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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 Englin Arizona State University Mesa, AZ USA Kevin House University of Nevada, Reno Reno, NV USE. - PowerPoint PPT Presentation
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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