DEPAR TMENT OF AGRICULT URE

Pacific Northwest 

Research Station

General Technical 

Report

PNW-GTR-883

May 2013

United States Department of Agriculture

Forest Service

Estimation of National Forest 

Visitor Spending Averages 

From National Visitor Use 

Monitoring: Round 2 

Eric M. White, Darren B. Goodding, and Daniel J. Stynes
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Authors

Eric M. White is assistant professor and Darren B. Goodding is a graduate 

research assistant, Department of Forest Engineering, Resources and Management, 

College of Forestry, Oregon State University, 280 Peavy Hall, Corvallis, OR 97331. 

Daniel J. Stynes was professor emeritus in the Department of Community, Agriculture, Recreation, and Resource Studies, Michigan State University, 131 Natural 

Resources Building, East Lansing, MI 48824. 

This work was performed under PNW joint venture agreement 10-JV-11261955. 

Cover Photos: Emily Jane Davis.
Abstract

White, Eric M.; Goodding, Darren B.; Stynes, Daniel J. 2013. Estimation of 

national forest visitor spending averages from National Visitor Use Monitoring: 

round 2. Gen. Tech. Rep. PNW-GTR-883. Portland, OR: U.S. Department of 

Agriculture, Forest Service, Pacific Northwest Research Station. 65 p. 

The economic linkages between national forests and surrounding communities 

have become increasingly important in recent years. One way national forests 

contribute to the economies of surrounding communities is by attracting recreation 

visitors who, as part of their trip, spend money in communities on the periphery 

of the national forest. We use survey data collected from visitors to all units in the 

National Forest System to estimate the average spending per trip of national forest recreation visitors engaged in various types of recreation trips and activities. 

Average spending of national forest visitors ranges from about $33 per party per 

trip for local residents on day trips to more than $983 per party per trip for visitors 

downhill skiing on national forest land and staying overnight in the local national 

forest area. We report key parameters to complete economic contribution analysis 

for individual national forests and for the entire National Forest System. 

Keywords: Visitor spending, economic impact, National Visitor Use 

Monitoring. 
Contents 

1 Introduction

1 Background on NVUM Surveys

2 Pertinent Survey Questions

2 NVUM Sample

3 Spending Profile Estimation

3 Analysis Considerations

7 Visitor Segments

8 National-Level Segment Shares

11 Nights Away From Home

12 Spending Profiles

12 Basic 7 Trip Spending

14 High and Low Spending Averages

15 Downhill Skier Visitor Spending

20 Lodging-Based Segmentation

21 Lodging-Based Segment Spending Averages

27 Conclusions

28 Acknowledgments

28 Metric Equivalents

28 References

30 Appendix 1: Applying the National Spending Profiles

47 An Example: Estimating Total Spending for the Hiawatha National 

 Forest

51 Appendix 2: Supplemental Tables for Completing Economic Analyses

54 Appendix 3: Wildlife-Related Visit Characteristics and Spending 

 Averages

54 Spending Profiles by Trip Segments

57 High and Low Spending Averages

60 Wildlife-Related Visitor Trip and Party Characteristics

60 Wildlife-Related Visits 
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Estimation of National Forest Visitor Spending Averages From National Visitor Use Monitoring: Round 2

Introduction 

This report updates previous figures on national forest recreation visitor spending 

(Stynes and White 2005a, 2005b) using data collected in all 5 years of Round 2 of 

National Visitor Use Monitoring (NVUM), starting in fiscal year 2005 through 

2009 (October 2004 through September 2009). Survey data used in this update 

come from the 123 administrative forest units that were sampled. We provide 

updated estimates of recreation visitor spending, the share of recreation visits 

associated with a number of trip types, average people per party, and other visit 

characteristics to assist in economic analyses. 

We discuss the analytical considerations in developing the spending profiles, 

present the national-level segment shares, and report the average, high, and low 

spending averages for seven trip-type segments (referred to as the “Basic 7” in the 

Round 1 NVUM). In addition, we present spending averages for downhill skiers 

and report on the use of lodging information to segment recreation visitors and 

describe their spending. 

In appendix 1, we provide guidance on how to apply the spending profiles for 

economic impact or contribution analysis and complete an example application for 

the Hiawatha National Forest. Appendix 2 contains additional tables at the forest 

and national levels that can serve as inputs for economic analyses at the forest and 

national levels. In appendix 3, we report on the recreation behavior and spending 

patterns of wildlife-related visitors for application in programmatic analyses. 

Background on NVUM Surveys 

The objective of the U.S. Department of Agriculture, Forest Service NVUM 

program is to estimate the number of recreation visits to national forests (Zarnoch 

et al. 2011). To achieve this objective, a subset of national forests in each region is 

sampled yearly with each administrative forest in the National Forest System (NFS) 

being sampled once every 5 years. The NVUM sampling approach involves the 

surveying of a sample of recreation visits to the national forest. A national forest 

visit is defined as one person recreating on national forest land for an indeterminate 

period of time and ending when the individual spends a night off national forest 

land. In addition to data necessary to estimate visitation, the NVUM survey gathers 

other visitor and trip characteristics. A separate economics survey administered to 

roughly a third of those sampled gathered spending information that provides the 

basis for development of the spending profiles reported here.
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general technical report pnw-gtr-883

Pertinent Survey Questions 

The results reported here are drawn from a subset of the questions on the NVUM 

survey instrument. To classify visitors into groups for economic analysis, we rely 

on questions related to the distance traveled to the site; whether nights away from 

home were spent in the local area; the different types, if any, of lodging used; and 

the primary purpose for the trip away from home. Wording of survey questions and 

directions to surveyors for administration of the survey are available in the 2007 

National Visitor Use Handbook (USDA FS 2007, p. 37). The wording of many of 

those questions has been improved to gather more precise information, and the 

lodging questions have been added between the initial application of NVUM across 

the NFS in 2000 and the present implementation reported here. Additionally, the 

questions relating to nights spent in the local area and the purpose of the trip were 

moved from the economic survey to the basic survey—increasing the number of 

NVUM respondents who were asked those questions. 

For visitor spending, NVUM respondents are asked to report the spending of 

their travel party (generally those they travelled with in the same vehicle) within 50 

mi of the interview site. Reported spending is collected in 10 expenditure categories 

related to outdoor recreation (e.g., money spent in restaurants/bars, for gas and oil, 

for souvenirs, and for motels/hotels). Respondents are asked only to report spending 

in the local area of the recreation site related to the current trip—both expenses 

already made and those anticipated. Visitors are allowed to select a response that 

“they do not know or choose not to report their expenses.” Those respondents are 

excluded when calculating average trip spending. Since the initial implementation 

in 2000, the spending question was changed to explicitly request spending for the 

entire travel party (rather than only the individual interviewed), and the spending 

categories were slightly revised to improve clarity. 

NVUM Sample 

National forest visitors were sampled at both designated recreation sites (e.g., picnic 

areas, campgrounds, visitor centers on national forest land) and in the general 

forest area (GFA) of individual national forests. A stratified sampling scheme was 

employed based upon the expected visitation (very high, high, medium, or low 

last-exiting recreation traffic) for a given location on a given day (termed a “site 

day”). Individual dates and locations selected for recreation sampling were termed 

“sample days.” On sample days, individuals leaving the recreation site selected for 

sampling who voluntarily stopped at the interview point and who stated they were 

recreating on the national forest and leaving the site (or leaving the national forest 

at GFA sites) that day completed an NVUM survey. Approximately 25 forests were 

Reported spending 

is collected in 10 

expenditure categories 

related to outdoor 

recreation.
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Estimation of National Forest Visitor Spending Averages From National Visitor Use Monitoring: Round 2

surveyed each year in the 5 years of Round 2 (table 1). More than 105,000 individuals sampled on those forests were deemed eligible and completed a basic survey,1

and 33,713 completed the economic supplemental survey. 

Spending Profile Estimation 

Analysis Considerations 

The spending analysis involved several decisions related to (1) identifying local 

visitors, (2) identifying outlier observations, (3) identifying visitors whose primary 

trip purpose was something other than recreating on the national forest, (4) determining the appropriate weights to place on individual observations, and (5) determining how to treat recreation visits with the primary purpose of downhill skiing. 

Local visitors— 

Locals were defined as those claiming to have traveled 60 mi or less from home to 

the recreation interview location. In Round 1, visitors were classified as “locals” if 

the centroid of their reported home ZIP code was within 30 straight-line miles of 

the boundary of the visited national forest. In year 4 of Round 1, a travel distance 

question was added to the basic survey, and analysis indicated that a travel distance 

to the site of 50 to 60 mi approximated a ZIP code proximity to the national forest 

boundary of 30 straight-line miles (Stynes and White 2005a). 

Outliers and contaminants— 

The criteria adopted here to identify outliers are meant to reduce the likelihood of 

including both contaminant observations and true outliers when estimating spending averages. Contaminants are observations that do not belong to the population or 

are erroneous observations. Recreation visitors completing an NVUM survey were 

asked to report only expenses that occurred within 50 mi of the interview site and 

that were related to the current recreation trip. A survey observation that included 

spending that actually occurred outside the 50-mi radius around the recreation site 

or spending from another recreation trip would be a contaminant. Likewise, an 

observation that had a misplaced decimal point in a reported expense (i.e., 1,000.00 

dollars versus 10.00) would be considered a contaminant. 

An outlier is an observation that does belong to the population under study but 

has undue influence on the estimation of the sample mean given the size of the 

sample. For example, some day visitors may spend $800 during a recreation trip to 

the national forest, but such spending is uncommon, and the vast majority of 

1

 This figure excludes those who stated they were not recreating on the forest but did 

choose their travel route to view the forest. These individuals count as recreation visits but 

were ineligible to complete a basic survey.
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visitors spend substantially less or nothing at all (Stynes and White 2006). When 

sample sizes are small, outlier observations can significantly influence the estimate of the sample mean. See Stynes and White (2006) for additional discussion of 

outliers and contaminants in the context of measuring recreation visitor spending.

Three rules, related to length of stay, party size, and total spending, were 

developed to remove likely outliers and contaminants. Collectively, these rules 

exclude 1,801 cases from the analysis (table 2). Respondents stating that they stayed 

overnight away from home in the local forest area for more than 30 nights were 

excluded. Individuals on long trips have greater difficulty in accurately recalling 

trip spending, and some appear to have reported expenses beyond 50 mi of the 

recreation site (e.g., Rylander et al. 1995). Respondents recreating in parties of eight 

or more individuals were excluded owing to likely problems in estimating expenses 

for everyone in the party.

Respondents reporting spending of $500 or more per night or a total of $500 

or more in sporting goods expenditures in the local forest area were also excluded. 

Some of these respondents are likely contaminants with misplaced decimal points, 

and others are true outliers that would influence the estimates of sample means. 

Omitting cases with high reported expenditures on sporting goods was designed 

to omit purchases of durable goods. The rule adopted for excluding visitors with 

reported high spending differs from that used in Round 1. The Round 2 data allow 

us to place individual spending on a per-day/night basis. Using per-day/night 

spending to identify spending outliers is an improvement over the approach used in 

Round 1 because those groups with high spending only as a result of a longer trip 

now remain in the sample. See appendix D of White and Stynes 2010a for additional analysis on the criteria used in defining all outliers. 

A fourth rule removed 82 cases that did not include a reported travel distance 

(used to classify respondents as locals or nonlocals). Some foreign visitors did not 

report a distance traveled but were included in the analysis and were classified as 

nonlocals. Additionally, visitors who failed to report a travel distance but were classified as “nonprimary” visitors (see below) were included in the analysis. 

Table 1—National forests sampled and number of respondents in the 5 years of 

Round 2 of National Visitor Use Monitoring

2005 2006 2007 2008 2009 Total

 Number

National forests sampled 24a 23 24 27 25 123

Basic survey respondents 24,695 20,001 22,904 17,925 19,991 105,516

Economic survey respondents 7,932 6,405 7,257 5,777 6,342 33,713

a

 Spring Mountain National Recreation Area on the Humboldt-Toiyabe National Forest was sampled in calendar 

year 2005 while the remainder of the Humboldt-Toiyabe National Forest was sampled in fiscal year 2006.
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Estimation of National Forest Visitor Spending Averages From National Visitor Use Monitoring: Round 2

Table 2—Economic cases excluded from analysis

Factor 2005 2006 2007 2008 2009 Total

 Number

Outliers and contaminants:

Nights in the local area > 30 58 23 62 24 37 204

People per vehicle > 8 143 93 109 85 83 513

Spending per night > $500 or 

sporting good expenditures > $500 291 155 204 255 179 1,084

 Total 492 271 375 364 299 1,801

Missing distance traveleda 22 11 10 24 15 82

Total 514 282 385 388 314 1,883

a In total, 100 cases had missing travel distances. Of these, 10 were removed from analysis as outliers and appear 

in those totals. Of the remaining 90 cases, 8 were classified in the nonprimary visitor segment—a segment not 

requiring differentiation into local and nonlocal visitors. Those eight cases were included in the analysis. The 

final 82 cases missing a travel distance were excluded from analyses involving the trip segments.

Trip purpose— 

Only those claiming to be traveling away from home primarily for the purpose of 

recreating on the national forest are classified as “primary purpose” visitors and 

are distributed to the six primary purpose visitor segments (i.e., nonlocal day trip, 

local overnight national forest, etc.). Visitors stating that their primary reason for 

being away from home was to recreate somewhere other than the national forest, 

visit family/friends, complete business, or for some other reason are classified in 

the “nonprimary” trip segment. The spending of individuals in the “nonprimary” 

trip segment would generally be excluded from economic contribution and impact 

analyses (Crompton et al. 2001). In Round 1, the question employed to gauge trip 

purpose was phrased in a manner that did not allow for identification of all individuals whose purpose for being away from home was something other than visiting the national forest, although that was the intent. In year 4 of Round 1, analysis 

of the revised trip purpose question indicated that approximately 5 percent of the 

Round 1 respondents were not appropriately classified as “nonprimary” under the 

original question (Stynes and White 2005a).

Weighting scheme— 

Survey data collected from a random sample of people are often weighted to ensure 

that the sample is representative of the group of people covered by the sample. For 

NVUM, there are two weighting schemes used in analyses. The first, exposure 

weighting, is used to correct the collected sample for overrepresentation of those 

who recreate at multiple sites during the visit. Sampling under NVUM occurs at 

specific sites selected randomly on any given day. To have the opportunity to be 

sampled on any given day, a recreationist must “correctly choose” to recreate at 
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the specific site undergoing NVUM sampling. Most national forest visitors recreate at just one site on their visit—meaning those visitors have only one chance to 

“correctly choose” a site undergoing NVUM sampling. Visitors who recreate at 

more than one site have more than one chance at “correctly” selecting an NVUM 

sampling site to recreate. As a consequence, those who visit more recreation sites 

during their visit are overrepresented in an unweighted sample. Exposure weighting 

is important because those who recreate at multiple sites have different recreation 

behavior than visitors who recreate at just one site.

The second weighting scheme used in NVUM is national visit expansion 

weighting (or referred to here simply as case weights). Under NVUM, the sites 

and areas of the national forest are classified into strata for sampling. In most 

cases, each stratum receives roughly the same number of opportunities for NVUM 

sampling. However, the strata differ in the amount of recreation use they experience. That differing recreation use means that the ratio of individuals sampled 

to the amount of recreation use differs across the strata. In a simplified example, 

stratum A may have yielded five visitor interviews and have recreation use of 1,000 

visits. Stratum B may have yielded 10 visitor interviews and have recreation use 

of 5,000 visits. Stratum B has five times the recreation use of Stratum A, but only 

twice the number of recreation interviews. The resulting visitor samples from strata 

A and B do not reflect the pattern of use across the strata. The case weight applied 

to respondents in each stratum adjusts the sample to be representative of the amount 

of use in each stratum. In this simplified example, the case weights applied to 

each respondent in stratum A would be 200 (1,000 visits/five interviews). The case 

weight assigned to each respondent sampled in stratum B would be 500 (5,000 visits/10 interviews). Although not shown in this simplified example, the case weights 

also incorporate the expansion weights described above. 

Downhill skiers— 

Recreation visits by individuals whose primary recreation activity is downhill skiing account for about 16 percent of all national forest visits (see table 30 in app. 2). 

Generally, downhill skiers spend more than individuals engaged in other recreation 

activities. In Round 1, downhill skiers were included in the sample when developing the general trip spending averages (distinct spending profiles applicable only to 

downhill skiers were also estimated in Round 1). The Round 2 economic sample 

includes a much higher percentage of downhill skiers than in Round 1. If left in 

the sample, the downhill skiers inflate the general trip spending estimates. In 

particular, spending in the “entry fees” category is very sensitive to the inclusion 

of downhill skiers. Given their influence on spending averages, we have excluded 

downhill skiers when estimating the general spending averages and instead 
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Estimation of National Forest Visitor Spending Averages From National Visitor Use Monitoring: Round 2

developed separate spending profiles for downhill skiers. The skier profiles can 

be used when conducting economic analyses related to downhill ski facilities and 

downhill ski recreation. The general profiles, omitting downhill skiers, will better 

apply to applications unrelated to downhill skiing or those facilities. 

Over 7,600 NVUM respondents claimed downhill skiing was their primary 

recreation activity (table 3). Approximately 2,400 downhill skiers completed an 

economic survey. About 10 percent of those skiers were excluded as outliers or 

contaminants, the majority because of reported high spending. Skier spending 

outliers are most frequently in the nonlocal overnight segment. The rate of outlier 

exclusion in the downhill skier cases was higher than that found for the economic 

sample in general. Relaxing the outlier criteria for downhill skiers would increase 

the estimates of downhill skier spending. 

Visitor Segments 

A primary objective of the spending analysis is to estimate spending profiles for a 

set of meaningful segments of recreation visitors to the national forest. To be useful, 

the segments must (1) be identifiable from the NVUM survey variables, (2) help to 

explain differences in spending across different applications, (3) be large enough 

to obtain adequate sample sizes in the survey, and (4) be meaningful to anticipated 

national forest management and policy applications. The segment shares reported 

here are estimated from all respondents who completed an NVUM basic survey. In 

Round 1, the segment shares were estimated largely from the economic subsample 

because the necessary questions were not included on the basic survey. 

