OMB
Review
Draft
December
17,
2003
4­
1
SECTION
4
ECONOMIC
IMPACT
ANALYSIS
Congress
and
the
Executive
Office
have
imposed
statutory
and
administrative
requirements
for
conducting
economic
analyses
to
accompany
regulatory
actions.
Section
317
of
the
CAA
specifically
requires
estimation
of
the
cost
and
economic
impacts
for
specific
regulations
and
standards
promulgated
under
the
authority
of
the
Act.
In
addition,
Executive
Order
(
EO)
12866
requires
a
more
comprehensive
analysis
of
benefits
and
costs
for
significant
regulatory
actions.
Office
of
Management
and
Budget
(
OMB)
guidance
under
EO
12866
stipulates
that
a
full
benefit­
cost
analysis
is
only
required
when
a
regulatory
action
has
an
annual
effect
on
the
economy
of
$
100
million
or
more.
Other
statutory
and
administrative
requirements
include
examination
of
the
composition
and
distribution
of
benefits
and
costs.
For
example,
the
Regulatory
Flexibility
Act
(
RFA),
as
amended
by
the
Small
Business
Regulatory
Enforcement
and
Fairness
Act
of
1996
(
SBREFA),
requires
EPA
to
consider
the
economic
impacts
of
regulatory
actions
on
small
entities.
The
OAQPS
Economic
Analysis
Resource
Document,
which
can
be
found
at
http://
www.
epa.
gov/
ttn/
ecas/
econdata/
Rmanual2/
index.
html
,
provides
detailed
instructions
and
expectations
for
economic
analyses
that
support
rulemaking
(
EPA,
1999).

The
engineering
analysis
described
in
Section
3
provides
estimates
of
the
total
annual
costs
associated
with
the
abatement
strategies
that
bring
each
facility
into
compliance
with
the
final
standards.
Note,
however,
that
these
engineering
cost
estimates
do
not
account
for
behavioral
responses
by
facilities,
such
as
changes
in
output
quantities
and
prices.
In
this
section,
engineering
cost
estimates
are
used
as
inputs
to
an
economic
model
of
the
automobile
and
LDT
assembly
industry
to
predict
market,
industry
and
social
welfare
impacts
of
the
final
regulation.
Small
business
impacts
are
addressed
in
Section
5
and
a
benefits
analysis
is
presented
in
Section
6
of
this
report.

4.1
Methodology
This
analysis
will
address
several
special
characteristics
of
the
automobile
industry.
First,
the
industry's
products
are
highly
differentiated
with
vehicles
varying
along
dimensions
such
as
their
functions,
carrying
capacity,
fuel
efficiency,
and
comfort
features.
OMB
Review
Draft
December
17,
2003
1Exclusive
dealership
arrangements
are
also
found
in
the
sewing
machine,
agricultural
machinery
and
gasoline
markets.

2EPA's
1999
Fuel
Economy
Guide
Data
(
EPA,
2000),
car
buyers
guides
such
as
Edmunds.
com
(
Edmunds,
2001),
and
the
Automotive
News
Market
Databook
(
Crain
Automotive
Group,
2000)
were
used
to
assign
vehicle
models
to
the
appropriate
market
segments.

3Recall
that
a
semi­
elasticity
refers
to
the
percentage
change
in
quantity
demanded
of
model
j
when
price
of
model
i
changes
by
$
1
but
all
other
model
prices
remain
unchanged.

4­
2
Second,
the
market
for
automobiles
within
the
United
States
may
be
characterized
as
imperfectly
competitive.
Only
14
companies
operate
in
this
market.
In
1998­
1999,
the
Herfindahl­
Hirschmann
Index
for
the
industry
was
1,471,
and
the
four­
firm
concentration
ratio
(
CR4)
was
72
percent.
Third,
exclusive
dealerships
play
an
intermediary
role
between
manufacturers
and
final
consumers.
1
Finally,
international
trade
is
a
major
component
of
the
U.
S.
market
for
automobiles.
In
1999,
imports
accounted
for
approximately
20
percent
of
car
sales
in
the
United
States
(
Crain
Automotive
Group,
2000).
Given
the
data
available,
we
will
evaluate
the
economic
effects
of
the
final
regulation
at
the
facility
level
within
the
context
of
the
overall
industry
conditions.
This
approach
is
consistent
with
accepted
economic
logic
and
provides
consistent
estimates
for
the
impacts
on
all
the
required
variables.

4.1.1
Product
Differentiation
To
address
the
high
degree
of
product
differentiation
in
this
industry,
the
Agency
has
segmented
the
market
into
eight
vehicle
classes:
subcompacts,
compacts,
intermediate/
standard,
luxury,
sports,
pickups,
vans,
and
other.
2
Separate
demand
and
cost
curves
are
developed
for
each
of
these
market
segments.

Since
all
domestic
vehicle
categories
are
subject
to
price
changes
due
to
the
final
regulation,
we
will
estimate
the
consumer
response
to
these
price
changes
within
each
vehicle
class.
However,
we
will
not
estimate
spillover
impacts
between
domestic
vehicle
classes
because
available
estimates
of
the
cross­
price
elasticities
of
demand
suggest
that
consumers
rarely
substitute
between
vehicle
classes
in
response
to
relatively
small
price
changes.
In
particular,
Goldberg
(
1995)
estimates
cross
price
semi­
elasticities
of
demand
for
some
specific
vehicle
models
and
finds
that
these
semi­
elasticities
are
low
if
the
models
belong
to
different
classes.
3
For
example,
the
cross
price
semi­
elasticity
between
a
Honda
Civic
and
a
Honda
Accord
is
only
14.9
×
10­
7.
Furthermore,
our
priors
suggest
that
the
tendency
to
switch
between
vehicle
categories
will
be
low
given
the
relatively
small
OMB
Review
Draft
December
17,
2003
4­
3
magnitude
of
price
changes
expected
for
this
NESHAP.
Therefore,
our
basic
market
segmented
model
is
designed
to
capture
the
within­
segment,
first
order
impacts
of
the
regulation.

4.1.2
Imperfect
Competition
Although
the
U.
S.
automobile
industry
comprises
14
firms,
a
smaller
subset
of
these
firms
operates
within
each
vehicle
category
segment.
Given
our
assumption
of
imperfect
competition
in
the
industry
as
a
whole
and
within
each
segment
in
particular,
we
will
use
a
Cournot
model
to
characterize
the
market
for
each
vehicle
category.
The
implicit
assumption
is
that
vehicles
within
a
given
category
are
close
substitutes.
In
the
Cournot
model,
one
of
several
models
of
oligopoly,
firms
are
modeled
as
choosing
production
quantities.
Unlike
a
competitive
market,
in
which
the
price
equals
the
marginal
cost
of
production
and
firms
take
the
price
as
given,
the
Cournot
model
reflects
the
fact
that
automobile
manufacturers
may
have
market
power
and
thus
charge
a
price
in
excess
of
marginal
cost
by
producing
a
quantity
that
is
less
than
in
a
competitive
equilibrium.

4.1.3
Role
of
Dealerships
Manufacturers
in
the
U.
S.
automobile
industry
do
not
actually
set
final
consumer
prices.
Instead,
they
set
wholesale
prices
for
dealers
which
are
then
marked
up
to
form
retail
or
list
prices.
The
final
transaction
price
paid
by
the
consumer
can
also
differ
from
these
retail
prices
because
of
dealer­
specific
rebates,
local
and
state
taxes,
and
individual
bargaining
power.
This
pricing
scheme
is
summarized
in
Figure
4­
1.
Note
that
manufacturer
decisions
are
based
on
wholesale
prices,
while
consumer
decisions
are
based
on
transaction
prices.

This
relationship
can
be
viewed
as
a
successive
oligopoly
game,
with
the
manufacturer
adding
a
markup
over
the
marginal
cost
of
production,
and
the
dealer
adding
Wholesale
Price
List
Price
Transaction
Price
Manufacturer
Dealer
Consumer
Figure
4­
1.
Pricing
in
Automobile
Markets
OMB
Review
Draft
December
17,
2003
4All
production
facilities
located
within
the
United
States
are
subject
to
the
final
NESHAP
regardless
of
whether
they
are
owned
by
domestic
or
foreign
companies.
For
the
purposes
of
this
analysis,
imports
refers
to
vehicles
produced
outside
of
the
United
States.

4­
4
his
own
markup.
In
stage
1,
the
manufacturer
maximizes
his
profits
by
comparing
his
marginal
costs
to
his
marginal
revenues.
His
marginal
revenue
depends
on
the
wholesale
price
and
the
wholesale
price
elasticity
of
demand.
In
the
second
stage,
the
dealer
maximizes
her
profits
by
comparing
her
own
marginal
costs
to
her
marginal
revenue,
which
depends
on
the
transaction
price
and
the
transaction
price
elasticity
of
demand.

If
the
marginal
cost
of
production
increases,
the
impacts
can
be
borne
by
the
manufacturer
who
changes
input­
output
quantities,
the
dealer
who
earns
a
reduced
markup,
or
the
consumer
who
faces
a
higher
list
price.
Gron
and
Swenson
(
2000)
examine
the
degree
of
cost
pass­
through
to
final
consumers
in
the
U.
S.
automobile
market.
They
find
that
cost
shocks
common
to
all
manufacturers
have
a
greater
effect
on
list
price
than
do
modelspecific
cost
shocks.
This
is
consistent
with
the
theoretical
predictions
of
Dornbusch
(
1987)
who
showed
in
the
context
of
exchange
rate
shocks
that
firms
competing
in
a
Cournot
game
will
increase
the
level
of
cost
pass­
through
as
the
proportion
of
the
market
that
is
exposed
to
the
cost
increase
grows.

Because
the
final
regulation
covers
all
facilities
assembling
vehicles
in
the
United
States,
we
have
made
the
simplifying
assumption
that
the
dealer
can
charge
the
same
percentage
markup
as
before
the
regulation.
Assuming
that
the
percentage
markup
(
including
discounts,
taxes,
etc.)
between
the
wholesale
price
(
PW)
and
the
transaction
price
(
PT)
is
constant,
i.
e.
PW
=
8PT,
the
demand
elasticity
with
respect
to
wholesale
prices
coincides
with
the
transaction
price
elasticity.
Thus
we
can
collapse
the
two­
stage
game
between
the
manufacturer,
dealer,
and
consumer
to
a
one­
stage
game
between
the
manufacturer
and
a
"
composite
customer"
(
dealer/
consumer).

4.1.4
Foreign
Trade
While
the
final
NESHAP
will
directly
affect
domestic
facilities
that
use
coatings
in
automobile
and
LDT
assembly
operations,
the
rule
can
also
have
indirect
foreign
trade
implications.
4
On
the
import
side,
the
demand
for
imported
cars
could
increase
if
they
become
inexpensive
relative
to
domestic
cars
that
are
affected
by
the
coating
process
standard.
We
will
assume
that
foreign
firms
can
meet
this
spillover
demand
by
using
excess
capacity
in
their
existing
plants.
On
the
export
side,
foreign
demand
for
vehicles
produced
in
the
United
States
can
decrease
if
they
become
relatively
more
expensive
because
of
the
OMB
Review
Draft
December
17,
2003
4­
5
regulation.
Finally,
domestic
facilities
could
relocate
to
foreign
countries
with
laxer
environmental
regulations
if
domestic
production
costs
increase.
However,
given
the
small
size
of
the
compliance
costs
relative
to
company
sale
it
is
unlikely
that
the
final
regulations
will
trigger
industrial
flight
at
least
in
the
short
run.
This
assumption
is
consistent
with
empirical
studies
in
the
literature
that
have
found
little
evidence
of
environmental
regulations
affecting
industry
location
decisions
(
Levinson,
1996).
This
discussion
illustrates
the
theory
underlying
estimation
of
the
economic
impacts
of
the
final
MACT
standard.
The
next
task
is
to
operationalize
this
model
to
calculate
the
impacts.

4.2
Operational
Model
The
final
regulation
will
increase
the
cost
of
production
for
existing
vehicle
assembly
plants.
The
regulated
facilities
may
alter
their
current
levels
of
production
or
even
close
a
plant
in
response
to
the
increased
costs.
These
responses
will
in
turn
determine
the
impact
of
the
regulation
on
total
market
supply
and
ultimately
on
the
equilibrium
price
and
quantity.
To
determine
the
impact
on
equilibrium
price
and
quantity,
we
will
C
characterize
the
demand
for
each
domestic
vehicle
type;

C
characterize
the
costs
of
production
for
classes
of
domestic
vehicles
at
the
individual
facility
and
at
the
market
level;

C
develop
the
solution
algorithm
to
determine
the
new
with­
regulation
equilibrium;

C
characterize
spillover
impacts
on
the
demand
for
imported
and
exported
cars
and
LDTs;
and
C
compute
the
values
for
all
the
impact
variables.

An
intuitive
overview
of
our
economic
model
is
presented
below.
Details
of
the
modeling
exercise
and
its
implementation
are
relegated
to
Appendix
A.

The
Agency
has
modeled
separate
markets
for
each
of
the
eight
vehicle
categories:
subcompacts,
compacts,
intermediate/
standard,
luxury,
sports,
pickups,
vans,
and
other.
Given
the
imperfect
competition
observed
within
each
market
segment,
Cournot
models
are
used
to
reflect
the
fact
that
oligopolistic
manufacturers
can
charge
a
price
in
excess
of
marginal
cost
by
producing
a
quantity
that
is
less
than
the
competitive
optimum.

U.
S.
demand
for
domestic
vehicles
in
each
category
is
characterized
by
a
downwardsloping
demand
curve,
which
implies
that
the
quantity
demanded
is
low
when
prices
are
high
and
quantity
demanded
is
high
when
prices
are
low
due
to
the
usual
income
and
substitution
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Review
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17,
2003
4­
6
P0
P
Q0
Q
D
MR
MC0
Figure
4­
2.
Baseline
Equilibrium
effects.
The
demand
curve
for
each
vehicle
category
is
constructed
using
baseline
quantity
and
retail
price
data
and
available
estimates
of
own
price
elasticities
of
demand.

