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Fish & Wildlife Economic Values

Changing Values/Changing Times

September, 2003
Economic Valuation Studies of Fish and Wildlife Resources in Montana
John W. Duffield, University of Montana


This chapter provides an overview and interpretation of nonmarket valuation studies of fish and wildlife resources that have been completed in Montana over the last four decades. The focus here is on three issues. The first issue is how nonmarket valuation has been utilized in fish and wildlife policy decisions. Secondly, the results of these studies are examined with regard to how values vary across locations, users (resident/nonresident, types of users, activities) and time. Finally research priorities are discussed that would document trends and identify links between nonmarket fish and wildlife values and demographic and socioeconomic trends.

A primary finding of this review is that the literature on the economics of Montana fish and wildlife and related natural environments is surprisingly extensive and varied. This is probably because Montana is blessed with some of the most important, unique, and largely intact, land, water, and wildlife resources in North America. These include a corner of the world’s first national park (Yellowstone, established in 1872), perhaps the country’s premier mountain landscape park (Glacier), and some of the best fishing and hunting on the continent. These resources attract recreationists, who, in turn, may be the subject of economic studies. It was discovered in the course of this review that several of the very first economic studies of the demand for outdoor recreation included Montana sites (L.C. Merriam’s study of the Bob Marshall Wilderness, published in 1963, and Clawson and Knetsch’s (1966) study of Glacier Park visitation). Studies have since been undertaken relating to elk, deer, and antelope hunting, stream and lake fishing, waterfowl and upland game bird hunting, wildlife viewing, wolf recovery in Yellowstone NP, grizzly bear recovery, instream flow values, and numerous other topics, as detailed below. While many of these are academic or agency-funded research efforts on a rather modest scale, Montana has also been a focus of one of the most extensive (and expensive) studies of the value of fishing ever conducted. The latter was in the context of a superfund case (State of Montana v. Atlantic Richfield Company [1] ) involving historic metals mining and smelting at Butte and Anaconda. These operations in the headwaters of the Clark Fork River impacted the downstream fisheries, and an empirical issue in the case was the economic value to be placed on the foregone use of this fishery by Montana anglers. Both the State of Montana and the Atlantic Richfield Company developed complex economic demand models for this fishery, and involved a number of leading natural resource economists [2] (Desvousges and Waters (1996); Hanemann (1995); McFadden (1995, 1996), Morey et al. 1995, and Morey et al. (2002)).

A basic motivation for identifying the values associated with fish and wildlife resources is that often management and policy decisions are trading off fish and wildlife uses against market commodities. Litigation to recover for damages to fish and wildlife resources is an obvious example, as already noted. However, it is not uncommon for agencies or other entities to be faced with needing to know the value of noncommercial natural resources. For example, if an agency is considering the purchase of a fishing access site (the price of which will be based on the market for river or lake frontage), it would be useful to know what value anglers will derive from use of such a site before deciding to invest. Similarly if an agency or conservation group is considering purchasing land for elk (or other species) winter range, it is useful to know if the wildlife values associated with the site exceed the value of the property in other, commercial uses. The methods for estimating values associated with fish and wildlife resources are called "nonmarket valuation" methods, since most of these resources are not traded in established markets. While in many countries (such as Norway, Ireland, etc) the right to fish and hunt are privately owned, the historic evolution of property rights in fish and wildlife in the United States has been toward state or federal ownership. There are good economic reasons in many cases for this, having to do with the migratory nature of wildlife and the "public good" uses of many resources. However, there are some uses, such as hunting and fishing for resident wildlife species, where markets could be used. At present, fee fishing and fee hunting occurs in only a limited way in Montana, compared to some other states such as Texas.

The studies discussed here rely on several different general nonmarket valuation methods, including some based on observed behavior (such as the travel cost model) and others based on respondent stated preferences (such as in contingent valuation studies). It is beyond the scope of this paper to discuss these methods in detail; Mitchell and Carson (1989) and Freeman (2003) provide good introductions. Which methods can be applied depends on the type of use at issue. One common distinction is between direct use and passive use. The former includes all types of direct on-site uses such as fishing, hunting, gathering and use of genetic resource. Within the direct use category, uses such as fishing and hunting are sometimes termed "consumptive use" as distinct from wildlife viewing which is a "nonconsumptive use". Passive use refers to the value individuals may place on just knowing that a species exists and is viable (existence value) or that future generations will be able to also enjoy the use of the given species (bequest value) (Krutilla 1967). For example, the fact that U.S. residents will contribute money to the World Wildlife Fund for the protection of pandas in China or penguins in Antarctica (which they will almost certainly never themselves lay eyes on) is evidence of passive use values.

Both travel cost models and contingent valuation models can be used to estimate direct use values, such as for hunting and fishing. There are a large number of such studies that have been reported in the economics literature. A recent literature review by Rosenberger and Loomis (2001) identified 163 separate empirical research studies of outdoor recreation use values in the U.S. and Canada for the period 1967 to 1998. The review identified 760 specific value estimates covering 21 different kinds of recreational activity. Boyle et al. (1998) and Markowski et al. (2001) provide a review and database focused on U.S. sport fishing studies conducted from 1975-1996. A total of 109 such nonmarket fishery valuation studies were identified. Loomis and White (1996) review 18 studies of the economic benefits (primarily passive use value) of rare and endangered species.

Fish and wildlife resource valuation is a type of microeconomic analysis that relies in part on identifying the spatial extent of "the market" for use and may involve both supply and demand analysis. The discussion here is limited to these types of microeconomic studies, which are generally used in a benefit-cost framework. Another type of economic framework often used to inform policy decisions is regional economic analysis or economic impact analysis, where the economic criteria is jobs and income (as distinct from net economic benefits or costs). These latter types of studies may relate to fish and wildlife policy decisions, but are not included in the discussion here.

Fish and Wildlife as Economic Resources

For many people, the idea that economics could have anything to do with fish and wildlife resources is a foreign one. The opening line of Norman Maclean’s A River Runs Through It is"In our family, there was no clear line between religion and fly fishing." Nonetheless, empirical studies of fish and wildlife-related recreation and passive use indicate behavior consistent with economic principles. Most of the studies summarized here are basically models of economic demand. The underlying economic theory is relative terse: individuals make choices based on their preferences so as to maximize their well being subject to budget (income) constraints and given prices. From this simple model economists derive the "law of demand" (as prices go up, quantity demanded goes down, other things equal). The only other testable proposition is that for "normal" goods, an increase in income implies an increase in quantity demanded. Applying the methods noted above (travel cost model and contingent valuation) amounts to estimating the demand function (or relationship of price, income and quantity demand) for some resource, such as a day of fishing on the Madison River. Given the demand function, one can then also identify the average value individuals place on a given resource. In the following sections of this paper, for brevity, only this average value (usually referred to as the net economic benefit) is reported [3]. But underlying all of these studies are detailed models of economic demand.

One example of such a model, presented here to illustrate the general consistency of these estimates with economic theory, is the demand for wolf viewing and existence value in Yellowstone National Park. Prior to the reintroduction of wolves in the park in January, 1995, and as part of the federal environmental planning process, surveys of visitors and economic studies were conducted. One finding from these studies is that park visitors have well-defined preferences for wildlife viewing. This is a fundamental pre-requisite for the existence of a definable demand function for these activities. Table 1 shows data from a 1990 survey (Duffield 1992) that asked park visitors to indicate the top three species they would like to see on a visit to Yellowstone NP from a list of species present or potentially present in the park. The most preferred species to view was the grizzly bear, with 52 percent of regional (ID, MT, WY) residents listing it as one of their top three to view and 61 percent of out-of-region residents (rest of the U.S. and foreign visitors). It is interesting to note how similar the rankings of the two sub-samples are. Table 2 shows a comparison over time that indicates that there is fair consistency in preferences to view wildlife between 1990 and 1999, with the exception that wolves (now present in the park) move up from 9 th to 2 nd overall and black bear and elk drop.

Table 3 shows the statistical results defining the economic demand function for wolf viewing and existence in Yellowstone NP based on the 1990 survey data. The explanatory variables include a price-like term (bid amount), gross family income, and various measures of individual preference including measures of the desire to see wolves, general environmental attitudes, measures of the preferences for viewing wolf prey species (deer, elk, and moose) and an indicator of whether the respondent hunts big game. All of these variables are statistically significant, and from an economic standpoint, the signs of the variables are all consistent with economic theory. For example, the negative sign on the price term indicates consistency with the law of demand and the positive sign on income indicates that respondents with higher income would be more likely to value wolf recovery, other things equal. Individuals who want to see wolves are more likely to value wolf recovery, but individuals who prefer to see the prey species or who hunt big game are less likely to value wolf recovery, as one would expect.

Because this model has statistically significant and theoretically consistent parameters, and provides a good overall fit to the data, one can say that this model provides a reasonable behavioral model of the underlying economic demand for wolf recovery in Yellowstone NP.

Economic demand models can be used not only to estimate net economic benefits (such as the average value of a day of fishing) but also to forecast changes in demand in response to changes in the underlying explanatory variables, such as income or attitudes and preferences. In the remainder of this paper, only the summary average value results from the estimated models are described.

Montana Nonmarket Studies: Policy and Research

Table 4 provides lists 40 economic studies that have estimated nonmarket values for fish and wildlife resources in Montana. The table lists for each study the geographic location, the date of the study, the object or type of use valued, the valuation method, the net economic value estimates, the policy or research application, and a reference citation and/or physical location for the study report. These studies have in common that they all are based on original survey data that was collected specifically for the given study. Typically these involved mail or phone surveys of random samples of user populations (for example, Montana licensed anglers or Montana licensed hunters or Montana households).

Policy studies

About half of these studies were motivated by specific Montana public policy issues, while the remainder were either baseline or methodological research studies or in support of litigation. Almost all of the studies were funded by public agencies, including Montana state agencies (Fish, Wildlife and Parks; Department of Natural Resources and Conservation; State Lands), and a number of federal agencies (National Park Service, U.S. Forest Service, and the U.S. Environmental Protection Agency). Policy issues represented in this set of studies include the following:

  1. water resource allocation (value of instream flows for recreation and hydro-electricity compared to irrigation on the Upper Missouri; instream flow values on the Bitterroot and Big Hole Rivers; comparison of recreational values versus hydroelectric development at Kootenai Falls);
  2. land allocation (purchase of wildlife habitat);
  3. wildlife management (benefits and costs of wolf reintroduction in Yellowstone N.P.; grizzly reintroduction in the Bitterroots);
  4. recreation management (floater versus bank angler values on Rock Creek; winter use (snowmobile) management in Yellowstone NP); and
  5. pricing (state lands recreation fee permit pricing study).

In general, all of the policy studies are cases where decision makers knew the market values that were at stake (price of land, electricity, irrigated crops, predation on livestock, etc.) but needed to know the nonmarket values for fish and wildlife uses such as the value of a day of fishing, the value of a day of hunting, passive use and wildlife viewing values for wolves or grizzly bear, or the recreational value of an additional acre foot of instream flow, and so on. A general finding is that there are cases where the highest value that can society can realize from a given resource is in its nonmarket fish and wildlife-related use. For example, based on the study of recreation values of instream flows in the Upper Missouri River Basin (Duffield, Patterson, Neher and Allen 1990), the Montana DNRC EIS on water reservation allocations for this basin found that of 219 proposed irrigation project withdrawals, a total of 159 would generate economic values less than the loss in recreation values. Another example is the decision on the proposed Kootenai Falls hydroelectric project in the early 1980's. This is one of the very few cases where the Federal Energy Regulatory Commission has found that for a major proposed hydroelectric development, the value of the electricity that would be generated was not sufficient to outweigh the loss of recreational and aesthetic values for the general public, and spiritual values for Native Americans. Unless nonmarket valuation studies had been conducted in these cases, it is likely that the proposed developments would have gone forward and society would have, as a whole, been worse off for the loss of the more valuable fish and wildlife-related uses.

Another interesting finding from the policy studies is that the benefit-cost results can be sensitive to the defined extent of the market. For example, in the benefit-cost analysis of wolf recovery in Yellowstone NP (Duffield and Neher 1996), it was found that residents of the three-state (ID, MT, WY) region were closely divided over the issue, with a small majority favoring wolf reintroduction. As a result, the benefits of recovery from the standpoint of the region were quite small (Table 5) and much less than the estimated costs of the recovery effort. By contrast, viewing Yellowstone as a national resource, out-of-region residents favored recovery by 2:1 (and greatly outnumber regional residents). Accordingly, from a national perspective the estimated benefits associated with wolf recovery were quite large and about ten times larger than estimated costs (Table 6).

Research studies

Interestingly, from an historical standpoint, the earliest nonmarket valuation studies undertaken in Montana were among the first, if not the very first, such studies undertaken anywhere. Clawson and Knetsch (1966) in their pioneering text on the travel cost method, include a model for Glacier National Park among the handful of empirical studies they report. [4] An even earlier (1963) nonmarket study was conducted by L.C. Merriam, Jr. as part of his doctoral dissertation at Oregon State University. Merriam examined the benefits and costs of alternative management strategies (timber, recreation, etc.) for the Bob Marshall Wilderness. Merriam’s research support was from the U.S. Forest Service and the Wildlands Research Center at the University of California. As a condition of his research support, he was requested to conduct field interviews of wilderness vacationists during July and August 1960, using a questionnaire designed by the center. Merriam completed 35 interviews, including 26 responses to the question: " If it were necessary to charge a yearly license fee in order to preserve wilderness areas for wilderness use, what would be the maximum price you would be willing to pay"?This form of " willingness to pay" question has become known as an "open-ended" contingent valuation question. Merriam’s application, published in a Montana Forest and Conservation Experiment Station bulletin in 1963, was completed in the same year as a dissertation on the benefits of outdoor recreation in Baxter State Park in Maine (Davis (1963)). The latter is usually credited as being the first use of contingent valuation methods (e.g. Mitchell and Carson (1989) at p. 9). Other early Montana research studies include a pioneering study by Cichetti and Smith (1973, 1976a, 1976b) in which an initial sample of 600 users of the Spanish Peaks Primitive Area were asked how much they would be willing to pay to reduce congestion in the area from other hikers. [5] Sutherland (1982) undertook a study of the recreation and preservation value of the Flathead River and Lake system, based on an earlier published model for the Pacific Northwest (Sutherland (1981)). Travel cost model estimates of the value for swimming, fishing, and camping were $5 to $6 per trip and $12 per trip for boating. Sutherland also estimated the "preservation" value of the system at $64 per household based on a sample of residents of four Montana cities.

