EPA-600/5-79-00le

February 1979

METHODS DEVELOPMENT FOR ASSESSING

AIR POLLUTION CONTROL BENEFITS

Volume V

Executive Summary

by

David S. Brookshire, Thomas D. Crocker (Project Director),

Ralph C. d\'Arge

University of Wyoming

Laramie, Wyoming 82071

Shaul Ben-David and Allen V. Kneese

University of New Mexico

Albuquerque, New Mexico 87131

William D. Schulze

University of Southern California

Los Angeles, California 90007

USEPA Grant #R805059010

Project Officer

Dr. Alan Carlin

Office of Health and Ecological Effects

Office of Research and Development

U.S. Environmental Protection Agency

Washington, D.C. 20460

OFFICE OF HEALTH AND ECOLOGICAL EFFECTS

OFFICE OF RESEARCH AND DEVELOPMENT

U.S. ENVIRONMENTAL PROTECTION AGENCY

WASHINGTON, D.C. 20460

DISCLAIMER

This report has been reviewed by the Office of Health and Ecological
Effects, Office of Research and Development, U.S. Environmental
Protection Agency, and approved for publication. Approval does not
signify that the contents necessarily reflect the views and policies of
the U.S. Environmental Protection Agency, nor does mention of trade
names or commercial products constitute endorsement or recommendation
for use.

PREFACE

This project was initiated in the late fall of 1976 when Drs. Alan
Carlin and Roger Cortesi of the USEPA wished to consider the
contributions economic analysis might make to assessing the values of
EPA\'s environmental improvement programs. Both men made numerous useful
suggestions in the early stages of the project. Dr. Carlin has been a
uniquely valuable project officer. He has prodded when prodding (in
retrospect) was necessary, has offered encouragement at times when
discouragement reigned, and has been a useful technical critic. In
short, he has been a highly valued colleague.

In addition to the principal investigators, many individuals have
contributed research studies for this project. These include Dr. Richard
M. Adams of the University of Wyoming; Drs. Maureen L. Cropper and W.
Russell Porter of the University of California, Riverside; and Drs.
Robert A. Jones and John G. Riley of the University of California, Los
Angeles. Mr. Narongsakdi Thanavibulchai of the University of Wyoming,
Dr. Mark A. Thayer of the University of New Mexico, and Mr. Berton J.
Hansen of the University of California, Riverside, have also made
substantive written research contributions. Mr. Barry Ives and Ms. Kris
Kirshner of the University of New Mexico; Mr. Larry Eubanks and Dr.
Robert L. Horst, Jr., of the University of Wyoming; and Dr. Osman Bubik
of the University of the Bosphorus (Turkey) have contributed their
analytical and their organizing talents.

Many research assistants have put in almost countless hours in data
collection, preparation and collation. These are, from the University of
Wyoming, John Accardo, Rex Adams, Curt Anderson, Julie Berglund, Tony
Fest, Steve Furtney, Clive Jones, David Livingston, Mike Miller,
Stephanie Morrow, Bulent Paker, Morteza Rahmathan, and Mohammed Saidi;
and from the University of New Mexico, David Boldt, Kay Meyer, Lex
Tysseling, John Tysseling, and Dolores Willett.

Drs. Dennis Aigner of the University of Southern California, Shelby
Gerking of the University of Wyoming, Leon Hurwitz of the Department of
Pharmacology at the University of New Mexico, Lester Lave of the
Brookings Institution, Roland Phillips of the Department of Epidemiology
at Loma Linda University, and Eugene Seskin and V. Kerry Smith of
Resources for the Future have provided sound advice and cautions on
various aspects of the epidemiological effort. None, however, are
responsible for the results obtained.

Finally, Ms. Stephanie Morrow, Ms. Susan Pynn, Mrs. Wendy Clements, and
Mrs. Levi Stephenson have provided efficient and timely administrative
services.

ABSTRACT

The studies summarized by this volume represent original efforts to
construct both a conceptually consistent and empirically verifiable set
of methods for assessing environmental quality improvement benefits.
While the state-of-the-art does not at present allow us to provide
highly accurate estimates of the benefits of reduced human or plant
exposure to air pollutants, these studies nevertheless provide a set of
fundamental benchmarks on which further efforts might be built. These
are: (1) many benefits traditionally viewed as intangible and therefore
non-measurable can, in fact, be measured and be made comparable to
economic values as expressed in markets; (2) aesthetic and morbidity
effects may dominate the measure of benefits as opposed to previous
emphases on mortality health effects; and (3) the likely economic
benefits of air quality improvements are perhaps as much as an order of
magnitude greater than pevious studies had hypothesized.

CONTENTS

Page

Abstract \...\...\...\..... iv

Figures \.... vi

Tables vii

Introduction 1

Benefit Analysis and the New Generation of Environmental

Problems 2

Epidemiology Experiments 3

The South Coast Air Basin Urban Experiment 15

The South Coast Air Basin Agricultural Experiment 19

Related Studies 20

General Conclusions 20

Footnotes 22

References 23

FIGURES

[Number]{.underline} [Page]{.underline}

1 A Representation of the Effect of Air Pollution Upon Labor

Productivity 9

TABLES

[Number]{.underline} [Page]{.underline}

1 Summary of Two-Stage Linear Estimates of Factors in Human

Mortality Hypotheses not Rejected at the 97.5% Confidence

Level (One-tailed t-test, t \> 20) 5

2 Methodology for Health Benefits Assessment 6

3 Urban Benefits from Reduced Mortality: Value of Safety for

60 Percent Air Pollution Control 7

4 Major Assumptions Limiting Generality of Results 10 & 11

5 Distinguishing Features that Enhance the Generality of Results 12

6 Estimated Aggregate Gains in 1970 U.S. Urban Labor Productivity

Due to a 60 Percent Reduction in Air Pollution 14

7 Alternatives Estimates of Monthly Bids by Household, and

Aggregate Benefits for Air Quality Improvement in the South

Coast Air Basin 17

[Introduction]{.underline}

Benefit-cost analysis is a well established mode of applied economics
extensively used for the evaluation of public investment projects. It is
now also being employed increasingly to evaluate new technologies,
scientific programs, and environmental policies. These applications
present special difficulties. Before turning to these more explicitly,
it will be useful to say a little about the history of benefit-cost
analysis.