Given
the
capital
in
place,
each
automobile
and
LDT
assembly
facility
will
be
assumed
to
face
an
upward­
sloping
marginal
cost
function.
In
addition,
it
is
assumed
that
if
revenue
falls
below
its
minimum
average
variable
costs,
then
the
firm's
best
response
is
to
cease
production
because
total
revenue
does
not
cover
total
variable
costs
of
production.
In
this
scenario,
producers
lose
money
on
operations
as
well
as
capital.
By
shutting
down,
the
firm
avoids
additional
losses
from
operations.

Figure
4­
2
shows
how
the
market
prices
and
quantities
are
determined
by
the
intersection
of
the
marginal
revenue
and
marginal
cost
curves
in
a
concentrated
market
model.
The
baseline
consists
of
a
market
price
and
quantity
(
P0,
Q0)
that
is
determined
by
the
downward­
sloping
market
demand
curve
(
D)
and
the
upward­
sloping
marginal
cost
curve
(
MC0)
that
reflects
the
sum
of
the
individual
marginal
cost
curves
of
the
assembly
facilities.
Any
individual
supplier
would
produce
amount
Q0
(
at
price
P0)
and
the
facilities
would
collectively
produce
amount
Q0.
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2003
4­
7
P0
P
Q0
Q
D
MR
Q1
P1
MC1
MC0
Figure
4­
3.
With­
Regulation
Equilibrium
Now
consider
the
effect
of
the
regulatory
control
costs
(
see
Figure
4­
3).
Incorporating
the
regulatory
control
costs
will
involve
shifting
the
marginal
cost
curve
upward
for
each
regulated
facility
by
the
per­
unit
variable
compliance
cost.
As
a
result,
the
market
output
declines
from
Q0
to
Q1
and
the
market
price
(
as
determined
from
the
market
demand
curve,
DM)
increases
from
P0
to
P1.

Because
the
final
coating
standard
will
only
be
binding
on
automobile
and
LDT
assembly
facilities
operating
within
the
U.
S.,
the
Agency
has
also
modeled
the
impact
of
the
predicted
domestic
price
increase
on
foreign
trade.
Imports
of
foreign
vehicles
into
the
U.
S.
could
increase
because
they
become
cheap
relative
to
domestic
vehicles.
The
ratio
between
quantities
of
imported
versus
domestic
vehicles
purchased
by
U.
S.
consumers
is
modeled
as
a
function
of
their
relative
prices
and
the
ease
of
substitution
between
these
vehicles.
Exports
of
U.
S.­
made
vehicles
can
also
decline
if
their
price
increases
while
other
exogenous
determinants
of
foreign
demand
are
held
constant.
Foreign
demand
is
modeled
as
a
downward
sloping
function
that
depends
on
average
price
of
exported
U.
S.
vehicles
and
the
export
elasticity
of
demand.
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Review
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2003
4­
8
4.3
Economic
Impact
Results
Based
on
the
simple
analytics
presented
above,
automobile/
LDT
manufacturers
will
attempt
to
mitigate
the
impacts
of
higher
production
costs
by
shifting
as
much
of
the
burden
on
other
economic
agents
as
market
conditions
allow.
Potential
responses
include
changes
in
production
processes
and
inputs,
changes
in
output
rates,
or
closure
of
the
plant.
This
analysis
focuses
on
the
last
two
options
because
they
appear
to
be
the
most
viable
for
auto
assembly
plants,
at
least
in
the
short
term.
We
expect
upward
pressure
on
prices
as
producers
reduce
output
rates.
Higher
prices
reduce
quantity
demanded
and
output
for
each
vehicle
class,
leading
to
changes
in
profitability
of
facilities
and
their
parent
companies.
These
market
and
industry
adjustments
determine
the
social
costs
of
the
regulation
and
its
distribution
across
stakeholders
(
producers
and
consumers).

4.3.1
Market­
Level
Impacts
The
increased
costs
of
production
due
to
the
regulation
are
expected
to
slightly
increase
the
price
of
automobiles/
LDT
and
reduce
their
production
and
consumption
from
1999
baseline
levels.
As
shown
in
Table
4­
1,
the
regulation
is
projected
to
increase
the
price
of
all
vehicle
classes
by
at
most
0.01
percent
(
or
at
most
$
3.08
per
vehicle).
Similarly,
the
model
projects
small
declines
in
domestic
production
across
all
vehicle
classes
(
ranging
from
17
to
384
vehicles).

4.3.2
Industry­
Level
Impacts
Industry
revenue,
costs,
and
profitability
change
as
prices
and
production
levels
adjust
in
response
to
the
increased
compliance
costs.
These
impacts
are
described
in
detail
below.

4.3.2.1
Changes
in
Profitability
As
shown
in
Table
4­
2,
the
economic
model
projects
that
pre­
tax
earnings
for
assembly
plants
will
decrease
by
$
152
million,
or
1.1
percent.
This
is
the
net
result
of
three
effects,
the
first
two
of
which
partially
offset
each
other:

C
Decrease
in
revenue
($
21
million):
Revenue
decreases
as
a
result
of
reductions
in
output.
However,
these
losses
were
mitigated
by
increased
revenues
as
a
result
of
small
increases
in
vehicle
prices.

C
Decrease
in
production
costs
($
22.5
million):
Production
costs
decline
as
output
declines.
OMB
Review
Draft
December
17,
2003
4­
9
Table
4­
1.
Market­
Level
Impacts
by
Vehicle
Class:
1999
Vehicle
Class
Baseline
Absolute
Change
Relative
Change
Subcompacts
Wholesale
Price
($/
unit)
$
15,522
$
0.40
0.00%

Domestic
Production
(
103/
yr)
586,257
 
50
 
0.01%

Compacts
Wholesale
Price
($/
unit)
$
16,487
$
1.05
0.01%

Domestic
Production
(
103/
yr)
1,766,657
 
384
 
0.02%

Intermediate/
Standard
Wholesale
Price
($/
unit)
$
21,155
$
0.61
0.00%

Domestic
Production
(
103/
yr)
2,187,415
 
280
 
0.01%

Luxury
Wholesale
Price
($/
unit)
$
33,587
$
3.08
0.01%

Domestic
Production
(
103/
yr)
749,746
 
131
 
0.02%

Sports
Wholesale
Price
($/
unit)
$
25,797
$
1.21
0.00%

Domestic
Production
(
103/
yr)
349,955
 
17
0.00%

Pickups
Wholesale
Price
($/
unit)
$
22,126
$
0.23
0.00%

Domestic
Production
(
103/
yr)
2,908,018
 
106
0.00%

Vans
Wholesale
Price
($/
unit)
$
22,910
$
0.80
0.00%

Domestic
Production
(
103/
yr)
1,447,482
 
220
 
0.02%

SUV
Wholesale
Price
($/
unit)
$
27,694
$
0.41
0.00%

Domestic
Production
(
103/
yr)
2,692,763
 
163
 
0.01%
OMB
Review
Draft
December
17,
2003
4­
10
C
Increase
in
control
costs
($
154
million):
Costs
associated
with
coating
operation
HAP
controls
increase.

Although
aggregate
industry
pre­
tax
earnings
decline,
the
regulation
creates
both
winners
and
losers
based
on
the
distribution
of
compliance
costs
across
facilities.
As
shown
in
Table
4­
3,
18
of
the
65
plants
(
28
percent)
are
projected
to
become
more
profitable
with
the
regulation
with
a
total
gain
of
$
2
million.
These
plants
are
either
not
subject
to
additional
controls
or
have
lower
per­
unit
control
costs
(
less
than
$
1
per
vehicle)
relative
to
other
assembly
plants.
The
remaining
47
plants
are
projected
to
experience
a
total
loss
of
$
154
million.
These
plants
have
higher
per­
unit
costs
($
16
per
vehicle
on
average).
This
results
in
an
average
loss
of
$
3.3
million
and
represents
a
1.5
percent
decline
in
the
average
pre­
tax
profit
of
these
plants.

4.3.2.2
Facility
Closures
and
Changes
in
Employment
Economic
theory
suggests
that
a
facility
will
cease
production
if
market
prices
fall
below
the
minimum
average
variable
cost.
EPA
estimates
that
no
automobile
or
LDT
assembly
plant
is
likely
to
prematurely
close
as
a
result
of
the
regulation.
However,
employment
in
the
automobile
and
LDT
assembly
industry
is
projected
to
decrease
by
37
full­
time
equivalents
(
FTEs)
as
a
result
of
decreased
output
levels.
This
represents
a
0.02
percent
decline
in
manufacturing
employment
at
these
assembly
plants.
Table
4­
2.
National­
Level
Industry
Impacts:
1999
Baseline
Absolute
Change
Relative
Change
Revenues
($
106/
yr)
$
290,789
 
$
20.7
 
0.01%

Costs
($
106/
yr)
$
276,746
$
131.1
0.05%

Compliance
$
0
$
153.6
NA
Production
$
276,746
 
$
22.5
 
0.01%

Pre­
Tax
Earnings
($
106/
yr)
$
14,043
 
$
151.8
 
1.08%

Plants
(#)
65
0
0.00%

Employment
(#)
219,817
 
37
 
0.02%
OMB
Review
Draft
December
17,
2003
4­
11
4.3.3
Foreign
Trade
Given
the
small
changes
in
domestic
vehicle
prices
projected
by
the
economic
model,
EPA
estimates
foreign
trade
impacts
associated
with
the
rule
are
negligible.
The
price
of
domestic
vehicles,
averaged
across
all
eight
vehicle
categories,
is
expected
to
rise
by
0.003
percent
as
a
result
of
the
final
regulation,
while
the
price
of
imported
cars
will
remain
unchanged.
The
Agency
computed
two
quantitative
measures
of
foreign
trade
impacts
based
on
this
predicted
price
impact.
As
shown
in
Table
4­
4,
the
ratio
of
imports
to
domestic
sales
is
expected
to
rise
by
approximately
0.01
percent.
Furthermore,
export
sales
are
predicted
to
decline
by
approximately
0.01
percent.

4.3.4
Social
Costs
The
social
impact
of
a
regulatory
action
is
traditionally
measured
by
the
change
in
economic
welfare
that
it
generates.
The
social
costs
of
the
final
rule
will
be
distributed
across
consumers
and
producers
alike.
Consumers
experience
welfare
impacts
due
to
changes
in
market
prices
and
consumption
levels
associated
with
the
rule.
Producers
experience
welfare
impacts
resulting
from
changes
in
profits
corresponding
with
the
changes
Table
4­
3.
Distributional
Impacts
Across
Facilities:
1999
Pre­
Tax
Earnings
Total
Loss
Gain
Assembly
Plants
(#)
47
18
65
Baseline
Production
Total
(
units/
yr)
9,642,611
3,045,681
12,688,292
Average
(
units/
facility)
205,162
169,205
195,204
Baseline
Compliance
Costs
Total
($
106/
yr)
$
153.2
$
0.5
$
153.66
Average
($/
unit)
$
15.89
$
0.16
$
12.11
Change
in
Pre­
Tax
Earnings
($
106/
yr)
 
$
153.6
$
1.7
 
$
151.8
Change
in
Employment
(#)
 
37
1
 
37
OMB
Review
Draft
December
17,
2003
5Those
impacts
are
the
focus
of
the
benefits
analysis
presented
in
Section
6
of
this
report.

4­
12
in
production
levels
and
market
prices.
However,
it
is
important
to
emphasize
that
this
measure
does
not
include
benefits
that
occur
outside
the
market,
that
is,
the
value
of
reduced
levels
of
air
pollution
due
to
the
regulation.
5
The
national
baseline
compliance
cost
estimates
are
often
used
as
an
approximation
of
the
social
cost
of
the
rule.
The
engineering
analysis
estimated
annual
costs
of
$
154
million
(
1999$).
In
this
case,
the
burden
of
the
regulation
falls
solely
on
the
affected
facilities
that
experience
a
profit
loss
exactly
equal
to
these
cost
estimates.
Thus,
the
entire
loss
is
a
change
in
producer
surplus
with
no
change
(
by
assumption)
in
consumer
surplus.
This
is
typically
referred
to
as
a
"
full­
cost
absorption"
scenario
in
which
all
factors
of
production
are
assumed
to
be
fixed
and
firms
are
unable
to
adjust
their
output
levels
when
faced
with
additional
costs.

In
contrast,
the
economic
analysis
conducted
by
the
Agency
accounts
for
behavioral
responses
by
producers
and
consumers
to
the
regulation
(
i.
e.,
shifting
costs
to
other
economic
agents).
This
approach
results
in
a
social
cost
estimate
that
may
differ
from
the
engineering
estimate
and
also
provides
insights
on
how
the
regulatory
burden
is
distributed
across
stakeholders.

Higher
market
prices
lead
to
consumer
losses
of
$
9.1
million,
or
6
percent
of
the
total
social
cost
of
the
rule.
Although
automobile
or
LDT
producers
are
able
to
pass
on
a
limited
amount
of
cost
increases
to
final
consumers,
the
increased
costs
result
in
a
net
decline
in
profits
at
assembly
plants
of
$
152
million.
As
shown
in
Table
4­
5,
EPA
estimates
the
total
social
cost
of
the
rule
to
be
$
161
million.
Note
that
social
cost
estimates
exceeds
baseline
engineering
cost
estimates
by
$
7
million.
The
projected
change
in
welfare
is
higher
because
the
regulation
exacerbates
a
social
inefficiency
(
see
Appendix
B).
In
an
imperfectly
competitive
equilibrium,
the
marginal
benefit
consumers
place
on
the
vehicles,
the
market
price,
exceeds
the
marginal
cost
to
producers
of
manufacturing
the
product.
Thus,
social
Table
4­
4.
Foreign
Trade
Impacts:
1999
%
change
Ratio
of
imports­
to­
domestic
vehicles
0.01%

Exports
 
0.01%
OMB
Review
Draft
December
17,
2003
4­
13
welfare
would
be
improved
by
increasing
the
quantity
of
the
vehicles
provided.
However,
producers
have
no
incentive
to
do
this
because
the
marginal
revenue
effects
of
lowering
the
price
and
increasing
output
is
lower
than
the
marginal
cost
of
these
extra
units.

4.4
Energy
Impacts
Executive
Order
13211
"
Actions
Concerning
Regulations
that
Significantly
Affect
Energy
Supply,
Distribution,
or
Use"
(
66
Fed.
Reg.
28355,
May
22,
2001)
requires
federal
agencies
to
estimate
the
energy
impact
of
significant
regulatory
actions.
The
final
NESHAP
will
trigger
both
an
increase
in
energy
use
due
to
the
operation
of
new
abatement
equipment
as
well
as
a
decrease
in
energy
use
due
to
a
small
decline
in
automobile
production.
The
net
impact
will
be
an
overall
increase
in
the
automobile
industry's
energy
costs
by
about
$
26.41
million
per
year.
These
impacts
are
discussed
below
in
greater
detail.