Seven trip-type segments were identified in the analysis of Round 1 NVUM 

data, and we use these seven (also referred to as the “Basic 7”) in this section: 

1. Nonlocal day trips: nonlocal residents on day trips to the national forest

2. Nonlocal OVN-NF: nonlocal residents staying overnight on the national forest

3. Nonlocal OVN: nonlocal residents staying overnight off the national forest in the 

local area 

4. Local day trips: local residents on day trips to the national forest

5. Local OVN-NF: local residents staying overnight on the national forest

6. Local OVN: local residents staying overnight off the national forest in the local 

area 

7. Nonprimary: visits where recreating on the national forest is not the primary trip 

purpose 

Local visitors are those who have traveled 60 mi or less from home to reach the 

recreation site. Day visitors are those who did not report a night spent in the local 

forest area. Visitors in this segment include those who did not spend a night away 
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general technical report pnw-gtr-883

from home as well as those passing through the forest area and spending a night 

away from home outside the local forest area. 

Overnight national forest visitors are those who spent a night away from 

home and reported using a cabin, developed campground, or primitive area on the 

national forest (or some combination of those three) for lodging. This definition 

of OVN-NF differs from that used in Round 1 where only those claiming to have 

spent “last night on the national forest” were classified into the OVN-NF segment. 

The question used in Round 1 likely erroneously included some individuals who 

actually stayed overnight off the forest in private accommodations because the 

respondent was unable to differentiate between spending the night on national 

forest land and in the area of the national forest. The revised question on lodging 

types in Round 2 appears to lead to a more correct classification. Visitors in the 

overnight off-forest (OVN) category are those who spent a night away from home 

in the local forest area and reported using any lodging off the national forest or 

some combination of lodging on and off the national forest. The OVN segment 

also includes a few respondents, otherwise classified as on day trips, who reported 

lodging expenses. 

These seven trip-type visitor segments explain about 27 percent of the variation 

in trip spending by travel parties (White and Stynes 2008). The average spending 

estimated for these trip segments is statistically different between segments, with 

the exception of the local OVN-NF and local OVN combination. These trip segments have proven useful in USDA FS economic analyses and appear to now be 

intuitive to agency economists and analysts. 

National-Level Segment Shares 

The national-level visitor segment shares are estimated from all cases, not just those 

visitors completing the economic survey. Day trips by individuals who live in the 

Table 3—Downhill skiing respondents to the basic and economic surveys

Respondents and missing distance traveled

Number

All downhill skiing respondents 7,667

Downhill skiing respondents completing the economic survey 2,467

Respondents excluded as outliers and contaminants:

Nights in the local area > 30 13

People per vehicle > 8 56

Spending per night > $500 or sporting good expenditures > $500 170

 Total 239

Missing distance traveled 9

Total 248
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Estimation of National Forest Visitor Spending Averages From National Visitor Use Monitoring: Round 2

local forest area are the most common type of national forest visit (49 percent of all 

forest visits) (fig. 1). Local visits collectively account for more than half of all visits 

to the national forest. Visits by nonlocals are most frequently overnight trips away 

from home with nights off the national forest. Finally, approximately one of every 

eight national forest visits is a trip where recreation on the national forest is secondary to some other reason for being away from home. Approximately 81 percent of 

nonprimary visits are associated with individuals who live outside the local forest 

area. 

The percentage of visits that are classified into each trip segment (the “segment 

shares”) differs depending on which weighting scheme is applied to the visitor survey data (table 4). Local day trip segment shares are most responsive to the chosen 

weighting scheme, increasing from a 37 percent share of visits unweighted to a 49 

percent share under the case weights. The exposure weight corrects the sample for 

overrepresentation of those visits involving recreation at multiple sites and thus 

having a greater opportunity to be sampled. As such, exposure weighting reduces 

the share of nonlocal overnight trips (those most likely to visit multiple sites) and 

increases the share of local day trips (those less likely to visit multiple sites). The 

case weights (which include the exposure weights) adjust the sample to be representative of the number of visits to the forest. Case weighting further increases 

the percentage of local day visits (those visits most likely to occur in the GFA) and 

reduces the percentage of nonlocal OVN-NF visits. 

The trip segment shares are fairly stable across all years of Round 2 (table 5). 

The nonlocal OVN and nonprimary segment shares differed the most from year to 

year, which is reasonable given that the extent of off-forest accommodations (both 

Figure 1—Trip-type segment distribution, all 5 years of National Visitor 

Use Monitoring Round 2.

Local visits collectively 

account for more than 

half of all visits to the 

national forest.
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Table 4—National forests visitor segment distribution, all 5 years 

of Round 2

Number Exposure Case

Trip segmenta of cases Unweighted weighted weights

– – – – – – – – – Percent – – –– – – – – – 

NL day 11,042 10 11 10

NL OVN-NF 16,425 15 12 9

NL-OVN 13,189 12 11 14

Local day 38,481 37 42 49

Local OVN-NF 6,734 6 6 4

Local OVN 1,324 1 1 1

Nonprimary 19,466 19 17 13

 Total 106,661 100 100 100

a

 NL = nonlocal, OVN = overnight, NF = national forest. 

Table 5—Trip segment shares, all years of Round 2a

 Five

Trip segmentb 2005 2006 2007 2008 2009 years

Percent

NL day 12 10 10 7 11 10

NL OVN-NF 8 10 10 9 9 9

NL-OVN 18 11 20 9 9 14

Local day 42 47 43 58 55 49

Local OVN-NF 3 3 4 5 5 4

Local OVN 1 1 2 1 1 1

Nonprimary 16 18 11 11 10 13

 Total 100 100 100 100 100 100

a

 Estimated from the full sample using the case weights.

b

 NL = nonlocal, OVN = overnight, NF = national forest.

privately owned businesses and the private homes of friends and relatives) and 

other attractions around the national forest are variable across the individual forests 

sampled from year to year. The local day segment shares also differed year to year 

and are likely responsive to changes in size of populations proximate to the national 

forest sampled each year. 

The inclusion or exclusion of downhill skiing visits yields differing segment 

shares (table 6). Excluding visits where the primary activity is downhill skiing 

yields a segment share mix that has fewer visits in the nonlocal OVN segment and 

more visits in the local day segment compared to the general segment share mix. 

The segment shares excluding downhill skiers are most appropriate for spending 

analyses that do not involve downhill skier visits. For analyses aimed specifically 
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Estimation of National Forest Visitor Spending Averages From National Visitor Use Monitoring: Round 2

Table 6—Segment shares estimated for all visits, nonskiers, and skiers onlya

Nonlocal Local

Visits Day OVN-NF OVN Day OVN-NF OVN Nonprimary Total

 Percent

All visits (including skiers) 10 9 14 49 4 1 13 100

Nondownhill skiing visits 9 10 9 51 5 1 15 100

Downhill skiing visits 16 b 41 35 b 2 6 100

a

 Estimated from the full sample using case weights. OVN = overnight, NF = national forest.

b

 For skiers, the OVN-NF visits are included in the OVN segments.

at downhill skier visits, analysts should use the downhill ski visit segment shares. 

Compared to general segment shares, skier visits are more likely to be nonlocal 

visits and are most likely to be overnight trips. Conversely, fewer skier visits are 

associated with locals, compared to the national shares. Nonprimary visits comprise 

a smaller share of skier visits than other activities on national forests. Forest-level 

segment shares are included in appendix 2. 

Nights Away From Home 

Revised questions on the Round 2 survey allowed us to estimate both the average 

nights away from home and the average nights in the local forest area. Like the segment shares, we compute average nights for visits not involving downhill skiing and 

for only downhill skiing visits (table 7). For those visits where the primary activity 

was not downhill skiing, individuals on overnight trips away from home spend 

on average 2.3 nights away from home, 1.3 of which are spent within 50 mi of the 

national forest (table 7). Those on nonlocal OVN trips spend the greatest number 

of nights away from home (6.1) and within the local area (4.4) while those on local 

OVN-NF trips spend the least number of nights away from home (2.4). Those on 

nonprimary trips have the greatest disparity between the nights spent away from 

home and the nights spent in the local forest area—reflecting the lesser importance 

of the national forest in these trips. Within trip type, locals spend fewer nights away 

from home than nonlocals, as expected. 

On average, downhill skiers on overnight trips spend about 2.6 nights away 

from home, 2.3 of which are within 50 mi of the forest (table 7). Nonlocals spend 

the greatest number of nights in the local area during their visit (4.9). Downhill 

skiers have a slightly longer average number of nights in the local area compared 

to other national forest visitors. This is intuitive given the nature of the downhill 

skiing trip and the expenditures required for travel and access to the ski area (e.g., 

airfare, lift tickets, etc.).
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Table 7—Average number of nights away from home and in the local forest area for national 

forest visitorsa

 Nonlocal Local

OVN-NF OVN OVN-NF OVN Nonprimary All visits

 Number of nights

Nondownhill skiing visits:

Nights away from home 3.9 6.1 2.4 4.0 7.9 2.3

Nights in the local area 3.2 4.4 2.4 3.7 2.9 1.3

Only downhill skiing visits:

Nights away from home b 5.3 b 4.4 5.5 2.6

Nights in the local area b 4.9 b 4.4 3.9 2.3

a

 Estimated from the full sample using case weights. The average nights for all visits including skiers did not differ appreciably 

from the nondownhill skiing visits averages and are not shown here. OVN = overnight, NF = national forest.

b

 For skiers, the OVN-NF visits are included in the OVN segments.

Spending Profiles 

Spending profiles describe the average amount spent within a set of spending 

categories for a particular subgroup of visitors. The unit of analysis for the spending profiles presented here is the party and covers all expenses by the travel party 

within 50 mi of the interview site during the trip to the local forest area. Spending 

reported in the observations for each NVUM sample year were price adjusted to 

2009 using a distinct Bureau of Labor Statistics price index for each spending 

category. Downhill skiers have distinct spending patterns and those visitors are 

excluded in the calculation of the initial spending profiles. Average spending of 

downhill skiers is reported in separate spending profiles. 

Basic 7 Trip Spending 

The average expenditures per party per trip for national forest visitors in 2009 

ranges from $33 for local visitors on day trips to $514 for nonlocal visitors on OVN 

trips (table 8). The confidence intervals around our estimates (at the 95 percent 

level) range from 3 percent to 15 percent across the seven segments. For day trips, 

spending on gas and oil is the greatest single expense followed by spending on food 

in either restaurants or grocery stores depending on whether the visitor is a local. 

Lodging expenses are the greatest single expenditure for nonlocal visitors on OVN 

trips, followed by spending in restaurants and for gas and oil. Spending in grocery 

stores and for gas and oil are the greatest expenditures for local visitors on OVN 

trips. The greatest expenditure for nonlocals staying overnight on the national forest 

is groceries, followed by gasoline and oil. The opposite pattern is found for locals 

staying on the national forest. The spending of nonprimary visitors is similar to that 

of nonlocal OVN visitors.

Average expenditures 

for national forest 

visitors ranges from 

$33 for local visitors 

on day trips to $514 for 

nonlocal visitors on 

OVN trips.
13

Estimation of National Forest Visitor Spending Averages From National Visitor Use Monitoring: Round 2

Table 8—National forest visitor spending profiles by trip-type segment and spending category, dollars 

per party per tripa

Spending Nonlocal Local Non- All 

categories Day OVN-NF OVN Day OVN-NF OVN primary visitsb

 Dollars

Motel 0.00 33.54 151.77 0.00 5.36 33.84 114.86 39.75

Camping 0.00 26.81 18.85 0.00 23.63 17.11 11.95 7.72

Restaurant 15.30 26.31 111.34 5.19 6.78 33.99 88.62 34.16

Groceries 8.63 55.65 68.29 6.31 67.30 54.54 43.36 27.40

Gas and oil 23.16 52.67 71.17 12.83 37.57 40.18 48.40 31.50

Other 

transportation 0.58 1.83 3.98 0.13 0.49 1.09 3.26 1.30

Entry fees 4.56 8.93 18.39 2.17 3.76 6.86 11.11 6.56

Recreation and 

entertainment 4.34 7.70 27.13 1.50 3.50 5.67 16.71 8.03

Sporting goods 2.94 12.19 15.18 4.16 11.23 12.85 6.44 6.97

Souvenirs and other 

expenses 3.15 7.80 28.10 0.72 2.85 6.87 25.83 8.84

 Total 62.65 233.44 514.20 33.02 162.48 212.99 370.54 172.24

Sample size (unweighted) 2,224 4,276 3,062 9,832 1,809 445 4,737 26,385

Standard deviation of total 71 364 646 49 184 335 605 n/a

n/a = not applicable.

a

 Outliers are excluded and exposure weights are applied in estimating spending averages. All figures expressed in 2009 dollars. These averages exclude visitors who claimed their primary activity was downhill skiing. When completing analyses involving skiers, refer to subsequent 

tables on average skier spending. OVN = overnight, NF = national forest. 

b

 The all-visit averages are computed as a weighted average of the columns using the national trip segment shares as weights.

Average lodging expenses for OVN and OVN-NF visitors may appear low. 

However, visitors in both of those segments use a variety of lodging types that have 

a range of costs. Some lodging (e.g., homes of friends/relative, owned seasonal 

homes, and national forest roadsides) will be used free. The shown averages reflect 

this mix of costs. In a later section, we report spending profiles for visitors engaged 

in a variety of lodging types. In those profiles, average expenditure for motels and 

camping are more consistent with average room rates and camping fees. 

Dividing the spending averages for trips involving overnight stays shown in 

table 8 by the average number of nights in the local area for each segment (table 7) 

gives average party spending on a per-day/night basis (table 9). For nonlocal OVN 

visitors, average spending is a little less than $117 per night. Local OVN visitors 

spend about $58 per night, on average. On a per-day/night basis, the spending of 

nonlocal day, local OVN, local OVN-NF, and nonlocal OVN-NF visitors is similar, 

although there are differences in spending patterns within specific expenditure 

categories. On a per-day/night basis, the spending of nonprimary visitors is the 

greatest of all the segments—reflecting the general tourism spending patterns of 

these visitors. 
14

general technical report pnw-gtr-883

Table 9—National forest visitor spending profiles by trip-type segment and spending category, dollars 

per party per day/nighta

Spending Nonlocal Local Non- All

categories Day OVN-NF OVN Day OVN-NF OVN primary visitsb

 Dollars

Motel 0.00 10.48 34.49 0.00 2.23 9.15 39.61 11.10

Camping 0.00 8.38 4.28 0.00 9.85 4.62 4.12 2.33

Restaurant 15.30 8.22 25.30 5.19 2.83 9.19 30.56 12.53

Groceries 8.63 17.39 15.52 6.31 28.04 14.74 14.95 10.91

Gas and oil 23.16 16.46 16.18 12.83 15.65 10.86 16.69 15.25

Other transportation 0.58 0.57 0.90 0.13 0.20 0.29 1.12 0.46

Entry fees 4.56 2.79 4.18 2.17 1.57 1.85 3.83 2.93

Recreation and 

entertainment 4.34 2.41 6.17 1.50 1.46 1.53 5.76 3.07

Sporting goods 2.94 3.81 3.45 4.16 4.68 3.47 2.22 3.67

Souvenirs and other 

expenses 3.15 2.44 6.39 0.72 1.19 1.86 8.91 3.01

 Total 62.65 72.95 116.86 33.02 67.70 57.56 127.77 65.27

Sample size (unweighted) 2,224 4,276 3,062 9,832 1,809 445 4,737 26,385

a

 Outliers are excluded and exposure weights are applied in estimating spending averages. All figures expressed in 2009 dollars. These 

averages exclude visitors who claimed their primary activity was downhill skiing. When completing analyses involving skiers, refer to 

subsequent tables on average skier spending. OVN = overnight, NF = national forest. b

 The all-visit averages are computed as a weighted average of the columns using the national trip segment shares as weights.

High and Low Spending Averages 

As in Round 1, sample sizes at the forest level are generally too small to reliably 

estimate spending averages for all seven visitor segments for individual national 

forests. For many forests, the national-level spending profiles presented in the 

previous section are applicable and can be combined with segment share estimates 

for the specific forest under consideration (table 23) to estimate total visitor spending for the forest (see app. 1 for a detailed example of the steps to estimating total 

spending). However, visitor spending can differ from place to place owing to the 

extent of local spending opportunities and local prices, and to accommodate these 

differences, we developed spending profiles for areas with above-average and 

below-average spending. 

Following the same approach used in Round 1, we grouped observations from 

forests with above- or below-average spending (table 22) to develop “high” and 

“low” spending profiles. Forests with above- or below-average spending were identified by comparing spending averages for each forest with the national averages.2

2

 Here we construct a 95 percent confidence interval around forest estimates to test for 

statistical differences. In Round 1, we used an 80 percent confidence interval consistent 

with other NVUM research at the time.
15

Estimation of National Forest Visitor Spending Averages From National Visitor Use Monitoring: Round 2

Day and overnight visitor spending averages (excluding nonprimary visitors and 

downhill skiers) were estimated based on the sample of visitors on each forest. 

To control for differences in the visitor mix across forests, a standardized overall 

average was computed for each forest, assuming a fixed mix of 60 percent day trips 

and 40 percent overnight trips. The standardized spending average for each forest 

was compared to the national standardized spending average (see Stynes et al. 2002 

for additional discussion of this analysis). Of the 123 forests sampled in the 5 years 

of Round 2, 67 have spending that was not found to be statistically different from 

the national average. Of those national forests where spending did differ from the 

national average, 16 forests were classified as “above-average spending” and 40 

forests as “below-average spending.” 

On average, the high and low spending profiles are approximately 40 percent 

higher/lower than the average spending profile (tables 10 through 14). The spending 

of local day visitors does not follow this pattern and is lower at “high” spending 

forests than “low” spending forests. In many cases, a forest identified as a high 

spending area (table 22) should use the profiles in table 10 or table 13 instead of 

the national averages in tables 8 and 9. Similarly, forests identified as low spending 

areas (table 22) should use the averages in table 11 or table 14 for many analyses. 

The high and low spending profiles also can be used for economic analysis aimed at 

specific geographic areas around a national forest with higher or lower than average 

spending opportunities or prices. Areas near major tourist destinations or in proximity or easy access to commercial areas and spending opportunities can generally 

expect above-average visitor spending, while sites in more remote, rural areas will 

likely experience below-average spending. On many national forests there will be 

both “high” and “low” spending areas. An assessment of nearby spending opportunities and prices can help in deciding between the average, high, or low spending 

profiles for a particular application. 

On average, visitors to high spending forests spend a greater number of nights 

away from home than those visiting low spending forests (table 12). This is reasonable given the likely greater number of spending opportunities and recreation 

activities around high spending forests. As with the national spending profile, those 

on nonlocal trips spend a greater number of nights away from home than those on 

local trips. Visitors on nonprimary trips spend the greatest number of nights away 

from home. 

