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OCR for page 99
SBenefit
Assessment
INTRODUCTION
If EPA determines that a pesticide meets or exceeds the risk criteria
defined in 40 CFR 162.11 (see Chapters 2 and 4), the Agency is obligated
to issue an RPAR. If the presumption of risk is not successfully rebutted,
some type of regulatory response is likely to be forthcoming. In making a
determination as to the specific form the response should take, the
Agency is allowed by 40 CFR 162.11 to take into consideration the
findings of an analysis of the benefits arising from the use of a pesticide.
Moreover, analyses of the economic and social impacts of pesticide
regulatory actions are required by the FEPCA of 1972 and its subsequent
amendments. The purpose of this chapter is to examine critically the
current USDA/EPA approach to assessing the benefits of pesticide usage
and, where appropriate, to recommend certain changes in that approach.
This chapter argues that oPP's benefit-risk methodology could be
improved by better use of standard analytical procedures. At the outset,
we wish to make it clear that federal pesticide law does not require the
use of a formal benefit-cost (or risk) analysis. Except where a statute
expressly so provides, the courts have not interpreted a statutory duty to
balance benefits against costs to require a formal benefit-cost (or risk)
analysis. Instead, agencies like EPA have taken it upon themselves to
adapt formal benefit-risk methodology to the regulatory problem at
hand. The difference between a duty to carry out a formal benefit-risk
99
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REGULATING PESTICIDES
analysis and to balance benefits against risks is significant, for the degree
of rigor required by the latter is much less than that required by the
former. If an agency undertakes a formal benefit-risk analysis, it should
use the best available state of the art; we offer some suggestions for
improving the procedures that oPP has voluntarily agreed to follow.
Before turning to a critical evaluation, two introductory and clarifying
comments are in order. The first is definitional. In connection with the
evaluation of government regulations, the term "benefit" is usually
employed to describe the advantages of a regulation such as the
improvement in human health that will result from prohibiting the use of
a hazardous pesticide (see, for example, NRC 1977~. Consequently, the
reader is cautioned that USDA/EPA defines benefits differently. Spe-
cifically, "benefits" are defined as desirable erects resulting from
continued use of a pesticide. In this context, a regulatory action limiting
the use of a pesticide would result in a reduction in risks and a loss of
benefits. This report adheres to the definitions employed by the
USDA/EPA analysts.
The second point is concerned with the presumed objectives of a
benefit assessment. In keeping with conventional principles of benefit-
cost analysis (which are discussed in more detail later in this chapter), a
benefit assessment should strive to meet two separate but related
objectives. First, a benefit assessment should attempt to measure the
"real" (or economic efficiency) benefits of a pesticide that is, the extent
to which use of a pesticide contributes to the available quantity of
desirable goods and services, thereby enhancing society's standard of
living. Second, a benefit assessment should attempt to identify and
quantify the distributional erects (or "economic impacts") associated
with use of a pesticide. In principle, a distributional (or economic
impact) analysis involves more than a determination of how the real
benefits are spread among various groups. It also encompasses an
assessment of the distribution of "pecuniary" erects (that is, transfers of
purchasing power from one group to another arising out of price
changes). The distinction between economic efficiency erects and
distributional impacts is important and will be emphasized in our
. · .
olscusslon.
This chapter is devoted to procedures and methods for assessing the
benefits of using particular pesticides; since most pesticides (almost 75
percent by volume, U.S. EPA 1979b) are used in the production of food
and fiber, the discussion is framed primarily in terms of the agricultural
uses of pesticides. This is not to say that the Committee believes
nonagricultural uses do not pose significant human health and environ-
mental risks. Rather, the Committee had to limit the scope of its review
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Benefit Assessment
101
and chose agricultural uses since oPP devotes a majority of its effort to
this area.
The discussion is divided into the following major parts. The first
section considers the problems associated with measurement of pesticide
productivity, that is, the extent to which use of a chemical increases
production of things people value. The second section focuses on the
problem of estimating how much the use of a specific pesticide reduces
pest control costs and other production costs. These two components
pesticide productivity and cost savings-are brought together in the third
section, which presents appropriate methods for measuring the real
benefits of pesticide usage and for distributing both real and pecuniary
erects among certain key groups.
Our critical evaluation of the methods currently employed by
USDA/EPA economists to assess benefits of pesticide use is based upon a
review of several actual benefit assessments, namely, those for chloro-
benzilate (Luttner 1977a, by, DBCP (U.S. EPA/USDA 1978a), endrin
(Luttner 1977c, Mattson et al. 1977), lindane (U.S. EPA/USDA 1978c),
toxaphene (U.S. EPA/USDA 1978b), and trifluralin (USDA et al. 1977~.
These six assessments consist of fifty-eight separate use-pattern assess-
ments or analyses, with each analysis focusing on a specific use of a
pesticide. For instance, the trifluralin assessment consists of six separate
analyses for uses on cotton, soybeans, other field crops, fruits and
vegetables, miscellaneous crops, and noncrop sites.
ANALYSIS OF PESTICIDE PRODUCTIVITY
Pesticides are toxic chemicals used to kill a variety of organisms (e.g.,
rodents, insects, pathogens, and weeds) that people consider objection-
able for any one of several reasons. Many organisms are viewed as pests
because they interfere with agricultural and forestry production. Others
transmit diseases to humans and thus pose a hazard to public health.
