Document ID: EPA-HQ-OW-2002-0049-0273
Agency: epa
Document Type: Supporting & Related Material
Title: 
Posted Date: 2003-03-19T05:00Z

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Commercial
fisheries
can
be
adversely
impacted
by
Impingement
and
Entrainment
(
I&
E)
and
many
other
stressors.
Because
commercially
landed
fish
are
exchanged
in
markets
with
observable
prices
and
quantities,
it
may
seem
as
if
estimating
the
economic
value
of
losses
due
to
I&
E
(
or
the
economic
value
of
the
benefits
of
reducing
I&
E)
would
be
relatively
straightforward.
However,
there
are
many
complicating
conceptual
and
empirical
issues
that
pose
significant
challenges
to
estimating
the
change
in
economic
surplus
from
changes
in
the
number
of
commercially
targeted
fish.

This
chapter
provides
an
overview
of
these
issues,
and
indicates
how
EPA
is
considering
methods
for
estimating
the
change
in
commercial
fisheries­
related
economic
surplus
associated
with
the
§
316(
b)
regulation.
This
chapter
includes
a
review
of
the
concept
of
economic
surplus,
and
describes
the
theory
and
empirical
evidence
on
how
readily
observable
dockside
prices
and
quantities
may
relate
to
the
economic
welfare
measures
of
producer
and
consumer
surplus
that
are
suitable
for
a
benefit­
cost
assessment.
This
chapter
also
provides
an
overview
of
the
commercial
fishery
sector,
including
an
assessment
of
several
relevant
fishery
stocks,
trends
and
patterns
of
how
the
commercial
fishing
sector
operates,
and
issues
of
commercial
fisheries
management
and
how
they
affect
the
analysis
of
economic
welfare
measures.

	


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In
estimating
the
effects
of
increased
fish
populations
as
a
result
of
reduced
I&
E
losses,
it
is
important
to
understand
who
is
affected.
First
and
foremost,
there
are
the
commercial
watermen,
the
individuals
engaged
in
fish
harvesting.
These
watermen
typically
haul
their
catch
to
established
dockside
wholesale
markets,
where
they
sell
their
catch
to
processors
or
wholesalers.
Processors
package
or
can
the
fish
so
that
they
can
be
sold
as
food
products
for
people,
or
as
pet
and
animal
feed,
or
as
oils
and
meals
for
various
other
uses.
Wholesalers
often
resell
fish
to
retailers
(
e.
g.,
grocery
stores),
restaurants,
or
final
consumers
(
households).

The
market
and
welfare
impacts
of
a
change
in
commercial
fishery
harvests
can
be
traced
through
a
series
of
economic
agents
 
individuals
and
businesses
 
that
are
linked
together
through
a
series
of
"
tiered
markets."
Through
these
economic
relationships
between
the
various
levels
of
buyers
and
sellers,
the
final
value
of
the
fish
product
(
e.
g.,
a
family
dinner)
creates
economic
signals
(
e.
g.,
prices)
that
carry
back
through
the
various
intermediate
parties
to
the
watermen
who
actually
engage
in
the
harvest.
Additionally,
beneficial
changes
in
the
commercial
fishery
may
encourage
watermen
to
purchase
more
fishing
gear,
fuel,
and
vessel
repairs,
which
will
benefit
suppliers
(
the
businesses
that
supply
these
goods
and
services),
although
such
purchases
from
input
suppliers
would
not
typically
be
estimated
as
part
of
benefits.


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A13­
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A13­
A13­
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A13­
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A13­
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12
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A13­

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)

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Commercial
watermen
include
the
individuals
supplying
the
labor
and/
or
capital
(
e.
g.,
fishing
vessels)
engaged
in
the
harvesting
of
fish.
These
watermen
typically
haul
their
catch
to
established
dockside
wholesale
markets,
where
they
sell
their
catch
to
processors
or
wholesalers.
The
transactions
between
the
watermen
and
these
intermediate
buyers
provide
observable
market
quantities
and
prices
of
dockside
landings,
and
it
is
these
data
that
serve
as
a
starting
point
for
estimating
changes
in
economic
surplus.

Commercial
fishing
is
often
a
demanding
and
risky
occupation.
However,
commercial
anglers
often
find
great
satisfaction
in
their
jobs
and
lifestyles.
Additional
detail
on
the
economic
and
noneconomic
aspects
of
commercial
fishing
are
provided
in
several
of
the
sections
that
follow,
including
a
discussion
of
the
nonmonetary
benefits
of
commercial
fishing
(
Section
A13­
10).

	


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Dockside
transactions
typically
involve
buyers
for
whom
the
fish
are
an
input
to
their
production
or
economic
activity.
For
example,
processors
convert
raw
fish
into
various
types
of
final
or
intermediate
products,
which
they
then
sell
to
other
entities
(
e.
g.,
retailers
of
canned
or
frozen
fish
products,
or
commercial
or
industrial
entities
that
rely
on
fish
oil
as
a
production
input).
Wholesalers
may
serve
as
middlemen
between
the
watermen
who
harvest
the
fish
and
those
who
will
use
the
fish
as
production
inputs
or
to
retail
vendors
(
e.
g.,
supermarkets).
Depending
on
the
market
and
the
type
of
fish,
there
may
be
numerous
economic
actors
and
layers
between
the
commercial
watermen
who
caught
the
fish
and
the
final
consumer
who
eats
or
otherwise
uses
the
fish
product.

	


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After
passing
through
perhaps
several
intermediate
buyers
and
sellers,
the
fish
(
or
fish
products)
ultimately
end
up
with
a
final
consumer
(
typically
a
household).
This
final
consumption
may
take
the
form
of
a
fish
dinner
prepared
at
home
or
purchased
in
a
restaurant.
Final
consumption
may
also
be
in
the
form
of
food
products
served
to
household
pets,
or
as
part
of
a
nonfood
product
that
relies
on
fish
parts
or
oils
as
an
input
to
production.

	


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Transactions
in
the
fishery
sector
are
often
affected
by
various
levels
of
fishery
management
regulations.
Nearshore
fishing
(
ocean
and
estuary
fishing
less
than
3
miles
from
shore)
and
Great
Lakes
fishing
are
primarily
regulated
by
state,
interstate,
and
tribal
entities.
The
content
and
relative
strength
of
state
laws
affecting
ocean
fishing
vary
from
state
to
state.

The
regulated
nature
of
many
fisheries
affects
the
manner
in
which
the
impacts
and
economic
benefits
of
the
§
316(
b)
regulation
should
be
evaluated.
For
example,
if
the
impacted
fisheries
were
perfectly
competitive
with
open
access
(
i.
e.,
no
property
rights
or
fishery
regulations),
then
all
economic
rents,
surplus,
and
profits
associated
with
the
resource
would
be
driven
to
zero
at
the
margin.
However,
where
fisheries
are
regulated
or
in
other
ways
depart
from
the
neoclassical
assumptions
of
perfectly
competitive
markets,
there
are
rents
and
surplus
that
will
be
affected
by
changes
in
I&
E.
These
economic
considerations
are
addressed
later
in
this
chapter.

The
primary
federal
laws
affecting
commercial
fishing
in
U.
S.
ocean
territory
are
the
Magnuson
Fishery
Conservation
and
Management
Act
of
1976
and
the
Sustainable
Fisheries
Act
(
SFA)
of
1996
(
the
SFA
amended
the
1976
act
and
renamed
it
the
Magnuson­
Stevens
Fishery
Conservation
and
Management
Act).
The
purpose
of
the
1976
act
was
to
establish
a
U.
S.
exclusive
economic
zone
that
ranges
from
3
to
200
miles
offshore,
and
to
create
eight
regional
fishery
councils
to
manage
the
living
marine
resources
within
that
area.
These
councils
comprised
"
commercial
and
recreational
fishermen,
marine
scientists
and
state
and
federal
fisheries
managers,
who
combine
their
knowledge
to
prepare
Fishery
Management
Plans
(
FMPs)
for
stocks
of
finfish,
shellfish
and
crustaceans.
In
developing
these
FMPs
the
Councils
use
the
most
recent
scientific
assessments
of
the
ecosystems
involved
with
special
consideration
of
the
requirements
of
marine
mammals,
sea
turtles
and
other
protected
resources"
(
NMFS,
2002a).
The
SFA
amended
the
law
to
include
numerous
provisions
requiring
science,
management,
and
conservation
action
by
the
National
Marine
Fisheries
Service
(
NMFS)
(
NMFS,
2002b).

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

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



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

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


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

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
 
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$




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




The
eight
fishery
management
councils
created
by
the
1976
act
have
regulatory
authority
within
the
eight
regions.
They
receive
technical
and
scientific
support
from
the
National
Oceanic
and
Atmospheric
Administration
(
NOAA),
NMFS
Fisheries
Science
Centers,
which
are
organized
into
the
following
regions:
Alaska,
Northeast,
Northwest,
Southeast,
and
Southwest.
Table
A13­
1
presents
how
the
regions
used
for
this
analysis
fit
into
the
fishery
management
council
regions
and
other
fishery
regions
defined
by
NMFS.

Table
A13­
1:
Regional
Designation
of
Fisheries
§
316(
b)
Phase
II
Region
States
NMFS
Science
Center
NMFS
Marine
Recreation
Region
NMFS
Commercial
Region
Fishery
Management
Council
(
FMC)
Large
Regions
Reported
in
Our
Living
Oceans
(
NMFS,
1999)

North
Atlantic
Maine,
New
Hampshire,
Massachusetts,
Connecticut,
Rhode
Island
Northeast
North
Atlantic
New
England
New
England
Northeast
Mid­
Atlantic
New
York,
New
Jersey,
Delaware,
Maryland,
District
of
Columbia,
Virginia
Northeast
Mid­
Atlantic
Chesapeake
Mid
Atlantic
Mid­
Atlantic
Northeast
South
Atlantic
North
Carolina,
South
Carolina,
Georgia,
Florida
(
Atlantic
Coast)
Southeast
South
Atlantic
South
Atlantic
South
Atlantic
(
NC
in
Mid­
Atlantic)
Southeast
Gulf
of
Mexico
Florida
(
Gulf
Coast),
Alabama,
Mississippi,
Louisiana,
Texas
Southeast
Gulf
of
Mexico
Gulf
Gulf
of
Mexico
Southeast
Northern
California
California,
north
of
San
Luis
Obispo/
Santa
Barbara
county
border
Southwest
Northern
California
Pacific
Coast
Pacific
Pacific
Coast
Southern
California
California,
south
of
San
Luis
Obispo/
Santa
Barbara
county
border
Southwest
Southern
California
California
Pacific
Pacific
Coast
Great
Lakes
Minnesota,
Wisconsin,
Illinois,
Indiana,
Michigan,
Ohio,
Pennsylvania,
New
York
Northeast
na
Great
Lakes
na
na
	


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
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



	
&



'
%




'
In
estimating
the
benefits
of
reducing
I&
E
losses,
it
is
important
to
understand
how
increased
fish
populations
may
affect
stocks
in
different
fisheries.
Where
stocks
are
thriving,
a
small
increase
in
the
number
of
individual
fish
affected
by
I&
E
may
not
be
noticed,
but
where
stocks
are
already
depleted
the
marginal
impact
of
a
small
increase
may
be
much
more
important.

Many
fisheries
in
the
United
States
tend
to
be
heavily
fished.
In
the
mid­
1900s,
many
U.
S.
fisheries
were
over­
fished,
some
to
the
point
of
near
collapse
(
NMFS,
1999,
2001;
BLS,
2002).
The
situation
currently
is
showing
some
improvement
slowly
because
of
recent
management
efforts
mandated
by
Magnuson­
Stevens
Act
and
other
regulations.
However,
many
of
the
current
restrictions
on
fishing
have
not
been
in
place
long
enough
to
have
a
dramatic
impact
on
fisheries.

Table
A13­
2
shows
the
utilization
rate
of
fisheries
in
the
United
States
by
region.
The
status
reported
is
obtained
from
Our
Living
Oceans
(
NMFS,
1999).
The
regions
for
which
fish
status
are
reported
in
NMFS
(
1999),
and
in
TableA13­
2,
are
larger
than
those
used
in
the
§
316(
b)
Phase
II
regional
analysis.
The
Northeast
region
comprises
both
the
North
Atlantic
and
the
Mid­
Atlantic
regions
for
the
analysis;
the
Southeast
region
in
the
report
includes
the
South
Atlantic
and
Gulf
of
Mexico
regions;
and
the
Pacific
Coast
region
includes
the
Northern
California
and
Southern
California
regions
as
well
as
Oregon
and
Washington.



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
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

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$


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"


1
RAY
is
measured
as
"
reported
fishery
landings
averaged
for
the
most
recent
3­
year
period
of
workable
data,
usually
1995­
1997"
(
NMFS,
1999,
p.
4).

2
LTPY
is
"
the
maximum
long­
term
average
catch
that
can
be
achieved
from
the
resource.
This
term
is
analogous
to
the
concept
of
maximum
sustainable
yield
(
MSY)
in
fisheries
science"
(
NMFS,
1999,
p.
5).
LTPY
may
not
be
the
yield
that
maximizes
surplus
rents.

3
Of
the
550
total
in­
scope
Phase
II
facilities,
fewer
than
1%
are
located
in
the
Alaska
and
Western
Pacific
regions:
1
is
located
in
Alaska,
3
are
in
Hawaii.

4
CPY
is
measured
as
"
the
potential
catch
that
can
be
taken
depending
on
the
current
stock
abundance
and
prevailing
ecosystem
considerations"
(
NMFS,
1999,
p.
4).






Table
A13­
2:
Utilization
of
U.
S.
Ocean
and
Nearshore
Fisheries
by
Region
in
1999
Our
Living
Oceans
Regiona
#
Fisheries
with
Known
Status
#
Fisheries
with
Unknown
Status
#
Under­
Utilized
#
Fully
Utilized
#
Over­
Utilized
Alaska
43
8
10
33
0
Northeast
55
15
4
15
36
Pacific
Coast
55
11
12
37
6
Southeast
34
35
2
15
17
Western
Pacific
20
7
8
9
3
Total
207
76
36
109
62
%
of
Total
Known
17%
53%
30%

Source:
NMFS,
1999
a
The
Northeast
region
includes
the
North
Atlantic
and
Mid­
Atlantic
regions;
the
Pacific
Coast
region
includes
the
Northern
and
Southern
California
regions,
as
well
as
Oregon
and
Washington;
the
Southeast
includes
the
South
Atlantic
and
Gulf
of
Mexico
regions.
The
Alaska
and
Western
Pacific
regions
are
not
included
in
the
Phase
II
CWIS
benefit­
cost
analysis,
but
are
included
here
for
comparison.