In the early 1980's baseline studies of hunting and fishing uses in Montana, including willingness-to-pay estimates per trip and per day were undertaken by Montana Fish, Wildlife and Parks (see Table 4). These studies estimated baseline values and expenditures that could be used by the agency in their day-to-day policy and management decisions. The studies were statewide and included estimates for per trip and per day values of cold-water stream and lake fishing, and per day and per trip values for hunting for elk, deer, antelope, waterfowl, moose, bighorn sheep and mountain goats. Both travel cost and contingent valuation methods were used. To date, only one of these original studies has been (in part) replicated: contingent valuation studies of Montana elk hunting were undertaken in both 1987 and 1998. Another mid-1980's study is a marginal cost pricing analysis by Daniels (1987) that used a zonal travel cost model for the demand side of the problem. Estimated equilibrium prices were $15 to $19 per recreation visitor day for several campgrounds on the Lolo National Forest near Seeley Lake, MT More recent research studies include fishery valuation studies in the Greater Yellowstone Area (headwaters of the Missouri, Yellowstone and Snake Rivers)(Kerkvliet and Nowell (1999, 2000); Kerkvliet, Nowell and Lowe (2002)), and nearby Henry’s Fork fishery in Idaho (Nowell and Kerkvliet (2000)). In the 1999 study (based on a 1993 data set) estimated per day values for the GYA based on travel cost models ranged from $1100 to $190 depending on trip itinerary (as discussed below). Values for the Henry’s Fork fishery were estimated to be about $2,400 per trip and $160 per day.

Other nonmarket valuation research summarized in Table 4 includes methodological studies. One such study was funded by the U.S. Forest Service and focused on direct recreational use values of instream flow on the Big Hole and Bitterroot Rivers (three publications are listed for this study) and one by the U.S. Environmental Protection Agency to develop general methods for estimating passive use values. (The application for the latter was valuation of two endangered fish species: arctic grayling and Yellowstone cutthroat trout.) A third methodological study examined statistical issues in the design of contingent valuation studies.


Studies related to natural resource damage assessment for the Clark Fork superfund site were mentioned in the introduction. In the context of this case both the State of Montana and ARCO supported the development of random utility travel cost models to value the foregone use of recreational fisheries that had been impacted by the Butte-Anaconda mining and smelting works, as previously noted. Both studies derived the marginal value of trips that would be substituted from nearby sites at around $17 per trip [6] for Montana resident anglers, but the two research efforts differed considerably in terms of aggregate values associated with a recovered Clark Fork River fishery (Desvousges and Waters (1996); Morey et al. (1995)). This difference was largely due to a four-fold difference in the number of predicted additional trips to a recovered Clark Fork River Fishery, and to the different approaches taken with respect to nonresident anglers. The ARCO analysis chose to not value any losses to nonresident anglers, while the State of Montana included these losses in their estimates (at about $201 average WTP per expected additional trip to the impacted sites). As a result of these differences, the aggregate annual estimates of foregone recreational use differed by an order of magnitude: $133,000 versus $1,376,000. This litigation also motivated a contingent valuation application to estimate the economic damages to fishery, groundwater resources, and upland resources (Schulze and Rowe (1995); Bishop (1995); Hausman (1995)) and an avoided cost analysis for groundwater resources (Desvousges 1995). [7] .

Variation in Values Over Location, User Type, and Time

The studies summarized in Table 4 were not specifically designed to provide insights into how values toward fish and wildlife have changed over time. Most of the studies are one-time efforts motivated by specific policy or research questions. However, it is anticipated that follow-up studies may occur in the future for the baseline studies initiated by Montana Fish, Wildlife and Parks in the 1980's. [8] To date, as mentioned, this has only been done for elk hunting. This section provides a summary of what can be learned from these studies in terms of how values vary over location, user type and time.

Variation across location

The baseline studies sponsored by Montana Fish, Wildlife and Parks in the mid-1980's provide estimates of values per trip and per day for some specific fishing sites and by some big game hunt areas. The estimates for values per trip for fishing (Duffield and Allen 1988) are representative of this work and are the most detailed in that both travel cost and contingent valuation models were estimated for a subset of the 17 top fishing streams in Montana. As can be seen (Table 7), the values vary considerably across site, with the more famous rivers (the Madison, Big Hole, Rock Creek, the Upper Yellowstone through the Paradise Valley) having values per trip considerably in excess of the more local fisheries. The table also shows the comparison between the two model estimates, which are based on totally different methods and data sets. For the complete 17 river sample, the Person and Spearman correlation coefficients are about 0.71 to 0.73 for the two models’ estimates and for the 12 rivers with 80 or more observations each, the correlation is 0.80. The consistency between these estimates provides a measure of validation (convergent validity) for the estimates.

In general, the variation in value per trip that is observed is within the range of variation one experiences in European fee fisheries, where the more productive waters have higher access fees.

Table 7 provides values per trip, but another way to look at variation in value across location is to look at aggregate values per mile of fishing stream (the product of trip or per day values times total angler use over a year).  Figure 1 shows results for such an estimate developed in 1990 and based on the valuation studies referenced earlier. Aggregate value per mile is influenced not only by the value of the experience but the total demand. Accordingly, streams that provide both high quality experiences and support a lot of use (the Madison and the Missouri Holter-Cascade section) rank highest and rivers that provide less valuable experiences and/or support very little use rank lower. For example, the Upper Clark Fork is not a productive fishery and is lightly used. The Smith provides a very high quality experience, but use is very limited based on a highly competitive (lottery) float permit system and the need to commit to a 3 to 5 day float trip to access the best fishing sections. Another factor, other things equal, is proximity to population centers.

No attempt has been made to estimate average fishing values across the three Montana regions defined for this project. However, most of the top fisheries are in the West in the headwaters of the three major Montana River systems: the Columbia, the Missouri and the Yellowstone. The one exception is the Big Horn, which is a tail-water fishery south of Billings. In the almost 20 years since the data underlying Table 7 was collected, this fishery has become one of the one or two top cold-water stream fisheries in the state.

Variation across User Type

A common finding in nonmarket valuation studies of fishing and hunting use is that nonresidents (out-of-state) users tend to have higher average values than resident anglers and hunters. This may be in part due to higher average incomes and preferences for nonresidents who would make the effort to travel to Montana in order to recreate. Table 8 provides one example of this difference, based on a 1989 survey of resident and nonresident anglers on the Upper Missouri River. Nonresident angler values per trip are three to five times those for residents. The difference in value per day is less because nonresidents tend to be on longer trips. The table also shows higher values across residency status for river fishing compared to reservoir fishing in this basin.

The values across both residency and location in Montana fishing streams can be compared to results for another destination fishery, Alaska, where studies have been completed using methods similar to those applied in Montana (Carson et al. 1987; Duffield and Neher 2002). The estimates reported in Table 9 are for several studies all corrected for inflation to the same year dollars. The nonresident and resident values are similar across the two states (1997). It is interesting to see that the per day values for nonresident trout fishing in Montana are roughly on a par with nonresident values for fishing for salmon and grayling in Alaska.

