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Balancing the Multiple Objectives of Conservation Programs
Andrea Cattaneo, Daniel Hellerstein, Cynthia Nickerson,
and Christina Myers
Economic Research Report No. (ERR-19), May 2006
To help minimize the negative and maximize the positive environmental
impacts of agricultural production, the Federal Government supports
a variety of conservation programs. These include land retirement,
working lands, and easement programs. Land retirement programs,
such as the Conservation Reserve Program (CRP) and the Wetlands
Reserve Program, pay landowners to implement environmentally
enhancing practices on land they voluntarily take out of production.
Working lands and easement programs, such as the Environmental
Quality Incentive Program, Conservation Security Program, and
the Farm and Ranch Lands Protection Program, pay participants
to maintain or enhance conservation efforts on farmland kept
in production. In 2005, expenditures for these programs exceeded
$2.8 billion. Each of these programs seeks to achieve multiple
environmental objectives, including reducing soil erosion, increasing
water and air quality, and protecting wildlife habitat cost
effectively.
What Is the Issue?
Implementing multi-objective programs efficiently requires
balancing different environmental and economic objectives. A
number of the largest U.S. conservation programs use an “index,”
in which measures of multiple environmental and cost objectives
are weighted by program manager perceptions of relative importance.
The index calculates a score for, and is used to rank, applications
for enrollment submitted by potential program participants.
This approach gives program managers the option, in each enrollment
period, to change the relative weights assigned to each objective
in the index. For example, new information about heightened
public interest in protecting wildlife habitat may induce program
managers to increase the weight on a wildlife habitat objective.
Applications meeting the favored objective would then be prioritized,
resulting in a different mix of applications selected from the
pool of applicants. Getting new information about societal preferences
for environmental outcomes can be expected, given that at present,
little is known about how society values one environmental improvement
over another. Also, little is known about the effect of index
weight changes on environmental outcomes. That is, do small
changes in weights significantly affect the mix of applications
selected for enrollment, leading to very different program outcomes?
Or do large changes in weights only minimally affect the selected
set of applicants and thus have a limited impact on program
outcomes?
What Did the Study Find?
Small changes to index weights made relatively little
difference in environmental outcomes, but larger changes generated
larger impacts in the CRP. Environmental outcomes in the CRP were not very sensitive to small changes in the program’s
index weights, even when the size of the enrollment was allowed
to vary from 2 to 33 million acres. For example, environmental
objectives sought in the CRP included soil erosion reduction,
water quality improvements, and increased wildlife benefits,
and these three objectives have received equal weight in recent
years. A 10-percent change in the weight on the soil erosion
weight objective increased erosion reduction benefits by 5 percent
at most. Weight changes of more than 20 percent generated larger
impacts on environmental outcomes. For example, an approximately
50-percent increase in the wildlife objective weight increased
wildlife benefits up to 15 percent. The largest weight changes
generated the largest changes in outcomes: tripling the erosion
reduction weight increased erosion reduction benefits by 50
percent.
These findings may seem intuitive. Yet, they highlight that
as long as CRP outcomes approximately reflect public preferences,
then few opportunities exist for improving environmental outcomes
by fine-tuning the index weights. But if new information suggests
that an alternative mix of environmental improvements is preferred,
program outcomes can be affected by larger changes in weights.
In terms of tradeoffs, only a large increase in the weight
of a particular environmental objective caused losses of benefits
related to other objectives. Throughout our analyses, tradeoffs
occurred between achieving additional wildlife benefits and
erosion reduction benefits, but the effects were relatively
weak. Erosion reduction benefits declined 15 percent when the
wildlife habitat weight doubled, and wildlife benefits declined
about 5 percent when the erosion weight was doubled. Other tradeoffs
appeared to have more modest responses, although this effect
varied by region.
Changes in the CRP objectives’ weights affected program
costs more than environmental outcomes. In particular, improvements
in water quality were more costly to obtain than other objectives.
A 10-percent increase in water quality benefits generated by
the CRP would increase costs up to 20 percent, while increasing
wildlife benefits by 10 percent entailed less than a 14-percent
cost increase. Also, benefits could be achieved more cost effectively
when we simulated enrollment in a newly formed program. This
effect suggests that achieving environmental improvements may
become more expensive as ongoing enrollments reduce the pool
of available lands.
When program objectives, overall program sizes, or other features
are mandated by law, changing index weights can serve as a lever
for moderately affecting CRP outcomes. In addition to changing
index weights, program decisionmakers may find that adjusting
other program design features, such as eligibility criteria
or the mix of allowable land management practices, or allowing
weights to vary by region helps bring about changes in program
outcomes.
How Was the Study Conducted?
The CRP has used an environmental benefits index (EBI) since
the early 1990s to rank applications for land enrollment. In
the CRP’s 26th signup in 2003, the EBI considered several
different types of objectives: wildlife habitat quality, water
quality, erosion reduction potential, enduring benefits, air
quality, and cost. We used CRP application and enrollment data
from this signup to simulate how small and large changes in
the EBI objectives’ weights would affect the economic
and environmental outcomes of the program. The simulations considered
the types of land available for enrollment and the degree to
which changes in index weights induce landowners to enroll different
types of land. We examined the impacts of changing the weights
for a single enrollment period (i.e., when 2 million acres are
added to an ongoing program). We also simulated the effects
of weight changes when no land was previously enrolled (that
is, when 33 million acres are enrolled—simulating a full-program
enrollment).
The analyses assumed applications scoring the highest among
each of several objectives would have the largest actual environmental
impacts in the CRP. As different simulations generated new scores
for applications, different sets of farmland were selected for
enrollment. Because each set contributed different environmental
impacts and entailed different costs, different environmental
and cost outcomes were possible.
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