4.4.1
Increase
in
Energy
Consumption
As
described
earlier
in
Section
3
of
this
report,
automobile
and
LDT
coating
facilities
can
adopt
multiple
strategies
to
reduce
their
HAP
emissions
in
compliance
with
the
final
regulation.
Input
substitution
strategies
2
and
3
will
not
require
significant
amounts
of
extra
energy
because
they
only
involve
the
application
of
modified
coating
materials.
However,
adoption
of
strategy
1
and/
or
strategy
4
will
necessitate
extra
fan
horsepower
to
convey
Table
4­
5.
Distribution
of
Social
Costs:
1999$
Value
($
106/
yr)

Change
in
Consumer
Surplus
 
$
9.1
Subcompacts
 
$
0.2
Compacts
 
$
1.9
Intermediate/
Standard
 
$
1.3
Luxury
 
$
2.3
Sports
 
$
0.4
Pickups
 
$
0.7
Vans
 
$
1.2
SUV
 
$
1.1
Change
in
Producer
Surplus
 
$
151.8
Total
Social
Cost
 
$
160.9
OMB
Review
Draft
December
17,
2003
4­
14
additional
air
streams
to
add­
on
control
devices,
as
well
as
additional
natural
gas
and
electricity
for
operating
these
devices
(
which
are
assumed
to
be
regenerative
thermal
oxidizers).
The
operation
of
such
abatement
equipment
is
estimated
to
require
an
additional
4.9x109
standard
cubic
feet
per
year
of
natural
gas
and
1.8x108
kilowatt
hours
per
year
of
electricity
nationwide
at
a
cost
of
$
3.20
per
thousand
cubic
feet
of
natural
gas
and
$
0.06
per
kilowatt
hour
of
electricity
(
Green,
2002).
Therefore,
the
nationwide
cost
of
the
energy
needed
to
operate
the
control
equipment
required
by
strategies
1
and
4
is
estimated
at
$
26.48
million
per
year.
This
incremental
energy
cost
was
included
in
the
operation
and
maintenance
component
of
the
engineering
cost
estimates
presented
in
Section
3.

4.4.2
Reduction
in
Energy
Consumption
The
economic
model
described
in
Section
4.2
predicts
that
increased
compliance
costs
will
result
in
an
annual
production
decline
of
approximately
1,300
vehicles
valued
at
$
21
million
collectively.
This
production
decline
will
lead
to
a
corresponding
decline
in
energy
usage
by
automobile
manufacturers.
EPA
has
computed
an
average
"
energy
per
unit
output
ratio"
and
multiplied
it
by
the
decline
in
production
to
quantify
this
impact.

Census
data
presented
in
Table
4­
6
indicates
that
the
U.
S.
automobile
and
LDT
industry
incurred
energy
costs
of
$
669
million
to
produce
$
205.8
billion
worth
of
vehicles
in
1997.
This
translates
into
an
energy
consumption
per
unit
of
output
ratio
of
about
0.3
percent
for
the
automobile
and
LDT
industry.
Therefore,
energy
costs
are
estimated
to
decline
by
approximately
$
0.07
million
per
year
if
the
industry's
production
declines
by
1,300
vehicles
valued
at
$
21
million
per
year.

4.4.3
Net
Impact
on
Energy
Consumption
The
operation
of
additional
abatement
capital
is
estimated
to
result
in
an
increase
in
energy
use
worth
$
26.48
million
per
year,
while
the
decline
in
automobile
production
will
result
in
a
decrease
in
energy
use
worth
$
0.07
million
per
year.
These
competing
factors
will
result
in
a
net
increase
in
annual
energy
consumption
by
the
automobile
industry
of
approximately
$
26.41
million,
on
balance.

The
total
electricity
generation
capacity
in
the
U.
S.
was
785,990
Megawatts
in
1999
(
DOE,
1999a).
Thus,
the
electricity
requirements
associated
with
the
additional
abatement
capital
represent
a
small
fraction
of
domestic
generation
capacity.
Similarly,
the
natural
gas
requirements
associated
with
the
final
NESHAP
are
insignificant
given
the
23,755
billion
OMB
Review
Draft
December
17,
2003
4­
15
cubic
feet
of
natural
gas
produced
domestically
in
the
U.
S.
in
1999
(
DOE,
1999b).
Hence,
the
final
NESHAP
is
not
likely
to
have
any
significant
adverse
impact
on
energy
prices,
distribution,
availability,
or
use.
Table
4­
6.
Energy
Usage
in
Automobile
and
LDT
Production
(
1997)

Industrial
Sector
NAICS
Value
of
Shipments
($
106)
Fuel
&
Electricity
Costs
($
106)

Automobile
Mfg.
336111
$
95,385
$
339
Light
Truck
and
Utility
Vehicle
Mfg.
336112
$
110,400
$
330
Total
$
205,785
$
669
Source:
U.
S.
Department
of
Commerce,
Census
Bureau.
October
1999a.
"
Automobile
Manufacturing."
1997
Economic
Census
Manufacturing
Industry
Series.
EC97M0­
3361A.
Washington,
DC:
Government
Printing
Office.

U.
S.
Department
of
Commerce,
Census
Bureau.
October
1999b.
"
Light
Truck
and
Utility
Vehicle
Manufacturing."
1997
Economic
Census
Manufacturing
Industry
Series.
EC97M­
3361B.
Washington,
DC:
Government
Printing
Office.
OMB
Review
Draft
December
17,
2003
5­
1
SECTION
5
OTHER
IMPACT
ANALYSES
The
economic­
and
energy­
impacts
associated
with
the
final
NESHAP
were
described
in
the
previous
section.
Statements
discussing
additional
impacts
on
small
businesses,
unfunded
mandates,
and
new
sources
are
presented
below.

5.1
Small
Business
Impacts
The
Regulatory
Flexibility
Act
(
RFA)
of
1980
as
amended
in
1996
by
the
Small
Business
Regulatory
Enforcement
Fairness
Act
(
SBREFA)
generally
requires
an
agency
to
prepare
a
regulatory
flexibility
analysis
of
a
rule
unless
the
agency
certifies
that
the
rule
will
not
have
a
significant
economic
impact
on
a
substantial
number
of
small
entities.
Small
entities
include
small
businesses,
small
organizations,
and
small
governmental
jurisdictions.

For
purposes
of
assessing
the
impacts
of
the
final
rule
on
small
entities,
a
small
entity
is
defined
as:
(
1)
a
small
business
that
is
a
parent
company
according
to
Small
Business
Administration
(
SBA)
size
standards
for
NAICS
codes
336111
(
automobile
manufacturing)
and
336112
(
light
truck
and
utility
vehicle
manufacturing)
with
1,000
or
fewer
employees;
(
2)
a
small
governmental
jurisdiction
that
is
a
government
of
a
city,
county,
town,
school
district
or
special
district
with
a
population
of
less
than
50,000;
and
(
3)
a
small
organization
that
is
any
not­
for­
profit
enterprise
which
is
independently
owned
and
operated
and
is
not
dominant
in
its
field.

Based
on
the
above
definition
of
small
entities
and
data
reported
in
Section
2
of
this
report,
the
Agency
has
determined
that
there
are
no
small
businesses
within
this
source
category
that
would
be
subject
to
this
final
rule.
Therefore,
because
this
final
rule
will
not
impose
any
requirements
on
small
entities,
EPA
certifies
that
this
action
will
not
have
a
significant
economic
impact
on
a
substantial
number
of
small
entities.

5.2
Unfunded
Mandates
Title
II
of
the
Unfunded
Mandates
Reform
Act
of
1995
(
UMRA),
Public
Law
104­
4,
establishes
requirements
for
federal
agencies
to
assess
the
effects
of
their
regulatory
actions
on
state,
local,
and
tribal
governments
and
on
the
private
sector.
Under
Section
202
of
the
OMB
Review
Draft
December
17,
2003
5­
2
UMRA,
EPA
generally
must
prepare
a
written
statement,
including
a
cost­
benefit
analysis,
for
proposed
and
final
rules
that
includes
any
federal
mandate
that
may
result
in
expenditures
to
state,
local,
and
tribal
governments,
in
the
aggregate,
or
to
the
private
sector,
of
$
100
million
or
more
in
any
one
year.
As
indicated
below,
EPA
is
responsive
to
all
required
provisions
of
UMRA.

Section
202(
a)(
1)
requires
EPA
to
identify
the
relevant
statutory
authority.
The
final
standard
to
limit
emissions
of
HAPs
associated
with
the
automobile
and
LTD
coating
process
is
being
developed
under
Section
112
of
the
CAA
of
1990.

Section
202(
a)(
2)
requires
a
quantitative
and
qualitative
assessment
of
the
anticipated
costs
and
benefits
of
the
regulation.
Section
3
of
this
report
provides
detailed
estimates
of
the
costs
incurred
by
the
private
sector
to
comply
with
the
final
NESHAP.
The
estimated
effects
of
the
regulation
on
the
national
economy
are
described
in
Section
4.
Section
6
of
this
report
provides
a
qualitative
assessment
of
the
benefits
of
reducing
HAP
emissions,
as
well
as
the
additional
benefits
of
reducing
VOC
emissions
due
to
HAP
controls.

Before
EPA
establishes
any
regulatory
requirement
that
significantly
or
uniquely
affects
small
governments,
including
tribal
governments,
it
must
develop
a
small
government
agency
plan
under
Section
203
of
UMRA.
The
final
automobile
and
LDT
coating
NESHAP
does
not
impose
an
unfunded
mandate
on
state,
local,
and
tribal
governments;
the
cost
of
the
regulation
is
borne
by
industry.
Thus,
Section
203
of
UMRA
does
not
apply
to
the
current
rule.

Section
205
of
UMRA
generally
requires
EPA
to
identify
and
consider
a
reasonable
number
of
regulatory
alternatives
and
adopt
the
least
costly,
most
cost­
effective,
or
least
burdensome
alternative
that
achieves
the
objectives
of
the
rule.
For
reasons
discussed
in
the
preamble
of
the
rule,
EPA
has
determined
that
the
current
rule
constitutes
the
least
burdensome
alternative
consistent
with
the
CAA.

5.3
Impact
on
New
Sources
There
is
a
potential
that
new
sources
such
as
new
paint
shops
at
existing
plants
or
new
plants
will
operate
in
the
automobile
industry
in
the
future.
The
final
rule
imposes
more
stringent
limits
on
emissions
from
these
new
sources.
If
control
costs
for
new
sources
and
facilities
are
sufficiently
higher
than
that
for
current
producers,
new
source
performance
standards
can
raise
the
cost
of
entry
in
the
automobile
market.
Thus,
EPA
has
analyzed
the
OMB
Review
Draft
December
17,
2003
5­
3
relative
effect
of
new
source
controls
to
determine
whether
they
are
likely
to
impose
significant
entry
barriers.

It
is
difficult
to
predict
which
of
the
65
facilities
that
currently
operate
in
the
U.
S.
automobile
and
LDT
assembly
industry
will
replace
their
existing
paint
shops
in
the
future.
The
engineering
cost
analysis
presented
in
Section
3
of
this
report
assumes
that
all
existing
plants
will
keep
their
current
paint
shops
and
make
the
necessary
material
changes
and
control
equipment
additions
to
meet
the
final
Maximum
Achievable
Control
Technology
(
MACT)
rule.
This
is
a
conservative
(
higher
MACT­
specific
compliance
cost)
assumption
compared
to
assuming
that
only
some
of
these
paint
shops
will
be
replaced.

The
construction
of
greenfield
facilities
is
also
difficult
to
predict.
EPA
examined
the
list
of
current
facilities
and
determined
that
over
the
past
23
years
there
has
been
about
one
new
greenfield
plant
per
year,
on
average.
These
were
more
frontloaded
in
the
earlier
years
for
many
reasons
including
the
industry­
wide
change
to
basecoat/
clearcoat
from
single
coating
topcoats,
"
retooling"
to
take
advantage
of
new
production
strategies
and
technologies,
and
the
arrival
of
non­
U.
S.
manufacturers
such
as
Honda,
Nissan,
and
Toyota.
Thus,
the
assumption
of
one
new
greenfield
plant
per
year
in
the
future
would
be
an
overly
generous
one.
The
engineering
analysis
does
not
explicitly
include
greenfield
facilities
because
they
are
difficult
to
predict,
the
number
is
both
absolutely
and
relatively
small
compared
to
the
existing
facility
population,
and
the
cost
and
economic
impacts
are
likely
to
be
very
small.

Even
though
the
number
of
affected
entities
cannot
be
predicted,
the
impact
of
new
source
controls
can
be
estimated
qualitatively.
The
additional
MACT­
specific
compliance
costs
for
a
new
source
(
greenfield
plant
or
new
paint
shop
at
an
existing
plant)
would
be
very
low
because
these
new
sources
will
comply
with
existing
VOC
regulations
and
already
have
all
of
the
control
equipment
needed
to
meet
the
final
MACT
rule.
The
only
incremental
costs
for
new
sources
would
be
the
small
cost
of
lower
HAP
coating
materials
and
some
MACT­
specific
monitoring,
reporting,
and
record
keeping
costs
that
they
would
not
have
incurred
in
the
absence
of
the
final
rule.
However,
these
costs
are
in
line
with
the
costs
incurred
by
existing
facilities
and
thus
do
not
impose
any
barriers
to
entry
into
the
industry.
Overall,
given
the
minimal
impacts
on
price
and
production
described
in
Section
4
of
this
report,
it
is
very
unlikely
that
a
substantial
number
of
firms
who
may
consider
entering
the
industry
will
be
significantly
affected.
OMB
Review
Draft
December
17,
2003
6­
1
SECTION
6
BENEFITS
ANALYSIS
The
emission
reductions
achieved
by
this
environmental
regulation
will
provide
benefits
to
society
by
improving
environmental
quality.
This
section
provides
information
on
the
types
and
levels
of
social
benefits
anticipated
from
the
automobile
and
LDT
NESHAP.
This
section
discusses
the
health
and
welfare
effects
associated
with
the
HAPs
and
other
pollutants
emitted
by
automobile
and
LDT
coating
operations.