Based
on
the
NMFS
definitions,
a
fishery
is
considered
to
be
producing
at
a
less
than
optimal
level,
if
its
recent
average
yield
(
RAY)
1
is
less
than
the
estimated
long­
term
potential
yield
(
LTPY)
2.
This
can
occur
as
a
result
of
either
underutilization
of
the
fishery
or
collapse
of
the
fish
stock.
These
data
indicate
that
a
majority,
53%,
of
the
ocean
and
nearshore
fisheries
with
known
status
were
fully
utilized
in
1999.
Approximately
30%
of
these
fisheries
are
identified
as
over­
utilized.
For
more
than
a
third
of
the
fisheries,
the
status
is
unknown.

The
three
regions
most
affected
by
the
§
316(
b)
Phase
II
regulations3
 
Northeast,
Pacific
Coast,
and
Southeast
 
are
home
to
144
fisheries,
or
69%
of
the
total
fisheries
in
the
United
States.
Of
these,
83
had
known
status
in
1999;
a
greater
percent
of
fisheries
in
these
three
regions
are
of
"
known"
status
relative
to
the
status
of
all
fisheries.
A
higher
proportion,
40%,
of
the
fisheries
in
the
three
regions
of
interest
are
over­
utilized
compared
to
30%
for
the
United
States
as
a
whole.
In
addition,
a
higher
proportion
are
under­
utilized
(
35%
in
the
three
regions,
versus
17%
in
the
United
States).
The
Northeast
and
Southeast
both
have
high
rates
of
over­
fishing,
approximately
65%
and
50%,
respectively.
The
rate
of
over­
fishing
on
the
Pacific
Coast
is
much
lower,
with
just
over
10%
of
fisheries
listed
as
being
over­
utilized.

Table
A13­
3
shows
the
overall
production
of
U.
S.
fisheries
by
region.
In
total,
the
annual
RAY
has
been
over
12
million
metric
tons,
with
Alaska
and
the
Western
Pacific
providing
nearly
two
thirds
of
the
catch.
Because
of
under­
utilization
in
some
fisheries
and
over­
fishing
in
others,
the
total
RAY
in
the
United
States
is
only
60%
of
the
estimated
long­
term
potential
yield
(
LTPY).

The
three
regions
directly
affected
by
the
Phase
II
regulations
currently
produce
2.67
million
metric
tons
of
fish,
which
is
about
37%
of
the
U.
S.
total.
Within
these
regions,
fisheries
in
the
Southeast
tend
to
be
producing
closest
to
their
current
and
long­
term
potential.
The
RAY
in
the
Southeast
is
very
close
to
the
current
potential
yield
(
CPY),
4
and
is
closer
to
the

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

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


LTPY
than
any
other
region.
In
the
Northeast
region,
where
many
fisheries
are
over­
utilized,
and
in
the
Pacific
region,
where
many
fisheries
are
utilized
to
full
capacity,
the
RAY
is
less
than
60%
of
the
LTPY
and
only
about
70%
of
the
CPY.

Table
A13­
3:
Productivity
of
U.
S.
Regional
Fisheries
in
1999
(
million
metric
tons)

Our
Living
Oceans
Regionsa
Total
Longterm
Potential
Yield
(
LTPY)
Total
Current
Potential
Yield
(
CPY)
Total
Recent
Average
Yield
(
RAY)

CPY
%
of
LTPY
RAY
%
of
LTPY
%
of
CPY
Alaska
4.47
3.52
78.7%
2.51
56.1%
71.3%

Northeast
1.59
1.35
85.2%
0.89
55.7%
65.4%

Pacific
Coast
1.04
0.85
81.9%
0.62
59.7%
72.9%

Southeast
1.50
1.15
76.7%
1.16
76.8%
100.2%

Western
Pacific
3.44
3.44
100.1%
2.05
59.6%
59.6%

TOTAL
12.04
10.32
85.7%
7.22
60.0%
70.0%

Source:
NMFS,
1999
a
The
Northeast
region
includes
the
North
Atlantic
and
Mid­
Atlantic
regions;
the
Pacific
Coast
region
includes
the
Northern
and
Southern
California
regions,
as
well
as
Oregon
and
Washington;
the
Southeast
includes
the
South
Atlantic
and
Gulf
of
Mexico
regions.
The
Alaska
and
Western
Pacific
regions
are
not
included
in
the
Phase
II
CWIS
benefit­
cost
analysis,
but
are
included
here
for
comparison.

More
detailed
information
on
the
status
of
individual
species
affected
by
I&
E
appears
in
the
regional
analyses
presented
in
the
Notice
of
Data
Availability
(
NODA).

	


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








'
!

+
&
!
'
Dockside
landings
and
revenues
are
relatively
easy
to
observe,
and
readily
available
from
NMFS.
These
data
can
be
used
to
develop
a
rough
estimate
of
the
value
of
increased
commercial
catch.
However,
it
is
not
always
easy
to
interpret
these
data
properly
in
estimating
benefits.
First,
there
are
some
empirical
issues
about
whether
the
data
accurately
reflect
the
full
market
value
of
the
commercial
catch.
Second,
simply
applying
an
average
price
to
a
change
in
catch
does
not
account
for
a
potential
price
response
to
the
change
in
catch.
Third,
even
if
the
price
effect
is
accounted
for,
change
in
gross
revenue
is
not
necessarily
the
right
conceptual
or
empirical
basis
for
estimating
benefits
from
reduced
I&
E.
This
section
addresses
these
key
issues.

	


"
/
)



	


-



1




+





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


0
-





1

 



While
the
commercial
landings
data
available
from
NMFS
are
the
most
comprehensive
data
available
at
the
national
and
regional
levels,
the
data
may
not
fully
capture
the
economic
value
of
the
commercial
catch
in
the
United
States.
Data
limitations
occur
here
as
well
as
in
any
other
data
that
are
gathered
in
any
data
collection
effort,
such
as
database
overlap
and
human
error.
Additional
reasons
the
data
may
not
fully
capture
the
economic
value
of
the
commercial
catch
are
varied
and
include,
but
are
not
limited
to,
the
following:


Fishermen
often
receive
noncash
payments
for
their
catch.
Crutchfield
et
al
(
1982)
noted
that
"
the
full
amount
of
the
payment
to
fishermen
should
include
the
value
of
boat
storage,
financing,
food,
fuel,
and
other
non­
price
benefits
that
are
often
provided
to
fishermen
by
processors.
These
are
clearly
part
of
the
overall
`
price,'
but
are
very
difficult
to
measure,
since
they
are
not
generally
applicable
to
all
fishermen
equally
and
are
not
observed
as
part
of
dockside
prices."


Some
unscrupulous
fishermen
may
sell
their
catch
illegally.
There
are
three
main
reasons
why
illegal
transactions
occur.
Some
of
the
most
important
motivations
for
illegal
transactions
are:
°
To
circumvent
quantity
restrictions
(
quotas)
on
landings
allowed
under
fishery
management
rules.
°
To
avoid
or
reduce
taxes
by
having
a
reported
income
less
than
true
earnings.
°
To
reduce
profit
sharing,
boat
owners
have
been
know
to
negotiate
a
lower
price
with
the
buyer
and
then
recover
part
of
their
loss
"
in
secret"
so
they
do
not
have
to
share
the
entire
profit
with
the
crew.










	
























































 


!


"
 



"

#










 
$
$










"








Some
species
are
recorded
inaccurately.
Seafood
dealers
fill
out
the
reports
for
commercial
landings
and
may
mislabel
a
species
or
not
specifically
identify
the
species
(
e.
g.,
entering
"
rockfish"
instead
of
"
blue
rockfish").
Thus
data
on
the
landings
for
blue
rockfish
would
underestimate
total
landings,
while
data
for
"
other
rockfish"
would
be
overestimated
(
David
Sutherland,
NMFS,
Fisheries
Statistics
and
Economics
Division,
personal
communication
November
4,
2002).


NMFS
commercial
landings
data
captures
landings
only
at
U.
S.
docks.
It
is
possible
that
fish
populations
in
the
Great
Lakes
that
are
affected
by
in­
scope
facilities
on
the
Great
Lakes
may
migrate
into
Canadian
fishing
waters.
This
will
need
to
be
looked
at
carefully
once
the
revised
list
of
species
impacted
by
I&
E
in
the
Great
Lakes
region
is
determined.
If
there
is
evidence
that
Canadian
fishermen
are
affected
then
it
may
be
necessary
to
incorporate
Canadian
landings
data
into
the
calculation.


Federal
law
prohibits
reporting
confidential
data
that
would
distinguish
individual
producers
or
otherwise
cause
a
competitive
disadvantage.
These
"
confidential
landings"
are
entered
as
"
unclassified"
data
(
e.
g.,
finfishes,
unc.)
and
do
not
distinguish
individual
species.
Although
most
summarized
landings
are
not
confidential,
species
summary
data
may
under­
report
actual
landings
if
some
of
those
landings
have
been
confidential
and
therefore
were
not
reported
by
individual
species
(
NMFS,
2002c).


Landings
data
are
combined
from
nine
databases
that
overlap
spatially
and
temporally,
and
although
they
are
carefully
monitored
for
double­
counting,
some
overlap
may
go
unnoticed
(
NMFS,
2002c).

	


"
/
)
*
















+









+












A
key
issue
in
this
analysis
is
whether
the
change
in
fishery
conditions
associated
with
regulatory
options
will
be
sufficiently
large
to
generate
price
changes
in
the
relevant
fishery
markets:


If
the
estimated
changes
in
commercial
landings
are
so
small
relative
to
the
applicable
markets
that
no
price
change
of
consequence
is
anticipated
(
as
appears
to
be
the
case
for
two
regional
analyses
conducted
to
date
for
the
NODA
 
as
discussed
later
in
this
chapter),
then
the
approach
to
estimating
benefits
becomes
relatively
simple.
As
will
be
developed
later
in
this
chapter,
this
is
because
the
change
in
revenues
becomes
straightforward
to
estimate
(
i.
e.,
the
estimated
change
in
quantity
landed
times
the
original
price).
Further,
with
no
change
in
price,
there
is
a
fairly
transparent
relationship
between
the
change
in
revenues
and
the
change
in
economic
surplus
measures
that
are
suitable
for
a
benefits
assessment
(
i.
e.,
there
is
no
change
in
consumer
surplus,
and
the
change
in
producer
surplus
may
be
equivalent
to
a
percent
of
or
even
equal
to
the
change
in
revenues).


If
changes
in
landings
are
such
that
a
price
reduction
is
anticipated,
then
the
conceptual
and
empirical
analysis
becomes
more
complicated.
As
detailed
in
greater
depth
later
in
this
chapter,
a
price
change
makes
it
more
difficult
to
estimate
changes
in
gross
revenues
(
in
fact
the
change
in
revenues
may
be
either
positive
or
negative,
depending
on
the
relative
elasticity
of
demand).
Further,
a
change
in
price
is
anticipated
to
generate
changes
in
both
producer
and
consumer
surplus,
and
there
are
numerous
complex
factors
to
be
considered
in
assessing
these
changes
in
welfare
(
e.
g.,
some
of
the
gain
in
consumer
surplus
will
reflect
a
transfer
away
from
producer
surplus,
the
overall
change
in
producer
surplus
may
be
positive
or
negative,
and
the
relationship
between
these
measures
of
surplus
and
the
estimated
market
revenues
is
much
less
transparent
than
in
the
case
where
price
is
reasonably
constant).

As
discussed
later
in
this
chapter,
for
the
two
regions
that
have
been
analyzed
for
the
NODA,
the
change
in
estimated
harvest
is
small
relative
to
the
applicable
market
and
EPA
has
assumed
that
there
would
be
no
effective
change
in
price.
The
issues
with
estimating
changes
in
revenues
and
surplus
are
then
relatively
straightforward.

EPA
has
yet
to
conduct
its
empirical
analyses
of
potential
harvest
increases
in
the
other
regions
it
intends
to
study
for
the
final
rulemaking.
It
may
be
the
case
that
price
changes
are
likely
to
apply
in
some
of
the
markets
in
the
regions
that
will
be
analyzed
in
the
future.
Therefore,
EPA
is
proceeding
in
this
chapter
to
provide
discussion
of
conceptual
and
empirical
issues
that
may
arise
 
and
the
methods
that
EPA
might
consider
applying
 
in
the
event
a
price
change
scenario
may
be
relevant
for
some
portion
of
the
future
analyses
that
will
accompany
the
final
rulemaking.


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
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Price
Quantity
S
D
=
P(
Q)

Q*
P*

C
B
A
	


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Before
progressing
into
the
details
of
defining
and
measuring
surplus
and
revenues,
or
discussing
further
why
prices
may
change
and
how
one
might
estimate
by
how
much,
it
is
important
to
first
establish
some
basic
economic
concepts
relative
to
markets
and
measures
of
welfare.
Figure
A13­
1
depicts
a
simple
market
for
a
typical
economic
good,
with
demand
(
labeled
as
line
D)
downward
sloping
to
reflect
what
economists
refer
to
as
decreasing
marginal
utility,
and
supply
(
line
S)
upward
sloping
to
reflect
increasing
marginal
costs.
There
are
numerous
reasons
why
the
market
for
commercial
fish
often
differs
in
important
ways
from
the
typical
market
depicted
in
the
figure.
Commercial
fisheries
are
considered
renewable
natural
resources
whereby
supply
is
limited
by
ecological
constraints.
As
a
consequence,
fisheries
markets
deviate
from
the
traditional
neoclassical
view
of
fully
competitive
markets
due
to
the
impacts
of
open
access,
the
socially
desirable
need
to
maximize
resource
rents,
the
corresponding
need
for
regulations
that
limit
catch
or
prevent
the
entry
of
fishermen
(
suppliers),
and
the
possibility
that
costs
may
not
increase
in
the
relevant
range
of
changes
to
fishery
conditions.
Such
issues
that
are
discussed
later
in
the
chapter.
Nonetheless,
to
help
introduce
some
core
concepts,
we
begin
with
the
standard
neoclassical
depiction
of
a
market
as
depicted
in
the
figure.

Figure
A13­
1:
Market
for
Typical
Economic
Good
An
equilibrium
is
established
where
supply
and
demand
intersect,
such
that
Q*
reflects
the
quantity
of
good
exchanged
and
P*
reflects
the
market
clearing
price
(
i.
e.,
the
price
at
which
the
quantity
supplied
is
equal
to
the
quantity
demanded).
The
gross
revenues
in
this
market
(
the
sum
total
paid
by
consumers
and
the
sum
total
received
by
sellers)
are
equal
to
P*
multiplied
by
Q*,
which
in
the
figure
is
depicted
by
the
rectangle
made
up
of
areas
B
plus
C.

