ECONOMIC
ANALYSIS
OF
PESTICIDES
EMERGENCY
EXEMPTION
PROCESS
REVISIONS
Prepared
by:

BIOLOGICAL
AND
ECONOMIC
ANALYSIS
DIVISION
OFFICE
OF
PESTICIDE
PROGRAMS
September
12,
2005
U.
S.
Environmental
Protection
Agency
1200
Pennsylvania
Ave,
NW
Washington,
DC
20640
Table
of
Contents
I.
Background
for
the
Proposed
Rule:
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1
A.
Overall
Approach:
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1
B.
Reason
for
the
Proposed
Changes
Are:
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2
C.
Description
of
the
Current
Revenue
Variation
Method
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3
D.
Description
of
the
Proposed
Loss­
based
(
Tiered)
Approach:
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1.
Tier
Thresholds
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3
2.
Basis
for
Tier
Thresholds
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4
E.
Statutory
and
Regulatory
Requirements:
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6
1.
Statutory
Provisions:
FIFRA,
Section
18
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6
2.
Regulatory
Provisions:
40
CFR,
Part
166
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6
II.
Methodology
of
Economic
Analysis
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6
A.
Purpose
of
EA
(
economic
analysis)
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B.
Significant
Economic
Loss
(
SEL)
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7
C.
Re­
certification
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III.
Results
of
the
Analysis
of
Proposed
Method
for
Determining
SEL
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A.
Summary
of
exemption
requests.
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8
B.
Dataset
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9
C.
Losses
Qualifying
as
a
SEL
under
the
Revenue
Variation
Method.
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D.
Cost
Savings
as
a
Result
of
Changing
Data
Requirements
for
Determining
SEL
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12
E.
Comparison
of
Findings
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15
IV.
Results
of
Analysis
of
Re­
certification
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17
A.
Applicant
(
States)
Savings
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B.
EPA
Savings
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17
C.
Total
Savings
from
Re­
certification.
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V.
Combined
Savings
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18
VI.
Information
Collection
Request
(
ICR)
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18
VII.
Limitations
of
Analysis
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19
A.
Total
Savings.
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B.
Average
Savings.
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19
C.
Unrealized
Savings.
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D.
Time
Savings.
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19
E.
Conclusions.
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19
VIII.
Conclusions
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20
A.
Benefits
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B.
Impacts.
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20
IX.
References
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20
1
Economic
Analysis
of
Pesticides
Emergency
Exemption
Process
Revisions
I.
Background
for
the
Proposed
Rule:
1
EPA
is
proposing
several
revisions
to
the
regulations
at
40
CFR
part
166,
which
govern
such
2
FIFRA
section
18
emergency
exemptions.
The
most
significant
of
these
proposed
improvements
are
3
two
revisions
intended
to
streamline
and
improve
the
application
and
review
process
by
reducing
the
4
burden
to
both
applicants
and
the
EPA,
allowing
for
quicker
decisions
by
the
Agency,
and
providing
5
for
more
equitable
determinations
of
"
significant
economic
loss"
as
the
basis
for
an
emergency.
6
These
two
proposals
are
currently
being
employed
in
limited
pilot
programs.
The
first
would
allow
7
applicants
for
certain
exemptions
to
re­
certify
that
the
emergency
conditions,
which
initially
qualified
8
for
an
exemption,
continue
to
exist.
The
second
proposal
would
allow
greater
flexibility
in
the
9
submission
of
data
to
demonstrate
significant
economic
loss
(
SEL)
and
corresponds
to
a
change
in
10
methodology
to
make
that
determination.
The
new
methodology
focuses
on
the
loss
compared
to
11
current
economic
and
agronomic
conditions
rather
than
conditions
over
the
past
five
years.
In
12
addition,
EPA
is
proposing
to
revise
the
regulations
to
clarify
that
quarantine
exemptions
may
be
used
13
for
control
of
invasive
species,
and
to
update
or
revise
certain
administrative
aspects
of
the
14
regulations.
All
of
these
proposed
revisions
can
be
accomplished
without
compromising
protections
15
for
human
health
and
the
environment.
16
A.
Overall
Approach:
17
This
is
primarily
a
cost
saving
rule,
reducing
burden
on
states
and
on
EPA.
In
conducting
the
18
economic
analysis
the
Agency
is
analyzing
the
benefits
and
impacts
of
the
proposed
rule.
The
benefits
19
of
the
proposed
rule
are
the
cost
savings
from
both
the
re­
certification
and
reduction
in
data
20
requirements
by
using
the
loss­
based
method.
The
impacts
of
the
proposed
rule
are
analyzed
by
21
comparing
the
outcomes
of
SEL
findings
for
both
the
current
method
and
the
proposed
method.
22
1.
Benefits 
estimating
cost
savings.
The
re­
certification
part
of
the
rule
reduces
costs
for
both
23
states
and
EPA
with
respect
to
submitting
and
reviewing
section
18
packages.
The
new
24
data
requirements
for
demonstrating
a
SEL
do
not
demand
historical
information,
25
particularly
the
more
onerous
requirement
for
yearly
production
costs.
Because
the
26
proposed
SEL
method
uses
a
tiered
screening
system,
states
may
be
able
to
submit
less
data
27
and
will
in
no
case
need
to
submit
more.
This
EA
estimates
how
often
a
cost
savings
event
28
occurs
and
adds
up
the
reduced
burden
using
the
section
18
ICR
estimates
of
burden.
The
29
analysis
demonstrates
that
the
proposed
rule
would
result
in
considerable
cost
savings
to
30
the
applicants
and
some
savings
to
EPA.
31
2.
Impacts 
comparing
findings
of
SEL
(
significant
economic
loss)
under
the
current
and
32
proposed
methods
for
determining
SEL.
The
analysis
demonstrates
that
there
would
be
no
33
change
in
the
overall
likelihood
of
a
SEL
finding,
although
there
would
be
different
SEL
34
findings
in
about
12%
of
the
requests.
EPA
believes
that
these
differences
would
be
more
35
equitable
than
the
current
findings.
36
2
B.
Reason
for
the
Proposed
Changes
Are:
37
1.
Re­
certification:
The
Agency
believes
that
most
candidates
for
re­
certification
can
be
38
determined
relatively
quickly.
This
will
allow
applicants
for
certain
repeat
exemptions
to
39
re­
certify
that
the
emergency
conditions,
which
initially
qualified
for
an
exemption,
continue
40
to
exist.
The
applicants'
own
certification
that
the
emergency
situation
is
ongoing,
along
41
with
their
incorporation
by
reference
of
their
earlier
full
application,
will
take
the
place
of
42
the
submission
of
data
generally
required
to
support
a
repeat
request
for
an
emergency
43
exemption.
In
this
way,
the
burden
associated
with
the
application
process
for
select
repeat
44
requests
will
be
significantly
reduced.
In
addition,
re­
certification
will
often
allow
EPA
to
45
make
quicker
decisions
on
exemption
requests.
46
2.
Determination
of
Significant
Economic
Loss
(
SEL):
In
developing
a
more
appropriate
47
methodology
for
determining
SEL,
the
Agency
considered
three
factors:
48
a.
To
focus
the
determination
of
losses
due
to
emergencies
caused
by
urgent
and
non­
49
routine
pest
problems
on
existing
conditions.
The
current
methodology
may
confound
50
the
issue
with
past
price
volatility
and
may
result
in
an
inappropriate
criterion
of
51
significant
economic
loss.
Historical
data
have
been
used
to
provide
a
baseline
for
52
estimating
both
normal
profits
and
variation
in
the
absence
of
the
emergency
condition
53
for
the
affected
area.
However:
54
(
1)
Historical
data
may
not
be
representative
of
existing
physical
and
economic
55
conditions.
While
unusual
weather
conditions
may
lead
to
pest
outbreaks,
the
56
weather
conditions
themselves
should
not
influence
the
calculation
or
significance
57
of
loss.
Similarly,
many
crops
have
demonstrated
high
price
variability
or
58
significant
changes
in
price
over
the
past
several
years.
59
(
2)
Historical
data
are
often
affected
by
the
emergency
condition.
Pest
pressure
60
related
to
the
emergency
condition
in
previous
years
(
even
if
not
significant)
may