Nonresident hunters also tend to have higher per trip and per day values compared to resident hunters in Montana (Table 10). This is true except for per day values for sheep hunting, where the difference in resident and nonresident values is probably not statistically significant. Sheep hunting may be a special case in that chances of obtaining a permit are very low for anyone, and a permit is accordingly highly valued. In addition to differences in net economic benefits measures, there is also a large disparity in state-managed license prices in Montana, as shown in Table 11. This disparity is in part due to limits on the supply side (quotas) for nonresident hunting permits in Montana. (Market prices are now used by Montana Fish, Wildlife and Parks to on average meet legislated quotas for certain categories (outfitter sponsored) of elk and deer hunting permits.) However, prices at the level nonresidents pay (up to $925 for the right to hunt elk) would not be supportable if the experience was not also highly valued. Table 11 also shows results for permit auction prices for the one or two sheep and moose permits provided each year to conservation organizations to auction off as fundraisers. These very high prices are a reminder that the average values reported here for hunting and fishing are just that – averages - and that at the high end of the distribution some individuals are willing to pay very high prices for fishing and hunting access. Table 11 also reports some limited (and dated) information on fee hunting from a survey conducted in the early 1990's. These values tend to support findings (Table 10) of quite high net values for hunting in Montana on the part of nonresident participants.

Table 11 shows some of the differences across hunting values by species targeted based largely on contingent valuation studies. Table 12 also shows similar differences in per trip and per day hunting values across species targeted. The three studies conducted of deer, antelope and elk in the mid-1980's provide a good comparison since all three used very similar travel cost models and similar data sources. The results show elk hunting trips to be almost twice as valuable as deer hunting trips, with antelope midway between deer and elk in value per trip. However, most of this difference is due to trip length (as indicated by the per day values in Table 12). Based on the estimates in Table 12, hunting for moose and bighorn sheep is a much more highly valued experience than pursuit of the more common species.

Building on work in the recreation literature on recreational specialization (Bryan, 1977), the baseline studies sponsored by Montana Fish, Wildlife and Parks in the mid-1980's developed categories of hunter and angler types based on motivation. For the angler studies (Allen 1988a), survey respondents were asked to rank the importance of 17 possible reasons for choosing to fish a given river on their last fishing trip. The reasons included solitude, be outdoors, family, catch large fish, catch many fish, close to home, eating fish, etc. Cluster analysis generated four general angler types: nature generalists (outdoors, solitude, close to home important), fishing generalists (catch large trout, wild trout, eat trout), casual anglers (not wild trout, close to home) and specialists (skills, large trout, be outdoors). Table 13 shows a cross tabulation of the classifications derived from motivation against other respondent characteristics. For example compared to the other angler types, specialists tended to be more likely to be nonresidents, used flies, preferred fishing and belonged to sport or conservation clubs. The average values per trip for these motivation-based categories were also computed and varied dramatically from $8 per trip for the casual angler to $170 per trip for the specialist, with the generalist categories at $91 for the nature generalist and $117 for the fishing generalist (Duffield and Allen 1988).

A similar analysis was undertaken for Montana elk hunters, with again four categories identified based on motivations: nature hunter, generalist, meat hunters and trophy hunters. Table 14 shows the cross-tabulation of respondent characteristics for these hunter types (Allen 1988b). The per trip values estimated for these groups were: nature hunter - $248, generalists - $300, meat hunters - $165, and trophy hunters - $360.

Using travel cost models, Kerkvliet and Nowell (1999) estimate the variation in value across anglers fishing in the Greater Yellowstone Area as a function of the trip itinerary. Single day visitors (including some anglers who traveled by air for one day of fishing in the GYA) values were estimated to value days at $1100. Visitors with a single destination (the GYA) but a multiple day itinerary had estimated per day values of $440, and visitors on multiple destination trips had per day values of $190.

A final area of variation in value across user types are differences in relative values for consumptive (fishing, hunting) and nonconsumptive (wildlife viewing) activities. The 1996 National Survey of Fishing, Hunting, and Wildlife Associated Recreation used similar methods and data sources for these different user types (Boyle and Roach 1998). The results are only available at the regional level, and the regional groupings vary somewhat across activity (Table 15). However, a general finding is that on a per day basis, the values for wildlife viewing and fishing are on a par, while values for hunting tend to be about double the per day estimates for viewing and fishing.

Trends in values

Most of the studies listed in Table 4 do not provide information on trends in fish and wildlife-related use values, since few of them have been replicated over time. However, information on trends in value can be derived from several sources:

  1. the one Montana baseline study that has been replicated, that for elk hunting (Loomis, Cooper and Allen 1988; King and Brooks 2001);
  2. license sales data;
  3. meta-analysis (at the national level); and
  4. the National Survey of Fishing, Hunting and Wildlife Associated Recreation.

The last of these sources, the National Survey, would seem to provide a good basis for trend. These studies are conducted by the U.S. Fish and Wildlife Service and the Census Bureau every five years. Economic valuation has been a part of this survey effort beginning in 1975; however no state-level estimates for Montana have ever been reported for this initial effort. However, Hansen (1977) did use this data to estimate the value of deer, antelope and elk hunting in the Intermountain Region (which includes Idaho and part of Wyoming). Using open-ended CVM data, per day values were estimated at $41, $23 and $45, respectively. The most recent economic publication from this survey (Boyle, Roach, and Waddington (1998)) is for the 1996 survey. Unfortunately, these surveys are not as useful as they could be for understanding trends in values due to changes in sampling and valuation methodology over the years, and, for some years, relatively small state-level samples. For example, as shown in Table 15 for the 1996 survey, most fishing and hunting use samples were not large enough to report state-level values and only regional level estimates (e.g., Intermountain, Pacific Northwest, etc.)are reported. One would need to work with the original data sets from these studies to be able to interpret trend.

The comparison of Montana elk hunting values for 1987 and 1998 surveys is reported in Table 16. The average value per trip (with the earlier study corrected for inflation to 1998 price levels) in 1987 was $380 and in 1998 is $503. This is an increase of about one-third in value or about 2.3 percent per year, over and above inflation. A limitation of the comparison is that the sampling of resident and nonresident hunters was not in proportion to actual hunter numbers in either sample year. The average value for 1998 was derived by using a weighted average at the proportion of residents and nonresidents in the 1987 sample. Resident and nonresident values were not reported in the 1987 study, so it is not possible to examine the relative change across residency. For example, it is possible that resident values are stable or declining and the increase is all due to nonresident demand shifts.

Another source of information on trends in values is a meta-analysis estimated on a database of 163 U.S. and Canada outdoor recreation studies conducted between 1967 and 1998(760 separate estimates) (Rosenberger and Loomis, 2001). Unlike the other studies discussed in this paper, this meta-analysis is not restricted to fish and wildlife-related uses. The estimated regression model used net benefit per day estimates from the various studies as the dependent variable, had 26 significant explanatory variables, with an adjusted R-square of 0.27. A variable for "trend" was statistically significant and implied that benefits were increasing faster than inflation at about $1 per year per activity day per person. Given an average value per day for outdoor recreation of $20 to $30, this estimate shows an annual percent increase (over and above inflation) that is similar to the estimate derived from the Montana elk hunting studies.

A final source on trends in fish and wildlife-related values is the Montana Fish, Wildlife and Parks reported license sales (and prices) for all fishing and hunting permits. Sales data provides information on participant response to a standing offer by the state for the right to hunt or fish for a known (permit or license) price. The value information is on a year or season level rather than on a per day or per trip value as derived from most survey-based studies. A strength of this data set from the standpoint of interpreting trends is that it is based on actual sales (rather than samples) and that the data is generally consistent from year to year. [9] For nonresidents, only fishing and bird hunting permits are available in unlimited quantities. Accordingly, market-clearing sales quantities are not known for most nonresident hunting license categories.

Figures 2 and 3 show plots of resident and nonresident upland bird hunting license sales and real (constant dollar) prices from 1970 to 2000. Resident license prices have been relatively stable over the period, mostly around $6 to $8 in year 2000 dollars, but participation declined steadily beginning in the early 1980's. During the last decade and up to the present, participation has been steady at about one-half earlier levels. Nonresident prices have fluctuated more (and at a much higher level) at from about $40 to $120 dollars, being at their highest levels in 1970 and 2000. Throughout this period nonresident participation has increased fairly steadily from about 1000 hunters in 1970 to around 10,000 in recent years. Demand models fitted to this data show that nonresident demand is more price elastic than resident, but price response is minor over time compared to the positive shift in demand.

For fishing licenses, resident license prices have been fairly stable at around $12 to $20 and sales have also been fairly stable at around 140,000 to 170,000 per year, although there has been a modest and steady decline in sales since the early 1980’s) (Figure 4). Just as for upland bird hunting, nonresident fishing permit sales have been steadily increasing from around 7,000 at the beginning of the period to around 30,000 in recent years. Prices have been between $45 and $75 dollars, declining in the first decade and fairly stable around $50 to $60 dollars since (Figure 5).

The trend for both fishing and bird hunting is that demand has been stable to decreasing for residents over the period 1970 to 2000, but increasing to levels four to six times as great as at the beginning of the period for nonresidents.

Another source of information on fish and wildlife-related values is the long-term data on visitation to Yellowstone NP. Based on surveys conducted in the 1990's (for example, Duffield 1992), wildlife observation is the primary reason visitors give for visiting Yellowstone. (Viewing geothermal features is a distant second.) Figure 6 shows the long-term relationship of entrance fee and visitation at Yellowstone, for the period 1916-2002. During this period prices have declined in real terms from about $165 to $20 in current terms (and have, in the last decade, been under $5), while visitation has climbed from a few thousand visitors per year to around 3 million at present. The tremendous increase in visitation over this long time period may be a function of a number of factors, including increased population, leisure time and disposable income levels, and a reduction in the cost of travel, in part due to significant investments in travel infrastructure and technical advances in the automotive sector. Figure 7 shows a plot of the same data (entrance fee and visitation) for the last two decades. In this period prices increased by a factor of three in 1986-1988 and doubled in 1996-1997. As is apparent from the figure, there is no observable price response. Models fit to the visitation and entrance data show entrance fees, at the current level, are not a significant factor in decisions to visit the park. Entrance fees at present are a very small fraction of both the total cost of visiting the park (especially for nonresidents) and the net benefits visitors derive from their trips.

Research Priorities

This section summarizes research priorities suggested by this review of the economic valuation literature on Montana fish and wildlife resources. Possible research areas include use of demand models for explaining trends in past use and projecting future use, improving our understanding of participation in non-consumptive fish and wildlife uses, examining markets for these uses both from a supply and demand perspective, understanding participation and turnover in fish and wildlife-related recreation, investigating the very significant changes in nonresident use from a national perspective and undertaking a Northern Rockies meta-analysis with a focus on passive use values for fish and wildlife resources.

A question that has not, to a large extent, been addressed by the existing research summarized in this project is the relationship between changing demographics and the use of natural resources. The demographic and regional economic trends show us how Montana is changing, but the implication for and connection to fish and wildlife uses is not well understood. It would be of interest to integrate the descriptive materials on changing demographics with the economic demand models described in this chapter. From the standpoint of microeconomic theory, the socioeconomic characteristics of household income, population, gender, and age distribution are factors that affect the demand for natural resources. In terms of statistical modeling, these are exogenous variables. A specific project would be to use the economic demand models for Montana sport hunting and fishing that were estimated in the mid-1980's to explain the change in use by region over the last twenty years. For example, this could be relatively straightforward for the zonal travel cost models that were estimated for the major stream fisheries in the state. These models were developed to explain the pattern of use and valuation across space in the study year. However, the models could also be used to project use using year-to-year changes in demographic factors. It would be of interest to see how closely the predicted levels of use matched the observed by basin or region. Models could also be re-estimated using current data sets. Should the models prove to be robust, they could prove useful for looking into the future. For example, given the trends in demographic factors, what will be the relative level of use on the Bitterroot River in the year 2023 compared to use on the Yellowstone, Marias, Big Hole, etc? This could have implications for future management of these rivers.

While previous research on economic demand for fish and wildlife resources has focused on " consumptive" activities (fishing and hunting), the demand for nonconsumptive activities such as wildlife observation is not well understood. It may be possible to undertake some analysis of this issue using the national fishing and hunting survey databases. This area would merit the collection of new data sets.

Most previous research in this area has been organized along the supply side - looking at markets associated with given resources such as the Madison River or Glacier National Park. However, it would be of interest to compare and contrast participation and demand across regions or by major population centers such as Billings, Bozeman, Missoula, Helena and Great Falls. It would be interesting to examine how much participation varies across these centers (or regions or by rural-urban divisions) and to what extent participation is driven more by supply-side or demand-side factors.

A related issue is explaining the changes in overall participation in outdoor recreation in Montana. It is apparent from license sales data, for example, that Montana resident participation in fishing and hunting is on a very different trajectory than nonresident. One approach to beginning to understand this change is to make use of the recently created automated license database now used by Montana Fish, Wildlife and Parks. Following a subsample of license holders would provide considerable information on the turnover among participants.

Understanding nonresident demand would require an analysis that took into account changes in attitudes and changes in fish and wildlife-related opportunities throughout the nation. While some issues can be addressed by understanding what is happening within Montana, nonresident demand can only be understood in a national context. This may be another area where some insights could be gained using existing data sets.

While the emphasis in most fish and wildlife-related research is on direct use, existence and bequest motives are also often important factors in many wildlife-related policy decisions. This suggests research that is not user-based, but explores changing attitudes and values in the entire population. One approach to summarizing what is known about attitudes and values toward wildlife would be to undertake a meta-analysis based on studies done in Montana and nearby states.

The discussion here and the research cited have been limited to economic benefits related directly or indirectly to wildlife. However, many policies designed to benefit wildlife, particularly those that restore, protect or enhance wildlife habitats, also create many other direct and indirect benefits related to the ecosystem services provided by these habitats. For example, restoring riparian and aquatic habitat for a given fish species also generates benefits related to clean water, flood absorption capacity, other wildlife species that use the same habitat, and aesthetics – all of which benefit property owners adjoining the stream as well as the general public. Evaluating public policy decisions about wildlife habitat without identifying the full range of possible benefits is misleading. It would be of interest to undertake a case study in Montana of wildlife habitat restoration for a given site or species that was relatively comprehensive in the evaluation of possible benefits and costs associated with the action.


