Impact of Climate Change and Land Use on the Southwestern United States

Impacts of climate change on society

The Endangered Species Act and Critical Habitat Designation: An Integrated Biological and Economic Approach

The authors are (in reverse alphabetical order):
Gary Watts, Watts and Associates;
William Noonan, U.S. Fish and Wildlife Service;
Henry Maddux, U.S. Fish and Wildlife Service; and
David S. Brookshire, Department of Economics, University of New Mexico.

April 1997

Originally prepared for the "Social Order and the Endangered Species Act" Conference at the University of Wyoming.

The individuals who contributed time, effort, and data to this study are far too numerous to list here. A complete list can be found in the project reports Brookshire et al. (1993, 1994, 1995). We owe a special debt of gratitude to Mel Schamberger, Larry Shanks, Kristen Kingery, Reed Harris, Bob Williams, and Margot Zallen. The authors acknowledge the contributions of Michael McKee, University of New Mexico, who, although he declined to be an author, contributed extensively to the Regional Impact Modeling section.


The Endangered Species Act of 1973, as amended, assigns the U.S. Fish and Wildlife Service the responsibility for listing species of plants and animals in the United States whose existence is either threatened or endangered. After a species is listed, the Service is responsible for, among other things, developing recovery plans, reviewing proposed federal actions to ensure that they do not compromise recovery efforts, and designating critical habitat.

The designation of critical habitat for endangered species involves reallocation of resources. This paper sets forth the methodology and results from two case studies that measured the economic impacts of designating critical habitat. The case studies vary in regional scope. The first study incorporates seven states along a 2200 mile stretch of the Colorado River and its major tributaries and focuses on six endangered fishes. A second study analyzes two endangered fishes in a two county study region in Utah and Nevada through which the Virgin River flows.

The methodology utilized in both case studies was to measure the impacts of designating critical habitat and involves the following steps: (1) determining how the biological needs of endangered fish will affect the allocation of resources among river users; (2) assessing the direct economic impacts of resource reallocations on river users; and (3) using a set of applied general equilibrium models of the affected region in order to capture all of the direct and indirect effects of resource reallocations.

Approaching the estimation of the impacts of designating critical habitat in this fashion insures that all actions taken on behalf of the endangered species will be captured in the analyses as reallocation of resources. This insures that impacts are inclusive of negative as well as positive effects that stem from the reallocation process.

The principle results of the two case studies are that sectoral impacts are both positive and negative. The sub-regional impacts for both case studies are not distributed evenly. The regional impacts, whether positive or negative, are small relative to a baseline level of economic activity representing no actions taken on behalf of the fishes. The national efficiency effects as determined in the Colorado study are effectively zero for the designation of critical habitat.


The Endangered Species Act (Act) of 1973, as amended, assigns the U.S. Fish and Wildlife Service (Service) the responsibility for listing species of plants and animals in the United States whose existence is either threatened or endangered. After a species is listed, the Service is responsible for, among other things, developing recovery plans, reviewing proposed federal actions to ensure that they do not compromise recovery efforts, and designating critical habitat for listed species. Such critical habitat designations, at least in certain situations, can alter economic activity in critical habitat areas that might otherwise be of detriment to certain specles.

Although the Act has no provisions for studying the economic consequences of listing threatened and endangered species, it does require the Service to assess the economic impacts of all proposed critical habitat designations. As a result, economists have been participating in the ongoing process of designating critical habitat for endangered species and assessing the economic impacts of such designations.

It has been argued that the process of listing a species as endangered or threatened has far greater economic consequences than subsequent critical habitat designations, an argument that has some merit with respect to the examples discussed in this paper. As a practical matter, however, most economic studies of critical habitat designations attempt to estimate the combined effects of both listing and critical habitat designations, and then allocate a proportion of effects to each administrative action.

It is almost axiomatic that setting aside critical habitat for endangered species involves a reallocation of resources. Threatened and endangered species are usually listed because the current allocation of resources has resulted in excessive habitat degradation. Such adverse modification of natural habitat is generally due to economic activity that has occurred as a result of human settlement and economic development. Resources are allocated to particular uses as a result, and stabilizing and/or reversing this development requires that these resources be allocated to other uses. For example, trees may not be harvested that provide habitat for birds, water may not be used for irrigation so that stream flows are returned to more historic levels, and land may not be developed for housing so that habitat for plant species is preserved. However, by not harvesting trees or building houses, recreational uses may be enhanced and setting aside minimum stream flows in one area may imply that more water is available for development elsewhere. Assessing the economic impacts of designating critical habitat thus requires a general equilibrium analysis to fully capture the range of potential activities created by the designation as well as the range of activities that are eliminated or reduced. In short, the reallocation will yield economic impacts that are benefits as well as costs.

This paper reports the methodology and results from a study that measured the economic impacts of designating critical habitat for four endangered fishes along a 2,200 mile stretch of the Colorado River and its major tributaries. A second case study covering two fishes and 160 miles of the Virgin River in Nevada and Utah is also discussed. The two case studies analyze the impacts of critical habitat designation on two regions greatly differing in size. For the Colorado study, designation affects all seven states in the Colorado river basin: Arizona; California; Colorado; Nevada; New Mexico; Utah; and Wyoming. The critical habitat analyzed in the Virgin study covers a river flowing through three counties in Arizona, Nevada, and Utah. In both cases, the study region was determined on the basis of habitat needs and direct economic impacts.

Two study regions differ considerably in the sizes of their economies. The output of the region in the Colorado study is approximately $1.3 trillion annually, compared to $28 billion for the Virgin study region. The Colorado study region constitutes a diversified economy that has experienced growth above the national average during the last several decades. The region of the Virgin study is currently one of the fastest growing areas in the United States, with continued high population growth rates projected for the time horizon of the study. The time horizons of the studies coincide with the time span of the proposed recovery plans for the species: 1995 to 2020 in the Colorado study; and 1995 to 2040 in the Virgin study. The major characteristics of the two studies are summarized in Table l.

Table 1
Summary of the Two Case Studies

 Colorado River StudyVirgin River Study
Listed SpeciesColorado squawfish, humpback chub, bonytail, razorback suckerwoundfin, Virgin River chub
Proposed Critical Habitat2200 km of river160 km of river
Direct Impactsoperational pattern of federal reservoirs, recreational activities, agricultural sectors re-allocation to municipal and industrial, new power facilitiestiming of flows, agricultural sector ajustments, expedited water project construction
Affected RegionArizona, California, Colorado, New Mexico, Nevada, Utah, Wyomingthree counties in Nevada, Utah, and Arizona
Time Horizon1995-20201995-2040
Regional Impact ModelInput-Output, Computable General EquilibriumInput-Output
Number of Economic Sectors2016
Number of Impact Scenarios12

To recover the endangered fishes in these two river systems, the river systems must be protected and/or altered to more closely represent the natural conditions that are believed to be biologically necessary for species survival. Alteration of biological conditions, through listing and the designation of critical habitat, will in turn restrict or alter human uses of the river systems and thus generate direct and indirect economic impacts. The methodology used in the Colorado River and Virgin River studies to measure such impacts involves the following steps:

  1. determining how the biological needs of endangered fishes will affect the allocation of resources among river users;
  2. assessing the direct economic impacts of resource reallocations on river users; and
  3. using a general equilibrium model of the affected region to capture all of the direct and indirect effects of resource reallocations.

Approaching the estimation of critical habitat impacts in this fashion can avoid pitfalls that arise when the focus is on the losing sectors of a local economy. Perhaps the most publicized economic analysis of proposed critical habitat designations was that for the northern spotted owl (Schamberger et al. 1992). That analysis presented a thorough assessment of the impacts of critical habitat designations on the timber industry utilizing public forest resources in the Pacific Northwest, and at one time was designated as a "model for subsequent analysis" by the Service (ECO Northwest 1994). Yet the spotted owl study did not address some of the basic economic questions that arise when resources are reallocated, such as how the rate of timber harvesting on private lands and non-critical habitat lands would change in response to critical habitat designations on federal lands, or how labor resources formerly used to harvest lumber of public lands would be redeployed. The case studies described in this paper attempt to address issues such as these in the context of critical habitat designations for endangered fish.

From Biological Needs to Resource Reallocations

The administrative procedures of the Endangered Species Act prescribe certain steps in the evaluation of the economic impacts of critical habitat. These have been widely discussed elsewhere (see Rolf 1989; Berrens et al. 1997.).
The first step in both the Colorado River and Virgin River studies was a biologically-based determination of potential critical habitat needs (Maddux et al. 1993, 1995). In many instances, critical habitat studies are conducted for a single species. Since there are several endangered fishes in each river system and their habitat needs are similar both studies cover multiple species. The four listed fish species in the Colorado River basin are the Colorado squawfish (Ptychocheilus lucius), the razorback sucker (Xyrauchen texanus), the humpback chub (Gila sypha), and the bonytail (Gila elegans). The Virgin River listed species are the woundfin (Plagopterus argentissimus) and the Virgin River chub (Gila seminuda).

The Colorado squawfish and the humpback chub were listed as endangered species on March 11, 1967 (32 Federal Register 4001), and thus were originally listed under the auspices of the Endangered Species Preservation Act of 1966. The razorback sucker was listed as endangered on October 23, 1991 (56 Federal Register 54957), the bonytail on April 23, 1980 (45 Federal Register 27713). The listing of the woundfin occurred on October 13, 1970 (35 Federal Register 16047), and the listing of the Virgin River chub on August 24, 1989 (54 Federal Register 35305).
Endemic fish populations in both study regions have been declining since the turn of the century. The declines are a result of physical and biological changes in the river systems: stream flow alterations, habitat fragmentation and modification, contaminants, and competition with and predation by introduced non-native fish. The natural hydrography of the systems have been significantly altered by the construction of dams and increasing consumptive water uses. Current consumptive water uses include agricultural, municipal and industrial, and reservoir evaporation (Maddux et al. 1993, 1995). In order to enhance consumption over time, a series of dams have been constructed throughout the Colorado River system. A total of 43 major dams and diversions have been constructed.

Determination of critical habitat requires consideration of physical and biological features that are essential to species conservation. The critical habitat designated in both river basins was aimed at creating biological conditions that enhance the constituent elements for the target species. These features, referred to as constituent elements, include: (1) space for populations; (2) food, water, or other nutritional or physiological requirements; (3) cover or shelter; (4) sites for breeding, reproduction, and rearing of offspring; and (5) habitats that are protected from disturbance or are representative of the historical and ecological distribution of species.

In the Colorado River study, over 2,200 miles of the river and its tributaries were designated critical habitat to provide one or more of the constituent elements described above. These designations protect river flows deemed necessary for species survival and recovery as well as riparian areas in the flood plain that are used as backwater breeding areas during periods of high spring flows. The designations also effect how water is released from federal reservoirs along the river system. For example, all four Colorado River fishes require high spring flows for successful breeding and the survival of juvenile fish. Storage of peak flows in federal reservoirs for later release to downstream users could thus be considered an adverse modification of critical habitat in violation of the Endangered Species Act.

The practical effect of the designations on the reallocation of resources among other river users is a function of geography. A substantial amount of critical habitat was designated in the state of Colorado on the upper Colorado River and its tributaries, the Gunnison and Yampa Rivers. Along these river reaches, the practical effect of the designation is to limit further consumptive uses of waters that would reduce peak spring flows needed to provide breeding habitat for fish. These restrictions might inhibit or prevent the state of Colorado from proceeding with plans to divert more Colorado River water to front range communities for municipal and industrial uses. They may also restrict Wyoming's ability to develop and use water in the Little Snake River, a tributary of the Yampa. Water that would otherwise have been consumptively used in Colorado and Wyoming could instead be stored in Lake Powell and eventually released for use by lower basin states. Furthermore, in lieu of water from the Colorado River, municipal and industrial water users in Wyoming and Colorado may rely more heavily on purchases of agricultural water rights or increased agriculture effficiencies.

Critical habitat designated along the San Juan River in New Mexico, a major tributary to the Colorado, would also have negative impacts upon agricultural production. In this case, the existence of critical habitat could prevent the Navajo Tribe from implementing plans to expand the Navajo Irrigation Project near Farmington over the next two decades. As a result, water that would otherwise have been put to irrigation use in New Mexico will also flow into Lake Powell and eventually be released for use by lower basin states.

Substantial amounts of critical habitat were also designated along the lower Green River below Flaming Gorge Reservoir in Colorado and Utah and along the Colorado River between Lake Powell and Lake Mead. The practical effect of these designations will be to cause the U.S. Bureau of Reclamation to alter its operating plans for those reservoirs. Prior to listing and critical habitat designations, these reservoirs were operated primarily to maximize hydropower production subject to the restrictions of meeting downstream demands and maintaining flood control storage space. This operational regime resulted in relatively constant monthly releases with extreme diurnal fluctuations to provide peaking power for electricity consumers. To provide the constituent elements of critical habitat, however, both Glen Canyon and Flaming Gorge Dams are being reoperated to increase spring releases and decrease fall releases with fewer diurnal fluctuations to provide for breeding habitat for endangered fish. These new operating plans will, in turn, affect hydropower production and recreational uses of the river.

Other tributary reservoirs on the Gunnison and San Juan Rivers are also being reoperated to enhance habitat for endangered fish.
Critical habitat was also designated on the Lower Colorado River below Lake Mead. To provide the constituent elements of habitat needed in this area, a different reallocation of resources was needed than for the upper and middle sections of the basin. Along the lower river, the primary threats to endangered fish consist of competition from non- native warm-water fish species and bankside developments such as recreational vehicle parks that can impinge upon backwaters and spawning areas. In many cases, future game-fish stocking and management programs and stream side developments will be altered or prohibited in critical habitat areas. Thus, the practical effect of designations along the lower river will be to transfer water from recreational to preservation uses.

In the Virgin study area, water is being redirected from the currently dominant use, irrigated agriculture, to municipal and industrial uses in order to satisfy the demands of a rapidly growing population. The demands for the endangered fishes will compete with municipal and industrial demands for water currently used in agricultural production. The designation of critical habitat is not the primary cause of declining agricultural production in the area, but will accelerate the ongoing conversion from agricultural uses to other, predominantly municipal and industrial uses.

