An aggregate economic analysis of potential erosion and plant nutrient controls in the Corn Belt


Taylor, C.R.; Frohberg, K.K.; Seitz, W.D.

An aggregate economic analysis of potential erosion and plant nutrient controls in the Corn Belt: 25-45

1977


This study indicates that reasonable soil erosion control programs can be implemented without having serious economic impacts on the agricultural sector or on consumer expenditure)l If however, the high soil loss coefficients are accurate, and if a stringent soil loss restriction such as a 2-ton-per-year limit were adopted, the economic impacts would be serious. Serious economic impacts would also be generated by tight controls on nitrogen use. Contrary to popular belief, the economic burden of the restriction falls more on consumers than on producers for many of the controls considered. This occurs because the model includes demand and supply functions for the major crops, allowing impacts of controls to be translated into higher prices generating higher gross receipts at the farm level. The higher receipts help offset or, in some cases, more than offset the higher production costs or lower yields associated with controls. Such results will not be demonstrated by a model limited to fixed commodity prices. Two sets of soil loss coefficients were used in the study. One set was supplied by the Federal Soil Conservation Service, while the other set was supplied by Illinois Soil Conservation Service personnel. It appears that the two sets of coefficients bracket actual soil losses. To obtain more precise estimates of the economic impacts of non-point pollution controls, precise estimates of soil loss coefficients must be obtained.

An
Aggregate
Economic
Analysis
of
Potential
Erosion
and
Plant
Nutrient
Controls
in
the
Corn
Be10
1
by
C.
Robert
Taylor,
Klaus
K.
Frohberg,
and
Wesley
D.
Seitz*
Agricultural
non
-point
sources
of
water
pollution
are
receiving
increas-
ing
attention
because
of
impending
controls
under
the
1972
amended
Water
Pollution
Control
Act
(P.L.
92-500).
The
two
non
-point
sources
that
have
been
receiving
primary
attention
in
the
Corn
Belt
are
sediment
and
nitrates.
Sediment
may
be
classified
as
a
pollutant
because
of
its
deleterious
effect
on
stream
water
quality
and
the
filling
up
of
reservoirs.
Nitrates
in
water
supplies
are
of
concern
because
at
certain
concentrations
they
are
dangerous
to
human
and
animal
health.
In
certain
circumstances
nitrates
also
pose
a
threat
to
balanced
aquatic
life
in
surface
waters.
Finally
it
has
recently
been
alleged
that
the
increased
fixation
of
nitrogen
threatens
to
reduce
the
protective
ozone
content
of
the
upper
atmosphere,
thus
increasing
the
incidence
of
skin
cancer.
See
CAST
(1976)
for
a
review
of
the
allegations.
This
paper
presents
estimates
of
the
intermediate
term
economic
effects
of
imposing
various
controls
on
erosion
and
nitrogen
fertilizer
use
in
the
Corn
Belt.
Controls
imposed
uniformly
throughout
the
Corn
Belt
are
being
considered
now
because
the
Federal
EPA
must
approve
all
State
and
local
non
-
point
pollution
controls;
Section
103
of
the
act
states
"The
Administrator
(of
EPA)
shall
encourage
--so
far
as
practicable,
uniform
state
laws
relating
to
the
prevention,
reduction,
and
elimination
of
pollution.
.
."
Also,
consid-
eration
of
all
combinations
of
controls
that
differed
by
State
would
be
impractical.
ij
Research
supported
by
a
contract
from
the
U.S.
Environmental
Protection
Agency
#68-01-3584.
The
final
report
"Alternative
Policies
for
the
Control
of
Nonpoint
Sources
of
Water
Pollution
from
Agriculture"
by
Seitz,
et
al.,
is
in
preparation.
The
research
was
conducted
through
the
Institute
for
Environmental
Studies
with
the
cooperation
of
the
Agricultural
Experiment
Station
at
the
University
of
Illinois,
Urbana
-Champaign.
The
authors
acknowledge
the
contributions
of
other
members
of
the
research
team.
*Respectively,
Assistant
Professor
of
Agricultural
Economics
at
Texas
A&M
University,
former
graduate
assistant
at
the
University
of
Illinois
(now
an
economic
analyst
with
the
International
Institute
for
Applied
Systems
Analysis
in
Laxenburg,
Austria),
and
Associate
Professor
of
Agricultural
Economics
and
Associate
Director
of
the
Institute
for
Environmental
Studies
at
the
University
of
Illinois,
Urbana
-Champaign.
25
THE
MODEL
Impacts
of
soil
-loss
and
nitrogen
restrictions
were
analyzed
through
the
solution
of
a
large
linear
programming
model
of
Corn
Belt
crop
production.
This
model
provides
the
capability
to
estimate
market
prices
for
corn
and
soybeans
based
on
estimates
of
the
demands
for
these
products.
Thus,
the
model
generates
a
competitive
market
equilibrium
in
the
production
of
these
crops
and
is
able
to
indicate
the
price
impacts
of
several
types
of
restric-
tions.
In
addition
to
estimating
the
effects
on
producers
and
consumers,
solutions
to
the
model
indicate
changes
in
soil
loss,
nitrogen
use,
crop
production,
acreage,
pesticide
use,
and
crop
prices.
The
land
base
for
the
area
modelled
was
divided
into
11
land
capability
units
(LCU's)
within
each
of
17
geographical
regions
which
are
land
resource
areas
(LRA's)
defined
by
the
Soil
Conservation
Service
(table
1).
Crop
production
activities
in
the
model
differ
by
crop
rotation
(an
average
of
about
11
rotations
for
each
LCU
within
each
LRA),
conservation
practices
(straight
row,
contouring,
and
terracing)
and
tillage
methods
(fall
plow,
spring
plow,
and
chisel
plow).
Rotations
rather
than
just
single
crop
activities
are
included
in
the
model
to
reflect
the
influence
of
the
previous
crop
on
the
fertilizer
and
pesticide
requirements
of
the
current
crop.
The
model
has 14,372
crop
production
alternatives
and
545
resource
constraints.
With
the
exception
of
the
soil
loss
coefficients,
the
model
is
the
same
as
one
used
in
an
earlier
study
by
Taylor
and
Frohberg
(1977).
Two
sets
of
soil
-loss
coefficients
were
used.
The
model
was
initially
constructed
with
coefficients
supplied
by
the
Federal
Soil
Conservation
Service.
Local
SCS
personnel
reviewed
these
results
and
suggested
that
the
soil
losses
were
higher
than
expected.
A
new
set
of
soil
-loss
coefficients
were
constructed
by
Illinois
SCS
personnel
using
the
Universal
Soil
Loss
Equation
(USLE).
A
number
of
policy
runs
were
repeated
using
these
coeffi-
cients.
As
will
be
indicated
in
the
discussion
of
results,
the
revised
soil
losses
may
be
somewhat
low.
If
so,
the
two
sets
of
results
bracket
the
actual
soil
losses
to
be
expected.
MODEL
RESULTS
The
model
was
run
for
each
of
the
following
conditions
and
constraints:
2
/
A.
High
Soil
-Loss
Coefficient:—
1.
Benchmark
2.
Soil
-loss
constraints
of
2,
3,
4,
5
tons/A
(*)
3.
Soil
-loss
taxes
on
$4, $2,
$1,
and
$.5/T
(*)
4.
Terracing
subsidies
of
$4,
$10,
$15,
$20,
and
$40/A
(*)
5.
Prohibition
of
chisel
plowing
2/
Results
of
runs
designated
by
an
*
asterisk
were
reported
in
an
article
by
Taylor
and
Frohberg
(1977)
and
are
duplicated
here
for
comparison
with
the
additional
runs.
26
Table
1
--Actual
acreages
of
crops
planted
in
1969
compared
to
acreages
in
the
benchmark
solution
of
the
Corn
Belt
model,
using
high
soil
-loss
coefficients
Corn
and
:
Hay
LRA
Region
Soybeans
Small
grains
••
:grain
sorghum
:
:
and
pasture
:Actual
:
Model
:
Actual
:
Model
:
Actual
:
Model
:
Actual
:
Model
Thousand
acres
91
Wisconsin
and
Minnesota
Sandy
Outwash
218
0
7
0
153
487
608
781
95
Southeastern
Wisconsin
:
Drift
Plain
:
1,677
789
191
789
781
1,810
1,981
1,930
97
Southwestern
Michigan
Fruit
and
Truck
Belt
.
109
95
16
0
46
223
106
136
98
Southern
Michigan
Drift
Plain
:
1,428
2,844
607
645
610
523
1,184
1,225
102
Loess,
Till,
and
Sandy
Prairies:
5,259
5,718
1,151
2,039
3,689
2,611
3,803
4,145
103
Central
Iowa
and
Minnesota
.
Till
Prairies
:
4,976
4,993
3,644
4,308
1,132
1,460
2,084
2,276
104
Eastern
Iowa
and
Minnesota
N)
Till
Prairies
:
1,630
1,356
789
1,356
465
415
984
1,021
--.1
105
Northern
Mississippi
Valley
Loess
Hills
:
1,440
1,980
133
0
660
22
2,511
2,644
106
Nebraska
and
Kansas
Loess-
Drift
Hills
:
1,474
1,028
280
748
418
382
1,013
1,112
107
Iowa
and
Missouri
Deep
Loess
Hills
:
3,189
2,001
1,406
2,001
530
328
2,205
2,613
108
Illinois
and
Iowa
Deep
Loess
and
Drift
:
7,874
8,241
4,090
4,619
1,218
247
3,096
3,328
109
Iowa
and
Missouri
Heavy
Till
Plain
:
1,207
890
897
611
253
0
2,927
3,270
110
Northern
Illinois
and
Indiana
Heavy
Till
Plain
:
1,472
1,541
1,135
1,541
203
56
291
395
111
Indiana
and
Ohio
Till
Plain
:
4,480
4,591
3,475
2,272
1,687
4,283
2,434
2,329
113
Central
Claypan
Areas
:
870
1,421
983
657
384
302
956
907
114
Southern
Illinois
and
Indiana
Thin
Loess
and
Till
Plain
:
1,729
2,035
1,420
2,035
563
0
1,236
1,364
115
Central
Mississippi
Valley
Wooded
Slopes
:
2,015
2,249
1,269
1,238
627
339
2,506
2,340
Total
:41,047
41,700
21,493
24,859
13,419
13,488
29,925
31,816
6.
Soil
loss
of
3
tons/A
and
terracing
subsidies
of
50
percent
of
costs,
$15/A
and
$20/A
7.
Nitrogen
restriction
to
50
lbs/A
8.
Nitrogen
restriction
to
50
lbs/A
and
soil
-loss
constraints
of
2,
3,
4,
5
tons/A
9.
Nitrogen
restriction
to
100
lbs/A
10.
Nitrogen
restriction
to
100
lbs/A
and
soil
-loss
constraints
of
2,
3,
4,
5
tons/A
B.
Low
Soil
-Loss
Coefficients:
1.
Benchmark
2.
Prohibition
of
chisel
plowing
3.
Restriction
of
chisel
plowing
4.
Soil
-loss
constraints
of
2,
3,
4
tons/A
5.
Soil
-loss
tax
of
$4/T
6.
100
percent
cost
sharing
for
terracing
7.
100
percent
cost
sharing
for
terracing
and
soil
-loss
constraint
of
2
tons/A
8.
Nitrogen
restriction
to
50
and
100
lbs/A
In
the
following
discussion,
selected
results
of
these
runs
will
be
presented
to
illuminate
the
nature
of
the
impacts
of
the
several
policies
and
policy
components
studied.
Benchmark
Solution
An
understanding
of
the
benchmark
runs
is
important
because
the
results
serve
as
a
basis
of
comparison
for
results
obtained
under
each
of
the
con-
strained
runs.
Table
1
gives
the
actual
acreages
of
crops
planted
in
the
several
regions
of
the
Corn
Belt
and
crop
acreages
developed
in
the
benchmark
solution
of
the
model
using
the
high
soil
-loss
coefficients.
The
two
sets
of
acreages
are
reasonably
consistent.
Regions
with
large
acreage
tend
to
be
more
accurately
reflected
in
the
model
results
than
some
of
the
regions
with
less
acreage.
Because
farm
operators
may
prefer
certain
crops
and
because
any
given
field
may
include
several
LCU's,
results
would
not
be
as
clear
cut
as
indicated
here.
These
factors
tend
to
give
model
results
indicating
more
efficient
crop
production,
with
higher
net
farm
income
and
less
soil
loss,
than
would
actually
be
observed.
The
LCU
designations
are
based
on
the
1967
Conservation
Needs
Inventory.
Thus,
conservation
practices
in
effect
at
that
time
are
reflected
in
the
model.
In
general,
the
benchmark
solution
indicates
a
somewhat
more
efficient
organization
for
the
production
of
crops
than
would
be
expected
in
practice.
This
fact
should
not
have
a
significant
adverse
effect,
however,
on
compar-
isons
among
solutions.
Restriction
of
Chisel
Plowing
The
runs
in
which
varying
levels
of
chisel
plowing
were
permitted
are
summarized
in
table
2.
When
chisel
plowing
was
used
in
all
situations
where
it
would
have
been
profitable,
as
reflected
in
two
benchmark
solutions,
over
28
Table
2--Computer-simulated
effects
of
restricting
chisel
plowing
Item
Unit
:Chisel
:
Chisel
:
Chisel
plowing
1/
:
plowing
:
plowing
:
on
33
million
.Benchnlar
:
prohibited
:
prohibited
:
acres
only
:(High
SLC)
/
:
(High
SLC)
:
(Low
SLC)
:
(Low
SLC)
Social
cost
a/
Consumer
cost
-
5/
Producer
cost
-
Corn
prices
Corn
Soybeans
Production
Corn
Soybeans
Mil.
dol.
Mil.
dol.
Mil.
dol.
Dol./bu.
Dol./bu.
:
Mil.
bu.
:
Mil.
bu.
0
0
0
2.46
5.26
3744.20
785.00
-270.80
210.51
-481.31
2.46
5.22
3736.60
792.30
-281.55
269.60
-551.15
2.46
5.22
3740.30
792.30
-269.14
222.60
-491.74
2.46
5.22
3738.40
792.30
Acres
terraced
Mil.
acres
0
0
0
0
Reduced
tillage
:
Mil.
acres
77.33
0
0
33.22
Gross
soil
loss
Mil.
tons
595.81
2275.85
578.07
478.19
Gross
soil
loss
:
Tons
per
:
acre
planted
5.30
20.35
5.17
4.27
Insecticide
expenditures
index
100
92
97
98
Herbicide
expends
itures
index
:
100
86
87
93
N
load
:
Bil.
lbs.
4.19
4.19
4.19
4.19
N
load
:
Lbs./acre
100.58
100.93
100.24
100.21
1/
Some
small
price
and
production
differences
were
found
between
the
benchmark
run
with
low
soil
-loss
coefficients
and
the
benchmark
run
with
high
soil
-loss
co-
efficients,
These
differences
must
be
due
to
the
random
choices
possible
in
a
model
of
this
size
and
complexity
and
to
rounding
errors.
To
avoid
confusion,
only
the
run
for
the
high
soil
-loss
coefficients
is
shown.
The
minor
differences
that
were
found
should
remind
the
reader
of
the
need
to
interpret
all
results
with
care;
minor
differences
among
model
runs
may
not
be
significant.
2/
SLC
denotes
soil
-loss
coefficients
used
in
the
model.
3/
Social
cost
is
defined
to
be
the
sum
of
producer
cost
and
consumer
cost.
4/
The
method
used
to
estimate
consumer
cost
accounts
for
both
the
price
and
quantity
impacts.
5/
Producer
cost
includes
the
impact
on
returns
to
land,
labor,
capital,
and
management.
29
77
million
acres
were
chisel
plowed,
resulting
in
substantial
reductions
in
soil
loss.
The
magnitude
of
the
impact
can
be
appreciated
by
comparing
runs
where
chisel
plowing
is
completely
prohibited
with
those
restricting
chisel
plowing
to
33
million
acres
--the
estimated
acreage
on
which
the
practice
is
currently
used
(see
figure
1).
With
high
soil
-loss
coefficients,
use
of
chisel
plowing
(wherever
profitable)
would
have
reduced
soil
loss
to
26
percent
of
the
more
than
20
tons
per
acre
lost
when
chisel
plowing
was
pro
-
22
20
18
16
14
l2
0
to
0.
0
8
0
(i)
6
2
>
High
Soil
Loss
Coefficients
Model
Low
Soil
Loss
Coefficients
Model
0
77.33
0
3322
77.33
Million
Acres
Chisel
Plowed
Figure
1.
Average
soil
loss
per
acre
per
year
with
and
without
chisel
plow
constants.
30
hibited.
With
low
soil
-loss
coefficients,
chisel
plowing
on
33
million
acres
would
reduce
losses
from
5.33
to
4.27
tons per
acre,
while
use
on
77
million
acres
would
hold
soil
losses
to
2.96
tons
per
acre.
Because
soil
losses
would
have
been
reduced
if
chisel
plowing
were
expanded,
and
since
more
farmers
continue
to
adopt
the
practice,
the
benchmark
runs
may
be
interpreted
as
a
projection
of
what
can
be
expected
in
the
future
under
the
present
institutional
arrangement.
All
soil
-loss
and
nitrogen
fertilizer
constraint
runs
in
this
analysis
were
compared
to
the
benchmark
solutions
where
chisel
plowing
was
not
limited.
If
all
runs
with
soil
-loss
constraints
were
made
with
no
restrictions
on
chisel
plowing
(thus
showing
the
tendency
to
shift
to
that
practice
as
a
means
of
meeting
the
constraint)
and
were
compared
to
a
run
with
restricted
chisel
plowing
(reflecting
current
practice)
the
following
changes
would
be
observed:
(1)
the
reduction
in
soil
loss
from
soil
-loss
constraints
would
be
greater,
(2)
the
social
cost
of
soil
-loss
control
would
be
reduced,
and
(3)
some
modifications
in
crop
production
pattern
changes
might
be
observed.
Thus,
the
manner
in
which
chisel
plowing
is
handled
in
the
model
results
in
conser-
vative
estimates
of
the
impact
of
expenditures
for
soil
erosion
control.
Soil
-Loss
Limitations
The
results
presented
in
figure
2
illustrate
the
impact
of
restricting
Corn
Belt
soil
losses
to
2,
3,
4,
and
5
tons
per
acre.