While
the
level
of
total
(
gross)
revenues
is
of
interest,
it
is
not
the
same
as
the
amount
of
benefit
(
economic
welfare)
that
is
generated
by
this
market,
which
is
measured
by
what
is
referred
to
as
economic
surplus.
Economic
surplus
consists
of
the
consumer
surplus
generated
(
which
is
depicted
by
area
A)
plus
the
producer
surplus
generated
(
depicted
as
area
B).
Consumer
surplus
reflects
the
amount
by
which
willingness
to
pay
(
as
reflected
by
the
demand
curve)
exceeds
the
market­
clearing
price
for
each
quantity
exchanged
up
to
Q*
(
i.
e.,
it
reflects
the
degree
by
which
consumers
obtained
the
traded
commodity
at
a
price
less
than
what
the
good
was
worth
to
them).
Likewise,
producer
surplus
reflects
the
extent
to
which
suppliers
realized
revenues
above
and
beyond
the
marginal
cost
of
producing
some
of
the
units
(
up
to
Q*).
Beyond
Q*,
there
is
neither
additional
consumer
or
producer
surplus
to
be
gained
 
at
the
margin,
all
the
surplus
has
been
extracted
and
there
is
no
additional
surplus
to
be
gained
by
adding
more
output
to
the
market.

Now
suppose
there
is
a
change
that
increases
the
amount
of
a
key
input
to
production,
such
that
the
more
bountiful
input
is
now
available
at
a
lower
cost
to
suppliers
than
before
(
e.
g.,
when
increasing
the
amount
of
locally
harvestable
fish
makes
it
easier
to
catch
a
given
number
of
fish).
This
could
result
in
an
outward
shift
in
supply
(
a
decrease
in
the
marginal
cost
of

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Price
Quantity
S
0
S
1
D
G
Q
1
Q*
Z
Y
D
F
P*

P
1
E
B
A
X
C
producing
any
given
quantity
of
the
good).
This
is
depicted
in
Figure
A13­
2,
where
supply
shifts
from
S
0
to
S
1.
With
the
increased
supply,
a
new
market
clearing
price
emerges
at
P
1
(
which
is
lower
than
the
original
P*,
and
the
quantity
exchanged
increases
from
Q*
to
Q
1.

Figure
A13­
2:
Increased
Supply
in
Typical
Economic
Market
These
changes
in
the
quantity
exchanged
and
the
market
clearing
price
make
it
somewhat
complex
to
envision
how
(
and
by
how
much)
gross
revenues
and
economic
surplus
measures
may
change
as
a
consequence
of
the
shift
in
supply.
Using
Figure
A13­
2
as
a
guide:


Under
the
original
supply
conditions
(
S
0)
consumer
surplus
had
been
area
A,
but
it
has
now
increased
to
A+
B+
C+
D.
Therefore,
consumer
surplus
has
increased
by
an
amount
depicted
by
areas
B+
C+
D.


Producer
surplus
had
been
area
B
+
E
before
the
supply
shift,
but
becomes
E+
F+
G
after
the
shift
in
supply.
Hence
the
change
in
producer
surplus
is
depicted
as
areas
F+
G­
B.

°
Note
that
area
B
is
subtracted
from
producer
surplus
but
added
to
consumer
surplus
 
i.
e.,
it
represents
a
transfer
of
surplus
from
producers
to
consumers
when
supply
shifts
outward
and
prices
decline.

°
Also
note
that
consumer
surplus
has
increased
by
more
than
the
transfer
of
area
B
from
producers;
the
additional
consumer
surplus
(
above
and
beyond
the
transfer)
is
depicted
by
the
amount
C+
D.

°
Finally,
note
that
the
change
in
producer
surplus
might
be
positive
or
negative,
depending
on
whether
the
addition
of
F+
G
outweighs
the
loss
of
B
(
assuming
the
supply
curves
are
parallel).


The
total
change
in
economic
surplus
(
consumer
plus
producer
surplus)
therefore
equals
C+
D+
F+
G.


Revenues
had
been
P*
times
Q*
(
areas
B+
C+
E+
F+
X),
but
now
becomes
P
1
times
Q
1
(
areas
E+
F+
X+
G+
Y).
The
change
in
revenues
thus
becomes
(
G+
Y)
­
(
B+
C).

°
Note
that
the
change
in
revenue
can
be
positive
or
negative,
depending
on
whether
G+
Y
is
greater
than
or
less
than
B+
C.

°
Also
note
that
if
one
does
not
know
by
how
much
the
price
will
decrease,
and
relies
on
the
original
price
(
P*)
to
estimate
the
change
in
revenues,
then
the
change
in
revenues
would
be
over­
estimated
as
P*
times
(
Q
1
­
Q*),
which
is
equivalent
to
the
areas
G+
Y+
D+
Z.







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

	






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

















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


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








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






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







 


!


"
 



"

#





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



 
$
$










"







°
If
the
change
in
revenues
is
estimated
relying
on
the
original
price
level
(
P*)
when
in
fact
the
new
price
becomes
P
1,
then
the
amount
by
which
the
change
in
revenues
will
be
over­
estimated
would
be
B+
C+
D+
Z.

Even
though
the
illustration
above
relies
on
a
relatively
simple
depiction
of
a
market
that
adheres
to
the
basic
economic
assumptions
and
conditions
of
perfect
competition,
it
reveals
how
complex
the
analysis
can
become
if
there
is
an
anticipated
change
in
price
when
supply
is
increased.
The
analysis
can
become
even
more
complex
when
fishery­
related
deviations
from
the
assumptions
of
open
access
perfect
competition
are
considered.

	


"
/
)
/


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
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

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
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+
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

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5
	



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1

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

	






3


6

One
key
observation
from
the
illustration
above
is
the
importance
of
predicting
the
change
in
price,
because
relying
on
the
baseline
price
can
lead
to
potential
errors.
Correct
estimation
of
the
change
in
price
of
fish
as
a
result
of
the
regulation
requires
two
pieces
of
information:
the
expected
change
in
the
commercial
catch,
and
the
relationship
between
demand
for
fish
and
the
price
of
fish.
Ideally,
a
demand
curve
would
be
estimated
for
the
market
for
each
fish
species
in
each
regional
market.
The
level
of
effort
required
to
model
demand
in
every
market
is
not
feasible
for
this
analysis.
However,
if
reasonable,
empirically
based
assumptions
can
be
made
for
the
price
elasticity
of
demand
for
fish
in
each
region,
the
change
in
price
can
be
accurately
estimated.

The
price
elasticity
of
demand
for
a
good
measures
the
percentage
change
in
demand
in
response
to
a
percent
change
in
price.
If
the
price
elasticity
of
demand
for
fish
is
assumed
to
be
­
2
over
the
relevant
portion
of
the
demand
function,
then
a
1%
increase
in
price
creates
a
2%
decrease
in
the
quantity
demanded.
Essentially,
this
determines
the
shape
of
the
demand
curve
because
it
indicates
how
demand
responds
to
a
change
in
price.
The
inverse
of
the
price
elasticity
of
demand
can
be
used
to
estimate
the
change
in
price
as
a
result
of
a
change
in
the
quantity
demanded.
If
the
price
elasticity
of
demand
is
assumed
to
be
­
2,
the
inverse
is
1/­
2
=
­
0.5.
This
would
imply
that
a
1%
increase
in
demand
would
correspond
to
a
0.5%
decrease
in
price.

For
example,
in
Figure
A13­
2,
if
Q*
is
equal
to
10,000
pounds
of
fish
per
year
and
reductions
in
I&
E
are
expected
to
add
500
pounds
of
fish
to
the
annual
catch,
Q
1
will
equal
10,500
per
year.
This
is
a
5%
increase
in
the
quantity
of
fish
supplied
to
the
market.
In
response
to
the
increase
in
supply,
price
will
need
to
decrease
from
P*
to
P
1.
To
clear
the
market,
the
quantity
demanded
would
need
to
increase
until
Q
1
is
also
the
quantity
of
fish
demanded.
If
the
price
elasticity
of
demand
for
fish
in
this
market
is
known
to
be
approximately
­
2,
then
the
inverse
of
the
price
elasticity
of
demand
is
­
0.5
and,
as
described
above,
the
expected
change
in
price
necessary
to
clear
the
market
would
be
5%
x
­
0.5
=
­
2.5%.
If
P*
equals
$
1.00
per
pound,
then
P
1
will
equal
$
0.975
per
pound,
and
the
change
in
gross
revenues
will
be
(
10,500
×
$
0.975)
­
(
10,000
×
$
1.00)
=
$
237.50.
This
represents
a
2.375%
increase
in
gross
revenues
for
commercial
fishermen
in
this
market.

A
variety
of
sources
in
the
economics
literature
provide
estimates
of
the
price
elasticity
of
demand
for
fish.
In
the
proposed
rule
and
the
NODA,
EPA
assumed
that
the
changes
in
supply
of
fish
as
a
result
of
reduced
I&
E
would
not
be
large
enough
to
create
a
significant
change
in
price
(
see
discussion
below
describing
the
two
regions
EPA
analyzed
for
the
NODA).
In
the
final
Phase
II
analysis,
for
those
markets
(
if
any)
in
which
the
estimated
change
in
harvest
is
considered
large
enough
to
generate
a
price
change
of
consequence,
EPA
will
review
the
available
research
on
the
elasticity
of
demand
and
price,
and
will
develop
assumptions
suitable
for
modeling
the
effect
of
a
reduction
in
price
on
estimated
changes
in
gross
revenues.
If
the
effect
on
price
is
found
to
be
significant,
changes
in
dockside
gross
revenue
will
be
calculated
as
(
quantity
of
fish
demanded
post
regulation
×
post­
regulation
price)
­
(
quantity
of
fish
demanded
pre
regulation
×
preregulation
price).

	


"
7











'
!

+
&
!
'
Even
if
the
change
in
gross
revenue
is
measured
accurately
and
potential
price
effects
(
if
any)
are
accounted
for,
changes
in
gross
revenues
are
not
generally
considered
to
be
a
true
measure
of
economic
benefits.
According
to
broadly
accepted
principles
of
microeconomics,
benefits
should
be
expressed
in
terms
of
economic
surplus
to
consumers
and
producers.



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

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



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
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
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

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5
In
this
simplified
illustration
P(
F)
is
really
an
inverse
demand
curve
since
it
determines
price
as
a
function
of
quantity,
F.
It
is
not
of
vital
importance
here.

6
Note
that
Figure
A13­
3
is
a
highly
simplified
characterization
of
benefits
derived
from
a
commercial
fishery,
where
the
goal
is
to
maximize
producer
surplus
and
consumer
surplus.
Figure
A13­
3
is
drawn
from
Bishop
and
Holt
(
2003),
who
indicate
that
P(
F)
represents
a
general
equilibrium
demand
function,
accounting
for
markets
downstream
of
harvesters,
and
that
the
welfare
triangle
(
area
T
in
Figure
A13­
3)
represents
consumer
surplus
plus
post­
harvest
rents.
F
1
is
the
supply
of
fish
under
a
fixed,
optimal
quota
before
the
Phase
II
rule
and
F
2
is
the
supply
after
the
Phase
II
rule
takes
effect.
A
more
complete
interpretation
of
the
graph
in
the
context
of
renewable
resources
also
reveals
that
costs
for
the
harvester
(
e.
g.,
fishing
fleet)
is
the
area
W
(
for
a
quota
equal
to
F
1)
and
that
area
U+
V
is
equal
to
the
rents
potentially
captured
by
the
harvester.







	


"
7
)







-




'
-



-

To
understand
consumer
surplus,
consider
the
following
illustration.
Suppose
a
seafood
lover
goes
to
a
fish
market
and
pays
$
A
for
a
salmon
for
a
tasty
dinner.
She
pays
$
A
because
that
is
the
current
market
price.
However,
she
would
have
been
willing
to
pay
a
lot
more
than
$
A,
if
necessary.
The
maximum
she
would
have
paid
for
the
salmon
is
$
B.
The
difference
between
$
B
and
$
A
represents
an
additional
benefit
to
the
consumer.
When
this
benefit
is
summed
across
all
consumers
in
the
market,
it
is
called
consumer
surplus.

Figure
A13­
3
shows
one
possible
representation
of
a
market
for
fish.
The
demand
curve,
P(
F),
shows
the
aggregate
demand
that
would
prevail
in
the
market
(
F)
at
each
price
level
(
P).
5
The
curve
F1
is
the
quantity
of
fish
supplied
to
the
market
by
fishermen.
Equilibrium
is
attained
a
the
point
where
P(
F)
equals
F1.
Under
these
conditions,
the
price
is
P1.
In
this
case
the
total
amount
paid
by
consumers
for
fish
is
equal
to
P1
×
F1,
which
is
equal
to
the
area
of
the
boxes
U+
V+
W
in
the
graph.
The
extra
benefit
to
consumers,
i.
e.,
the
consumer
surplus,
is
equal
to
the
area
of
the
triangle
T.
6

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
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7
Producer
surplus
equals
economic
profit
minus
the
opportunity
cost
of
the
owner's
resources
invested
in
the
fishery
enterprise
(
see
Section
A13.8
for
additional
details).

8
In
this
case
average
cost
is
assumed
to
equal
marginal
cost
at
C
and
the
marginal
cost
is
assumed
constant.
Note
that
this
is
a
simplification
used
here
only
to
assist
with
the
discussion.
For
example,
the
§
316(
b)
rulemaking
might
lead
to
a
decrease
in
cost
per
unit
of
fish
caught.
Also,
if
marginal
cost
were
assumed
to
be
upward
sloping,
the
figure
would
more
closely
resemble
the
familiar
graph
of
supply
and
demand
with
an
upward­
sloping
supply
curve,
as
depicted
in
Figure
A13­
2.

9
Note
that
economists
usually
assume
that
C
includes
the
opportunity
cost
of
investing
and
working
in
commercial
fishing.
Thus,
producer
surplus
is
profit
earned
above
and
beyond
normal
profit.
In
a
perfectly
competitive
market,
when
economic
profit
is
being
earned,
it
induces
more
producers
to
join
the
market
until
producer
surplus
is
zero.
However,
many
commercial
fisheries
are
no
longer
allowing
open
access
to
all
fishermen,
thus
it
is
realistic
to
assume
that
a
level
of
producer
surplus
greater
than
zero
is
attainable
in
many
U.
S.
commercial
fisheries.
In
the
case
of
managed
fisheries
(
P1
­
C)
can
be
referred
to
as
rent.