Estimating Direct Economic Impacts

The resource reallocations described above were translated into estimates of output changes in directly affected sectors of local and regional economies dependent upon the river. In the Colorado River study, prohibitions upon further water depletions in critical habitat reaches along the upper river were modeled by reducing the output of the agricultural sectors of Colorado and Wyoming. The rationale for this approach is that in lieu of developing Colorado River waters for municipal and industrial uses, the municipalities in the two states will increase the rate at which irrigation water rights are being purchased and transferred to other uses. The amount of agricultural output foregone was computed using estimates of crop consumptive irrigation requirements, field irrigation efficiencies, cropping patterns and yields; all taken from published sources. State agricultural production was reduced to match the equivalent amount of water depletions foregone due to critical habitat designations based upon state water planning documents.

The effects of critical habitat designations on water users below Flaming Gorge and Glen Canyon dams were modeled in two ways. First, a sample of outfitters providing rafting, fishing and other recreational services to the public was interviewed in person to assess their reactions to the flow changes needed to enhance spawning habitat for endangered fish. Each outfitter was shown visual hydrographs of average river flows by week, both before and after critical habitat designations, for reaches of the river where he operated. Each outfitter was then asked to identify periods of the year when his operations would be affected by the new operating regimes. In most cases, the outfitters were able to identify some negative impacts of the new operating regimes on their operations. These consisted primarily of an increased frequency of high-flow periods in the spring when river boating and rafting would be too dangerous and an increased frequency of low-flow periods in the late summer and fall when boating and rafting would be impractical. Outfitters would not be able to shift trips to other times of the season because of launch restrictions imposed by federal resource management agencies. Because the most likely substitute sources of similar recreational experiences are outside of the Colorado River basin, it was assumed that regional output in the recreation and tourism sectors of the economy would decline relative to pre-critical habitat conditions. Based upon the interview results the amount of the decline was estimated using Colorado River recreational usage and expenditure data assembled by federal agencies, adjusted to reflect the percentage of time that the river would have unusable recreation flows.

The second direct effect of new operating regimes was to limit the amount and timing of hydropower production. Estimates of the direct economic effects of this resource reallocation were developed by Stone and Webster Management, Inc., which has extensive experience modeling hydropower impacts for the Bureau of Reclamation. The results of the Stone and Webster study indicate that the new operating plans would result in the construction of an additional 121 megawatts of electrical generating capacity in the basin, a somewhat higher average market price for electricity, and somewhat lower consumption.

Estimates of direct impacts for critical habitat reaches on the lower Colorado River below Lake Mead involved both the recreational and agricultural sectors of the regional economy. Because Wyoming and Colorado will forego some future consumptive uses of Colorado River water to protect endangered fish, the state of California likely will be the net beneficiary of that foregone consumption. At present, none of the upper Colorado River basin states (Colorado, New Mexico, Utah, and Wyoming) utilize their full allotment of water under terms of the Colorado River Compact. This water is currently stored in Lake Powell until it is released for hydropower production or to create storage space for flood control purposes.

Historically, California has been the beneficiary of such releases because Arizona and Nevada (the other lower basin states) have not been able to fully utilize the additional water. Although that situation may change in the future, for this study it was assumed that California would continue to benefit from foregone upstream developments. The study originally assumed that all water consumption foregone in upper basin states would benefit California's economy. That assumption was later relaxed to allow some additional consumption by Nevada to serve the burgeoning need for municipal and industrial water in the Las Vegas area.

The benefit to California will be the inverse of the impact to Colorado's economy. Instead of increasing the rate of irrigation water rights transfers to municipal and industrial uses, critical habitat designations will allow California to experience a decrease in the rate of such transfers relative to baseline conditions. As a result, California will experience relatively higher output in its agricultural sectors compared with pre-critical habitat conditions. The amount of this increase was estimated using a similar approach and data sources were used to estimate the magnitude of agricultural output declines in Colorado and Wyoming. In addition, it was necessary to estimate river transit and reservoir evaporation losses in moving water from the upper to the lower basin. This information was provided by the Bureau of Reclamation.

The other direct economic impact that was quantified for the lower basin was a decrease in sport fishing activity at Lake Mead and Lake Mohave relative to pre-critical habitat conditions. This decrease would come about because state plans to enhance warm-water recreational fisheries in the two reservoirs may be restricted or prohibited because of potential negative impacts on endangered fishes. The magnitude of this effect was estimated using data on fishing activity and fishing expenditures supplied by state officials. Although there may be other direct impacts to the lower basin involving development restrictions in riparian areas, they were not quantified during this study.

For the Virgin River study, the direct physical impacts consisted primarily of flow changes (levels and timing) with some consideration given to water quality issues stemming largely from salinity levels. The resulting direct economic impacts fall largely on the agricultural sector. However, there is an additional category of impact that arises in this case. Several water delivery projects are planned for the next 45 years to cope with regional population growth. Critical habitat designations will necessitate that these projects be constructed earlier with a consequent increase in the cost of water delivery and this will have the effect of reducing household and firm budgets for other expenditures. Alternatively, conservation actions will be required which will also raise costs to water users in the form of additional investments in conservation actions.

Per capita water use in the St. George, UT area is considerably greater than in other southwest urban areas. Current use is 465 gallons per capita per day (gpcd). For the conservation scenario this was reduced to approximately 260 gpcd which is comparable to Phoenix and well above Tucson, AZ which has a use rate of 160 gpcd. Conservation requires expenditures which raises the effective cost of water and this was incorporated into the scenario.

Regional Impact Modeling

The detailed accounts of the modeling are found in Brookshire, McKee, and Watts (1993), Brookshire, McKee, and Watts (1994), and Brookshire, McKee, and Schmidt (1995). This section draws upon and is taken in part from chapters 7, 8, and 15 (section K) of Brookshire et al. (1993) and was utilized in Brookshire et al. (1994, 1995).
Two classes of applied general equilibrium models were developed for the analysis of the economic impacts associated with the protection and recovery of endangered species in the Colorado study. The first class consists of a set of conventional Input-Output (I-O) models of the entire region and of the sub-regional units (e.g., one for each of the seven states). The second class is a Computable General Equilibrium (CGE) model of the entire region. For the Virgin River study, separate I-O models for each of the two impacted counties and a regional model for all three counties were developed.

The I-O and CGE analyses enable the determination of a variety of impact measures. Impacts are measured as changes in output. The two model classes measure impacts at three levels: the sub-regional level; the regional level; and the national level. Depending on the case study, the sub-regional level differs considerably in size. In the Colorado study individual states are the lowest level at which impacts are determined. For the Virgin River case study, the county is the sub-regional level, the regional level being a three county region.

CGE models offer several advantages over I-O models, but the central advantage is that CGE models admit factor substitution in production in response to changes in relative prices, while the conventional input-output model employs a fixed proportion (Leontief) production function. The usual production function employed in CGE models consists of a nested form involving either Cobb-Douglass/Leontief or Constant Elasticity of Substitution (CES)/Leontief forms. The intermediate inputs (outputs of the other sectors in the economy) enter the production function in fixed proportions with coefficients from a regional input-output table. The primary inputs (labor and capital along with land, energy, etc., if these are modeled) enter the top-level of the production function along with the composite input produced as intermediate goods. CGE models are, however, much more data-demanding than I-O models. Thus, only a single CGE model was constructed for the Colorado study and none for the Virgin study.