If
the
low
soil
-loss
coefficients
were
correct,
costs
to
society
would
not
be
large.
If
the
high
coefficients
were
accurate,
costs
would
be
significant, especially
if
the
lower
soil
-loss
restrictions
were
adopted.
Because
of
the
manner
in
which
the
model
is
constructed,
it
is
not
possible
to
model
the
impact
of
adopting
the
soil
-loss
tolerances
set
by
the
SCS.
These
tolerances
generally
vary
between
2
and
5
tons,
so
results
presented
here
should
bracket
the
expected
impact.
SCS
limits
are
established
at
a
level
which
will
not
prevent
produc-
tion;
hence
the
impact
would
be
less
severe
with
those
limits
than
indicated
by
the
model
solution.
In
the
latter
case,
considerable
acreage
is
not
used
for
production
because
the
technology
required
to
achieve
the
specified
soil
-
loss
limit
is
not
available.
(Erosion
is
assumed
to
cease
to
be
a
problem
on
land
removed
from
the
productive
base.)
Contrary
to
popular
belief,
the
burden
of
the
restrictions
falls
more
on
consumers
than
producers.
For
all
soil
-loss
restrictions,
consumers
lose,
while
producers
gain
with
some
restrictions
and
lose
with
others.
In
this
particular
case,
it
is
thought
the
mixed
impact
on
producers
results
from
idiosyncrasies
of
the
model
(related
to
steps
on
the
demand
function).
Allow-
ing
for
these,
it
would
seem
that
the
effect
on
producers
is
either
very
small
or
beneficial.
Although
the
restrictions
increase
the
prices
of
major
crops
and
the
cost
of
production
on
land
in
production,
producers
benefit
because
effects
on
costs
are
smaller
than
price
effects.
The
crop
price
and
produc-
tion
impacts
using
the
low
soil
-loss
coefficients
are
not
shown
in
figure
2
because
they
are
insignificant.
For
example,
soybean
production
drops
only
3
percent
with
a
2
-ton
-per
-acre
limit.
Of
course,
producers
with
high
soil
-
loss
rates
would
earn
lower
profits
if
a
restriction
were
imposed;
those
without
serious
soil
erosion
problems
would
gain.
Thus,
we
see
that
under
a
soil
-loss
restriction
the
largest
losses
would
be
taken
by
producers
with
serious
erosion
problems
and
by
consumers.
31
Soi
l
Loss
Constraints
(tons
per
acre
per
year)
28
A
8
O
8
CD
8
0)
8
Change
(mi
l.$)
A
r)
m
o
8
0
0
8
cn
0
0
8
O
0 0
O
Crop
Prices
(percent
of
benchmark)
A
u
m
-4
,3,
0
6
=
5
W
zo
0
0
0 0 0 0 0 0 0 0 0
0
CU
A
A
O
0'
I
I I
0
C
O
a
0
1
1
1
1
1
C)
0
3
Soi
l
Loss
(tons/acre)
0
-
m
Acreage
and
Corn
and
Soybean
Production
(percent
of
benchmark)
w
20
=
cn
A
(N)
A
0
(Cl
0
0)
0
CO
0
0
O
g g 0
O
g
i
g
a
CD
a
CD
cD
C)
Figure
2.
Impacts
of
soil
loss
limits.
32
Although
consumers
would
pay
more
for
food,
some
of
them,
and
many
farmers,
would
benefit
from
a
restriction
because
off
-site
damages
would
be
reduced.
All
future
consumers
would
be
expected
to
benefit
from
the
mainte-
nance
of
a
higher
quality
soil
resource.
The
soil
-loss
restrictions
do
not
significantly
affect
the
total
use
of
pesticides
(the
only
substantial
changes
in
pesticide
occur
in
those
runs
in
which
the
acreage
chisel
plowed
changes).
With
increasingly
stringent
soil
-
loss
limits,
nitrogen
use
per
acre
increases
slightly,
but
the
total
amount
used
decreases
as
a
result
of
reduced
corn
acreage.
Soil
-Loss
Taxes
Figure
3
summarizes
impacts
of
imposing
soil
-loss
taxes
at
rates
of
$.50,
$1.00, $2.00,
and
$4.00
per
ton
of
gross
soil
loss.
The
net
social
cost
of
achieving
reductions
in
soil
loss
would
be
somewhat
less
with
soil
-loss
taxes
than
with
soil
-loss
limits.
Consumers
would
fare
somewhat
better.
The
impact
on
producers
would
be
reversed.
Soil
-loss
taxes
would
result
in
a
large
negative
impact
on
producers,
as
is
reflected
by
the
significant
govern-
ment
receipts
that
would
be
generated
by
the
taxes.
Crop
prices
would
be
significantly
affected.
The
price
of
soybeans
--
the
most
erosive
of
the
crops
--would
increase
dramatically,
while
corn
prices
would
hold
about
constant;
prices
of
non
-row
crops
would
decrease
signifi-
cantly.
Higher
soybean
prices
would
be
consistent
with
the
significant
reduction
in
soybean
production
in
the
Corn
Belt.
As
expected,
all
of
the
impacts
(except
for
hay
and
pasture
prices)
were
reduced
when
the
$4.00
per
ton
constraint
model
was
run
with
the
low
soil
-
loss
coefficients.
Terracing
Subsidies
Figure
4
summarizes
the
impacts
of
terracing
subsidies
ranging
from
$5
to
$40
per
acre.
In
the
model,
costs
of
terracing
were
annualized
to
reflect
the
annual
impact
on
farm
income
of
an
investment
in
a
terrace
system.
It
was
assumed
that
an
annual
terracing
subsidy
at
a
fixed
rate
per
acre
would
be
paid
to
encourage
installation
of
terraces.
It
was
assumed
that
the
total
amount
would
be
paid
regardless
of
the
annual
cost
of
the
terrace.
Thus,
in
the
$40
-per
-acre
run,
the
farm
operator
would
receive
compensation
above
the
actual
cost
of
installing
terraces.
Since
the
$40
-per
-acre
-per
-year
subsidy
would
be
higher
than
the
actual annual
cost
of
terracing
on
any
of
the
land
where
the
technique
was
assumed
to
be
possible,
the
$40
run
would
indicate
the
maximum
possible
impact
from
a
terracing
program.
