Choice Modeling Externalities:
A Conjoint Analysis of
Transportation Fuel Preferences
Matthew Winden and T.C. Haab, Ph.D.
Agricultural, Environmental, and Development Economics
The Ohio State University
Outline
• Motivation
• Methodology
• Results
• Conclusions
Motivation
• Transportation Fuel Consumption Creates Large
Externalities
• Market Pricing Mechanism Has Failed
-Public Goods Nature of Externalities
• Government Correction Has Failed
-Regressive Nature of Price Correction
-Lack of Political Will Power
Motivation
• Correct price is necessary to achieve efficiency
So,
• What are the optimal levels (costs) of
externalities to society?
• Knowing allows internalization (MSC=MPC)
Motivation
• Are externality types valued differently?
• Impacts on:
(1) Human Health Risk
Vs
(2) Natural Resource Depletion
Vs
(3) Environmental Damage
Motivation
Attribute
Env. Damage:
Examples of Attribute Components
Fish and Animal Populations
Levels of Air and Water Pollution
Nat. Res. Use:
Extraction Rates and Stocks for Ores,
Minerals, Oil, Natural Gas
Hum. Health Risk: Incidence Rate of Asthma & Cancers
Motivation
• Goals:
1.) Establish Willingness-To-Pay estimates for
reductions in damages
2.) Establish Marginal Price estimates for
externality classes
Methodology: Conjoint Analysis
• Estimates the structure of preferences
• Specify attributes & bundle into alternatives
• Respondent chooses preferred alternative
• Resultant choices allow for statistical inference
Methodology: Conjoint Analysis
• Each alternative represents potential fuel
profile (i.e. mix of fuel types used)
• Different profiles embody different levels of
externalities (attributes) imposed on society
• Impacts of profile measureable and capable of
aggregation into an index for each externality
Methodology: Conjoint Analysis
Attribute
Env. Damage
Levels of Attribute Components
37.5, 45, 50, 55, 62.5
Nat. Res Use
37.5, 45, 50, 55, 62.5
Hum. Health Risk
37.5, 45, 50, 55, 62.5
Price ($/gallon)
-10%, -5%, 0%, 5%, 10%
Methodology: Conjoint Analysis
• Based in RUM Framework
• Respondent chooses 1 of 3 alternatives
• Attributes:
Environmental Damage
Natural Resource Usage
Human Health Risk
Price
Methodology: Conjoint Analysis
Current Fuel Mix
$[GASPRICE] per gallon
100
90
80
70
60
50
40
30
20
10
0
50
50
50
Environmental
Damage
Natural
Resource Use
Human Health
Risk
Methodology: Conjoint Analysis
Fuel Mix A
100
90
80
70
60
50
40
30
20
10
0
$[GASPRICE] per gallon
62.5
Environmental
Damage
37.5
50
Natural
Resource Use
Human Health
Risk
Methodology: Conjoint Analysis
RUM framework
Vij = V(xij , β) + εij
i = individual
j = alternative
x = vector of attributes and characteristics
ε = stochastic error term
Methodology: Conjoint Analysis
RUM Formalized: Linear and IID
Vij = β0 + xij β1 + (Mi - pij) β2 + εij
M = Income
p = price
Methodology: Conjoint Analysis
Probability of K chosen over j, for all j≠k
Pr(dVij>0) = ϑ (Δ(x) β1 – Δ(p) β2)
(See Kanninen 2007)
Results
Survey
Representative Sample of 857 Ohio Adults
Completed by 537 (62.5%),
532 useable; met criteria of
(1) Adult Resident of Ohio
(2) Estimate Vehicle MPG
(3) Estimate price of fuel at last fill-up
Results
• Homeowner, Older, and Driver (more likely)
• Price (self-reported)
mean = $1.88
min = $1.00
max = $2.99
• Attribute means 49.9(ED), 50.2(NR), 50.3(HH)
Results
Attribute
Price
Env. Damage
Nat. Res. Use
Hum. Health Risk
(Environmental Damage)2
(Nat. Res. Use)2
(Hum. Health Risk)2
EnvDam × NatRes
NatRes × HumHea
HumHea × EnvDam
EnvDam×NatRes×HumHea
Conditional Logit Parameter Estimates
-1.722*
-0.099
-0.427*
0.142
-0.0003
0.003*
-0.002*
0.003
0.002
0.001
-0.0001
Results
Alternative (Difference from Current)
10% Reduction in Each Attribute
25% Reduction in Each Attribute
WTP ($/Alternative)
$0.84/gal
$2.98/gal
Attribute
Environmental Damage Reduction
Natural Resource Use Reduction
Human Health Risk Reduction
MP ($/Alternative)
$0.030/gal
$0.035/gal
$0.036/gal
Conclusions
• Demand (WTP) for reduction in externalities
related to transportation fuel usage exists
• Current (baseline situation) reveals one class
of externality is not viewed as more important
• Starting point for policy discussions
Limitations
• Price increase still necessary (political will)
• Less impact, result in more driving?
• Do respondents accurately understand and
value indexes?
• