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Valuation 9: Travel cost modelPowerPoint Presentation

Valuation 9: Travel cost model

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Valuation 9: Travel cost model. A simple travel cost model of a single site Multiple sites Implementation The zonal travel cost method The individual travel cost model Travel cost with a random utility model. Last week. Revealed preference methods Defensive expenditures Damage costs

Valuation 9: Travel cost model

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- A simple travel cost model of a single site
- Multiple sites
- Implementation
- The zonal travel cost method
- The individual travel cost model

- Travel cost with a random utility model

- Revealed preference methods
- Defensive expenditures
- Damage costs
- Defensive expenditures: A simple model
- An example: Urban ozone

- Most frequently applied to valuation of natural environments that people visit to appreciate
- Recreation loss due to closure of a site
- Recreation gain associated with improved quality

- Natural areas seldom command a price in the market
- Basic premise: time and travel cost expenses represent the „price“ of access to the site
- WTP to visit the site

- Travel is a complement to recreation

- Application of TCM
- Reservoir management, water supply, wildlife, forests, outdoor recreation etc.

- History: Harold Hotelling 1947
- Value of national parks

- Variations of the method
- Simple zonal travel cost approach
- Individual travel cost approach
- Random utility approach

- A single consumer and a single site
- The park has the quality q
- higher qs are better

- Consumer chooses between visit to the park (v) and market goods (x)
- He works for L hours at a wage w and has a total budget of time T
- He spends p0 for the single trip
- The maximisation problem is:

- The maximisation problem is:
- The maximisation problem can be reduced to
- For a particular consumer the demand function for visits to the park is:

- What is the WTP for a small increase in quality?
- For a given price the demand increases
- Consumer would visit more often

- What is the marginal WTP ?
- Surplus gain from quality increase / change in quality

pv

A

C

p*

B

f(pv,q1+Dq,y)

f(pv,q1,y)

v1

v2

v

- If we repeat the above experiment for a variety of quality levels, the marginal WTP-function for quality can be generated
- However, consumer chooses among multiple sites
- The demand for one site is a function of the prices of the other sites as well as the qualities
- For three sites the demand function for one site changes to
- This is straightforward but empirical application is more complicated
- Random utility models (RUM)

- Visiting site i gives utility
- b is a parameter and e is an error term representing unknown factors
- We do not observe utility but consumer choice
- If consumer chooses site i over site j than ui> uj
- Different values of b yield in different values of ui and uj
- From b we can compute the demand for trips to a site as a function of quality of the site and the price of a visit
- We can then examine how demand changes when quality of the site changes

- The approach follows directly from the original suggestion of Hotelling
- Gives values of the site as a whole
- The elimination of a site would be a typical application

- It is also possible to value the change associated with a change in the cost of access to a site
- Based on number of visits from different distances
- Travel and time costs increase with distance
- Gives information on „quantities“ and „prices“
- Construct a demand function of the site

- Define a set of zones surrounding the site
- Collect number of visitors from each zone in a certain period
- Calculate visitation rates per population
- Calculate round-trip distance and travel time
- Estimate visitors per period and derive demand function

Visits/1000 = 300 – 7.755 * Travel Costs

So now we have two points on our demand curve.

- Not data intensive, but a number of shortcomings
- Assumes that all residents in a zone are the same
- Individual data might be used instead
- More expensive
- Sample selection bias, only visitors are included

- Assumption that people respond to changes in travel costs the same way they would respond to changes in admission price
- Opportunity cost of time
- Single purpose trip
- Substitute sites
- Unable to look at most interesting policy questions: changes in quality

- Single-site application of beach recreation on Lake Erie within two parks in 1997 (Sohngen, 2000)
- Maumee Bay State Park (Western Ohio) offers opportunities beyond beach use
- Headlands State Park (Eastern Ohio) is more natural

- Data is gathered on-site (returned by mail)
- Single-day visits by people living within 150 miles of the site
- Response rate was 52% (394) for Headlands and 62% (376) for Maumee Bay

- Substitute sites
- Nearby beaches similar in character
- One substitute site for Maumee Bay and two for Headlands

- Variables included
- Own price
- Substitute prices
- Income
- Importance (scale from 1 to 5) of water quality, maintenance, cleanliness, congestion and facilities
- Dummy variable measures whether or not the primary purpose of the trip was beach use

- Trip cost was measured as the sum of travel expenses and time cost
- Time cost: imputed wages (30% of hourly wage) times travel time

- Functional form
- They tried different specifications and chose a Poisson regression

- Per-person-per-trip values are:
- $25 for Maumee Bay
=1/0.04

- $38 for Headlands
=1/0.026

- Extremely flexible and account for individuals ability to substitute between sites
- Can estimate welfare changes associated with:
- Quality changes at one/many sites
- Loss of one/many sites
- Creation of one/many new sites

- Main drawback: estimate welfare changes associated with each trip
- Visitors might change their number of visits

- Zonal travel cost method – trips to one site by classes of people
- Individual travel cost method – trips to one site by individual people
- Random utility models – trips to multiple sites by individual people