Prices
and
acreages
under
the
several
runs
were
not
summarized
in
figure
4
because
there
were
no
significant
changes
from
the
benchmark
solution.
The
high
government
cost
and
high
levels
of
producer
benefits
under
the
larger
terrace
subsidies
result
from
the
way
subsidies
were
assumed
to
be
paid;
that
is,
more
funds
would
be
paid
to
producers
than
necessary
to
fully
compensate
their
terracing
costs.
Governmental
costs
and
producer
benefits
could
cancel
each
other
where
overpayment
occurs.
Thus,
the
terrac-
ing
subsidy
plan
is
a
reasonable
indication
of
the
cost
of
achieving
given
levels
of
reduction
in
soil
losses.
It
is
of
particular
interest
that
the
33
(dollars/ton)
U)
E
1200
1000
800
600
400
200
0
x
y-200
°
-400
co
N
-600
o
-800
C/)
-1000
-1200
-1400
-1600
0=
Revised
Soil
Loss
Coefficient
-
Government
Receipts
7
Consumers'
Surplus
0
Net
Social
Cost
Producers'
Surplus
-
I
1
1
I
1
2
3
4
112
110
108
•-106
-1C
t-
o
E
104
a)
102
.o
15.
100
0
98
a)
96
94
•_
92
0
0
90
88
86
84
0
0=
Revised
Soil
Loss
Coefficient
-
oybeans-
Corn
\_
0
Oats
Wheat
Hay
Pasture
I
1
I
I
1
2
3
4
0.
Revised
Soil
Loss
Coefficient
-
0
1
1
I
0
1
2
3
4
.
108
O
4
-106
C
104
ip
0.
102
0
100
-0
O
a.
a-
98
O
96
a)
.0
0
(1)Q.
4
'a
°
92
C
iF)
90
-
o
c
88
0
0,
86
0
084
0
0.
Revised
Soil
Loss
Coefficient
-
Corn
Acreage
Soybeans
1
I
I
1
1
2
3
4
Impacts
of
soil
—loss
taxes.
LEVEL
OF
SUBSIDY
(dollars
per
acre)
CHANGE
(mil.$)
O
5
N)
O
(.4
O
s
i
-P
0
0
a
0
0
co
0
0
a)
0
0
.6
O
O
n)
r\.)
.p.
0
0 0
0
0
0
0
a)
o
o
co
o
O
O
0
O O
_r
,
8
I
I
I
I
I I
-
8
Cl
M<
ox,
(nn
-
CA
Z
Co
-I
M
Z
M
Z
0
-1
n
m
c3
.-
D
cn
-i
0
m
cn
rn
v)
n
cn
,-
I>
r
-
I
I
I
I
I I
cn
-
I)
0
c
x)
x
-
0
C
0
I
--
Co
cn
73
(/).
SOIL
LOSS
(tons/acre/year
)
0
N.)
W
A
al
0
•••
••••••1
5 -
O
_
8
-
ACRES
TERRACED
(millions)
O
to
5
Er
-
)
N
(A
c.A
O
0
(../1
Figure
4.
Impacts
of
terrace
subsidies.
35
model
showed
little
reduction
in
soil
loss
or
only
a
slight
increase
in
acres
terraced
when
the
subsidy
level
was
increased
from
$20
to
$40
per
acre.
Combinations
of
Soil
Erosion
Control
Policies
Figure
5
compares
impacts
of
several
approaches
to
controlling
soil
losses.
Policy
D
would
combine
a
soil
-loss
restriction
of
3
tons
per
acre
with
a
50
percent
reduction
in
the
cost
of
terracing
through
a
government
cost
-sharing
program.
Policy
E
would
combine
a
soil
-loss
restriction
of
3
tons
per
acre
with
a
$15
-per
-acre
terracing
cost
subsidy,
the
full
amount
of
which
would
be
paid
regardless
of
the
cost
of
terracing
to
any
farm
operator
installing
terraces.
In
policy
F,
a
soil
-loss
restriction
of
3
tons
per
acre
would
be
imposed
and
cost
-sharing
at
$20
per
acre
would
be
provided:
that
is,
a
farmer
who
terraced
his
land
would
be
eligible
to
receive
the
full
cost
of
the
terraces
--up
to
$20
per
acre.
In
each
case,
the
terracing
-cost
subsidy
is
computed
on
an
annualized
basis.
Also
included
in
the
figure
is
policy
A,
the
benchmark
solution;
policy
B,
which
would
provide
a
$15
terracing
subsidy
alone;
and
policy
C,
which
would
include
only
a
soil
-loss
restriction
of
3
tons
per
acre.
From
these
results
it
is
apparent
that
the
impacts
of
the
three
combi-
nation
policies
(in
terms
of
sdil-loss
rates
and
economic
effects)
would
be
approximately
equivalent
to
those
of
a
3
-ton
-per
-acre
soil
-loss
restriction.
They
would
also
be
equivalent
in
terms
of
acreage
planted,
production
of
corn
and
soybeans,
and
commodity
prices.
The
social
costs
for
all
of
the
combi-
nation
policies
would
be
higher
than
for
the
terracing
subsidy
alone,
reflect-
ing
primarily
the
higher
cost
to
consumers
in
the
form
of
reduced
consumers'
surplus.
Producers
would
benefit
from
all
of
the
policies,
but
the
combination
policies
would
generate
a
higher
level
of
producer
benefits
than
the
soil
-loss
limits
alone
or
the
terracing
subsidy
alone.
The
difference
would
be
greater
when
compared
to
the
terracing
subsidy
alone.
The
combination
policies
and
the
soil
-loss
restrictions
all
would
generate
lower
levels
of
soil
loss
than
the
terracing
subsidy
alone.
This
$15
-per
-acre
terracing
subsidy
would
reduce
soil
losses
from
5.3
to
3.46
tons
per
acre.
A
soil
-loss
restriction
of
3
tons
per
acre
would
generate
a
soil
loss
of
2.25
tons
per
acre.
The
most
effective
of
the
combination
policies
(one
combining
the
soil
-loss
limit
with
a
$15
-per
-
acre
subsidy)
would
reduce
soil
losses
to
1.87
tons
per
acre.
Thus,
the
terracing
subsidy
alone
would
reduce
soil
losses
35
percent.