61
reduce
revenues
and
distort
the
estimation
of
baseline
revenues
and
variation.
62
For
example,
historical
data
often
reflect
increasing
pesticide
resistance
that
may
63
have
begun
before
an
emergency
exemption
was
requested,
but
where
the
64
resistance
later
becomes
the
basis
for
requesting
the
exemption.
In
the
case
of
65
repeat
emergency
exemptions,
the
historical
data
are
affected
by
both
the
66
revenue­
decreasing
emergency
condition
and
revenue­
increasing
use
of
the
67
requested
pesticide,
which
will
not
necessarily
equally
offset
each
other.
68
(
3)
Historical
data
may
be
unavailable
in
many
states
for
minor
and
new
crops.
69
(
4)
The
focus
on
historical
data
may
make
it
difficult
to
demonstrate
some
pest­
70
related
losses.
While
pest
damage
usually
results
in
a
loss
in
quantity
harvested,
71
sometimes
the
losses
are
due
to
reduced
quality
of
the
product
that
decrease
the
72
price
received
by
growers.
Damage
to
orchards
and
other
perennial
crops
may
73
result
in
losses
over
several
years.
These
types
of
losses
have
not
fit
well
under
74
the
present
method
of
analysis.
75
b.
To
increase
transparency
and
establish
more
consistent
measures
of
economic
loss.
In
76
the
current
revenue
variation
method,
crops
with
high
yield
variability
(
such
as
many
77
non­
irrigated
crops)
or
with
high
price
variability
must
have
high
pest
losses
to
meet
78
the
criterion
of
SEL
compared
to
crops
with
stable
yields
and
prices.
Therefore,
this
79
3
criterion
may
be
unfair
to
farmers
already
facing
high
yield
and
price
risk
while
80
inappropriately
granting
exemptions
to
farmers
of
low­
risk
crops
with
minor
pest
81
losses
.
82
c.
To
reduce
the
burden
of
data
collection
and
analysis
on
the
part
of
the
states
and
the
83
Agency.
In
many
cases
a
decision
can
be
made
with
less
information,
thus
speeding
84
decisions
for
these
cases
and
permitting
more
resources
to
be
devoted
to
more
85
complex
situations.
86
C.
Description
of
the
Current
Revenue
Variation
Method
87
The
revenue
variation
method
defines
an
economic
loss
as
significant
if
it
would
cause
expected
88
net
revenue
to
fall
below
the
minimum
historical
net
revenue
over
a
period
of
typically
five
years.
In
89
some
cases,
past
yields
and/
or
prices
may
be
considered
to
be
outside
normal
bounds.
For
example,
90
drought
may
reduce
yields
such
that
one
year
in
the
data
cannot
be
considered
typical.
Analysts
may
91
use
judgement
to
eliminate
outliers
from
the
determination
of
the
minimum
net
revenue.
92
The
economic
consequences
of
the
emergency
are
determined
separately.
In
most
cases,
yield
93
losses
are
predicted,
but
the
impacts
may
also
include
quality
losses
or
increases
in
pest
control
costs.
94
For
example,
an
unusual
pest
outbreak
might
be
controlled
by
multiple
applications
of
a
registered
95
pesticide
when
typically
only
one
application
would
be
necessary.
If
these
predicted
losses
would
96
result
in
net
revenue
that
is
lower
than
the
lowest
net
revenue
over
the
past
five
years
(
after
97
eliminating
outliers)
then
these
losses
are
considered
significant.
98
D.
Description
of
the
Proposed
Loss­
based
(
Tiered)
Approach:
99
The
loss­
based
approach
uses
the
same
methodology
to
calculate
the
economic
consequences
of
100
an
unusual
pest
outbreak.
States
will
still
have
to
submit
data
to
demonstrate
the
emergency
nature
101
of
the
outbreak
and
the
expected
losses
in
quantity,
quality
and/
or
additional
production
costs.
The
102
proposed
approach
would
provide
applicants
with
greater
flexibility
in
establishing
the
baseline
103
scenario.
Even
though
5
years
of
historical
economic
data
are
not
required
under
the
proposed
104
approach,
applicants
may
continue
to
utilize
historical
data
to
establish
baseline
gross
and
net
105
revenues
from
which
to
estimate
economic
losses
in
Tiers
2
and
3
described
below.
The
new
106
approach
imposes
a
standard
criterion
for
determining
the
significance
of
that
loss,
rather
than
107
comparing
losses
to
past
revenues.
The
goal
of
the
criterion
is
to
compare
losses
to
expected
farm
108
income
in
a
manner
that
can
be
easily
measured.
Further,
successive
screening
levels
have
been
109
chosen
that
will
permit
situations
that
clearly
qualify
to
be
resolved
quickly
and
with
a
minimum
of
110
data.
111
1.
Tier
Thresholds
112
Tier
1,
Yield
loss
$
20%:
The
first
screen
is
based
on
crop
yield
loss
and
is
a
quantity­
based
113
measure.
EPA
will
conclude
that
a
significant
economic
loss
will
occur
if
the
projected
yield
loss
due
114
to
the
emergency
condition
is
verified
to
be
20%
of
expected
yields
or
greater.
The
yield
loss
115
threshold
in
Tier
1
will
be
the
same
for
all
crops
and
regions.
This
threshold
is
set
at
a
level
such
that
116
a
loss
which
exceeds
the
threshold
would
generally
also
meet
the
thresholds
in
Tiers
2
and
3,
if
the
117
additional
economic
data
were
submitted
and
analyzed.
Therefore,
for
large
yield
losses
it
is
not
118
4
necessary
to
separately
estimate
economic
loss,
which
requires
detailed
economic
data.
Yield
losses
119
are
measured
as
the
difference
between
expected
yields
in
the
absence
of
the
emergency
and
yields
120
under
the
emergency
condition
when
using
the
best
available,
registered
alternative.
121
Tier
2,
Economic
Loss
$
20%
of
Gross
Revenues:
For
situations
with
yield
losses
that
do
not
122
meet
the
yield
loss
criterion
for
Tier
1,
EPA
will
evaluate
estimates
of
economic
loss
as
a
percent
of
123
gross
revenue
in
Tier
2.
Economic
losses
result
not
only
from
yield
losses,
but
also
from
causes
such
124
as
quality
losses
and
changes
in
production
costs,
including
pest
control,
harvesting,
sorting
and
125
processing.
EPA
will
conclude
that
a
significant
loss
will
occur
if
the
projected
losses
due
to
the
126
emergency
condition
are
verified
to
be
20%
of
expected
gross
revenues
or
higher.
This
threshold
will
127
be
the
same
for
all
crops
and
regions.
Quality
losses
occur
when
damage
results
such
that
the
128
commodity
fails
to
meet
the
market
standards
for
a
high­
value
segment
(
e.
g.,
export
or
fresh
market)
129
and
must
be
sold
in
a
lower
value
outlet
(
e.
g.,
domestic
or
processed
market).
Quality
losses
can
130
occur
without
loss
in
quantity
or
can
occur
in
conjunction
with
yield
losses.
This
tier
will
also
131
consider
losses
due
to
higher
production
costs.
Higher
production
costs
could
include
additional
pest
132
control
costs,
for
example,
mechanical
weeding,
or
additional
harvest
costs,
for
example,
sorting
into
133
different
grades.
However,
these
costs
must
be
a
result
of
the
emergency
before
the
expenses
can
be
134
included
in
the
projected
loss.
135
Tier
3,
Economic
Loss
$
50%
of
Net
Revenues
above
Operating
Costs:
For
situations
in
136
which
losses
do
not
meet
the
criteria
for
Tiers
1
and
2,
EPA
will
evaluate
estimates
of
economic
loss
137
as
a
percent
of
net
revenue
in
Tier
3
.
Economic
losses
are
defined
as
in
Tier
2.
EPA
will
conclude
138
that
a
significant
loss
will
occur
if
the
projected
losses
due
to
the
emergency
condition
are
50%
of
139
expected
net
revenues
or
higher.
This
threshold
will
be
the
same
for
all
crops
and
regions.
For
this
140
purpose,
the
Agency
defines
net
revenue
as
gross
revenues
less
variable
operating
costs
(
purchased
141
inputs
and
hired
labor).
The
Agency
considers
only
variable
operating
costs
because
these
costs
are
142
easier
to
measure
and
document
than
fixed
costs,
such
as
overhead
and
depreciation
of
machinery,
143
and
because
they
are
likely
to
be
more
reflective
of
short­
term
impacts
due
to
emergency
conditions.
144
The
Agency
recognizes
that
net
revenues
above
operating
costs
overstate
grower
income,
but
145
believes
the
facility
of
measurement
and
verification
make
it
a
more
useful
measure.
146
Losses
that
do
not
fit
into
this
general
pattern
will
be
evaluated
on
a
case­
by­
case
basis.
For
147
example,
damage
to
perennial
crops
that
may
result
in
losses
over
several
years
could
be
evaluated
as
148
a
loss
in
capital
or
in
returns
on
an
investment,
depending
on
the
situation.
In
those
cases,
the
states
149
must
submit
data
appropriate
to
their
case.
150
2.
Basis
for
Tier
Thresholds
151
The
choice
of
thresholds
20%,
20%,
and
50%
is
based
on
the
following
three
considerations.
152
a.
Farm
income
153
The
tier
thresholds
are
based
on
average
farm
income
and
production
expenses
for
the
USA.
154
The
latest
annual
report
from
USDA
shows
farm
production
expenditures
in
the
USA
to
average
155
about
80%
of
gross
revenue
(
USDA,
2003).
The
remainder,
net
farm
income,
is
essentially
the
wages
156
earned
by
the
growers.
See
table
below.
157
5
Table
1.
Aggregate
Farm
Income
and
Costs
for
the
U.
S.
in
$
billions
158
1997
1998
1999
2000
2001
Average
%
of
gross
revenue
Gross
Revenue
159
$
238.1
$
232.1
$
234.5
$
241.7
$
246.5
$
238.6
100.0%

Total
Production
Costs
160
$
187.6
$
186.5
$
188.3
$
193.7
$
200.8
$
191.4
80.2%
Operating
Costs
161
$
136.1
$
134.8
$
136.5
$
140.4
$
147.0
$
139.0
58.2%
Fixed
Costs
162
$
51.5
$
51.7
$
51.8
$
53.3
$
53.7
$
52.4
22.0%

Net
Revenue
=
163
gross
revenue
­
operating
164
costs
165
$
102.0
$
97.3
$
98.0
$
101.3
$
99.5
$
99.6
41.8%

Net
Farm
Income
=
166
gross
revenue
­
167
total
production
cost
168
$
50.5
$
45.6
$
46.2
$
48.0
$
45.7
$
47.2
19.8%

Source:
USDA
Agricultural
Statistics,
2003.
169
An
economic
loss
of
20%
of
gross
revenue
would
be
sufficient
to
eliminate
net
farm
income,
170
which
is
on
average
about
20%
of
gross
revenue.
A
yield
loss
of
20%
results
in
economic
loss
of
171
20%
or
more
of
gross
revenue.
172
Since
net
farm
income
is
a
little
less
than
50%
of
net
revenue,
an
economic
loss
that
is
50%
of
173
net
revenue
would
be
sufficient
to
eliminate
net
farm
income.
174
b.
Retrospective
Analysis
175
In
addition,
a
retrospective
analysis
was
done
on
past
emergency
exemptions
and
the
results
are
176
shown
in
Figure
1
in
Section
IIIC.
To
qualify
as
a
SEL
under
a
direct
use
(
without
subjective
177
judgement)
of
the
revenue
variation
approach,
the
losses
caused
by
the
emergency
must
result
in
the
178
expected
net
revenue
being
equal
to
or
less
than
the
minimum
net
revenue
over
the
last
5
years.
179
According
to
the
retrospective
analysis:
180
(
1)
Tiers
1
and
2.
The
average
and
median
economic
losses
that
would
have
qualified
181
as
a
SEL
under
the
current
method
(
i.
e.
calculated
thresholds
of
losses)
were
182
about
18%
and
15%
of
gross
revenue,
respectively.
183
(
2)
Tier
3.
The
median
economic
loss
that
would
have
qualified
as
a
SEL
under
the
184
current
method
was
about
51%
of
net
revenue.
185
Since
the
first
2
tiers
are
screening
thresholds,
these
thresholds
were
rounded
up
to
20%
to
be
a
186
little
more
stringent,
with
the
idea
being
that
if
they
did
not
pass
Tiers
1
or
2,
they
could
qualify
with
187
Tier
3.
Tier
3
compares
losses
to
net
revenue
(
gross
revenue
minus
operating
costs).
188
6
c.
Neutral
to
Likelihood
of
a
SEL
189
The
proposed
approach
is
not
expected
to
significantly
change
the
likelihood
of
an
application
190
qualifying
for
a
SEL.
That
is,
approximately
the
same
number
of
emergency
requests
that
qualified
191
for
a
SEL
using
the
current
revenue
variation
approach,
would
have
qualified
using
the
proposed
192
loss­
based
(
tiered)
approach,
although
there
would
be
differences
in
individual
cases.
That
is,
some
193
cases
would
have
qualified
for
a
SEL
under
the
proposed
method
that
did
not
qualify
under
the
194
current
method
and
visa­
versa
with
the
total
number
qualifying
being
the
about
the
same
with
both
195
methods.
See
Section
IIIE,
Comparison
of
Findings.
EPA
believes
that
the
differences
in
which
196
cases
qualify
would
be
more
equitable
and
consistent
under
the
proposed
method.
197
E.
Statutory
and
Regulatory
Requirements:
198
1.
Statutory
Provisions:
FIFRA,
Section
18
199
FIFRA
generally
prohibits
the
sale
and
distribution
of
any
pesticide
product,
unless
it
has
been
200
registered
by
EPA
in
accordance
with
section
3.
One
exception
to
this
general
prohibition
is
section
201
18
of
FIFRA,
which
gives
the
Administrator
of
EPA
broad
authority
to
exempt
any
Federal
or
State
202
agency
from
any
provision
of
FIFRA
if
the
Administrator
determines
that
emergency
conditions
exist
203
which
require
such
exemption.
204
2.
Regulatory
Provisions:
40
CFR,
Part
166
205
Regulations
governing
such
FIFRA
section
18
emergency
exemptions
are
codified
in
40
CFR
206
part
166.
Generally,
these
regulations
allow
a
Federal
or
State
agency
to
apply
for
an
exemption
to
207
allow
a
use
of
a
pesticide
that
is
not
registered
when
such
use
is
necessary
to
alleviate
an
emergency
208
condition.
A
State,
as
defined
by
FIFRA
section
2(
aa),
means
a
State,
the
District
of
Columbia,
the
209
Commonwealth
of
Puerto
Rico,
the
Virgin
Islands,
Guam,
the
Trust
Territory
of
the
Pacific
Islands
210
and
American
Samoa.
The
regulations
set
forth
information
requirements,
procedures,
and
standards
211
for
EPA's
approval
or
denial
of
such
exemptions.
212
II.
Methodology
of
Economic
Analysis
213
A.
Purpose
of
EA
(
economic
analysis)
214
The
purpose
of
this
EA
is
to
evaluate
the
costs
and
benefits
of
the
proposed
rule
change.
The
215
EA:
216
1.
Compares
findings
(
both
the
overall
likelihood
of
a
finding
and
the
findings
for
individual
217
cases)
to
determine
if
there
would
be
an
impact
with
substantially
different
conclusions
218
under
more
flexible
data
requirements,
given
changes
in
guidance
for
evaluating
SEL.
The
219
analysis
indicates
that
there
would
be
virtually
no
impact
in
the
overall
likelihood
of
a
220
finding
of
SEL,
and
that
small
differences
in
findings
for
individual
cases
would
be
more
221
equitable.
222
7
2.
To
estimate
the
cost
savings
of
the
rule
as
a
result
of
:
223
a.
More
flexible
data
requirements
for
determining
SEL
(
significant
economic
loss).
224
b.
Reduced
data
requirements
for
re­
certification
of
emergency
conditions.
225
B.
Significant
Economic
Loss
(
SEL)
226
1.
SEL
Database.
The
first
step
in
this
analysis
was
to
populate
a
database
of
SEL
findings
227
under
different
approaches.
EPA
developed
a
SEL
spreadsheet
template
that
determines
228
SEL
findings
under
both
the
current
and
proposed
methods,
as
well
as
what
the
analyst
229
concluded.
This
SEL
spreadsheet
was
used
to
analyze
many
of
the
exemption
requests
230
since
2000
and
to
populate
the
SEL
database
used
for
this
analysis.
231
2.
Cost
Savings
Analysis.
232
a.
Number
of
cases
qualifying.
With
the
SEL
database
EPA
determined
the
number
of
233
cases
