PREDICTING NATURAL RESOURCE DAMAGES FROM OIL SPILLS IN THE UNITED STATES

The Oil Pollution Act of 1990 allows federal and state government agencies, acting as Trustees for natural resources on behalf of the public, to collect monetary damages from parties responsible for oil spills in the United States for the concomitant natural resource injuries. The monetary damages are usually based on the cost of projects to restore the lost or impaired services resulting from injuries to natural resources.¹ Oversight and monitoring costs for the restoration projects are often included in settlement amounts.

In this paper we develop a statistical model that explains most of the variations in NRD settlement amounts for past oil spills. The next section of our paper describes the sources of the NRD settlement data, explains the challenges in determining the NRD amount for oil spill settlements, and presents the NRD settlement data. Then, the following section provides our statistical model and its results. Finally, the last section of our paper illustrates the use of our statistical model to predict NRD settlement amounts for future oil spills.

We obtained information for our analysis of NRD settlements from a variety of sources. The consent decrees accompanying settlements were our preferred source for settlement amounts. When consent decrees were not available, we used NRD documents such as Damage Assessment and Restoration Plans for settlement amounts. We also used Federal Register notices, press releases, and newspaper articles for settlement amounts, when necessary.

We encountered several difficulties in developing our NRD settlements database. The main difficulty was in isolating the NRD amount in “global” settlements, which often included reimbursement for response costs, penalties and fines, litigation costs, and other non-NRD elements. In several settlements, assessment costs were combined with a portion of response costs or other non-NRD costs. Even when assessment costs were not combined with non-NRD costs, the settlement documents often excluded earlier payments of assessment costs. (For example, sometimes the responsible party had paid for some of the government's assessment costs in an earlier stage of the assessment, so those costs were not part of the settlement amount.) Furthermore, the assessment costs in NRD settlements only reflect the government's assessment costs. The assessment costs incurred by the responsible party are not included in the settlement amount. Therefore, we excluded assessment costs from our measure of NRD amounts, focusing exclusively on primary restoration costs, compensatory restoration costs, compensable values, and oversight/monitoring costs for restoration projects. Furthermore, we excluded payments for unspecified support of governmental and non-governmental programs (e.g., oil spill prevention programs) whenever possible under the assumption that these payments were made in lieu of fines or penalties.

We also found that some of the NRD settlements included projects that the responsible party was going to implement for which there was no cost estimate in the settlement. For example, the responsible parties on the 1994 Tampa Bay oil spill purchased some coastal property and developed a mangrove marsh on that property as part of the NRD settlement, but the settlement documents do not include a dollar value for that compensatory restoration project. Therefore, the Tampa Bay settlement amount in our database understates the full cost of that NRD settlement.

Finally, different sources of information on NRD settlements sometimes did not agree on the amount of the settlement or other characteristics of the spill (e.g., the amount of oil spilled). In such instances we assumed that the consent decree or the NRD document from the trustees (if we did not have the consent decree) was the most reliable source of the information in dispute. We also used the lower end of the range provided for the amount of oil spilled.

Our analysis includes every oil spill having an NRD settlement, except for some “anomalous” NRD settlements. For example, we excluded the Exxon Valdez NRD settlement ($900 million paid over a 10-year period) because it is more than an order of magnitude bigger than the next largest NRD settlement. We also excluded the $0 NRD settlement for the Mega Borg oil spill, which involved almost five million gallons of oil but caused no measurable environmental damages. We excluded the NRD settlements for small oil spills in Washington based on that state's NRD formula and three spills outside Washington for which we had no information on the amount of oil spilled. Finally, we excluded NRD settlements for “chronic” oil spills occurring over decades (e.g., the diluent leaks in the Guadalupe, California, oil field). In conclusion, our database includes NRD settlements for 86 oil spills ranging from 422 to 3,800,000 gallons.

Table 1 provides summary information on the oil spills and NRD settlements in our database. For the purposes of this paper we have listed the oil spills alphabetically by the name of the spill. The NRD settlements (excluding assessment costs) average $3.6 million in 2012 dollars after adjusting for inflation, and range from $0 to $41.94 million.² The total for all of the NRD settlements in Table 1 is about $319 million after adjusting for inflation to 2012.

Our statistical model uses a multiple-regression approach to explain variations in inflation-adjusted NRD settlement amounts (less assessment costs) for oil spills in the United States. The goal of a multiple regression approach is to explain changes in the “dependent” variable as a function of the magnitude of the “explanatory” variables. The dependent variable in our statistical model is the inflation-adjusted NRD settlement amount (minus assessment costs) in millions of dollars.³ Table 2 describes the explanatory variables (i.e., the variables that may explain variations in NRD settlement amounts) included in our statistical model. In general, the explanatory variables are the basic characteristics of an oil spill that might affect the magnitude of natural resource damages, including:

• amount of oil spilled,

• type of oil spilled,

• year of the settlement,

• number of years between the spill and the settlement,

• season in which the spill occurred,

• geographic region in which the spill occurred,

• whether the spill occurred in saltwater or freshwater,

• whether threatened or endangered species were injured by the spill,

• whether the spill closed a recreation area,

• whether unvalued compensatory restoration costs are part of the settlement,

• the number of trustees, and

• whether one or more of the trustees were tribes.