Soil
-loss
limits
alone
would
reduce
it
58
percent.
The
most
effective
of
the
combination
policies
would
reduce
soil
losses
65
percent.
Relative
Efficiency
of
Soil
-Loss
Control
Policies
Figures
6,
7,
8,
and
9
indicate
the
relative
economic
efficiency
of
the
several
policies
for
controlling
soil
loss.
The
changes
in
net
social
cost,
producers'
surplus,
consumers'
surplus,
and
governmental
cost
are
plotted
relative
to
the
percentage
reduction
in
gross
soil
loss
in
the
Corn
Belt.
It
is
important
to
note
three
additional
categories
of
costs
and
benefits
not
included
in
these
calculations:
1.
Costs
of
administering
the
policies
in
question.
2.
Environmental
benefits
associated
with
adopting
the
policies.
3.
Long
run
impacts
on
soil
productivity.
36
Change
(mil.
$)
Soil
Loss
(tons/acre/year)
Change
In
Change
In
Change
In
Change
In
Net
Social
Consumers'
Producers'
Government
1000
-
Cost
Surplus
Surplus
Cost
800-
600-
400-
200-
A
A
B
A
B
C
D
E
F
A
C
L.
-200-
B
C
D
E
F
C
D
E
F
B
D
E
F
-400-
-600-
-800-
-1000-
-1200-
5
4
3
2
0
A
(i)
0
E
Acres
Terraced
6-
5-
4-
3
2
1
0
A
B
C
D
E
F
A
=
Benchmark
Solution
B
=
$15/acre
Terracing
Subsidy
C
=
Soil
Loss
5
3
tons/acre/year
D
=
Soil
Loss
3
tons/acre/year
and
50%
Terracing
Cost
Subsidy
E
=
Soil
Loss
5
3
tons/acre/year
and
$15/acre
Terracing
Subsidy
F
=
Soil
Loss
:5
3
tons/acre/year
and
$
20/acre
Terracing
Cost
Reduction
Figure
5.
Impacts
of
terracing
subsidies
and
soil
-loss
constraints.
37
Net
Increase
in
Social
Cost
(
mil
$)
1300
1200
1
100
1000
900
800
700
600
500
400
300
200
100
0
I
I
I
I
I
I
0
High
Soil
Loss
Coefficients
1=
Soil
Loss
Limits
2=Terrace
Subsidy
3=
Soil
Loss
Tax
4=
Soil
Loss53,
50%
Terrace
Cost
Subsidy
5=
Soil
Loss
<3,
$
15
Terrace
Subsidy
6=
Soil
Loss
$
20
Terrace
Cost
Reduction
7=
No
Straight
Row
Cultivation
Low
Soil
Loss
Coefficients
la
=
Soil
Loss
Limits
lb
=
Soil
LossS2,
100%
Terrace
Subsidy
2a=100%
Terrace
Subsidy
3a
=
Soil
Loss
Tax
$
4.00
2a
07
8
5
6
lb
04
3
03a
0
10
20
30
40
50
60
Reduction
in
Gross.
Soil
Loss
(percent)
70
Figure
6.
Change
in
net
social
cost
and
percentage
reduction
in
gross
soil
loss.
80
90
1000
0
5
800
06
600
04
400
fir)
,
0
lb
200
_
E
!
o
0
__
I
I
i
I
I
,..
(f)
n
-200_
70
-
cr)
if)
(...)
=
-400.—
_
2
0
High
Soil
Loss
Coefficients
cL
1=
Soil
Loss
Limits
c
-600
_
2=
Terrace
Subsidy
._
a>
3=
Soil
Loss
Tax
cn
o
c
-800
4=
Soi
l
Loss
....5
3,
50%
Terrace
Cost
Subsidy
.c
5=
Soil
Loss
s
3,
$15
Terrace
Subsidy
U
6
=Soil
Loss
Is.
3,
$20
Terrace
Cost
Reduction
-
1000
_
7
=
No
Straight
Row
Cultivation
03a
-1200
-1400
-
1600
0
O
Low
Soil
Loss
Coefficients
Ia
=
Soil
Loss
Limits
lb
=
Soil
Loss
<
2
,I00%
Terrace
Subsidy
2a
=100°4
Terrace
Subsidy
3o
=
Soil
Loss
Tax
$4.00
I
I
I I
I-
I
10
20
30
40
50
60
Reduction
in
Gross
Soil
Loss
(percent)
70
80
90
Figure
7.
Change
in
producers'
surplus
and
percent
reduction
in
gross
soil
loss.
1200
1000
800
600
400
E
cn
200
cn
0
'In
E
-200
(r)
O
c
U
-400
--
a)
r
,
c
-600
C
I
I
I
I
I
1 1
I
o
High
Soi
l
Loss
Coefficients
1=
Soil
Loss
Limits
2=
Terrace
Subsidy
3=
Soil
Loss
Tax
4=
Soi
l
Loss
5
3,50%
Terrace
Cost
Subsidy
5=
Soil
Loss
s
3,
$15
Terrace
Subsidy
6
=Soi
l
Loss
<
3,
$20
Terrace
Cost
Reduction
7=
No
Straight
Row
Cultivation
0
Low
Soil
Loss
Coefficients
la
=
Soi
l
Loss
Limits
lb
=
Soil
Loss
5
2
,100%
Terrace
Subsidy
2a
=100%
Terrace
Subsidy
3a
=
Soil
Loss
Tax
$4.00
-800
_
-1000
_
1200
1400
2
2a
-0
- 0
I
07
El.,
c1
0
la
3a
CI
lb
6_5
0
10
20
30
40
50
60
70
80
90
Reduction
in
Gross
Soi
l
Loss
(percent)
Figure
8.
Change
in
consumers'
surplus
and
percent
reduction
in
gross
soil
loss.
Change
in
Government
Cost
(mil.$)
1200
1000
800
ra
600
_
8
Cr
400
200
-200
-400
-
1000
-
1200
-1400
T
I
I
I
0
High
Soi
l
Loss
Coefficients
0
Low
Soil
Loss
Coefficients
I=
Soil
Loss
Limits
lb
=
Soi
l
Loss
5.
2
,100%
Terrace
Subsidy
2=
Terrace
Subsidy
2a
=100%
Terrace
Subsidy
-
3=
Soil
Loss
Tax
3a
=
Soil
Loss
Tax
$4.00
4=
Soi
I
Loss
s.
3,
50%
Terrace
Cost
Subsidy
5=
Soil
Loss
s
3,
$15
Terrace
Subsidy
-
6
=Soil
Losss
3,
$20
Terrace
Cost
Reduction
0
04
oe
❑lb
05
1
1
I
1
1
I
I
10
20
30
40
50
60
70
80
Reduction
in
Gross
Soil
Loss
(percent)
Figure
9.
Change
in
government
cost
and
percent
reduction
in
gross
soil
loss.
When
comparing
results
generated
by
the
model
(using
the
high
soil
-loss
coefficients),
it
is
clear
that
the
soil
-loss
tax
would
be
the
most
economi-
cally
efficient
overall,
as
would
be
expected
from
economic
theory.
However,
while
net
social
costs
of
achieving
a
given
reduction
in
soil
loss
would
be
lowest
in
the
case
of
taxation,
it
is
important
to
realize
that
such
a
policy
would
significantly
reduce
producers'
surplus
as
a
result
of
taxes
paid.
These
governmental
tax
receipts
would
be
reflected
in
the
net
social
cost,
raising
the
overall
efficiency
of
that
policy.
The
taxation
policy,
then,
would
be
the
only
one
generating
a
significant
reduction
in
the
producers'
well-being,
with
benefits
to
both
government
and
to
consumers.
It
is
also
likely
that
administrative
costs
--primarily
for
tax
collection
--would
be
quite
significant
under
a
policy
of
this
type.
Soil
-loss
restrictions,
except
for
the
2
-ton
-per
-acre
limit,
would
approximate
the
tax
solution
reasonably
well
when
high
soil
-loss
coefficients
were
used.
That
is,
a
soil
-loss
limit
policy
would
not
be
significantly
less
efficient
than
the
tax
policy.
The
distribution
of
benefits
and
costs,
however,
would
be
quite
different.
If
a
policy
limiting
soil
loss
to
3
tons
per
acre
per
year
would
result
in
a
$500
million
increase
in
cost
over
the
benchmark
solution,
the
total
negative
impact
on
consumers
would
be
approxi-
mately
$1
billion,
because
producers
gain
$500
million.
As
noted
earlier,
low
soil
-loss
coefficients
would
significantly
lower
the
net
economic
impacts
to
less
than
$200
million.
As
previously
discussed,
the
higher
net
social
cost
generated
by
soil
-
loss
restrictions
would
be
due
in
part
to
the
fact
that
some
land
must
be
taken
from
production
to
meet
soil
-loss
limits,
which
were
applied
on
a
uniform
per
-acre
basis.
Hence,
impacts
on
individual
farmers
would
be
quite
variable.
While
some
farmers
would
receive
higher
net
incomes
resulting
from
higher
prices
for
the
major
crops,
others
would
be
forced
to
remove
land
from
pro-
duction
and
would,
therefore,
be
adversely affected.
Terracing
policies
would
not
be
as
effective
in
reducing
soil
losses
as
the
soil
-loss
restriction
or
taxation
policies.
With
a
terracing
subsidy
providing
a
fixed
number
of
dollars
per
acre,
there
would
be
a
significant
shift
of
funds
from
taxpayers
to
farmers
as
a
result
of
subsidizing
at
a
higher
level
than
the
cost
experienced.
Policy
2A
(a
100
-percent
subsidy)
shows
that
the
transfer
would
be
eliminated
if
the
subsidy
were
based
on
a
percentage
of
the
actual
cost
incurred,
as
in
the
present
practice.
Combining terracing
subsidies
with
soil
-loss
restrictions
would
produce
a
more
efficient
result
than
can
be
achieved
by
a
soil
-loss
restriction
alone.
In
this
case,
benefits
would
flow
to
producers
from
both
consumers
and
tax-
payers.
Soil
-Loss
and
Nitrogen
Restrictions
Figure
10
summarizes
some
of
the
major
impacts
of
imposing
soil
-loss
limits
while
constraining
maximum
nitrogen
application
rates
to
50
and
100
pounds
per
acre.
The
nitrogen
restriction
would
reduce
application
rates
from
approximately
140
pounds
per
acre
to
the
constraints
level.
The
constraints
were
assumed
to
apply
to
all
sources
of
nitrates
--including
those
added
by
legumes.
They
would
be,
therefore,
quite
restrictive.
In
general,
it
is
42
3000
---
2000
-69
3000
2000
E
3000
2000
E
50
E
1000
in
1000
1000
in
100
0
cn
1
7
0
3
NR
NR
Cr)
-1000
100
-1000
"
100
In
50
-
2000
E
-
2000
-2000
a)
Z
-3000
U)
0
-3000
11,
0
-3000
0_
50
a)
-4000
-4000
-4000
CP
NR
.
No
Nitrogen
NR
=No
Nitrogen
a)
rn
NR
=
No
Nitrogen
_c
-5000
Restrict
ion
°
-5000
Restriction
o
-
5000
Restriction
50
=
N
5
50
lbs/A
50=N
5
50
lbs/A
50=
N
5
50
lbs/A
100
=
N
<
100Ibs/A
100.N
5
100
lbs/A
100=
N
5
100
lbs/A
-6
None
I
1
I
1
-6000
None
-6000.
None
5
4
3
2
5
4
3
2
5
4
3
2
Soil
Loss
Constraints
(tons/acre/year)
g
140
w.
_
x
A
=
Acreage
o
0
130
C
r
Corn
Production
(1)
E
SB
=
Soybean
Production
O
120
50
=
N
5.
50
lbs
/A
_
c c
o
w
ICO=
N
:5
100
lbs/A
110
1
6
4
6
sBioo
0_
-=
100
cn
C
°
100
c
90
S
8
50
0
80
0
-
a
C
0
o
o
CL
I
1 1 1
60
None
5
4
3
2
,—.
140
-V
E
130
_c
w
120
.o
4-
o
110
a)
u
100
41)
0.
-
90
Crop
Pr
ices
S50
S100-
100
C
=
Corn
80
S
=
Soybeans
W=
Wheat
70
W
I
W50
60
1
I
1
1
None
5
4
3
2
140
130
120
110
100
90
80
70
60
P100
P50
H50
Hioo
0
=
Oats
H
=
Hay
P
=
Pasture
I
I I I
None
Soil
Loss
Constraints
(tons/acre/year)
5
4
3
2
Figure
10.