Finally, some organisms, such as household lawn and garden pests,
create nuisances or aesthetic problems. For whatever reason, control of
pest organisms offers certain advantages, such as improvements in food
and fiber yields and the quality of products or reductions in the
incidence of human disease. A regulatory decision to prohibit or
otherwise restrict the use of a pesticide may consequently force society to
forgo substantial benefits.
A crucial first step in analyzing benefits offered by a pesticide is an
assessment of that pesticide's productivity that is, its electiveness at
providing something that people value, such as higher crop yields. Of
course, if a pesticide has a detrimental impact on nontarget organisms
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REGULATING PESTICIDES
resulting in negative productivity, such an impact must also be included
in an assessment of the pesticide's ejects.
Pesticide productivity is not the same as pesticide efficacy. "Efficacy"
refers to the pesticide's effectiveness at reducing a pest population,
whereas, in this context, "productivity" refers to the pesticide's
electiveness at providing more or better food and fiber, improvements in
public health, or more attractive surroundings. Thus, a highly efficacious
pesticide would be relatively unproductive if its target organism actually
had little eject on, say, crop yield or quality. Pesticide efficacy and
productivity are related but quite clearly different concepts. This part of
the chapter focuses on the issue of pesticide productivity.
CURRENT APPROACH: METHODOLOGY AND DATA
The USDA/EPA procedure for evaluating the productivity of an agricultur-
al pesticide concentrates on quantifying the pesticide's ejects on crop
yield or output. The possibility that quality ejects may also be important
is, of course, recognized in the USDA/EPA benefit assessments; however,
data are generally inadequate to quantify such ejects. Post-harvest losses
resulting from pre-harvest infections by pests are also often omitted
because of lack of data.
In estimating yield ejects, an attempt is made to measure the change
in output (e.~.. bushels of corn reaching the marketplace) that would
rid- ~
occur if a particular chemical were withdrawn from the market and
replaced by alternative chemical or nonchemical methods of pest
control. The estimation requires two basic types of data: (1) an
indication of the extent to which each of the various alternatives would
be employed as a substitute for the suspect chemical, and (2) an estimate
of differences in yield or output between the suspect chemical and the
alternatives. Unfortunately, these data are not always available. Conse-
quently, the benefit assessments are sometimes forced to consider these
important aspects of productivity in qualitative terms only. For instance,
18 of the 58 use-pattern assessments reviewed for this chapter contain no
quantitative evaluation of the impacts of cancellation.
Primary responsibility for assembling evidence on the productivity of
a pesticide and its alternatives falls to the USDA/EPA benefit assessment
team (see Chapter 2~. More specifically, the biologists (e.g., entomolo-
gists, plant pathologists) on the assessment team are responsible for
providing estimates of yield and, if possible, quality ejects. Often these
data are developed from published sources, but the team biologists may
also rely upon their own judgment or upon other unpublished sources
such as personal communications with other pest control specialists.
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1
Benefit Assessment
RECOMMENDED APPROACH
103
The measures of pesticide productivity that the USDA/EPA benefit
assessments attempt to implement are basically sound; that is, the
assessments define pesticide productivity correctly. Of course, it does not
follow that the actual estimates of pesticide productivity will be accurate.
As is noted at various points in this chapter, incomplete data often
prevent the analyst from making more than a very crude estimate of the
productivity of a pesticide. There are some problems with the current
method of predicting the use pattern that would arise among the
alternatives were a suspect chemical to be withdrawn; however,
discussion of the problems are deferred until later in this chapter.
Another methodological problem arises not only in connection with
estimating pesticide productivity, but also throughout most of the benefit
analyses. Specifically, USDA/EPA estimates of yields (and of other
benefits) are usually expressed as clearly determined magnitudes even
though there may be considerable uncertainty about their accuracy. The
practice lends an unjustifiable aura of precision to the benefit estimates.
In general, an uncertain measure should be reported as an interval a
probable estimate with upper- and lower-bound estimates rather than
as a single number.
The central recommendation specific to the measurement of pesticide
productivity relates to the current procedure for assembling the yield and
quality data. Benefit assessments currently place excessive reliance on
"data," often unpublished, and sometimes contained in controversial
reports, that have not been subjected to conventional scientific tests of
validity.
The credibility of a benefit analysis depends ultimately upon the
credibility of the data that support it. Of course, the regulatory process
cannot await the generation of a complete set of sound scientific data.
However, the regulatory process can, and should, demand that benefit
(and risk) analyses be performed with the best available data and with
data that have withstood some scrutiny.
The problem with the current procedure for assembling benefit data is
illustrated by the USDA/EPA analyses for the pesticides chlorobenzilate
and dimethoate. Data for these analyses were obtained mainly from
unpublished reports and personal communications with pesticide spe-
cialists. A few relevant published studies were identified by oPP with the
aid of several computerized bibliographic indexes. However, literature
searches commissioned by this Committee identified numerous impor-
tant published studies that were either missed or intentionally omitted by
the USDA/EPA procedure (see Chapter 7 and Appendix D). Moreover, the
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REGULATING PESTICIDES
independent literature searches revealed that the data obtained through
personal communications on balance differed significantly from the
published information. For several pests and crops, the chlorobenzilate
and dimethoate data derived from unpublished sources tended to
overstate the benefits of the suspect chemical.
The recommended procedure for assembling an acceptable data base
for a benefit analysis involves the following steps. First, a thorough
search of the published literature must be undertaken. The literature
search should use all major indexing bibliographies, and recent issues of
relevant, but unindexed, scientific journals should also be examined.