In
general,
the
reduction
of
HAP
emissions
resulting
from
the
regulation
will
reduce
human
and
environmental
exposure
to
these
pollutants
and
thereby
reduce
the
likelihood
of
potential
adverse
health
and
welfare
effects.
This
section
provides
a
general
discussion
of
the
various
components
of
total
benefits
that
may
be
gained
from
reducing
HAPs
through
this
NESHAP.
The
rule
will
also
achieve
reductions
of
VOCs
and
hence
may
reduce
ground­
level
ozone
and
particulate
matter
(
PM),
the
benefits
of
which
are
presented
separately
from
the
benefits
associated
with
reductions
in
HAPs.
We
do
not
present
a
monetized
benefits
estimate
for
the
HAP
and
other
emission
reductions
associated
with
this
final
rule
for
reasons
discussed
later
in
the
chapter.
We
do
provide
a
qualitative
treatment
of
the
benefits
of
this
final
rule
in
this
chapter.

6.1
Identification
of
Potential
Benefit
Categories
The
benefit
categories
associated
with
the
emission
reductions
predicted
for
this
regulation
can
be
broadly
categorized
as
those
benefits
that
are
attributable
to
reduced
exposure
to
HAPs
and
those
attributable
to
reduced
exposure
to
other
pollutants.
Benefit
categories
include
reduced
incidence
of
neurological
effects,
respiratory
irritation,
and
eye,
nose,
and
throat
irritation
associated
with
exposure
to
noncarcinogenic
HAPs
and
VOCs.
In
addition
to
health
impacts
occurring
as
a
result
of
reductions
in
HAP
and
VOC
emissions,
welfare
impacts
can
also
be
identified.
Each
category
is
discussed
separately
below.
OMB
Review
Draft
December
17,
2003
1In
general,
the
RfC
is
an
estimate
(
with
uncertainty
spanning
perhaps
an
order
of
magnitude)
of
a
daily
inhalation
exposure
of
the
human
population
(
including
sensitive
subgroups)
that
is
likely
to
be
without
an
appreciable
risk
of
deleterious
effects
during
a
lifetime.

6­
2
6.1.1
Benefits
of
Reducing
HAP
Emissions
The
HAP
emissions
reductions
achieved
by
this
rule
are
expected
to
reduce
exposure
to
ambient
concentrations
of
ethylbenzene,
EGBE,
methanol,
methyl
ethyl
ketone
(
MEK),
methyl
isobutyl
ketone
(
MIBK),
toluene,
and
xylenes.
According
to
baseline
emission
estimates,
this
source
category
will
emit
approximately
10,000
tons
per
year
of
HAPs
at
affected
sources
in
the
fifth
year
following
promulgation.
The
regulation
will
reduce
approximately
6,000
tons
of
emissions
per
year
of
the
HAPs
listed
above.
Human
exposure
to
these
HAPs
is
likely
to
occur
primarily
through
inhalation,
but
people
may
also
be
exposed
indirectly
through
ingesting
contaminated
food
or
water
or
through
dermal
contact.
These
substances
may
also
enter
terrestrial
and
aquatic
ecosystems
through
atmospheric
deposition
or
may
be
deposited
on
vegetation
and
soil.
These
HAPs
may
also
enter
the
aquatic
environment
from
the
atmosphere
via
gas
exchange
between
surface
water
and
the
ambient
air
or
by
wet
or
dry
deposition
of
particles
to
which
they
adsorb.
This
analysis
is
focused
only
on
the
air
quality
benefits
of
HAP
reduction.
A
summary
of
the
range
of
potential
physical
health
and
welfare
effects
categories
that
may
be
associated
with
HAP
emissions
is
provided
in
Table
6­
1.
As
noted
in
the
table,
exposure
to
HAPs
can
lead
to
a
variety
of
acute
and
chronic
health
impacts
as
well
as
welfare
impacts.

6.1.1.1
Health
Benefits
of
Reduction
in
HAP
Emissions
The
HAP
emissions
resulting
from
automobile
and
LDT
coating
operations
are
associated
with
a
variety
of
adverse
health
effects.
Acute
(
short­
term)
exposure
to
ethylbenzene
in
humans
results
in
respiratory
effects
such
as
throat
irritation
and
chest
constriction,
irritation
of
the
eyes,
and
neurological
effects
such
as
dizziness.
Chronic
(
long­
term)
exposure
of
humans
to
ethylbenzene
may
cause
eye
and
lung
irritation,
with
possible
adverse
effects
on
the
blood.
Animal
studies
have
reported
effects
on
the
blood,
liver,
and
kidneys
from
chronic
inhalation
exposure
to
ethylbenzene.
No
information
is
available
on
the
developmental
or
reproductive
effects
of
ethylbenzene
in
humans,
but
animal
studies
have
reported
developmental
effects,
including
birth
defects
in
animals
exposed
via
inhalation.
EPA
has
established
a
reference
concentration
(
RfC)
1
of
1
mg/
m3
to
protect
against
adverse
health
effects
other
than
cancer.
The
RfC
is
based
on
the
critical
OMB
Review
Draft
December
17,
2003
2The
critical
effect
is
the
first
adverse
effect,
or
its
known
precursor,
that
occurs
to
the
most
sensitive
species
as
the
dose
rate
of
an
agent
increases.

6­
3
effect2
of
developmental
toxicity
observed
in
studies
with
rats
and
rabbits.
EPA
has
classified
ethylbenzene
in
Group
D,
not
classifiable
as
to
human
carcinogenicity.
OMB
Review
Draft
December
17,
2003
6­
4
Table
6­
1.
Potential
Health
and
Welfare
Effects
Associated
with
Exposure
to
Hazardous
Air
Pollutants
Effect
Type
Effect
Category
Effect
End
Point
Citation
Health
Mortality
Carcinogenicity
EPA
(
1990),
Graham,
Holtgrave,
and
Sawery
(
1989)
Genotoxicity
Graham,
Holtgrave,
and
Sawery
(
1989)
Non­
Cancer
lethality
Voorhees,
Hassett,
and
Cote
(
1989)

Chronic
Morbidity
Neurotoxicity
Immunotoxicity
Pulmonary
function
decrement
Liver
damage
Gastrointestinal
toxicity
Kidney
damage
Cardiovascular
impairment
Hematopoietic
(
Blood
disorders)
Reproductive/
Developmental
toxicity
All
morbidity
end
points
obtained
from
Graham,
Holtgrave,
and
Sawery
(
1989),
Voorhees,
Hassett,
and
Cote.
(
1989),
Cote,
Culpit,
and
Hassett
(
1988)

Acute
Morbidity
Pulmonary
function
decrement
Dermal
irritation
Eye
irritation
Welfare
Materials
Damage
Corrosion/
deterioration
NAS
(
1975)

Aesthetic
Unpleasant
odors
Transportation
safety
concerns
Agriculture
Yield
reductions/
foliar
injury
Stern
et
al.
(
1973)

Ecosystem
Structure
Biomass
decrease
Species
richness
decline
Species
diversity
decline
Community
size
decrease
Organism
lifespan
decrease
Trophic
web
shortening
Weinstein
and
Birk
(
1989)

Source:
Mathtech,
Inc.
May
1992.
Benefit
Analysis
Issues
for
Section
112
Regulations.
Final
report
prepared
for
U.
S.
Environmental
Protection
Agency.
Office
of
Air
Quality
Planning
and
Standards.
Contract
No.
68­
D8­
0094.
Research
Triangle
Park,
NC.
OMB
Review
Draft
December
17,
2003
6­
5
EGBE
is
a
member
of
the
glycol
ethers
HAP
category,
a
large
group
of
related
compounds.
Acute
exposure
in
humans
to
high
levels
of
glycol
ethers
results
in
narcosis,
pulmonary
edema,
and
liver
and
kidney
damage.
Chronic
exposure
to
glycol
ethers
may
result
in
neurological
and
blood
effects,
including
fatigue,
nausea,
tremor,
and
anemia.
No
information
is
available
on
the
reproductive
or
developmental
effects
of
glycol
ethers
in
humans,
but
animal
studies
have
reported
such
effects,
including
testicular
damage,
reduced
fertility,
maternal
toxicity,
early
embryonic
death,
birth
defects,
and
delayed
development.
EPA
has
established
an
RfC
of
13
mg/
m3
to
protect
against
adverse
health
effects
other
than
cancer
based
on
the
critical
effect
of
decreases
in
red
blood
cell
count
observed
in
studies
with
rats.

No
reliable
human
epidemiological
studies
are
available
that
address
the
potential
carcinogenicity
of
EGBE,
but
a
draft
report
of
a
2­
year
rodent
inhalation
study
reported
equivocal
evidence
of
carcinogenic
activity
in
female
rats
and
male
mice.
Because
of
the
uncertain
relevance
of
these
tumor
increases
to
humans,
the
fact
that
EGBE
is
generally
negative
in
genotoxic
tests,
and
the
lack
of
human
data
to
support
the
findings
in
rodents,
the
human
carcinogenic
potential
of
EGBE
cannot
be
determined
at
this
time.
EPA
has
classified
EGBE
as
a
Group
C,
possible
human
carcinogen.

Acute
inhalation
exposure
to
MEK
in
humans
results
in
irritation
to
the
eyes,
nose,
and
throat.
Little
information
is
available
on
the
chronic
effects
of
MEK
in
humans,
but
inhalation
studies
in
animals
have
reported
slight
neurological,
liver,
kidney,
and
respiratory
effects.
No
information
is
available
on
the
developmental,
reproductive,
or
carcinogenic
effects
of
MEK
in
humans.
Developmental
effects,
including
decreased
fetal
weight
and
fetal
malformations,
have
been
reported
in
mice
and
rats
exposed
to
MEK
via
inhalation
and
ingestion.
EPA
has
established
an
RfC
of
1
mg/
m3
to
protect
against
adverse
health
effects
other
than
cancer
based
on
the
critical
effect
of
decreased
birth
weight
observed
in
studies
with
mice.
EPA
has
classified
MEK
in
Group
D,
not
classifiable
as
to
human
carcinogenicity.

Acute
or
chronic
exposure
of
humans
to
methanol
by
inhalation
or
ingestion
may
result
in
blurred
vision,
headache,
dizziness,
and
nausea.
No
information
is
available
on
the
reproductive,
developmental,
or
carcinogenic
effects
of
methanol
in
humans.
Birth
defects
have
been
observed
in
the
offspring
of
rats
and
mice
exposed
to
methanol
by
inhalation.
A
methanol
inhalation
study
using
rhesus
monkeys
reported
a
decrease
in
the
length
of
pregnancy
and
limited
evidence
of
impaired
learning
ability
in
offspring.
EPA
has
not
established
an
RfC
for
methanol
or
classified
methanol
with
respect
to
carcinogenicity.
The
OMB
Review
Draft
December
17,
2003
6­
6
California
Environmental
Protection
Agency
has
developed
a
reference
exposure
level
(
similar
in
concept
to
an
RfC)
of
4
mg/
m3
based
on
the
critical
effect
of
birth
defects
observed
in
studies
with
mice.

Acute
exposure
to
MIBK
may
irritate
the
eyes
and
mucous
membranes
and
cause
weakness,
headache,
and
nausea.
Chronic
exposure
to
workers
has
been
observed
to
cause
nausea,
headache,
burning
eyes,
insomnia,
intestinal
pain,
and
slight
enlargement
of
the
liver.
No
information
is
available
on
reproductive
or
developmental
effects
of
MIBK
in
humans,
but
studies
with
rats
and
mice
have
reported
neurological
effects
and
increased
liver
and
kidney
weights.
EPA
has
not
established
an
RfC
for
MIBK
or
classified
it
with
respect
to
carcinogenicity.
Animal
studies
are
currently
underway
that
are
expected
to
provide
the
foundation
for
an
EPA
assessment.

Acute
inhalation
of
toluene
by
humans
may
cause
effects
to
the
central
nervous
system
(
CNS),
such
as
fatigue,
sleepiness,
headache,
and
nausea,
as
well
as
irregular
heartbeat.
Adverse
CNS
effects
reported
in
chronic
abusers
exposed
to
high
levels
of
toluene
include
tremors;
decreased
brain
size;
involuntary
eye
movements;
and
impaired
speech,
hearing,
and
vision.
Chronic
inhalation
exposure
of
humans
to
lower
levels
of
toluene
also
causes
irritation
of
the
upper
respiratory
tract,
eye
irritation,
sore
throat,
nausea,
dizziness,
headaches,
and
difficulty
with
sleep.
Studies
of
children
whose
mothers
were
exposed
to
toluene
by
inhalation
or
mixed
solvents
during
pregnancy
have
reported
CNS
problems,
facial
and
limb
abnormalities,
and
delayed
development.
However,
these
effects
may
not
be
attributable
to
toluene
alone.
EPA
has
established
an
RfC
of
0.4
mg/
m3
to
protect
against
adverse
health
effects
other
than
cancer.
The
RfC
is
based
on
the
critical
effect
of
decreased
neurological
performance
in
workers
exposed
to
toluene
emitted
from
glue.
EPA
has
classified
toluene
in
Group
D,
not
classifiable
as
to
human
carcinogenicity.

Acute
inhalation
of
mixed
xylenes
(
a
mixture
of
three
closely
related
compounds)
in
humans
may
cause
irritation
of
the
nose
and
throat,
nausea,
vomiting,
gastric
irritation,
mild
transient
eye
irritation,
and
neurological
effects.
Chronic
inhalation
of
xylenes
in
humans
may
result
in
nervous
system
effects
such
as
headache,
dizziness,
fatigue,
tremors,
and
incoordination.
Other
reported
effects
include
labored
breathing,
heart
palpitation,
severe
chest
pain,
abnormal
electrocardiograms,
and
possible
effects
on
the
blood
and
kidneys.
EPA
has
not
developed
an
RfC
for
xylenes.
The
Agency
for
Toxic
Substances
and
Disease
Registry
has
published
a
minimum
risk
level
(
similar
to
an
RfC)
for
xylenes
of
0.43
mg/
m3
based
on
CNS
effects
in
rodents.
EPA
has
classified
xylenes
in
Category
D,
not
classifiable
with
respect
to
human
carcinogenicity.
OMB
Review
Draft
December
17,
2003
6­
7
For
the
HAPs
covered
by
the
automobile
and
LDT
NESHAP,
evidence
on
the
potential
toxicity
of
the
pollutants
varies.
However,
given
sufficient
exposure
conditions,
each
of
these
HAPs
has
the
potential
to
elicit
adverse
health
or
environmental
effects
in
the
exposed
populations.