The I-O Model Structures

The methodology for constructing regional I-O models is widely discussed in the literature. [See Miller and Blair (1985) for a complete development of the theoretical and empirical foundations of I-O analysis.] I-O models are a device for organizing the basic accounting relations that describe the production sector of the economy. The I-O method assumes: all sectors of the economy are tied together by virtue of economic relations called "linkages." Further, the production of a good or service can be described by a "recipe" with the ingredients being the outputs of the other sectors of the economy as well as the primary inputs such as labor, capital, and other raw resources.

Defining I as the identity matrix, A the interindustry matrix, X the vector of outputs, and Y the vector of final demands, the I-O model equations can be represented as:

(I-A)X = Y

and the outputs necessary to satisfy intermediate and final demand may be solved for as:

X = (I-A)-1Y

where (I-A)-1 is known as the Leontief inverse.

Given exogenous shocks to a local economy, changes in gross outputs required to satisfy changes in final demands and/or resource availability are determined. Through its multiplier impact analysis, the I-O model is capable of generating estimates of the changes in output of given commodities, changes in employment, and changes in income.

The primary database for the construction of the initial I-O models was the IMPLAN data. For the Colorado River study, the baseline matrices were constructed from 1982 databases. The Virgin River study utilized 1990 databases. The original 528 IMPLAN sectors were aggregated to 20 for the Colorado River study and 16 for the Virgin River study. This aggregation reduced the dimensionality of the analysis to manageable levels and enabled the sectors that were affected by direct impacts to be analyzed.

The IMPLAN modeling and database project were initially undertaken by the U.S. Forest Service to provide regional I-O modeling capability (see U.S. Department of Agriculture 1993). The database management and development and the software development are now conducted by the Minnesota IMPLAN Group (MIG). For these projects, the use of IMPLAN was confined to the construction of the input data sets to the I-0 models that were developed in the GAUSS programming language (see Brooke and Meeraus 1992).
To update the Colorado River model to the 1989 baseline used for analysis, the Gross State Product data from the Department of Commerce, Bureau of Economic Analysis (BEA) were used to update final demand levels for each of the 20 sectors of the I-O model. These data are available at the state level for the period from 1982 through 1989 for 73 sectors which can be matched (via SIC codes) to the 20 sectors represented in the I-O models constructed for the Colorado project. In this way, the economic activity reported in the 1982 IMPLAN data set was updated to 1989 (in 1982 dollars). The updated gross output levels were used to update the remaining components of the I-O models based on the 1982 ratios and coefficients. The analyses results are reported as output changes.

Impacts on employment, wages, and taxes are also presented for the region and by sector in Brookshire et al. (1993, 1994, 1995).

CGE Model Structure

The approach used in constructing the CGE model of the Colorado River seven state region follows from the work of Sherman Robinson and his colleagues. This model assumes that the economy is competitive; all prices are presumed to be able to adjust to clear factor and goods markets; all consumers maximize utility; and all producers maximize profits (or, equivalently, minimize costs). Production is characterized by constant returns to scale so that factor payments exhaust the value of the product. Supply (domestic production plus imports) equals demand (domestic consumption plus exports) in all markets.

Models constructed via the "Robinson" approach are typically solved using computer programs designed to solve large-scale systems of non-linear equations. The GAMS (General Algebraic Modeling System) software was adopted to solve the model of the seven-state region. This package offers considerable flexibility in the construction of the CGE model and in conducting simulation analyses. See Dervis, de Melo and Robinson (1982), Berck, Robinson, and Goldman (1991), and McKee et al. (1996) for a discussion of this class of CGE model.
The household sector is represented as utility-maximizing consumers; the production sector is represented as profit-maximizing firms whose decisions determine the supply of goods and the demand for factors of production (primary and intermediate inputs); international (interregional) trade is represented; there is a government sector collecting taxes and providing collective goods; and there are the market clearing conditions (may be based on assumptions concerning equilibrium or disequilibrium outcomes).

The Social Accounts Matrix (SAM) provides a link between the National Income and Product Accounts (NIPA) data, and the input-output accounts data. As such, it serves as a cornerstone of the CGE models constructed using the Robinson method. The specific structure of the SAM is determined by the application at hand.

A 19 sector model was constructed with the benchmark data set for 1982. The outputs of the 19 sectors of the economy are produced with inputs of labor, capital, land (where applicable), and an intermediate good. The intermediate good is a composite commodity with the weights determined by the input-output coefficients from the baseline data set. The production function is defined as a constant returns Cobb-Douglas over the primary factors:

(this is the expression for the non-agriculture sectors) where
and Ai is a constant. The primary factors account for the output net of that explained by the intermediate good and the imports used in that intermediate good. This residual is labeled the unit value added, and it is defined as:

where the second term represents the value of the intermediate input to good I, ti the indirect taxes, and Mi the imports used to produce good I. This unit value added is attributed to the labor and capital (also land) inputs from the region. Profit maximization requires that these factors be hired to the point that their price equals their marginal value added:

The factor markets clear when this condition is met and when the sum of labor (capital, land) demanded equals the sum supplied.

There are three households in the economy classified as High Income, Middle Income, and Low Income. [The baseline income levels are in 1982 dollars.] Income is earned through the sale of factors of production. Each household devotes income to the goods produced by the 19 sectors of the economy and to savings. Total consumption for each household class is given by:

where s denotes the marginal propensity to save and Y the household disposable income. The consumption for each good is then the share of this total consumption devoted to each good:

where [equation] denotes the share spent on good I and C is total consumption from.

In classical trade theory, for a small open economy (SOE) there is an assumption concerning prices of traded goods that is sometimes referred to as "the law of one price". Traded goods are assumed to be perfect substitutes independent of the geographic area of production, the implication being that prices are independent of region of production. Since regions are observed simultaneously importing and exporting the same "good," the law of one price is probably not an accurate reflection of price formation in the SOE. That is, domestic and imported goods are likely to be imperfect substitutes, especially in cases with the levels of aggregation commonly used in applied work. As an approach, Armington (1969) postulated a weighted price formation mechanism in which the domestic price of a good is generated by a function that applied weights to the fraction of the regional consumption of the good that was domestically produced and the fraction imported into the region.

In constructing the CGE model for this study, the SOE assumption was used as the basis for constructing the model of the seven states region. This well-developed approach has the advantage of fairly modest data requirements while maintaining theoretical soundness. The linkages between the regional economy and the rest of the world are maintained through the assumptions implicit in the SOE approach: the region takes the world prices as given and differences in products by origin are accommodated through the Armington functions. Since the bulk of the region's trade is with the rest of the U.S., the assumption of "world" prices is a reasonable one. In keeping with the SOE assumptions, the flow of funds from outside the region are fixed at the baseline levels. This condition is based on the fact that the regional economy, while large in absolute terms, is a fairly small part of the national economy.

Domestic consumers are assumed to have a CES utility function over domestic produced and imported goods (for a given category of goods):

where [equation] and [equation] are constants estimated from the baseline data and a is the elasticity of substitution between domestic and imported goods and
. Consumers are assumed to choose a mix of domestic and imported goods which minimizes the cost of obtaining a level of utility.