Computerized indexing services may be of some supplemental use in this
literature search, but they are too far from being complete to be relied
upon as the sole guide to relevant literature.
Whenever feasible, data on use of the suspect chemical and its
alternatives outside the United States should also be assembled.
Although it may not be appropriate to use such data directly, they may
provide helpful support to the data based on U.S. experience.
After the published literature has been searched thoroughly, it might
prove useful to consult some unpublished sources in the form of
unpublished reports or perhaps the firsthand knowledge of pest control
specialists. Each specialist contacted should be informed of the relevant
published information concerning the pest or pesticide and encouraged
to think in terms of a total accounting of all major losses of the
commodity in question due to pests. Presumably, the broader perspective
will help reduce the likelihood that the yield or quality elects attributed
to any one pesticide or to any one pest will be either exaggerated or
understated. The problem of overestimating yield erects is especially
troublesome. The pest control literature offers examples in which
estimates of aggregate yield losses from the combined erect of insects
and other pests exceed 100 percent (Pimentel et al. 19784.
Once data on productivity effects of both chemical and nonchemical
alternatives have been assembled, such data should be further validated
for thoroughness and accuracy through critical internal and external
reviews by knowledgeable scientists. At present, it is the legal responsi-
bility of the SAP to provide an external scientific review of oPP's health
and environmental hazard assessments. In practice, the SAP has also
provided some review of the benefits analysis (see SAP comments
published with EPA'S notice of final determination on chlorobenzilate,
U.S. EPA 1979a), but the arrangement results in inadequate reviews of the
benefits data and analyses. Since the involvement of the SAP iS limited
largely to the final stages of the RPAR process (see Chapter 2), the SAP iS
confronted with the task of reviewing analyses that are virtually
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Benefit Assessment
105
complete and thus unlikely to be changed in any significant way. The
usefulness of such reviews could be enhanced greatly through earlier SAP
involvement in the analyses. An additional problem with the current
scientific review procedure is that the SAP was created, and its
membership chosen, primarily to provide a review of risk-related issues.
Consequently, benefits data and analyses appear to receive relatively
little attention from individuals chosen for their expertise in the benefits
area.
For these reasons, the Committee makes the following recommenda-
tion:
· oPP should establish an external Benefits Review Panel, similar in
organization to the SAP, consisting of entomologists, plant pathologists, weed
specialists, economists, and others with expertise in the assessment of
benefits. The panel would have the responsibility of providing external
scientific reviews of the benefits data and analyses. For each REAR
compound, a review team (consisting for example of one entomologist and
one economists should be selectedirom the panel. This team, in contrast to
current SAP procedures, should be involved from the earliest stages of the
benefits assessment, and should have primary responsibility for presenting an
evaluation of the assessment to the entire Benefits Review Panel.
ESTIMATING CHANGES IN PEST CONTROL COSTS
CURRENT APPROACH
The second key component of a benefit analysis is an assessment of the
erect that withdrawal of an RPAR chemical would have on pest control
costs. (Other costs of cultivation or production may also be important
and are considered later in this chapter.) The operational definition that
oPP attempts to implement for each specific use of the suspect chemical
is (assuming the treated item is a crop):
/` P Ci = id, 2\ [A jTj ~ MCj + A Cj) ~
~ 1
K
~[A kTk( MCk + A Ck) ],
k I
where /`PCi is the change in pest control costs for the ith use of the RPAR
chemical (e.g., a particular crop in a certain region); j denotes one of the
J pest control methods not involving the suspect chemical; k indicates
one of the K control methods employing the suspect chemical; Aj and Ak
are the number of acres treated per year by methodsj and k, respectively
(sometimes referred to as "base access; Tj and Tk are the average
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REGULATING PESTICIDES
number of treatments per year by methods j and k, respectively; MC
and MCk are material costs per acre-treatment; and ACj and ACk are
application or treatment costs per acre-treatment.
The data for implementing this measure come from a variety of
sources. Much of the information (e.g., the number of acres treated) is
supposed to be developed by the USDA/EPA benefit assessment team.
Although it is difficult to generalize about the data sources employed by
the assessment teams, there appears to be fairly extensive reliance upon
unpublished sources and the judgments of individual team members or
other specialists. In certain instances some of the data are obtained from
surveys, especially those provided by Doane Agricultural Service, Inc.
Finally, some of the data used are simply plausible assumptions. For
instance, benefit analyses commonly suppose that the number of acres
treated would not be affected by withdrawal of the RPAR chemical (e.g.,
see Luttner 1977a).
RECOMMENDED APPROACH
For the most part, the current approach to estimating the change in pest
control costs is sound, but there are some aspects that should be altered.
First, the imprecision of many of the estimates is obscured by the
practice of reporting point estimates rather than interval estimates. As a
general rule, oPP's benefit assessments should be more forthright about
the uncertainty surrounding the estimates by reporting plausible mini-
mum and maximum values along with the most-probable estimates for key
variables.
A second recommendation relates to the current practice of estimating
material and application costs with data obtained from a variety of
sources. For example, oPP's chlorobenzilate benefit assessment (Luttner
1977a, b) employs information from the Doane Speciality Crops Survey,
dealer price lists, and pest control specialists (especially those serving on
the assessment team). Estimation of changes in pest control costs
requires information about differences in material and application costs.
Whenever feasible, these cost differentials should be estimated from a
single, consistent set of data (e.g., dealer price lists) rather than from data
generated from several sources. Estimating cost differentials with data
obtained from several different sources or in a variety of ways inevitably
heightens the inaccuracy associated with the estimates.