EPA
recently
prepared
a
relative
ranking
evaluation
for
all
HAPs
for
the
purpose
of
selecting
30
HAPs
posing
the
greatest
health
risk
in
urban
areas
(
Smith
et
al.,
1999).
This
evaluation
combined
all
available
data
on
toxic
potential
with
nationwide
emission
and
ambient
concentration
information
(
i.
e.,
not
just
urban)
for
all
188
HAPs,
considering
both
cancer
and
noncancer
end
points
and
both
inhalation
and
ingestion
exposures.
The
available
database
supported
quantitative
ranks
for
more
than
150
HAPs,
including
the
seven
HAPs
most
commonly
used
in
(
or
emitted
by)
this
source
category.
None
of
these
seven
HAPs
were
found
to
present
a
hazard
sufficient
to
justify
including
them
on
the
list
of
urban
air
toxics.

EPA
recently
prepared
a
draft
national­
scale
assessment
as
part
of
its
National
Air
Toxics
Assessment
activities
(
EPA,
2001).
This
draft
assessment
estimates
human
inhalation
exposures
to
the
urban
HAPs
selected
based
on
the
ranking
study
described
above.
To
the
extent
that
EPA's
ranking
analysis
was
effective,
HAPs
included
in
the
urban
list
were
likely
to
present
greater
health
risks
than
those
that
did
not.
Less
than
one­
third
of
the
noncarcinogens
evaluated
by
the
national­
scale
assessment
were
judged
likely
to
have
human
exposure
exceeding
the
RfC
anywhere
in
the
U.
S.

It
is
important
to
note
that
the
national­
scale
assessment
did
not
include
ingestion
exposures
or
acute
time­
scales
and
used
simplified
models
that
were
not
efficient
at
estimating
hot
spots
or
maximum
individual
exposures.
However,
the
results
suggest
that
most
of
the
noncarcinogens
included
in
the
assessment
do
not
present
national
concerns.
Because
the
HAPs
in
the
national­
scale
assessment
arguably
present
greater
potential
hazards
than
the
seven
HAPs
most
commonly
used
in
(
or
emitted
by)
this
source
category,
EPA
has
no
information
that
suggests
there
is
presently
any
widespread
overexposure
to
these
six
HAPs.
Nevertheless,
given
the
limitations
of
the
national­
scale
assessment,
this
may
not
be
true
in
all
areas
or
for
all
receptors.

6.1.1.2
Welfare
Benefits
of
Reducing
HAP
Emissions
The
welfare
effects
of
exposure
to
HAPs
have
received
less
attention
from
analysts
than
the
health
effects.
However,
this
situation
is
gradually
changing,
as
over
the
past
10
years,
ecotoxicologists
have
started
to
build
models
of
ecological
systems
that
focus
on
OMB
Review
Draft
December
17,
2003
6­
8
interrelationships
in
function,
the
dynamics
of
stress,
and
the
adaptive
potential
for
recovery.
This
perspective
is
reflected
in
Table
6­
1
where
the
end
points
associated
with
ecosystem
functions
describe
structural
attributes
rather
than
species­
specific
responses
to
HAP
exposure.
This
development
is
consistent
with
the
observation
that
chronic
sublethal
exposures
may
affect
the
normal
functioning
of
individual
species
in
ways
that
make
them
less
than
competitive
and
therefore
more
susceptible
to
a
variety
of
factors
including
disease,
insect
attack,
and
decreases
in
habitat
quality
(
EPA,
1991).
All
of
these
factors
may
contribute
to
an
overall
change
in
the
structure
(
i.
e.,
composition)
and
function
of
the
ecosystem.

The
overall
environmental
behavior
of
these
HAPs
can
be
evaluated
using
fugacity
models.
Fugacity
is
a
thermodynamic
property
and
is
equal
to
the
partial
pressure
of
a
substance
in
compartment.
Thus
the
fugacity
of
a
substance
in
an
environmental
medium
(
e.
g.,
air,
water,
soil,
or
sediment)
is
a
measure
of
the
substance's
tendency
to
escape
that
medium
and
enter
another
medium.
The
Mackay
Level
III
model
is
a
relatively
rigorous
representation
of
multiple
environmental
compartments
and
the
fate
and
transport
process
through
which
chemicals
are
moved
through
them
(
Mackay,
1991).

The
Level
III
model
indicates
that
the
HAPs
released
from
automobile
and
LDT
coating
operations
once
emitted
to
the
ambient
air
as
vapors
are
likely
to
remain
in
the
vapor
phase
as
VOCs.
Model
estimates
of
HAPs
remaining
in
the
air
compartment
range
from
greater
than
99
percent
of
the
ethyl
benzene,
xylenes,
and
toluene
to
approximately
85
percent
of
methanol
emissions.

The
median
half­
lives
for
these
HAPs
in
the
vapor
phase
range
from
23
hours
for
xylenes
to
57
hours
for
toluene.
As
VOCs,
they
under
go
various
chemical
reactions
that
contribute
to
the
formation
of
other
atmospheric
pollutants
that
can
affect
welfare.
For
example,
these
VOCs
can
contribute
to
ozone
in
the
environment.
EPA
has
previously
stated
(
59
FR
1788,
January
12,
1994)
that
ozone's
effects
on
green
plants
include
injury
to
foliage,
reductions
in
growth,
losses
in
yield,
alterations
in
reproductive
capacity,
and
alterations
in
susceptibility
to
pests
and
pathogens.
Based
on
known
interrelationships
of
different
components
of
ecosystems,
such
effects,
if
of
sufficient
magnitude,
may
potentially
lead
to
irreversible
changes
of
a
sweeping
nature
to
ecosystems.

In
addition
to
directly
contributing
to
ozone
formation,
the
reaction
of
methanol
with
nitrogen
dioxide
in
a
smog
chamber
has
been
shown
to
yield
methyl
nitrite
and
nitric
acid.
The
reaction
of
methanol
with
nitrogen
dioxide
may
be
the
major
source
of
methyl
nitrite
OMB
Review
Draft
December
17,
2003
6­
9
that
has
the
potential
to
cause
allergic
responses
in
polluted
atmospheres.
However,
methyl
that
is
short
lived
in
the
atmosphere.
It
is
rapidly
photolyzed
by
sunlight,
with
a
mean
lifetime
of
about
10
to
15
minutes.
The
result
is
the
production
of
NOx,
which
contributes
to
an
increase
in
ozone.

Beyond
photochemical
removal
processes,
a
relatively
small
portion
of
these
vaporphase
HAPs,
as
well
as
some
of
the
particulates,
leave
the
ambient
air
via
removal
processes
such
as
wet
or
dry
deposition.
Compounds
such
as
methanol,
EGBE,
and
MIBK
are
slightly
miscible
in
water
and
can
therefore
be
physically
removed
from
the
air
by
rain.
The
other
HAPs
(
i.
e,
toluene,
xylenes,
ethyl
benzene)
are
less
soluble
but
can
be
deposited
on
surfaces
via
processes
such
as
dry
deposition
or
impaction.

In
water,
the
HAPs
released
from
automobile
and
LDT
coating
operations
exhibit
low
to
moderate
acute
aquatic
toxicity.
Methanol,
EGBE,
and
MIBK
represent
the
low
side
and
MEK,
xylenes,
toluene,
and
ethyl
benzene
are
considered
to
present
moderate
acute
toxicity.
All
of
these
HAPs
exhibit
low
persistence
and
low
bio­
accumulation
potential.
The
persistence,
as
indicated
by
median
half­
lives
in
water,
range
from
a
low
of
96
hours
for
methanol
to
a
maximum
of
312
hours
for
toluene.
The
bio­
accumulation
factor
(
BAF)
is
defined
as
the
concentration
of
a
substance
in
an
organism
divided
by
the
concentration
of
the
chemical
in
the
surrounding
medium
measured
in
an
intact
ecosystem.
As
such,
the
BAF
takes
into
account
accumulation
through
ingested
food,
as
well
as
the
concentration
from
the
surrounding
medium.

A
low
bio­
accumulation
potential
indicates
that
they
are
not
likely
to
bio­
concentrate
through
the
food
chain.
However,
substances
that
do
not
tend
to
readily
bio­
accumulate
or
bio­
concentrate
may
be
taken
up
by
biota
and
still
exert
a
deleterious
effect.
These
effects
could
potentially
include
such
impacts
as
lethality
or
reproductive
impairment
to
vulnerable
species
resulting
in
impacts
to
recreational
or
commercial
fishers,
as
well
as
the
ecosystems
supporting
these
fisheries.
This
not
only
has
potential
adverse
implications
for
individual
wildlife
species,
(
including
threatened
or
endanger
species)
and
ecosystems
as
a
whole,
but
also
to
humans
who
may
depend
on
contaminated
fish
and
waterfowl.

Once
deposited
on
soil
or
sediments
these
HAPs
are
subject
to
a
variety
of
competing
removal
mechanisms
including
evaporation,
mobility,
bio­
transformation,
and
chemical
reactions.
Xylenes
deposited
on
soil
can
vaporize
or,
if
contained
on
sediment,
be
buried.
Methanol
and
ethyl
benzene
demonstrate
high
mobility
in
soil
and
can
end
up
in
ground
water,
and
EGBE
and
MIBK
are
readily
subject
to
aerobic
and
anaerobic
bio­
transformation.
OMB
Review
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December
17,
2003
6­
10
The
estimated
median
half­
lives
for
these
HAPs
in
soil
ranges
from
96
hours
for
MIBK
and
methanol
to
420
hours
for
xylenes.
In
sediment,
the
estimated
median
half­
lives
are
384
hours
for
MIBK
and
methanol
to
1,248
hours
for
toluene.
Once
deposited
on
soil
or
in
sediments,
these
HAPs
can
enter
into
terrestrial
biota
through
diet
or
directly
from
the
surrounding
media.
The
potential
for
this
uptake
of
HAPs
to
adversely
affect
individual
wildlife
species
(
including
threatened
or
endanger
species)
as
well
as
ecosystems
as
a
whole
is
not
understood.

In
summary,
the
potential
adverse
effects
of
these
HAPs
on
individual
wildlife
species
or
aquatic
terrestrial
ecosystems
have
not
been
characterized.
However,
HAP
emission
reductions
achieved
through
the
automobile
and
LDT
NESHAP
should
reduce
the
associated
adverse
environmental
impacts.

6.1.2
Benefits
of
Reducing
VOC
Emissions
due
to
HAP
Controls
VOCs
are
a
precursor
to
tropospheric
(
ground­
level)
ozone,
and
exposure
to
groundlevel
ozone
has
been
linked
to
acute
and
chronic
effects
on
human
health
and
welfare.
This
section
addresses
these
effects.

Human
exposure
to
elevated
concentrations
of
ozone
primarily
results
in
respiratoryrelated
impacts
such
as
coughing
and
difficulty
in
breathing.
Eye
irritation
is
another
frequently
observed
effect.
These
acute
effects
are
generally
short­
term
and
reversible.
Nevertheless,
a
reduction
in
the
severity
or
scope
of
such
impacts
may
have
significant
economic
value.

Recent
studies
have
found
that
repeated
exposure
to
elevated
concentrations
of
ozone
over
long
periods
of
time
may
also
lead
to
chronic,
structural
damage
to
the
lungs
(
EPA,
1995b).
To
the
extent
that
these
findings
are
verified,
the
potential
scope
of
benefits
related
to
reductions
in
ozone
concentrations
could
be
expanded
significantly.

Major
ozone
adverse
health
effects
are
alterations
in
lung
capacity
and
breathing
frequency;
eye,
nose
and
throat
irritation;
reduced
exercise
performance;
malaise
and
nausea;
increased
sensitivity
of
airways;
aggravation
of
existing
respiratory
disease;
decreased
sensitivity
to
respiratory
infection;
and
extra
pulmonary
effects
(
CNS,
liver,
cardiovascular,
and
reproductive
effects).
It
is
expected
that
VOC
reductions
through
the
automobile
and
LDT
coatings
rule
will
lead
to
a
reduction
in
ambient
ozone
concentrations
and,
in
turn,
reduce
the
incidence
of
the
adverse
health
effects
of
ozone
exposure.
OMB
Review
Draft
December
17,
2003
6­
11
Major
ozone
adverse
welfare
effects
are
reduction
in
the
economic
value
of
certain
agricultural
crops
and
ornamental
plants
and
materials
damage.
Over
the
last
decade,
a
series
of
field
experiments
has
demonstrated
a
positive
statistical
association
between
ozone
exposure
and
yield
reductions
as
well
as
visible
injury
to
several
economically
valuable
cash
crops,
including
soybeans
and
cotton.
Damage
to
selected
timber
species
has
also
been
associated
with
exposure
to
ozone.
The
observed
impacts
range
from
foliar
injury
to
reduced
growth
rates
and
premature
death.
Benefits
of
reduced
ozone
concentrations
include
the
value
of
avoided
losses
in
commercially
valuable
timber
and
aesthetic
losses
suffered
by
nonconsumptive
users
(
EPA,
1995b).

There
are
some
benefits
from
reduced
VOC
emissions
beyond
merely
a
reduction
in
ozone
concentration.
Approximately
1
to
2
percent
of
VOCs
precipitate
in
the
atmosphere
to
form
particulate
matter
(
PM)
with
an
aerodynamic
diameter
at
or
below
10
micrometers
(
called
PM­
10).
There
are
a
number
of
benefits
from
reduced
PM
concentration,
including
reduced
soiling
and
materials
damage,
increased
visibility,
and
reductions
in
excess
deaths
and
morbidity.
However,
the
focus
of
this
part
of
the
benefits
section
is
on
the
benefits
from
reduced
ozone
concentrations
because
they
are
greater
than
those
from
reduced
PM­
10
concentrations.
PM­
10
control
is
already
prescribed
by
primary
and
secondary
National
Ambient
Air
Quality
Standards
(
NAAQS)
promulgated
by
EPA,
which
are
now
under
review.
For
more
information
on
ozone
health
and
welfare
effects,
refer
to
the
1996
Ozone
NAAQS
Staff
Paper
developed
by
the
Agency.