Downhill Skier Visitor Spending 

The trip spending of downhill skiers on day trips is about double that of day visitors 

on other national forest recreation trips (table 15). Similarly, nonlocal overnight 
16

general technical report pnw-gtr-883

Table 10—High spending profiles by trip-type segment and spending category, dollars per party

per tripa

Nonlocal Local Non- All

Spending categories Day OVN-NF OVN Day OVN-NF OVN primary visitsb

 Dollars

Motel 0.00 74.20 243.61 0.00 13.50 77.02 176.17 65.00

Camping 0.00 27.20 17.95 0.00 18.82 6.16 9.45 7.00

Restaurant 25.58 50.03 184.51 5.29 5.01 83.70 137.75 54.43

Groceries 8.60 68.47 81.76 4.22 79.69 87.82 50.67 31.19

Gas and oil 28.32 76.57 92.15 10.31 38.21 40.43 55.95 36.88

Other transportation 0.17 1.84 2.79 0.38 3.41 5.39 5.74 1.70

Entry fees 5.93 12.63 32.60 1.79 0.75 11.26 23.30 10.34

Recreation and 

entertainment 6.88 9.24 47.38 1.10 2.99 6.16 27.79 12.49

Sporting goods 2.94 18.02 21.35 3.92 17.21 17.41 10.21 9.02

Souvenirs and other 

expenses 9.61 14.17 57.85 0.79 2.06 12.38 45.01 16.78

 Total 88.02 352.37 781.95 27.81 181.65 347.74 542.04 244.82

Sample size (unweighted) 213 471 777 1,469 152 46 1,048 4,176

Standard deviation of total 92 525 788 50 190 617 671 n/a

n/a = not applicable.

a

 Outliers are excluded and exposure weights are applied in estimating spending averages. All figures expressed in 2009 dollars. These averages exclude visitors who claimed their primary activity was downhill skiing. When completing analyses involving skiers, refer to subsequent 

tables on average skier spending. OVN = overnight, NF = national forest.

b

 The all-visit averages are computed as a weighted average of the columns using the national trip segment shares as weights.

Table 11—Low spending profiles by trip-type segment and spending category, dollars per party

per tripa

Nonlocal Local Non- All

Spending categories Day OVN-NF OVN Day OVN-NF OVN primary visitsb

 Dollars

Motel 0.00 6.82 77.42 0.00 3.02 10.46 64.59 20.07

Camping 0.00 23.26 22.31 0.00 26.28 27.31 10.75 7.94

Restaurant 11.95 14.45 52.15 4.21 5.63 15.49 44.53 18.03

Groceries 8.29 47.62 48.48 6.41 66.02 50.01 26.63 21.65

Gas and oil 21.40 45.87 56.89 13.02 35.72 37.24 39.39 27.53

Other transportation 0.81 0.28 0.92 0.00 0.21 0.00 0.46 0.30

Entry fees 4.42 5.71 7.22 2.19 3.13 3.41 5.18 3.87

Recreation and entertainment 4.62 5.50 11.78 1.72 4.32 4.43 5.47 4.38

Sporting goods 2.72 7.92 9.03 4.26 11.97 14.78 2.76 5.32

Souvenirs and other expenses 2.04 4.33 12.13 0.51 3.28 4.46 12.33 4.32

 Total 56.24 161.75 298.34 32.33 159.58 167.57 212.08 113.42

Sample size (unweighted) 896 1,476 699 3,704 803 169 1,128 8,875

Standard deviation of total 62 184 355 45 177 198 443 n/a

n/a = not applicable.

a

 Outliers are excluded and exposure weights are applied in estimating spending averages. All figures expressed in 2009 dollars. These averages exclude visitors who claimed their primary activity was downhill skiing. When completing analyses involving skiers refer to subsequent 

tables on average skier spending. OVN = overnight, NF = national forest.

b

 The all-visit averages are computed as a weighted average of the columns using the national trip segment shares as weights.
17

Estimation of National Forest Visitor Spending Averages From National Visitor Use Monitoring: Round 2

Table 12—Average number of nights away from home and in the local forest area for 

national forest visitors to high- and low-spending forestsa

 Nonlocal Local Non- All

Spending OVN-NF OVN OVN-NF OVN primary visits

High spending:

Nights away from home 5.2 7.6 2.2 5.0 9.7 4.0

Nights in the local area 3.7 4.9 2.1 4.3 3.6 2.0

Low spending:

Nights away from home 3.0 5.6 2.5 3.7 7.3 1.5

Nights in the local area 2.7 4.0 2.4 3.5 2.3 0.9

a Estimated from the full sample using case weights and excluding downhill skiers. OVN = overnight, NF = national 

forest.

Table 13—High spending profiles by trip-type segment and spending category, dollars per party per 

day/nighta

Nonlocal Local Non- All

Spending categories Day OVN-NF OVN Day OVN-NF OVN primary visitsb

 Dollars

Motel 0 20.05 49.72 0 6.43 17.91 48.94 15.56

Camping 0 7.35 3.66 0 8.96 1.43 2.62 1.89

Restaurant 25.58 13.52 37.66 5.29 2.38 19.47 38.26 16.90

Groceries 8.60 18.51 16.69 4.22 37.95 20.42 14.07 10.48

Gas and oil 28.32 20.69 18.81 10.31 18.19 9.40 15.54 15.22

Other transportation 0.17 0.50 0.57 0.38 1.62 1.25 1.60 0.61

Entry fees 5.93 3.41 6.65 1.79 0.36 2.62 6.47 3.59

Recreation and 

entertainment 6.88 2.50 9.67 1.10 1.42 1.43 7.72 3.88

Sporting goods 2.94 4.87 4.36 3.92 8.20 4.05 2.84 4.00

Souvenirs and other 

expenses 9.61 3.83 11.81 0.79 0.98 2.88 12.50 5.04

 Total 88.02 95.24 159.58 27.81 86.50 80.87 150.57 77.18

Sample size (unweighted) 213 471 777 1,469 152 46 1,048 4,176

a

 Outliers are excluded and exposure weights are applied in estimating spending averages. All figures expressed in 2009 dollars. These 

averages exclude visitors who claimed their primary activity was downhill skiing. When completing analyses involving skiers, refer to 

subsequent tables on average skier spending. OVN = overnight, NF = national forest.

b

 The all-visit averages are computed as a weighted average of the columns using the national trip segment shares as weights.
18

general technical report pnw-gtr-883

Table 14—Low spending profiles by trip-type segment and spending category, dollars per party per 

day/nighta

Nonlocal Local Non- All

Spending categories Day OVN-NF OVN Day OVN-NF OVN primary visitsb

 Dollars

Motel 0 2.53 19.36 0 1.26 2.99 28.08 6.67

Camping 0 8.62 5.58 0 10.95 7.80 4.67 2.68

Restaurant 11.95 5.35 13.04 4.21 2.35 4.43 19.36 8.22

Groceries 8.29 17.64 12.12 6.41 27.51 14.29 11.58 10.00

Gas and oil 21.40 16.99 14.22 13.02 14.88 10.64 17.13 14.97

Other transportation 0.81 0.10 0.23 0 0.09 0 0.20 0.15

Entry fees 4.42 2.11 1.81 2.19 1.30 0.97 2.25 2.31

Recreation and 

entertainment 4.62 2.04 2.94 1.72 1.80 1.26 2.38 2.29

Sporting goods 2.72 2.93 2.26 4.26 4.99 4.22 1.20 3.34

Souvenirs and other 

expenses 2.04 1.60 3.03 0.51 1.37 1.27 5.36 1.79

 Total 56.24 59.91 74.59 32.33 66.49 47.88 92.21 52.43

Sample size (unweighted) 896 1,476 699 3,704 803 169 1,128 8,875

a

 Outliers are excluded and exposure weights are applied in estimating spending averages. All figures expressed in 2009 dollars. These 

averages exclude visitors who claimed their primary activity was downhill skiing. When completing analyses involving skiers, refer to 

subsequent tables on average skier spending. OVN = overnight, NF = national forest.

b

 The all-visit averages are computed as a weighted average of the columns using the national-trip segment shares as weights.

Table 15—Per-trip spending profiles of downhill skiers, dollars per partya

Spending Nonlocal segments Local segments Non- All

category Day OVN Day OVNb primary visitsc

 Dollars

Motel 0 237.37 0 36.34 145.58 106.78

Camping 0 0.62 0 18.37 0.10 0.63

Restaurant 22.52 158.95 13.57 31.47 136.24 82.33

Groceries 4.60 75.86 3.49 51.01 52.59 37.24

Gas and oil 20.73 50.38 9.99 47.45 42.23 30.95

Other transportation 0 3.10 0.01 1.12 2.51 1.45

Entry fees 45.98 145.32 20.82 6.56 68.10 78.44

Recreation and 

entertainment 31.00 84.33 13.13 5.40 67.94 48.32

Sporting goods 5.32 22.04 3.13 12.62 12.06 11.96

Souvenirs and 

other expenses 1.85 20.75 0.77 6.81 16.99 10.23

 Total 132.00 798.72 64.91 217.14 544.34 408.31

Sample size (unweighted) 459 516 907 445 130 2,048

Standard deviation of total 103 822 82 338 623 552

a

 Outliers are excluded and exposure weights are applied in estimating spending averages. All figures expressed in 2009 

dollars. These averages are based on visitors sampled at ski areas, and analyses involving nonskier visits should refer to 

previous tables on national forest visitor average spending. For downhill skiers, we have combined the overnight (OVN) 

national forest and OVN segments into a single OVN segment.

b

 The sample size for local overnight visitors sampled at ski areas was insufficient and here we substitute the local OVN 

averages from the national spending profile. c

 The all-visit averages are computed as a weighted average of the columns using the skier segment shares as weights.
19

Estimation of National Forest Visitor Spending Averages From National Visitor Use Monitoring: Round 2

visitors who are downhill skiing spend about 50 percent more than nonlocal 

overnight visitors doing other activities on national forest trips. The additional 

spending by downhill skiers can primarily be traced to greater spending on entry 

fees, recreation and entertainment, and restaurants. In addition, downhill skiers 

on nonlocal overnight trips spend more on lodging than other nonlocal overnight 

visitors. Across all trip types, downhill skiers tend to spend less than other visitors 

on groceries and gas and oil. Note that expenses for season passes likely are not 

represented in these trip-specific spending averages. Similarly, lift tickets sold as 

part of a package deal may not have been reported separately by the respondent. 

Economic analyses that incorporate analyses of downhill skier spending should 

use tables 15 or 16 or reliable visitor spending figures available from other sources 

applicable to the study area. 

On a per-day/night basis, downhill skiers on overnight trips spend more money 

on lodging, more on groceries, and less on entry fees compared to downhill skiers 

on day trips (table 16). The greater expense of day visitors on entry fees may reflect 

overnight visitors purchasing package deals where lift tickets are not explicitly 

priced. Recall that the overnight segments include a mix of visitors using different 

Table 16—Per-day/night spending profiles of downhill skiers, dollars per partya

Nonlocal segments Local segments Non- All

Spending category Day OVN Day OVNb primary visitsc

 Dollars

Motel 0.00 48.44 0.00 8.26 37.33 22.27

Camping 0.00 0.13 0.00 4.18 0.03 0.14

Restaurant 22.52 32.44 13.57 7.15 34.93 23.89

Groceries 4.60 15.48 3.49 11.59 13.48 9.34

Gas and oil 20.73 10.28 9.99 10.78 10.83 11.89

Other transportation 0.00 0.63 0.01 0.25 0.64 0.31

Entry fees 45.98 29.66 20.82 1.49 17.46 27.88

Recreation and 

entertainment 31.00 17.21 13.13 1.23 17.42 17.68

Sporting goods 5.32 4.50 3.13 2.87 3.09 4.03

Souvenirs and

other expenses 1.85 4.24 0.77 1.55 4.36 2.60

 Total 132.00 163.00 64.91 49.35 139.57 120.03

Sample size (unweighted) 459 516 907 445 130 2,048

a

 Outliers are excluded and exposure weights are applied in estimating spending averages. All figures expressed in 2009 

dollars. These averages are based on visitors sampled at ski areas and analyses involving nonskier visits should refer to 

previous tables on national forest visitor average spending. For downhill skiers, we have combined the overnight (OVN) 

national forest and OVN segments into a single OVN segment.

b

 The sample size for local overnight visitors sampled at ski areas was insufficient, and here we substitute the local 

overnight averages from the national-spending profile.

c

 The all-visit averages are computed as a weighted average of the columns using the skier segment shares as weights.

Additional spending 

by downhill skiers can 

primarily be traced to 

entry fees, recreation 

and entertainment, and 

restaurants.
20

general technical report pnw-gtr-883

lodging types, some requiring lodging expenditures and others not, so the average 

lodging expenditure here may not be consistent with typical room rates in the area. 

Lodging-Based Segmentation 

The OVN and, to a lesser extent, the OVN-NF segments of the Basic 7 trip segments contain a mix of visitors using a variety of overnight lodging. A question 

regarding the type of lodging used during the trip included on the Round 2 survey 

allows us to further classify and better estimate spending for overnight visitors 

using different types of lodging. When respondents reported using multiple lodging types, they were placed in the most expensive lodging segment. For example, a 

number of respondents reported camping and use of a hotel/motel. Those respondents were classified in the “motel” segment. The lodging-based segments provide 

an alternative to the Basic 7 trip segments and will prove most useful when the 

economic analysis has a strong focus on overnight trips. Using the responses to the 

lodging question and extending from the Basic 7 trip segments yields 10 lodgingbased segments: 

1. Nonlocal day trips: nonlocal residents on day trips to the local forest area

2. Local day trips: local residents on day trips to the local forest area

3. National forest undeveloped: visitors lodging in the undeveloped area on 

the national forest

4. National forest developed: visitors lodging in a developed campground on 

the national forest

5. National forest cabin: visitors lodging in a cabin on the national forest

6. Motel: visitors staying in a rented hotel, cabin, condo, home, etc. off the 

national forest

7. Off-forest camp: visitors lodging in a campground off the national forest 

8. Private home: visitors staying at a private home of a friend or relative or an 

owned second home 

9. Other/multiple: visits with undesignated, missing, or multiple lodging types

10.Nonprimary: visits where recreating on the national forest is not the primary trip purpose 
21

Estimation of National Forest Visitor Spending Averages From National Visitor Use Monitoring: Round 2

Table 17—Segment shares for lodging-based segmentsa

All visits Nondownhill- Downhill

Segment (including skiers) skiing visits skiing visits

 Percent

Nonlocal day 10 9 16

Local day 48 51 34

National forest undeveloped 

camping 4 5 b

National forest developed 

camping 7 8 b

National forest cabin 1 2 1

Motel 8 4 27

Private campground 1 1 b

Private home 6 4 13

Other/multiple 2 2 2

Nonprimary 13 14 7

 Total 100 100 100

a

 Estimated using case weights and the full sample.

b

 Lodging types on the national forest are combined into a single segment, national forest cabin. No visits 

occurred in the off-forest camp segment.

The day trip and nonprimary segment shares for the lodging-based segments 

are unchanged from that found for the Basic 7 segments (table 17). Of the overnight 

visits, motel stays (including B&Bs, rented condos, etc.) are the most frequent 

lodging choice (8 percent of all visits) followed by developed campgrounds on the 

national forest (7 percent of visits) and private homes (6 percent of visits). The least 

common overnight lodging types for national forest visits are private campgrounds 

located off the national forest and national forest cabins. Excluding downhill skiers 

from the segment share estimation reduces the percentage of visits staying in motels 

and private homes and increases the percentage of visits staying on the national forest. Considering only downhill skiers, 27 percent of visits involve a stay in a motel 

with another 13 percent involving a stay in a private home. 

Lodging-Based Segment Spending Averages 

The day and nonprimary trip spending averages (table 18) are unchanged from that 

shown in table 8. Trip spending in the overnight segments ranges from $151 for 

those camping in the undeveloped portions of the forest to $700 for those staying overnight off-forest in motels. Those staying in private homes and camping 

off-forest spend about half that of individuals staying in motels off-forest. In the 

lodging-based segments, local visitors on overnight trips are not separated from 
22

general technical report pnw-gtr-883 Table 18—Per-trip national forest visitor spending profiles by lodging type segment and spending category, dollars per partya Spending Nonlocal Local National forest Private Private Other/ Non- All category day day Undeveloped Developed Cabin Motel campground home multiple primary visitsb

Dollars

Motel 0.00 0.00 3.46 3.14 220.10 312.30 29.49 32.20 73.11 114.86 46.16Camping 0.00 0.00 9.79 35.70 3.11 0.80 79.79 1.06 41.64 11.95 6.23Restaurant 15.30 5.19 14.12 13.81 74.00 153.41 55.55 101.66 59.32 88.62 37.93Groceries 8.63 6.31 47.25 63.25 68.13 53.77 74.81 86.68 68.57 43.36 28.15Gas and oil 23.16 12.83 46.24 45.80 61.66 69.56 83.64 67.29 61.29 48.40 32.10Other transp. 0.58 0.13 2.00 0.41 5.32 4.42 2.44 3.87 4.30 3.26 1.40Entry fees 4.56 2.17 5.58 7.29 7.86 24.23 16.43 14.79 14.10 11.11 7.03Recreation and 

entertainment 4.34 1.50 4.19 6.43 11.09 35.94 9.24 23.12 17.02 16.71 8.75

Sporting goods 2.94 4.16 15.12 10.14 14.10 12.68 22.17 16.50 14.26 6.44 7.09Souvenirs and

other expenses 3.15 0.72 3.11 5.61 17.63 33.00 23.30 26.97 15.53 25.83 9.51

Total 62.65 33.02 150.85 191.59 483.00 700.11 396.87 374.15 369.12 370.54 184.37

Sample size 

unweighted 2,224 9,832 1,329 4,031 629 1,257 413 887 659 4,737 25,998

Standard

deviation of total 71 49 242 245 590 717 429 543 623 605 n/a

n/a = not applicable.a Outliers are excluded and exposure weights are applied in estimating spending averages. All figures expressed in 2009 dollars. These averages exclude visitors who claimed their primary activity was downhill skiing. When completing analyses involving skiers, refer to subsequent tables on average skier spending. NF = national forest. b The all-visit averages are computed as a weighted average of the columns using the lodging-based segment shares as weights.
23

Estimation of National Forest Visitor Spending Averages From National Visitor Use Monitoring: Round 2

nonlocal visitors. Operationally, sample sizes were not large enough to estimate 

lodging-based spending profiles separately for locals and nonlocals. 

Placing overnight segment spending on a per-day/night basis and using the 

lodging-based segments provides an opportunity to gauge the face validity of the 

spending averages. On a per-day/night basis, the spending of the overnight visitors 

ranges from $50 for those camping in undeveloped portions of the forest to $171 for 

those staying off-forest in motels (table 19). Those staying in motels average $76 on 

lodging expenses, $37 on restaurants, and $17 on gas and oil, per night. Those staying in national forest campgrounds pay approximately $13 on lodging/campground 

fees, $23 on groceries, and $16 on gas and oil, per night. 

The trip spending of those engaged in downhill skiing in the lodging-based 

segments ranges from $65 for those on local day trips to $983 for those staying 

in motels/hotels/B&Bs in the local forest area (table 20). Those staying in motels, 

hotels, or B&Bs average approximately $391 per trip on lodging expenditures while 

those staying in private homes average $26 in lodging expenses. 

Those engaged in downhill skiing have an average length of stay that is slightly 

greater than other visitors—2 nights compared to 1.2 nights for other visitors (table 

21). Those staying overnight in motels/hotels/B&Bs average 4.6 nights in the local 

area. On a per-day/night basis, those staying in motels/hotels/B&Bs spent $214 

while those staying in private homes spent $97 (table 21). Increased spending on 

entry fees and recreation and entertainment are the distinguishing features of the 

downhill skier spending averages compared to the spending of nonskiers. Downhill 

skiers tend to spend slightly less than other visitors on gas and oil in the local area. 

With the exception of the previously mentioned spending, on a per-day/night basis 

the spending of downhill skiers is similar to that of nonskiers. Much of the difference in trip spending between downhill skiers and other visitors can be traced to a 

longer length of stay of those skiing. 

The spending of 

overnight visitors 

ranges from $50 for 

those camping in 

undeveloped portions 

of the forest to $171 for 

those staying off-forest 

in motels. 
24

general technical report pnw-gtr-883 Table 19—Per-day/night national forest visitor spending profiles by lodging type segment and spending category, dollars per partya Spending Nonlocal Local National forest Private Private Other/ Non- All category day day Undeveloped Developed Cabin Motel campground home multiple primary visitsb

Dollars

Motel 0 0 1.15 1.12 68.78 76.17 6.41 6.85 16.62 39.61 22.53

Camping 0 0 3.26 12.75 0.97 0.20 17.35 0.23 9.46 4.12 3.04Restaurant 15.30 5.19 4.71 4.93 23.13 37.42 12.08 21.63 13.48 30.56 18.51Groceries 8.63 6.31 15.75 22.59 21.29 13.11 16.26 18.44 15.58 14.95 13.74Gas and oil 23.16 12.83 15.41 16.36 19.27 16.97 18.18 14.32 13.93 16.69 15.67Other transp. 0.58 0.13 0.67 0.15 1.66 1.08 0.53 0.82 0.98 1.12 0.68Entry fees 4.56 2.17 1.86 2.60 2.46 5.91 3.57 3.15 3.20 3.83 3.43Recreation and 

entertainment 4.34 1.50 1.40 2.30 3.47 8.77 2.01 4.92 3.87 5.76 4.27

Sporting goods 2.94 4.16 5.04 3.62 4.41 3.09 4.82 3.51 3.24 2.22 3.46Souvenirs and

other expenses 3.15 0.72 1.04 2.00 5.51 8.05 5.07 5.74 3.53 8.91 4.64

Total 62.65 33.02 50.28 68.43 150.94 170.76 86.28 79.61 83.89 127.77 89.98

Sample size 

unweighted 2,224 9,832 1,329 4,031 629 1,257 413 887 659 4,737 25,998

Average days/ 

nights in the local area 1.0 1.0 3.0 2.8 3.2 4.1 4.6 4.7 4.4 2.9 2.0

a Outliers are excluded and exposure weights are applied in estimating spending averages. All figures expressed in 2009 dollars. These averages exclude visitors who claimed their primary activity was downhill skiing. When completing analyses involving skiers refer to subsequent tables on average skier spending. NF = national forest. b The all-visit averages are computed as a weighted average of the columns using the lodging-based segment shares computed without downhill skiers as weights and divided by the average number of nights in the local area.
25

Estimation of National Forest Visitor Spending Averages From National Visitor Use Monitoring: Round 2

Table 20—Per-trip national forest visitor spending profiles of downhill skiers by lodging-type segment and spending category, dollars per partyaSpending Nonlocal Local National Private Other/ Non- Allcategory day day forestb Motel home multiplec primary visitsd

Dollars

Motel 0 0 237.61 391.11 25.73 73.11 145.58 66.60Camping 0 0 1.73 0 0 41.64 0.10 0.16Restaurant 22.52 13.57 68.97 174.65 139.49 59.32 136.24 58.16Groceries 4.60 3.49 63.67 63.79 88.67 68.57 52.59 24.77Gas and oil 20.73 9.99 54.42 49.04 47.24 61.29 42.23 24.37Other transportation 0 0.01 0 3.81 2.25 4.30 2.51 0.86Entry fees 45.98 20.82 73.98 164.68 112.98 14.10 68.10 59.62Recreation and 

entertainment 31.00 13.13 40.64 95.00 89.87 17.02 67.94 39.47

Sporting goods 5.32 3.13 11.46 20.58 24.83 14.26 12.06 8.85Souvenirs and other 

expenses 1.85 0.77 4.77 20.71 21.68 15.53 16.99 6.94

Total 132.00 64.91 557.26 983.36 552.73 369.12 544.34 289.79

Sample size (unweighted) 459 907 53 264 203 659 130 2036

Standard deviation of total 103 82 553 858 746 623 623 n/a

n/a = not applicable.a Outliers are excluded and exposure weights are applied in estimating spending averages. All figures expressed in 2009 dollars. These averages are for visitors engaged in downhill skiing. b Here we combine all lodging types on the national forest into a single segment. The analyst should be cautious in using this segment as it is not clear if visitors are able to differentiate between lodging on or off the national forest. c There was an insufficient number of downhill skiing respondents in the other/multiple segment, and we substitute the spending averages shown for the 

general lodging-based segments here. 

d The all-visit averages are computed as a weighted average of the columns using the lodging-based segment shares computed without downhill skiers as weights.
26

general technical report pnw-gtr-883 Table 21—Per-day/night national forest visitor spending profiles of downhill skiers by lodging-type segment and spending category, dollars per partya Spending Nonlocal Local National Private Other/ Non- All category day day forestb Motel home multiplec primary visitsd Dollars

Motel 0 0 88.00 85.02 4.51 17.41 37.33 33.30

Camping 0 0 0.64 0 0 9.91 0.03 0.08Restaurant 22.52 13.57 25.54 37.97 24.47 14.12 34.93 29.08Groceries 4.60 3.49 23.58 13.87 15.56 16.33 13.48 12.39Gas and oil 20.73 9.99 20.16 10.66 8.29 14.59 10.83 12.19Other transportation 0 0.01 0 0.83 0.39 1.02 0.64 0.43Entry fees 45.98 20.82 27.40 35.80 19.82 3.36 17.46 29.81Recreation and 

entertainment 31.00 13.13 15.05 20.65 15.77 4.05 17.42 19.74

Sporting goods 5.32 3.13 4.24 4.47 4.36 3.40 3.09 4.43Souvenirs and other 

expenses 1.85 0.77 1.77 4.50 3.80 3.70 4.36 3.47

Total 132.00 64.91 206.39 213.77 96.97 87.89 139.57 144.90

Sample size (unweighted) 459 907 53 264 203 659 130 2036

Average days/nights in the 

local area 1.0 1.0 2.7 4.6 5.7 4.2 3.9 2.0

a Outliers are excluded and exposure weights are applied in estimating spending averages. All figures expressed in 2009 dollars. These averages are for visitors engaged in downhill skiing. b Here we combine all lodging types on the national forest into a single segment. The analyst should be cautious in using this segment as it is not clear if visitors are able to differentiate between lodging on or off the national forest. c There was an insufficient number of downhill skiing respondents in the other/multiple segment and we substitute the spending averages shown for the 

general lodging-based segments here. 

d The all-visit averages are computed as a weighted average of the columns using the lodging-based segment shares computed without downhill skiers as weights and divided by the average number of nights in the local area.
27

Estimation of National Forest Visitor Spending Averages From National Visitor Use Monitoring: Round 2

Conclusions

We have presented spending averages and visit and trip characteristics for use in 

completing economic contribution and impact analysis for the NFS. In addition to 

using the Round 2 data to compute the spending averages, this report extends the 

previous analysis by reporting national forest visitor spending on a per-day/night 

basis and by using updated outlier rules. We also present spending averages for a 

lodging-based segmentation approach, which we first presented using the year 4, 

Round 1 NVUM data. 

On average, visitors to national forests spend about $172 per party per trip. On a 

per-day/night basis, this spending translates into an average of about $67 per party. 

Visitors engaged in downhill skiing spend more than other visitors, as expected, 

about $408 per party per trip or $120 per day/night. Much of the additional spending by downhill skiers can be traced to spending on entry fees, recreation and 

entertainment, restaurants, and lodging. Downhill skiers tend to spend a bit less 

than other visitors on gas and oil. The lodging-based segments we present are 

useful for estimating average spending for visitors using specific lodging types. 

Overnight visitors staying in motels/hotels/B&Bs spend the most ($700 per party 

per trip) while those staying in the undeveloped area of the forest spend the least 

($151 per party per trip). On a per-day/night basis, those staying overnight in 

motels/hotels/B&Bs spend about $175 per party; spending about $78 per night on 

lodging. 

For most applications, the Basic 7 trip segments and the associated spending 

averages will be appropriate. In situations where downhill skiing visits are an 

important component of the analysis, the downhill skiing profiles and estimated 

characteristics should be incorporated in the analysis for that portion of use. In 

instances where overnight trips are particularly important to the analysis, the 

lodging-based segments should prove useful. The wildlife-related spending figures 

reported in appendix 3 can be applied for wildlife programmatic analysis. Finally, 

activity-specific spending profiles, which are contained in other reports (White 

and Stynes 2010b) and electronic files, can be used for analyses aimed at specific 

activities, such as travel management planning. 

As data in future NVUM rounds become available, it will be possible to 

examine the potential for pooling data across rounds to develop forest-specific 

spending profiles and to update spending profiles for particular activities. Pooled 

data could also be used to improve the classification of forests into high, medium, 

and low spending areas. The lodging-based segments capture important variations 

in spending, but the NVUM samples at the forest level are often not adequate to 

reliably estimate the lodging segment shares. Another round of NVUM data would 
28

general technical report pnw-gtr-883

improve estimates of lodging shares for individual forests. Lodging segment shares 

could also be based on inventories of lodging opportunities around each forest. 

Acknowledgments

We thank J. Ross Arnold, Rickard Hokans, and Stanley J. Zarnoch for their helpful 

comments on an earlier version of this report. We also appreciate the assistance of 

Don English in providing the NVUM data and Susan Winter and Barbara Ott for 

their support for this reporting effort. The development of the approach to reporting NVUM visitor spending has benefited from the involvement of a number of 

individuals over the years. Early contributors to this research effort include Greg 

Alward, J. Ross Arnold, Rickard Hokans, Sue Kocis, Mike Niccolucci, Dick Phillips, Mike Retzlaff, and Mike Vasievich. 

Metric Equivalents

When you know: Multiply by: To get:

Miles (mi) 1.609 Kilometers

References 

Crompton, J.L.; Lee, S.; Shuster, T.J. 2001. A guide for undertaking economic 

impact studies: the Springfest example. Journal of Travel Research. 40: 79–87. 

Rylander, R.G., II; Propst, D.B.; McMurty, T.R. 1995. Nonresponse and recall 

biases in a survey of traveler spending. Journal of Travel Research. 33: 39–45. 

Stynes, D.J.; White, E.M. 2005a. Effects of changes in the FY 2003 

NVUM instrument and development of national forest visitor spending 

profiles for lodging-based segments. 37 p. http://mgm2impact.com/nvum/

NVUMFY2003report.pdf. (2 May 2012). 

Stynes, D.J.; White, E.M. 2005b. Spending profiles of national forest visitors, 

NVUM four-year report. 44 p. http://www.fs.fed.us/recreation/programs/nvum/

NVUM4YrSpending.pdf. (2 May 2012). 

Stynes, D.J.; White, E.M. 2006. Reflections on measuring recreation and travel 

spending. Journal of Travel Research. 45: 8–16. 

Stynes, D.J.; White, E.M.; Leefers, L.A. 2002. Spending profiles of national 

forest visitors: years 2000 and 2001. 57 p. http://mgm2impact.com/nvum/

NVUM2Year.pdf. (2 May 2012). 
29

Estimation of National Forest Visitor Spending Averages From National Visitor Use Monitoring: Round 2

U.S. Department of Agriculture, Forest Service. [USDA FS] 2007. National 

Visitor Use Monitoring Handbook. 87 p. http://www.fs.fed.us/recreation/

programs/nvum/reference/july07_handbook.pdf. (2 May 2012). 

White, E.M.; Stynes, D.J. 2008. National forest visitor spending averages and the 

influence of trip type and recreation activity. Journal of Forestry. 116(1): 17–24. 

White, E.M.; Stynes, D.J. 2010a. Spending profiles of national forest visitors, 

NVUM Round 2 update. 68 p. http://www.fsl.orst.edu/lulcd/Publicationsalpha_

files/White_Stynes_NVUM2010a.pdf. (2 May 2012). 

White, E.M.; Stynes, D.J. 2010b. Updated spending profiles for national 

forest recreation visitors by activity. 42 p. http://www.fsl.orst.edu/lulcd/

Publicationsalpha_files/White_Stynes_NVUM2010b.pdf. (2 May 2012). 

Zarnoch, S.J.; White, E.M.; English, D.B.K.; Kocis, S.M.; Arnold, R. 2011.

The National Visitor Use Monitoring methodology and final results for Round 1. 

Gen. Tech. Rep. SRS-144. Asheville, NC: U.S. Department of Agriculture, Forest 

Service, Southern Research Station. 74 p.
30

general technical report pnw-gtr-883

Appendix 1: Applying the National Spending Profiles 

This section provides guidance on applying the spending profiles for economic 

analysis and has been adapted from Stynes et al. (2002). A number of distinct 

spending profiles have been generated from the National Visitor Use Monitoring 

(NVUM) survey data. These include: 

• National average spending profiles by trip segments (tables 8 and 9)

• High and low spending profiles by trip segments (tables 10, 11, 13, and 14)

• Downhill skier spending profiles (tables 15 and 16)

• Spending profiles by lodging-based segment (tables 18 through 21)

• Spending profiles for select segment/activity combinations available in 

White and Stynes (2010b) and in upcoming reports. 

These spending profiles can be used in national-, regional-, forest- and 

subforest-level planning. For economic impact or contribution analyses, the spending profiles must be combined with (1) estimates of total visits, (2) estimates of the 

percentage of visits within given trip or activity segments, and (3) appropriate local 

input-output (I-O) models or multipliers. 

For national-, regional- and forest-level estimates, the number of visits and trip 

segment shares may be derived from the NVUM survey or other sources.1

 The 

NVUM estimates will be most reliable at the national level, with increasing potential errors at regional and forest levels. Other local sources may be more reliable in 

estimating the number of visits within particular activity subgroups or for subforestlevel analysis. The Round 2 estimates of segment and activity shares should be 

more reliable than those reported for Round 1 owing to improved allocation of 

sampling effort across seasons and sites and the inclusion of all segment variables 

in the general survey. 

The NVUM spending categories were developed to easily bridge to sectors in 

I-O models estimated with IMPLAN so the application of the spending data to I-O 

models is reasonably straightforward. For most applications, acquiring the estimates 

of visits and segment shares will be the greater problem. 

1

 The NVUM segment shares on individual forests should be compared with other sources 

or local knowledge, as they may not adequately represent different types of visitors on 

particular forests. The NVUM sampling plan was not designed to necessarily represent 

particular types of visitors on a given forest—be they local, day trips, overnight trips, or 

particular activity groups. Estimates of the percentage of anglers, snowmobilers, or hikers 

from the NVUM survey may therefore be unreliable as they will be sensitive to the sites 

and time periods selected for sampling. Activities that tend to be concentrated at a few 

locations or during selected time periods can be completely missed or overrepresented in 

the NVUM sampling plan.

NVUM spending 

categories were 

developed to easily 

bridge to sectors in 

I-O models.
31

Estimation of National Forest Visitor Spending Averages From National Visitor Use Monitoring: Round 2

The general steps for making spending and economic impact/contribution 

estimates with the NVUM spending profiles are: 

1. Choose a set of visitor segments—When analyzing spending by all visitors to a 

particular forest, we recommend using the Basic 7 trip segments. When conducting 

more targeted analyses, one or more of the activity-based segments (White and 

Stynes 2010b) may be used. We suggest using the Basic 7 trip segments as defaults 

and developing more specific segments only for groups whose spending will differ 

from these and for which reliable use estimates can be made. For most analyses, 

a set of mutually exclusive visitor segments should be chosen for which both visit 

estimates and spending profiles can be generated. 

2. Choose a spending profile for each segment—If using the NVUM trip segments, 

begin by selecting from the high, national average, or low profiles based on the 

characteristics of the particular application. Note that even though a forest may be 

classified (table 22) as an above-average spending area, if the application relates to 

more remote areas of the forest, the low spending profiles may be more appropriate, as spending within trip segments is largely a function of the number and kinds 

of nearby spending opportunities. The NVUM spending profiles may be adjusted 

to suit the local situation/application, as needed. See text later in this appendix for 

guidance on adjusting spending averages for local applications and for how to use 

an engineering approach to estimate spending profiles when survey data are not 

available or of limited applicability. When the analysis involves downhill skier visits, the downhill skier spending profiles should be incorporated in the analysis and 

both the downhill skier spending profiles (e.g., table 15) and the “general” spending 

profiles (e.g., table 8) may need to be used in the analysis. 

3. Estimate the number of visits by each segment—At the national or forest level, 

one may multiply the NVUM estimated number of national forest visits by the 

estimates of trip segment shares (table 23) to distribute total visits across the trip 

segments.2

 If the economic analysis being completed treats downhill skier visits 

and other visits separately, then the analyst should consider using the segment 

shares computed for downhill skier visits (table 24) for that portion of recreation use 

associated with downhill skiing. 