Impacts
of
restrictions
on
nitrogen
application
and
soil
loss.
43
clear
that
the
50
-pound
-per
-acre
nitrogen
restriction
would
have
a
significant
impact
when
applied
alone;
if
more
stringent
soil
-loss
limits
were
added,
the
impact
would
generally
increase.
The
impact
of
100
-pound
-per
-acre
nitrogen
restriction
would
not
be
significantly
different
from
the
impact
of
a
soil
-
loss
restriction
alone;
the
impact
on
producers
would
be
almost
exactly
the
same.
Another
significant
result
would
be
increased
producers'
income
when
nitrogen
applications
were
restricted.
Thus,
while
farm
income
would
be
reduced
by
restrictions
at
the
individual
farm
or
regional
level
(realization
of
this
explains
the
negative
farmer
reaction
to
nitrogen
restrictions),
restrictions
at
the
national
level
would
improve
overall
farm
income.
The
difference
is
explained
by
the
price
-increasing
effect
of
a
national
restric-
tion.
Nitrogen
restrictions
alone
have
a
reasonably
strong
impact
on
the
agri-
cultural
sector.
Reducing
the
level
of
nitrogen
applied
would
reduce
yield
and
profitability
of
corn,
making
soybeans
relatively
more
attractive.
At
the
50
-pound
-per
-acre
nitrogen
limit,
yield
would
be
reduced
enough
to
reduce
total
production,
despite
increased
acreage
of
corn
and
beans
relative
to
that
of
other
crops.
When
increased
prices
for
corn
and
soybeans
are
combined
with
lower
production
costs
(resulting
from
the
use
of
less
nitrogen)
net
farm
income
would
increase
$2
billion.
The
100
-pound
-per
-acre
restriction
would
not
significantly
influence
producers'
income.
Both
the
50
and
100
pound
restrictions
would
generate
costs
to
consumers,
with
the
50
-pound
-per
-acre
restriction
having
a
much
more
significant
effect.
When
soil
-loss
restrictions
are
applied
along
with
nitrogen
restrictions,
impacts
are
increased.
Soil
-loss
restrictions
would
force
some
acreage
out
of
production
entirely,
because
soil
-loss
limits
could
not
be
met,
as
dis-
cussed
above.
In
addition,
at
the
more
restrictive
soil
-loss
limits,
the
use
of
intensive
row
-crop
production
would
be
reduced
in
favor
of
less
intensive
crop
rotations,
significantly
reducing
wheat
and
oats
prices.
Reductions
in
yield
resulting
from
fertilizer
restrictions
and
lower
row
-crop
acreage
would
combine
to
reduce
production
and
increase
prices
for
corn
and
soybeans.
This
combination
would
lead
to
a
significant
positive
impact
on
producers'
surplus
and
a
major
negative
impact
on
consumers'
surplus.
While
the
results
presented
here
indicate
the
general
tendency
of
response
to
specific
restrictions,
the
fact
that
demand
curves
for
the
minor
crops
are
not
included
may
introduce
some
bias
(a
fixed
quantity
of
the
minor
crops
is
specified
in
the
model
under
a
perfectly
inelastic
demand
curve).
The
model
does
not
have
as
much
fexibility
to
meet
these
constraints
as
would
be
expected
in
the
real
world.
The
general
findings,
however,
are
considered
to
be
a
reasonable
reflection
of
what
could
be
expected
in
a
real
situation
--
reduced
corn
and
soybean
acreage,
and
consequently
higher
prices
for
these
crops
resulting
in
improved
farm
income,
a
negative
impact
on
consumers,
and
an
overall
impact
in
terms
of
net
social
costs.
CONCLUSION
This
study
indicates
that
reasonable
soil
erosion
control
programs
can
be
implemented
without
having
serious
economic
impacts
on
the
agricultural
44
sector
or
on
consumer
expenditure)!
If
however,
the
high
soil
loss
coeffi-
cients
are
accurate,
and
if
a
stringent
soil
loss
restriction
such
as
a
2
-ton
-
per
-year
limit
were
adopted,
the
economic
impacts
would
be
serious.
Serious
economic
impacts
would
also
be
generated
by
tight
controls
on
nitrogen
use.
Contrary
to
popular
belief,
the
economic
burden
of
the
restriction
falls
more
on
consumers
than
on
producers
for
many
of
the
controls
considered.
This
occurs
because
the
model
includes
demand
and
supply
functions
for
the
major
crops,
allowing
impacts
of
controls
to
be
translated
into
higher
prices
generating
higher
gross
receipts
at
the
farm
level.
The
higher
receipts
help
offset
or,
in
some
cases,
more
than
offset
the
higher
production
costs
or
lower
yields
associated
with
controls.
Such
results
will
not
be
demonstrated
by
a
model
limited
to
fixed
commodity
prices.
Two
sets
of
soil
loss
coefficients
were
used
in
the
study.
One
set
was
supplied
by
the
Federal
Soil
Conservation
Service,
while
the
other
set
was
supplied
by
Illinois
Soil
Conservation
Service
personnel.
It
appears
that
the
two
sets
of
coefficients
bracket
actual
soil
losses.
To
obtain
more
precise
estimates
of
the
economic
impacts
of
non
-point
pollution
controls,
precise
estimates
of
soil
loss
coefficients
must
be
obtained.
3/
Although
not
tested
with
this
model,
the
tolerance
limits
used
by
the
Soil
Conservation
Service
are
expected
to
be
"reasonable"
limits.
LITERATURE
CITED
Council
on
Agricultural
Science
and
Technology
"Effect
of
Increased
Nitrogen
Fixation
on
Stratospheric
Ozone,"
Report
No.
53.
Ames,
Iowa,
Jan.
1976.
Taylor,
C.
R.,
and
K.
Frohberg,
"The
Welfare
Effects
of
Erosion
Control,
Banning
Pesticides,
and
Limiting
Fertilizer
Application
in
the
Corn
Belt,"
Amer.
J.
Agr.
Econ.,
Vol.
59,
No.
1,
Feb.
1977,
pp.
25-36.
45