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Duffield, J., J. Loomins, and R. Brooks. 1987. The Net Economic Value of Fishing in Montana. Montana Department of Fish, Wildlife and Parks. Helena, MT.

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Duffield, J. 1991. Existence and Nonconsumptive Values for Wildlife: Application to Wolf Recovery in Yellowstone National Park. Western Regional Research Project W-133: Benefits and Costs in Natural Resources Planning. Compiled by Catherine Kling. Davis, CA.

Duffield, J. 1992. "Economic Valuation of Fisheries: Nonmarket Studies in the Clark Fork Basin" in V. Watson, Ed., Proceedings of the Clark Fork River Symposium pp. 141-162. Bozeman: Montana Academy of Sciences.

Duffield, J. 1992. An Economic Analysis of Wolf Recovery in Yellowstone: Park Visitor Attitudes and Values. In John D. Varley and Wayne G. Brewster, Ed. Wolves for Yellowstone? A Report to the U.S. Congress Vol. IV. Research & Analysis, pp. 2-31 to 2-87. National Park Service, Yellowstone National Park.

Duffield, J and S. Allen. 1988. "Angler Preference Study Final Economics Report: Contingent Valuation of Montana Tout Fishing by River and Angler Subgroup." Report for Montana Department of Fish, Wildlife, And Parks. Helena, MT.

Duffield, J. T. Brown, and C. Neher. 1992. Recreation Benefits of Instream Flow: Application to Montana's Big Hole and Bitterroot Rivers, Water Resources Research Vol. 28, No. 9, pages 2169-2181.

Duffield, J., T. Brown, and D. Patterson. 1994. Economic Value of Instream Flow in Montana's Big Hole and Bitterroot Rivers, Research Paper RM-317, Fort Collins: Rocky Mountain Forest and Range Experiment Station.

Duffield, J. and C. Neher. 1990. Montana Deer Hunting: a Contingent Valuation Assessment of Economic Benefits to Hunters. Report for the Montana Department of Fish, Wildlife, and Parks.

Duffield, J. And C. Neher 1993. Economic Analysis of the Values of Surface Uses of State Lands: Fair market Value for Recreational Uses. Report for the Montana Department of State Lands.

Duffield, J., C. Neher and M. Garrity. 1993. Montana Outfitter Survey: Land Use Fees and Trip Characteristics. Report for the Montana Department of State Lands. Helena, MT.

Duffield, J. and C. Neher. 1996. Economics of Wolf Recovery in Yellowstone National Park. Trans. 61st No. Am. Wildl. and Nature. Resource. Conf.: 285-292.

Duffield, J and C. Neher. May 2000. "Winter 1998-99 Visitor Survey Yellowstone N.P., Grand Teton N.P., and the Greater Yellowstone Area."Report of the National Park Service. Denver, CO.

Duffield, J. and C. Neher. 2000. The Reintroduction of Grizzly Bears to the Bitterroot Mountains: Final Environmental Impact Statement (Socioeconomics sections). U.S. Fish and Wildlife Service, Missoula, MT.

Duffield, J., C. Neher, And M. Merritt. 2002. Region III Angler Survey: Use and Valuation Estimates for 1996, with a Focus on Arctic Grayling Fisheries. Report for the Alaska Department of Fish and Game, Division of Sport Fish. Fairbanks, AK.

Duffield, J., D. Patterson, C. Neher, and S. Allen. 1990. Instream Flows in the Missouri River Basin: A Recreation Survey and Economic Study. Report for the Montana Department of Natural Resources and Conservation.

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Duffield, J. and D. Patterson. 1991. Inference and Optimal Design for a Welfare Measure in Dichotomous Choice Contingent Valuation. Land Economics 67(2):225-239.

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Duffield, J., D. Patterson, and C. Neher. 2000. "National Telephone Survey of Attitudes Toward Management of Yellowstone National Park." Report for the National Park Service. Denver, CO.

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Hausman, Jerry A. 1995. Expert Report of Jerry A. Hausman. United States District Court, District of Montana, Helena Division, State of Montana v. Atlantic Richfield Company. No. CV-83-317-HLN-PGH. (July 13).

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Kerkvliet, Joe, Clifford Nowell, and Scott Lowe. 2002. The economic value of the Greater Yellowstone’s blue-ribbon fishery. North American Journal of Fisheries Management 22(2): 418-424.

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Table 1. Order of Preference to See Animals in Yellowstone NP:
Regional vs. Out-of-Region Residents.
Source: Duffield 1992
Rank Non-residents Percent Residents Percent
1 Grizzly 0.52 Grizzly 0.61
2 Moose 0.33 Black bear 0.38
3 Black bear 0.31 Moose 0.34
4 Sheep 0.25 Elk 0.28
5 Elk 0.22 Lion 0.26
6 Lion 0.22 Sheep 0.16
7 Eagle 0.20 Bison 0.15
8 Bison 0.17 Eagle 0.14
9 Wolf 0.17 Wolf 0.13
10 Wolverine 0.04 Wolverine 0.07

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Table 2. Order of Preference to See Animals in Yellowstone NP: 1990 vs. 1999 Visitor Samples.
Source: Duffield 1992, Duffield, Patterson and Neher 2000.
Rank Non-residents Percent Residents Percent
1 Grizzly 0.55 Grizzly 0.58
2 Black bear 0.33 Wolf 0.36
3 Moose 0.33 Moose 0.35
4 Elk 0.24 Lion 0.31
5 Lion 0.23 Black bear 0.29
6 Sheep 0.22 Sheep 0.23
7 Eagle 0.19 Eagle 0.21
8 Bison 0.16 Bison 0.19
9 Wolf 0.15 Elk 0.14
10 Wolverine 0.05 Wolverine 0.06

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Table 3. Multivariate Logistic Model of Wolf Recovery Trust Fund Responses (Total Valuation).
Variable / Statistic Entire Sample Residents Non-residents
Constant -31.39 -34.56 -32.48
Log of bid amount -0.984 -1.314 -0.918
Log of gross family income 0.4631 0.548 0.484
Log of 1-4 index of familiarity with trust funds 1.345 -- 1.263
Log of composite variable related to desire to see wolves 3.589 7.594 2.764
Log of composite of environmental attitude variables 7.30 6.57 7.99
Dummy for high preference to see deer, elk, or moose -0.336 -- -0.336
Dummy for "hunts big game" -0.522 -1.62 --
Sample size 524 158 366
Hosmer-Lemeshow P-value 0.86 0.896 0.133