$

P1
C
T
U
V
W
X
Y
Z
P(
F)

F
P2
F1
F2
Figure
A13­
3:
Conceptual
Model
of
Benefits
from
an
Increase
in
Fish
Catch
Source:
Bishop
and
Holt
(
2003)

If
the
quantity
of
fish
available
to
the
market
increases
from
F1
to
F2,
then
the
price
decreases
to
P2.
This
changes
the
total
amount
paid
by
consumers
to
P2
×
F2,
which
is
equal
to
the
area
of
the
boxes
V+
W+
Y+
Z,
and
increases
the
consumer
surplus
to
be
equal
to
the
area
of
the
triangle
T+
U+
X.

	


"
7
)
*

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-




'
-



-

In
the
example
above,
there
is
also
a
producer
surplus
that
accrues
to
the
fish
seller.
When
the
fish
market
sold
the
salmon
to
our
consumer,
it
sold
it
for
$
A
because
that
was
the
market
price.
However,
it
is
likely
that
it
cost
less
than
$
A
to
supply
the
salmon.
If
$
D
is
the
cost
to
supply
the
fish,
then
the
market
earns
a
profit
of
$
A
minus
$
D
per
fish.
This
profit
is
akin
to
the
economic
concept
of
producer
surplus.
7
In
Figure
A13­
3,
the
line
C
represents
a
simplified
representation
of
the
cost
to
the
producer
of
supplying
a
pound
of
fish.
8
When
the
supply
of
fish
is
equal
to
F1,
the
producers
sell
F1
pounds
of
fish
at
a
price
of
P1.
The
difference
between
P1
and
C
is
the
producer
surplus
that
accrues
to
producers
for
each
pound
of
fish.
9
Total
producer
surplus
realized
by
producers
is
equal
to
(
P1
­
C)
×
F1.
In
the
example,
this
producer
surplus
is
equal
to
the
area
of
U+
V.
The
area
W
is
the
amount
that
producers
pay
to
their
suppliers
if
the
harvest
equals
the
quota
(
F1).
In
the
example
presented
here,
W
might
be
the
amount
that
the
fish
market
paid
to
a
fishing
boat
for
the
salmon
plus
the
costs
of
operating
the
market.










	




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
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


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







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
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
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


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
 
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$




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
10
Note
that
the
producer
surplus
may
be
smaller
at
quantity
F2,
depending
on
whether
U
is
bigger
than
Y.
The
relative
sizes
of
U
and
Y
depend
on
the
slope
of
P(
F).
When
the
P(
F)
curve
is
less
steep,
i.
e.,
when
demand
is
more
price
elastic,
Y
will
be
larger
compared
to
U.
When
the
P(
F)
curve
is
steeper,
i.
e.,
when
demand
is
more
price
inelastic,
Y
will
be
smaller
compared
to
U.
Changes
in
producer
surplus
may
be
negative
with
increased
harvest
if
demand
is
sufficiently
inelastic.

11
As
described
in
Section
A13­
7
and
Bishop
and
Holt
(
2003),
the
total
consumer
surplus
accumulated
through
tiered
markets
can
be
estimated
from
a
general
equilibrium
demand
function
(
but
not
from
a
more
typical
single
market
partial
equilibrium
demand
curve).







When
supply
increases
to
F2,
the
producers
sell
F2
pounds
of
fish
at
a
price
of
P2.
The
total
cost
to
produce
F2
increases
from
W
to
W+
Z.
The
total
producer
surplus
changes
from
U+
V
to
V+
Y.
10
In
this
simple
example,
where
C
is
assumed
to
be
constant,
the
producer
surplus
earned
by
producers
is
equal
for
all
units
of
F
produced.
If
C
increases
as
F
increases,
however,
some
of
the
producer
surplus
per
unit
will
be
eaten
away
by
increased
costs.
In
the
figure,
this
would
be
seen
as
a
decrease
in
the
areas
of
V
and
Y
and
an
increase
in
the
areas
of
W
and
Z
as
a
greater
share
of
the
revenues
from
the
sale
of
the
catch
go
to
cover
costs.

Exhibit
A13­
3
is
a
graphical
representation
of
a
single
market.
In
the
real
world,
a
fishing
boat
captain
will
sell
the
boat's
catch
to
a
processor,
who
sells
processed
fish
to
fish
wholesalers,
who
in
turn
sells
fish
to
retailers,
who
may
sell
fish
directly
to
a
consumer
or
to
a
restaurant,
which
will
sell
fish
to
a
consumer.
There
will
be
consumer
and
producer
surplus
in
each
of
these
markets.
11
As
a
result,
it
is
conceptually
inaccurate
to
estimate
the
change
in
the
quantity
of
fish
harvested,
multiply
by
the
price
per
pound,
and
call
this
change
in
gross
revenue
the
total
benefits
of
the
regulation.

In
the
sections
of
this
chapter
that
follow,
we
detail
methods
being
considered
for
the
final
analysis
of
commercial
fishing
benefits
attributable
to
the
Phase
II
regulations.
This
involves
four
basic
steps:
estimating
the
increase
in
pounds
of
commercial
catch
under
the
rule,
estimating
the
gross
value
of
the
increased
catch,
estimating
the
increase
in
producer
surplus
as
a
proportion
of
increased
gross
value,
and
estimating
the
increase
in
consumer
surplus
across
all
affected
markets
as
a
proportion
of
increased
gross
value.
The
approaches
discussed
depend
on
whether
or
not
a
price
change
is
anticipated;
hence
the
methods
are
presented
according
to
these
two
possible
scenarios.

	


"
8
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9

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
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%
	

.

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

+




As
shown
in
Tables
A13­
4
and
A13­
5,
the
proposed
regulatory
option
is
expected
to
result
in
small
changes
in
commercial
landings
and
gross
dockside
revenues
for
the
North
Atlantic
and
Northern
California
regions.
The
total
landings
of
commercial
species
are
estimated
to
increase
by
less
than
0.06%
and
0.08%
(
and
total
revenues
are
expected
to
increase
by
0.23%
and
0.14%)
in
the
North
Atlantic
and
Northern
California
coastal
regions,
respectively.

Table
A13­
4:
Expected
Increase
in
Commercial
Harvest
(
in
pounds
per
year)
Resulting
from
Proposed
Rule
Species
Avg.
Annual
Harvest
1993­
2001
(
pounds)
Expected
Increase
(
pounds)
as
a
Result
of
the
Proposed
Rule
Expected
%
Increase
as
a
Result
of
the
Proposed
Rule
North
Atlantic
American
plaice
9,613,591
0
0.00%

Atlantic
cod
31,393,275
699
0.00%

Atlantic
herring
163,991,515
30
0.00%

Atlantic
mackerel
9,800,077
5
0.00%

Atlantic
menhaden
957,771
3,027
0.32%

Atlantic
silverside
3,704
0
0.00%

Bluefish
1,447,480
17
0.00%

Butterfish
4,850,330
86
0.00%

Pollock
9,381,311
88
0.00%










	
























































 

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!


"
 
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
"
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#





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



 
$
$




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"


Table
A13­
4:
Expected
Increase
in
Commercial
Harvest
(
in
pounds
per
year)
Resulting
from
Proposed
Rule
Species
Avg.
Annual
Harvest
1993­
2001
(
pounds)
Expected
Increase
(
pounds)
as
a
Result
of
the
Proposed
Rule
Expected
%
Increase
as
a
Result
of
the
Proposed
Rule






Rainbow
smelt
10,137
435
4.29%

Red
hake
2,275,389
66
0.00%

Scup
2,821,173
146
0.01%

Searobin
41,507
3
0.01%

Silver
hake
20,135,235
6,750
0.03%

Skate
species
23,893,387
215
0.00%

Tautog
178,721
1,892
1.06%

Weakfish
83,536
1,813
2.17%

White
perch
10,266
18
0.17%

Windowpane
1,234,554
1,298
0.11%

Winter
flounder
9,982,853
155,202
1.55%

Total
292,105,811
171,788
0.06%

Northern
California
Anchovies
13,083,041
8,160
0.06%

Cabezon
210,879
937
0.44%

California
halibut
957,231
1,699
0.18%

Croakers
381,954
84
0.02%

Dungeness
9,612,166
3,718
0.04%

Flounders
13,058,871
4,108
0.03%

Herrings
94,972,504
47,534
0.05%

Rock
crabs
1,129,209
7,405
0.66%

Rockfishes
6,524,159
31,767
0.49%

Sculpins
3,450
601
17.41%

Smelts
1,254,723
1,227
0.10%

Surfperches
55,602
2,565
4.61%

Total
141,243,790
109,804
0.08%

Southern
California
Species
group
1
Species
group
2
Species
group
3
Species
group
4
Species
group
5
Total
Great
Lakes
Species
group
1
Species
group
2
Species
group
3
Species
group
4
Species
group
5
Total
Middle
Atlantic










	
























































 


!


"
 



"

#










 
$
$










"


Table
A13­
4:
Expected
Increase
in
Commercial
Harvest
(
in
pounds
per
year)
Resulting
from
Proposed
Rule
Species
Avg.
Annual
Harvest
1993­
2001
(
pounds)
Expected
Increase
(
pounds)
as
a
Result
of
the
Proposed
Rule
Expected
%
Increase
as
a
Result
of
the
Proposed
Rule






Species
group
1
Species
group
2
Species
group
3
Species
group
4
Species
group
5
Total
Gulf
of
Mexico
Species
group
1
Species
group
2
Species
group
3
Species
group
4
Species
group
5
Total
South
Atlantic
Species
group
1
Species
group
2
Species
group
3
Species
group
4
Species
group
5
Total
Inland
facilities
Species
group
1
Species
group
2
Species
group
3
Species
group
4
Species
group
5
Total










	
























































 


!


"
 



"

#





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



 
$
$










"








Table
A13­
5:
Expected
Increase
in
Commercial
Harvest
Gross
Revenues
(
in
dollars
per
year)
Resulting
from
Proposed
Rule
Species
Average
Annual
Gross
Revenues
1993­
2001
($)
Expected
Increase
($
Gross
Revenues)
as
a
Result
of
the
Proposed
Rule
Expected
Increase
(%
Gross
Revenues)
as
a
Result
of
the
Proposed
Rule
North
Atlantic
American
plaice
11,473,506
0
0.00%

Atlantic
cod
29,677,576
629
0.00%

Atlantic
herring
9,695,038
2
0.00%

Atlantic
mackerel
2,156,477
2
0.00%

Atlantic
menhaden
54,847
143
0.26%

Atlantic
silverside
1,615
0
0.00%

Bluefish
400,219
4
0.00%

Butterfish
2,804,084
54
0.00%

Pollock
6,833,565
61
0.00%

Rainbow
smelt
10,367
88
0.85%

Red
hake
496,107
14
0.00%

Scup
2,943,897
118
0.00%

Searobin
5,046
7
0.14%

Silver
hake
7,510,935
2,278
0.03%

Skate
species
3,612,204
30
0.00%

Tautog
193,702
1,416
0.73%

Weakfish
73,376
1,450
1.98%

White
perch
8,096
20
0.24%

Windowpane
659,752
727
0.11%

Winter
flounder
12,401,675
198,511
1.60%

Total
91,012,084
205,554
0.23%

Northern
California
Anchovies
697,536
653
0.09%

Cabezon
631,763
3,111
0.49%

California
halibut
2,460,353
4,263
0.17%

Croakers
263,178
48
0.02%

Dungeness
14,532,547
5,727
0.04%

Flounders
4,470,096
1,273
0.03%

Herrings
9,509,412
9,982
0.10%

Rock
crabs
1,377,021
8,441
0.61%

Rockfishes
5,581,044
17,471
0.31%

Sculpins
9,792
1,573
16.07%

Smelts
319,613
319
0.10%

Surfperches
87,413
4,026
4.61%

Total
39,939,769
56,887
0.14%

Southern
California
Species
group
1
Species
group
2










	

























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




















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





 

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

"
 



"
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#





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



 
$
$










"


Table
A13­
5:
Expected
Increase
in
Commercial
Harvest
Gross
Revenues
(
in
dollars
per
year)
Resulting
from
Proposed
Rule
Species
Average
Annual
Gross
Revenues
1993­
2001
($)
Expected
Increase
($
Gross
Revenues)
as
a
Result
of
the
Proposed
Rule
Expected
Increase
(%
Gross
Revenues)
as
a
Result
of
the
Proposed
Rule






Species
group
3
Species
group
4
Species
group
5
Total
Great
Lakes
Species
group
1
Species
group
2
Species
group
3
Species
group
4
Species
group
5
Total
Middle
Atlantic
Species
group
1
Species
group
2
Species
group
3
Species
group
4
Species
group
5
Total
Gulf
of
Mexico
Species
group
1
Species
group
2
Species
group
3
Species
group
4
Species
group
5
Total
South
Atlantic
Species
group
1
Species
group
2
Species
group
3
Species
group
4
Species
group
5
Total
Inland
facilities
Species
group
1
Species
group
2
Species
group
3
Species
group
4
Species
group
5
Total



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





	




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
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






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







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


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
















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




 


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

"
 



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

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
 
$
$




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"







	
Price
Quantity
A
B
C
F
E
D
P
S
0
S
1
D
Q
1
Q
0
Such
modest
changes
in
landings
are
not
expected
to
influence
the
respective
markets
for
the
commercially
impacted
fisheries,
such
that
it
seems
reasonable
to
presume
that
there
will
be
no
appreciable
impacts
on
wholesale
or
retail
fish
prices.
Under
such
a
scenario
of
no
price
impacts,
economic
theory
indicates
that
all
changes
in
economic
welfare
will
be
confined
to
changes
in
producer
surplus
(
i.
e.,
changes
in
consumer
and
related
post­
harvest
surplus
will
be
zero).
The
benefits
estimation
issue
then
can
be
confined
to
examining
producer
surplus,
and
the
core
empirical
and
conceptual
issue
becomes
how
the
change
in
producer
surplus
relates
to
estimates
of
added
gross
revenues,
when
prices
remain
constant.

	


"
8
)



+



-




'
-



-







+










.







4


-




	


-

















+





Given
the
potential
for
increases
in
producer
surplus
for
the
harvest
sector
(
including
rents
to
harvesters)
under
conditions
where
fish
price
does
not
change,
EPA
has
relied
on
and
continues
to
explore
percentages
or
fractions
of
gross
revenue
change
as
a
proxy
for
changes
in
producer
surplus.

If
we
assume
a
fishery
is
regulated
such
that
harvests
are
sustainable
and
reflect
efforts
to
maximize
resource
rents,
then
increases
in
harvest
are
expected
as
stocks
increase.
As
an
example
assume
that
quotas
are
the
regulatory
instrument
and
that
quotas
increase
in
response
to
reduced
impingement
and
entrainment,
and
that
supply
curve
(
as
represented
by
a
marginal
cost
curve)
shifts
as
a
result
of
increased
stock,
then
we
can
relate
change
in
producer
surplus
to
change
in
gross
revenue
using
Figure
A13­
4.
Producer
surplus,
before
the
increase
in
stock
and
change
in
quota,
is
area
A.
Producer
surplus
after
increase
in
stock
and
change
in
quota
is
area
(
A+
B+
D+
E).
Change
in
producer
surplus
is
therefore
equal
to
area
(
B+
D+
E).