On the supply side, a comparable construction yields a CET function between domestically consumed (XDi) and exported (Ei) goods:

where [equation] is domestic output, [equation] and [equation] are constants estimated from the baseline data, and the elasticity of transformation between domestic consumption and exports is
Producers are assumed to maximize revenues from a given level of domestic production by allocating this domestic and export sales. For a regional economy, the exchange rate is 1.0 (most of the trade appears as transactions with the rest of the U.S.) so export and domestic prices are identical.

The CGE model describes a regional economy within the U.S. economy. For a regional economy there are no trade deficits. Any difference between real imports and real exports is made up through the capital account as funds flow into the region or out of the region to balance the goods and services account.

Several conditions must be met for an economy to be in equilibrium and are specified in the model closure conditions. Supply must equal demand in all markets (goods and factors), the external sector account must be in equilibrium (imports equal exports plus/minus capital account flows), and savings must equal investment. By Walras's Law one of these conditions is redundant. The current model omits the savings-equal-investment condition as the redundant closure condition. The government sector is permitted to run a debt financed through borrowing. Additionally, the model also specifies some conditions as fixed in order to close the model. Capital is fixed by sector thus the model solves for labor movements in response to exogenous shocks. Labor is freely mobile across sectors, and the labor market clears when aggregate demand equals aggregate supply. These relationships assume that the direct impacts being evaluated are not large.

The CGE model allows the analysis of the national economic efficiency effects of the actions taken under listing and the designated critical habitat. A measure of the change in producer surplus is computed directly in the CGE model as the change in rents earned in the producing sectors. Since capital is fixed in the short run, these rents represent producer surplus. Household consumption is computed as:

where [equation] denotes the share spent on good I and C is total consumption, it is possible to construct cost-of-living indices that are first-order approximations of consumer surplus changes.

The following is adapted from Boadway and Bruce (1984, 212-213) and is also discussed in Varian (1992).
Two indices are commonly constructed for this purpose, the Laspeyres and the Paasche quantity indices. These are defined, respectively, as follows:

where the superscript n refers to the new prices and quantities and the superscript o refers to the old prices and quantities. These can be written in level form and the Laspeyres index is written as:

As Boadway and Bruce (1984) show, this is a first order approximation ofthe equivalent variation (EV) and the compensating variation (CV) associated with the quantity changes between resource allocations. Since the higher order terms require more information than is observable in price and quantity changes, these indices are widely used to approximate changes in consumer surplus due to exogenous shocks to the economy. If these indices are positive (negative) consumer surplus has increased (decreased).

Of course, there are various means of obtaining exact measures of consumer surplus changes from individual expenditure functions. This is widely used when dealing with changes in a price or quantity of a single good but the data requirements are beyond what is typically available in a general equilibrium analysis. In fact, the story is much more complex. The Laspeyres and Paasche indices just described relate to a single consumer. In order to aggregate these measures over all consumers in the economy some rather stringent conditions must be met. In particular, the marginal social utility of income must be the same for all persons. This is not likely to be the case. However, policy questions must be addressed and it is common to add the surplus changes across consumers. Boadway and Bruce provide some rationale for this approach in pages 262-263.
The input data for the CGE model were derived from three sources. The IMPLAN data bases (1982) provided the data necessary to construct the inter-industry flows matrix (the input-output table) and the national accounts data which are required to construct the Social Accounts Matrix (SAM). In addition, the production sectors required capital stock data and labor data. The labor data were included in the IMPLAN data base although adjustments were required to convert these data to full time equivalents (FTEs). The capital stock data were obtained from the Census of Agriculture and the BEA Wealth Data disks. Tax data for household and business taxes were included in the national accounts portions of the IMPLAN data bases.

The test of the accuracy of the CGE model is its ability to reproduce the benchmark data set as the equilibrium of the model. The 1995 direct impacts were scaled to reflect the level of economic activity in the 1982 benchmark data set. These direct impacts were introduced as changes in the components of final demand for the various sectors.

Implementing the Case Studies in the Context of the Act

The Recovery Implementation Program (RIP) (U.S. Department of Interior 1987) for the endangered species set a goal for recovery around 2020 for the Colorado River fishes. The Fish and Wildlife Service Office in SLC estimated recovery by about 2040 for the Virgin River fishes. To fully capture the economic activity changes due to recovery efforts over time, a comparison was made to a baseline economy where no recovery actions are undertaken. The building blocks for the construction of the baseline were the Bureau of Economic Analysis (BEA) state level projections to 2020 (2040 for the Virgin study). These projections were augmented with such local information as was available.

The BEA projections include data on employment by sector and state and were used to project the gross output by sector on the basis of the 1982 or 1990 coefficients and ratios. The employment/output ratios for each sector calculated from the 1989 baseline model were used to generate the sector output levels for the baseline projections. The generated gross output figures were then used to generate the remaining baseline forecast data. This forms the benchmark against which the impacts due the critical habitat effects on economic activity within the respective region were compared. A recovery projection was developed utilizing the direct effects of the resource reallocations as inputs to the models. The impacts associated with listing and the designation of critical habitat were measured as the present value of the differences between the baseline and recovery scenarios.

The Virgin River flows through one the fastest growing regions in the U.S.. Recent and projected population growth in this region is significantly above the state average levels for Utah and Nevada. Recent population projections undertaken by the local public agencies in the St. George, UT area were used to modify the BEA data.
The Act draws a distinction between economic impacts arising from the listing of the endangered species and those arising from the designation of critical habitat. Only the latter are to be considered in the final determination of the critical habitat. After critical habitat is proposed, and an economic analysis is conducted, an exclusion process is conducted in which the economic impacts of designating critical habitat are evaluated. The Act directs the Secretary of the Interior to consider economic and other relevant impacts based upon biological and economic findings in determining whether to exclude proposed areas from the designated critical habitat. In this process, the USFWS may exclude areas from critical habitat designation when the benefits (economic impacts avoided) of such exclusion outweigh the benefits (species preservation) of specifying the such area as part of the critical habitat.

In many cases it is difficult to distinguish between economic impacts attributable to listing a species as threatened or endangered and the economic impacts associated with designating critical habitat for that species. Technically, listing impacts are those associated with protecting individual members of a species from harm, while critical habitat impacts are those associated with protecting the species' habitat from harm. A plan to drain a pond filled with endangered fish, however, would harm both individual species members and their habitat, thus posing the dilemma of how to allocate the impacts of not draining the pond to listing versus critical habitat designation.

Because it is difficult to separate the impacts of listing from the impacts of critical habitat designation, the standard approach is to estimate the combined impacts of both and then judgmentally allocate a proportion of total impacts to each cause. The rationale for the allocation method used in the Colorado River and Virgin River studies revolves around the timing of critical habitat designation relative to listing.

This approach was used in the critical habitat study for the northern spotted owl (Schamberger et al. 1992), and to our knowledge all critical habitat studies that have taken place since then.
In the Colorado River case, there was a substantial lag between listing the fish as endangered and designating critical habitat (ranging from 26 years for the Colorado squawfish and humpback chub to two years for the razorback sucker). As a result, most of the recovery plans for the fish that generate impacts were either already prepared or in the planning stage before critical habitat was designated. For this reason, only 10 percent of all combined impacts associated with resource reallocations for the fish were attributed to critical habitat. In the Virgin River study, however, the relatively close concurrence of listing and critical habitat designation led to assigning 50 percent of combined impacts to each cause.