The technique was developed initially to evaluate water resources
investment made by the federal water agencies in the United States,
principally the United States Bureau of Reclamation and the United
States Army Corps of Engineers. The general objective of benefit-cost
analysis in this application was to provide a useful picture of the
costs and gains from making investments in water development. The
intellectual \"father\" of benefit-cost analysis is often said to be the
19th Century Frenchman, Jules Dupuit, who in 1844 wrote a study \"On the
Measure of the Utility of Public Works.\" In this remarkable article he
recognized the concept of consumers surplus and saw that consequently
the benefits of public works are not necessarily the same thing as the
direct revenues that the public works projects will generate.

Early contributions to development of benefit-cost analysis as a
practical technique generally did not come from the academic or research
communities but rather from government agencies. The agencies
responsible for water development in this country have for a long time
been aware of the need for economic evaluation of projects. In 1808
Albert Gallatin, Jefferson\'s Secretary of the Treasury, produced a
report on transportation programs for the new nation. He stressed the
need for comparing the benefits with the costs of proposed waterway
improvements. The Federal Reclamation Act of 1902 which created the
Bureau of Reclamation and was aimed at opening western lands to
irrigation required economic analysis of projects. The Flood Control Act
of 1936 proposed a feasibility test based on classical welfare economics
which requires that the benefits to whomsoever they accrue must exceed
costs. In 1946 the Federal Interagency River Basin Committee appointed a
subcommittee on benefits and costs to reconcile the practices of federal
agencies in making benefit-cost analyses. In 1950 the subcommittee
issued a landmark report entitled \"Proposed Practices for Economic
Analysis of River Basin Projects.\" While never fully accepted either by
the parent committee or the federal agencies, this report was remarkably
sophisticated in its use of economic analysis and laid an intellectual
foundation for research and debate which set it apart from other major
reports in the realm of public expenditures. This document also provided
general guidance for the routine development of benefit-cost analysis of
water projects which persists to the present day.

Even while the benefit-cost technique was limited largely to the
relatively straightforward problem of evaluating water resources
investments there was much technical debate among academic economists
about the proper way of handling both empirical and conceptual
difficulties with the technique. Some of the discussion surrounded
primarily technical issues, e.g. ways of computing consumer surplus and
how best to estimate demand functions for various outputs. Others were
more clearly value and equity issues, e.g., whether the distribution of
benefits and costs among individuals needed to be accounted for or
whether it was adequate to consider only aggregates, and what is the
appropriate rate of time discount to use on water projects.

[Benefit Analysis and the New Generation of Environmental
Problems]{.underline}

The next large task of environmental regulation in this country is to
manage the flow of toxic and hazardous materials into our environment in
some socially optimum manner. To the extent that this effort is to be
aided by explicit benefit-cost analyses, the capabilities of the
technique will be stretched to its limits. Both the empirical and value
issues which have existed in the traditional water resource applications
are aggravated. While water resource applications often involve the
evaluation of public goods (in the technical economic sense of goods
exhibiting jointness in supply) the bulk of outputs pertain to such
things as irrigation, navigation, flood control and municipal and
industrial water supplies which usually could be reasonably evaluated on
the basis of some type of market information. In the newer applications
we are dealing almost entirely with public goods where market surrogates
are much more difficult to establish. The problem of finding justifiable
monetary values, on outcomes of the projects or regulatory decisions is
a very difficult one.^[1]{.underline}/^ In most instances there will be
two central questions: How does one obtain a dose-response function, and
what value does one place on risks to life, health, and aesthetic
phenomena?

The research efforts reported in the four volumes synthesized in this
executive summary represent a variety of attempts to elevate the
state-of-the-art in assessing the benefits of environmental quality
enhancement. There are two primary areas of emphasis. First, new
experimental techniques for measuring the value of air quality
improvements and other environmental amenities are developed and tested
for a specific area, the South Coast Air Basin of southern California.
However, the study of the South Coast Air Basin is not holistic in that
some types of effects such as oxidant damage to materials and forests
have not been evaluated. Second, the analytical and empirical methods of
economics are used to develop hypotheses on disease etiologies and to
value labor productivity and consumer losses due to air
pollution-induced mortality and morbidity. Since the major focus for
each area of emphasis has been on methodological development and
experimentation, all the reported empirical results are only properly
regarded as tentative and ongoing rather than definitive and final. For
policy applications, these results require further refinement.
Nevertheless, these results do suggest that previous commentaries may
have substantially [underestimated]{.underline} the economic losses
caused by the aesthetic and the morbidity impacts of air pollution, and,
by implication, benefits of improvements inair quality. We turn first to
what we call the epidemiology experiments.

[Epidemiology Experiments]{.underline}

Volume I focuses on developing methodology for valuing the benefits to
human health associated with air pollution control. Air pollution may
affect human health in three ways: (1) by increasing mortality rates;
(2) by increasing the incidence and severity of chronic illness
(morbidity); and (3) by increasing the incidence and severity of acute
illness (morbidity).