Three
scenarios
can
be
used
to
show
how
change
in
revenue
may
over
or
underestimate
change
in
producer
surplus:

1.
If
B<
F,
then
change
in
revenue
overestimates
change
in
producer
surplus
2.
If
B=
F,
then
change
in
revenue
approximates
change
in
producer
surplus
3.
B>
F,
then
change
in
revenue
underestimates
change
in
producer
surplus.

Note
that
if
the
first
scenario
prevails,
then
some
fraction
of
gross
revenue
may
be
more
suitable
as
a
reliable
proxy
for
change
in
producer
surplus
when
price
is
assumed
constant.
If
the
marginal
cost
of
supplying
the
extra
fish
for
Q
1
is
minimal
or
close
to
zero,
then
the
second
or
third
scenarios
prevail,
and
100%
or
more
of
the
change
in
revenue
may
serve
as
a
reliable
proxy
for
change
in
producer
surplus.

Figure
A13­
4:
Surplus
in
a
Regulated
Fishery










	
























































 


!


"
 



"

#










 
$
$










"


12
This
would
be
consistent
with
the
EPA
Guidelines
for
Economic
Analysis
(
2003)
(
EPA
240­
R­
00­
003).
The
guidelines
describe
options
for
estimating
ecological
benefits
for
fisheries,
and
note
that
"
if
changes
in
service
flows
are
small,
current
market
prices
can
be
used
as
a
proxy
for
expected
benefit
.
.
.
a
change
in
the
commercial
fish
catch
might
be
valued
using
the
market
price
for
the
affected
species."







	


"
8
)
*







-









'
-



-


:

















+








	










There
are
scenarios
that
may
arise
when
fishery
conditions
improve
such
that
supply
shifts
outward,
but
not
enough
to
generate
any
price
change
of
consequence.
In
such
cases,
there
is
no
anticipated
change
in
post­
harvest
surplus
to
consumers
on
other
post­
harvest
entities,
because
reduction
in
price
is
required
to
generate
such
surplus
improvements.
Hence,
the
change
in
economic
welfare
is
limited
to
changes
in
producer
surplus
under
these
conditions.

As
shown
in
the
previous
section,
estimates
of
changes
in
dockside
revenues
become,
under
some
scenarios,
equivalent
to
the
change
in
producer
surplus.
Hence,
the
change
in
gross
revenues
could
be
used
as
a
proxy
to
estimate
of
the
change
in
producer
surplus
for
the
two
regional
studies
developed
to
date,
and
EPA
is
evaluating
this
option.
12
EPA
also
recognizes
that
under
some
of
the
possible
scenarios
that
may
arise
when
there
is
a
quota­
governed
market,
the
full
change
in
revenues
(
as
estimated
through
a
projected
change
in
landings
but
no
price
change)
might
overstate
the
change
in
producer
surplus.
However,
if
dockside
prices
and/
or
dockside
landings
(
quantities)
are
understated
 
as
may
often
be
the
case
 
then
the
change
in
surplus
will
be
understated
in
most
scenarios
by
the
estimated
change
in
gross
revenues.

EPA's
analysis
of
commercial
fishery
benefits
in
the
NODA
relies
on
the
premise
that
the
change
in
producer
surplus
is
only
a
fraction
of
the
projected
change
in
revenues.
Currently,
EPA
is
using
a
range
of
0%
to
40%
of
the
gross
revenue
changes
estimated
as
a
means
of
estimating
the
change
in
producer
surplus.
This
is
based
on
a
review
of
empirical
literature
(
restricted
to
only
those
studies
that
compared
producer
surplus
to
gross
revenue)
that
is
described
in
greater
detail
in
Section
A13­
8.
This
represents
a
change
from
the
analysis
for
the
proposed
rule,
which
assumed
a
range
of
40%
to
70%.
EPA
will
continue
to
review
this
approach
for
the
final
analysis.

	


"
;


'
!

+
&
!
'


'



	





!

 



'



	



'




$
%


%

+






%
	

.

'


	
(
	


'

In
the
preceding
section,
the
discussion
was
limited
to
cases
in
which
no
notable
change
in
price
was
anticipated.
These
scenarios
appear
reasonable
for
very
small
improvements
in
fishery
conditions,
which
appears
to
apply
in
the
two
regions
empirically
studied
to
date
for
the
NODA
for
the
rulemaking.
However,
EPA
may
find
that
more
appreciable
impacts
to
commercial
fisheries
may
arise
in
one
or
more
of
the
remaining
regional
analyses
it
intends
to
conduct
between
the
NODA
and
final
rulemaking.
In
such
an
instance,
it
may
be
inappropriate
to
assume
that
there
will
be
no
price
effects
in
any
of
the
commercial
fishery
markets
affected
by
the
§
316(
b)
regulation.
This
section
discusses
the
conceptual
and
empirical
basis
the
Agency
is
evaluating
to
estimate
economic
surplus
(
i.
e.,
benefits)
in
instances
where
price
changes
are
more
likely
to
arise.

	


"
;
)

























+








4












<
















$







Figure
A13­
5
portrays
a
standard,
neoclassical
economic
depiction
of
a
market,
with
demand
downward
sloping
and
supply
upward
sloping
to
reflect
increasing
marginal
costs.
There
are
several
reasons
why
this
neoclassical
depiction
may
not
be
directly
revealing
or
applicable
to
the
commercial
fisheries
market,
as
will
be
discussed
later
in
this
chapter.
But
for
the
moment,
Figure
A13­
5
provides
a
useful
starting
point
for
considering
how
the
measures
of
economic
benefit
 
the
sum
of
producer
and
consumer
surplus
 
might
change
due
to
a
policy
that
shifts
the
supply
curve
outward
from
S
0
to
S
1.










	
























































 


!


"
 



"

#










 
$
$










"


13
Later
in
this
chapter,
an
approach
developed
by
Bishop
and
Holt
(
2003)
to
estimating
post­
harvest
surplus
as
depicted
by
areas
U+
V+
B
is
described.
Also,
note
that
if
the
fishery
in
question
is
being
conducted
under
open
access,
this
means
that
rents
to
the
resource
are
zero
or
very
close
it.
Suppose
furthermore
that
in
this
particular
case
other
rents
(
e.
g.,
rents
to
scarce
fishing
skills
and
knowledge)
are
also
zero.
Now
suppose
that
§
316(
b)
regulations
are
imposed
on
power
plants,
causing
an
increase
in
the
harvest
of
fish.
The
catch
increases,
but
any
effects
in
rents
to
the
resource
are
dissipated
by
entry.
The
effect
of
the
regulation
is
to
increase
consumer
surplus
by
an
amount
comparable
to
areas
U+
V+
B
in
Figure
A13­
9,
but
there
is
no
offsetting
decline
in
producer
surplus
because
there
was
no
producer
surplus
in
the
first
place.







S
0
S
1
D
Y
P
1
P
0
A
Z
B
C
P
1
P
0
W
U
T
X
V
Figure
A13­
5:
Neoclassical
Model
At
baseline,
producer
surplus
is
depicted
by
areas
U+
W,
consumer
surplus
by
area
T,
and
gross
revenues
by
areas
U+
V+
W+
X+
C.
With
an
outward
shift
in
the
supply
curve
to
S
1,
we
observe:


Producer
surplus
becomes
W+
X+
Y,
hence
the
change
in
producer
surplus
is
(
W+
X+
Y)
­
(
U+
W),
which
is
equal
to
X+
Y­
U.


Consumer
surplus
becomes
T+
U+
V+
B,
hence
the
change
in
consumer
surplus
(
which
previously
had
been
area
T
alone)
becomes
U+
V+
B.


Total
change
in
surplus
(
the
sum
of
changes
in
consumer
and
producer
surplus)
is
therefore
equal
to
areas
X+
Y+
V+
B.


Gross
revenues
become
W+
X+
Y+
Z+
C,
hence
the
change
in
revenues
becomes
(
W+
X+
Y+
Z+
C)
minus
(
U+
V+
W+
X+
C),
which
equals
(
Y+
Z)
­
(
U+
V).

There
are
several
observations
to
make
based
on
the
above.
First,
note
that
the
area
U
is
instrumental
in
the
change
of
all
three
measures.
Area
U
is
a
positive
component
of
the
change
in
consumer
(
post­
harvest)
surplus,
but
it
is
subtracted
from
baseline
producer
surplus
to
obtain
a
measure
of
the
change
in
that
measure
of
welfare.
Hence,
in
the
neoclassical
market
model,
part
of
the
gain
in
consumer
surplus
is,
in
effect,
a
transfer
from
producer
surplus.
Area
U
reflects
this
conceptual
transfer
of
surplus,
and
any
empirical
effort
to
estimate
changes
in
surplus
needs
to
ensure
that
if
area
U
is
included
in
the
estimate
of
post­
harvest
surplus,
the
producer
surplus
estimate
should
be
made
net
of
area
U
to
ensure
there
is
no
double
counting.
13
Another
noteworthy
observation
from
the
above
neoclassical
characterization
is
that,
under
some
circumstances,
the
change
in
revenues
may
be
zero
or
even
negative
(
depending
on
how
area
Y+
Z
compares
to
area
U+
V).
Likewise
the
change
in
producer
surplus
can
be
positive
or
negative
(
depending
on
how
X+
Y
compares
to
area
U);
with
the
transfer
of
area
U
from
producer
to
consumer
surplus,
there
are
still
positive
net
gains
in
producer
surplus
if
X+
Y>
U.










	






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






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







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
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

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





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






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







 


!


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


"
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

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



 
$
$





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
14
Given
the
highly
regulated
nature
of
many
fisheries
today,
a
wide
range
of
producer
effects
is
conceivable.
Even
where
revenues
decline
with
a
reduction
in
price,
producer
surplus
could
increase
despite
the
loss
in
revenues.
This
could
occur
if
the
effect
on
price
is
relatively
small
and
the
effect
on
costs
and
revenues
is
relatively
large.
The
only
way
to
know
for
sure
is
to
examine
producer
effects
in
specific
cases
or
try
to
do
a
benefits
transfer
exercise
using
experience
in
real
world
fisheries
as
a
guide.
Simplistic
approaches
(
e.
g.,
assuming
that
there
is
no
consumer
surplus
because
of
offsetting
producer
effects)
are
not
satisfactory
if
there
are
changes
in
prices.







	


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;
)
*





-











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















$






The
discussion
above
regarding
welfare
measures
 
and
how
they
change
with
shifts
in
supply
within
the
neoclassical
framework
 
is
fairly
complex,
even
in
its
simplest
form.
To
estimate
such
changes
in
welfare
as
may
arise
from
the
§
316(
b)
regulation,
the
problem
becomes
even
more
complicated.
Some
of
the
empirical
and
conceptual
complications
are
discussed
here.

In
an
expedited
regulatory
analysis
that
must
cover
a
broad
range
of
fish
species
across
locations
and
fishery
markets
that
span
the
nation,
EPA
must
rely
on
readily
applicable
generalized
approaches
(
rather
than
more
detailed,
market­
specific
assessments)
to
estimate
changes
in
welfare.
Hence,
as
noted
earlier
in
this
chapter,
EPA
must
rely
on
readily
estimated
changes
in
gross
revenues
and
from
there
infer
potential
changes
in
post­
harvest
(
consumer)
and
producer
surplus.
In
turn,
there
are
several
issues
associated
with
how
to
implement
an
expedited
approach
to
accomplish
this.

First,
there
is
the
issue
of
how
to
estimate
the
change
in
gross
revenues.
These
changes
in
revenues
are
the
product
of
the
projected
changes
in
fish
harvests
times
observed
baseline
market
prices.
Thus,
EPA
can
readily
obtain
an
estimate
comparable
to
the
area
Y+
Z+
A+
B
in
Figure
A13­
5.
This
has
been
the
approach
contemplated
by
the
Agency
for
this
rulemaking
to
date.
To
more
suitably
capture
the
impact
of
a
price
change,
EPA
may
in
the
future
attempt
to
apply
an
applicable
estimate
of
price
elasticity
to
obtain
an
estimate
that
better
reflects
the
true
measure
of
the
change
in
gross
revenues
(
i.
e.,
areas
Y+
Z­
U­
V
in
Figure
A13­
5).

Second,
there
is
the
issue
of
how
to
infer
changes
in
post­
harvest
(
consumer)
surplus
based
on
changes
in
revenues.
The
approach
described
by
Bishop
and
Holt
(
2003),
described
in
greater
detail
in
Section
A13­
9,
is
specifically
designed
to
examine
this
benefits
transfer
issue.
Their
empirical
research
 
limited
to
date
to
some
regions
and
fisheries
(
e.
g.,
the
Great
Lakes)
 
suggests
that
the
changes
in
post­
harvest
surplus
may
be
approximated
by
the
estimated
change
in
gross
revenues
(
where
the
latter
is
based
on
holding
price
constant
at
baseline
levels).
EPA
is
working
with
Bishop
and
Holt
to
continue
its
evaluation
of
this
benefits
transfer
approach
and
it
applicability
in
other
regions
and
fisheries.

Third,
there
are
a
series
of
issues
associated
with
how
to
estimate
the
change
in
producer
surplus.
Estimating
the
change
in
producer
surplus
under
a
scenario
in
which
market
forces
produce
a
price
change
is
a
challenging
exercise
for
a
number
of
reasons,
including:


Many
commercial
fishery
markets
do
not
adhere
to
the
usual
assumptions
of
the
neoclassical
model
because
of
regulations
that
establish
harvest
quotas
and/
or
restrict
entry
through
a
permit
system.
These
regulations
typically
are
instituted
to
protect
stocks
that
have
been
or
are
at
risk
of
being
over­
fished.
There
also
may
be
nonregulatory
barriers
to
entry
that
also
affect
this
market
as
well,
such
as
the
high
fixed
costs
and
specialized
knowledge
and
skill
set
required
to
effectively
compete
in
some
fisheries.