At the time that each of the four Colorado fishes were listed, the Service reported that their habitat needs were not determinable. Critical habitat designations were undertaken later as the result of a lawsuit filed by environmental groups.

Virgin River and Colorado River I-O Sub-regional and Regional Impacts

For the Virgin study there are two classes of direct impacts that arise from actions taken on behalf of the fishes. The first class concerns impacts that are due to the conversion of water use from agriculture to municipal and industrial uses. Such conversion will occur in the absence of actions taken on behalf of the fish. However, the changes in the river flows necessary for recovery of the fish will change the timing of the conversion of the agriculture water. Sets of agriculture templates were developed and used to calculate the output changes that would result from changes in the amount of irrigation water allocated to agriculture. These output changes were entered directly into the I-O model in the manner of mixed exogenous-endogenous models (or supply-side and demand-side models). Thus, the quantity of output for each of the affected agriculture sectors was changed directly to reflect the particular scenario being investigated.

The second class of direct impacts arise from changes in the demands for goods and services stemming from actions taken on behalf of the fishes. The changes in the river flows required for the fish result in a change in the timing of the municipal and industrial water delivery projects that have been planned as an integral part of the region's projected growth. Moving these projects up in time increases the unit (acre-foot) cost of the water and moving the projects back in time reduces the unit cost of the water.

The changes in the cost of the water were introduced in the form of a change in final demand that is apportioned across all sectors of the economy. Thus, an increase in the cost of water to users will result in increased expenditures on water. Under the fixed budget assumption of the small open economy, the increased expenditure on water must crowd out other expenditures. An extreme assumption is that the demand for water is infinitely inelastic. That is, the quantity demanded does not fall as the price rises. In this case, the increase in the cost of water delivery results in an increase in the level of expenditure on water of a per unit cost increase times the original quantity of water delivered. [This assumption ensures that the water projects recover all costs including those associated with accelerating the projects in time.] In effect, all of the cost increase for each water delivery project is absorbed as an increase in the expenditures for water by the users in the area. Thus, crowding out is complete, the expenditure on all other goods in the economy falls by the exact amount of the increase in the level of expenditure on water. This is the assumption that underlies the computation of the direct impacts. For the purposes of the I-O analysis, the expenditure change was prorated across the sectors in proportion to each sector's share of total final demand.

In the Virgin River study the major impacts were projected to occur in the agriculture sectors as land is retired from agricultural production and the construction sector through increased costs due to water conservation. All sectors experience some impacts due to the increased cost of water as delivery projects are modified to meet the needs of the endangered fishes.

For the Virgin study two impact scenarios are developed. Table 2 presents the values for each scenario. The first scenario, the construction scenario (ST), meets the increased instream water demand on behalf of the fishes by bringing proposed structural water delivery projects on-line earlier than previously planned, and accelerating ongoing conversion from agricultural to municipal and industrial uses. The second scenario, the conservation scenario (CO), in addition to some accelerated construction of water delivery projects, assumes that increased water demands are partially met by reducing per-capita water consumption through a series of water conservation measures. These measures include more efficient appliances and plumbing as well as xeriscaping.

Table 2
Regional Direct Impacts in Virgin River for Critical Habitat (1990$ Millions)

Year Sector
LivestockLivestock FeedFruits & VegetablesImpacts
  • Critical Habitats are 50% of total direct impacts.
  • ST signifies the Construction Scenario
  • CO signifies the Conservation Scenario

Table 3 presents the Virgin River critical habitat direct and indirect impacts for sub-regional and the region. The sub-regional impacts are determined for two counties: Clark County, Nevada and Washington County, Utah. The impacts in Clark County include those to the small section of Mohave County, Arizona, that is included in the study region. As no direct impacts accrue to Iron County, Utah, no separate county-level impacts are calculated. Under the construction scenario, the net present value (NPV) of output losses in Clark County is -$10.6 million, a deviation of -0.00001 percent from the baseline. For Washington county, impacts under the construction scenario are slightly larger, but still small. The NPV of lost output is -$47.5 million, a reduction in economic activity by -0.0016 percent from the baseline.

Table 3
Virgin River Direct and Indirect Regional Impacts of Critical Habitat Designation

 Output Changes
NPV @ 3%
(1990$ Millions)
Percentage Deviations from Baseline
Sub-regional Results
Construction Scenario1
Washington County-47.5-0.0016
Clark County-10.6-0.00001
Conservation Scenario2
Washington County-13.7-0.00046
Regional Results
Construction Scenario-59.8-0.0001
Conservation Scenario-20.9-0.0000
  1. The Construction Scenario (ST) for the Virgin Study meets the increased needs on behalf of the endangered fishes by accelerating the construction of reservoirs and accelerated retirement of agricultural land.
  2. The Conservation Scenario (CO) for the Virgin Study meets the increased water demands primarily by reducing per capita consumption through investment in water conservation measures, e.g., low-flow shower heads, xeriscaping, etc. for residential and commercial buildings.

Under the conservation scenario, no direct impacts accrue to Clark County. Thus, only impacts in Washington- County are presented. Implementing the conservation scenario will reduce the N.V. of output by -$13.7 million, a change of less than -0.00046 percent from the baseline. In terms of output, impacts are actually positive after the year 2025, when increased construction costs for more efficient buildings are offset by reduced expenditures on water. The designation of critical habitat will reduce the number of employed on average by four.

For the Virgin study, the regional impacts due to the designation of critical habitat is projected to decrease output by an N.V. of -$59.8 million for the construction scenario, a deviation of -0.0001 percent from the baseline. For the conservation scenario, the N.V. of lost output is -$20.9 million, a deviation from the baseline by less than -0.0001 percent.

Estimates of the direct economic impacts of critical habitat designations for the four Colorado River endangered fishes are presented in Table 4 (A, B, and C). These impact estimates reflect annual output changes in directly-affected industrial sectors in the various states without considering indirect effects on production in other sectors of the state economies. The impacts are a direct reflection of the resource allocations described in Section 3.

Critical habitat designations in the upper basin (Table 4-A) would tend to shift irrigation water use to lower basin states relative to baseline conditions. As a result, Colorado and Wyoming would experience reduced output in the livestock feed and other crop sectors totaling about -$2 million annually by the year 2020. New Mexico would suffer a -$10 million annual output decline in those sectors by the year 2020. Those declines would be more than offset in the Lower Basin (Table 4-B), however, by a $13 million increase in California's agricultural output by 2020.