2

 Another complication for some applications is potential double counting of spending 

by visitors staying overnight off the forest and making multiple visits during their stay in 

the area. Spending averages are on a trip basis (to the area). If the incidence of multiple 

national forest visits per trip is known, national forest visits should be converted to distinct 

trips to the area by dividing by an estimate of visits per trip. 
32

general technical report pnw-gtr-883

Table 22—Classification of national forests as above, below, or average spending

Above-average spending: Kaibab Below-average spending:

Black Hills Klamath Allegheny

Bridger-Teton Lake Tahoe Management Unit Angeles

Carson Land Between the Lakes Bitterroot

Chippewa Lassen Boise

Chugach Lewis & Clark Cherokee

Cibola Lincoln Clearwater

Coconino Lolo Cleveland

Gallatin Medicine Bow Daniel Boone

Hiawatha Midewin Tallgrass Prairie Fremont

Inyo Mount Baker-Snoqualmie George Washington-Jefferson

Nebraska Mount Hood Gifford Pinchot

Rio Grande National forests in Mississippi Gila

San Juan National forests in North Carolina Hoosier

Tongass-Chatham Nez Perce Idaho Panhandle

White River Okanogan Kisatchie

Olympic Kootenai

Average spending: Ottawa Los Padres

Apache-Sitgreaves Payette Malheur

Arapaho-Roosevelt Pike-San Isabel Manti-La Sal

Ashley Plumas Mark Twain

Beaverhead-Deerlodge Routt Mendocino

Caribbean Salmon-Challis Modoc

Caribou-Targhee Santa Fe Monongahela

Chattahoochee-Oconee Sawtooth National forests in Alabama

Chequamegon-Nicolet Sequoia National forests in Florida

Columbia River Gorge Shasta Trinity National forests in Texas

Colville Shoshone Ochoco

Coronado Sierra Ouachita

Custer Siskiyou Ozark-St. Francis

Dakota Prairie Six Rivers Prescott

Deschutes Stanislaus Rogue River

Dixie Superior San Bernardino

Eldorado Tahoe Shawnee

Fishlake Tongass-Ketchikan Siuslaw

Flathead Tongass-Stikine Umatilla

Francis Marion-Sumter Tonto Wasatch-Cache

Grand Mesa-Uncompahgre-Gunnison Uinta Wayne

Green Mountain and Finger Lakes Umpqua Wenatchee

Helena Wallowa-Whitman Willamette

Humboldt-Toiyabe White Mountain Winema

Huron-Manistee
33

Estimation of National Forest Visitor Spending Averages From National Visitor Use Monitoring: Round 2

Table 23—Segment shares by foresta

Nonlocal Local

OVN- OVN- NonNational forest Day NF OVN Day NF OVN primary Total

Percent

Allegheny 10 13 10 50 6 3 8 100

Angeles 12 1 1 73 3 1 9 100

Apache-Sitgreaves 8 27 12 38 2 1 12 100

Arapaho-Roosevelt 21 5 21 39 4 1 9 100

Ashley 10 33 2 37 9 0 9 100

Beaverhead-Deerlodge 13 13 9 46 6 0 13 100

Bighorn 18 21 6 25 10 0 20 100

Bitterroot 4 3 4 80 7 0 2 100

Black Hills 6 4 28 50 2 1 9 100

Boise 12 20 2 54 8 0 4 100

Bridger-Teton 5 9 21 51 1 1 12 100

Caribbean 7 0 17 24 1 1 50 100

Caribou-Targhee 13 6 16 42 4 1 18 100

Carson 11 7 25 39 2 1 15 100

Chattahoochee-Oconee 11 4 8 55 4 1 17 100

Chequamegon-Nicolet 3 6 23 25 4 2 37 100

Cherokee 12 5 13 50 4 2 14 100

Chippewa 9 14 8 48 2 1 18 100

Chugach 9 12 9 21 3 2 44 100

Cibola 6 1 11 49 0 1 32 100

Clearwater 22 14 7 33 5 3 16 100

Cleveland 4 3 1 77 9 1 5 100

Coconino 11 6 25 33 2 0 23 100

Columbia River Gorge 8 2 5 56 1 1 27 100

Colville 19 7 5 48 8 2 11 100

Coronado 5 4 4 65 4 1 17 100

Custer 19 8 14 39 2 2 16 100

Dakota Prairie 7 9 7 50 13 2 12 100

Daniel Boone 10 15 6 52 6 2 9 100

Deschutes 6 11 15 48 7 2 11 100

Dixie 11 10 23 25 7 1 23 100

Eldorado 16 10 12 36 2 2 22 100

Fishlake 7 30 14 30 5 2 12 100

Flathead 7 3 12 61 4 1 12 100

Francis Marion-Sumter 11 1 3 69 4 2 10 100

Fremont 15 8 6 53 9 0 9 100

Gallatin 4 3 14 66 3 1 9 100

George Washington-Jefferson 4 6 4 69 6 2 9 100

Gifford Pinchot 24 11 10 26 4 0 25 100

Gila 21 17 11 25 4 1 21 100

Grand Mesa-UncompahgreGunnison 7 8 17 53 3 2 10 100
34

general technical report pnw-gtr-883

Table 23—Segment shares by foresta (continued)

Nonlocal Local

OVN- OVN- NonNational forest Day NF OVN Day NF OVN primary Total

Percent

Green Mountain and 

Finger Lakes 11 1 20 60 0 2 6 100

Helena 9 2 7 66 5 2 9 100

Hiawatha 3 4 25 39 4 1 24 100

Hoosier 5 8 2 55 19 1 10 100

Humboldt-Toiyabe 3 4 8 65 3 3 14 100

Huron Manistee 12 13 24 36 1 4 10 100

Idaho Panhandle 9 9 4 64 7 1 6 100

Inyo 3 23 39 20 1 1 13 100

Kaibab 11 17 11 11 1 1 48 100

Kisatchie 13 5 2 71 7 0 2 100

Klamath 6 24 7 45 5 2 11 100

Kootenai 17 3 4 59 3 1 13 100

Lake Tahoe Management Unit 3 4 28 27 0 0 38 100

Land Between the Lakes 9 24 7 31 14 0 15 100

Lassen 14 13 5 49 5 2 12 100

Lewis and Clark 27 14 13 22 5 2 17 100

Lincoln 15 16 13 40 2 0 14 100

Lolo 5 4 6 65 3 2 15 100

Los Padres 10 12 4 50 5 1 18 100

Malheur 5 46 5 29 4 0 11 100

Manti-La Sal 16 14 6 43 5 4 12 100

Mark Twain 8 13 3 57 7 1 11 100

Medicine Bow 15 14 10 44 4 1 12 100

Mendocino 11 25 1 50 4 1 8 100

Midewin Tallgrass Prairie 3 0 1 85 0 0 11 100

Modoc 5 18 2 66 2 1 6 100

Monongahela 8 29 24 8 1 2 28 100

Mount Baker-Snoqualmie 14 6 2 62 8 0 8 100

Mount Hood 34 7 4 42 5 0 8 100

National forests in Alabama 18 2 1 60 11 3 5 100

National forests in Florida 12 9 4 61 8 3 3 100

National forests in 

Mississippi 8 3 1 81 2 1 4 100

National forests in 

North Carolina 5 5 10 62 4 2 12 100

National forests in Texas 7 4 3 74 6 1 5 100

Nebraska 7 9 3 64 0 0 17 100

Nez Perce 11 19 15 27 12 1 15 100

Ochoco 8 16 5 53 6 1 11 100

Okanogan 12 11 16 46 1 0 14 100

Olympic 18 8 4 44 7 1 18 100

Ottawa 8 4 21 17 1 1 48 100
35

Estimation of National Forest Visitor Spending Averages From National Visitor Use Monitoring: Round 2

Table 23—Segment shares by foresta (continued)

Nonlocal Local

OVN- OVN- NonNational forest Day NF OVN Day NF OVN primary Total

Percent

Ouachita 8 18 13 49 4 3 5 100

Ozark-St. Francis 3 7 6 61 4 5 14 100

Payette 29 18 15 22 4 0 12 100

Pike-San Isabel 12 9 8 47 3 1 20 100

Plumas 11 7 12 45 8 3 14 100

Prescott 6 10 4 61 4 0 15 100

Rio Grande 9 11 31 35 3 1 10 100

Rogue River 8 7 2 54 10 1 18 100

Routt 4 4 44 35 1 2 10 100

Salmon-Challis 19 20 25 21 2 1 12 100

San Bernardino 20 14 7 46 5 1 7 100

San Juan 5 6 18 49 3 1 18 100

Santa Fe 13 6 7 61 1 2 10 100

Sawtooth 6 12 28 36 3 1 14 100

Sequoia 14 31 13 17 4 1 20 100

Shasta Trinity 7 19 8 46 7 1 12 100

Sierra 22 16 9 38 2 6 7 100

Siskiyou 11 4 8 48 6 0 23 100

Shawnee 11 6 16 48 2 3 14 100

Shoshone 15 5 15 44 4 3 14 100

Siuslaw 10 17 9 33 4 0 27 100

Six Rivers 4 9 5 43 6 1 32 100

Stanislaus 28 33 9 18 5 1 6 100

Superior 6 21 18 19 1 0 35 100

Tahoe 14 6 25 48 2 1 4 100

Tongass-Chatham 1 0 3 44 1 0 51 100

Tongass-Ketchikan 12 6 22 48 6 0 6 100

Tongass-Stikine 1 2 6 72 6 2 11 100

Tonto 6 8 2 67 7 1 9 100

Uinta 11 19 1 45 17 0 7 100

Umatilla 15 13 2 55 6 2 7 100

Umpqua 14 27 2 39 5 0 13 100

Wallowa-Whitman 14 20 15 13 3 3 32 100

Wasatch-Cache 2 3 6 80 4 0 5 100

Wayne 13 6 6 63 5 3 4 100

Wenatchee 20 26 3 38 3 1 9 100

White Mountain 17 8 30 27 1 1 16 100

White River 11 2 51 23 1 3 9 100

Willamette 22 16 5 34 7 2 14 100

Winema 5 20 1 31 29 2 12 100

National average 10 9 14 49 4 1 13 100

a Estimated using the full sample and case weights. OVN = overnight, NF = national forest.
36

general technical report pnw-gtr-883

Table 24—Segment shares by forest for downhill skiing visitsa

Nonlocal Local

 Non- Sample

National forest Day OVN Day OVN primary Total size

Percent

Angeles 42 1 49 2 6 100 59

Arapaho-Roosevelt 30 41 25 1 3 100 396

Beaverhead-Deerlodge 27 13 54 1 5 100 152

Bighorn 65 30 5 0 0 100 132

Bitterroot 0 0 77 23 0 100 114

Boise 0 2 93 3 2 100 56

Bridger-Teton 3 36 46 1 14 100 229

Caribou-Targhee 40 23 29 4 4 100 82

Carson 13 45 35 0 7 100 132

Coconino 31 37 24 1 7 100 366

Colville 28 7 61 2 2 100 88

Custer 20 21 46 5 8 100 107

Deschutes 5 50 28 2 15 100 90

Dixie 30 50 14 0 6 100 104

Eldorado 14 19 38 4 25 100 120

Flathead 5 28 61 2 4 100 147

Gallatin 8 14 75 2 1 100 173

Grand MesaUncompahgre-Gunnison 6 27 61 1 5 100 189

Green Mountain and 

Finger Lakes 21 36 39 4 0 100 114

Humboldt-Toiyabe 3 17 56 2 22 100 236

Idaho Panhandle 56 10 29 1 4 100 136

Inyo 2 75 17 1 5 100 115

Kaibab 29 51 7 0 13 100 39

Kootenai 6 9 81 3 1 100 116

Lake Tahoe

Management Unit 4 42 9 1 44 100 161

Lewis and Clark 59 11 28 0 2 100 95

Lincoln 13 23 62 0 2 100 31

Lolo 1 4 81 2 12 100 316

Medicine Bow 41 12 34 0 13 100 31

Mount BakerSnoqualmie 10 0 82 8 0 100 39

Mount Hood 51 6 38 2 3 100 256

Payette 29 34 33 0 4 100 78

Pike-San Isabel 17 24 38 2 19 100 167
37

Estimation of National Forest Visitor Spending Averages From National Visitor Use Monitoring: Round 2

Table 24—Segment shares by forest for downhill skiing visitsa (continued)

Nonlocal Local

 Non- Sample

National forest Day OVN Day OVN primary Total size

Percent

Rio Grande 2 70 22 1 5 100 152

Rogue River 5 5 80 10 0 100 184

Routt 3 62 31 0 4 100 146

San Bernardino 51 15 32 2 0 100 132

San Juan 6 43 39 1 11 100 125

Santa Fe 11 24 60 1 4 100 214

Sawtooth 5 56 33 1 5 100 178

Sierra 43 21 31 4 1 100 119

Stanislaus 45 42 13 0 0 100 271

Tahoe 26 49 22 0 3 100 237

Umatilla 62 2 31 1 4 100 191

Wasatch-Cache 4 10 83 1 2 100 155

White Mountain 23 35 36 1 5 100 183

White River 13 64 17 4 2 100 241

Willamette 59 11 24 2 4 100 120

National average 16 41 35 2 6 100 7,627

a

 Estimated using the full sample and case weights. Only forests with more than 30 respondents stating their primary activity was 

downhill skiing are shown. OVN = overnight.

4. Convert the estimate of visits to party visits or party visit days/nights—One must 

be careful to put visits and spending into common units. Recreation visits are on a 

per-person basis, while the spending averages reported in the above tables is on a 

per-party basis. One must either divide the spending averages by the average party 

size to put spending on a per-person basis or convert visits to parties by dividing 

visits by an average party size.3 The NVUM estimates of average party sizes by 

segment for each forest are reported in table 25. If one elects to use the spending 

profiles estimated on a day/night basis (e.g., table 9), then it is also necessary to 

place the party visits on a day/night basis by multiplying party visits by the average 

numbers of nights in the local area (treating day trips as involving 1 day/night). The 

NVUM estimates of the average numbers of nights in the local area for each forest 

are in table 26. 

5. Estimate total spending—The estimate of total spending is calculated by multiplying the number of visits (i.e., party visits or party day/night visits) of each trip 

type (segment) by the appropriate per-trip or per-day/night spending averages for 

that segment and summing across segments. 

3

 The NVUM averages for people per vehicle are used to estimate party sizes. It must be 

assumed that in most cases, all people traveling in the same vehicle is the spending unit.
38

general technical report pnw-gtr-883

Table 25—People per vehicle by segment by foresta

Nonlocal Local

OVN- OVN- NonNational forest Day NF OVN Day NF OVN primary Total

 Number

Allegheny 2.4 2.5 2.2 2.0 3.2 2.5 2.2

Angeles 2.6 3.0 2.1 2.8 2.4 2.2

Apache-Sitgreaves 2.5 3.4 2.9 1.8 2.6 2.5

Arapaho-Roosevelt 2.4 2.4 2.8 2.1 2.4 2.1 2.8 2.4

Ashley 3.1 2.8 3.0 2.7 3.1 2.4 2.8

Beaverhead-Deerlodge 2.1 2.4 2.5 2.0 2.7 2.1 2.2

Bighorn 3.0 2.7 2.7 2.6 2.3 2.5 2.7

Bitterroot 1.9 2.3 2.2 2.1 2.2 2.6 2.1

Black Hills 2.7 2.7 2.6 2.2 3.2 2.6 2.4

Boise 1.9 2.2 2.6 2.0 2.4 2.2 2.1

Bridger-Teton 2.5 2.8 2.8 1.9 2.2 2.6 2.2

Caribbean 3.6 2.7 3.2 3.1 3.1

Caribou-Targhee 2.7 2.7 2.6 2.0 3.3 2.8 2.4

Carson 1.9 2.5 2.6 2.4 2.0 2.9 2.4

Chattahoochee-Oconee 2.3 2.5 2.6 2.1 2.7 2.7 2.3

Chequamegon-Nicolet 2.1 2.6 2.0 1.8 2.4 2.0 2.0

Cherokee 2.8 2.6 3.3 2.2 2.8 2.1 2.9 2.5

Chippewa 2.6 2.6 1.8 1.8 2.3 2.3 2.1

Chugach 2.5 3.2 2.7 2.0 2.8 2.9 2.7

Cibola 2.5 3.0 2.5 2.5 2.9 2.6

Clearwater 2.0 2.5 2.0 2.0 1.8 2.2 2.1

Cleveland 2.8 2.7 2.2 2.5 2.2 2.3

Coconino 2.8 2.8 2.6 2.0 2.2 2.5 2.4

Columbia River Gorge 2.6 2.6 2.9 2.3 2.9 2.6 2.4

Colville 2.6 2.4 2.3 2.2 2.1 2.1 2.3

Coronado 2.3 2.4 2.4 2.0 2.4 3.0 2.5 2.2

Custer 2.4 2.9 2.5 2.1 2.6 2.7 2.4

Dakota Prairie 2.0 2.3 2.3 2.5 2.4 3.1 2.4

Daniel Boone 3.0 2.4 3.1 2.2 3.1 1.5 2.3 2.5

Deschutes 3.1 2.7 2.8 2.0 2.3 2.8 2.5 2.3

Dixie 2.5 3.1 2.8 2.6 3.0 2.5 2.7

Eldorado 2.4 2.6 2.5 2.4 2.7 2.8 2.5

Fishlake 2.3 2.9 2.7 2.5 2.8 2.6 2.6

Flathead 2.2 2.5 2.7 1.9 2.9 2.6 2.1

Francis Marion-Sumter 2.3 1.9 2.6 2.2 1.7 2.9 2.3

Fremont 1.6 2.4 2.7 2.8 2.4

Gallatin 2.4 2.8 2.9 2.0 3.0 2.6 2.3

George WashingtonJefferson 2.0 2.6 1.7 2.0 3.0 1.5 2.4 2.1

Gifford Pinchot 2.7 2.3 2.7 2.3 2.3 2.6 2.5

Gila 2.7 2.3 2.5 2.3 2.4 2.4

Grand Mesa-UncompahgreGunnison 2.4 2.6 2.4 2.3 1.9 2.4 2.8 2.4
39

Estimation of National Forest Visitor Spending Averages From National Visitor Use Monitoring: Round 2

Table 25—People per vehicle by segment by foresta (continued)