Barriers
to
entry,
regardless
of
the
source,
can
have
a
profound
impact
on
the
economic
welfare
analysis.
For
example,
the
neoclassical
model
of
open
access
would
have
rents
driven
to
zero,
but
it
is
more
likely
in
regulated
markets
(
or
a
nonregulated
market
with
economic
barriers
to
entry)
that
there
are
positive
rents
accruing
from
the
fishery
resource
(
not
to
mention
rents
that
accrue
as
well
to
specialized
fishing
skills
and
knowledge).
14

Empirical
evidence
regarding
the
magnitude
of
producer
surplus
is
limited
(
especially
for
purposes
of
inferring
a
relationship
with
gross
revenues).
These
data
are
presented
later
in
this
chapter,
and
suggest
producer
surplus
may
be
from
0%
to
40%
of
gross
revenues.
However,
interpreting
these
data
properly
is
challenging,
for
a
number
of
reasons:

°
Available
empirical
data
pertain
to
average
producer
surplus,
and
EPA's
regulatory
analysis
must
instead
address
changes
in
producer
surplus
at
the
margin.










	




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
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

















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





























 


!


"
 



"

#










 
$
$










"








°
The
portion
of
producer
surplus
that
is
transferred
to
consumers
when
there
is
a
price
reduction
(
represented
by
area
U
in
Figure
A13­
5)
should
not
be
double­
counted
if
it
is
captured
in
the
estimate
of
post­
harvest
surplus
and
also
in
the
estimated
change
in
producer
surplus.
Since
area
U
is
included
in
the
Bishop­
Holt
analysis
of
changes
in
postharvest
surplus,
one
needs
to
ensure
that
area
U
is
not
included
(
e.
g.,
has
been
netted
out
of)
the
applicable
estimate
of
the
change
in
producer
surplus.

°
The
limited
empirical
data
from
the
literature
that
estimates
producer
surplus
and
gross
revenues
for
fisheries
can
be
expanded
to
include
studies
with
data
on
"
normal
profits."
However,
these
estimates
of
normal
profits
need
to
be
adjusted
downward
in
a
logical
manner
to
provide
the
more
suitable
producer
surplus
estimate.
Later
in
this
chapter
some
empirical
evidence
is
provided
to
indicate
the
potential
magnitude
of
such
an
adjustment.

These
issues
are
discussed
at
greater
length
later
in
the
chapter,
but
it
is
important
here
to
address
because
of
the
manner
in
which
the
departure
from
the
neoclassical
model
affects
how
to
interpret
estimates
of
average
producer
surplus
relative
to
changes
expected
at
the
margin.
For
example,
marginal
costs
(
MC)
for
commercial
watermen
may
be
minimal
for
a
small
increase
in
landings
arising
from
a
small
increase
in
harvestable
fish
 
for
small
increases
in
numbers
of
fish
suitable
for
harvest
in
an
area,
small
increases
in
harvest
are
likely
to
be
realized
with
minimal
added
operating
expense
(
i.
e.,
MC
at
or
near
zero).
This
might
arise
where
the
watermen
fill
their
quotas
more
easily,
or
exert
essentially
the
same
level
of
effort
but
come
back
with
a
few
more
fish.
Where
fishing
effort
and
hence
fishing
costs
would
not
change
much,
benefits
(
producer
surplus)
would
equal
the
change
in
total
revenue
or
be
very
close
to
it.
For
larger
changes,
marginal
and
average
costs
could
shift
down.

This
has
implications
when
interpreting
the
empirical
literature
available
on
producer
surplus
as
a
percent
of
gross
revenues.
The
standard
neoclassical
model
always
asserts
increasing
MC
in
the
relevant
range,
so
that
producer
surplus
approaches
zero
with
additional
increments
in
landings.
But
for
the
type
of
situation
that
applies
to
§
316(
b)
 
i.
e.,
with
a
small
change
in
the
harvestable
number
of
fish
 
and
given
the
nature
of
the
commercial
fishery
(
e.
g.,
high
barriers
to
entry
due
to
quotas
or
high
fixed
costs),
the
context
is
likely
to
reflect
a
situation
in
which
costs
decrease
(
e.
g.,
a
shift
downward
in
MC,
and
perhaps
MC
that
are
at
or
near
zero).
If
so,
then
the
argument
that
the
average
estimate
for
producer
surplus
overstates
the
marginal
value
does
not
hold
(
in
fact,
the
opposite
may
be
true
 
average
surplus
could
be
less
than
producer
surplus
at
the
margin).

	


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=


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'



	



.

+


 
!




'
!

+
&
!
'
An
important
portion
of
commercial
fishing
benefits
is
the
producer
surplus
generated
by
the
estimated
marginal
increase
in
landings.
The
level
of
effort
and
data
required
to
model
supply
and
demand
in
every
regional
fishing
market
to
compute
producer
surplus
are
unavailable
to
EPA.
Various
researchers,
however,
have
developed
empirical
estimates
that
can
be
used
to
infer
producer
surplus
for
watermen
based
on
gross
revenues
(
landings
times
wholesale
price).
EPA's
analysis
for
the
proposed
§
316(
b)
Phase
II
rule
was
built
on
evidence
from
economic
literature
and
expert
opinion
that
suggested
that
producer
surplus
values
for
commercial
fishing
range
from
40%
to
70%
of
the
gross
revenues
(
Cleland
and
Bishop,
1984;
Rettig
and
McCarl,
1985;
Huppert,
1990;
Bishop,
personal
communication,
2002;
and
Holt
and
Bishop,
2002).
EPA
is
now
considering
how
to
interpret
this
literature,
particularly
in
the
context
of
a
potential
change
in
market
prices.

Based
on
comments,
a
wider
review
of
the
economic
literature
on
commercial
fishing
was
performed
for
the
NODA.
This
body
of
research
provides
two
types
of
data
that
can
be
used
to
estimate
producer
surplus
as
a
percentage
of
gross
revenues.
These
percentages
can
easily
be
applied
to
changes
in
gross
revenues
expected
under
the
Phase
II
rule
to
estimate
the
changes
in
producer
surplus
expected
under
the
Phase
II
rule.

The
most
common
result
reported
in
the
literature
is
normal
profit.
A
large
number
of
studies
across
a
variety
of
fisheries
estimate
the
revenues
earned
and
costs
borne
by
commercial
fishing
operations.
These
results
can
be
used
to
estimate
normal
profit.
As
defined
here,
normal
profit
is
the
standard
accounting
definition
of
profit,
i.
e.,
total
revenues
earned
minus
the
costs
of
production
(
e.
g.,
fishing
equipment,
fuel,
boat
maintenance,
hired
labor,
bait).
For
example,
assume
a
commercial
fishing
vessel
brings
in
a
total
catch
worth
$
100,000
in
a
given
year.
Also
assume
that
it
incurred
variable
material
costs
of
$
50,000
and
hired
labor
costs
of
$
30,000.
The
normal
profit
received
by
the
owner
would
then
be
$
20,000
($
100,000
­
$
50,000
­
$
30,000
=
$
20,000).

The
more
useful
concept
and
result
reported
in
the
literature
is
producer
surplus
because,
as
described
above,
producer
surplus
is
a
more
appropriate
indicator
of
social
welfare
than
is
profit.
Producer
surplus
equals
normal
profit
minus
the
vessel










	
























































 


!


"
 



"

#










 
$
$




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

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"


15
Most
of
the
estimates
in
this
table
are
a
variation
of
the
following
equation:
1
 
(
variable
cost
/
gross
revenue),
where
the
variable
cost
includes
the
opportunity
cost
of
participating
in
commercial
fishing
for
the
producer
surplus
measures.







owner's
opportunity
cost
of
participating
in
commercial
fishing.
In
other
words,
producer
surplus
nets
out
the
return
to
capital
that
the
owner
of
a
commercial
fishing
operation
could
expect
to
earn
in
another
industry.
Thus,
producer
surplus
is
the
level
of
profits
above
and
beyond
what
the
owner
would
earn
on
his
capital
in
another
industry
(
or
by
investing
in
the
stock
market),
and
is
less
than
or
equal
to
normal
profits.
If
the
owner
of
the
commercial
fishing
vessel
in
the
previous
example
could
expect
to
make
a
$
1,000
return
by
investing
his
capital
in
another
industry,
then
the
producer
surplus
for
this
vessel
owner
would
be
$
19,000
($
100,000
­
$
50,000
­
$
30,000
­
$
1,000
=$
19,000).

While
producer
surplus
is
a
preferable
welfare
measure,
the
literature
review
performed
for
the
NODA
identified
only
four
studies
reporting
results
that
can
be
used
as
direct
estimates
of
producer
surplus.
Available
measures
of
producer
surplus
and
normal
profits
are
reported
as
a
percentage
of
gross
revenue
in
Tables
A13­
6
and
A13­
7,
respectively.
Table
A13­
6
reports
estimates
of
the
more
desirable
producer
surplus,
and
Table
A13­
7
reports
the
more
common
estimates
of
normal
profits.
EPA
calculated
this
percentage
value
from
data
included
in
each
cited
study.
15
Looking
at
the
values
reported
in
the
studies,
it
is
clear
that
no
single
estimate
of
producer
surplus
as
a
percentage
of
gross
revenue
is
appropriate
for
all
regions,
boat
types,
and
species.
For
those
studies
that
most
closely
approximate
producer
surplus
(
Table
A13­
6),
the
rough
estimates
of
producer
surplus
range
from
0%
to
37%,
with
an
average
of
approximately
23%.
Therefore,
EPA
is
considering
a
range
of
0%
to
40%,
and
has
used
this
range
in
the
NODA.

The
estimates
of
normal
profit
span
a
wider
range,
with
results
in
Table
A13­
7
ranging
from
a
low
of
­
5%
to
a
high
of
91.2%.
One
of
the
key
issues
for
using
the
data
on
"
normal
profit'
is
whether
some
adjustment
is
reasonable
to
convert
the
ratios
of
normal
profit
to
revenues
into
suitable
estimates
of
the
ratio
of
producer
surplus
to
revenues.
EPA
has
found
limited
empirical
information
on
which
to
evaluate
the
potential
adjustment
factor.
For
example,
King
and
Flagg
(
1984)
provide
data
for
California
fisheries,
itemizing
various
components
of
fixed
and
variable
costs,
and
also
providing
annual
revenues.
Assuming
that
owners
might
be
able
to
earn
a
7%
real
rate
return
on
all
of
their
fixed
costs
that
might
otherwise
be
invested
productively
elsewhere,
and
netting
these
estimated
returns
from
normal
profit,
the
implied
ratios
of
producer
surplus
to
revenues
are
only
between
0.4%
and
2.6%
lower
than
the
ratios
of
normal
profit
to
revenues,
for
the
seven
fishery
types
evaluated
to
date
by
EPA
from
the
King
and
Flagg
data.
EPA
also
identified
another
study
that
contained
relevant
data
(
Larkin,
Adams
and
Lee,
2000),
and
interpreting
the
data
provided
in
similar
fashion,
the
change
in
ratios
is
only
2.3%
(
consistent
with
the
effect
seen
in
King
and
Flagg).



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



	





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









































	
 






!


"


#
!



#

$










!
%
%










#






&
'

Table
A13­
6:
Summary
of
Research
on
Commercial
Fisher
Producer
Surplus
Measures:
Producer
Surplus
(
Studies
that
Report
Profit
Estimates
that
Include
a
Return
to
the
Owner
as
Part
of
Costs)

Author(
s)
Year
Geographic
Area/
Fishery
Analysis
Year(
s)
Type
Boat(
s)
Fish
Species
Sought
Producer
Surplus
%
of
Gross
Revenuea
Notes
on
Study
Cleland
and
Bishop
1984
Michigan's
Upper
Great
Lakes
1981
Varied
Most
common:

whitefish,
lake
trout,
chubs
28%
Reported
data
used
by
EPA
to
calculate
costs
(
including
return
to
owner)
as
%
of
gross
revenue
 
 
for
5
large
Native
American
fishing
operations
35%
Reported
data
used
by
EPA
to
calculate
costs
(
including
return
to
owner)
as
%
of
gross
revenue
 
 
for
11
moderately
large
Native
American
fishing
operations
27%
Reported
data
used
by
EPA
to
calculate
costs
(
including
return
to
owner)
as
%
of
gross
revenue
 
 
for
36
small
Native
American
fishing
operations
Huppert
and
Squires
1987
U.
S.
Pacific
Coast
1984
Trawlers
Groundfish
37%
Reported
results
used
by
EPA
to
estimate:

1
­
(
profit
+
variable
costs)/(
total
revenue)

Estimates
includes
return
to
owner
as
part
of
costs
Gilbert
1988
North­
East
North
Island,
New
Zealand
1980s
Varied
Snapper
35%
Estimated
economic
surplus
at
dynamic
maximum
economic
yield
Estimates
include
return
to
owner
as
part
of
costs
Hauraki
Gulf,
New
Zealand
1980s
Varied
Red
gurnard
20%

Firth
of
Thames,
New
Zealand
1980s
Varied
Yellow
belly
flounder
15%

Norton
et
al.
1983
U.
S.
South
Atlantic
Coast
1980
Varied
Striped
bass
0%
Estimated
producer
surplus
per
pound
of
fish
and
revenue
per
pound
of
fish
U.
S.
New
England
Coast
1980
Varied
Striped
bass
11%

a
Estimate
includes
returns
to
owners
as
part
of
costs,
and
thus
excludes
them
from
calculation
of
profit.
This
estimate
can
be
considered
a
close
proxy
for
producer
surplus.









	


















































	
 






!


"


#
!



#

$










!
%
%










#






&
'
(
Table
A13­
7:
Summary
of
Research
on
Commercial
Fisher
Producer
Surplus
Measures:
Normal
Profits
(
Studies
That
DO
NOT
Report
Profit
Estimates
that
Include
a
Return
to
the
Owner
as
Part
of
Costs)

Author(
s)
Year
Geographic
Area/
Fishery
Year(
s)

of
Analysis
Type
Boat(
s)
Fish
Species
Sought
Normal
Profit
as
%
of
Gross
Revenuea
Notes
on
Study
Brown
et
al
1976
Columbia
River
1960s
Varied
Salmon
and
steelhead
90%
Citation
from
other
literature
of
percentage
of
gross
revenue
that
goes
to
total
surplus
in
a
salmon
fishery.

