Environmental Valuation using Revealed Preference Methods • Lectures include: – A little welfare economic theory that forms basis of environmental valuation techniques – Conceptual implementation issues – Econometric implementation issues • Illustrations using actual applications • Hands-on experience using actual data
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Environmental Valuation using Revealed Preference Methods
Environmental Valuation using Revealed Preference Methods. Lectures include: A little welfare economic theory that forms basis of environmental valuation techniques Conceptual implementation issues Econometric implementation issues Illustrations using actual applications - PowerPoint PPT Presentation
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Environmental Valuation using Revealed
Preference Methods
• Lectures include:– A little welfare economic
theory that forms basis of environmental valuation techniques
– Conceptual implementation issues
– Econometric implementation issues
• Illustrations using actual applications
• Hands-on experience using actual data
Why are there so many more stated preference
than revealed preference studies?
• Less statistical knowledge necessary? (perhaps?)
• RP can’t handle existence value? (not always relevant)
• Nature conspires against revealed preference methods
What Concepts Do We Need?
• A theoretical model of how people make decisions in some environmentally related context
• A means of relating this behavior to a well-defined welfare measure
• A means of obtaining consistent estimates of the parameters of the behavioral functions
• A mathematical relationship between the parameters and the welfare measure
What Data/Circumstances Do We Need for RP
Methods to have a Chance?
• Behavior “footprints” – environmental change must influence some behavior
• Behavioral change must constitute most of, and not more than, a response to environmental change
• Behavior must relate to money prices
Stated and Revealed Preference
• Stated preference methods– very sensitive to way ask question– not so sensitive to econometric
specification
• Revealed preference – not so sensitive to data collection
methods – very sensitive to econometric
specification
Why?
• In SP you are asking people directly for their values
• In RP you are asking people for facts and then you are deducing values based on models of behavior
Models of recreational demand are really household production models.
Household production models are about allocating both money and time.
Household Production Including Time Allocation
Maximization decision is now:
)()''(
)),,(,(max,,
thTxrqpwhm
btxzqUqtx
The household production function now includes time spent in taking trips.The money constraint explicitly takes account of labor time.
Valuing time as function of wage rate
If people can easily substitute work for leisure, then the opportunity cost of time is (after-tax) wages and two constraints collapse into one:
)''(
)),,(,(max
)'')((
)),,(,(max
,,
,,
wtxrqpwTm
btxzqU
xrqptTwm
btxzqU
qtx
qtx
Full incomeFull price
Corner and Interior Solutions in Labor Market
If some people have fixed work times, then work/leisure substitution may not be easy.
In these cases, time constraint does not collapse into money constraint and two constraints remain.
Some Labor Market Solutions
Leisure
Money
T=total available time
Slope=wage rate
h=labor
Earned income =w*h
indifference curve
T=total available timeLeisure
Money
Earned income =w*h
Slope=implicit wage rate of primary job
INTERIORSOLUTION
CORNERSOLUTION
h=labor
Slope=wage rate of secondary job
In Practice….
• Labor market model has better theoretical basis, but…– Difficult to determine which
respondents have flexible time– Sometimes multicollinearity
between time and money costs if included separately in model
• “Ad hoc” opportunity cost of time model often values time at some fraction of the wage rate (e.g. .4 or .5 – may change with different tax rates)
What happens if ignore time costs?
Since time costs and money costs are generally correlated, leaving out time will cause an upward bias in the coefficient on money costs.
“True” model is:
...)(
)(
2
10
wTwhm
wtcz
But you estimate:
...)(2
10
whm
cz
If measuring value of site…
with a linear demand function…
Number of tripsz
“true” 1/1
biased 1/1 estimate
Constant marginalcost of z
Consumer surplus =1
2
2z
0zc
(Note: since the dependent variable in the model is trips, the slope of the line in the graph is really 1/1).
Consumer surplus is underestimated
If measuring value of site…
with a semi-log demand function,
consumer surplus = -z/1
Estimate of CS will also be biased downward if your estimate of 1 is biased upward.
Specification issue #2:
Demand function for z should include money and time costs (and environmental quality) of substitutes.
If substitutes left out and these are correlated over the sample with the “own” money and time costs (and quality), then estimates will be biased.
Suppose there are two sites, A and B, thatare substitutes in recreation.
As you look across observations on people who visit these sites, suppose people who live far from one site also tend to live relatively far from the other site.
Now, suppose you make the mistake of estimating the demand for trips to site A without including costs to site B.