A third recommendation pertains to the current method of predicting
the extent to which the various alternatives would actually substitute for
a withdrawn RPAR chemical. In some instances the use-pattern forecast
for the alternatives is based on unrealistic assumptions. For instance, the
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Benefit Assessment
107
chlorobenzilate analysis assumes that the base acres treated with
chlorobenzilate would be evenly divided among the several alternatives,
even though there are significant cost differences among those alterna-
tives. A benefit assessment should estimate changes in pest control cost
using a more plausible assumption.
In the absence of information to the contrary, it would be reasonable
to adopt, as a working hypothesis, the assumption that the relative
distribution of base acres among alternatives is unaffected by withdrawal
of the RPAR chemical (unless, of course, some of the alternatives were
also likely to be withdrawn or otherwise restricted. As is noted in
Chapter 3, in making these comparisons it is necessary to have a well-
founded judgment as to which alternatives are likely to be permitted or
cancelled.) That is, the increase in base acres treated with the jth
alternative (AA,) following cancellation of a suspect pesticide should be
presumed to equal
AAj = Pj Ok,
where Ak is total base acres treated with the RPAR chemical, end pj is the
ratio of (1) base acres currently treated with thejth alternative to (2) base
acres currently treated with all of the alternatives to the RPAR pesticide.
Even this estimation procedure is highly arbitrary and, whenever
possible, should be amended to reflect the best available information.
ECONOMIC EVALUATION OF PRODUCTIVITY AND COST
EFFECTS
This section appraises current USDA/EPA procedures for evaluating the
productivity and cost ejects of proposed pesticide regulations. Two
related tasks are involved. The first is to assign values, generally
monetary, to the real benefits (i.e., goods and services) that would be
forgone were the compound to be withdrawn or its use otherwise
restricted. The second task is to determine, to the extent feasible, the
distribution of the benefits (which may be negative in some cases) among
affected segments of the population. This section outlines the current
USDA/EPA approach to these two tasks, compares it with standard
methods of benefit-cost analysis, and recommends some changes in the
USDA/EPA procedures. As noted at the outset of this chapter, the
discussion is framed primarily in terms of agricultural uses of the suspect
chemicals.
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CURRENT APPROACH
REGULATING PESTICIDES
The USDA/EPA benefit analyses all adopt a partial equilibrium framework
referred to as "partial budgeting." In measuring the benefits that would
be forgone if a pesticide's uses were restricted or cancelled, the USDA/EPA
economists usually assume that proposed restrictions would significantly
affect only (1) the quantity of substitute pesticides that would be used in
place of the one that is restricted, and (2) the output of the treated item.
Of course, for agricultural uses and most nonagricultural uses, changes in
these two variables imply changes in production costs and revenues. In a
few instances, the ejects these changes would have on output prices is
also taken into account (see, for instance, USDA et al. 1977~. (The
quantitative assessments of public health uses of pesticides assume that
tighter restrictions on use of a suspect compound will significantly
influence only the quantities of alternative pesticides applied in these
uses [A.L. Aspelin, oPP' EPA, Washington, D.C., personal communica-
tion, October 1978~.) Typically, other variables in the quantitative
analyses are assumed to remain constant, including the quantity of other
inputs to the productive process, input prices, and output quality. The
benefit assessments usually note that these variables may change as the
result of a regulatory action, but inadequacy of available data commonly
prevents the analysts from developing quantitative estimates of these
changes. In a few instances, estimates of output price changes are
employed in evaluating the distributional (but not the economic
efficiency) consequences of a regulatory action (see, for instance, Luttner
1977c and U.S. EPA/USDA 1978a).
The operational benefit measure currently used in the USDA/EPA
assessments is the saving in pest control costs arising from continued use
of the RPAR pesticide plus the value of the output that would be lost
without the RPAR chemical. This concept can be expressed in equation
form as:
USDA/EPA annual benefit measure =
(PCs - PCr) + (Pr Xr
Pang), (5.1)
where PC', is equal to the aggregate annual pest control costs with only
the substitute controls; PC, is equal to the aggregate annual pest control
costs with the RPAR chemical; Pr is the price per unit of output (e.g., of a
crop), assumed constant (estimated, for example, by the average of the
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Benefit Assessment
previous 3 years); Xr is the annual output (e.g., total crop produced) if
the RPAR pesticide is available; and X',, is the annual output that would
be produced in the absence of the suspect chemical, assuming the price
Pr remains constant. Of the 58 use-pattern assessments reviewed, 21
estimate both components of the above benefit definition. Another 19 of
the assessments estimate only the expected change in pest control costs
(PC`- PCr); they assume that the substitutes are as efficacious as the
RPAR chemical. This assumption is often adopted because data on actual
yield differences are unavailable. The remaining 18 assessments contain
no quantitative evaluation of the economic impacts of a cancellation. It
is often necessary to rely upon qualitative assessments because data are
either nonexistent or inaccessible, or time and resources are inadequate
to undertake quantitative analyses.
In some instances the benefit assessments intermix estimates of the
real benefits of a compound with estimates of the monetary gains and
losses associated with use of the compound (see, for example, USDA et al.
1977~. This practice of combining estimates of real and pecuniary ejects
will sometimes obscure the underlying definitions and methods used by
the USDA/EPA analysts in measuring the separate effects. We will return
to this issue in a later part of this chapter.