Sizable
uncertainties
exist
in
any
risk
estimates,
including
these.
Emissions
estimates
can
be
off
by
a
factor
of
two
or
more
one
time
out
of
three,
and
air
dispersion
models
can
have
a
similar
uncertainty.
Consideration
of
actual
exposures
also
adds
uncertainty.
Estimates
of
the
total
burden
of
disease
associated
with
air
pollution
and
air
toxics
are
rough.
Cancer
potency
factors
contribute
additional
uncertainty
of
often
greater
magnitude.
Although
we
did
not
formally
estimate
the
combined
uncertainties
for
these
risk
estimates,
it
is
very
likely
that
the
uncertainty
around
these
estimates
is
at
least
a
factor
of
10
above
or
below
the
stated
values.

We
did
not
quantify
the
benefits
from
VOC
reductions
for
this
rule
because
of
a
lack
of
Science
Advisory
Board
(
SAB)­
approved
methods
for
doing
so.
EPA
is
working
with
the
SAB
to
develop
better
methods
for
analyzing
the
benefits
of
reductions
in
VOCs.

6.2
Lack
Of
Approved
Methods
To
Quantify
HAP
Benefits
OMB
Review
Draft
December
17,
2003
6­
12
There
are
both
cancer
and
non­
cancer
health
effects
associated
with
the
HAPs
that
are
controlled
under
this
rule.
In
previous
analyses
of
the
benefits
of
reductions
in
HAPs,
EPA
has
quantified
and
monetized
the
benefits
of
reduced
incidences
of
cancer.
23,
24
In
some
cases,
EPA
has
also
quantified
(
but
not
monetized)
reductions
in
the
number
of
people
exposed
to
non­
cancer
HAP
risks
above
no­
effect
levels.
25
Monetization
of
the
benefits
of
reductions
in
cancer
incidences
requires
several
important
inputs,
including
central
estimates
of
cancer
risks,
estimates
of
exposure
to
carcinogenic
HAPs,
and
estimates
of
the
value
of
an
avoided
case
of
cancer
(
fatal
and
nonfatal
In
the
above
referenced
analyses,
EPA
relied
on
unit
risk
factors
(
URF)
developed
through
risk
assessment
procedures.
The
unit
risk
factor
is
a
quantitative
estimate
of
the
carcinogenic
potency
of
a
pollutant,
often
expressed
as
the
probability
of
contracting
cancer
from
a
70
year
lifetime
continuous
exposure
to
a
concentration
of
one
:
g/
m3
of
a
pollutant.
These
URFs
are
designed
to
be
conservative,
and
as
such,
are
more
likely
to
represent
the
high
end
of
the
distribution
of
risk
rather
than
a
best
or
most
likely
estimate
of
risk.

In
a
typical
analysis
of
the
expected
health
benefits
of
a
regulation
(
see
for
example,
"
Regulatory
Impact
Analysis:
Heavy­
Duty
Engine
and
Highway
Diesel
Fuel
Sulfur
Control
Requirements",
December
2000,
EPA420­
R­
00­
026),
health
effects
are
estimated
by
applying
changes
in
pollutant
concentrations
to
best
estimates
of
risk
obtained
from
epidemiological
studies.
As
the
purpose
of
a
benefit
analysis
is
to
describe
the
benefits
most
likely
to
occur
from
a
reduction
in
pollution,
use
of
high­
end,
conservative
risk
estimates
will
lead
to
a
biased
estimate
of
the
expected
benefits
of
the
regulation.

However
the
methods
to
conduct
a
risk
analysis
of
HAP
reductions
produces
highend
estimates
of
benefits
due
to
assumptions
required
in
such
analyses.
While
we
used
highend
risk
estimates
in
past
analyses,
recent
advice
from
the
EPA
Science
Advisory
Board
(
SAB)
and
internal
methods
reviews
have
suggested
that
we
avoid
using
high­
end
estimates
in
current
analyses.
Also,
limited
input
data
on
non­
cancer
effects
associated
with
exposure
to
these
HAPs
does
not
allow
us
to
quantify
the
benefits
from
risk
reductions
of
these
effecs.
For
these
reasons,
we
will
not
attempt
to
quantify
the
health
benefits
of
reductions
in
HAPs
unless
best
estimates
of
risks
are
available.
EPA
is
working
with
the
SAB
to
develop
better
methods
for
analyzing
the
benefits
of
reductions
in
HAPs.
While
not
appropriate
as
part
of
a
primary
estimate
of
benefits,
to
estimate
the
potential
baseline
risks
posed
by
the
Auto
and
Light­
Duty
Truck
source
category
,
EPA
performed
a
"
rough"
risk
assessment,
described
below.
There
are
large
uncertainties
regarding
all
components
of
the
risk
quantification
step,
including
location
of
emission
reductions,
emission
estimates,
air
concentrations,
exposure
OMB
Review
Draft
December
17,
2003
6­
13
levels
and
dose­
response
relationships.
However,
if
these
uncertainties
are
properly
identified
and
characterized,
it
is
possible
to
provide
estimates
of
the
reduction
in
inhalation
cancer
incidence
associated
with
this
rule.
It
is
important
to
keep
in
mind
that
these
estimates
will
only
cover
a
very
limited
portion
of
the
potential
HAP
effects
of
the
rule,
as
they
exclude
non­
inhalation
based
cancer
risks
and
non­
cancer
health
effects.

6.2.1
Characterization
of
Industry
Emissions
and
Potential
Baseline
Health
Effects
For
the
automobile
and
light­
duty
truck
surface
coating
source
category,
seven
HAP
account
for
over
95
percent
of
the
total
HAP
emitted.
Those
seven
HAP
are
toluene,
xylene,
glycol
ethers
(
including
ethylene
glycol
monobutyl
ether
(
EGBE)),
MEK,
MIBK,
ethylbenzene,
and
methanol.
Additional
HAP
which
may
be
emitted
by
some
automobile
and
light­
duty
truck
surface
coating
operations
are:
ethylene
glycol,
hexane,
formaldehyde,
chromium
compounds,
diisocyanates,
manganese
compounds,
methyl
methacrylate,
methylene
chloride,
and
nickel
compounds.

Of
the
seven
HAP
emitted
in
the
largest
quantities
by
this
source
category,
all
can
cause
toxic
effects
following
sufficient
exposure.
The
potential
toxic
effects
of
these
seven
HAP
include
effects
to
the
central
nervous
system,
such
as
fatigue,
nausea,
tremors,
and
loss
of
motor
coordination;
adverse
effects
on
the
liver,
kidneys,
and
blood;
respiratory
effects;
and,
developmental
effects.
In
addition,
one
of
the
seven
predominant
HAP,
EGBE,
is
a
possible
carcinogen,
although
information
on
this
compound
is
not
currently
sufficient
to
allow
us
to
quantify
its
potency.

In
accordance
with
section
112(
k),
EPA
developed
a
list
of
33
HAP
which
present
the
greatest
threat
to
public
health
in
the
largest
number
of
urban
areas.
None
of
the
predominant
seven
HAP
is
included
on
this
list
for
the
EPA's
Urban
Air
Toxics
Program,
although
three
of
the
other
emitted
HAP
(
formaldehyde,
manganese
compounds,
and
nickel
compounds)
appear
on
the
list.
In
November
1998,
EPA
published
"
A
Multimedia
Strategy
for
Priority
Persistent,
Bioaccumulative,
and
Toxic
(
PBT)
Pollutants."
None
of
the
predominant
seven
HAP
emitted
by
automobile
and
light­
duty
truck
surface
coating
operations
appears
on
the
published
list
of
compounds
referred
to
in
the
EPA's
PBT
strategy.

To
estimate
the
potential
baseline
risks
posed
by
the
source
category
,
EPA
performed
a
"
rough"
risk
assessment
for
56
of
the
approximately
60
facilities
in
the
source
category
by
using
a
model
plant
placed
at
the
actual
location
of
each
plant
and
simulating
OMB
Review
Draft
December
17,
2003
6­
14
impacts
using
air
emissions
data
from
the
1999
EPA
Toxics
Release
Inventory
(
TRI).
In
addition
to
the
seven
predominant
HAP,
the
following
additional
HAP
were
included
in
this
rough
risk
assessment
because
they
were
reported
in
TRI
as
being
emitted
by
facilities
in
the
source
category:
ethylene
glycol,
hexane,
formaldehyde,
diisocyanates,
manganese
compounds,
nickel
compounds
and
benzene.
The
benzene
emissions
and
some
of
the
nickel
emissions
are
from
non­
surface
coating
activities
which
are
not
part
of
the
source
category.
Of
the
HAP
reported
in
TRI
which
are
emitted
from
automobile
and
light­
duty
truck
surface
coating
operations,
three
(
formaldehyde,
nickel
compounds,
and
EGBE)
are
carcinogens
that,
at
present,
are
not
considered
to
have
thresholds
for
cancer
effects.
Most
facilities
in
this
source
category
emit
some
small
quantity
of
formaldehyde.
In
the
1999
TRI,
however,
only
two
facilities
in
this
source
category
reported
formaldehyde
emissions.
No
other
facilities
exceeded
the
TRI
reporting
threshold
for
formaldehyde
in
1999.

6.2.2
Results
of
Rough
Risk
Assessments
of
Alternative
Control
Options
Under
CAA
Sections
112
(
d)
4
and
112(
c)(
9)

The
results
of
the
human
health
risk
assessments
described
below
are
based
on
approaches
for
quantifying
exposure,
risk,
and
cancer
incidence
that
carry
significant
assumptions,
uncertainties,
and
limitations.
For
example,
in
conducting
these
types
of
analyses,
there
are
typically
many
uncertainties
regarding
dose­
response
functions,
levels
of
exposure,
exposed
populations,
air
quality
modeling
applications,
emission
levels,
and
control
effectiveness.
The
risk
estimates
from
this
rough
assessment
are
also
based
on
typical
facility
configurations
(
i.
e.,
model
plants).
As
such,
they
are
subject
to
significant
uncertainties.
The
actual
risks
at
any
one
facility
could
be
significantly
higher
or
lower.
Because
the
estimates
derived
from
the
various
scoping
approaches
are
necessarily
rough,
we
are
concerned
that
they
not
convey
a
false
sense
of
precision.
Any
point
estimates
of
risk
reduction
or
benefits
generated
by
these
approaches
should
be
considered
as
part
of
a
range
of
potential
estimates.

If
this
final
rule
is
implemented
at
all
automobile
and
light­
duty
truck
surface
coating
facilities,
the
number
of
people
exposed
to
hazard
index
(
HI)
values
equal
to,
or
greater
than,
1
was
estimated
to
be
reduced
from
about
100
to
about
10.
The
number
of
people
exposed
to
HI
values
of
0.2
or
greater
was
predicted
to
decrease
from
about
3500
to
about
1200.
(
Details
of
these
analyses
are
available
in
the
docket.)
OMB
Review
Draft
December
17,
2003
6­
15
The
baseline
cancer
risk
and
subsequent
cancer
risk
reductions
were
estimated
to
be
minimal
for
this
source
category.
The
rough
risk
assessment
indicated
that
currently
no
one
would
be
exposed
to
a
lifetime
cancer
risk
above
10
in
a
million
and
perhaps
6,000
people
would
be
exposed
to
a
lifetime
cancer
risk
above
1
in
a
million
as
a
result
of
emissions
from
these
facilities.
The
final
rule
is
not
expected
to
have
any
significant
effect
on
cancer
risk.
Of
the
three
carcinogens
included
in
the
assessment,
emission
reductions
attributable
to
the
final
rule
could
be
estimated
for
only
EGBE.
The
cancer
risk
for
EGBE,
however,
cannot
currently
be
quantified.
OMB
Review
Draft
December
17,
2003
R­
1
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2003
R­
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OMB
Review
Draft
December
17,
2003
Appendix
A
Economic
Model
for
Automobile
and
LDT
Market
Under
Imperfect
Competition
OMB
Review
Draft
December
17,
2003
A­
1
The
final
regulation
will
increase
the
cost
of
production
for
existing
vehicle
assembly
plants.
The
regulated
facilities
may
alter
their
current
levels
of
production
or
even
close
the
facility
in
response
to
the
increased
costs.
These
responses
will
in
turn
determine
the
impact
of
the
regulation
on
total
market
supply
and
ultimately
on
the
equilibrium
price
and
quantity.
The
economic
analysis
described
below
employs
standard
concepts
of
microeconomics
to
model
these
impacts.

A.
1
U.
S.
Demand
for
Domestic
Vehicles
The
Agency
has
modeled
separate
markets
for
eight
domestic
vehicle
categories:
subcompacts,
compacts,
intermediate/
standard,
luxury,
sports,
pickups,
vans,
and
other.
Domestic
demand
for
each
vehicle
category
i
can
be
expressed
by
the
following
constant
elasticity
demand
function:

where
pi
is
the
average
price
of
vehicle
category
i,
,
i
d
is
the
own­
price
demand
elasticity
for
vehicle
category
i,
and
Ai
is
a
multiplicative
demand
parameter
that
calibrates
the
demand
equation
given
data
on
price
and
the
demand
elasticity
to
replicate
the
observed
baseline
year
(
1999)
level
of
domestic
consumption
of
vehicles
of
class
i.

Estimates
of
average
retail
prices
and
own­
price
elasticities
by
vehicle
class
are
presented
in
Table
A­
1.
The
average
retail
price
for
each
of
the
eight
vehicle
classes
is
derived
from
the
Automotive
New
Market
Data
Book,
as
described
previously
in
Section
2.4.3.
The
own­
price
elasticity
of
demand
for
each
vehicle
class
is
taken
from
Goldberg
(
1995)
who
estimates
them
using
micro
data
on
transaction
prices
and
make/
models
from
the
Consumer
Expenditure
Survey
and
the
Automotive
News
Market
Data
Book.
Note
that
these
demand
elasticity
estimates
are
all
greater
than
one
in
absolute
value
but
vary
across
vehicle
classes
in
an
intuitive
manner.
For
example,
the
demand
for
intermediate
and
standard
automobiles
is
highly
elastic,
while
that
for
sports
and
luxury
cars
is
the
least
price
elastic.