which
would
have
qualified
as
a
SEL
under
each
Tier.
Then,
EPA
assumed
the
234
same
proportion
would
qualify
in
the
future.
A
significant
economic
loss
(
SEL)
is
235
defined
as
a
loss
that
would
pass
any
one
of
the
following
tiers:
236
Tier
1
­
Yield
loss
$
20%.
Significant
cost
savings
for
both
states
and
EPA.
237
Tier
2
­
Economic
loss
as
a
percent
of
gross
revenue
$
20%.
This
tier
also
covers
238
quality
losses
and
cost
increases.
Economic
loss
is
defined
as
loss
in
revenue
from
239
yield
and
quality
losses
plus
increased
costs
as
a
result
of
the
emergency,
such
as
240
increased
pest
control
or
harvesting
costs.
This
tier
would
also
save
resources
because
241
production
costs
other
than
cost
increases
are
not
required.
242
Tier
3
­
Economic
loss
as
a
percent
of
net
revenue
$
50%.
This
tier
also
considers
the
243
impact
on
net
revenue.
This
tier
has
the
same
numerator,
economic
loss
as
Tier
2,
but
244
compares
that
economic
loss
to
a
different
denominator,
net
revenue.
Net
revenue
is
245
defined
as
gross
revenue
minus
operating
costs.
This
tier
should
still
save
some
246
resources
since
historical
data
are
not
required.
However,
operating
cost
information
247
needs
to
be
more
documented
than
has
often
been
the
case
in
the
past,
when
states
248
have
not
clearly
defined
the
costs
included
in
the
submitted
data.
Therefore,
BEAD
249
assumes
that
the
resource
requirements
would
be
comparable
to
the
revenue
variation
250
method.
251
b.
Cost
saving
per
case.
Using
ICRs
(
information
collection
requests)
and
expert
opinion
252
from
scientists
in
EPA,
the
agency
estimated
the
savings.
253
c.
Estimate
cost
impacts.
The
agency
can
estimate
the
total
cost
savings
by
multiplying
254
the
number
of
cases
qualifying
for
a
SEL
per
year
under
Tiers
1
and
2
by
the
cost
255
savings
per
case
for
each
respective
tier,
i.
e.:
256
3
(
cost
savings
for
Tiers
1
&
2
requests)
X
(
number
of
cases
qualifying
for
Tiers
1
&
2)
257
This
calculation
may
overestimate
the
cost
savings,
since
states
may
choose
to
submit
258
more
data
than
would
be
necessary
in
case
EPA
does
not
concur
with
their
loss
259
estimates.
That
is,
states
claiming
yield
losses
in
excess
of
20%
may
still
decide
to
260
8
submit
price
and
production
cost
data
in
case
EPA's
evaluation
suggests
that
yield
261
losses
will
be
less
severe.
This
calculation
also
assumes
that
there
will
be
no
savings
262
under
Tier
3,
although
more
flexible
data
requirements
may
mean
that
applicants
will
263
be
able
to
provide
adequate
baseline
data
more
easily
than
under
the
revenue
variation
264
method.
265
3.
Comparison
of
SEL
Findings.
The
database
can
also
be
used
to
compare
findings
with
266
respect
to
the
likelihood
of
a
SEL
finding
and
the
findings
in
individual
cases.
The
database
267
provides
what
the
findings:
268
a.
Would
be
with
a
direct
use
(
without
judgement)
of
revenue
variation
method,
269
b.
Would
have
been
with
the
proposed
loss­
based
approach
given
data
submitted
under
270
the
current
methodology,
and
271
c.
What
they
actually
were
determined
to
be
by
the
analyst.
272
C.
Re­
certification
273
To
estimate
the
potential
cost
savings
EPA
estimated
the:
274
1.
Number
of
section
18s
that
would
have
been
eligible
for
re­
certification.
EPA
assumes
that
275
75%
of
repeat
requests
would
have
been
eligible,
and
that
the
same
proportion
will
be
276
eligible
in
the
future.
277
2.
Resources
required
by
the
state
and
EPA
for
a
full
application
&
review
compared
to
a
278
review
with
re­
certification.
279
III.
Results
of
the
Analysis
of
Proposed
Method
for
Determining
SEL
280
A.
Summary
of
exemption
requests.
See
Table
2
below.
281
Table
2.
Summary
of
emergency
exemption
requests
received
by
EPA
annually,
and
the
282
numbers
of
requests
used
in
the
Economic
Assessment
for
the
section
18
proposed
rule.
283
Set
of
exemption
requests
284
Average
Annual
Number
Comments
Total
exemption
requests
received/
year
285
541
Includes
all
specific,
quarantine,
public
health,
and
crisis
exemption
requests
Number
of
specific
exemption
requests
286
received/
year
287
500
The
proposed
process
revisions
only
apply
to
specific
exemptions.

Number
of
specific
exemption
requests
288
received/
year
for
which
bio/
econ
analysis
is
289
done
290
95
The
Biological
and
Economic
Analysis
Division
(
BEAD)
does
not
do
analysis
when
the
emergency
is
not
SEL­
type,
when
BEAD's
conclusion
for
one
state
applies
to
others
for
same
emergency
in
same
year,
or
for
many
repeat
requests.
Set
of
exemption
requests
Average
Annual
Number
Comments
1
BEAD
is
the
Biological
and
Economic
Analysis
Division
of
the
Office
of
Pesticide
Programs
of
EPA.
BEAD
does
the
biological
and
economic
reviews
and
analyses
of
emergency
exemption
requests
to
determine
if
there
is
an
emergency
condition
and
if
the
emergency
condition
would
lead
to
a
SEL.

9
Number
of
specific
exemption
requests
291
received/
year
for
which
bio/
econ
analysis
is
292
done,
AND
for
which
we
have
complete
293
data
to
do
comparative
analysis
of
revenue
294
variation
and
loss­
based
methods
295
45
BEAD
keeps
a
database
in
which
analysts
record
certain
data
from
the
application,
the
results
of
the
revenue
variation
method,
and
the
analyst's
SEL
conclusion.
However,
in
some
cases
the
data
is
incomplete.

Number
of
specific
exemption
requests
296
received/
year
for
which
bio/
econ
analysis
is
297
done,
AND
for
which
we
have
complete
298
data
to
do
comparative
analysis
of
revenue
299
variation
and
loss­
based
methods,
AND
for
300
which
we
have
the
analyst's
SEL
301
conclusion
available
in
the
database
302
26
In
some
cases,
the
BEAD
database
is
complete,
except
for
the
conclusion
on
SEL.

