THE VALUATION OF ENVIRONMENTAL AMENITIES ACROSS BROAD GEOGRAPHIC REGIONS:

AN EMPIRICAL APPLICATION OF THE HEDONIC TRAVEL COST METHODOLOGY TO THE FORESTS OF THE SIERRA NEVADA WILDERNESS

Jeffrey EnglinArizona State UniversityMesa, AZ USA

Kevin HouseUniversity of Nevada, RenoReno, NV USE

Overview• Historical context of the hedonic travel cost model• Hedonic travel cost model intuition• Theory• Implementation Issues• Data• Results• Conclusions and speculations

Historical context of the hedonic travel cost model

• Proposed by Brown and Mendelsohn in 1984• At the same time RUM models were becoming tractable• US Environmental Protection Agency ran a large proposal

competition and chose the RUM to develop• US Environmental Protection Agency focus was on site

remediation • Hedonic travel cost models have been applied

sporadically (about a dozen times) since 1984

Why refocus now?• Hedonic travel cost models produce regional (national)

welfare measures• Suitable for regional (national) regulations and

development objectives• Forms a utility theoretic alternative to meta analysis

• Pendleton and Mendelsohn (2000) show theoretical equivalence with RUM Models

• Can often be applied where insufficient studies exist for a meta analysis

• Quantitative possibilities have grown enormously since 1984 – many new tools are available!

• GIS• Econometric tools

Hedonic Travel Cost Model Intuition• Follows traditional hedonic theory• Consumers choose best bundle of attributes given the

prices they face• In a this setting the cost is the price they face

• The precise prices consumers face depends on where they live – or which market they purchase trips in

• Cost may be out-of-pocket travel cost, time travel cost etc. It is the opportunity cost of the trip.

• The site chosen is the best bundle of attributes given the travel costs

Theory

• Model follows classic two-stage hedonic models• Stage 1 is to realize that people in different markets

probably face different prices• In Nancy, Metz, etc look at all the hiking trails residents of each

town chose and regress travel costs on the attributes of the trail • Stage 2 is to take the different quantities purchased at the

individual level prices and regress them on the quantities bought• Pool individuals across Nancy, Metz etc and regress the quantities

of attributes they purchased on the marginal hedonic prices estimated in stage

Implementation Issues

• Can be either a survey or visitation count method• Surveys need to elicit places visited and cost• Visitation counts (common in North America)

• Develop mean marginal and total willingness to pay measures for site attributes by the population

• Covers broad geographic areas • Values can be aggregated up by total visitation to a place

Data

• Uses permit data from US Forest Service for• Ansel Adams, Golden Trout and John Muir Wilderness Areas

• Total users total 25,363• There are 57 sites (trails) in the data• Data includes 1991, 1992, and 1993 users

Detail of the Study Area

Study area of population

To put population study area in perspectiveName of Country/State Area in km2Three European Countries

France 675000 km2

Spain 504000 km2

Germany 357000 km2

Combined Area 1536000 km2

Study Area

California 414000 km2

Arizona 295000 km2

Nevada 286000 km2

Oregon 254000 km2

Washington 184000 km2

Study Area Total 1433000 km2

Site attributes• Ecosystem attributes

• Lodgepole pine• Other conifers• Riparian meadows

• Development attributes• Trailhead campgrounds• Nearby campgrounds• Dirt roads

Analysis• Two methods have been used to estimate marginal

prices, both are applied here• Marginal prices and demand are estimated for the

attributes of interest • Both marginal and total welfare measures are calculated

Econometric and Welfare Results• Present Summary of Econometric Price Regression/LP

Results• Summarize 155 regression marginal price regression estimates

• uses only sites chosen• Summarize 186 LP marginal price estimates

• uses all possible sites• Summarize marginal welfare implications

• Present Summary Hedonic Demand Systems• Seven attributes for each method• Summarize total welfare implications (consumer surplus measures)