Crutchfield
et
al
1982
Tazimina
River
(
Bristol
Bay,
Alaska)
1970s
Varied
Salmon
85%
to
90%
Authors
estimate
net
economic
value
of
a
change
in
availability
of
salmon
in
a
fishery
with
limited
access
and
excess
capacity
King
and
Flagg
1984
California
coast
1982
Trawlers
in
North
CA
Groundfish
67%
Reported
data
by
fish/
boat
type
used
by
EPA
to
calculate
1
­
(
variable
cost
/
gross
revenue)

Costs
do
not
include
return
to
owner
Trawlers
in
South
CA
Groundfish
89%

Trawlers
Shrimp
4%

Seiners
Tuna
45%

King
and
Flagg
(
cont.)
1984
California
coast
1982
Seiners
Wetfish
22%
Reported
data
by
fish/
boat
type
used
by
EPA
to
calculate
1
­
(
variable
cost
/
gross
revenue)

Costs
do
not
include
return
to
owner
Gillnetters
Herring
­
5%

Gillnetters
Other
69%

Small
trollers
Salmon
49%

Large
trollers
Salmon
52%

Crabbers
Salmon
74%

Albacore
Salmon
57%

Longliners
Varied
89%

Varied:
using
hook
&
line
Varied
66%

Varied:
using
pots
Black
Cod
91%

Varied
Crab­
Lobster,

North
74%

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
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





































	
 
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
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


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

"


#
!



#

$






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

!
%
%










#



Table
A13­
7:
Summary
of
Research
on
Commercial
Fisher
Producer
Surplus
Measures:
Normal
Profits
(
Studies
That
DO
NOT
Report
Profit
Estimates
that
Include
a
Return
to
the
Owner
as
Part
of
Costs)

Author(
s)
Year
Geographic
Area/
Fishery
Year(
s)

of
Analysis
Type
Boat(
s)
Fish
Species
Sought
Normal
Profit
as
%
of
Gross
Revenuea
Notes
on
Study



&
'
)
King
and
Flagg
(
cont.)
1984
CA
Coast
1982
Varied
Crab­
Lobster,

South
50%
Reported
data
by
fish/
boat
type
used
by
EPA
to
calculate
1
­
(
variable
cost
/
gross
revenue)

Costs
do
not
include
return
to
owner
Bailboats
Varied
38%

Jigboats
Varied
22%

Diveboats
Varied
59%

Varied:
using
harpoon
Billfish
49%

Rettig
and
McCarl
1985
U.
S.
Varied
Varied
Varied
Varied
50%
Authors
review
several
studies
and
suggest
that
"
variable
costs
may
be
approximately
50%
of
revenues
for
all
commercial
operators"

Estimates
do
not
include
return
to
owner
as
part
of
costs
Usher
1987
Lake
of
the
Woods,

Ontario
1980­

1982
Varied
Varied
28%
Reported
results
used
by
EPA
to
estimate:

(
net
revenue)
/
(
gross
revenue)

Estimate
does
not
include
return
to
owner
as
part
of
costs
Talhelm
1988
Great
Lakes
1985
Varied
Varied
51%
Reported
food
fishery
stats
used
by
EPA
to
calculate:

(
gross
value
minus
harvest
costs)
/
(
total
value)

Estimate
does
not
include
return
to
owner
as
part
of
costs
Larkin
et
al
2000
U.
S.
Atlantic
Coast
1996
Longline
Varied,
includes:
swordfish,

tuna,
sharks,

and
other
55%
Reported
data
used
by
EPA
to
calculate:

(
total
net
revenue)
/
(
total
gross
revenue)

Estimate
does
not
include
return
to
owner
as
part
of
costs
a
Estimate
does
not
include
returns
to
owners
as
part
of
costs,
and
thus
overstates
producer
surplus
by
that
amount.










	
























































 


!


"
 



"

#










 
$
$










"


16
As
an
illustration,
suppose
one
assumes
that,
on
average,
owners
of
commercial
fishing
operations
would
earn
a
producer
surplus
that
is
5%
less
than
normal
profit
(
each
as
a
proportion
of
revenues).
Then,
the
approximate
producer
surplus
for
the
studies
in
Table
A13­
7
would
range
from
­
10%
to
86.1%.

17
For
a
more
detailed
discussion
of
the
difference
in
consumer
surplus
and
CV,
the
reader
is
referred
to
in
Varian
(
1992,
Chapters
7
and
9)
or
any
graduate­
level
microeconomics
text.

18
Bishop
and
Holt
do
not
estimate
changes
in
producer
surplus,
and
indicate
such
changes
need
to
be
estimated
separately
and
then
combined
with
post
harvest
consumer
surplus
results.







While
EPA's
empirical
investigation
into
this
issue
has
been
limited
to
date,
initial
indications
suggest
that
the
use
of
an
adjustment
factor
on
the
order
of
3%
to
5%
may
be
conservative
and
possibly
over­
state
the
differences
for
how
producer
surplus
relates
to
normal
profits.
16
Finally,
EPA
is
also
reviewing
how
to
best
estimate
producer
surplus
in
a
context
of
different
scenarios
and
other
issues.
Issues
EPA
is
assessing,
and
for
which
input
is
sought
from
reviewers,
include
whether
a
different
set
of
producer
surplus
to
revenues
ratios
should
apply
to
contexts
in
which
(
a)
there
is
no
anticipated
change
in
prices
and
(
b)
a
reduction
in
prices
is
anticipated.
One
issue
that
arises
in
the
context
of
price
change
scenarios
is
how
to
ensure
that
transfers
in
surplus
from
producers
to
consumers
are
not
double­
counted
(
i.
e.,
how
to
net
out
such
transfers
from
producer
surplus).










	



	







	







	





















	











	

Estimating
producer
surplus
provides
an
estimate
of
the
benefits
to
commercial
fishermen,
but
significant
benefits
can
also
be
expected
to
accrue
to
final
consumers
of
fish
and
to
commercial
consumers
(
including
processors,
wholesalers,
retailers,
and
middlemen)
if
the
projected
increase
in
catch
is
accompanied
by
a
reduction
in
price.
These
benefits
can
be
expected
to
flow
through
the
tiered
commercial
fishery
market
(
as
described
in
Section
A13­
1
and
in
Bishop
and
Holt,
2003).

Bishop
and
Holt
(
2003)
developed
an
inverse
demand
model
of
six
Great
Lakes
fisheries
that
they
use
to
estimate
changes
in
welfare
as
a
result
of
changes
in
the
level
of
commercial
harvest.
This
flexible
model
that
can
be
used
to
model
welfare
changes
under
a
variety
of
conditions
in
the
fishery.
It
takes
as
an
input
the
expected
change
in
harvest
and
baseline
gross
revenues,
and
provides
as
outputs
the
expected
change
in
gross
revenues
and
change
in
total
compensating
variation
(
CV).

CV
is
the
change
in
income
that
would
be
necessary
to
make
consumers'
total
utility
the
same
as
it
was
before
the
reduction
in
I&
E
losses
resulting
from
the
Phase
II
rule.
This
is
analogous
to
a
measure
of
willingness
to
accept
compensation
in
order
to
forgo
the
improvement.
Conceptually,
CV
is
a
measure
of
welfare
similar
to
consumer
surplus.
The
key
difference
is
that
consumer
surplus
is
calculated
using
the
familiar
demand
function
(
or
curve),
which
defines
the
quantity
demanded
as
a
function
of
price
and
income
(
in
the
simple
example,
Figures
A13­
1
and
A13­
2,
income
is
assumed
to
be
constant).
CV,
on
the
other
hand,
is
calculated
using
a
compensated
demand
function,
which
defines
the
quantity
demanded
as
a
function
of
price
and
utility.
While
consumer
surplus
and
CV
are
generally
very
similar
welfare
measures,
CV
is
considered
to
be
the
true
measure
of
benefits
(
i.
e.,
a
more
consistent
indicator
of
utility),
and
consumer
surplus
is
an
approximation.
The
distinction
between
the
two
is
a
subtle
point
in
welfare
economics;
the
exact
details
are
not
crucial
to
the
analysis.
17
The
key
point
to
note
is
that
estimates
of
CV
from
the
Holt­
Bishop
model
capture
the
benefits
to
final
consumers
and
commercial
consumers
throughout
the
various
markets
in
which
fish
are
bought
and
resold
for
a
given
level
of
harvest.
The
model
output
provides
a
convenient
way
to
estimate
the
benefits
of
an
increase
in
harvest
as
a
percentage
of
gross
revenues,
and
thus
a
tractable
way
to
estimate
the
benefits
of
increased
catch
that
do
not
accrue
to
the
primary
producers.
18
See
Holt
and
Bishop
(
2002)
for
further
detail
on
the
model.

For
the
commercial
benefits
estimated
for
the
proposed
rule,
EPA
used
the
results
of
the
Holt­
Bishop
model,
as
applied
to
a
specific
Great
Lakes
application.
These
results
indicated
that
the
change
in
CV
for
the
Great
Lakes
fisheries
can
be
expected
to
be
approximately
78%
of
the
change
in
total
surplus
(
with
producer
surplus
equal
to
the
remaining
22%).
In
each
case
study
analysis
at
proposal,
EPA
applied
this
22%
estimate
as
a
benefits
transfer
to
all
the
commercial
benefits
estimates
in
the

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case
studies
developed
at
that
time.
To
estimate
consumer
surplus
from
gross
revenues,
EPA
first
estimated
the
change
in
producer
surplus
lost
at
each
case
study
facility
due
to
I&
E
and
then
divided
the
producer
surplus
estimate
by
0.22
to
estimate
total
surplus.
For
example,
if
producer
surplus
was
estimated
to
be
$
1,000,
total
surplus
(
producer
surplus
+
CV)
was
estimated
to
be
$
1,000/
0.22
=
$
4,545.
This
approach
is
undergoing
significant
revision.

Based
on
comments
received
on
the
commercial
benefits
analysis
for
the
proposed
Phase
II
rule,
EPA
has
worked
with
Dr.
Bishop
to
re­
assess
the
suitability
of
using
the
results
from
Holt
and
Bishop
(
2002)
in
a
benefits
transfer.
EPA
has
determined
that
the
magnitude
of
the
changes
in
commercial
catch
modeled
in
the
Holt
and
Bishop
paper
is,
in
most
cases,
larger
than
the
magnitude
of
the
expected
changes
as
a
result
of
the
Phase
II
regulations.
Since
the
magnitude
of
the
change
assumed
in
the
Holt
and
Bishop
(
2002)
paper
is
much
larger,
the
benefits
may
be
quite
different.
To
address
this
issue,
additional
analyses
were
conducted
to
explore
the
impacts
on
surplus
measures
for
more
moderate
changes
in
fishery
conditions,
and
Bishop
and
Holt
(
2003)
reports
on
the
findings
of
the
re­
estimation
of
their
Great
Lakes
model
in
terms
that
related
economic
surplus
to
levels
of
gross
revenues.
EPA
is
exploring
the
possibility
of
using
new
model
results
from
Bishop
and
Holt
to
estimate
the
change
in
CV
as
a
percentage
of
the
expected
change
in
gross
revenue
(
rather
than
based
on
the
change
in
producer
surplus,
as
was
done
at
proposal),
if
changes
in
market
prices
are
expected.

In
their
recent
work
Bishop
and
Holt
(
2003)
observe
that,
as
a
general
rule
of
thumb,
in
the
fisheries
they
model
the
change
in
CV
as
a
percentage
of
the
change
in
gross
revenues
is
more
or
less
linearly
related
to
change
in
catch.
In
other
words,
a
10%
increase
in
catch
as
a
result
of
the
Phase
II
rule
would
be
expected
to
produce
an
increase
in
CV
equal
to
approximately
a
10%
of
the
change
in
gross
revenues.
As
an
example,
if
the
Phase
II
rule
increases
the
catch
of
a
species
by
10%
and
the
gross
value
of
the
additional
catch
is
$
100,000,
then
the
increase
in
CV
would
be
$
10,000.

If
 
after
further
analysis
 
this
basic
relationship
found
by
Bishop
and
Holt
for
the
Great
Lakes
is
found
to
be
a
reasonable
approximation
across
other
regions
and
species,
it
may
be
used
in
benefits
transfer
for
the
final
analysis.
If
not,
a
different
value
will
be
developed
and
applied
in
a
similar
manner.

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As
with
many
activities,
commercial
fishing
provides
benefits
that
are
not
measured
in
the
value
of
the
catch.
Fishing
is
hard
work.
It
involves
strenuous
outdoor
work,
long
hours,
and
lengthy
trips
to
sea,
often
in
hazardous
weather
conditions.
Fishing
is
also
dangerous
work.
"
Fishing
has
consistently
ranked
as
the
most
deadly
occupation
since
1992,"
when
the
Bureau
of
Labor
Statistics
(
BLS)
started
publishing
fatality
rates
by
occupation
(
Drudi,
1998,
p.
1).
In
addition,
the
BLS
Occupational
Handbook:
Fishers
and
Fishing
Vessel
Operators
(
BLS,
2002)
predicts
that
"
employment
of
fishers
and
fishing
vessel
operators
is
expected
to
decline
through
the
year
2010.
These
occupations
depend
on
the
natural
ability
of
fish
stocks
to
replenish
themselves
through
growth
and
reproduction,
as
well
as
on
governmental
regulation
of
fisheries.
Many
operations
are
currently
at
or
beyond
maximum
sustainable
yield,
partially
because
of
habitat
destruction,
and
the
number
of
workers
who
can
earn
an
adequate
income
from
fishing
is
expected
to
decline."

In
spite
of
this
evidence,
individuals
still
express
a
desire
to
fish,
perhaps
even
because
of
the
hardships
and
challenges
of
the
job.
Studies
on
why
fishermen
choose
to
fish
have
determined
that
income
is,
not
surprisingly,
the
primary
reason
for
participating
in
commercial
fishing.
Fishermen
fish
to
support
themselves
and
their
families,
and
generally
earn
more
in
fishing
than
they
would
in
other
occupations.
There
are
other
important
factors,
though,
including
the
importance
of
fishing
to
the
way
of
life
in
small,
coastal
towns
(
not
unlike
the
importance
of
farming
to
many
rural
towns
throughout
the
United
States);
the
belief
that
fishing
helps
the
U.
S.
economy;
and
identity,
i.
e.,
people
opt
to
work
in
commercial
fishing
because
it
provides
enjoyment
and
because
it
is
an
integral
part
of
how
they
identify
themselves
psychologically
and
socially
(
Berman
et
al,
1997;
Townsend,
1985;
Smith,
1981).

Research
in
the
economic
literature
indicates
that
some
fishermen
opt
to
remain
in
the
fishing
industry
despite
the
ability
to
make
higher
incomes
in
other
industries.
Some
economists
have
suggested
that
there
exists
a
worker
satisfaction
bonus
that
can,
at
least
in
theory,
be
measured
and
should
be
included
in
cost­
benefit
analyses
when
making
policy
decisions.
(
Anderson,
1980).
One
study
identified
in
a
cursory
literature
review
of
this
topic
also
found
evidence
in
the
Alaskan
fisheries
that
as
many
as
29.5%
of
all
vessels
across
14
fisheries
from
1975
to
1980
earned
net
incomes
that
were
lower
than
the
income
they
could
receive
from
selling
their
fishing
permit.
The
author
concluded
that
"
this
pattern
of
apparent
losses
seems
to
confirm
much
of
the
casual
observation
that
is
the
source
of
speculation
that
non­
pecuniary
returns
are
a
significant

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factor
in
commercial
fishing.
It
is
thought
that
these
financial
losses
are
accepted
only
because
they
are
offset
by
non­
money
gains"
(
Karpoff,
1985).