NOTE:
average
annual
numbers
are
based
on
four­
year
averages
for
FY2000­
FY2003.
Each
set
of
303
exemption
requests
is
a
subset
of
the
set(
s)
described
in
the
row(
s)
above
it.
304
B.
Dataset
305
1.
Number
of
Applications
Received
for
specific
exemptions
from
2000
through
2003
306
averaged
about
500
annually.
This
average
is
assumed
to
be
the
likely
number
of
307
applications
to
be
received
in
the
future.
(
EPA,
2003b)
The
proposed
rule
only
applies
to
308
specific
exemption
requests.
309
2.
Number
of
Applications
Reviewed
for
SEL
by
BEAD1
from
2000
through
2003
averaged
310
about
95
annually
for
specific
exemptions
only.
This
average
is
assumed
to
be
the
likely
311
number
of
applications
to
be
reviewed
by
BEAD
for
SEL
in
the
future.
A
BEAD
review
312
for
SEL
was
conducted
on
less
than
one­
fifth
of
the
applications
received.
Many
requests
313
are
not
reviewed
by
BEAD
for
SEL
for
various
reasons
such
as
repeat
requests,
low
risk,
314
and
similar
conditions
to
granted
requests
from
another
state.
(
EPA,
2003a)
315
3.
SEL
Database
316
a.
As
explained
above,
this
database
derived
from
SEL
spreadsheet
templates,
was
used
317
to
estimate
the
likelihood
of
an
application
qualifying
for
a
SEL
318
(
1)
as
recommended
by
the
analyst
using
the
current
method,
including
the
analyst's
319
judgement,
320
10
(
2)
under
a
direct
use
of
the
revenue
variation
method
without
the
analyst's
321
judgement
or
conclusion,
and
322
(
3)
under
the
loss­
based
method,
given
data
submitted
under
the
current
323
methodology.
324
b.
The
SEL
database
contains
information
from
181
(
45
per
year)
SEL
spreadsheets
325
compiled
in
the
course
of
the
BEAD
review
covering
almost
one­
half
of
the
378
(
95
326
per
year)
requests
reviewed
for
SEL
by
BEAD
from
2000
through
2003.
SEL
327
spreadsheets
were
not
necessarily
utilized
nor
complete
for
each
review
for
a
number
328
of
reasons
including:
329
(
1)
Incomplete
data
submitted
by
the
applicant.
330
(
2)
Determination
by
the
biologist
that
there
was
not
an
emergency
condition.
331
(
3)
Withdrawal
of
request
by
the
applicant.
332
(
4)
The
revenue
variation
methodology
was
not
appropriate
for
the
situation.
333
c.
Of
the
181
(
45
per
year)
observations,
the
analyst's
recommendation
is
known
for
103
334
(
26
per
year)
observations
because
of
incomplete
data
in
the
SEL
database.
Some
335
requests
in
the
database
were
determined
to
be
routine
or
non­
urgent
situations.
336
However,
these
data
may
be
used
to
calculate
what
losses
would
be
required
to
be
337
significant
even
if
a
SEL
was
not
determined.
338
4.
Specific
exemption
requests
eligible
for
self­
certification
are
estimated
to
be
about
247
per
339
year
(
75%
of
an
average
of
329
repeat
exemption
requests
per
year).
(
EPA,
2005
)
340
5.
ICR
(
Information
Collection
Request).
The
ICR
for
emergency
exemptions
was
used
to
341
estimate
the
resources
required
to
apply
for
an
emergency
exemption
and
for
EPA
to
342
review
these
requests.
(
EPA,
2000)
343
C.
Losses
Qualifying
as
a
SEL
under
the
Revenue
Variation
Method.
344
To
qualify
as
a
SEL
under
the
revenue
variation
method,
the
loss
should
cause
expected
net
345
revenue
as
a
result
of
the
emergency
to
fall
below
the
minimum
net
revenue
over
a
period
of
5
years.
346
This
loss
threshold
is
calculated
as
a
percent
of
gross
revenue
as
follows:
347
baseline
net
revenue
­
minimum
revenue
over
past
5
years
348
baseline
gross
revenue
349
The
chart
below
presents
the
frequency
distribution
of
the
losses
as
a
percent
of
gross
revenue
350
that
would
have
resulted
in
the
expected
net
revenue
being
equal
to
the
minimum
net
revenue
for
the
351
181
analyses
available
for
observation
from
the
period
2000­
2003.
352
Figure
1.
Frequency
Distribution
of
Minimum
Losses
Qualifying
as
SEL.
353
11
0­
5%
5­
10%
10­
15%
15­
20%
20­
25%
25­
30%
30­
35%
35­
40%
40­
45%
45­
50%
50­
55%
55­
60%

Economic
Loss
as
a
%
of
Gross
Revenue
0
10
20
30
40
50
in
each
5%
interval
Number
of
Observations
Frequency
Distribution
of
the
Minimum
Losses
that
Qualify
as
Significant
with
5­
Year
Revenue
Variation
Method
This
frequency
distribution
demonstrates
the
perverse
nature
of
the
current
method
of
354
determining
SEL.
Out
of
the
181
observations,
the
following
number
(
and
percent)
of
requests
355
could
have
qualified
as
having
a
SEL
under
a
direct
interpretation
(
without
judgement)
of
the
revenue
356
variation
method
with
the
following
losses
as
a
percent
of
gross
revenue:
357
1.
12
(
7%
of
181)
requests
with
a
loss
of
5%.
358
2.
45
(
25%)
requests
with
a
loss
of
10%.
359
3.
91
(
50% 
the
median)
requests
would
have
qualified
with
a
loss
of
15.3%.
The
other
90
360
would
have
required
losses
ranging
between
15.3
%
and
60%
to
qualify
with
a
SEL.
361
4.
117
(
65%)
requests
with
a
loss
of
20%.
The
other
64
(
181­
117
or
35%)
requests
would
362
have
required
losses
ranging
between
20%
and
60%
to
qualify
with
a
SEL.
363
5.
3
(
2%)
requests
would
have
required
a
loss
of
50%
or
more
to
qualify
as
having
a
SEL
364
under
a
direct
interpretation
of
the
revenue
variation
(
current)
method.
365
6.
Conclusion.
A
consistent
standard
of
loss
(
as
the
proposed
loss­
based
method)
that
would
366
qualify
as
a
SEL
would
be
more
equitable.
367
7.
Average.
The
average
calculated
loss
threshold
under
the
current
variation
method
was
368
about
18%
of
gross
revenue.
The
average
was
higher
than
the
median
of
15%
because
of
369
the
skewed
distribution.
The
calculated
loss
threshold
is
the
minimum
loss
required
to
370
qualify
as
a
SEL.
371
2
Results
may
be
slightly
different
under
more
flexible
data
requirements
since
the
historical
data
used
for
this
analysis
may
not
be
representative
of
situation
growers
face.
For
example,
under
the
current
method
average
historical
price
was
generally
used
as
a
baseline,
while
proposed
method
may
use
other
information
to
determine
the
price
most
likely
to
be
received
by
growers.

12
D.
Cost
Savings
as
a
Result
of
Changing
Data
Requirements
for
Determining
SEL
372
1.
Requests
Passing
Each
Tier
with
a
Finding
of
a
SEL.
Table
3
below
shows
the
percent
and
373
number
of
requests
that
would
have
qualified
for
a
SEL
under
the
proposed
loss­
based
374
method,
given
data
submitted
under
the
current
methodology2.
375
a.
About
55%
would
qualify
for
Tier
1
and
would
not
require
economic
data
nor
an
376
economic
review.
377
b.
Another
10%
that
would
not
qualify
for
Tier
1
would
qualify
for
Tier
2
and
not
378
require
production
cost
data.
379
c.
Another
15%
would
qualify
only
for
Tier
3,
for
which
we
assume
no
savings
compared
380
to
the
current
method.
381
d.
No
savings
are
assumed
for
requests
not
qualifying
for
any
tier.
382
e.
EPA
receives
about
500
specific
exemption
requests
per
year.
Of
these
about
95
are
383
reviewed
for
SEL.
Therefore,
the
annual
applicant
savings
are
based
on
500
requests
384
submitted,
while
the
annual
EPA
savings
are
based
95
applications
reviewed
for
SEL.
385
Table
3.
Requests
Likely
to
Pass
Each
Tier
Using
the
Loss­
based
Method
386
Tier
387
Threshold
Required
Data
&
Analysis
Requests
likely
to
pass
tier*

