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«Toward More Effective Endangered Species Regulation By Jacob P. Byl Dissertation Submitted to the Faculty of the Graduate School of Vanderbilt ...»

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Theoretical models can help assess the promise of alternative regulatory tools by predicting how landowners may respond to incentives. Langpap and Wu (2004) use a model of landowner behavior to find that voluntary agreements are likely to allow for more endangered species habitat, but that levels are still below the socially optimal amount. Polasky and Doremus (1998) model behavior relating to how landowners will share information with regulators, which has large practical implications in a world where landowners are likely to have more information about endangered species on their properties than regulators do. While these papers provide valuable clues about how landowners will respond to endangered species regulations, the models rely on untested assumptions. In this paper, I use a theoretical model to predict behavior, then test those predictions with data.

A common way to gather data to test predictions is to look at real-world interactions. Lueck and Michael (2003) use data from federal agencies to determine that landowners in North Carolina who have mature pine trees on their properties are more likely to harvest those pine trees if there are endangered woodpeckers nearby. While this methodology using revealed-preference data provides an empirical sense of what is going on in the world, it can only be used to look at policies that are in place and have been running long enough to generate adequate data.

Often revealed-preference data are unavailable, so researchers turn to methodologies using stated-preference data. Zhang (2004) uses a survey of landowners to assess the impact of red-cockaded woodpecker on wood harvests, much like Lueck and Michael had done with revealed-preference data, and finds similar results of habitat destruction through timber harvests. Langpap (2006) uses survey data to find that a combination of assurances of no new future regulations, which are much like safe-harbor agreements, and financial incentives hold the most promise to get private landowners to provide habitat.

A third way to gather data is to use experiments. Experiments allow researchers to impose an element of randomness to use as exogenous variation. For example, Newell and Swallow (2013) use a field experiment to help determine how much people value the attributes, including provision of wildlife habitat, of a wetland. They generate eighteen different true descriptions of two real wetland parcels, then use randomization to determine which description people would read before being asked how much they were willing to contribute to conservation of the wetland parcels. Parkhurst and Shogren (2007) use a computer-based experiment to find that landowners will respond to a policy that provides a bonus for the conservation of properties that are adjacent to other conserved properties.

This paper contributes to the literature with the first experimental tests of landowner behavior in the existing safe-harbor program and the proposed markets for endangered species habitat. The experiment takes advantage of random assignment into treatment and control groups to see how people respond to regulations in hypothetical scenarios. By tying performance in the scenarios to real money payoffs, participants have incentives to pay attention and try to take home as much money as possible (List et al.


The paper proceeds in Section II with a brief description of the legal background that creates the environment in which landowners and FWS are constantly at odds.

Section III describes the methodology for the experiment I use to test how landowners respond to important elements of that legal environment and proposed changes to it.

Section IV presents a theoretical model that provides predictions for how landowners will respond in the different regulatory regimes, specifically within the structure of the experiment. Section V provides results of the experiment, which are discussed in Section VI. Section VII concludes with implications of the results for existing and proposed endangered species policies, and specifically the FWS proposed rule to use tradable credits to create a market for the provision of habitat.

II. Legal and Economic Context The ESA is known as the “pitbull of environmental laws” because it has teeth in situations where other environmental laws have failed to make much of a difference (Quarles 1998). The ESA gives authority to the FWS to promulgate rules to promote the conservation of species that are listed as endangered or threatened. Section 9 of the ESA prohibits the unauthorized “take” of listed species by either federal agencies or private actors. The FWS has defined take to include harming species, including habitat destruction. With this interpretation, private landowners can violate the ESA not only by purposefully killing or harming listed species, but also by engaging in economic activities like harvesting timber when that timber is habitat for a listed species. Some other protections afforded under the ESA, such as the Section 7 protections against jeopardy and adverse modification of critical habitat, apply to actions involving federal agencies, but the Section 9 restriction on take applies to private landowners as well.

With the Section 9 protections, it is not surprising that there is conflict between landowners and the FWS when the costs of protecting endangered species can fall largely on a small number of unlucky landowners. For example, when landowners in the coastal plain of North Carolina have mature pine on their properties, regulators set aside around 100 acres of land for each colony of red-cockaded woodpeckers (RCW), an endangered bird that resides there. Mature pine trees in this protected area can generally not be harvested, so landowners can be out up to $200,000 in present value of standing timber.

More woodpecker colonies means more land that will be protected, so landowners tend not to have incentives to encourage the endangered species to succeed. Courts have consistently held that this regulation does not constitute a “taking” of property that would require just compensation under the U.S. Constitution. In short, a problem with protecting endangered species on private property is that the ESA is “all sticks and no carrots” (Langpap 2006). Landowners and regulators like the FWS thus consistently find themselves in adversarial relationships, and sometimes landowners avoid regulatory restrictions by preventing endangered species from inhabiting their properties.

The FWS recognized that strict regulation of endangered species on private land may be having unintended consequences such as habitat destruction, so the agency started exploring creative approaches to try to mitigate the perverse incentives created by the ESA. In 1995, the FWS rolled out a voluntary program of safe-harbor agreements that represented a new option for landowners who were facing possible regulation for certain listed species. To enter a safe-harbor agreement, landowners promise to provide habitat sufficient to support a “baseline” number of the species in exchange for a promise from the FWS not to increase the regulatory burden if more members of the species move onto the property in the future. For example, a landowner who has a 500-acre property with three RCW colonies on it could enter an agreement by agreeing to restrict timber harvests on 300 acres to support the baseline in exchange for the certainty that she could continue to harvest trees on the remaining 200 acres. Another way to structure the agreement might be to agree to switch timber harvests from a 45-year rotation to a 75-year rotation.