109
Treatment of Uncertainty
The basic USDA/EPA approach to coping with uncertainty about the
magnitudes of key variables in the quantitative benefit assessment is
simply to omit highly uncertain variables. For instance, of the 40
quantitative use-pattern assessments reviewed (an additional 18 were
nonquantitative), 19 assumed that cancellation would not reduce the
yields of the crop in question. The assumption was adopted primarily
because of lack of data concerning the comparative ejects on yields of
different pest control measures.
The USDA/EPA benefit assessments treat the uncertainties of long-run
ejects in the same spirit. The assessments generally adopt a short-run
perspective (3-5 years) to avoid uncertainties inherent in long-run
forecasts of such key factors as technological changes in pest control or
development of pest resistance to a compound (H. Gaede, oPP' EPA,
Washington, D.C., personal communication, October 1978~.
Some of the assessments use "sensitivity analysis" to generate
alternative estimates for certain variables. Apparently this procedure is
used only when there is some convict in, say, estimates of yield ejects
reported in different studies. Sensitivity analysis is not routinely used to
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120
-
P
s
LL
p
UJ r
Cal
\
A
\/
E
/
S'
F ~
/
S
l
REGULATING PESTICIDES
S'
1 <
~ S
\D
xs xr
OUTPUT OF X
FIGURE 5.3 Distnbutional consequences of cancelling the registration of an RPAR
pesticide (see text for discussion).
their initial net benefit or consumers' surplus from having Or available at
price Pr is equal to A + B + C + D.
Suppose that a regulatory action against the RPAR pesticide raises
production costs and results eventually in a new equilibrium price and
quantity of Pa and I, respectively. Total revenue is now B + C + E
+ F + H; total cost is C + F + H; producers' surplus is B + E; and
consumers' surplus is area A.
The regulatory action has made consumers of X worse on by the
amount B + C + D. Growers, however, may have been made either
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Benefit Assessment
·21
better on or worse off, since the change in producers' surplus equals
B - F- G. Whether this change represents a gain or a loss depends upon
the elasticities of the market supply and demand curves. We might also
note that total revenue and total cost might either increase or decrease,
depending on the shapes of the demand and cost curves: total industry
revenue changes by B + C- G - I, whereas total industry cost changes
byF+ C-I.
Suppose that only a fraction of the growers of crop X use the RPAR
pesticide. Under these circumstances, conventional incidence analysis
suggests that if the regulatory action against the suspect chemical results
in cost increases or output losses substantial enough to occasion price
increases, then (1) consumers will clearly suffer, (2) nonusing growers
will clearly benefit, and (3) users may super either gains or losses,
depending upon demand and supply elasticities.
If the users of the RPAR pesticide are few relative to the total market,
the regulatory action is unlikely to affect output prices. In this case, only
the users suffer losses, which would be measured by their forgone
economic profits (rather than revenue reductions). In general, the smaller
the number of users relative to nonusers, the greater the likelihood that
the entire burden of the regulatory action will be borne by the users.
A technical qualification to the preceding discussion is in order. The
conventional approach assumes that reductions in the demand for
productive inputs result in a virtually instantaneous transfer of those
inputs into other equally productive activities. In reality, there will
generally be some transitional unemployment as resources move from
one productive activity to another. Incorporation of this effect into the
conventional analysis would result in an increase in the costs of a
regulatory action. Unfortunately the data available to the USDA/EPA
analysts are generally inadequate for considering these transitional
unemployment erects (H. Gaede, oPP, EPA, Washington, D.C., personal
communication, October 1978~.
There is an important flaw in the partial-equilibrium approach to
evaluating the distributive erects of pesticide regulation. While it offers a
more reasonable approach to assessing distributional implications than
the traditional partial-budgeting method, it provides only a limited,
partial view of true distributional impacts. A complete distributional
analysis would incorporate not only the direct erects of the regulation,
but also all of the major indirect or spillover erects on related markets. If
a detailed quantitative assessment of the major direct and indirect
distributive erects of a pesticide restriction is desired, it would be
necessary to conduct the distributive analysis in the context of multi-
sector (or multi-crop) programming or econometric models. Of course, if
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REGULATING PESTICIDES
the proposed regulation is expected to have only marginal yield or cost
erects, the resultant spillovers will generally be negligible, implying that
the partial-equilibrium estimates would be reliable.
The USDA/EPA benefit analysts currently have access to at least two
complex mathematical models that can, in principle, reveal how
regulatory decisions would impinge on the markets for certain major
agricultural crops (namely, cotton, corn, barley, soybeans, oats, grain
sorghum, and wheat). One of these models is a multi-crop linear
programming model developed by EPA in the early 1970s to analyze some
of the distributive erects of prohibiting the use of chlorinated hydrocar-
bon pesticides on corn (see Epp et al. 1977 for a more detailed
description, especially pages 30~2~. The second is a multi-crop
econometric model recently developed for oPP by Lacewell and Taylor
(described in Taylor et al. 1979~. However, neither of these models is
presently used by the USDA/EPA analysts in their benefit assessment work
(A.L. Aspelin, oPP, EPA, Washington, D.C., personal communication,
November 1978~.
Reluctance to rely on the mathematical modelling approach to
evaluate distributive effects of a pesticide regulation is justifiable.