%
Total*
Bio/
Econ*

Tier
1
388
$
20%
yield
loss
Yield
loss
55%
276
52
Tier
2,
but
not
389
Tier
1
390
Loss
$
20%
gross
revenue
Yield
loss
+
prices,
cost
changes
&
gross
revenue
10.5%
53
10
Tier
3,
but
not
391
Tiers
1
&
2
392
Loss
$
50%
of
net
revenue
All
of
the
above
+
operating
cost
&
net
revenue
15.5%
77
15
Requests
passing
any
tier
393
81%
406
77
Requests
not
passing
any
tier
394
19%
94
18
Total
requests
per
year
(
Average
2000­
03)
395
100%
500
95
Numbers
may
not
exactly
add,
due
to
rounding
396
*
While
the
average
number
of
requests
per
year
is
500,
about
95
are
reviewed
for
SEL.
The
percentages
passing
each
397
tier
are
based
on
181
observations
(
2000­
03)
where
EPA
had
data
on
past
analyses
of
SEL.
These
percentages
are
398
applied
to
all
500
applications
(
total)
for
estimating
annual
applicant
savings,
but
only
to
the
95
applications
in
which
a
399
biological
and
economic
review
(
Bio/
Econ)
was
done
to
determine
SEL
when
estimating
annual
EPA
savings.
400
13
2.
Cost
Savings
for
the
Applicants
(
States).
The
table
below
estimates
the
application
cost
401
savings
that
are
likely
to
occur
as
a
result
of
changing
to
the
loss­
based
method.
402
a.
The
ICR
(
EPA,
2000)
estimates
that
it
takes
about
99
hours
to
apply
for
an
emergency
403
exemption
at
a
cost
of
$
54
per
hour
or
over
$
5000
per
application.
Of
this
99
hours,
404
an
estimated
74
hours
is
spent
processing,
compiling,
reviewing,
and
providing
all
the
405
requested
data,
including
efficacy
and
risk
data.
EPA
assumes
that
about
25%
of
the
406
time
providing
all
of
the
data
is
required
to
provide
the
economic
data
under
the
407
current
method.
If
the
application
qualifies
for
a
SEL
in
Tier
1,
the
economic
data
408
would
not
be
required,
thus
saving
almost
19
hours
or
almost
$
1000
per
application.
409
For
276
applications
that
are
likely
to
qualify
under
Tier
1,
the
savings
would
be
410
almost
$
276,000.
411
b.
If
an
applicant
qualifies
for
a
SEL
under
Tier
2,
but
not
under
Tier
1,
limited
412
economic
data
is
required.
EPA
assumes
that
this
limited
data
would
require
about
413
half
of
the
time
required
for
economic
data
under
the
current
method.
Therefore,
the
414
savings
would
be
about
12.5%
of
the
time
required
to
provide
all
data
under
the
415
current
method
 
about
9
hours
or
$
500
per
application.
With
about
53
applications
416
that
are
likely
to
qualify
for
a
SEL
in
Tier
2,
but
not
Tier
1,
and
that
would
provide
417
limited
economic
data,
the
savings
would
be
almost
$
26,500.
418
c.
While
the
data
required
under
Tier
3
may
be
less
than
required
under
the
current
419
method,
EPA
makes
the
conservative
assumption
that
there
would
be
no
savings.
420
Often
an
applicant
may
provide
historical
data
to
establish
a
baseline
from
which
to
421
calculate
the
loss.
Also,
no
savings
are
assumed
for
requests
with
no
finding
of
SEL.
422
d.
EPA
estimates
the
total
annual
savings
to
the
applicants
to
be
almost
5,600
hours
or
423
over
$
300,000.
424
Table
4.
Cost
Savings
for
Applicants
from
Proposed
Loss­
based
Method
425
Applicant
426
Current
Cost
Savings
as
a
Result
of
Qualifying
for
a
SEL
Under:

Application
Data
*
Tier
1
Tier
2
Total
Savings
Avg
wage
rate
427
$
54
per
hour
%
savings
428
25%
12.5%

Hour/
application
429
99
74
18.5
9.25
Applications/
year
430
500
500
276
53
329
Hours
per
year
431
49,500
37,000
5,106
490
5,596
$
per
application
432
$
5,346
$
3,996
$
999
$
500
Total
$
per
year
433
$
2,673,000
$
1,998,000
$
275,724
$
26,474
$
302,198
Numbers
may
not
exactly
add,
due
to
rounding
434
*
The
estimate
of
the
time
and
cost
required
to
process,
compile,
review,
and
provide
data.
435
3
Based
on
TAIS
(
Time
Accounting
Information
System)
of
OPP
(
Office
of
Pesticide
Programs),
the
time
spent
for
the
biologic
and
economic
review
is
slightly
over
25%
of
the
time
reported
by
all
of
OPP
in
processing
emergency
exemptions.
(
EPA,
2003c)

14
3.
Cost
Savings
for
EPA.
The
table
below
estimates
the
review
cost
savings
that
are
likely
to
436
occur
as
a
result
of
changing
to
the
loss­
based
method.
437
a.
The
ICR
(
EPA,
2000)
estimates
that
it
takes
about
108
hours
for
EPA
to
review
an
438
emergency
exemption.
Of
this
108
hours,
it
takes
about
28
hours
to
review
the
439
biological
and
economic
data
in
order
to
determine
if
there
is
an
emergency
condition
440
and
a
SEL3.
Most
of
the
time
is
spent
by
the
biologist
in
reviewing
the
emergency
441
condition.
EPA
assumes
that
25%
of
the
28
hours
(
about
7
hours)
is
spent
by
the
442
economist
in
the
determination
of
SEL
under
the
current
method.
At
a
cost
of
$
67.25
443
per
hour
the
biologic
and
economic
review
costs
almost
$
1900
per
application,
with
444
the
economic
analysis
costing
about
$
470.
445
b.
If
the
application
qualifies
for
a
SEL
in
Tier
1,
the
economist
review
would
not
be
446
required,
thus
saving
about
7
hours
or
about
$
470
per
application
or
about
$
24,500
447
annually
for
52
applications
(
of
the
95
applications
reviewed
for
SEL)
likely
to
qualify
448
for
a
SEL
in
Tier
1.
449
c.
If
an
applicant
qualifies
for
a
SEL
under
Tier
2,
a
limited
economic
review
would
be
450
required.
EPA
estimates
that
this
limited
review
would
save
about
40%
of
the
normal
451
time
to
do
a
full
economic
analysis
or
10%
(
40%
x
25%)
of
the
time
required
for
the
452
biologic
and
economic
review
under
the
current
method
with
a
savings
of
almost
$
190
453
per
application
or
almost
$
1,900
for
10
applications
that
are
likely
to
qualify
for
a
SEL
454
in
Tier
2.
455
d.
EPA
makes
the
conservative
assumption
that
there
would
be
no
savings
in
the
review
456
of
Tier
3,
including
those
requests
with
no
finding
of
SEL.
457
e.
EPA
estimates
the
total
annual
savings
of
the
biologic
and
economic
review
to
be
458
almost
400
hours
or
about
$
26,000.
459
Table
5.
Cost
Savings
for
EPA
from
Proposed
Loss­
based
Method
460
EPA
461
Current
Cost
Savings
as
a
Result
of
Qualifying
for
a
SEL
Under:
Total
Savings
EPA
Bio/
Econ
Tier
1
Tier
2
Avg
wage
rate
462
$
67.25
per
hour
Savings
463
25%
10%

Hours/
application
464
108
28
7
2.8
#
of
applications
465
95
95
52
10
62
Total
hours
466
10,206
2,646
364
28
392
$
per
application
467
$
7,263
$
1,883
$
471
$
188
Total
$
per
year
468
$
686,354
$
177,944
$
24,479
$
1,883
$
26,362
4
Using
data
submitted
under
the
present
approach
may
result
in
some
bias
if
average
values
for
yield
and
prices
are
used
to
represent
typical
conditions.
Under
revised
data
requirements,
states
could
submit
data
that
better
represents
typical
conditions
if
historical
averages
are
inappropriate.