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Table 4. An Annotated Bibliography:
Nonmarket Valuation Studies of Montana Wildlife and Related Uses
Site/location Date Object
Valuation Method NEV
Estimate (1)
S / Yellowstone Area 1963 Wilderness use CV NEV/season for wilderness use: $3.60.  Wilderness Management Merriam 1963 *
NW/Glacier NP 1966 Visitor Demand Function TCM Visitor Demand Function. NEV/trip roughly $12.  Research Study Clawson and Knetsch 1966
SW/Spanish Peaks 1976 Congestion in wilderness recreation CV NEV per trip as function of congestion: $0.34 to $1.00.  Wilderness Management Cicchetti and Smith 1976
NW/ Flathead Basin 1982 Fishing, swimming, camping TCM CV NEV/day for fishing, swimming, and camping: $5 to $6; for preservation value $64/household  Research Study Sutherland 1982 *
NW/ Kootenai R. 1982 Recreational use of Kootenai Falls CV TCM Total value estimates for CV and TC methods.  Kootenai Falls EIS Duffield 1982
NW/ Kootenai R. 1984 Kootenai Falls Recreation CV TCM Total value estimates for CV and TC methods.  Kootenai Falls EIS Duffield 1984
Statewide 1987 Montana trout Fishing TCM NEV/trip: Statewide average between $49 and $104 depending on method.  Baseline study Duffield, Loomins, and Brooks 1987 *
W / Lolo NF 1987 Campground Use TCM NEV/RVD for campground Use: $15 to $19.  Forest Management Daniels 1987
Statewide 1988 Antelope Hunting TCM NEV/ Trip: Between $77 and $170 depending on method and area.  Baseline study Loomis, and Cooper 1988 *
Statewide 1988 Montana Elk Hunting TCM NEV/Trip: Between $80 and $195 depending on method.  Baseline study Duffield 1988 *
Statewide 1988 Deer Hunting TCM NEV/trip: Entire Sample $108.  Baseline study Brooks 1988 *
West central - Rock Creek 1989 Stream fishing CV NEV/Trip: current trip $212.  Fishery Management Duffield 1989 *
Statewide - Unique Waters 1988 Montana Trout Fishing CV NEV/Trip: Between $38 and $217 depending on stream.  Baseline study Duffield and Allen 1988 *
Statewide 1988 Montana Elk Hunting CV NEV/Trip: Current trip and conditions all responses $262.  Baseline study Loomis, Cooper, and Allen 1988 *
SE Powder River Basin 1989 Conservation Easement CV Estimates of several cost and benefit estimates of land acquisition.  Wildlife Habitat Acquisition Duffield 1989 *
Clark Fork R. Basin 1992 Angling CV TCM Numerous estimates of TC and CV WTP for stream fishing in Montana.  Clark Fork Baseline information Duffield 1992 *
Missouri R. Basin 1990 Instream Flows CV Many current trip, trust fund, and marginal flow values.  River water user allocation Duffield, Patterson, Neher and Allen 1990*
Statewide 1990 Deer Hunting CV NEV/Trip current trip: between $209 and $800 depending on sample.  Baseline study Duffield and Neher 1990 *
Big Hole And Yellowstone Basins 1991 Instream Flows existence value CV numerous hypothetical and actual WTP estimates.  State leasing of water for instream flows Duffield and Patterson 1991 *
YNP Region 1991 Existence value for wildlife CV WTP to trust fund for wolf reintroduction: $70 for entire sample.  Wolf Reintroduction Duffield 1991 *
Statewide 1991 Waterfowl hunting CV NEV/trip: Resident $126; nonresident $329.  Baseline study Neher and Duffield 1991 *
Statewide 1991 River angling CV NEV/trip current trip values for stream angling: between $44 and $192.  Research Study: standard errors for welfare estimates Duffield and Patterson 1991
Yellowstone Region 1992 Current trip; WTP for wolf reintroduction CV Estimates of total value, and existence value of wolf reintroduction, and current trip valuation.  Wolf Reintroduction Duffield 1992 *
Statewide 1993 Recreational use of state lands CV, TC WTP for state lands recreational permit: $15 to $69 depending on method.  State lands entry fees Duffield and Neher 1993 *
Yellowstone Region 1993 Wolf reintroduction to GYA CV Trust fund WTP value for both support and apposition to wolf reintroduction: Range of $2.73 to $26.33 depending on sample and position on issue.  Wolf Reintroduction Duffield, Patterson and Neher 1993 *
Big Hole and Bitterroot Rivers 1994 Angling; instream flows for angling/floating CV Numerous estimates of river user WTP and instream flow marginal values.  Research Report Duffield, Brown and Patterson 1994 *
Big Hole and Bitterroot Rivers 1992 Instream Flows CV Numerous estimates of river user WTP and instream flow marginal values.  Research Study Duffield, Brown and Neher 1992
SW / Clark Fork Basin 1995 Cleanup of superfund site CV NEV/household for complete cleanup: $49.  Litigation Schultze and Rowe 1995 *
SW / Clark Fork Basin 1995 Cleanup of superfund site TCM NEV/trip angler response to quality change: $17.  Litigation Morey, Rowe, Waldman and Duffield 1995*
YNP Region 1996 Wolf reintroduction to GYA CV Trust fund WTP value for both support and opposition to wolf reintroduction: Range of $1.52 to $20.50 depending on sample and position on issue.  Wolf Reintroduction Duffield and Neher 1996
Statewide 1996 Moose, Sheep and Goat hunting CV NEV/Trip: Moose all $642; Goat all $704; Sheep Res $800; Sheep nonres $1436.  Baseline study Brooks 1996 *
Statewide / Clark Fork River 1996 Changes in recreational services TCM NEV/new trips in response to quality change: $17.  Litigation Desvousges, Walters, and Train 1996 *
S / Yellowstone Area 1999 Recreational Angling TCM NEV/trip recreational anglers: $190 to $1100.  Research Study Kerkvliet and Nowell 1999
YNP Region: Summer Visitors 2000 Winter Use
in YNP
CV Current Trip WTP: residents $56; Nonresidents $349.  Winter Use Management Summer visitor survey Duffield, Patterson and Neher 2000 *
YNP Region; National Phone 2000 Winter Use
in YNP
CV WTP to support policy changes: Between $9 and $19 depending on sample and issue.  Winter Use Management National phone survey Duffield, Patterson and Neher 2000 *
YNP Region: Winter visitors 2000 Winter Use
in YNP
CV WTP current trip: $30 residents; $145 nonresidents; plus other valuation models.  Winter Use Management Winter User Survey Duffield and Neher 2000 *
Statewide 2001 Elk Hunting CV NEV/ Most Recent Trip: Residents $311; nonresidents $931.  Baseline study King and Brooks 2001 *
Statewide 2000 Grizzly Reintroduction CV WTP for trust fund to support reintroduction: $40 to $49 depending on sample.  Grizzly Reintroduction Duffield and Neher 2000
S/ Yellowstone Area 2002 Recreational angling TCM NEV/day for anglers: $172 to $977.  Fishery Management Kerkvliet, Nowell, and Lowe2002
SW / Clark Fork River 2002 Changes in recreational services TCM NEV/trip angler response to quality change: $17.  Litigation Morey, Breffel,Rowe, and Waldman 2002
(1) Net Economic Value
Note: Citations with an asterisk can be obtained from Dan McCollum at the USFS Rocky Mountain Experiment Station:

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Table 5. Estimate Mean Values of Wolf Reintroduction in the Yellowstone Area
Source: Duffield and Neher 1996
Welfare measure / Statistic 3-state region (WY,MT,ID) Out-of-region All US residents
Mean value for supporters $20.50 $8.92  
Mean value for those opposed $10.08 $1.52  
Population of supporters 391,202 50,152,416  
Population of those opposed 340,522 25,774,280  
Aggregate NEV / year $321,201 $28,572,785  
Scaler 0.286 0.286  
Estimated NEV per year
(standard error)