A number of approaches for determining health effects and valuing them

in economic terms are developed within the study. First, if a
dose-response relationship is known between mortality rates and air
pollution or between days lost from work due to illness (productivity
loss) and air pollution, economic losses can be approximated. In the
former case, one must know how consumers value increased safety. Thus,
if air pollution control reduces risk of death from air pollution
related disease, studies of the value consumers place on safety in other
situations \-- on the job, in transportation, etc. \-- can be applied to
measuring the benefits of pollution control programs. Note, however,
that valuing safety for small changes in risk is very different from the
alternative of valuing human life through lost earnings. The latter
approach is rejected in this study. Rather, the focus is on examining
the value of safety to individuals. That is, how much are consumers
willing to pay for the reduced risks to health obtained through
pollution control? For morbidity losses, lost time from work and lost
productivity during hours of work can be relatively easily valued by
using observed wage rates.

A second approach for valuing the effects of air pollution on human
health is to attempt to observe the direct effect of air pollution on
economic factors, thus avoiding the necessity of developing
dose-response relationships. If one can develop relationships employing
data on wages, wealth, and socioeconomic and health status
characteristics as well as pollution exposures, consumer willingness to
pay to avoid illness can be derived. We term this second methodology the
willingness to pay approach. It is based on traditional macroeconomic
theory.

In regard to these approaches two experiments were conducted. First, a
data set on sixty U.S. cities was explored to determine if some of the
problems of aggregate epidemiology \-- epidemiology using aggregate data
on groups of individuals as opposed to data on individuals \-- can be
overcome. The study attempted to estimate a human dose-response
expression in which 1970 city-wide mortality rates for major disease
categories are statistically associated with population characteristics
such as doctors per capita, cigarettes per capita, information on
dietary patterns, race, age, and air pollution. The study is unusual in
two respects. First, it is the first aggregate epidemiological study of
the effect of air pollution on mortality to include dietary variables,
which along with smoking and medical care, prove to be highly
significant statistically. Second, the study accounts for the fact that
human beings will attempt to adjust to disease by seeking out more
medical care. Thus, cities with higher mortality rates are likely to
have more physicians per capita. This adjustment process has in the past
prevented an estimate of the direct effect of physicians on the
prevention of disease. An estimation technique capable of accounting for
the actual contribution medical care makes to reducing mortality rates
is employed. The impact upon the analysis of including these new

variables and employing the heretofore epidemiologically unused
estimation technique is striking. In fact, the total effect of air
quality on mortality is about an order of magnitude smaller than other
estimates.^[2]{.underline}/^ Rather small but important associations are
found between pneumonia and bronchitis and particulates in air and
between early infant disease and sulfur dioxide air pollution. The
direction of the associations which were found among all the variables
are shown in Table 1.

The sixty city study does, however, have a number of remaining problems.
These incluse biases introduced by using aggregate as opposed to
individual data, the exclusion of data on radiation, exercise, and
migration of individuals between cities, and the possibility that
individuals may die from combinations of causes.

Given these qualifications, it is possible to construct benefit measures
using the methodology briefly summarized in Table 2.

First, to obtain national estimates, it is necessary to know the
population at risk. Since the sixty city sample is entirely urban, and
since toxic air pollution is principally an urban problem, a population
at risk for 1970 of 150 million urban dwellers was used. As a range for
the value of safety, Thaler and Rosen\'s (1975) estimate of \$340,000
(in 1978 dollars) was used as a lower bound and Smith\'s (1977) estimate
of \$1,000,000 as an upper bound. Finally, to provide an estimate of
reduced risk from air pollution control, an average 60 percent reduction
in ambient urban concentrations was assumed for both S02 and
particulates. Then, using the mean concentration of these pollutants in
the sixty city sample as a basis for calculation, it was possible to
derive the average reduction in risk of pneumonia mortality for a 60
percent reduction in particulates and the average reduction in risk of
infant diseases for a 60 percent reduction in S02 from the estimated
dose-response functions for these diseases.

Multiplying the population at risk by the assumed value of safety and
then by the [average]{.underline} reduction in risk given a crude
approximation of the benefits for a 60 percent reduction in national
urban ambient concentrations of particulates and S02 respectively.
National urban totals and the value of the average individual risk
reduction are shown in Table 3.

The second major experiment focused on morbidity rather than mortality.
It employed data on the health and the time and budget allocations of a
random sampling of the civilian population nationwide. The sample, which
was collected by the Survey Research Center of the University of
Michigan, consisted of approximately 5,000 heads of households for nine
years starting in 1967. Generalized measures of acute illness, stated in
terms of annual work-days ill, and chronic illness, stated in terms of
years of illness duration, were available. The measures of illness were
substantially less than ideal. For example, individuals who died between
the reference year

Table 1

Summary of Two-Stage Linear Estimates of Factors in Human Mortality

Hypotheses not Rejected at the 97.5% Confidence Level

(One-tailed t-test, t [\>]{.underline} 2.0)

  ------------------ ----------- ---------- --------- ----------- ------------ ----------- --------- ------------ ---------- --------
  Variable\          Total       Vascular   Heart     Pneumonia   Emphysema    Cirrhosis   Kidney    Congenital   Early      Cancer
  (Sign of           Mortality   Disease    Disease   and         and                      Disease   Birth        Infant     
  Hypothetical       Rate                             Influenze   Bronchitis                         Defects      Diseases   
  Effect)                                                                                                                    

  Doctors/Capita\*   \-          \-         \-                    \-                       \-                                \-
  (-)                                                                                                                        

  Median Age (+)     \+          \+         \+        \+                       \+          \+                                \+

  \% Nonwhite (+)    \+                     \+                                 \+          \+                     \+         \+

  Cigarettes (+)     \+          \+         \+                                                                               \+

  Room Density (+)   \+                               \+                       \+          \+                                

  Cold (+)           \+                               \+                                                                     \+

  Animal Fat (+)                            \+                                                                               

  Protein (+)        \+                                           \+                                                         \+

  Carbohydrates (?)                                               \-                                                         

  NO~2~ (+)                                                                                                                  

  SO~2~ (+)                                                                                                       \+         

  Particulates (+)                                    \+                                                                     

  R^2^               .82         .60        .77       .54         .39          .64         .54       .22          .55        .86
  ------------------ ----------- ---------- --------- ----------- ------------ ----------- --------- ------------ ---------- --------

\*Two-stage estimator employed.

  ------------------ ----------------- -------------------- --------------- --
  Table 2                                                                   

                                                                            

  Methodology for                                                           
  Health Benefits                                                           
  Assessment                                                                

                                                                            

                                                                            

                                                                            

  Benefits =                                                                
  (Population at                                                            
  Risk) x (Value of                                                         
  Safety) x                                                                 

                                                                            

  (Reduction in                                                             
  Health Risk)                                                              

                                                                            

                                                                            

  [Value of Safety                                                          
  Based on                                                                  
  Consumer\'s                                                               
  Willingness to                                                            
  Pay]{.underline}                                                          

                                                                            

                     Low estimate:     \$340,000                            

                                                                            

                     Source:           Thaler & Rosen                       
                                       (1975)                               

                                                                            

                     High estimates:   \$1,000,000                          

                                                                            

                     Source:           Robert Smith (1977)                  
  ------------------ ----------------- -------------------- --------------- --

  ------------ -------------- ------------------ -------------------------- --
  Table 3                                                                   

                                                                            

  Urban                                                                     
  Benefits                                                                  
  from Reduced                                                              
  Mortality:                                                                

  Value of                                                                  
  Safety for                                                                
  60 Percent                                                                

  Air                                                                       
  Pollution                                                                 
  Control                                                                   

                                                                            

                                                                            

  Disease      Pollutant      Average Individual National\                  
                              Safety Benefit\    Urban Benefits\            
                              (1978              (1978 Billion              
                              Dollars/Year)      Dollars/Year)              

  Penumonia    Particulates   29 - 92            4.4 - 13.7                 

  Early        SO~2~          5 - 14             .7 - 2.2                   
  Infant\                                                                   
  Disease                                                                   

  Total                       34 - 106           5.1 - 15.9                 
  ------------ -------------- ------------------ -------------------------- --

of the interview and the time of the interview are not included, and
years of illness duration are defined in terms of dissimilar multiples
of years rather than the actual number of years.

For most of the dose-response expressions estimated in this part of the
study, air pollution appears to be significantly associated with
increased time being spent acutely or chronically ill. Air pollution, in
addition, appears to influence labor productivity, where the reduction
in productivity is measured by the earnings lost due to reductions in
work time and effort. The reduction in productivity due to air
pollution-induced chronic illness seems to be much larger than any
reductions due to air pollution-induced acute illness.

Figure 1 is a hueristic representation of the structure forming the
basis of our estimate of potential labor productivity gains from air
pollution control. Air pollution is viewed as increasing directly both
chronic and acute illness. In addition, it causes an indirect increase
in acute illness via its positive effect on chronic illness. Acute
illness reduces hours worked, but, because of its passing nature, it has
no impact upon the worker\'s long-term productivity that determines the
level of his wages. However, chronic illness, which does reduce
long-term productivity, exerts a direct negative influence on both wages
and hours worked. It also influences hours worked in an indirect manner
through its effect upon wages.

Table 4 is a succinct list of the major assumptions underlying our
empirical implementation of the structure depicted in Figure 1 and its
extrapolation to a national aggregate. We divide these assumptions into
four classes: specification, measurement, estimation, and aggregation.
The table also indicates the probable direction of bias, if any, the
assumption introduces. However, we do not now know the sensitivity of
our estimates and calculations to any particular assumption or to the
entire set of assumptions. Upon reviewing Table 4, the judicious reader
will immediately become aware that our listing is sufficiently strenuous
to raise some questions about whether our estimates and calculations are
yet sufficiently compelling to warrant their serious use.

In spite of the lengthy listing of assumptions, we emphasize that our
treatment of the system in Figure 1 has several positive distinguishing
features. To balance any negative impressions established from Table 4,
we list these positive features in Table 5. Our estimates of the system
in Figure 1 are presented in Volume I, Table 6.3. As a result of a
one-unit (ug/m3) increase in air pollution utilizing the relationships
in Table 6.3, we estimate that the representative person will have his
annual work hours reduced by 0.547 hours. Of this reduction, only 0.046
hours will be due to acute illness. The loss in labor productivity
suffered by this person can be calculated by (where \^ stands for
change):

[∆(Work hours Wage)]{.underline} = [∆(Work hours]{.underline}) . Wage +
[∆(Wage)]{.underline} . Work hours

∆(Pollution) ∆(Pollution) ∆(Pollution)

Upon performing this calculation, we obtain:

= (0.547)(\$3.225) + (\$0.071)(1560.895)

= \$2.86.

Figure 1

A Representation of the Effect of Air Pollution

Upon Labor Productivity

![](media/image1.emf){width="5.598611111111111in"
height="2.1493055555555554in"}

Table 4

Major Assumptions Limiting Generality of Results

[Specification]{.underline}

1\. Air pollution affects only the duration of chronic illness. Our
inattention to the severity of chronic illness tends to
[reduce]{.underline} the estimated impact of air pollution on labor
productivity.

2\. Occupational exposures to hazards and environmental pollutants other
than air pollution do not influence either acute or chronic illness. If
air pollution is moderately and positively associated with these hazards
and polutants, this assumption tends to [increase]{.underline} the
estimated impact of air pollution on labor productivity.