A.
2
U.
S.
Supply
of
Domestic
Vehicles
Given
the
capital
in
place,
each
facility
is
assumed
to
face
an
upward
sloping
curve
for
a
particular
vehicle
class.
The
Generalized
Leontief
profit
function
is
used
to
OMB
Review
Draft
December
17,
2003
A­
2
Table
A­
1.
Retail
Prices
and
Own­
Price
Elasticities
of
Demand
by
Vehicle
Class
Vehicle
Class
Average
Retail
Pricea
Elasticityb
Subcompact
$
15,522
 
3.286
Compact
$
16,487
 
3.419
Intermediate
$
21,155
 
4.179
Standard
 
4.712
Luxury
$
33,587
 
1.912
Sports
$
25,797
 
1.065
Pick­
up
$
22,126
 
3.526
SUV
$
27,694
Van
$
22,910
 
4.363
Other
 
4.088
a
Includes
the
MSRP
and
destination
price
reported
by
the
Automotive
News
Market
Data
Book
(
Crain,
2000;
p:
75).
Prices
current
as
of
April
2000
and
were
considered
representative
of
1999
prices.

b
Goldberg,
Pinelopi
K.
1995.
"
Product
Differentiation
and
Oligopoly
in
International
Markets:
The
Case
of
the
U.
S.
Automobile
Industry."
Econometrica
63(
4):
891­
951,
Table
II.

(
A.
2)
characterize
the
facility
supply
function
under
perfect
competition.
Under
this
assumption,
the
supply
function
for
facility
j
for
producing
vehicles
of
class
i
would
take
the
form:

where
pi
is
the
average
price
for
vehicle
class
i,
and
(
ij
and
$
ij
are
model
parameters.
The
theoretical
restrictions
on
the
model
parameters
that
ensure
upward­
sloping
supply
curves
are
(
ij
$
0
and
$
ij
<
0.
Figure
A­
1
illustrates
the
theoretical
supply
function
represented
by
Eq.
(
A.
2).
As
shown,
the
upward­
sloping
supply
curve
is
specified
over
a
productive
range
with
a
lower
bound
of
zero
that
corresponds
with
a
shutdown
price
equal
to
and
an
upper
bound
given
by
the
production
capacity
of
qj
M
that
is
approximated
by
the
supply
parameter
(
ij.
The
curvature
of
the
supply
function
is
determined
by
the
$
ij
parameter.
OMB
Review
Draft
December
17,
2003
A­
3
$

p*

q
q
*

j
 
j
=
q
Mj
4 
j
2
 
2i
Figure
A­
1.
Facility­
Level
Marginal
Cost
Function
(
A.
3)

(
A.
4)
The
$
parameter
is
related
to
the
facility's
supply
elasticity
which
can
be
expressed
as:

Taking
the
derivative
of
the
facility
supply
function
(
equation
A­
2)
with
respect
to
price
and
multiplying
this
expression
by
pi/
qij
results
in
the
following
expression
for
the
supply
elasticity:

By
rearranging
terms,
$
can
be
expressed
as
follows:
OMB
Review
Draft
December
17,
2003
3The
calibration
method
is
modified
for
the
basic
oligopoly
model
described
in
Section
A.
3
where
the
marginal
revenue
term
in
Eq.
A.
8
is
substituted
for
pi.

A­
4
(
A.
5)

Under
perfect
competition,
3
EPA
estimated
the
$
parameter
by
substituting
an
assumed
supply
elasticity
for
the
vehicle
class
(>
ij),
the
baseline
production
level
by
facility
j
of
vehicle
class
i
(
qij),
and
the
average
market
price
for
the
vehicle
class
(
pi).
EPA
assumed
that
a
facility's
ability
to
respond
to
small
price
changes
depends
on
its
current
capacity
utilization
rate,
as
outlined
in
Table
A­
2.
The
remaining
supply
function
parameter,
(
ij,
does
not
influence
the
facility's
production
responsiveness
to
price
changes
as
does
the
$

parameter.
Thus,
the
parameter
(
j
is
used
to
calibrate
the
model
so
that
each
facility's
supply
equation
replicates
the
baseline
production
data.

Table
A­
2.
Supply
Elasticity
Assumptions
Capacity
Utilization
Rate
(
R)
Supply
Elasticity
(>)

R
>
1
0.10
0.9
<
R
<
1
0.50
R
<
0.9
1.00
A.
3
Baseline
Equilibrium
The
facility's
optimization
problem
with
respect
to
vehicle
class
i
is
then
given
by:

max
Ai,
j
=
P(
Qi)*
qi,
j
 
C(
qi,
j)
(
A.
6)

where
Qi
is
the
total
number
of
vehicles
of
class
i
available
in
the
market,
and
P(
Qi)
is
the
average
price
in
this
vehicle
category.
In
the
short­
run,
a
facility
owner
will
be
willing
to
supply
vehicles
at
a
markup
over
marginal
cost
as
long
as
the
market
price
is
high
enough
to
cover
average
variable
costs.
If
revenue
falls
below
average
variable
costs,
then
the
facility's
best
response
is
to
shut
down
production
because
total
revenue
does
not
cover
total
variable
costs
of
production.
In
this
scenario,
producers
lose
money
on
operations
as
well
as
capital.
OMB
Review
Draft
December
17,
2003
A­
5
By
shutting
down,
the
facility
avoids
additional
losses
from
operations.
The
sufficient
condition
for
production
at
facility
j
is
non­
negative
profits
(
Aj):

Aj
=
TRj
 
TCj
$
0
(
A.
7)

where
TRj
is
the
total
revenue
earned
from
the
sale
of
all
vehicles
assembled
at
facility
j
and
TCj
is
the
sum
of
the
variable
production
costs
(
production
and
compliance)
and
total
avoidable
fixed
costs
(
annualized
expenditure
for
compliance
capital)
incurred
by
facility
j
for
all
vehicles
that
it
produces.
The
underlying
assumption
is
that
if
a
facility
produces
multiple
models,
these
models
share
some
fixed
costs
that
cannot
be
separated.
Thus
the
facility
need
not
shut
down
if
one
product
line
is
unprofitable.
It
will
only
shut
down
if
the
aggregate
profits
from
all
models
are
negative
on
balance.

To
model
each
vehicle
category
as
a
concentrated
market,
we
have
used
a
Cournot
model
in
which
facilities
exercise
some
control
over
the
wholesale
price
of
the
vehicle.
In
these
noncompetitive
models,
each
supplier
recognizes
its
influence
over
the
market
price
and
chooses
a
level
of
output
that
maximizes
its
profits,
given
the
output
decisions
of
the
others.
Employing
a
Cournot
model
assumes
that
suppliers
do
not
cooperate.
Instead,
each
supplier
evaluates
the
effect
of
its
output
choice
on
price
and
does
the
best
it
can
given
the
output
decision
of
its
competitors.
Thus,
given
any
output
level
chosen
by
other
suppliers
there
will
be
a
unique
optimal
output
choice
for
a
particular
supplier.

The
basic
oligopoly
model
we
consider
is
the
"
Many
Firm
Cournot
Equilibrium"
described
in
Varian
(
1993,
page
290).
As
is
the
case
in
all
imperfectly
competitive
models
of
profit­
maximizing
behavior,
each
oligopolist
chooses
an
output
level
where
marginal
revenue
equals
marginal
cost.
In
the
Cournot
model,
marginal
revenue
is
a
fraction,
Zi,
j,
of
the
market
price:
Zi,
j
=
(
1
+
si,
j/,
i),
where
si,
j
=
qi,
j/
Qi.
If
we
optimize
Eq.
(
A.
7)
with
respect
to
qi,
j
we
can
derive
the
following
first­
order
condition:

P(
Qi)°(
1
+
sij/,
i)
=
MCij.
(
A.
8)

If
facility
j's
market
share
of
vehicle
category
i
(
sij)
is
1,
the
demand
curve
facing
it
is
the
market
demand
curve.
In
that
case,
Eq.
(
A.
8)
reduces
to
the
profit
maximization
condition
facing
a
monopolist
where
marginal
revenue
equals
marginal
cost,
and
the
marginal
revenue
is
only
a
function
of
the
demand
elasticity.
On
the
other
extreme,
if
the
producer
is
a
very
small
part
of
a
large
market,
its
market
share
is
near
zero,
and
Eq.
(
A.
8)
reduces
to
the
profit
maximization
condition
under
perfect
competition:
price
equals
marginal
cost.
OMB
Review
Draft
December
17,
2003
A­
6
P0
P
Q0
Q
D
MR
MC0
Figure
A­
2.
Baseline
Equilibrium
Using
data
on
the
approximated
market
price
of
vehicle
by
type
(
P(
Qi)),
total
quantity
produced
for
the
domestic
market
(
Qi),
the
amount
produced
by
each
affected
facility
(
qij),
and
the
price
elasticity
of
demand
(,
i,)
for
vehicle
class
i,
the
baseline
equilibrium
can
be
established
as
depicted
in
Figure
A­
2.
For
each
of
the
affected
facilities,
the
baseline
automobile
production
quantities
are
provided
in
Tables
2­
11
and
2­
12
of
Section
2.
Some
facilities
produce
vehicles
in
more
than
one
market
segment.
In
these
cases,
the
Agency
treated
each
market
segment
for
a
facility
as
a
separate
product
line
thus,
a
facility
may
have
multiple
product
lines
for
the
purposes
of
the
economic
impacts
model.
OMB
Review
Draft
December
17,
2003
4The
variable
compliance
costs
per
vehicle
were
calculated
given
the
annual
production
per
facility
and
the
variable
cost
component
of
the
total
compliance
cost
estimate
for
each
facility.
These
latter
cost
estimates
were
provided
by
the
engineering
analysis
and
include
annual
operating
and
maintenance
costs
and
monitoring
and
record
keeping
costs.

A­
7
(
A.
9)
A.
4
With­
Regulation
Market
Equilibrium
The
production
decision
at
assembly
facility
j
is
affected
by
the
variable
compliance
costs,
ci,
j,
which
are
expressed
in
dollars
per
vehicle.
4
Each
marginal
cost
equation
is
directly
affected
by
the
regulatory
control
costs.
Dropping
subscripts
henceforth
for
convenience,
the
profit
maximizing
solution
for
each
existing
facility
becomes:

Incorporating
the
regulatory
control
costs
(
c)
will
involve
shifting
the
marginal
cost
curve
upward
for
each
regulated
facility
by
the
per­
unit
variable
compliance
cost,
as
shown
in
Figure
A­
3.
The
marginal
cost
of
the
affected
facilities
shifts
upward,
causing
the
market
cost
curve
to
shift
upward
to
MC1.
At
the
new
with­
regulation
equilibrium,
the
market
price
increases
from
P0
to
P1
and
market
output
(
as
determined
from
the
market
demand
curve,
DM)
declines
from
Q0
to
Q1.

Facility
responses
and
market
adjustments
can
be
conceptualized
as
an
interactive
feedback
process.
Facilities
face
increased
production
costs
due
to
compliance,
which
causes
facility­
specific
production
responses
(
i.
e.,
output
reduction).
The
cumulative
effect
of
these
responses
leads
to
an
increase
in
the
market
price
that
all
producers
and
consumers
face.
This
increase
leads
to
further
responses
by
all
producers
and
consumers
and,
thus,
new
market
prices.
The
new
with­
regulation
equilibrium
is
the
result
of
a
series
of
these
iterations
between
producer
and
consumer
responses
and
market
adjustments
until
a
stable
market
price
equilibrium
is
reached
where
total
market
supply
equals
total
market
demand.
A
spreadsheet
nonlinear
solution
algorithm
was
used
to
compute
the
with­
regulation
equilibrium
price
and
quantities
in
each
market.

A.
5
Impact
on
Foreign
Trade
The
final
coating
regulation
will
only
be
binding
on
facilities
that
assemble
vehicles
in
the
United
States.
The
consequent
change
in
relative
prices
of
domestic
versus
foreign
OMB
Review
Draft
December
17,
2003
5Vehicle
classes
are
aggregated
in
the
foreign
trade
section
because
of
data
limitations.

A­
8
P0
P
Q0
Q
D
MR
Q1
P1
MC1
MC0
Figure
A­
3.
With­
Regulation
Equilibrium
vehicles
has
two
impacts
on
foreign
trade.
Foreign
imports
become
more
attractive
to
U.
S.
consumers
and
U.
S.
exports
become
less
attractive
to
foreign
consumers.
The
Agency
has
used
available
data
to
estimate
the
magnitude
of
these
impacts
as
described
below.

A.
5.1
U.
S.
Imports
The
final
regulation
may
lead
to
an
increase
in
the
price
of
domestic
vehicles,
which,
in
turn,
could
potentially
trigger
an
increase
in
demand
by
U.
S.
consumers
for
substitutes
such
as
unregulated,
imported
vehicles.
To
estimate
this
spillover
effect,
EPA
assumed
domestic
and
foreign
vehicles
are
imperfect
substitutes
that
are
differentiated
by
their
country
of
origin
(
commonly
referred
to
as
the
Armington
assumption).
The
conceptual
approach
for
estimating
spillover
effects
using
Armington
elasticities
is
described
in
Gallaway,
McDaniel,
and
Rivera
(
2000).
From
an
economy­
wide
perspective,
a
representative
consumer
maximizes
his
utility
for
"
composite"
vehicles
(
V)
by
allocating
expenditures
between
domestic
(
D)
and
imported
vehicles
(
M),
taking
relative
prices
as
given.
5
The
Armington
specification
assumes
a
constant
elasticity
of
substitution
(
CES)
utility
function
of
the
form:

V
=
"
[*
M
(
F­
1)/
F
+
(
1­*)
D
(
F­
1)/
F]
F/(
F­
1)
(
A.
10)
OMB
Review
Draft
December
17,
2003
A­
9
where
F
is
the
Armington
elasticity
of
substitution
between
domestic
and
imported
vehicles,
and
"
and
*
are
calibrated
parameters
of
the
demand
function.
Utility
maximization
subject
to
the
budget
constraint
leads
to
the
following
first
order
condition:

M/
D
=
[(*/(
1­*))
*
(
PD/
PM)]
F
(
A.
11)

Thus,
the
ratio
between
imported
and
domestic
vehicles
is
a
function
of
their
relative
prices
and
the
elasticity
of
substitution.
Gallaway,
McDaniel,
and
Rivera
(
2000)
use
monthly
data
from
1989
through
1997
to
estimate
Armington
elasticities
for
several
manufacturing
industries.
For
SIC
3714,
motor
vehicle
parts
and
accessories,
they
estimate
a
value
of
2.07.
Additional
substitution
elasticity
estimates
for
motor
vehicles
are
reported
in
Ho
and
Jorgenson
(
1998)
and
range
from
1.52
to
3.59.
The
Agency
has
used
all
three
estimates
to
compute
low
and
high
end
estimates
of
the
change
in
import­
to­
domestic
vehicles
ratio
for
a
given
change
in
the
price
of
domestic
cars.