Other factors might affect the magnitude of NRD settlements, such as:

• the duration of the cleanup,

• the geographical extent of the spill,

• the number and type of injured threatened or endangered species,

• the duration of recreation area closures, and

• the availability of similar substitute recreation areas for the closed recreation areas.

Unfortunately, we could not find information on these factors for most of the oil spills in our database. Consequently, we could not include these factors in our statistical analysis.

We included all of the variables in Table 2 in our initial statistical model. However, most of the variables did not have statistically significant coefficients. We then excluded most of the variables with insignificant coefficients in our next statistical model.⁴ Table 3 shows the results for that statistical model. As indicated by the R², our statistical model explains 78 percent of the variation in NRD settlements. Most of the explanatory variables in our model have statistically significant coefficients at the 1% level. Only one explanatory variable (Saltwater) does not have a statistically significant coefficient at the 10% level. Furthermore, all of the coefficients have the expected sign (i.e., positive or negative). Thus, the results from our statistical model are very good.

As shown in Table 3, the factors with positive coefficients in our model are: GALLONS, T&E SPECIES, CALIFORNIA, SALTWATER, and RECREATION CLOSURE. This means that NRD settlements tend to increase when these factors increase or when these factors are present, holding other factors in the model constant. For example, the results indicate that NRD settlements tend to be higher for larger oil spills than smaller oil spills, other things being equal. Similarly, NRD settlements tend be higher for spills that injure threatened or endangered species, holding other factors constant. NRD settlements also are higher for spills that occur in California, in saltwater, and when recreation areas are closed.

The negative coefficients in our model are: ZERO AND LA/TX, UNVALUED COMPENSATORY RESTORATION, and INTERIOR. The ZERO AND LA/TX variable accounts for seven spills in Louisiana or Texas that had a $0 NRD settlement after subtracting assessment costs. The responsible parties implemented all of the restoration projects in these oil spills, resulting in no payment to the Trustees for the cost of those projects. The UNVALUED COMPENSATORY RESTORATION variable reflects settlements that included some compensatory restoration that was not reflected in the settlement amount. The dollar amount of the settlements for these spills was lower, other things being equal. Finally, spills occurring in a non-coastal state had lower settlement amounts than spills occurring in coastal states, other things being equal.

Interestingly, several factors that we thought would explain some of the variation in NRD settlements did not have statistically significant coefficients. For example, the year of the settlement did not have a statistically significant coefficient in our best model, which indicates no change in NRD settlement amounts over time after taking into account other important factors. Other factors that did not explain the variation in NRD settlement amounts include: the season in which the spill occurred, the type of oil spilled, whether the spilled oil came from a vessel, a pipeline, or a storage tank; the number of years between the spill and the settlement, the number of trustees, and the presence of tribal trustees.

While our statistical model explains variations in NRD settlement amounts in the past, it can also be used to predict NRD settlement amounts for future oil spills. Specifically, we can predict the NRD settlement for a future oil spill by applying the coefficients from our model to the characteristics of the future spill. Since the coefficients are estimated with some statistical error, we use a technique called bootstrapping to estimate a range for the possible NRD settlement for a spill having certain characteristics. The 90-percent confidence interval comes from taking 1,000 random draws from the original dataset then running our model 1,000 times (once for each random draw). The regression results give us a range of settlement predictions that creates the confidence interval. Our point estimate for the predicted NRD settlement amount is the median of the NRD settlement amounts from the 1,000 repetitions of the model.⁵

To illustrate the use of our model for predicting future NRD settlement amounts, Table 4 provides the characteristics of three hypothetical oil spills. Spill 1 is a relatively small spill in a coastal area of California, with some injury to threatened or endangered species. Spill 2 is a much larger spill in a freshwater area of a non-coastal state, which injures some threatened or endangered species and closes some recreation areas. Finally, Spill 3 is a very large oil spill in a coastal state outside California, which injures threatened or endangered species and closes some recreation areas.

Table 4 shows the median and 90% confidence interval for the predicted NRD settlement amounts for the three hypothetical oil spills. The predicted settlement amount for Spill 2 is only slightly higher than the predicted settlement amount for Spill 1, because the spill occurs in a non-coastal state, even though Spill 2 involves a much larger amount of oil.

Barring any major changes in the process of quantifying NRDs, our statistical model should provide reasonably accurate predictions of NRD settlement amounts for oil spills in the next few years. Hopefully, such predictions will reduce the time required for negotiating NRD settlements, which will lead to faster primary and compensatory restoration actions. At a minimum, such predictions will inform potentially responsible parties of the potential cost of NRD settlements in advance of actually paying the costs.

Richard W. Dunford, Ph.D., is the owner of Environmental Economics Services (EES), a consulting firm located in Raleigh, North Carolina. He has led or worked on more than 70 natural resource damage assessments (NRDAs) on behalf of responsible parties. He has numerous publications on NRDA-related topics and also has made presentations at many NRDA conferences and workshops. Ms. Melissa K. Lynes, M.A., is a Ph.D. candidate in the Department of Agricultural Economics at Kansas State University. She previously was a Research Assistant for EES. The authors want to thank Michael A. Dunford, B.A., (currently an EES Research Assistant) for helping compile and validate the NRD settlement amounts.