3\. Annual geometric mean ambient concentrations of total suspended
particulates serve as an adequate proxy for all forms of air pollution.
The effect of this assumption upon the estimated effect of air pollution
on labor productivity is [unknown]{.underline}.

4\. All relationships depicted in Figure 1 are linear. It is
[unknown]{.underline} what effect this assumption has on the estimated
effect of air pollution on labor productivity.

5\. Air pollution-induced health effects do not cause the voluntary
substitution of leisure for work. This assumption tneds to
[reduce]{.underline} the estimated impact of air pollution on labor
productivity.

[Measurement]{.underline}

6\. Air pollution exposures for each individual in the sample are
adequately represented by a single annual average of ambient
concentrations obtained at a single monitoring station within the
individual\'s county of residence. Since pollution monitoring stations
in the early part of the 1970\'s were predominantly in downtown urban
locations, individuals\' air pollution exposures probably tend to be
exaggerated. This will [reduce]{.underline} the estimated health effects
of air pollution.

7\. The duration of any air pollution-induced chronic illness cannot
exceed ten years. This will [reduce]{.underline} the estimated effect of
air pollution upon the duration of chronic illness.

8\. Housewives, retirees, and students, who together constitute about
twenty percent of our samples, do not contract air pollution-induced
acute illnesses. This assumption will tend to [reduce]{.underline} the
estimated impact of air pollution upon labor productivity.

9\. Air pollution-induced chronic and acute illnesses are a constant
proportion of all illnesses. The effect of this assumption is
[unknown]{.underline}.

(continued)

Table 4

(continued)

10\. The quality of preventive and ameliorative medical care an
individual consumes is adequately measured by whether or not he has
medical insurance. This assumption has an [unknown]{.underline} effect
upon our estimates.

11\. Relative air pollution concentrations across the U.S. have been
fairly constant. This assumption has an [unknown]{.underline} effect
upon our estimates of air pollution-induced chronic illness.

12\. When interviewed, the individuals in the sample had no incentive to
bias their answers nor did they have difficulty accurately recalling
their personal medical histories of the previous twelve to sixteen
months. The effect of this assumption upon our estimates is
[unknown]{.underline}.

13\. No individual who would otherwise have been included in the sample
died between the time for which information was to be gathered and the
time of the interview. In fact, about five percent of the potential
respondents died each year. The effect of this assumption is to
[reduce]{.underline} the effects of air pollution upon labor
productivity.

[Estimation]{.underline}

14\. With the available data, classical linear regression procedures
provide consistent and unbiased estimates of the structure depicted in
Figure 6.1. The effect of this assumption upon our estimates is
[unknown]{.underline}.

[Aggregation]{.underline}

15\. The response of the health state of each individual in the U.S. to
any given change in ambient air pollution is a constant. The effect of
this assumption upon the calculation for the aggregate effect of air
pollution upon labor productivity is [unknown]{.underline}.

16\. The response of the health state of every individual in the U.S. to
ambient air pollution changes is identical. The effect of this
assumption upon the calculation for the aggregate effect of air
pollution upon labor productivity is [unknown]{.underline}.

Table 5

Distinguishing Features that Enhance

the Generality of Results

1\. The acute illness and chronic illness dose-response estimates used
to calculate the aggregate impact of air pollution-induced morbidity
upon U.S. labor productivity are representative of estimates obtained
from many different independent samples drawn from the same data set. In
effect, substantial quasi-replication of the dose-response estimates has
been performed.

2\. The system is estimated only for people who have always lived in one
state. We believe this restriction enhances the extent to which we
capture the effect of the history of air pollution exposures upon the
chronic illness dose-response function.

3\. Our estimated expressions for wages and hours worked are very
similar to those obtained by other economists.

4\. We include more information on life-styles and genetic and social
endowments than is usually included in dose-response expressions
estimated from epidemiological data.

That is, a one-unit reduction in air pollution would have increased this
representative person\'s 1970 earnings by \$2.86. Only \$0.15 of this
sum represents the gain from a reduction in acute illness.

The above \$2.86 sum represents our \"best\" estimate at this point of
the representative person\'s gain in 1970 earnings from a one-unit
reduction in air pollution. Lower and upper bounds for this estimate can
be established by making use of the confidence intervals for the effect
of pollution on chronic and acute illness; that is, we wish to calculate
the gain in earnings when the pollution coefficient in Table 6.3,
equation 1 is 0.0028 + 0.0011, and when the pollution coefficient in
equation 2 is 0.623 + 0.317. At least for the chronic illness
expression, this confidence interval captures nearly all the range of
the values for the pollution coefficients estimated in twelve different
chronic illness expressions, each of which was estimated from a separate
sample. Upon performing this calculation for the lower bound, we obtain
\$1.88, and for the upper bound, we obtain \$3.84.

Assume that the average exposure of the U.S. 1970 urban population to
annual geometric mean total suspended particulates was 100 ug/m3 and
that the standard deviation of these exposures was 30 ug/m3. Throughout
this study, total suspended particulate measures have been highly
correlated with other air pollutants so that total suspended
particulates probably serve as an adequate proxy for all air polution.
Further assume that the national urban population is approximately 150 x
10 6 people, of whom 75 percent, or 112.5 x 10 6, are 16 years or older.
At age 16, each of these adults has a lifespan of 56 years and any air
pollution induced chronic illnesses he contracts are distributed
rectangularly over the 56 years. The annual earnings he loses due to the
presence of an acute or chronic illness do not vary over the 56 years.

If the medium household size is 2.0, there are then 56.25 x 10 6

urban household heads. There is thus a \$160.88 x 10 6 = (\$2.86) (56.25
x l0 6) gain in the labor productivity for household heads from a one
unit reduction in air pollution.