Nonlocal Local

OVN- OVN- NonNational forest Day NF OVN Day NF OVN primary Total

Number

Green Mountain 

and Finger Lakes 2.0 2.1 2.2 1.7 3.2 2.2 1.8

Helena 2.9 2.9 2.8 2.1 2.4 3.6 2.3

Hiawatha 2.4 2.4 2.7 1.9 2.5 2.5 2.3

Hoosier 2.4 2.3 2.3 2.1 2.5 2.9 2.3

Humboldt-Toiyabe 2.3 2.7 2.9 2.2 2.9 2.9 2.5 2.3

Huron Manistee 2.2 2.2 2.1 2.1 1.9 2.3 2.2 2.1

Idaho Panhandle 2.5 2.3 2.4 1.8 2.4 2.6 2.7 2.0

Inyo 1.7 2.6 2.7 1.5 2.4 2.3

Kaibab 2.7 2.2 3.1 2.4 2.7 2.6

Kisatchie 2.6 2.4 3.3 2.2 3.1 2.1 2.3

Klamath 2.0 2.3 2.2 2.2 2.5 2.2

Kootenai 2.4 2.6 2.4 2.0 2.7 2.8 2.2

Lake Tahoe

Management Unit 3.7 2.6 2.7 2.1 2.2 2.5 2.4

Land Between the Lakes 1.9 2.0 2.5 1.9 1.9 2.1 2.0

Lassen 3.3 2.3 2.2 2.2 3.2 1.8 2.4

Lewis and Clark 2.6 2.4 1.9 2.7 2.3 2.5

Lincoln 2.9 2.7 2.6 2.2 3.1 2.8 2.6

Lolo 2.3 2.8 2.0 1.8 2.5 1.9 2.5 2.0

Los Padres 2.7 3.0 2.0 2.2 2.4 2.3 2.4

Malheur 2.0 2.5 2.1 2.6 2.3 2.4

Manti-La Sal 2.9 2.8 2.8 2.4 3.3 2.6 2.7

Mark Twain 2.4 2.8 4.0 2.1 2.2 2.6 2.3

Medicine Bow 2.3 2.4 3.5 2.2 3.0 2.3 2.4

Mendocino 2.3 2.4 1.6 2.7 1.7 1.9

Midewin Tallgrass Prairie 1.6 1.6

Modoc 2.5 2.1 2.6 2.5 2.2 2.4 2.4

Monongahela 2.3 3.0 2.5 2.0 3.0 2.6 2.6

Mendocino 2.3 2.4 1.6 2.7 1.7 1.9

Mount Baker-Snoqualmie 2.6 2.8 2.2 2.4 2.8 2.7 2.5

Mount Hood 2.5 3.4 2.9 2.2 2.5 3.0 2.5

National forests in Alabama 3.1 2.2 3.1 2.8 2.6

National forests in Florida 2.3 2.9 3.1 2.1 2.6 2.3 2.1 2.3

National forests in 

Mississippi 1.8 1.7 3.4 1.8

National forests in 

North Carolina 2.7 2.3 2.8 1.7 1.5 3.0 2.4 2.0

National forests in Texas 2.2 2.3 2.3 2.2 3.3 2.1 2.2

Nebraska 3.5 3.5 2.3 2.9 2.6

Nez Perce 2.9 2.3 2.7 2.3 3.0 2.7 2.6

Ochoco 3.6 2.3 1.6 2.6 2.9 2.5 2.6

Okanogan 1.8 2.2 2.4 1.5 2.2 1.9

Olympic 2.3 2.3 2.2 2.1 3.0 2.4 2.1 2.2

Ottawa 2.3 2.6 2.6 2.0 3.4 2.9 2.6
40

general technical report pnw-gtr-883

Table 25—People per vehicle by segment by foresta (continued)

Nonlocal Local

OVN- OVN- NonNational forest Day NF OVN Day NF OVN primary Total

 Number

Ouachita 2.6 2.5 3.1 1.9 2.4 2.3 2.3

Ozark-St. Francis 2.0 2.0 1.4 2.3 2.2 2.1 2.7 2.3

Payette 3.0 2.8 2.4 2.4 2.5 2.7

Pike-San Isabel 1.9 2.0 2.4 1.9 2.5 2.5 2.1

Plumas 2.2 2.4 2.7 2.6 2.6 2.9 2.6 2.6

Prescott 2.6 2.7 2.2 1.7 2.4 2.5 2.0

Rio Grande 1.7 2.2 3.0 2.2 2.7 2.4 2.4

Rogue River 3.1 2.5 2.2 2.6 2.1 2.9 2.7

Routt 1.6 2.4 2.9 1.7 3.4 2.6 2.2

Salmon-Challis 2.6 3.0 2.5 2.5 2.7 2.6

San Bernardino 2.8 2.6 2.9 2.2 2.0 3.3 3.0 2.4

San Juan 2.2 2.9 2.5 2.0 2.2 2.6 2.3

Santa Fe 2.2 2.6 2.5 1.8 2.6 2.0 2.4 2.0

Sawtooth 2.7 2.6 2.6 2.0 2.5 2.5 2.4

Sequoia 2.1 3.3 3.1 2.3 2.2 2.9 2.8

Shasta Trinity 2.6 2.6 2.8 2.0 1.9 2.3 2.2

Shawnee 2.9 2.2 2.5 2.2 2.7 2.3 2.2 2.4

Shoshone 2.6 2.7 2.4 2.0 1.7 2.6 2.3

Sierra 3.6 3.1 3.7 3.5 2.8 2.8 2.7 3.3

Siskiyou 2.3 2.2 2.5 2.5 2.2 2.4

Siuslaw 2.3 2.4 2.5 2.0 2.0 2.1 2.2

Six Rivers 3.3 2.7 2.5 2.4 3.1 2.7 2.6

Stanislaus 3.1 2.9 3.0 2.3 2.1 2.5 2.8

Superior 2.9 2.0 2.0 2.0 2.2

Tahoe 2.3 2.6 2.4 1.9 2.3 2.3 2.5 2.1

Tongass-Chatham 2.5 3.4 2.0 3.4 6.0 2.9 2.3

Tongass-Ketchikan 2.8 2.4 2.6 1.9 3.2 2.4 2.3

Tongass-Stikine 2.4 2.2 3.5 2.9 2.4

Tonto 2.6 3.1 2.2 2.2 2.2 2.5 2.3

Uinta 2.7 3.5 2.4 2.5 4.2 2.3 3.0

Umatilla 2.1 2.6 2.4 3.0 2.7 2.4

Umpqua 2.9 2.9 2.5 2.1 2.5 2.6

Wallowa-Whitman 2.9 2.2 2.9 2.7 3.4 2.3 2.6

Wasatch-Cache 2.6 3.3 2.7 2.2 3.2 2.8 2.3

Wayne 2.1 3.3 2.3 2.0 2.1 2.1 2.1

Wenatchee 2.2 2.2 2.2 2.5 2.2 2.4 2.3

White Mountain 2.2 2.4 2.8 2.0 2.1 3.3 2.6

White River 2.3 2.7 2.6 1.9 2.3 2.6 2.3

Willamette 2.5 2.3 2.5 2.1 2.5 2.7 2.8 2.4

Winema 2.5 2.7 2.5 2.4 2.5 2.5

National average 2.5 2.6 2.6 2.1 2.6 2.4 2.5 2.3

a

 Estimated from the full sample using the case weights. If a forest has less than 15 cases in a segment, the value is left blank. In these 

instances the national average may be used. OVN = overnight, NF = national forest.
41

Estimation of National Forest Visitor Spending Averages From National Visitor Use Monitoring: Round 2

Table 26—Average number of nights spent in the local area by segment by foresta

Nonlocal Local

 NonNational forest OVN-NF OVN OVN-NF OVN primary

 Number of nights

Allegheny 2.6 2.9 2.1 1.3

Angeles 1.7 1.9 4.3

Apache-Sitgreaves 2.9 4.0 5.2

Arapaho-Roosevelt 3.1 4.0 2.1 2.7 2.0

Ashley 4.9 2.8 1.6 1.6

Beaverhead-Deerlodge 5.1 9.7 2.7 3.8

Bighorn 3.9 4.8 2.4 1.2

Bitterroot 2.7 4.1 1.8 3.5

Black Hills 3.5 4.2 2.1 4.0

Boise 2.6 8.0 2.6 1.2

Bridger-Teton 4.0 5.7 3.2 3.4

Caribbean 6.8 4.6

Caribou-Targhee 4.7 4.9 1.9 3.5

Carson 2.9 4.5 3.9 3.8

Chattahoochee-Oconee 2.2 4.7 1.9 3.5

Chequamegon-Nicolet 3.2 2.7 3.0 2.3

Cherokee 2.2 3.1 2.7 2.2 3.7

Chippewa 3.6 2.5 3.2 1.2

Chugach 3.4 5.0 1.9 3.3

Cibola 3.5 5.8 3.8

Clearwater 3.6 4.4 4.0 1.7

Cleveland 1.9 1.6 0.8

Coconino 2.9 4.9 1.3 3.2

Columbia River Gorge 4.5 3.2 1.9 2.6

Colville 2.9 2.6 2.6 2.3

Coronado 2.7 5.6 1.6 4.4 5.3

Custer 3.2 4.1 1.9 1.8

Dakota Prairie 2.9 2.4 2.1 0.9

Daniel Boone 2.4 3.6 2.7 4.0 1.0

Deschutes 3.4 3.6 3.2 3.3 3.8

Dixie 2.9 3.5 1.3 3.9

Eldorado 2.9 2.7 2.2 2.3

Fishlake 3.6 5.9 2.5 3.0

Flathead 4.5 4.3 1.7 4.1

Francis Marion-Sumter 2.8 2.4 2.0 3.8

Fremont 7.8 2.4

Gallatin 3.8 6.0 2.3 4.2

George Washington-Jefferson 4.0 5.2 2.4 3.0 1.5

Gifford Pinchot 3.9 2.9 2.3 1.7
42

general technical report pnw-gtr-883

Table 26—Average number of nights spent in the local area by segment by foresta 

(continued)

Nonlocal Local

 NonNational forest OVN-NF OVN OVN-NF OVN primary

 Number of nights

Gila 3.4 4.3 1.9

Grand Mesa-UncompahgreGunnison 4.0 3.8 2.2 2.3 3.7

Green Mountain and Finger Lakes 2.9 3.2 1.6 3.1

Helena 3.9 5.0 2.6 3.4

Hiawatha 4.3 4.8 2.7 3.3

Hoosier 2.1 2.2 1.9 2.2

Humboldt-Toiyabe 3.5 4.9 1.8 6.6 3.6

Huron-Manistee 3.5 3.4 4.5 5.1 1.8

Idaho Panhandle 3.1 4.4 2.2 1.5 2.3

Inyo 4.0 3.8 3.2

Kaibab 4.1 2.2 1.9

Kisatchie 2.1 0.7 2.5 0.4

Klamath 5.0 3.9 1.3 5.5

Kootenai 4.5 6.9 2.6 2.2

Lake Tahoe Management Unit 4.6 4.3 2.5 3.0

Land Between the Lakes 6.4 4.6 6.0 2.9

Lassen 5.1 2.7 3.8 1.3

Lewis and Clark 3.3 6.1 1.9

Lincoln 3.2 4.6 2.4 2.3

Lolo 3.5 3.4 3.9 2.7 2.0

Los Padres 2.3 3.0 2.2 2.0

Malheur 5.5 11.0 1.0

Manti-La Sal 2.5 2.8 2.1 2.9

Mark Twain 2.8 3.6 2.5 1.0

Medicine Bow 4.0 4.5 2.6 2.8

Mendocino 2.3 2.2 1.8

Midewin Tallgrass Prairie

Modoc 4.2 4.2 3.8 1.4

Monongahela 2.7 2.7 1.0 3.1

Mount Baker-Snoqualmie 2.2 6.7 1.8 1.0

Mount Hood 2.3 4.3 1.7 1.5

National forests in Alabama 2.0 1.5

National forests in Florida 2.5 2.9 2.5 2.8 1.6

National forests in Mississippi 1.8

National forests in North Carolina 2.1 3.7 3.7 3.6 2.5

National forests in Texas 3.3 4.1 3.3 2.0

Nebraska 1.9 5.0 2.0

Nez Perce 3.9 3.5 1.5 3.3
43

Estimation of National Forest Visitor Spending Averages From National Visitor Use Monitoring: Round 2

Table 26—Average number of nights spent in the local area by segment by foresta

(continued)

Nonlocal Local

 NonNational forest OVN-NF OVN OVN-NF OVN primary

 Number of nights

Ochoco 6.3 2.3 5.6 1.0

Okanogan 3.2 4.0 3.7

Olympic 2.1 3.5 1.8 5.1 1.1

Ottawa 5.6 4.0 2.9 3.0

Ouachita 2.6 2.1 2.3 1.4

Ozark-St. Francis 1.8 2.0 2.3 1.1 0.4

Payette 2.6 3.4 1.4

Pike-San Isabel 2.9 5.6 1.9 2.0

Plumas 2.5 4.2 2.2 2.4 3.6

Prescott 2.1 3.6 2.9 2.7

Rio Grande 3.0 4.3 2.5 3.3

Rogue River 1.9 2.6 3.8 1.2

Routt 3.6 5.1 1.9 4.5

Salmon-Challis 3.1 3.1 1.6

San Bernardino 1.9 2.9 1.8 3.5 2.1

San Juan 4.8 5.3 2.0 3.5

Santa Fe 2.4 4.8 2.1 4.4 4.4

Sawtooth 2.8 6.0 2.6 2.8

Sequoia 3.1 3.4 2.0 2.8

Shasta Trinity 3.2 3.5 2.2 3.1

Shawnee 2.7 3.5 2.6 2.0 2.3

Shoshone 2.9 4.6 1.5 4.0

Sierra 2.6 3.1 2.8 2.1 3.2

Siskiyou 4.0 9.0 2.0 2.1

Siuslaw 2.6 3.6 1.9 2.6

Six Rivers 2.9 4.4 1.9 1.4

Stanislaus 2.9 3.3 4.0 2.8

Superior 4.0 5.2 3.5

Tahoe 3.1 3.5 2.7 2.7 2.6

Tongass-Chatham 4.7 7.4 2.7 1.0 1.5

Tongass-Ketchikan 5.4 2.6 3.1 3.5

Tongass-Stikine 4.6 2.5 6.0

Tonto 2.0 3.8 1.4 3.4

Uinta 2.3 5.9 2.2 2.6

Umatilla 3.7 1.6 1.5

Umpqua 3.0 2.1 1.9

Wallowa Whitman 3.0 3.4 1.7 2.0
44

general technical report pnw-gtr-883

Table 26—Average number of nights spent in the local area by segment by foresta 

(continued)

Nonlocal Local

 NonNational forest OVN-NF OVN OVN-NF OVN primary

 Number of nights

Wasatch-Cache 3.0 9.2 2.3 4.1

Wayne 2.3 2.6 2.0 0.4

Wenatchee 2.1 1.5 1.8 1.5

White Mountain 2.5 4.0 1.7 3.4

White River 3.2 6.3 1.6 5.5

Willamette 3.4 3.2 2.3 2.6 1.9

Winema 4.3 2.9 1.1

National average 3.2 4.4 2.4 3.7 2.9

a

 Estimated using the full data set and the case weights. If a forest has less than 15 cases in a segment, the value is left 

blank. In these instances, the national average may be used. OVN = overnight, NF = national forest.

6. Apply total spending within spending categories as final demand changes to an 

I-O model for the local region—The total spending estimated within each spending category can be applied to an I-O model for the local region using appropriate 

bridge tables to match the NVUM spending categories to IMpact Analysis for 

PLANning (IMPLAN) sectors. The spending profiles represent spending within a 

50-mi radius of the forest. 

7. Attribution issues—When making spending and contribution/economic impact 

estimates, some decisions must be made regarding which visits or spending should 

be counted. There are several alternatives. At one extreme is to count all spending 

within 50 mi of the forest by anyone who visits the national forest during a trip to 

the area. Adopting this extreme, all of the spending of anyone (including locals and 

nonprimary visitors) who visits the forest would be counted. This approach would 

include spending from incidental visits and quite a bit of spending not directly 

related to recreating on the national forest. At the other extreme is to make a “with 

vs. without” impact estimate and count only trips and spending that would not have 

been made in the absence of the forest recreation opportunities. Most situations, 

however, call for something in between. 

Whether to include spending by local residents is a common question. Some 

argue that local residents would spend the money locally regardless of the recreation opportunities on the national forest and that it doesn’t represent “new” money 

to the region. Others are interested in capturing all spending associated with forest 

recreation trips, which includes local resident spending. Taking a “with vs. without” approach, the question is whether this spending would remain in the region 

When making spending 

and contribution/

economic impact 

estimates, some 

decisions must be 

made regarding which 

visits or spending 

should be counted.
45

Estimation of National Forest Visitor Spending Averages From National Visitor Use Monitoring: Round 2

or go outside in the absence of forest recreation opportunities. If locals would go 

outside the region for recreation in the absence of national forest opportunities, 

their trip spending would represent a loss to the region’s economy. A loss of $100 

in local resident’s trip spending has the same effects as the loss from not attracting 

a nonresident trip. It therefore should be included in a “with vs. without” economic 

impact assessment. In most cases, some local substitution would occur and some 

additional trips would go outside the region in the absence of national forest recreation opportunities, so there isn’t a simple yes or no answer to the question of 

whether spending by local residents should be included. We recommend including 

spending by local residents to capture the economic contribution of forest recreation 

opportunities to the region, but excluding some or all of the local spending when 

estimating impacts. 

More problematic are trips to the region that are not generated by the national 

forest, but are made for some other purpose. The “nonprimary” purpose trip segment is included in our analysis so that these trips and associated spending may 

be treated separately. We recommend using the local day trip spending profile for 

nonprimary purpose trips when estimating the contribution of the forest to the local 

economy. The rationale is that the local day trip profile covers the additional spending of a recreation visit to the national forest for visitors who are already in the 

area for some other reason. It possibly excludes several nights of lodging and other 

expenses that are evident in the nonprimary trip spending profile, on the basis that 

this spending was not associated with the national forest visit. Only the additional 

spending for the national forest visit is assumed to be lost to the local economy in 

the absence of national forest recreation opportunities. This procedure will omit 

some lodging and related expenses associated with extending a stay in the area to 

visit the national forest. 

Some visitors would likely substitute other nearby recreation opportunities in 

the absence of those provided on the national forest. The extent of substitutions will 

depend on the local supply of recreation opportunities. In a pure “with vs. without” 

analysis, trips and associated spending that would not be lost to the region would 

also be excluded. Further study of substitution patterns would be required to fully 

address the substitution issue. More generally, many trips involving visits to the 

national forest will involve multiple purposes and activities, making it difficult in 

some cases to isolate which “caused” the trip to be made. 