15
4.
Total
Saving.
EPA
estimates
the
total
potential
savings
for
the
states
and
EPA
combined
to
469
be
about
a
third
of
a
million
dollars
as
a
result
of
changing
data
requirements
and
using
the
470
loss­
based
method
for
determining
SEL.
471
E.
Comparison
of
Findings
472
1.
Likelihood
of
a
SEL
Finding
473
The
table
below
compares
the
number
and
percent
of
findings
under
a
direct
use
(
without
474
judgement)
of
the
current
and
proposed
methods,
and
what
the
analyst
actually
concluded
using
475
judgement.
476
a.
The
analyst
found
a
SEL
a
higher
percentage
of
time
(
83%)
than
a
direct
use
of
the
477
revenue
variation
method
would
indicate
(
72%).
The
higher
findings
of
a
SEL
by
the
478
analyst
were
mainly
the
result
of
the
analyst
eliminating
outliers
where
past
revenues
479
were
very
low
due
to
unusual
conditions.
Such
outliers
distort
typical
conditions
and
480
the
loss
as
a
result
of
the
emergency
condition
would
have
to
be
overly
large
to
qualify
481
for
a
SEL.
By
eliminating
the
outliers,
the
historical
data
is
more
indicative
of
normal
482
conditions
and
the
calculated
threshold
needed
to
qualify
as
a
SEL
is
more
realistic.
483
b.
The
percent
of
time
the
loss
qualified
as
a
SEL
under
the
loss­
based
method
(
given
484
that
the
data
were
submitted
under
the
present
methodology)
was
closer
to
what
the
485
analysts
found
than
what
a
direct
use
of
the
revenue
variation
method
found.
Since
the
486
loss­
based
method
is
less
affected
by
outliers
in
the
historical
data4,
it
is
less
dependent
487
on
subjective
decisions
of
the
analyst.
488
Table
6.
Comparison
of
Findings
489
Finding
490
Number
and
Likelihood
of
a
Finding
Current
Method
Proposed
Method
Actual
by
Analyst*
Revenue
Variation*
Loss­
based
SEL
491
86
(
83%)
131
(
72%)
147
(
81%)

No
SEL
492
17
(
17%)
50
(
28%)
34
(
19%)

Total
Observations*
493
2000­
03
494
103
181
181
*
Out
of
181
observations,
the
actual
finding
by
the
analyst
is
known
in
103
cases.
The
actual
findings
of
SEL
by
the
495
analyst
exceeds
what
the
current
revenue
variation
method
would
have
found
without
judgement.
The
analyst
uses
496
judgement
to
eliminate
outliers
in
annual
revenue
data
that
distort
the
findings
of
SEL.
497
16
2.
Cross
Agreement
of
Findings
498
The
table
below
shows
the
percent
of
time
that
the
findings
of
a
SEL
agreed
with
each
other
499
under
the
following:
500
a.
What
a
direct
use
of
the
revenue
variation
method
would
have
determined.
501
b.
What
the
analyst
actually
determined.
502
c.
What
the
loss­
based
method
would
have
determined.
503
This
table
below
is
based
on
103
observations
where
the
recommendation
of
the
analyst
was
504
known.
The
results
show
a
high
degree
of
agreement
between
the
various
methods.
505
Table
7.
Cross
Agreement
of
Findings
506
Cross
Agreement
of
Findings
507
based
on
103
observations
2000­
03*
508
%
Agreement
SEL
no
SEL
total
Analyst
with
Revenue
Variation
Method
509
76%
14%
90%

Analyst
with
Loss­
based
Method
510
82%
6%
88%

Revenue
Variation
Method
with
Loss­
based
Method
511
76%
6%
82%

Analyst
with
Revenue
Variation
&
Loss­
based
Methods
512
74%
6%
80%
*
Out
of
181
observations,
the
finding
of
the
analyst
is
known
in
103
cases.
513
3.
Conclusions
of
comparisons.
The
two
tables
above
demonstrate
that
changing
from
the
514
current
method
to
the
proposed
loss­
based
method
would:
515
a.
Not
cause
a
significant
change
in
the
overall
likelihood
of
a
SEL
finding
as
compared
516
to
the
current
revenue
variation
method
as
modified
by
analyst
judgement
such
as
517
eliminating
outliers.
The
analyst
made
a
finding
of
SEL
in
83%
of
the
cases
studied,
518
while
the
loss­
based
method
would
have
found
a
SEL
in
81%
of
cases.
519
b.
Result
in
some
different
findings
in
individual
cases.
The
analyst
and
the
loss­
based
520
method
arrived
at
different
conclusions
12%
of
the
time.
In
a
few
cases
the
analyst
521
found
a
SEL
with
a
yield
loss
and
economic
loss
as
a
percent
of
gross
revenue
of
less
522
than
20%
because
these
losses
were
sufficient
to
cause
the
net
revenue
to
fall
below
523
the
lowest
net
revenue
of
the
past
5
years.
In
other
cases,
the
analyst
did
not
find
a
524
SEL
with
a
yield
loss
greater
than
20%
because
these
losses
were
not
sufficient
to
525
cause
the
net
revenue
to
fall
below
the
lowest
net
revenue
of
the
past
5
years.
In
some
526
cases
there
was
not
good
data
on
the
expected
yield
loss,
so
a
judgement
was
made
527
whether
or
not
the
expected
loss
would
exceed
the
minimum
loss
needed
to
qualify
as
528
significant
with
the
revenue
variation
method.
529
17
IV.
Results
of
Analysis
of
Re­
certification
530
A.
Applicant
(
States)
Savings
531
The
table
below
estimates
the
likely
savings
to
the
applicants
from
re­
certification.
The
532
calculations
are
similar
to
the
cost
savings
analysis
of
the
loss­
based
method
for
determining
SEL.
If
533
an
applicant
re­
certifies,
data
will
not
be
required,
thus
saving
the
74
hours
that
the
ICR
estimates
is
534
needed
to
provide
the
data,
thus
saving
about
$
4000
per
application.
EPA
estimates
that
about
75%
535
of
an
average
of
329
repeat
applications
per
year
may
qualify
for
re­
certification
resulting
in
a
total
536
savings
to
the
applicants
of
almost
$
1
million
per
year.
537
Table
8.
Cost
Savings
to
Applicants
from
Re­
certification
538
Applicant
539
Current
Cost
Savings
from
Re­
certification
Average
wage
rate
540
$
54
per
hour
Hours
per
application
541
99
74
75%

Number
of
applications
542
500
247
Total
hours
543
49,500
18,278
$
per
application
544
$
5,346
$
3,996
Total
$
per
year
545
$
2,673,000
$
987,012
B.
EPA
Savings
546
The
table
below
estimates
the
likely
savings
to
EPA
from
re­
certification.
Since
many
repeat
547
requests
that
would
have
qualified
for
re­
certification
are
currently
not
as
thoroughly
reviewed
as
new
548
requests,
the
EPA
savings
would
not
be
as
great
as
the
applicants'.
EPA
estimates
(
conservatively
549
low)
that
it
would
save
about
10%
of
the
average
time
it
currently
takes
to
review
an
application.
550
According
to
the
ICR
it
takes
about
108
hours
to
review
an
application,
thus
savings
for
EPA
would
551
be
almost
11
hours
or
over
$
700
per
application,
with
a
total
annual
savings
of
almost
2700
hours
or
552
about
$
180,000.
553
Table
9.
Cost
Savings
to
EPA
from
Re­
certification
554
EPA
555
Current
Average
Cost
Savings
from
Re­
certification
Average
wage
rate
556
$
67.25
per
hour
Hours
per
application
557
108
11
10%