Summary of the Hedonic Price Estimates

Regression Approach LP Approach

Total Significant Marginal Marginal

Variables units NegativePositive NegativePositiveDistance

PriceDistance

Price

Dirt Roads miles 71 84 4 9 0.38 2.18

Riparian Meadows acres 70 85 0 10 0.03 0.21

Trailhead Campgrounds 0,1 104 51 13 3 -6.9 6.99

Nearby Campgrounds 0,1 50 105 5 17 9.91 40.99

Peak Elevation1,000's of

feet 98 61 44 47 -1.91 13.16

Lodgepole Pine miles 100 55 25 46 -0.88 6.78

Other Conifers miles 38 117 1 7 7.04 15.69

On the issue of insignificant and negative marginal prices

Total Marginal Social Value of Site Attributes for an Example Trail in the Ansel Adams Wilderness

Attribute Quantity Regression Linear Programming

Dirt Roads 0 2.27 259.1

Riparian Meadows 1.2 0.23 15.52

Trailhead Campgrounds 0 -227.11 810.12

Nearby Campgrounds 0 306.88 2102.53

Peak Elevation 10.2 297.82 965.05

Lodgepole Pine 0.4 151.85 773.19

Other Conifers 5.5 168.66 986.43

Number of Visitors 67

Hedonic Price Regression Demand ResultsQuantities

Prices Dirt Wet Trailhead Nearby Peak Lodgepole OtherRoads Meadows Campgrounds Campgrounds Elevation Pine Conifers

Dirt Roads -0.212 -4.388 0.122** -0.003 -0.049 0.700** 0.036( -1.498 ) ( -1.319 ) ( 2.646 ) ( -0.089 ) ( -0.683 ) ( 4.925 ) ( 0.933 )

Wet Meadows -4.388 -314.77** -0.822 0.593 -4.592* 10.670** 2.617**( -1.319 ) ( -2.099 ) ( -0.519 ) ( 0.476 ) ( -1.917 ) ( 2.364 ) ( 2.338 )

Trailhead Campgrounds 0.122** -0.822 -0.102** 0.022 0.034 -0.322** 0.054**( 2.646 ) ( -0.519 ) ( -2.955 ) ( 1.152 ) ( 0.913 ) ( -4.606 ) ( 3.571 )

Nearby Campgrounds -0.003 0.593 0.022 -0.036* 0.157** 0.014 -0.112**( -0.089 ) ( 0.476 ) ( 1.152 ) ( -1.762 ) ( 5.399 ) ( 0.241 ) ( -8.529 )

Peak Elevation -0.049 -4.592* 0.034 0.157** -0.464** -0.029 0.276**( -0.683 ) ( -1.917 ) ( 0.913 ) ( 5.399 ) ( -6.052 ) ( -0.226 ) ( 10.550 )

Lodgepole Pine 0.700** 10.670** -0.322** 0.014 -0.029 -1.897** 0.215**( 4.925 ) ( 2.364 ) ( -4.606 ) ( 0.241 ) ( -0.226 ) ( -6.839 ) ( 4.443 )

Other Conifers 0.036 2.617** 0.054** -0.112** 0.276** 0.215** -0.257**( 0.933 ) ( 2.338 ) ( 3.571 ) ( -8.529 ) ( 10.550 ) ( 4.443 ) ( -9.279 )

Mean Demand System Welfare Results

Regression Approach LP Approach

VariableMean

QuantityMean Marginal

PriceConsumer Surplus

Mean Marginal Price

Consumer Surplus

Dirt Roads 0.49 $0.19 $28.56 $1.09 $5.93

Riparian Meadows 20.287 $0.02 $32.69 $0.10 $518.55 Trailhead Campgrounds 0.407 -$3.45 $39.91 $3.49 $46.94

Nearby Campgrounds 0.297 $4.96 $53.85 $20.95 $28.71

Peak Elevation 10.897 -$0.96 $210.74 $6.58 $19,234.02

Lodgepole Pine 0.872 -$0.44 $9.63 $3.39 $14.60

Other Conifers 0.187 $3.52 $3.34 $7.88 $3.52

Conclusions and speculations• Provides a tool to answer large scale questions• Can be implemented much more easily with modern tools

• GIS for attributes, costs• Statistical tools easily handle data

• May work well in European context• Can be implemented in countries with few empirical studies • No more costly than other surveys (if needed)• Less demanding of analyst than RUMs or choice modeling• Based solely on observed choices – no stated preference biases