If two-thirds of the household heads are married, if 35 percent of these
households have working wives, and if working wives earn 60 percent as
much as their male counterparts, there would then be a \$22.58 x 10 6
**=** (\$2.86) (0.6) (13-13 x 10 6) gain in the labor productivity of
working wives.

If the value of household services provided by all household members in
each urban household is 40 percent of the market earnings of the
household head, there would then be a \$64.35 x 10 6 = (\$2.86) (0.4)
(56.25 x 10 6) gain in the household labor productivity of all urban
households. Adding the results for household heads, working wives, and
household labor, we obtain a \$247.81 x 10 6 gain in labor productivity
for a one unit reduction in air pollution. A 60 percent reduction in
1970 air pollution would then, in August 1978 dollars, increase the
value of 1970 urban labor productivity by \$25.28 x 10 9 dollars. This
\"best\" estimate and its upper and lower bounds are presented in Table
6. Most of the gain would accrue due to reductions in air
pollution-induced chronic illness. If one performs

  -------------- ----------------------------- ---------------------------
  Table 6                                      

                                               

  Estimated                                    
  Aggregate                                    
  Gains in 1970                                
  U.S. Urban                                   
  Labor                                        
  Productivity                                 
  Due to a                                     

  60 Percent                                   
  Reduction In                                 
  Air Pollution                                

                                               

  (August 1978                                 
  Dollars)                                     

                                               

                                               

                                               [Aggregate]{.underline}

                                               

                 Lower Bound                   16 x 10^9^

                                               

                 \"Best\" Estimate             25 x 10^9^

                                               

                 Upper Bound                   34 x 10^9^
  -------------- ----------------------------- ---------------------------

these identical calculations in precisely the same fashion for a 1977
U.S. total population of 216.1 x 10^6^, one obtains a \"best\" estimate
of \$36.4 x 10^9^.

It must be strongly emphasized that the magnitudes exhibited in Table 6
are extremely sensitive to the assumptions we have made. Nevertheless,
given any reasonable set of assumptions about air pollution exposures,
size of the population exposed, etc., the estimates of labor
productivity gains in Table 6 are much larger than previous estimates of
all types of annual gains from air pollution control in the United
States. No gains in labor productivity, via reductions in air
pollution-induced health effects, have previously been developed. It
thus appears that the economic gains from the morbidity reduction
effects of air pollution control may have been greatly undervalued,
perhaps because most prior research efforts have concentrated upon
mortality rather than morbidity.

[The South Coast Air Basin Urban Experiment]{.underline}

The South Coast Air Basin of southern California was selected to test
some benefit measures of air pollution control. In this case both health
and aesthetic considerations were involved. For the household sector,
two rather distinct approaches to valuation of environmental quality
have emerged from recent research. The first involves the analysis and
observation of how some pertinent actual market prices, such as real
property prices, are influenced by environmental quality attributes. The
second tries to induce individuals to reveal directly their actual
preferences, in monetary terms, for environmental attributes. Clearly,
there should be a well-defined relationship between what people do pay
through differences in property values and what they say they will pay,
provided there are no incentives for them to distort their bids. New
survey techniques include ways of testing whether there are distortions
in what people say they will bid.^[3]{.underline}/^

During the past few decades, in general, air quality in the Los Angeles
area has deteriorated substantially. However, in some neighborhoods
deterioration has been slight, e.g., communities adjacent to the Pacific
Ocean, while in others, the deterioration has been relatively severe as
measured by concentrations of N02 or total oxidants. The researchers
believed the Los Angeles are, therefore, would be a good location to
make test comparisons of the effects of air quality on housing prices
and individual stated preferences where the comparisons could be
contained within a single large metropolitan area.

The South Coast Air Basin urban experiment consisted of an attempt to
value air quality through examination of differences in property values
and through an interview survey instrument designed to elicit
willingness to pay for improved air quality.

Six pairs of neighborhoods were selected for comparison purposes. The
pairings were made on the basis of similarities of housing
characteristics, socioeconomic factors, distance to beach and services,
average temperature, and subjective indicators of the \"quality\" of
housing. Thus, for each of

the pairs, an attempt was made to exclude effects on property values
other than differences in air quality. A survey of randomly selected
residents of single-family dwellings was then conducted for each paired
neighborhood to discover attitudinal preferences and valuation
responses.

A naive statistical comparison of these paired neighborhoods indicates
that property value differentials between poor and fair air quality
locales may be as high as \$140 per month per household. Utilizing more
advanced economic models, which better take into account factors other
than pollution such as distance to ocean and differences in tastes which
may influence property values, willingness to pay inferred from the
property value differentials is about \$40 per month. As a reasonably
comparable estimate, the survey results,showed an [average]{.underline}
bid of slightly less than \$30 per month. Thus, there is comparability
between the magnitudes obtained between the survey and property value
study estimates. Given various assumptions on income, location,
aggregation by areas, specific housing characteristics, and knowledge on
the health effects of air pollution, both the survey and property value
studies will yield estimates ranging from \$20 to \$150 per month per
household. These preliminary results indicate that air quality
deterioration in the Los Angeles area has had substantial effects on
housing prices and that these negative price effects on housing are
comparable in magnitude to what people say they are willing to pay for
improved air quality.

Crude estimates can be made to deduce willingness to pay for improved
air quality throughout the South Coast Air Basin. Difficulties are
encountered in making data sets or groups of diverse individuals exactly
comparable. Differences are observed between the survey and property
valuation groups in average income, age (the mean age in the survey
exceeded 42 years) and other socioeconomic factors. These differences
have not been controlled for in the following estimates of the aggregate
willingness to pay for air quality improvement in the South Coast Air
Basin.