Number
of
applications
558
500
247
Total
hours
559
54,000
2,668
$
per
application
560
$
7,263
$
726
Total
$
per
year
561
$
3,631,500
$
179,396
18
C.
Total
Savings
from
Re­
certification.
EPA
estimates
the
annual
combined
savings
for
the
562
applicants
and
EPA
from
re­
certification
to
be
almost
$
1.2
million.
563
V.
Combined
Savings
564
The
savings
from
re­
certification
and
the
loss­
based
method
for
determining
SEL
are
565
summarized
in
the
table
below:
566
Table
10.
Summary
of
Cost
Savings
567
Savings
568
Loss­
based
Method
Re­
certification
Total
Applicants
569
$
0.30
million
$
0.99
million
$
1.29
million
EPA
570
$
0.03
million
$
0.18
million
$
0.21
million
Total
571
$
0.33
million
$
1.17
million
$
1.50
million
By
provision.
The
total
savings
from
the
loss­
based
method
are
about
a
third
of
a
million
572
dollars,
and
from
re­
certification
are
almost
$
1.2
million
for
a
grand
total
of
about
$
1.5
million.
573
By
entities.
The
total
savings
to
the
applicant
and
EPA
are
about
$
1.3
million
and
$
210,000,
574
respectively,
for
a
grand
total
of
about
$
1.5
million.
575
VI.
Information
Collection
Request
(
ICR)
576
This
economic
analysis
is
based
on
the
ICR
for
emergency
exemptions
(
EPA,
2000).
The
577
provisions
of
the
proposed
rule
only
reduce
the
paperwork
burdens
as
estimated
in
this
economic
578
analysis.
Therefore,
the
current
ICR
is
still
valid
and
provides
an
estimate
of
the
paperwork
burden
579
for
those
applications
that
would
not
benefit
from
the
proposed
rule.
For
the
applicants
that
benefit
580
from
the
proposed
rule,
the
burden
will
be
reduced.
The
applicants
that
benefit
include:
581
1.
Those
qualifying
for
self­
certification
582
2.
Those
applicants
who
can
show
a
SEL
in
Tiers
1
or
2
of
the
loss­
based
method.
583
In
those
applications
where
the
applicant
burden
is
reduced,
EPA's
burden
is
also
reduced.
584
19
VII.
Limitations
of
Analysis
585
A.
Total
Savings.
The
savings
for
the
loss­
based
method
and
re­
certification
were
each
estimated
586
as
if
the
other
were
not
going
to
be
implemented,
i.
e.,
the
number
of
applications
would
benefit
587
from
the
savings
of
the
loss­
based
method
would
be
slightly
less
as
a
result
of
economic
data
and
588
analysis
not
being
required
because
of
re­
certification.
Also,
the
savings
from
re­
certification
589
were
based
on
the
current
method.
Since
the
loss­
based
method
would
usually
require
less
time
590
to
prepare,
the
savings
from
re­
certification
would
be
slightly
less
for
the
applicant.
However,
591
this
double
counting
of
savings
is
likely
to
be
small
because
repeat
applications
benefitting
from
592
re­
certification
are
not
likely
to
be
the
same
applications
that
would
benefit
from
the
loss­
based
593
method.
594
B.
Average
Savings.
This
analysis
was
based
on
average
hours
and
costs
required
to
prepare
and
595
review
applications.
However,
such
costs
vary
widely.
The
costs
to
prepare
and
review
a
first­
596
time
application
for
an
emergency
exemption
are
likely
to
be
higher.
Since
these
first­
time
597
applications
are
more
likely
to
benefit
from
the
savings
of
the
loss­
based
method
for
determining
598
SEL,
the
savings
from
the
loss­
based
method
are
likely
to
be
underestimated.
On
the
other
599
hand,
the
costs
for
preparing
repeat
applications
are
likely
to
be
less.
Since
repeat
applications
600
are
more
likely
to
benefit
from
the
savings
of
re­
certification,
the
savings
from
re­
certification
601
are
likely
to
be
over
estimated
for
the
applicants.
Since
EPA
has
no
basis
to
differentiate
the
602
costs
of
first
time
vs.
repeat
applications,
it
did
not
fully
attempt
to
do
so,
except
that
EPA
603
assumed
a
conservatively
low
savings
for
EPA
for
re­
certification.
These
under
and
over
604
estimates
are
likely
to
offset
each
other
somewhat.
605
C.
Unrealized
Savings.
Some
applicants
that
qualify
for
Tier
1
or
2
of
the
loss­
based
method
may
606
not
realize
their
potential
savings
because
they
might
provide
additional
data
in
case
they
do
not
607
pass
those
tiers.
Similarly,
some
applicants
that
would
qualify
for
re­
certification
may
not
take
608
advantage
of
it.
However,
EPA
has
no
basis
to
estimate
these
unrealized
savings.
Instead,
EPA
609
has
estimated
the
potential
saving
applicants
could
realize
if
they
chose
to
do
so.
610
D.
Time
Savings.
The
hours
that
would
be
saved
under
the
various
scenarios
(
Tier
1,
Tier
2,
re­
611
certification)
were
mostly
assumed.
In
making
these
assumptions,
EPA
has
tried
to
be
612
conservative
toward
underestimating
the
savings.
Several
factors
were
used
to
help
make
some
613
of
these
assumptions.
For
example,
the
74
hours
required
to
provide
data
is
the
basis
of
the
614
savings
for
re­
certification.
Other
savings
are
possible
from
other
parts
of
the
application
that
615
are
likely
be
simpler,
but
were
not
estimated.
Therefore,
the
savings
from
re­
certification
may
be
616
underestimated.
However,
repeat
applications
are
likely
to
be
less
costly,
thus
offsetting
this
617
underestimation.
618
E.
Conclusions.
In
spite
of
these
limitations,
the
conclusions
are
valid.
There
should
be
substantial
619
savings
from
re­
certification
and
from
changing
data
requirements
for
determining
SEL.
620
Increasing
flexibility
in
the
data
requirements
in
conjunction
with
changing
the
methodology
for
621
determining
SEL
will
also
increase
fairness,
openness
and
objectivity.
622
20
VIII.
Conclusions
623
A.
Benefits
624
1.
Cost
Savings.
EPA
estimates
substantial
cost
savings
to
applicants
and
some
savings
to
625
EPA
from
the
proposed
loss­
based
method
for
determining
SEL
and
re­
certification.
EPA
626
estimates
savings
of
about
$
1.3
million
to
the
applicants
and
over
$
200,000
to
EPA
.
627
Different
assumptions
in
the
analysis
would
change
the
magnitude
of
the
savings
estimates,
628
but
would
not
change
the
conclusion
that
there
will
be
cost
savings.
629
2.
Transparency,
Consistency,
and
Equity.
EPA
believes
that
the
determination
of
SEL
under
630
the
loss­
based
method
will
be
more
consistent
and
transparent.
Currently,
differences
in
631
variations
in
revenue
result
in
differences
in
the
magnitude
of
the
losses
that
would
qualify
632
as
SEL.
To
avoid
extremes
in
inequities,
analysts
use
judgement;
however,
such
judgement
633
is
not
consistent
nor
transparent.
By
reducing
judgement
the
loss­
based
method
is
more
634
transparent.
With
established
thresholds
for
SEL,
the
loss­
based
method
is
also
more
635
consistent
and
equitable.
EPA
believes
decision
making
will
be
improved
under
the
636
proposed
method.
637
3.
Timeliness.
Reduced
analysis
by
EPA
means
more
timely
decisions
on
emergency
638
exemptions.
639
B.
Impacts.
There
are
no
costs
associated
with
the
proposed
rule,
only
cost
savings.
With
respect
640
to
the
proposed
loss­
based
method,
our
analysis
shows
that
the
overall
likelihood
of
a
finding
of
641
SEL
would
not
be
changed.
However,
in
individual
cases,
the
proposed
method
would
result
in
642
different
findings
of
SEL
in
about
12%
of
the
requests.
As
discussed
above,
EPA
believes
that
643
these
different
findings
would
be
better
since
they
would
be
more
transparent,
consistent,
644
equitable,
and
timely.
645
IX.
References
646
BLS,
2003.
Bureau
of
Labor
Statistics.
http://
data.
bls.
gov/
cgi­
bin/
surveymost
647
EPA,
2000.
Information
Collection
Request,
Emergency
Exemptions.
648
EPA,
2003a.
Data
from
the
Biological
and
Economic
Analysis
Division,
Office
of
Pesticide
649
Programs.
650
EPA,
2003b.
Data
from
the
Registration
Division,
Office
of
Pesticide
Programs.
651
EPA,
2003c.
Time
Accounting
Information
System,
Office
of
Pesticide
Programs.
652
OPM,
2003.
Office
of
Personnel
Management.
http://
www.
opm.
gov/
oca/
03tables/
indexGS.
asp
653
USDA,
2003.
Agricultural
Statistics
­
2003
654
EPA,
2005.
Data
from
the
Registration
Division,
Office
of
Pesticide
Programs.
655