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Table 6. Annual Social Benefits and Costs of Yellowstone Wolf Recovery
Source: Duffield and Neher 1996
Benefit or cost category Annual value on thousands of 1992 dollars
Low estimate High estimate
(A) Benefits:
Annual NEV of reintroduction
$6,673.1 $9,854.3
(B) Costs:    
Foregone value to hunters 187.3 464.9
Value of livestock losses 1.9 30.5
Annual wolf management costs 441.0 441.0
Total Costs 630.2 936.4
Net benefits of wolf recovery 6,042.9 8,917.9

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Table 7. Estimated Value/Trip for Stream Fisheries in Montana
Source: Duffield and Allen 1988
River Dollar Value/Trip Ratio
Sample Size
Madison 234 228 1.3 357 148
Up. Yellowstone 230 150 1.53 81 121
Boulder 180 149 1.21 57 69
Rock Creek 173 92 1.88 89 78
Big Hole 164 218 0.75 187 140
Gallatin 161 180 0.89 264 152
Blackfoot 142 133 1.07 149 97
Bighorn 121 159 0.60 160 151
Beaverhead 112 188 0.59 120 108
Smith 94 153 0.61 43 44
Stillwater 82 85 0.96 133 113
Bitterroot 73 59 1.24 88 117
Md. Clark Fork 68 86 0.79 231 126
Md. Yellowstone 63 74 0.85 174 105
Missouri 60 63 0.95 357 148
Up. Flathead 56 99 0.57 66 65
Kootenai 56 38 1.47 121 72

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Table 8. Relative Values for Angler Use by Residency and Water Type, Upper Missouri River, Montana - 1989.  
Source: Duffield, Neher, Patterson, and Allen 1990
Water Type Value per Trip Value per Day
Resident Non-resident Resident Non-resident
Rivers 147 793 52 193
Reservoirs 143 507 40 129
Resident sample includes only residents from the Upper Missouri River Sub-basin.

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Table 9. Comparison of Alaska and Montana Angler Values
Study User Group Target Species / Resource Net Benefit
Est. Per Day
(1997 $)
Alaska – Carson et al. 1987 R & NR Salmon 285
Alaska – Duffield & Neher 2002 NR Grayling 217
Alaska –" NR Salmon 300
Alaska –" R Grayling ~50
Alaska –" R Stocked Lakes 15 – 44
Montana – Duffield et al. 1990 NR Up. Missouri R’s 249
Montana – " NR Reservoirs 167
Montana – " R Up. Missouri R’s 67
Montana – " R Reservoirs 52

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Table 10. Relative Values for Montana Hunters by Residency and Species 
See sources for species-specific studies listed in Table 4
Species Study Year Dollars per Trip Dollars per Day
Residents Nonresidents Residents Nonresidents
Deer 1988 209 706 46 102
Elk 1998 311 931 104 116
Ducks 1989 126 329 79 100
Sheep 1993 800 1,436 320 287

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Table 11. Permit Market Information on Montana Big Game Hunting Values. 
Sources: Montana DFWP 2003 Big Game Huntig Regulations; Personal Com. Rob Brooks, Montana DFWP; Duffield, Neher and Garrity 1993.
Species Residents Non-residents
(A) Current permit price (2003)
Elk 16 578–925
Deer 13 328–775
Antelope 14 203
Moose 78 753
Mountain goat 78 753
Bighorn sheep 78 753
(B) Auction price (1991-95)
Bighorn sheep $61,000 to $310,000
Moose $4,000 to $14,000
C) Landowner fees (1992)
Per animal 50 to 200
Per hunter 10 to 1,000

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Table 12. Relative Values for Montana Hunting by Species Targeted
See sources for species-specific studies listed in Table 4.
Species Year of Study Value per Trip Value per Day
Deer 1986 108 55
Antelope 1985 143 62
Elk 1985 185 66
Waterfowl 1989 168 89
Moose 1993 550 183
BighornSheep 1993 800 to 1,436 287 to 320

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Table 13. Key Characteristics of Montana Angler Types.
Source: Allen 1988a
Characteristic Nature Fishing Casual Specialist
Percent Resident 81 72 83 58
% for whom fishing is their favorite activity 20 22 14 30
% who used flies 30 34 29 60
% who caught no trout 15 14 34 15
% who belong to a sport or conservation group 23 28 19 43

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Table 14. Characteristics of Montana Elk Hunters: by Hunter Type             
Source: Allen 1988b
Characteristic Nature Generalist Meat Trophy
% Resident 72 69 88 48
% for whom hunting is favorite activity 13 22 12 21
% who used guides 8 13 4 20
% who agree vehicles should only be on open roads to retrieve game 59 60 39 51

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Table 15. Relative Values for Fishing, Hunting, and Wildlife Viewing.   
Source: 1996 National Survey of Fishing, Hunting & Wildlife Associated Recreation 
Region Per Year Per Day
(A) Trout Fishing
Mountain 268 27
(B) Hunting
Mountain (deer) 301 58
CO, ID, MT, OR, WY (elk) 410 59
Alaska (moose) 624 61
(C) Wildlife Viewing
Pacific 263 19
Mountain 312 31
Alaska 696 34

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Table 16. Trend in Montana Elk Hunting Values.
Source: derived from Loomis, Cooper, and Allen 1988 and King and Brooks 2001.
Year User Group Value per trip (1998$) Value per day
1987 All 380 53
1998 Residents 311 104
Non-residents 931 116
All* 503 108
* Weighted 31% non-resident, 69% resident to match 1987 sample

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[1] State of Montana v. Atlantic Richfield Company. No. CV-83-317-HLN-PGH. United States District Court, District of Montana, Helena Division.
[2] These included Daniel McFadden, who in 2000 was awarded the Nobel Prize in Economics for his pioneering work on models of individual choice, of the kind he helped apply in the Montana case.
[3] One exception is the values reported for the litigation-related studies of the Clark Fork River fishery. The values reported in these studies are the marginal values associated with the response to a change in quality at a given site. Most of these additional trips are substituted away from other sites and reflect only the cost savings (quality change benefits) over other sites, not the average value of the site across all users.
[4] The Glacier Park demand model may also have been described in an earlier report by Clawson (1959). The 1966 study shows the graph of a demand function for Glacier, but did not provide a net benefit estimate. The estimate in Table 4 is derived from the graph.
[5] It is interesting to note that Mitchell and Carson (1989) describe the work by Cichetti and Smith as the chronologically fourth known study to be completed (following the earlier work by Davis completed in 1963, air pollution studies completed by Ronald Ridker in 1967, and a study of duck hunting values initiated by Judd Hammack and Gardner Brown in 1969).
[6] Results from these models can also be interpreted in terms of annual average willingness to pay for improved catch rates at the impacted sites across the angler population. The per trip measure reported here is on the assumption that all WTP from the recreation demand model is just for new trips to the impacted sites.
[7] These studies are not exclusively focused on fish and wildlife resources per se and, in any case, are not easily summarized. Accordingly, they are not all included in the listing in Table 4.
[8] Several limited research efforts are currently in the data collection phase of replicating parts of these earlier fishing and hunting studies.
[9] One limitation is that occasionally new license classes are created from old ones and the definition of what can be hunted, and when and where, changes.

This report was completed in 2004.