In Table 7 are recorded estimates of monthly bids by households and, by
aggregation, estimates of the benefits for an approximate 30 percent
improvement in air quality within the South Coast Air Basin. It should
be noted that these experimental measures, while reflecting approximate
valuations, need further refinement before they can even cautiously be
applied to environmental policymaking. Nevertheless, they do suggest
that dollar benefits from an improvement in air quality in the South
Coast Air Basin are very large.

From the methodological standpoint it appears from these preliminary
results and comparisons that survey studies will tend to give a lower
valuation of air quality improvement than observations based on what
happens in an extremely volatile property market. However, only after
substantial further statistical examination and comparability checks
between the two methods will the researchers be able to state
unequivocably how these relationships may turn out. The results compiled
in this study, however, suggest that survey instruments, when compared
to property value techniques, provide a reasonable mechanism to obtain
environmental quality benefit estimates. The survey approach has the
advantages that: (1) data can be

  ------------------------- ---------------- ---------------- ------------
  Table 7                                                     

                                                              

  Alternatives Estimates of                                   
  Monthly Bids by                                             
  Household,                                                  

  and Aggregate Benefits                                      
  for Air Quality                                             

  Improvement in the South                                    
  Coast                                                       

  Air Basin                                                   

                                                              

  (Approximate 30 Percent                                     
  Improvement in Ambient                                      
  Air Quality)                                                

                                                              

                                                              

                                             1977 Dollars     

                            Property Value                    Survey Study
                            Study                             

                            Paired\          Calculated\      Mean\
                            Communities      Marginal\        Bid
                                             Willingness\     
                                             to Pay\*         

  Bid per household per     \$135            \$42\*\*         \$29\*\*\*
  month\                                                      
  (in dollars)                                                

  Annual benefits (in       \$3.96           \$.95            \$.65
  billions\                                                   
  of dollars) (selected                                       
  areas\                                                      
  and groups of the South\                                    
  Coast Air Basin)                                            

                                                              

  \*This benefit                                              
  calculation is considered                                   
  an improvement over the                                     
  paired sample approach                                      
  since explicit account is                                   
  made for a number of                                        
  housing and neighborhood                                    
  variables not captured in                                   
  the paired communities                                      
  comparison.                                                 

                                                              

  \*\*Best estimate. The                                      
  possible range is \$26-63                                   
  per month.                                                  

                                                              

  \*\*\*Based on maximum                                      
  total bid with an                                           
  adjustment for the number                                   
  of years to achieve                                         
  improvements in air                                         
  quality.                                                    
  ------------------------- ---------------- ---------------- ------------

collected at low cost on specific environmental problems (the
investigator is not tied to the availability of existing data sets); and
(2) benefit measures can be disaggregated across individuals and sources
of benefits from various characteristics such as aesthetic experiences
and perceived health can be obtained.

As a final caution, it should be kept in mind that the South Coast Air
Basin studies were conducted in an area where individuals have both an
exceptionally well-defined pollution situation that they have
experienced and a well-developed property value market for clean air.
The effect of clean air on property values, and in turn, on the degree
to which people are aware of increased housing prices in high air
quality areas appears to be exceptionally well specified at this time in
the South Coast Air Basin. Also worthy of note is that 1970 property
values on the basis of earlier studies have shown a much weaker
association with.air quality than those that were obtained utilizing the
1977-78 air quality data set used here. We feel that this change
reflects a substantial shift in interest and concern over air quality
for this regional population. Therefore, it should be recognized that
the results of this experiment may well not generalizable to other
situations where the environmental commodity, i.e., air quality, is not
so well specified, either through actual market prices or human
perception.

[The South Coast Air Basin Agricultural Experiment]{.underline}

The fact that air pollution can damage vegetation has been well
documented. Procedures for the measurement of the economic costs
associated with these damages, however, have not been clearly defined.
The primary purpose of the agricultural assessment component of the
research effort is to address and remove some conceptual and empirical
limitations of past studies dealing with economic damages to
agricultural crops arising from air pollution. Specific objectives
included: (1) the conceptualization of an analytic framework for
measuring economic damages to agricultural crops; (2) application of
this framework to an actual production region with poor ambient air
quality - namely southern California; and (3) measurement of
agricultural damages for a selected group of 14 annual crops within this
region.

A detailed review of the economic damage assessment literature for
agricultural crops revealed some conceptional weaknesses inherent in
previous studies. These weaknesses pertain to potential effects on both
production and consumption of agricultural commodities. From the
standpoint of consumption, a major issue is possible changes in prices
of a commodity due to the adverse effects of air pollution. That is, if
air pollution damages are widespread or if agricultural production of
specific commodities is concentrated in areas of high pollutant levels,
as is the case for many vegetable crops, then reductions in yield due to
air pollution may translate into changes in respective commodity prices
at the local and national retail level.

The analytical framework proposed in this study, while by no means
definitive, includes price effects directly in the measurement of
damages. Also, the \"comparative advantage\" nature of the analysis
allows for a wider range of potential producer strategies in the face of
rising levels of pollutants. The output provides an approximation of the
net distributional effects of changes in air pollution.

The research reported in Volume III provides a detailed discussion of
the analytical framework. Yield-response relationships measuring the
decrease in yield due to levels of pollutants and the price-forecasting
equations quantifying the increase in consumer prices accompanying a
yield decrease are evaluated. The fact that yield reductions within
southern California may increase retail prices at the national level is
due to the importance of southern California in the overall production
of selected crops, such as fresh vegetables on a seasonal basis.

The results of the assessment to date cover only the consumer effects of
southern California oxidant pollution, and then only for twelve
vegetable crops (beans, broccoli, cantalopes, carrots, cauliflower,
celery, lettuce, fresh and processed onions, potatoes and fresh and
processed tomatoes) and two field crops (cotton and sugar beets). Total
annual economic losses for each year in the period 1972 through 1975
averaged \$15 million. In 1976, the loss fell to \$11 million.
Ninety-nine percert of the 1976 losses are attributable to four crops:
celery (68%); fresh tomatoes (12%); potatoes (10%); and cotton (9%).
Similar proportions were obtained for 1972-1975.