Table 4-A
Colorado Study Direct Economic Impacts
Critical Habitat Designation for the Upper Basin (1991$ Millions)

Livestock Feed-0.345-0.690-1.015-1.072-1.293-1.652
Other Crops-0.063-0.126-0.174-0.223-0.272-0.320
Electric Power-0.256-0.436-0.949-0.501-0.880-0.033
Non-petrol Mining0.1530.2320.3640.1620.1880.166
Oil and Gas Mining0.2030.0200.0560.1210.5310.077
Combined Mfg.0.5760.5760.5760.5760.5760.576
Total Direct Impacts0.843-0.077-0.795-0.590-0.803-0.839
New Mexico
Livestock Feed0.000-0.324-1.186-1.909-2.697-3.312
Other Crops0.000-0.657-2.402-3.875-5.476-6.725
Electric Power-0.277-0.556-0.595-0.594-0.593-0.598
Total Direct Impacts-0.277-1.537-4.183-6.378-8.766-10.635
Livestock Feed0.000-0.017-0.038-0.076-0.079-0.083
Electric Power-0.608-0.600-0.62-0.648-0.688-0.717
Non-petrol Mining0.1090.1590.1650.147-0.1480.159
Total Direct Impacts-0.788-0.747-0.782-0.866-0.908-0.930
Livestock Feed0.000-0.038-0.038-0.038-0.038-0.038
Electric Power-0.050-0.050-0.05-0.050-0.050-0.050
Non-petrol Mining0.0000.0000.0050.0010.0120.009
Total Direct Impacts-0.05-0.099-0.094-0.098-0.087-0.090

Most of the Colorado River basin's states would suffer declining output (relative to baseline) with respect to electric power production and the recreation and tourism sectors of their economies. These results stem from reoperating federal reservoirs in the basin to provide flows for endangered fish at the expense of recreation and hydropower production. Colorado, however, is expected to see increased construction and manufacturing activity relative to baseline because it is the likely site for adding thermal power production capacity to replace lost hydropower generation.

Table 4-B
Colorado Study Direct Economic Impacts
Critical Habitat Designation For the Lower Basin (1991$ Millions)

Electric Power-0.235-0.253-0.152-0.195-0.403-0.326
Total Direct Impacts-0.235-0.281-0.217-0.293-0.533-0.489
Other Crops0.5251.9084.3745.8178.38710.935
Livestock Feed0.1000.3620.8271.1001.5862.054
Total Direct Impacts0.6252.2705.2016.9179.97312.989
Electric Power-0.114-0.114-0.114-0.114-0.114-0.114
Local Amusements1.8631.8631.8631.8631.8631.860
Total Direct Impacts1.7491.7211.6841.6511.6191.587

Table 4-C shows that the direct economic impacts of critical habitat designation roughly offset each other in magnitude for all seven states combined. There are significant distributional effects, however, with California experiencing increased economic output relative to baseline by the year 2020 while most of the other states show declines.

Table 4-C
Colorado Study Direct Economic Impacts
for Critical Habitat Designation for the Colorado River Basin (1991$ Millions)

Colorado River Basin
Livestock Feed-0.205-0.882-1.680-2.217-3.022-3.720
Other Crops0.5520.9671.4381.3722.3363.530
Electric Power-1.752-1.806-2.372-1.961-2.546-1.465
Non-petrol Mining0.2770.3980.5610.4330.2620.457
Oil and Gas Mining0.1280.0930.2950.2130.6880.143
Combined Mfg.0.7530.7680.8070.8070.8070.807
Local Amusements1.8631.8631.8631.8631.8631.863
Total Direct Impacts2.1611.8331.3470.9190.7711.972

The overall direct and indirect sectoral impacts of the critical habitat designations are presented in Table 5. These impacts include the direct and indirect effects of critical habitat as estimated from an I-O model for the seven-state basin. As can be seen the impacts are both positive and negative across sectors reflecting the reallocation process of resources that is required for the recovery of the endangered fishes. Thus, one outcome of the analyses is that there are sectoral distributional consequences. The largest negative impacts were projected for the electric power production sector and the livestock feed sector. The electric power sector must adjust to the changes in the flow regimes of the river system and the livestock feed sector represents a low value of water use so these uses are the first to be retired.

Table 5
Direct and Indirect Impacts by Economic Sector:
Critical Habitat - Colorado River Study

SectorOutput Impacts
(NVP 3%)
(1991$ Millions)
Other Crops62.755
Livestock Feed -66.913
Miscellaneous Agriculture3.853
Non-Petrol Mining19.360
Petroleum and Natural Gas5.766
Food Products-0.245
Wood Products5.102
Petroleum and Coal Products-16.760
Other Manufacturing52.088
Trans., Comm., & Util.-8.505
Recreation Services-16.506
Electric Power Products-113.447
Wholesale & Retail1.819
Hhold & Business Svcs.13.984
Local Amusements136.538
Health, Ed. & Soc. Svcs.0.617
Government Production0.173

Table 6 presents the direct and indirect sub-regional and regional impacts for the Colorado study. This gives an additional perspective on the distributional consequences of the resource reallocation. For the Upper Basin states, the total output change is negative. However, for the Lower Basin states the change is negative for Arizona but positive for Nevada and California. Although regional impacts are positive, impacts differ considerably across the different states within the study region. Among the seven states, the largest positive impacts accrue to California, resulting in a increase in output of 0.0013 percent over the baseline. This corresponds to an increase of $335.0 million. Impacts to New Mexico result in a reduction of output by -0.0280 percent, equivalent to lost output of -$245.5 million. In either case, changes over the baseline are still very small. The impacts of the other states lie between these two values.

The regional impact and the sum for the individual states will not match exactly since the state impacts were computer from state-level I-O models while the region was modeled as a complete entity as well. The differences are due to leakages at the state level that are captured by the larger region.

Table 6
Direct and Indirect Spatial Distribution of Critical Habitat Impacts for the Colorado Study

N.V. @ 3%
(1991$ Millions)
Deviations from Baseline
Upper Basin
New Mexico-245.5-0.0280
Lower Basin
Colorado River Basin

For the Colorado study, impacts at the regional levels are positive. At a 3 percent discount rate, the N.V. of the listing plus critical habitat regional impacts for the study period are $ 129.4 million (1991$). [All impacts are computed in constant dollars. The discount is a real rate and the basis for a 3% level is that this is quite close to the long run rate of growth of the economy.] While positive, these impacts are very small compared to the overall economic activity, consisting of no more than a 0.0003 percent increase over the baseline.

Throughout the following discussion it will be apparent that the impacts are extremely small. The percent deviations from the baseline are reported to illustrate this point. Neither the data nor the models are sufficiently precise to allow us to state that these percentage values are statistically different form zero.
In viewing the impacts from both studies, two points should be emphasized. In both studies, the impacts of actions taken on behalf of the endangered fish are extremely small. The designation of critical habitat is not expected to affect economic activity in the study regions at any significant level. However, as the Colorado study has shown, impacts can be unevenly distributed within the study regions. Different areas may be more dependent, both directly and indirectly, on the affected resources. Nevertheless, even when differences in state impacts are accounted for, impacts are quite small.

Colorado Study National Efficiency Effects

The CGE model utilized incorporates explicit accounting of the exchanges between the region and the remainder of the country (and world) through the SOE assumption. The CGE model treats the Colorado River Basin region as an SOE. Through the external trade sector, the implications for the national economy are accounted for in the results. Thus, the impacts are effectively measures of net national efficiency effects of the resource reallocation.

The CGE model reports changes in levels of output by sector, earnings, employment, gross regional product (GRP) and government revenues. These measures are reported as deviations from the baseline. In this analysis, labor supply is free to grow within the region. Economic links with the rest of the U.S. (and the world) take place through imports and exports of goods and services, foreign borrowing (investment), and employment payments from outside. The Armington and CET functions described earlier account for the external linkages that take place through the goods and services markets.