Frequently, the spillover erects of a proposed regulation are negligible
and thus too small for mathematical models to detect with any degree of
confidence (G. O'Mara, oPP, EPA, Washington, D.C., personal communi-
cation, June 19781. In addition, the generally poor quality of the cost
and, especially, the yield data raises serious doubt as to the appropri-
ateness of basing the benefit assessment on the results of sophisticated
programming or econometric models. The detailed, seemingly precise
results provided by the models may lend an unwarranted aura of
credibility to the economic impact estimates. Consequently, if the
mathematical modelling approach does become more important in the
assessment of pesticide benefits, the Committee recommends that the
analysts routinely report the results of sensitivity analyses in order to
reveal the actual uncertainty surrounding the impact estimates.
In the qualitative discussions of the economic impacts of a regulatory
action, the USDA/EPA analysts recognize the implications of conventional
economic incidence analysis. They note, for example, that consumer
prices are likely to rise following a regulatory response. However, the
quantitative assessments usually assume that the burden of a regulatory
decision will be borne entirely by the growers-or, more specifically, the
users of the IlPAR pesticide. Thus, the USDA/EPA quantitative benefit
assessments tend to overstate the losses suffered by users of a cancelled
(or otherwise regulated) pesticide. Similarly, they tend to understate the
losses suffered by consumers and the gains enjoyed by nonusers. These
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Benefit Assessment
123
inaccurate estimates arise mainly out of a failure to account explicitly for
the output price changes likely to result from a regulatory action.
In connection with the estimation of the distributive ejects, the
USDA/EPA approach suffers from at least one other problem. Some of the
distributive ejects involve income redistribution. Crop price increases, for
instance, will in large part redistribute purchasing power from consumers
to growers. Thus, if increases in crop prices benefit growers by, say, $50
million annually, those same price increases cost consumers $50 million
annually. (For simplicity, this statement ignores the likelihood that the
higher prices will lead to greater production.)
Unfortunately, several of the benefit assessments have failed to spell
out clearly the fact that gains to growers may entail losses for consumers.
For instance, in the endrin/apple assessment (endrin is used in apple
orchards to control voles) the following conclusion was reached
regarding the likely impacts on apple growers:
The greatest impacts will occur if current endnn users substitute zinc phosphide
in their control programs. Under this program, current endnn users would incur
losses in net returns equal to $19,110,000 after three years. Nonusers of endrin
would experience increased net returns equal to $51,323,000 after three years due
to higher apple prices caused by losses in the endr~n use areas. Over the initial
three-year period following the cancellation of endr~n, users would experience a
drop in net returns from $675 to $429 per acre, while nonusers would experience
an average increase in net returns from $675 to $788 per acre.
Under a cPN-DPN-herbicides-cultural methods program, the aggregate impacts
upon users and non-users would be approximately one-half the magnitude
Ace; "Stan ~ ~ ~ ~ or ~ On APE dreary m
_ _ _
rlVJ-~ ~ t~4 ~ ~-c. ~ I. ..... [C]u~ent ends users would experience
a loss in net returns of $9,479,000 over the initial three-year period. Non-users of
endrm would receive an aggregate increase In net revenues of $25,773,000 over
the same period (Luttner 1977c: 76, 80~.
In contrast, the analysis of the likely effect on consumers is essentially
limited to the following:
Although the cancellation of endr~n has the potential to cause economic hardship
for growers in the affected areas, the aggregate impact does not appear to be
significant on a macroeconomic level (Luttner 1977c:84~.
The reader should note that according to these three extracts, the net
eject on the incomes of apple growers of suspending the use of endrin
would be an increase of $32 million a year if zinc phosphide were
substituted, or an increase of $16 million if cPN-DPN-herbicides were
used. These figures give the misleading impression that there are no net
benefits of using endrin in apple orchards, by including the gain to
OCR for page 124
124
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OCR for page 126
126
REGULATING PESTICIDES
TABLE 5.2 An Example ofthe Recommended Format for the
Presentation of Benefit Assessment Results
Cost of Denying Reregistration to Trifluralin for Use on Cotton (assuming demand elasticity
is 0.3, horizontal supply curve)
Real Costs cuff Dental
Decrease in lint production 574 million lb at (0.60 + 0.715)/2
Decrease in seed production 959 million lb at o.oSa
Value of substitute cropa
Added cost of weed control
Reduced variable cost on acres shifted to substitute
Total real costs
Monetary G'sts cuff Dental
To trifluralin users:
Lint production (million lb)
Price
Gross sales ($ million)
Decrease in lint sales
Decrease in seed production a
Value of substitutea
Added cost of weed control
Reduced variable cost on acres shifted
Net monetary cost to users
To other cotton producers:
Increase in gross sales 1637 million lb at $0.115
To consumers (foreign and domestic):
Increased cost of output purchased 4829 million
Ibat $0.115
With
Trifluralin
3766
$0.60
2260
Loss in value from output restriction 574 million lb at
(0.60 +0.715)/2 - 0.60 = 0.0575
Total monetary costs
($ Million)b
$377
48
- 39
6
16
$376
Without
Trifluralin
3192
$0.715
2282
-$ 22
48
39
- 16
23
-$188
555
33
$588
$377
a Assumes change in output does not induce change in price.
b Negative entries indicate negative losses or gains.
Source: USDA et al. (1977, Table 1) .
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Benefit Assessment
·27
growers from the higher apple prices that would exist if it were not used,
while ignoring the offsetting loss to consumers.
