoms. For an individual with a large number of bad asthma days, a 50

percent reduction in bad asthma days and in overall asthma severity may be

quite similar. The correlation between 50 percent changes in these measures

is likely to lessen as the number of bad asthma days decreases, which was

supported with the sample data. This is another reason for using the

alternative of 25 percent of medical costs in a second application of the

consistency check. This is viewed as a weakness of the design of the

application, rather than the general design of the consistency check

procedure.

Overall, the bid evaluation and consistency check procedure indicate the tax

bids are quite reasonable once obvious protest bids are eliminated. Of the 7

bids not easily identified as protests (82 less 1 refused, 1 bid exceeding

income and 7 protest zeros) 5 were acceptable zeros, 37 passed the consistenc

check using .46 of the variable medical costs and 16 passed the consistency

check using .25 of variable medical cost. Therefore 79 percent of the

non-protest responses appear to be quite accurate in terms

consistency with other information.

Comparing COI and WTP Economic Measures of HealthDamage

Economic analyses of health damage often rely upon cost of

(COI) of damage, even though economic theory suggests that

of their

illness measures

these measures are

likely to understate conceptually correct WTP value measures. In this sectio

we briefly address the ratio of WTP to COI measures from the perspective of

the affected individual and the perspective of society based upon evidence in

this study.

The rankings provide the first simple evidence that WTP measures exceed COI

measures for the affected individual. If changes in discomfort and leisure

activity effects from changes in asthma are both ranked, and therefore valued

more highly than changes in medical costs; and changes in medical costs and

work loss are ranked, and therefore valued, approximately equally, then the

total WTP (the aggregate value of all damage categories) can be expected to b

at least twice COI.

-23-
An alternative approach, again from the perspective of the affected

individual, is to compare the total WTP tax bid for a 50 percent reduction in

bad asthma days to estimated changes in medical costs for a 50 percent

reduction in bad asthma days and, following the rankings, make the assumption

that work loss equals medical costs for a change in asthma. This leads to a

WTP/COI ratio of 1.61. Other approaches to measuring the WTP/COI ratio

suggest that the ratio may be as high as 3.7.

Society incurs costs and may hold values for reductions in morbidity

incidence beyond those costs and benefits incurred by the individual.

Society directly incurs the full medical costs including those paid by

insurance or government programs, while the individual typically incurs less

than the full medical costs associated with his illness. Further, society

directly incurs lost work productivity when an individual is away from work

whereas, due to paid sick leave, the individual may perceive a smaller

personal loss. Others in society may hold values related to reduced sickness

for those who are affected. This is reflected in the research of Needleman

(1976), where WTP by others to prevent an individual’s death increased total

WTP by 25 to 100 percent.

To obtain an estimate of the WTP/COI ratio from a social perspective, the

individual WTP and COI values were escalated by estimated social costs and

benefits. On a sample wide basis, households directly paid about one half of

variable medical costs while insurance or other programs paid the rest.

Therefore the total social medical cost component of WTP and COI is

approximately double that of the individual. This survey provides no

information to gauge the social versus individual costs related to work loss.

Therefore, for the sake of analysis and following the medical cost doubling,

we assume total social work loss costs are double the individual’s perceived

work loss costs. The estimated social COI measure is thus estimated to be

roughly double the individual’s COI measure. Social WTP also can be expected

* The estimated change in medical costs for a 50 percent change in bad asthma

days equals .92 (percent change in asthma) x $272 (average variable medical

costs), or $125. Assuming the workloss change equals the Change medical

costs (based upon the rankings), COI=$250. WPT/COI=$401/$250=1.61.

-24-
to exceed individual VTP. The estimated WTP/COI ratio for society is

dependent upon the assumptions about willingness to pay by others to reduce 

individual's asthma, which we call Z. Using the above assumption on sociall

incurred medical costs and work loss and assuming Z equals zero, the WTP/COI

ratio ranges from 1.31 to 2.35. Assuming Z equals 50 percent of the

individual’s WTP, the social WTP/COI ratio increases to between 1.55 and 2.6

The calculation of WTP/COI ratios undertaken here must be interpreted as

suggestive due to measurement error and the assumptions used. With these

caveats in mind, the analysis suggests that the WTP/COI ratio for asthma, as

we have defined COI measures, are best estimated to be in the range of 1.6 t

2.3, with 2.0 as the best point estimate using the perspective of an

individual. Using the perspective of society, the estimated range is 1.3 t

2.0, with 1.5 as the best point estimate. If full medical costs or work los

costs are not included in a COI measure, which is frequently the ease due to

data limitations, a COI measure may be capturing an even smaller portion of

total WTP.

-25-
6.0 BIBLIOGRAPHY

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Goods: A State of the Arts Assessment of the Contingent Valuation Method.

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Gerking, S.D., L.R. Stanley, and W.N. Weirick. An Economic Analysis of Air

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of Economics and the Institute for Policy Research, University of Wyoming,

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Gong, H., Jr., M.S. Simmons, V.A. Clark, D.P. Tashkin, A.H. Coulson, G.H.

Spivey. Relationship Between Air Quality and Respiratory Status of

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Rowe, R.D., and L.G. Chestnut. Addendum To: Oxidants and Asthmatics in Los

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