A.
5.2
U.
S.
Exports
Exports
of
U.
S.­
made
vehicles
can
also
fall
if
their
own­
price
increases
due
to
the
final
regulation.
While
U.
S.
exports
of
passenger
cars
in
this
industry
are
only
one­
fourth
the
level
of
imports,
they
still
represent
about
18
percent
of
domestic
production
in
1997
and
are
growing
(
AAMA,
1998).
Unfortunately,
data
were
lacking
connecting
specific
facilities
to
specific
markets.
Thus,
foreign
demand
for
U.
S.­
made
vehicles
is
modeled
by
one
representative
foreign
consumer
using
the
following
constant
elasticity
demand
function:

qx
=
Bx[
p],
x
(
A.
12)

where
p
is
the
average
price
of
exported
U.
S.
vehicles,
,
x
is
the
export
demand
elasticity,
and
Bx
is
a
multiplicative
demand
parameter
that
calibrates
the
foreign
demand
equation,
given
data
on
price
and
foreign
demand
elasticity
to
replicate
the
observed
baseline
year
1999
level
of
exports.
Ho
and
Jorgenson
(
1998)
report
export
demand
elasticities
for
motor
vehicles.
These
estimates
range
from
 
0.9
to
 
1.55.
These
export
demand
elasticity
estimates
are
used
along
with
our
estimates
of
change
in
the
average
price
of
U.
S.
vehicles
to
forecast
the
corresponding
change
in
quantity
demanded
by
foreign
consumers.
OMB
Review
Draft
December
17,
2003
Appendix
B
Estimating
Social
Costs
Under
Imperfect
Competition
OMB
Review
Draft
December
17,
2003
6The
Agency
has
developed
this
conceptual
approach
in
a
previous
economic
analysis
of
regulations
affecting
the
pharmaceutical
industry
(
EPA,
1996).
For
simplicity,
this
appendix
assumes
constant
marginal
costs.
The
marginal
cost
curves
developed
for
the
economic
model
are
upward
sloping
curves
.

7Fixed
control
costs
are
ignored
in
this
example
but
are
included
in
the
analysis.

B­
1
B.
1
Social
Cost
Effects
Under
Imperfect
Competition6
The
conceptual
framework
for
evaluating
social
costs
and
distributive
impacts
in
an
imperfectly
competitive
market
model
is
illustrated
in
Figure
B­
1.
The
baseline
equilibrium
is
given
by
the
price,
P0,
and
the
quantity,
Q0.
In
a
pure
monopoly
situation,
the
baseline
equilibrium
is
determined
by
the
intersection
of
the
marginal
revenue
curve
(
MR)
and
the
MC
curve.
In
imperfect
competition,
such
as
in
the
Cournot
model
used
in
this
analysis,
the
baseline
equilibrium
is
determined
by
the
intersection
of
MC
with
some
fraction
of
MR.
Without
the
regulation,
the
total
benefits
of
consuming
automobiles
is
given
by
the
area
under
the
demand
curve
up
to
Q0.
This
equals
the
area
filled
by
the
letters
ABCDEFGHIJ.
The
total
variable
cost
to
society
of
producing
Q0
equals
the
area
under
the
original
MC
function,
given
by
IJ.
Thus,
the
total
social
surplus
to
society
from
the
production
and
consumption
of
output
level
Q0
equals
the
total
benefits
minus
the
total
costs,
or
the
area
filled
by
the
letters
ABCDEFGH.

The
total
social
surplus
value
can
be
divided
into
producer
surplus
and
consumer
surplus.
Producer
surplus
accrues
to
the
suppliers
of
the
product
and
reflects
the
value
they
receive
in
the
market
for
the
Q0
units
of
output
less
what
it
costs
to
produce
this
amount.
The
market
value
of
the
product
is
given
by
the
area
DEFGHIJ
in
Figure
B­
1.
Since
production
costs
IJ,
producer
surplus
is
given
by
area
DEFGH.
Consumer
surplus
accrues
to
the
consumers
of
the
product
and
reflects
the
value
they
place
on
consumption
(
the
total
benefits
of
consumption)
less
what
they
must
pay
on
the
market.
Consumer
surplus
is
thereby
given
by
the
area
ABC.

The
with­
regulation
equilibrium
is
P1,
Q1.
Total
benefits
of
consumption
are
ABDFI
and
the
total
variable
costs
of
production
are
FI,
yielding
a
with­
regulation
social
surplus
of
ABD.
7
Area
BD
represents
the
new
producer
surplus
and
A
is
the
new
consumer
surplus.
The
social
cost
of
the
regulation
equals
the
total
change
in
social
surplus
caused
by
the
regulation.
Thus,
the
social
cost
is
represented
by
the
area
FGHEC
in
Figure
B­
1.
OMB
Review
Draft
December
17,
2003
B­
2
$

P
1
P
0
P
1
C
P0
C
Q
1
Q
0
Output
MC
+
Control
Costs
MC
D
MR
A
B
C
D
E
F
G
H
I
J
Figure
B­
1.
Economic
Welfare
Changes
with
Regulation:
Imperfect
Competition
The
distributive
effects
are
estimated
by
separating
the
social
cost
into
producer
surplus
and
consumer
surplus
losses.
First,
the
change
in
producer
surplus
is
given
by
)
PS
=
B
 
F
 
(
G+
H+
E)
(
B.
1)

Producers
gain
B
from
the
increase
in
price,
but
lose
F
from
the
increase
in
production
costs
due
to
regulatory
control
costs.
Furthermore,
the
contraction
of
output
leads
to
foregone
baseline
profits
of
G+
H+
E.

The
change
in
consumer
surplus
is
)
CS
=
 
(
B
+
C)
(
B.
2)

This
reflects
the
fact
that
consumer
surplus
shrinks
from
the
without­
regulation
value
of
ABC
to
the
with­
regulation
value
of
A.

The
social
cost
or
total
change
in
social
surplus
shown
earlier
can
then
be
derived
simply
by
adding
the
changes
in
producer
and
consumer
surplus
together
OMB
Review
Draft
December
17,
2003
B­
3
)
SC
=
)
PS
+
)
CS
=
 
(
F+
G
+
H
+
E
+
C)
(
B.
3)

B.
3
Comparison
of
Social
Cost
with
Control
Cost
It
is
important
to
compare
this
estimate
of
social
costs
to
the
initial
estimate
of
baseline
control
costs
and
explain
the
difference
between
the
two
numbers.
The
baseline
control
cost
estimate
is
given
by
the
area
FGH,
which
is
simply
the
constant
cost
per
unit
times
the
baseline
output
level.
In
the
case
of
imperfect
competition,
the
social
cost
estimate
exceeds
the
baseline
control
cost
estimate
by
the
area
EC.
In
other
words,
the
baseline
control
cost
estimate
understates
the
social
costs
of
the
regulation.
A
comparison
with
the
outcome
under
perfect
competition
helps
illustrate
the
relationship
between
control
cost
and
total
social
cost.

Suppose
that
the
MR
curve
in
Figure
B­
1
were
the
demand
function
for
a
competitive
market,
rather
than
the
marginal
revenue
function
for
a
monopolistic
producer.
Similarly,
let
the
MC
function
be
the
aggregate
supply
function
for
all
producers
in
the
market.
The
market
equilibrium
is
still
determined
at
the
intersection
of
MC
and
MR,
but
given
our
revised
interpretation
of
MR
as
the
competitive
demand
function,
the
without­
regulation
(
competitive)
market
price,
P0
C,
equals
MC
and
Q0
is
now
interpreted
as
the
competitive
level
of
product
demand.
In
this
type
of
market
structure,
all
social
surplus
goes
to
the
consumer.
This
is
because
producers
receive
a
price
that
just
covers
their
costs
of
production.

In
the
with­
regulation
perfectly
competitive
equilibrium,
price
would
rise
by
the
perunit
control
cost
amount
to
P1
c.
Now
the
social
cost
of
the
regulation
is
given
entirely
by
the
loss
in
consumer
surplus,
area
FG.
As
this
is
compared
to
the
initial
estimate
of
regulatory
control
costs,
FGH,
the
control
cost
estimate
overstates
the
social
cost
of
the
regulation.
The
overstatement
is
due
to
the
fact
that
the
baseline
control
cost
estimates
are
calibrated
to
baseline
output
levels.
With
regulation,
output
is
projected
at
Q1,
so
that
control
costs
are
given
by
area
F.
Area
G
represents
a
monetary
value
from
lost
consumer
utility
due
to
the
reduced
consumption,
also
referred
to
as
deadweight
loss
(
analogous
to
area
C
under
the
monopolistic
competition
scenario).

Social
cost
effects
are
larger
with
monopolistic
market
structures
because
the
regulation
already
exacerbates
a
social
inefficiency
(
Baumol
and
Oates,
1988).
The
inefficiency
relates
to
the
fact
that
the
market
produces
too
little
output
from
a
social
welfare
perspective.
In
the
monopolistic
equilibrium,
the
marginal
value
society
(
consumers)
places
on
the
product,
the
market
price,
exceeds
the
marginal
cost
to
society
(
producers)
of
OMB
Review
Draft
December
17,
2003
B­
4
producing
the
product.
Thus,
social
welfare
would
be
improved
by
increasing
the
quantity
of
the
good
provided.
However,
the
producer
has
no
incentive
to
do
this
because
the
marginal
revenue
effects
of
lowering
the
price
and
increasing
quantity
demanded
is
lower
than
the
marginal
cost
of
the
extra
units.
OMB
explicitly
mentions
the
need
to
consider
these
market
power­
related
welfare
costs
in
evaluating
regulations
under
Executive
Order
12866
(
OMB,
1996).
OMB
Review
Draft
December
17,
2003
TECHNICAL
REPORT
DATA
(
Please
read
Instructions
on
reverse
before
completing)

1.
REPORT
NO.

EPA­
452/
R­
???
2.
3.
RECIPIENT'S
ACCESSION
NO.

4.
TITLE
AND
SUBTITLE
Regulatory
Impact
Analysis
for
the
final
Automobile
and
Light
Duty
Truck
Coating
NESHAP
5.
REPORT
DATE
December
2003
6.
PERFORMING
ORGANIZATION
CODE
7.
AUTHOR(
S)
8.
PERFORMING
ORGANIZATION
REPORT
NO.

9.
PERFORMING
ORGANIZATION
NAME
AND
ADDRESS
U.
S.
Environmental
Protection
Agency
Office
of
Air
Quality
Planning
and
Standards
Research
Triangle
Park,
NC
27711
10.
PROGRAM
ELEMENT
NO.

11.
CONTRACT/
GRANT
NO.

None
12.
SPONSORING
AGENCY
NAME
AND
ADDRESS
Director
Office
of
Air
Quality
Planning
and
Standards
Office
of
Air
and
Radiation
U.
S.
Environmental
Protection
Agency
Research
Triangle
Park,
NC
27711
13.
TYPE
OF
REPORT
AND
PERIOD
COVERED
Final
regulation
14.
SPONSORING
AGENCY
CODE
EPA/
200/
04
15.
SUPPLEMENTARY
NOTES
16.
ABSTRACT
Pursuant
to
Section
112
of
the
Clean
Air
Act,
the
U.
S.
Environmental
Protection
Agency
(
EPA)
has
developed
National
Emissions
Standards
for
Hazardous
Air
Pollutants
(
NESHAP)
to
control
emissions
released
from
the
coating
of
automobiles
and
light­
duty
trucks
(
LDT).
The
purpose
of
this
rule
is
to
reduce
the
flow
of
HAPs
from
potential
emission
points
within
auto
and
LDT
facilities.
Eighty
percent
of
the
HAPs
released
are
xylene,
glycol
ethers
(
EGBE),
MIBK,
and
toluene.
The
other
HAPs
include
methanol,
glycol
ethers,
MEK,
formaldehyde,
and
ethyl
benzene.
The
facilities
in
the
auto
and
LDT
source
category
are
controlling
HAP
emissions
from
their
coatings
operations,
as
required,
to
meet
maximum
achievable
control
technology
(
MACT)
standards.
As
of
1999,
there
were
65
auto
and
LDT
assembly
facilities
owned
by
14
companies.
The
estimated
total
annual
cost
for
these
facilities
to
comply
with
the
final
MACT
standard
is
approximately
$
154
million.
Due
to
the
total
annual
cost
of
compliance,
an
economic
impact
model
estimates
that
production
of
autos
and
LDT
declines
by
0
to
0.02
percent
across
various
vehicle
classes.
The
estimated
price
increase
due
to
the
regulation
is
less
than
0.01
percent.
Pre­
tax
earnings
for
the
companies
owning
the
facilities
in
this
source
category
decline
by
about
1.08
percent
according
to
the
economic
model
developed
in
the
regulatory
impact
analysis.
According
to
the
Small
Business
Administration
size
standards,
none
of
these
businesses
are
considered
small.
Based
on
the
economic
impact
analysis,
impacts
of
the
NESHAP
on
companies
owning
auto
and
LDT
assembly
facilities
are
anticipated
to
be
negligible.

17.
KEY
WORDS
AND
DOCUMENT
ANALYSIS
a.
DESCRIPTORS
b.
IDENTIFIERS/
OPEN
ENDED
TERMS
c.
COSATI
Field/
Group
air
pollution
control,
environmental
regulation,
economic
impact
analysis,
maximum
achievable
control
technology,
automobile
and
light
duty
truck
18.
DISTRIBUTION
STATEMENT
Release
Unlimited
19.
SECURITY
CLASS
(
Report)

Unclassified
21.
NO.
OF
PAGES
131
20.
SECURITY
CLASS
(
Page)

Unclassified
22.
PRICE
EPA
Form
2220­
1
(
Rev.
4­
77)
PREVIOUS
EDITION
IS
OBSOLETE