As a general rule, the USDA/EPA benefit assessments need to pay more
attention to identifying implications of proposed regulations for the
distribution of income. In many instances, the data are inadequate for
measuring distributional ejects with much precision. However, reason-
able upper- and lower-bound estimates can usually be developed, for
instance, by adopting assumptions about the plausible upper- and lower-
bound values for demand and supply elasticities (see the chlorobenzilate
analysis in Chapter 7 for an illustration).
A final recommendation concerns the presentation of results of benefit
assessments. At present, no clear distinction is made in the benefit
assessment documents between the real and pecuniary (or distributional)
effects of not reregistering (or otherwise regulating) a pesticide. Not to
distinguish carefully between them is confusing to trained readers and
misleading to untrained readers.
An example of the type of format that is commonly used in reporting
results of benefit assessments is provided in Table 5.1. According to the
trifluralin assessment document (USDA et al. 1977), this table is supposed
to present "the estimated short-run economic impact of a trifluralin
suspension on cotton.... " Although the figures may be correct, the
impression given by the table is entirely misleading.3 According to the
table, if trifluralin were banned, the net incomes of cotton farmers who
use trifluralin would increase by $24 million a year (see the last column)
and those of other cotton farmers would increase by $188 million for a
total gain of $212 million in net farm income. As far as can be
determined from the table, the American economy would be better on
without trifluralin even apart from its effects on public health and the
ecology. Of course, the facts are otherwise. If trifluralin is forbidden,
more resources will be used to raise cotton and less cotton will be
produced. As a result, purchasers of cotton will pay higher prices and
receive less cotton.
A proper, "double-entry" accounting for the eject of banning
trifluralin is shown in Table 5.2. The real resource cost entailed is
constructed in the upper panel; it amounts to $376 million a year. The
incidence of those costs is displayed in the lower panel. The monetary
gains to cotton raisers are outweighed by the loss of $588 million
sustained by cotton users. The net monetary loss ($588 - $212 = $376
million) is equal to the real resource cost. In this world every component
of real cost is paid for by somebody.
The entries in the consumers category require a brief explanation. In
connection with the first entry, the 4,829 million pounds of lint available
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128
REGULATING PESTICIDES
without tr~fluralin would cost consumers $555 million more than that
same quantity would cost at the price that would reign if trifluralin were
available. In connection with the second entry, the $33 million measures
the difference beween (1) the value consumers place on the 574 million
pounds of lint that would be lost if tnfluralin were suspended and (2) the
value they place on the alternative commodities they can buy with the
purchasing power released by the reduction in the quantity of lint
demanded. The difference is nothing more than the consumers' surplus
triangle discussed earlier in this chapter.
The display of separate real and monetary ejects makes several things
clear. First, the monetary effects are a distribution of the real ejects.
Apart from a rounding error in Table 5.2, the total of the monetary
ejects equals the total of the real ejects. Second, in the present Instance,
the consumers sustain a loss that is more than 50 percent greater than the
real loss. The reason is the assumed inelasticity of demand, which makes
it possible for producers to more than shift their increased costs to
consumers. The key figures, which are not found in the USDA/EPA
presentation in Table 5.1, are that there would be a real loss measured by
$376 million, which would result in a purchasing power loss of $588
million on the part of cotton users. (Note that in keeping with a
preceding recommendation, these estimates should be reported as
ranges, rather than as precise numbers.)
The Committee recommends that tables similar to Table 5.2 be
routinely included in the benefit assessment reports.
NOTES
1. In economists' terms, this expression is the sum of the changes in producers' and
consumers' surpluses. The measure provides an estimate of the unobservable sum of the
compensating variations-the correct theoretical measure of changes in economic welfare.
For a discussion of some of the technical problems associated with estimating welfare gains
and losses with the producers' and consumers' surplus measures, see Chipman and Moore
(1976, 1979), Mishan (1976), Mohring (1971), Silberberg (1972), and Willig (1976). As some
of these authors note, there is considerable theoretical controversy as to whether consumer
surplus has any meaning beyond the level of individual consumers.
2. In some instances, a restriction on a pesticide used in the production of commodity
X (e.g., wheat) may indirectly affect the prices of other commodities (e.g., barley and oats)
through demand or supply interdependencies. The benefit measure set forth as Equation
5.2 abstracts from the gains and losses that would be associated with such price changes.
When the indirect price changes (and the related gains and losses) are important, allowance
has to be made for them. Otherwise, the benefits will be incorrectly measured. However, in
the Committee's opinion these indirect price effects will usually be small enough to neglect
safely. The reasoning behind this belief is as follows. Most of these indirect gains and losses
will be transfers of purchasing power between consumers and producers. While such
OCR for page 129
Benefit Assessment
129
transfers may be relevant to an evaluation of the distributional consequences of a
regulatory action, they are not relevant to an eval~l~tion of the economic efficiency
consequences of that action. In measuring the efficiency effects, it is necessary to account
only for the net (or "deadweight") gains or losses in the other, related markets. The net
gains or losses in these related markets appear likely to be small relative to the efficiency
gains or losses in the primary market. In any event, the data will generally not permit
quantification of either the gross or the net gains or losses associated with these market
interdependencies.
3. The trifluralin estimates are used in this table merely for illustrative purposes; the
Committee has not attempted to evaluate their accuracy.
REFERENCES
Anderson, L.G. and R.F. Settle (1977) Benefit-Cost Analysis: A Practical Guide.
Lexington, Mass.: D.C. Heath.