From a policy standpoint, the results are perhaps most meaningful in
terms of distributional effects. These results represent damages or
costs borne by all consumers (nationwide), through the higher prices
each must pay for these crops. The effects of air pollution are
therefore felt even by those individuals not residing in areas of high
pollution.

[Related]{.underline} [Studies]{.underline}

The research presented in Volume IV explores various facets of the two
central project objectives: the development of new experimental
techniques for measuring the value of improvements in environmental
quality; and the use of macroeconomic methods to develop hypotheses on
disease etiologies, and to value labor productivity and consumer losses
due to air pollution-induced mortality and morbidity. The emphasis is on
factors that are not completely treated in previous volumes. The
valuations developed in the previous volumes were all based on a partial
equilibrium framework; that is, economic events are assumed to be
isolated from each other. W.R. Porter considers the adjustments and
changes in underlying assumptions these values would require if they
were to be derived in a more general framework. In a second theoretical
paper, Robert Jones and John Riley examine the impact upon the
aforementioned partial equilibrium valuations of variations in consumer
uncertainty about the health hazards associated with various forms of
consumption.

Two empirical efforts conclude the volume. M.L. Cropper employs and
empirically tests a new model of the variations in wages for assorted
occupations across cities in order to establish an estimate of
willingness to pay for enviromental amenities. The valuation she obtains
for a 30% reduction in air pollution concerntrations accords very
closely with the valuations reported in the earlier volumes.

The volume concludes with a report of a small experiment by W.R. Porter
and B.J. Hansen intended to test a particular way to remove certain
biases that bidding game respondents have available to distort their
true valuations.

All of these studies tend to qualify the results of the experimental
procedures discussed in earlier volumes. In addition to assorted
empirical weaknesses, further research will require: (1) an adequate
specification of the mobility decision in response to degraded air
quality; (2) consideration of relative price changes not directly
related to air pollution as set forth in Volume II and discussed by
Porter; and (3) the manner in which consumers evaluate a multitude of
risks simultaneously, both in eating habits and pollution exposures
where their economic and physical losses are uncertain.

[General]{.underline} [Conclusions]{.underline}

This compliation of studies represents original efforts to construct
both a conceptually consistent and empirically verifiable set of methods
for assessing benefits of environmental quality improvement. While the
state-of-the-art does not at present allow us to provide highly accurate
estimates of the benefits of reduced human or plant exposure to air
pollutants, it is

intended to provide a set of fundamental benchmarks. These are: (1) many
benefits traditionally viewed as intangible and thereby non-measurable
can, in fact, be measured and be made comparable to economic values as
expressed in markets; (2) aesthetic experiences and morbidity (illness)
effects may dominate the measure of benefits as opposed to previous
emphases on mortality health effects; and (3) the likely economic
benefits of air quality improvements are perhaps as much as an order of
magnitude greater than previous studies had hypothesized.

The researchers in this study have viewed man as a purposeful, if
imperfectly informed, individual who chooses to respond to both
well-defined market and non-market characteristics of his/her
environment. In each experiment we have discovered that he attempts to
respond to the deleterious effects of air pollution. These reponses have
provided at least a partial roadmap toward identifying how he values the
environment in which he must always live.

EXECUTIVE SUMMARY

FOOTNOTES

[1]{.underline}/ Other major problem areas are as follows:

First, such matters as nuclear radiation and toxic materials relate to
exposure of the whole population or large sub-population to very subtle
influences of which they may be entirely unaware. It is difficult to
know what normative value individual preferences have under these
circumstances.

Second, we are in some cases dealing with long lived effects which could
extend to hundreds of thousands of years and many, many human
generations. This raises the question of how the rights and preferences
of future generations can be represented in this decision process.
Realistically, the preferences of the existing generation must govern.
The question is whether simple desires of existing persons are to rule
or whether it is necessary to persuade the present generation to adopt
some ethical rule or rules of a constitutional nature in considering
questions of future generations. Such a proposed rule is found in Rawls
(1971). Another, related, question of great importance is whether it is
legitimate to discount benefits and costs over these long periods thus
effectively ruling out the future beyond a relative few years, and if it
is legitimate what the proper rate is.

These issues are being studied by several members of the team that
produced the research sketched in this paper under a grant from the
National Science Foundations\'s Ethics and Values in Science and
Technology program.

[2]{.underline}/ See, for example, Lave and Seskin (1977).

[3]{.underline}/ For example one possible form of bias is known as
"starting point bias.\" This is the possibility that the final bid will
be influenced by the starting bid suggested by the interviewers \-- the
higher the latter the higher the former. A test for this is to start
with several different initial bids for different interviewees and then
test to see whether the final bids are different in a statistically
significant sense. Such tests indicated that starting point bias was not
a large problem in the research reported here.

REFERENCES

Lave, L. and E. Seskin, [Air Pollution and Human Health]{.underline},
Baltimore: Johns Hopkins University Press (1977).

Rawls, J., [A Theory of Justice]{.underline}, Cambridge: Harvard
University Press (1971).

Smith, R., \"The Feasibility of an \'Injury Tax\' Approach to
Occupational Safety,\" [Law and Contemporary Problems]{.underline},
(Summer-Autumn, 1974).

Thaler, R. and S. Posen, \"The Value of Saving a Life: Evidence from the
Labor Market,\" in N.E. Terlecky J., (ed) [Household Production and
Consumption]{.underline}, Columbia University Press, New York (1975),
265-297.