Because
the
Alaskan
fisheries
exist
under
much
different
conditions
than
those
in
the
rest
of
the
United
States,
it
would
be
a
mistake
to
assume
that
nearly
30%
of
U.
S.
fishing
vessels
earn
incomes
less
than
the
value
of
their
fishing
permits.
However,
based
on
the
cursory
review
of
the
commercial
fishing
literature
there
is
evidence
that
commercial
fishermen
gain
nonmonetary
benefits
from
their
work.
Despite
the
existence
of
these
nonmonetary
benefits
in
the
commercial
fishing
sector,
there
is
little
research
that
has
provided
defensible
methods
for
estimating
the
additional
nonmonetary
benefits
that
may
be
accrue
to
commercial
fishermen
as
a
result
of
the
Phase
II
regulations.
Thus,
the
omission
of
these
nonmonetary
benefits
noted
here,
but
no
estimates
will
be
included
in
the
benefits
analyses.

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EPA
will
estimate
the
commercial
benefits
expected
under
the
final
Phase
II
regulations
in
the
following
steps.
The
general
method
is
to
estimate
total
losses
under
current
I&
E
conditions
(
or
the
total
benefits
of
eliminating
all
I&
E)
in
steps
1
through
3.
Then,
in
step
4,
EPA
will
apply
the
estimated
percent
reduction
in
I&
E
to
estimate
the
benefits
expected
under
each
regulatory
option.
Each
step
will
be
performed
for
each
region
in
the
final
analysis:
the
North
Atlantic,
Mid­
Atlantic,
South
Atlantic,
Gulf
of
Mexico,
Northern
California,
Southern
California,
and
Great
Lakes,
and
the
internal
United
States.

The
steps
used
to
estimate
regional
losses
and
benefits
are
as
follows:

1.
Estimate
losses
to
commercial
harvest
(
in
pounds
of
fish)
attributable
to
impingement
and
entrainment
under
current
conditions.
EPA
models
these
losses
using
the
methods
presented
in
Chapter
A5
of
Part
A
of
the
§
316(
b)
Phase
II
Case
Study
Document.
Changes
in
these
methods
for
the
NODA
and
subsequent
analyses
are
provided
in
the
NODA
(
see
sections
on
"
Case
Study
Corrections
and
Clarifications"
and
"
Impingement
and
Entrainment
Methods").
The
basic
approach
is
to
apply
a
linear
stock
to
harvest
assumption,
such
that
if
10%
of
the
current
commercially
targeted
stock
is
harvested,
then
10%
of
the
commercially
targeted
fish
lost
to
I&
E
would
also
have
been
harvested
absent
I&
E.
The
percentage
of
fish
harvested
is
based
on
data
on
historical
fishing
mortality
rates.

2.
Estimate
gross
revenue
of
lost
commercial
catch.
The
approach
EPA
uses
to
estimate
the
value
of
the
commercial
catch
lost
due
to
impingement
and
entrainment
relies
on
landings
and
dockside
price
($/
lb)
as
reported
by
NMFS
for
the
period
1991­
2001.
These
data
are
used
to
estimate
the
revenue
of
the
lost
commercial
harvest
under
current
conditions
(
i.
e.,
the
increase
in
gross
revenue
that
would
be
expected
if
all
impingement
and
entrainment
impacts
were
eliminated).

3.
Estimate
lost
economic
surplus.
The
conceptually
suitable
measure
of
benefits
is
the
sum
of
any
changes
in
producer
and
consumer
surplus.
The
methods
used
for
estimating
the
change
in
surplus
depend
on
whether
the
physical
impact
on
the
commercial
fishery
market
appears
sufficiently
small
such
that
it
is
reasonable
to
assume
there
will
be
no
appreciable
price
changes
in
the
markets
for
the
impacted
fisheries.

3a)
Estimate
lost
surplus
when
no
change
in
price
anticipated.
For
the
two
regions
analyzed
to
date
by
EPA,
it
is
reasonable
to
assume
no
change
in
price,
which
implies
that
the
welfare
change
is
limited
to
changes
in
producer
surplus.
This
change
in
producer
surplus
is
currently
assumed
to
be
equivalent
to
a
portion
of
the
change
in
gross
revenues,
as
developed
under
step
2.
Currently,
EPA
is
using
a
range
of
0%
to
40%
of
the
gross
revenue
losses
estimated
in
step
2
as
a
means
of
estimating
the
change
in
producer
surplus.
This
is
based
on
a
review
of
empirical
literature
(
restricted
to
only
those
studies
that
compared
producer
surplus
to
gross
revenue)
and
is
consistent
with
recommendations
made
in
comments
on
the
EPA
analysis
at
proposal.
This
represents
a
change
from
the
analysis
for
the
proposed
rule,
which
assumed
a
range
of
40%
to
70%.

EPA
will
continue
to
review
this
approach
for
the
final
analysis.
In
particular,
EPA
believes
this
is
a
conservative
approach
to
estimating
producer
surplus
when
there
is
no
anticipated
price
changes.
EPA's
Guidelines
for
Preparing
Economic
Analyses
(
2003)
(
EPA
240­
R­
00­
003)
describes
options
for
estimating
ecological
benefits
for
fisheries,
and
notes
that
"
if
changes
in
service
flows
are
small,
current
market
prices
can
be
used
as
a
proxy
for
expected
benefit
.
.
.
a
change
in
the
commercial
fish
catch
might
be
valued
using
the
market
price
for
the
affected

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
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
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
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

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
	
species."
This
statement
indicates
that
100%
of
gross
revenue
change,
based
on
current
prices,
may
be
a
suitable
measure
of
value.

3b)
Estimate
economic
surplus
if
a
change
in
price
anticipated.
EPA
currently
relies
on
the
method
in
Step
3a
for
estimating
benefits
for
the
two
regional
examples
in
this
NODA,
because
no
changes
in
price
are
anticipated
in
those
markets.
However,
if
the
impact
on
commercial
fisheries
in
other
regions
analyzed
for
the
final
regulation
is
sufficiently
large
that
a
change
in
market
prices
becomes
a
likely
outcome,
then
a
more
complex
approach
may
be
considered
by
the
Agency.
This
approach
may
include
estimates
of
consumer
and
other
post­
harvest
surplus,
plus
any
net
change
in
producer
surplus
(
noting
that
one
of
the
important
aspects
would
be
to
net
out
potential
transfers
of
surplus
from
producers
to
consumers,
to
avoid
potential
double­
counting).

EPA
will
continue
to
review
this
approach
for
the
final
analysis,
and
in
particular
is
examining
and
soliciting
comment
on
using
empirical
information
from
the
literature
to
(
1)
estimate
price
change
for
revenue
calculations
and
netting
out
surplus
transfers,
(
2)
adjust
existing
estimates
of
normal
profit
so
that
they
might
better
reflect
the
more
suitable
measure
of
producer
surplus,
and
(
3)
model
and
interpret
changes
in
costs
to
harvesters
as
a
result
of
increasing
the
number
of
harvestable
fish
(
e.
g.,
how
to
interpret
data
on
average
producer
surplus
within
the
context
of
changes
in
harvest
at
the
margin,
especially
in
regulated
fisheries
and/
or
where
marginal
costs
may
be
minimal
and/
or
shifting
downward).

4.
Estimate
increase
in
surplus
attributable
to
the
Phase
II
regulations.
Once
the
commercial
surplus
losses
associated
with
impingement
and
entrainment
under
baseline
conditions
have
been
estimated
according
to
the
approaches
outlined
in
steps
2
and
3,
EPA
estimates
the
percentage
reduction
in
impingement
and
entrainment
at
each
in­
scope
facility
under
each
regulatory
option.
This
analysis
is
conducted
for
Northern
California
and
the
North
Atlantic
for
this
NODA
and
will
be
conducted
for
all
regions
for
the
final
rule.



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




	
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

EPA
reviewed
the
methods
used
to
estimate
the
benefits
expected
to
accrue
to
producers
and
consumers
in
commercial
fish
markets.
Based
on
this
review
and
on
comments
received
on
the
benefits
analysis
for
the
proposed
rule,
EPA
is
changing
some
of
the
methods
used
to
estimated
commercial
benefits.
EPA
believes
that
these
changes
will
improve
the
accuracy
and
reduce
the
uncertainty
of
the
estimates.

Some
uncertainties,
of
course,
will
remain.
Table
A13­
8
summarizes
the
caveats,
omissions,
biases,
and
uncertainties
known
to
affect
the
estimates
that
will
be
developed
for
the
final
benefits
analysis.

Table
A13­
8:
Caveats,
Omissions,
Biases,
and
Uncertainties
in
the
Commercial
Benefits
Estimates
Issue
Impact
on
Benefits
Estimate
Comments
Change
in
commercial
landings
due
to
I&
E
Uncertain
The
economic
analysis
described
in
the
chapter
relies
on
projected
changes
in
harvest
developed
using
data
and
methods
described
in
the
NODA
and
elsewhere.
These
projected
changes
in
harvest
may
be
underestimated
because
neither
cumulative
impacts
of
I&
E
over
time,
nor
interactions
with
other
stressors,
are
considered.

Estimates
of
commercial
harvest
losses
due
to
I&
E
under
current
conditions
not
region/
species
specific
Uncertain
EPA
estimates
the
impact
of
I&
E
in
the
case
study
analyses
based
on
data
provided
by
the
facilities.
The
most
current
data
available
were
used.
However,
in
some
cases
these
data
are
20
years
old
or
older.
Thus,
they
may
not
reflect
current
conditions.

Effect
of
change
in
stocks
on
number
of
landings
not
considered
Uncertain
EPA
assumes
a
linear
stock
to
harvest
relationship,
that
a
13%
change
in
stock
would
have
a
13%
change
in
landings;
this
may
be
low
or
high,
depending
on
the
condition
of
the
stocks.
Region­
specific
fisheries
regulations
also
will
affect
the
validity
of
the
linear
assumption.

Effect
of
uncertainty
in
estimates
Uncertain
EPA
assumes
that
NMFS
landings
data
are
accurate
and

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Table
A13­
8:
Caveats,
Omissions,
Biases,
and
Uncertainties
in
the
Commercial
Benefits
Estimates
Issue
Impact
on
Benefits
Estimate
Comments






of
commercial
landings
and
prices
unknown
complete.
In
some
cases
prices
and/
or
quantities
may
be
reported
incorrectly.

Estimates
of
producer
surplus
as
percentage
of
gross
landings
not
region/
species
specific
Uncertain
EPA
currently
estimates
that
the
increase
in
producer
surplus
as
a
result
of
the
rule
will
be
between
0%
and
4%
of
the
estimated
change
in
gross
revenues.
The
research
used
to
develop
this
range
is
not
region
specific,
thus
the
true
value
may
fall
outside
this
range
(
higher
or
lower)
for
some
regions
and
species.

Estimates
of
surplus
in
tiered
markets
as
percentage
of
gross
landings
not
region/
species
specific
Uncertain
If
applicable,
EPA
will
estimate
the
increase
in
surplus
in
tiered
markets
as
a
proportion
of
the
estimated
change
in
gross
revenues.
The
research
used
to
develop
this
range
does
not
exactly
match
all
the
regions
in
the
analysis,
thus
the
true
value
may
fall
outside
this
range
(
higher
or
lower)
for
some
regions
and
species.








average
cost:
the
total
cost
of
production
divided
by
the
total
output.

demand
curve
/
demand
function:
a
graphical,
or
mathematical,
representation
of
how
quantity
of
a
good
demanded
depends
on
the
price
of
the
good
and
utility,
all
other
factors
held
constant;
also
known
as
a
Hicksian
demand
function
or
curve.

compensating
variation
(
CV):
the
change
in
income
that
is
exactly
sufficient
to
leave
utility
unaffected
by
a
change
in
the
commercial
harvest
and
the
resulting
change
in
price
as
a
result
of
decreased
I&
E.

consumer
surplus:
the
extra
value
that
individuals
receive
from
consuming
a
good
above
what
they
pay
for
it.

current
potential
yield
(
CPY):
the
potential
catch
that
can
be
taken
depending
on
the
current
stock
abundance
and
prevailing
ecosystem
considerations.

demand
curve
/
demand
function:
a
graphical,
or
mathematical,
representation
of
how
quantity
of
a
good
demanded
depends
on
the
price
of
the
good
and
income,
all
other
factors
held
constant.

economic
profit:
the
difference
between
a
firm's
total
revenues
and
its
total
costs,
where
a
level
of
return
to
the
owner's
labor
and
capital
equal
to
that
which
could
be
attained
in
another
industry
is
included
as
a
cost;
i.
e.,
the
profit
the
owner
earns
above
and
beyond
what
she
would
expect
to
earn
in
another
industry;
analogous
to
producer
surplus.

inverse
demand
curve:
a
mathematical,
or
graphical,
representation
of
how
the
price
of
a
good
depends
on
the
quantity
of
the
good
demanded,
all
other
factors
held
constant.

long
term
potential
yield
(
LTPY):
the
maximum
long­
term
average
catch
that
can
be
achieved
from
the
resource.
This
term
is
analogous
to
the
concept
of
maximum
sustainable
yield
(
MSY)
in
fisheries
science.

marginal
cost:
the
additional
cost
of
producing
one
additional
unit
of
output.

maximum
sustainable
yield
(
MSY):
the
highest
average
yield
over
time
that
does
not
result
in
a
continuing
reduction
in
stock
abundance.

normal
profit:
the
difference
between
a
firm's
total
revenues
and
its
total
costs,
where
the
return
to
the
owner's
labor
and
capital
is
not
included
as
a
cost.



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


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
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
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
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
 
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$




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


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


opportunity
cost:
the
cost
of
a
good
or
service
as
measured
by
the
alternative
uses
that
are
foregone
by
producing
the
good
or
service.

price
elasticity
of
demand:
the
percentage
change
in
demand
in
response
to
a
percent
change
in
price.

producer
surplus:
the
extra
value
that
producers
get
for
a
good
in
excess
of
the
costs
(
including
a
return
to
the
owner's
labor
and
capital)
of
producing
the
good;
analogous
to
economic
profit.

recent
average
yield
(
RAY):
yield
measured
as
"
reported
fishery
landings
averaged
for
the
most
recent
3­
year
period
of
workable
data,
usually
1995­
1997"
(
NMFS,
1999,
p.
4).











Anderson,
L.
G.
1980.
"
Necessary
Components
of
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in
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and
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858­
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M.,
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








	






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
















































 


!


"
 



"

#










 
$
$










"








Larkin,
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