Chipman, J.S. and J.C. Moore (1976) The scope of consumers surplus arguments. Pages
69-123, Evolution, Welfare, and Time in Economics, edited by Tang, Westfield, and
Worley. Lexington, Mass.: D.C. Heath.
Chipman, J.S. and J.C. Moore (1979) Compensating Variation, Consumer's Surplus, and
Welfare. Mimeograph. Accepted for publication by the American Economic Review.
Epp, D.J., F.R. Tellefsen, G.A. Shute, R.M. Bear, and K.P. Wilkinson (1977) Identification
and Specification of Inputs for Benefit-Cost Modeling of Pesticide Use. A Report to the
Office of Research and Development, U.S. Environmental Protection Agency, Washing-
ton, D.C., EPA-600/5-77-012. Springfield, Va.: National Technical Information Service.
Headley, J.C. and J.N. Lewis (1967) The Pesticide Problem: An Economic Approach to
Public Policy. Washington, D.C.: Resources for the Future. (Distributed by The Johns
Hopkins Press, Baltimore, Md.)
Kennedy, R., R. Lowrey, A. Bernstein, and F. Rueter (1975) A Benefit Cost System for
Chemical Pesticides. A Report to the Office of Pesticide Programs, U.S. Environmental
Protection Agency, Washington, D.C., EPA-540/9-76-001. Springfield, Va.: National
Technical Information Service.
Luttner, M.A. (1977a) Preliminary Benefit Analysis of Chlorobenzilate. Criteria and
Evaluation Division, Office of Pesticide Programs, U.S. Environmental Protection
Agency, Washington, D.C. (Unpublished)
Luttner, M.A. (1977b) Supplement to the Preliminary Benefit Analysis of Chlorobenzilate.
Criteria and Evaluation Division, Office of Pesticide Programs, U.S. Environmental
Protection Agency, Washington, D.C. (Unpublished)
Luttner, M.A. (1977c) Preliminary Benefit Analysis of Endrin Use on Apple Orchards.
Criteria and Evaluation Division, Office of Pesticide Programs, U.S. Environmental
Protection Agency, Washington, D.C. (Unpublished)
Mattson, C.D., F.T. Arnold, G.L. Ballard, R.A. Freund, R.C. Holtorf, M.A. Luttner, and
D.E. Tegelman (1977) Preliminary Benefit Analysis of Endrin. Criteria and Evaluation
Division, Office of Pesticide Programs, U.S. Environmental Protection Agency,
Washington, D.C. (Unpublished)
Mishan, E.J. (1976) Cost-Benefit Analysis. New York: Praeger Publishers.
Mohring, H. (1971) Alternative welfare gain and loss measures. Western Economic Journal
9:349-368.
OCR for page 130
130
REGULATING PESTICIDES
National Research Council (1977) Decision Making in the Environmental Protection
Agency. Volume II, Analytical Studies for the U.S. Environmental Protection Agency.
Report of the Committee on Environmental Decision Making, Commission on Natural
Resources. Washington, D.C.: National Academy of Sciences.
Pimentel, D., J. Krummel, D. Callahan, J. Hough, A. Merrill, I. Schreiner, P. Vittum, F.
Koziol, E. Back, D. Yen, and S. Fiance (1978) Benefits and costs of pesticide use in U.S.
food production. BioScience 28:772, 778-784.
Silberberg, E. (1972) Duality and the many consumer's surpluses. American Economic
Review 62:942-952.
Sugden, R. and A. Williams (1978) The Principles of Practical Cost-Benefit Analysis.
Oxford: Oxford University Press.
Taylor, C.R., R.D. Lacewell, and H. Talpaz (1979) Use of extraneous information with an
econometric model to evaluate impacts of pesticide withdrawals. Western Journal of
Agricultural Economics 4(1): 1-7.
U.S. Department of Agriculture, State Land Grant Universities, and U.S. Environmental
Protection Agency (1977) Short-Run Economic Analysis of Trifluralin and Trichloro-
benzoic Acid. (Note: This unpublished Final Report is available from oPP' U.S. EPA,
Washington, D.C.)
U.S. Environmental Protection Agency (1979a) Chlorobenzilate. Notice of Intent to Cancel
Registrations and Deny Applications for Registration of Pesticide Products Containing
Chlorobenzilate. 44 Federal Register 9547-9567.
U.S. Environmental Protection Agency (1979b) Pesticide Industry Sales and Usage 1979
Market Estimates. Office of Pesticide Programs, EPA, Washington, D.C. 2~.
(Unpublished)
U.S. Environmental Protection Agency and U.S. Department of Agriculture (1978a)
Economic and Social Impacts of Cancelling Use of DBCP as a Pesticide for all Registered
Use Sites with Known Current Usage. (Note: This unpublished Final Report is
available from oPP' U.S. EPA, Washington, D.C.)
U.S. Environmental Protection Agency and U.S. Department of Agriculture (1978b)
Impact of the Loss of Toxaphene on Selected Agricultural Uses: A Partial Budgeting
Analysis. (Note: This unpublished Final Report is available from oPP, U.S. EPA,
Washington, D.C.)
U.S. Environmental Protection Agency and U.S. Department of Agriculture (1978c)
Preliminary Benefit Analysis of Lindane. (Note: This unpublished Final Report was
prepared under the general direction of Fred Hageman, Project Manager for Lindane,
and is available from oPP, U.S. EPA, Washington, D.C.)
Willig, R. (1976) Consumer's surplus without apology. American Economic Review
66:589-597.
Representative terms from entire chapter:
benefit assessment