It is important to note that although the results are reported for the regional economy that these incorporate national impacts through imports and exports and labor mobility.
To evaluate the national economic consequences of critical habitat designation the analysis must be conducted in such a manner that the following assumptions are violated to a minimum degree. First, to use market prices to value the resources displaced by the impact requires that the market for the good in question be free of distortions so that the prices truly reflect the opportunity costs of the resources used to produce it. Second, all other markets in the economy must be operating completely free of distortions. That is, the price paid by consumers must be identical to the cost of producing the good in all markets. Third, the entire national impact must be identical with the regional level impact.

An alternative to this assumption is that the economic consequences of the listing and proposed critical habitat designation are confined to the markets in which the direct impacts occur. That is, there are no indirect effects that are felt in related markets.
The analyst must still make judgements concerning the extent to which regional impacts are, in fact, national impacts or whether they are pure transfers of resources from elsewhere in the country. This is particularly important in the case of direct impacts relating to large scale investment in new facilities. If the construction and capital equipment sectors are operating at capacity, then the newly installed thermal capacity within the Colorado River Basin region will displace capacity expansion activities elsewhere in the U.S. economy. If the value of the displaced activities is very close to the value of the thermal generation plants and since these changes occur at the margin, the net national impact of the thermal capacity addition would have a zero value. On the other hand, if there is sufficient excess capacity in the construction and capital equipment sectors then the investment in expansion of the thermal capacity is a pure addition to the national economy.

The hydropower capacity that is lost due to the changes in the hydrographs in the with-fish scenario is a sunk cost. The owners of the resources in this sector will experience a loss but not the national economy.
Another sector for which the possibility of offsetting effects outside the region is important is the recreation services sector. If recreation opportunities are reduced within the Colorado River Basin region it may be that there are substitute activities that will be undertaken outside the region. This is, again, an excess capacity argument. The extent to which recreation substitutes are available is debatable. We present here an analysis whereby the recreation resources in the Basin are assumed to be unique and the loss of these recreation opportunities cannot be replaced within the U.S. economy. The results are only slightly different if this assumption does not hold.

To select the most likely scenario for the future would involve detailed projections for these sectors and such projections are not available. All additions to thermal generation capacity require the withdrawal of resources from elsewhere. The net result is a direct impact of zero for the construction and combined manufacturing sectors. The true situation most likely lies in between these polar cases, by presenting these extremes, the bounds on the actual outcome are provided. The solution is to construct a set of scenarios which provide boundary estimates of the overall economic effects.

Two polar scenarios related to the direct regional impacts projected for 1995 regarding thermal facilities are reported.

Scenario A:
There exists sufficient underutilized capacity in the construction and capital equipment sectors (within the basin or elsewhere in the national economy) that all additions to thermal electric capacity are a net positive addition to the level of national economic activity. The recreation resources within the basin are unique and the loss of these recreation opportunities cannot be replaced within the U.S. economy.

Scenario B:
There is no underutilized capacity in the construction and capital equipment sectors (within the basin or elsewhere in the national economy) and all additions to the thermal electric capacity within the basin are constructed with resources that must be displaced from elsewhere in the national economy. Thus, there is no net positive impact from this expenditure on thermal expansion. The recreation resources within the basin are unique and the loss of these recreation opportunities cannot be replaced within the U.S. economy.

The aggregate total percent changes from the baseline are reported in Table 7. For Scenario A, regional gross product is projected to increase by 0.0009 percent as a result of listing and the proposed critical habitat. Since the national effects are accounted for in the CGE model, this would represent an increase in the national gross product. Employment is projected to increase by 0.0015 percent, earnings by 0.0018 percent, and government revenues by 0.0007 percent. In Scenario B, the additions to the thermal generation capacity are treated as a transfer from the rest of the national economy; expenditures are the result of a pure shift of resources from outside the region. Gross regional product is projected to decline from the without-fish baseline value by -0.0008 percent. Employment is projected to decline by -0.0010 percent, earnings by -0.0002 percent and government revenue by -0.0016 percent.

Table 7
CGE Results as Percent Deviations from a Baseline Economy: The Case of Thermal Generation
Scenarios A and B
(Critical Habitat)

Scenario AScenario B
Real Gross Regional Product0.0009%-0.0008%
Total Government Revenues0.0007%-0.0016%

Finally, under Scenario A, aggregate consumer surplus increases by $1.95 million. Producer surplus is projected to decline by $0.41 million. Under Scenario B, aggregate consumer surplus decreases by -$2.59 million and producer surplus decreases by $0.50 million. The total surplus changes for Scenario A and B respectively are $1.55 million and -$3.09 million. Overall national efficiency impacts depend on whether the expansion in thermal generating capacity is a net addition to the level of economic activity or is a simple transfer from other sectors in the national economy.

Exclusion Process and Conclusion

The applied general equilibrium approach forces recognition of potential offsetting effects as resources are reallocated to preserve critical habitat for endangered species. Thus, in the Colorado River study, the flow changes required for the endangered fishes decreases agricultural activity in the upper basin of the Colorado River but increases this activity in the lower basin. A partial equilibrium analysis ignores such effects. Further, reallocating water uses causes some activities to decline while others increase. The partial equilibrium analysis omits such effects. The exclusion process utilizing the economic analyses for both the Colorado and Virgin studies resulted in all of the proposed critical habitat being designated. No areas were excluded for economic reasons.

The economic impacts associated with critical habitat designation arise from the required resource reallocation. The impacts are typically regional, rather than local, and thus necessitate regional economic modeling. The appropriate modeling framework must capture both the aggregate and distributional consequences resulting from resource reallocation caused by the designation of critical habitat. Applied general equilibrium models, either input-output (I-O) models or computable general equilibrium (CGE) models, are suitable for these purposes. Partial equilibrium models are inappropriate as they assume that resources not employed in the sectors constrained by the critical habitat will simply cease to exist instead of being reallocated within the regional economy. By the same token, focus on local impacts will obscure potentially offsetting (or magnified) impacts at a regional level. Applied general equilibrium models circumvent this problem by explicitly incorporating the resource reallocation within the regional economy.

The method of analyzing the economic impacts of designating critical habitat and the exclusion process is more than of academic interest. To date, the only USFWS sponsored studies we are aware of which analyze critical habitat impacts in a general equilibrium framework are those presented in this paper. This type of analysis is essential for the exclusion process. A critical habitat exclusion process requires that the analysts promulgate some criteria deciding whether or not to make an exclusion. For both studies, the recommended threshold for exclusion was one percent deviation from the baseline projection of aggregate economic activity (Department of the Interior 1994; Brookshire, McKee, and Schmidt 1995). The geographic scope ofthe study and the breadth of the economic impacts required that the criterion be based on aggregate economic activity. In the spotted owl study, the threshold was defined in terms of change in employment in the logging industry at the county level.

The consequences of adopting a narrow region for analysis and an essentially partial equilibrium framework are most apparent in the case of the critical habitat assessment for the northern spotted owl. In that case, the exclusion process resulted in approximately 40 percent of the critical habitat initially proposed being excluded. It is by no means certain that the outcome would have been different had the northern spotted owl study utilized an applied general equilibrium model. Perhaps, however, less habitat would have been lost as a result of the exclusion process.


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