Safe-harbor agreements can thus act as insurance policies against regulatory burdens, decreasing uncertainty for landowners for things like timber harvests.

Section 10 of the ESA provides FWS with authority to “permit... any taking.. if such taking is incidental to, and not the purpose of, the carrying out of an otherwise lawful activity” when there is a habitat conservation plan in place for the species (16 U.S.C. § 1539(a)(1)). Habitat conservation plans are species-level plans that specify how land will be managed in a way that helps endangered species rather than hurting them.

FWS has added other voluntary conservation tools like candidate conservation agreements that perform a similar role as safe-harbor agreements, but focus on protecting species that are candidates to be listed rather than species that are already listed as threatened or endangered.

Despite efforts by the FWS to use voluntary mechanisms to mitigate the perverse incentives of the ESA, there is still concern that habitat destruction on private land continues. The FWS has proposed a new policy that would reward landowners who provide habitat for species by providing the landowners with tradable credits (79 Fed.

Reg. 42525 (July 22, 2014)). The policy is targeted at pre-listing conservation efforts, so landowners who provide habitat for species that have not been listed as endangered or threatened, but may be in the future, are potentially eligible for credits. The policy is in its nascent stages, with public comment recently closed on an advanced notice of proposed rulemaking, so the details have not been laid out yet. The idea of the rule is as follows: A landowner who provides pre-listing habitat for eligible species receives credits for that habitat. If the species is later listed, the landowner can use those credits to offset habitat modification, such as timber harvest or development, on another property.

Alternatively, the landowner can sell the credits to others who may want to modify habitat. By creating a market for endangered species habitat, the policy intends to provide positive incentives for landowners who engage in conservation efforts. The FWS hopes tradable credits will be the sought-after carrot to get landowners to have better incentives to cooperate with the FWS in conservation efforts.

III. Experimental Design To test how landowners may respond in various regulatory regimes, 139 participants were recruited from the student population at Vanderbilt University.

Participants sat at computer stations for approximately 30 minutes as they engaged in the study. Participants were instructed to play a computer simulation in which they were landowners with 100 acres of mature pine trees. In each of 20 years of the simulation, landowners were asked how many of the 100 acres they would like to harvest. Trees became worth more as they grew older, as described in Table 1. Money from harvests was added to the landowners’ accounts, which were paid to them in cash after they were done taking the study. All participants went through practice rounds that provided familiarity with the mechanics of harvesting trees and adding money to accounts.

In each year, there was a probability that an endangered woodpecker would move onto the property. This probability increased with the average age of the trees, with a 0% chance of woodpeckers for trees below 20 years old and gradually increasing to a 20% chance of woodpeckers for trees 50 years old. In each year, participants were given the option of investing $0.25 in habitat improvement to increase by 50% the chance that woodpeckers would move in during the next year.

Participants were randomly assigned to one of four groups and were informed of

the following consequences of woodpeckers moving onto their property:

–  –  –

choice of entering a conservation agreement in which the landowner agreed to harvest no more than 5 acres in each year in exchange for regulators agreeing not to ban harvests if woodpeckers did move onto the property. Landowners could

–  –  –

landowner would receive a credit for each woodpecker that moved onto the property. If the landowner was in the agreement at the end of 20 years, each credit

–  –  –

Landowners who were in conservation agreements were able to exit them in any year by entering a harvest amount larger than the 5 acres allowed in the agreement. If landowners who were in a conservation agreement entered a harvest amount that would break them out of their agreement, they were given a warning that this would result in them leaving the agreement and they would not be able to reenter. If they currently had woodpeckers residing on their property, they are given an additional warning that their harvest activity went against the purpose of the safe-harbor agreement that they entered, and that they would be sent to the end of the game if they continued with the harvest.

However, these landowners were allowed to continue to break out of their agreements by harvesting more than 5 acres in that year before being sent to the end of the game. This meant that in the twentieth year of the simulation, landowners in agreements could break out of them and harvest all of their trees, even if there were woodpeckers residing on their property.

–  –  –

approximately two-thirds male and half of the participants are nonwhite. One-quarter of participants are Democrat, one-quarter are Republican, and half are independent or other.

Forty percent describe themselves as environmentalists, ten percent are smokers, and about two-thirds are risk averse based on a question about how they would handle a windfall of money.

–  –  –

To formalize the experiment in mathematical terms, this section describes how a utility-maximizing landowner may play the game. The landowner maximizes utility

–  –  –

go toward either general consumption or savings, and a taste for conservation, c. The utility function is assumed to be increasing in x and c, meaning the landowner is happier with more money and more conservation. The landowner discounts the future with factor β, so when β is below one there is a premium for utility in the earlier years over the later years. The landowner will choose actions that result in the set of pairs {x,c} that give the highest overall utility level over the entire period.

–  –  –

another year. The value of the trees next year is thus given by 1 − ℎ! ∗ (෱! + ෰!!! ).

€ In each year, there is probability γ that endangered woodpeckers will move in. If woodpeckers move in, the FWS invokes jurisdiction under the ESA to regulate the entire

–  –  –

randomly assigned group of the landowner, as described below. Table 1 provides values of ω and γ for selected tree ages.

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