8. High spending recreation parties—Nationally, a majority of those on recreation visits to the National Forest System are associated with those who spend less 

than $50 during the trip. However, a limited number of visits involve high spending 

and, because of the fairly conservative spending outlier rule we adopt in estimating 
46

general technical report pnw-gtr-883

spending profiles, our standard spending profiles may not fully represent spending by these high spending groups. One such group, downhill skiers, do have high 

spending patterns, and we have identified a spending profile applicable to economic 

analyses involving downhill skiers. Another group with potentially high spending 

that is not represented in our standard spending profiles is visitors using guides and 

outfitters. If it was possible, we would have identified visits involving the use of 

guides and outfitters and constructed a spending profile for that group. However, in 

the current NVUM survey instrument, no question clearly identifies those respondents using guides and outfitters. Even if such a question existed, it is possible 

that the resulting sample size of respondents using guides and outfitters would be 

inadequate (because these visits are such a small component of total recreation use 

and these visitors may be using nontraditional entry and exit points, not identified in NVUM, between private lands and the national forest) to reliably estimate 

the spending patterns of those using guides and outfitters. One of the spending 

categories (recreation and entertainment) does include reference to recreation guide 

fees, but the generality of the spending category makes it impossible to definitively 

identify those reporting guide expenses.

In cases where the spending by visitors using guides and outfitters, or other 

analyses involving high spenders, is an important component of the economic 

analysis and that spending is not adequately represented by the existing spending 

profiles, the forest could opt to (1) use one of the high spending profiles (or the 

downhill skier profile) we have reported here for the component of recreation use 

associated with guides and outfitters, (2) use the results of other studies that have 

reported reliable estimates of average or total spending of visits associated with 

guides and outfitters, or (3) use an engineering approach to construct a guide and 

outfitter spending profile applicable to the specific application. For the last option, 

the analyst can use an existing profile (e.g., the national-level average spending 

profile) and modify the average spending values in the appropriate categories (e.g., 

recreation and entertainment and lodging) to reflect the average costs in the local 

area associated with guide and outfitter use.

In a previous analysis for a national forest in U.S. Department of Agriculture, 

Forest Service Eastern Region, an engineering approach to estimate the average 

spending of visitors using horseback riding guides and outfitters was used. We 

describe that process here as an example of how to use an engineering approach 

to modify existing spending profiles. In that application, horse users who were 

recreating on the forest and using guides and outfitters were divided into day 

visits (those hauling horses to the outfitter and then recreating on the forest) and 

overnight visits (those hauling horses, staying overnight on the outfitter property, 
47

Estimation of National Forest Visitor Spending Averages From National Visitor Use Monitoring: Round 2

and taking day trips onto the forest). For the day-trip visits, we first determined 

the average spending in each expenditure category for local and nonlocal day trips 

using the national-level spending profile applicable to the forest. Next, we identified 

those expenditure categories that day horse users could reasonably be expected to 

have greater spending than other day users. Day horse users could reasonably be 

expected to pay more in gas and oil (as a result of hauling horse trailers) and could 

reasonably be expected to pay more in entry fees (to pay for parking at private horse 

outfitters that provide entry from their property to the forest). To account for this 

expected greater than average spending, we increased the total spending in the gas 

and oil expenditure category by $5 and increased the total spending in the entry 

fees category by $4 based on the published local prices at the time. 

For overnight visits, we identified an appropriate overnight spending profile 

as a base from which to begin. To accommodate the needs of the specific application, we converted that per-trip spending profile to a per-night basis assuming an 

average of two nights per trip. Based on local knowledge and published rates, we 

determined that overnight horseback visitors could be expected to spend more for 

lodging and in restaurants and bars than other overnight visitors. After examining 

published local outfitter prices at the time, we determined that overnight horse 

visitor parties could reasonably be expected to pay $35 in lodging for campsites and 

cabins and $25 in restaurants, all located on the outfitters and guides’ properties. 

We substituted these engineered expenditures estimated from local information into 

the appropriate spending categories in the per-night spending profile. Examination 

of local rates at the time indicated that parking fees on outfitter properties were 

waived for overnight visitors so we did not include additional expenditures in the 

entry fees expenditure category. 

An Example: Estimating Total Spending for the Hiawatha 

National Forest

The above steps for applying the spending profiles are illustrated for the Hiawatha 

National Forest in Michigan’s Upper Peninsula. Here we assume no visits by downhill skiers on the Hiawatha National Forest. Had there been downhill skier visits, 

we would have removed those visits from the estimate of total visits to the forest 

and duplicated the process detailed below for just the skier visits using the downhill 

skier spending profile (table 15). The number of recreation visits to the Hiawatha 

National Forest in 2007 was 546,000 based on the NVUM report (USDA FS 2007). 

Computation of total visitor spending is shown in table 27. In Round 2, we are 

now able to estimate spending profiles on a per-trip basis and a per-day/night basis, 

whereas the Round 1 spending profiles could only be estimated on a per-trip basis. 
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Table 27—Visitor spending for Hiawatha National Forest using National Visitor Use Monitoring (NVUM) dataa

 Nonlocal Local NonDay OVN-NF OVN Day OVN-NF OVN primary Totalb

Total recreation – – – – – – – 546,000

Segment shares (percent) 3 4 25 39 4 1 24 100

Visits by segmentb 16,380 21,840 136,500 212,940 21,840 5,460 131,040 546,000

Party size 2.4 2.4 2.7 1.9 2.5 2.4 2.5

Avg. number of days/nights 1 4.3 4.8 1 2.7 3.7 3.3

Party visitsb 6,825 9,100 50,556 112,074 8,736 2,275 52,416 241,981

Visits (number of days 

and nights)b 6,825 39,130 242,667 112,074 23,587 8,418 52,416 485,116

Average spending ($) 

(party trip) 88.02 352.37 781.95 27.81 181.65 347.74 27.81c

Average spending ($) 

(party day and night) 88.02 95.24 159.58 27.81 86.50 80.87 27.81d

Spending totalb ($) 601 3,207 39,532 3,117 1,587 791 1,458 50,292

Spending total 

(day and night)b 601 3,727 38,725 3,117 2,040 681 1,458 50,348

– = not applicable.

a

 Recreation visit estimate from Hiawatha National Forest NVUM report, segments shares from table 23, party sizes from table 25, average nights from 

table 26, and spending averages from tables 6 and 9. All figures expressed in 2009 dollars. OVN = overnight, NF = national forest. 

b

 Calculated rows are visits by segment = total recreation visits x segment share, party visits = visits by segment party size, party visits on a days/nights 

basis = party visits x average number of days/nights, spending total = spending ($/party/trip) x party visits, spending total (using day/night profile) = 

spending ($/party/day and night) x party visits on a day/night basis.

c

 The spending average for local day trips is used for nonprimary purpose trips to capture only the marginal change in spending owing to the national 

forest visit. 

d

 Here we assume that only 1 day of expenditures is associated with the visit to the national forest for nonprimary trips.

The approach to use the per-day/night spending profiles requires an additional 

calculation compared to the approach using the per-trip spending profiles. For most 

applications, we recommend using the per-day/night spending profiles because 

they better accommodate the different patterns of overnight length of stay across 

forests, whereas the per-trip spending profiles implicitly assume the same length 

of stay across forests. We detail both the per-trip and the per-day/night spending 

profile approaches below. We draw on several forest-specific figures from tables 

in appendixes 1 and 2. At some points in the calculation, because of small sample 

sizes, forest-specific parameters are not available, and we substitute national-level 

parameters. 

Recreation visits are first allocated to trip segments using the Hiawatha segment share estimates from table 23. Next visits are converted to party-visit basis 

by dividing by party size from table 25. If using the per-day/night spending profile, 

these party visits must be converted to party visits on a day/night basis by multiplying by the average number of days/nights on the trip (table 26). Party visits (or party 
49

Estimation of National Forest Visitor Spending Averages From National Visitor Use Monitoring: Round 2

visits on a per-day/night basis) are then multiplied by the per-party trip spending 

averages (or per-party day/night spending averages) to obtain total spending. The 

national high spending profiles are used in this example (tables 10 and 13) because 

the Hiawatha National Forest visitor spending patterns were deemed above the 

national average. Local visitors are included in this example, and the local day-trip 

spending average ($27.81) is applied to nonprimary purpose trips. 

Based on these calculations, recreation visitors to the Hiawatha National Forest 

spent approximately $50 million ($2009) in the local region in 2007. Local day trips 

accounted for 39 percent of visits and 6 percent of spending. Nonlocals on overnight trips staying off the forest account for 79 percent of the spending in the local 

area. The forest attracts a large number of visits from the nonprimary segment (24 

percent). Counting only the equivalent of local day trip spending (and just 1 day of 

expenditures when using the per-day/night spending profiles), the nonprimary segment accounts for $1.4 million in spending around the forest. Counting all spending 

by visitors whose primary purpose was not to recreate on the forest would increase 

spending attributed to the forest by $27 million. On the other hand, excluding all 

spending by local visitors would reduce the estimate by $5.5 million. 

To obtain spending in detailed categories (tables 28 and 29), simply multiply 

party visits (or party visits on a day/night basis) for each segment by the complete 

spending profile for that segment (e.g., table 10 or table 13). This itemizes spending 

within specific categories/sectors. The greatest spending for Hiawatha National 

Forest visitors is for lodging (about $13.3 million), restaurant meals (approximately 

$11.1 million), gas and oil ($7.7 million), and groceries ($6.4 million). 

As new recreation visit estimates become available, spending estimates may 

be updated by simply replacing the total visit estimate. Segment shares, party 

sizes, and spending averages based on the NVUM survey may also be modified 

as suggested by other local information sources or to simulate and evaluate future 

scenarios. In any event, the estimate of total spending for a given application should 

be based on the best estimates of each of the different inputs in the spending model. 
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Table 29—Total spending of Hiawatha National Forest recreation visitors using the per-party per-day/

night profilesa

Nonlocal Local NonSpending category Day OVN-NF OVN Day OVN-NF OVN primary Total

 Dollars

Motel 0 785 12,065 0 152 151 0 13,152

Camping 0 288 888 0 211 12 0 1,399

Restaurant 175 529 9,139 593 56 164 277 10,933

Groceries 59 724 4,050 473 895 172 221 6,594

Gas and oil 193 810 4,565 1,155 429 79 540 7,772

Other transportation 1 20 138 43 38 11 20 270

Entry fees 40 133 1,614 201 8 22 94 2,113

Recreation and 

entertainment 47 98 2,347 123 33 12 58 2,718

Sporting goods 20 191 1,058 439 193 34 205 2,141

Souvenirs and

other expenses 66 150 2,866 89 23 24 41 3,259

 Total 601 3,726 38,730 3,116 2,040 681 1,457 50,350

a

 All figures expressed in 2009 dollars. OVN = overnight, NF = national forest.

Table 28—Total spending of Hiawatha National Forest recreation visitors using per-party/trip spending 

profilesa

Nonlocal Local NonSpending category Day OVN-NF OVN Day OVN-NF OVN primary Total

 Dollars

Motel 0 675 12,316 0 118 175 0 13,284

Camping 0 248 907 0 164 14 0 1,333

Restaurant 175 455 9,328 593 44 190 277 11,062

Groceries 59 623 4,133 473 696 200 221 6,405

Gas and oil 193 697 4,659 1,155 334 92 540 7,670

Other transportation 1 17 141 43 30 12 20 264

Entry fees 40 115 1,648 201 7 26 94 2,130

Recreation and 

entertainment 47 84 2,395 123 26 14 58 2,747

Sporting goods 20 164 1,079 439 150 40 205 2,098

Souvenirs and other 

expenses 66 129 2,925 89 18 28 41 3,295

 Total 601 3,207 39,532 3,116 1,587 791 1,457 50,290

a All figures expressed in 2009 dollars. OVN = overnight, NF = national forest.
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Estimation of National Forest Visitor Spending Averages From National Visitor Use Monitoring: Round 2

Appendix 2: Supplemental Tables for Completing 

Economic Analyses 

Estimating the total spending, for the purposes of completing economic contribution analysis, of visitors to a recreation area is one use of the spending averages 

developed in this report. A variety of intermediate parameters and inputs are 

needed to estimate total spending. In this appendix, we provide the necessary 

parameters to estimate total spending of visitors to specific national forests or to 

all national forests collectively. In tables 30 and 31, we report results on recreation 

activities for all forests nationally. 
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Table 30—Participation in recreation activities and reported primary activity on 

the trip for all forests nationally

Primary All Economic

Recreation activity Participatinga activitya cases subsample

 Percent

Biking 4 2 2,041 681

Boatingb 6 3 3,846 1,263

Cross-country skiing 4 3 1,988 619

Developed camping 8 3 6,203 1,991

Downhill skiing 15 16 7,657 2,467

Driving 23 4 4,349 1,402

Fishing 13 8 8,892 2,911

General/relaxing 36 6 9,757 3,061

Hiking 41 19 22,767 7,224

Horseback riding 1 <1 1,091 380

Hunting 8 7 3,682 1,209

Nature relatedb 51 7 10,946 3,432

OHV useb 6 3 2,543 834

Other activityb 16 5 5,598 1,774

Other nonmotorized 6 2 4,154 1,295

Picnic 10 2 2,882 953

Primitive camping/backpacking 5 1 2,157 690

Resort 2 <1 451 150

Snowmobile 3 3 1,910 619

Multiple primary activities 0 1 1,704 591

No primary activity 0 <1 808 264

 Total 0 100 105,516 33,810

a Estimated using case weights on full sample. Percentage of participating sums to more than 100 percent 

because respondents could check multiple activities.

b

 “Nature-related” activities include viewing wildlife, viewing natural features, nature study, or 

visiting a nature center. Off-highway vehicle (“OHV use”) also includes other motorized activity 

and using motorized trails. “Boating” combines motorized and nonmotorized boating. The “Other 

activity” category includes gathering and visiting historical sites.
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Estimation of National Forest Visitor Spending Averages From National Visitor Use Monitoring: Round 2

Table 31—Trip segment distribution by primary activitya

Nonlocal Local

OVN- OVN- NonPrimary activity Day NF OVN Day NF OVN primary Total

Percent

Bikingb 5 4 7 71 1 1 11 100

Boatingb 12 15 13 43 4 1 12 100

Cross-country skiing 7 2 13 69 1 1 7 100

Developed camping 3 43 4 2 36 2 10 100

Downhill skiing 16 2 39 35 0 2 6 100

Driving 10 1 7 51 1 1 29 100

Fishing 13 13 9 55 3 1 6 100

General/relaxing 6 22 11 32 11 1 17 100

Hiking 8 4 9 62 1 1 15 100

Horseback riding 12 14 4 56 7 1 6 100

Hunting 10 15 10 55 5 2 3 100

Nature relatedb 10 4 12 34 1 1 38 100

OHV use

b 10 11 8 58 4 1 8 100

Other activityb 9 6 7 60 2 1 15 100

Other nonmotorized 9 5 9 61 2 1 13 100

Picnic 12 8 8 54 3 1 14 100

Primitive camping/ 

backpacking 5 48 4 3 28 3 9 100

Resort 2 33 9 23 19 2 12 100

Snowmobile 16 3 18 50 1 1 11 100

Multiple activities 9 12 13 44 6 1 15 100

No primary activity 35 6 3 41 3 1 11 100

National average 10 9 14 49 4 1 13 100

a

 Estimated from the full sample using case weights. OVN = overnight, NF = national forest.

b “Nature-related” activities include viewing wildlife, viewing natural features, nature study, or visiting a nature 

center. Off-highway vehicle (OHV) use also includes other motorized activity and using motorized trails. “Boating” combines motorized and non-motorized boating. The “Other activity” category includes gathering and visiting 

historical sites.
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Appendix 3: Wildlife-Related Visit Characteristics and 

Spending Averages 

This appendix presents two sets of spending profiles for national forest visitors. 

One set is for visitors whose primary activity on the forest was wildlife related; the 

other is for visitors whose primary activity was one of 22 other general recreation 

activities (nonwildlife related). The wildlife-related activity spending profiles can 

be used to evaluate the economic contribution of wildlife-related recreation activity 

on national forests. Estimates are based on the National Visitor Use Monitoring 

(NVUM) data for the 5 years of the NVUM Round 2 (fiscal year 2005 through 

fiscal year 2009). 

Wildlife-related respondents were identified by their answers to two questions 

on the NVUM survey: “What activities have you participated in while on this 

visit?” and “Of these, which was your primary recreation activity?” Respondents 

who selected “viewing wildlife,” “hunting,” or “fishing” as their primary recreation 

activity were considered wildlife-related visitors. 

Fifty-two percent of national forest visits involved participation in a wildliferelated activity during the visit (table 32). Thirty-nine percent involved wildlife 

viewing, 14 percent involved fishing, and 8 percent involved hunting. For 18 percent 

of national forest visits, the primary recreation activity was wildlife related. Two 

percent of visits were related to viewing wildlife as the primary activity, 8 percent 

involved fishing, and 8 percent involved hunting as the primary activity. Only 

respondents to the economic portion of the survey who stated that their primary 

recreation activity was wildlife related are used in the subsequent analysis to 

estimate spending profiles for wildlife-related recreation. 

Spending Profiles by Trip Segments 

For some types of trips, the average spending of wildlife-related visitors is greater 

than that of other visitors (table 33). Wildlife-related visitors spent more per trip 

than nonwildlife visitors when on local day trips or nonlocal overnight national 

forest trips. Relative to the types of trips taken, wildlife-related visits are slightly 

more likely to be local day trips and nonlocal OVN-NF trips and less likely to be 

nonprimary trips than nonwildlife related visits. That pattern is explained in part 

because anglers and hunters are disproportionately likely to be on local day trips 

and nonlocal OVN-NF trips. 

Tables 34 and 35 provide the detailed spending profiles for wildlife-related and 

nonwildlife related visitors, respectively. The spending profiles for nonwildliferelated visitors are similar to the overall national averages, because the majority of 
55

Estimation of National Forest Visitor Spending Averages From National Visitor Use Monitoring: Round 2

Table 32—Participation in wildlife-related activitya

Any wildlife- Viewing 

All cases related wildlife Fishing Hunting

General survey: 

Participated (No.) 105,516 61,511 50,512 18,636 4,611

Raw (percent) 100 58 48 18 4

Weighted (percent)b 52 39 14 8

Primary activity (No.) 105,179 15,163 2,258 9,047 3,858

Raw (percent) 100 14 2 9 4

Weighted (percent)b 18 2 8 8

Economic subsample:

Primary activity (No.) 32,955 4,808 688 2,911 1,209

Raw (percent) 100 15 2 9 4

Weighted (percent)b 19 2 9 8

a

 Respondents identifying multiple primary activities or failing to provide a primary activity are excluded from primary 

activity figures.

b

 Weighted figures adjust the sample for sampling exposure and disproportionate sampling across National Visitor 

Use Monitoring (NVUM) strata using NVUM case weights.

Table 33—Comparison of wildlife-related and nonwildlife-related visitor spendinga

Nonlocal Local NonDay OVN-NF OVN Day OVN-NF OVN primary Totalb

Dollars

Spending per party 

per trip:

Wildlife related $59 $281d $450 $39d $188 $180 $361 $141

Nonwildlife related $63 $222d $527 $32d $158 $221 $371 $182

Percent

Segment shares:c

Wildlife related 11 13 9 54 4 2 7 100

Nonwildlife related 10 8 15 47 4 1 15 100

a

 All dollar figures expressed in 2009 dollars.

b

 Spending averages are computed as a weighted average of the columns using the full information segment shares.

c

 Estimated from the full data using the case weights. 

d

 Means that differ based on comparison of 95 percent confidence intervals. OVN = overnight, NF = national forest.
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Table 34—Wildlife-related visitor spending by trip-type segment and spending category, 

dollars per party per tripa

Nonlocal Local Non- All

Spending categories Day OVN-NF OVN Day OVN-NF OVN primary visitsb

 Dollars

Motel 0.00 33.10 101.29 0.00 9.92 13.75 107.02 21.58

Camping 0.00 25.15 24.13 0.00 22.31 26.88 16.33 8.01

Restaurant 7.75 28.75 80.11 3.04 7.04 14.76 78.39 19.51

Groceries 10.06 66.00 76.16 6.54 66.39 46.77 49.27 27.11

Gas and oil 26.62 70.11 82.87 16.57 45.73 38.02 51.11 34.61

Other transportation 0.02 2.20 1.57 0.31 2.49 1.52 4.65 1.05

Entry fees 1.36 13.07 21.16 1.52 1.67 4.00 9.56 5.39

Recreation and 

entertainment 2.97 8.26 20.79 1.35 3.36 4.25 11.71 5.04

Sporting goods 8.15 27.21 26.92 9.68 26.35 22.12 12.42 14.45

Souvenirs and

other expenses 1.77 7.56 14.95 0.41 3.06 8.21 20.46 4.46

 Total 58.69 281.42 449.94 39.42 188.32 180.29 360.93 141.22

Sample size 

(unweighted) 375 798 452 1,719 252 78 390 4,064

Standard deviation 

(total) 68 406 622 54 178 181 592 n/a

n/a = not applicable.

a

 Outliers are excluded and exposure weights are applied in estimating spending averages. All figures expressed in 

2009 dollars. OVN = overnight, NF = national forest.

b

 The all-visit averages are computed as a weighted average of the columns using the wildlife-related segment 

shares as weights.
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Estimation of National Forest Visitor Spending Averages From National Visitor Use Monitoring: Round 2

Table 35—Nonwildlife-related visitor spending by trip-type segment and spending 

category, dollars per party per tripa

Nonlocal Local Non- All

Spending categories Day OVN-NF OVN Day OVN-NF OVN primary visitsb

 Dollars

Motel 0.00 33.65 161.56 0.00 4.66 38.48 115.57 44.83

Camping 0.00 27.22 17.83 0.00 23.83 14.84 11.55 7.69

Restaurant 16.89 25.71 117.40 5.65 6.74 38.44 89.55 38.10

Groceries 8.33 53.09 66.77 6.26 67.45 56.34 42.83 27.72

Gas and oil 22.43 48.36 68.90 12.02 36.30 40.69 48.15 31.18

Other transportation 0.70 1.73 4.45 0.09 0.18 0.99 3.14 1.41

Entry fees 5.24 7.90 17.85 2.32 4.08 7.52 11.25 6.85

Recreation and 

entertainment 4.62 7.56 28.36 1.53 3.52 5.99 17.17 8.82

Sporting goods 1.84 8.49 12.90 2.97 8.89 10.71 5.89 5.54

Souvenirs and

other expenses 3.44 7.86 30.65 0.79 2.81 6.55 26.31 10.07

 Total 63.49 221.59 526.66 31.63 158.47 220.56 371.41 182.20

Sample size 

(unweighted) 1,849 3,478 2,610 8,113 1,557 367 4,347 22,321

Standard deviation 

(total) 72 352 649 48 185 359 606 n/a

n/a = not applicable.

a

 Outliers are excluded and exposure weights are applied in estimating spending averages. All figures expressed 

in 2009 dollars. These averages exclude visitors who claimed their primary activity was downhill skiing. OVN = 

overnight, NF = national forest.

b

 The all-visit averages are computed as a weighted average of the columns using the nonwildlife-related segment 

shares as weights.

visitors fall into this group. The higher spending by wildlife-related visitors in some 

trip segments results primarily from higher spending on sporting goods and gas and 

oil. 

High and Low Spending Averages 

Table 36 provides a high spending profile similar to table 10, but for visitors who 

specified their primary activity was wildlife related. In many cases, when completing analyses for wildlife-related recreation, a forest identified as a high spending 

area (table 22) should use the profile in table 36 instead of the national average in 

table 34. Similarly, forests identified as low spending areas (table 22) should use the 

averages in table 37 for many wildlife-related analyses. The high and low spending 

profiles also can be used for wildlife-related visitor economic analysis aimed at 

specific geographical areas around a national forest with higher or lower than average spending opportunities or prices. 
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Table 36—High spending profiles for wildlife-related visitors by trip-type segment and 

spending category, dollars per party per tripa

 Nonlocal Local

Over- Over- Non- All

Spending category Day night Day night primary visitsb

Dollars

Motel 0.00 149.79 0.00 35.43 247.14 52.38

Camping 0.00 23.32 0.00 22.65 8.80 7.11

Restaurant 7.12 98.03 4.50 10.42 169.53 37.27

Groceries 6.36 93.19 5.81 90.69 76.57 35.14

Gas and oil 26.44 97.29 15.58 37.16 82.02 40.70

Other transportation 0.22 5.25 1.98 19.53 7.66 3.96

Entry fees 4.17 38.07 1.76 1.15 28.92 11.88

Recreation and 

entertainment 4.76 15.32 1.02 5.43 18.70 6.08

Sporting goods 11.31 40.46 12.21 53.07 20.69 21.37

Souvenirs and

other expenses 7.05 28.97 0.19 4.36 55.37 11.39

 Total 67.42 589.70 43.05 279.90 715.40 227.27

Sample size (unweighted) 29 184 194 28 74 509

Standard deviation (total) 67 800 66 256 780 n/a

n/a = not applicable.

a Outliers are excluded and exposure weights are applied in estimating spending averages. All figures expressed in 

2009 dollars. We have combined the overnight national forest and overnight (OVN-NF and OVN) segments into a 

single overnight segment.

b

 The all-visit averages are computed as a weighted average of the columns using the wildlife-related

segment shares as weights.
59

Estimation of National Forest Visitor Spending Averages From National Visitor Use Monitoring: Round 2

Table 37—Low spending profiles for wildlife-related visitors by trip-type segment and 

spending category, dollars per party per tripa

 Nonlocal Local 

Over- Over- Non- All

Spending category Day night Day night primary visitsb

 Dollars

Motel 0 26.17 0 3.84 58.22 10.06

Camping 0 17.22 0 22.82 6.99 5.65

Restaurant 7.53 26.95 2.23 6.19 37.86 10.98

Groceries 10.02 53.80 5.47 54.01 24.53 20.85

Gas and oil 25.95 69.20 15.85 39.41 37.64 31.64

Other transportation 0 0.62 0 0.38 0 0.16

Entry fees 0.54 2.83 0.96 2.04 3.20 1.55

Recreation and 

entertainment 2.00 6.53 1.17 1.76 3.25 2.62

Sporting goods 8.00 19.34 8.49 27.42 6.26 11.80

Souvenirs and other 

expenses 1.98 4.48 0.40 4.63 6.64 2.16

 Total 56.02 227.14 34.57 162.50 184.58 97.47

Sample size (unweighted) 144 359 751 146 113 1,513

Standard deviation (total) 70 303 44 147 328 n/a

n/a = not applicable.

a Outliers are excluded and exposure weights are applied in estimating spending averages. All figures expressed in 

2009 dollars. We have combined the overnight national forest and overnight (OVN-NF and OVN) segments into a 

single overnight segment.

b

 The all-visit averages are computed as a weighted average of the columns using the wildlife-related segment 

shares as weights.
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Tables 38 and 39 also provide high and low spending profiles, respectively, 

but these profiles exclude visitors who stated their primary activity was wildlife 

related. These tables can be used for economic analysis aimed at specific geographical areas around a national forest with higher or lower than average spending 

opportunities or prices, where it is desired to exclude wildlife-related visitation 

from the analysis. These tables are likely applicable only for those completing a 

strict programmatic analysis aimed at wildlife-related recreation. 

Wildlife-Related Visitor Trip and Party Characteristics 

Visitors whose primary activity was wildlife-related typically were recreating 

in smaller travel parties (table 40). For wildlife-related visitors, nonprimary trips 

involved the largest travel parties. On average, the number of nights in the local 

area is similar for wildlife and nonwildlife groups. However, wildlife-related visitors staying overnight on the national forest had longer lengths of stay compared to 

nonwildlife-related visitors. Those wildlife-related visitors were likely hunters and 

anglers who are in the area for an extended trip.

Wildlife-Related Visits 

The percentage of visits where the primary activity was wildlife-related differs 

across forests (table 41). For some forests, the percentage of visits that are wildliferelated is sensitive to the choice of weights—although this sensitivity is less than 

was found in Round 1. For example, for Land Between the Lakes National Recreation Area, the percentage of wildlife-related visits is 31 percent unweighted but 

increases to 49 percent when case weights are applied. Conversely, 40 percent of 

the visits on the Modoc National Forest were wildlife-related visits unweighted, 

but after applying the case weights, the share of wildlife-related visits decreases 

to 19 percent. Figures in table 41 should be used cautiously if the weighted and 

unweighted estimates are very different. The percentage of the NVUM visits classified as wildlife related on each forest depends somewhat on the relative proportion 

of site days assigned to distinct locations and seasons, as these may differentially 

attract wildlife-related visitors. 

Visitors whose primary 

activity was wildliferelated typically were 

recreating in smaller 

travel parties. 
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Estimation of National Forest Visitor Spending Averages From National Visitor Use Monitoring: Round 2

Table 38—High spending profiles for nonwildlife-related visitors by trip-type segment and 

spending category, dollars per party per tripa

 Nonlocal Local 

Over- Over- Non- All

Spending category Day night Day night primary visitsb

Dollars

Motel 0.00 191.80 0.00 27.80 171.06 71.16

Camping 0.00 20.74 0.00 14.71 9.50 6.93

Restaurant 28.21 145.33 5.41 26.05 135.46 60.41

Groceries 8.92 74.66 3.98 80.27 48.80 31.27

Gas and oil 28.58 85.16 9.52 38.99 54.08 36.98

Other transportation 0.16 2.02 0.13 1.50 5.60 1.46

Entry fees 6.18 23.82 1.80 3.61 22.89 10.55

Recreation and entertainment 7.18 37.49 1.12 3.50 28.44 14.31

Sporting goods 1.75 16.94 2.66 11.79 9.46 7.33

Souvenirs and other expenses 9.97 45.25 0.88 4.58 44.27 18.69

 Total 90.96 643.20 25.50 212.80 529.57 259.09

Sample size (unweighted) 184 1,064 1,275 170 974 3,667

Standard deviation (total) 95 718 47 357 660 n/a

n/a = not applicable.

a

 Outliers are excluded and exposure weights are applied in estimating spending averages. All figures expressed 

in 2009 dollars. We have combined the overnight national forest and overnight (OVN-NF and OVN) segments 

into a single overnight segment. These averages exclude visitors who claimed their primary activity was downhill 

skiing.

b

 The all-visit averages are computed as a weighted average of the columns using the nonwildlife-related segment 

shares as weights.
62

general technical report pnw-gtr-883

Table 39—Low spending profiles for nonwildlife-related visitors by trip-type segment and 

spending category, dollars per party per tripa

 Nonlocal Local 

Over- Over- NonSpending category Day night Day night primary All visitsb

Dollars

Motel 0.00 31.43 0.00 4.46 65.31 17.25

Camping 0.00 24.17 0.00 27.09 11.18 8.59

Restaurant 12.84 27.13 4.72 7.62 45.29 16.92

Groceries 7.94 46.64 6.66 64.66 26.87 21.91

Gas and oil 20.48 45.35 12.29 35.42 39.59 25.96

Other transportation 0.97 0.47 0.01 0.14 0.51 0.29

Entry fees 5.21 6.94 2.51 3.37 5.41 4.28

Recreation and entertainment 5.15 7.83 1.87 4.78 5.73 4.29

Sporting goods 1.65 5.92 3.16 9.95 2.36 3.86

Souvenirs and other expenses 2.05 7.47 0.54 3.30 12.98 4.29

 Total 56.28 203.35 31.75 160.78 215.23 107.64

Sample size (unweighted) 752 1,816 2,953 826 1,015 7,362

Standard deviation (total) 61 253 45 186 454 n/a

n/a = not applicable.

a

 Outliers are excluded and exposure weights are applied in estimating spending averages. All figures expressed in 

2009 dollars. We have combined the overnight national forest and overnight (OVN-NF and OVN) segments into a 

single overnight segment. These averages exclude visitors who claimed their primary activity was downhill skiing.

b

 The all-visit averages are computed as a weighted average of the columns using the nonwildlife-related segment 

shares as weights.

Table 40—Wildlife-related and nonwildlife-related visitor characteristicsa

 Nonlocal Local

Wildlife OVN- OVN- NonCharacteristic related Day NF OVN DAY NF OVN primary Total

 Number

People per vehicle Yes 2.1 2.2 2.2 1.9 2.2 2.0 2.3 2.0

No 2.6 2.8 2.7 2.1 2.7 2.6 2.6 2.4

Nights in the local area Yes 4.0 4.3 2.9 4.4 2.5 1.3

No 2.9 4.4 2.3 3.4 2.9 1.3

a Estimated from the full sample using the case weights. OVN = overnight, NF = national forest.
63

Estimation of National Forest Visitor Spending Averages From National Visitor Use Monitoring: Round 2

Table 41—Percentage of wildlife-related visits by foresta

No Exposure Case

National forest weights weights weights

 Percent

Allegheny 19 21 43

Angeles 7 8 7

Apache-Sitgreaves 27 27 25

Arapaho-Roosevelt 15 15 18

Ashley 26 26 41

Beaverhead-Deerlodge 35 36 42

Bighorn 11 11 22

Bitterroot 16 16 16

Black Hills 22 25 18

Boise 20 19 24

Bridger-Teton 16 14 15

Caribbean 8 7 7

Caribou-Targhee 9 8 20

Carson 9 8 12

Chattahoochee-Oconee 21 21 22

Chequamegon-Nicolet 12 12 20

Cherokee 10 10 18

Chippewa 46 46 49

Chugach 26 22 22

Cibola 9 9 12

Clearwater 24 24 29

Cleveland 4 3 3

Coconino 3 4 7

Columbia River Gorge 2 2 2

Colville 12 12 7

Coronado 7 6 11

Custer 16 14 13

Dakota Prairie 40 41 38

Daniel Boone 9 11 23

Deschutes 15 15 15

Dixie 21 22 24

Eldorado 9 9 10

Fishlake 43 39 49

Flathead 19 20 30

Francis Marion-Sumter 29 28 32

Fremont 41 41 66

Gallatin 10 8 8

George Washington-Jefferson 25 24 31

Gifford Pinchot 12 15 18

Gila 32 38 30

Grand Mesa-UncompahgreGunnison 17 15 10
64

general technical report pnw-gtr-883

Table 41—Percentage of wildlife-related visits by foresta

(continued)

No Exposure Case

National forest weights weights weights

 Percent

Green Mountain and 

Finger Lakes 8 9 14

Helena 20 20 24

Hiawatha 8 8 18

Hoosier 20 20 21

Humboldt-Toiyabe 7 6 7

Huron-Manistee 31 31 49

Idaho Panhandle 15 15 26

Inyo 14 12 10

Kaibab 5 4 12

Kisatchie 23 23 30

Klamath 11 11 21

Kootenai 20 23 37

Lake Tahoe Management Unit 2 3 3

Land Between the Lakes 31 35 49

Lassen 33 35 31

Lewis and Clark 16 16 30

Lincoln 5 5 5

Lolo 9 8 10

Los Padres 9 8 8

Malheur 30 28 48

Manti-La Sal 25 24 24

Mark Twain 23 22 26

Medicine Bow 20 20 23

Mendocino 5 4 5

Midewin Tallgrass Prairie 45 43 46

Modoc 40 38 19

Monongahela 19 17 8

Mount Baker-Snoqualmie 1 1 1

Mount Hood 5 5 6

National forests in Alabama 6 6 13

National forests in Florida 16 16 40

National forests in Mississippi 43 42 50

National forests in North Carolina 11 10 16

National forests in Texas 43 43 59

Nebraska 21 21 41

Nez Perce 14 14 17

Ochoco 23 24 22

Okanogan 10 10 14

Olympic 7 8 27

Ottawa 18 19 16

Ouachita 17 18 40
65

Estimation of National Forest Visitor Spending Averages From National Visitor Use Monitoring: Round 2

Table 41—Percentage of wildlife-related visits by foresta 

(continued)

No Exposure Case

National forest weights weights weights

 Percent

Ozark-St. Francis 12 13 41

Payette 21 20 29

Pike-San Isabel 10 10 27

Plumas 28 30 29

Prescott 10 10 7

Rio Grande 14 12 13

Rogue River 10 9 12

Routt 9 9 5

Salmon-Challis 44 49 45

San Bernardino 8 8 4

San Juan 9 9 9

Santa Fe 13 10 7

Sawtooth 8 8 9

Sequoia 11 15 18

Shasta Trinity 17 17 22

Shawnee 10 11 18

Shoshone 14 12 16

Sierra 6 4 6

Siskiyou 13 13 24

Siuslaw 15 16 12

Six Rivers 10 9 19

Stanislaus 12 11 24

Superior 22 21 21

Tahoe 13 12 14

Tongass 14 11 15

Tonto 15 14 15

Uinta 15 15 11

Umatilla 20 18 20

Umpqua 23 27 37

Wallowa-Whitman 20 21 25

Wasatch-Cache 6 5 3

Wayne 12 11 21

Wenatchee 13 15 28

White Mountain 2 2 1

White River 6 6 2

Willamette 19 19 20

Winema 28 28 24

National average 14 14 18

a Wildlife-related percentages are estimated using the full sample. Respondents 

reporting multiple primary activities or failing to provide a primary activity are 

excluded.
Pacific Northwest Research Station

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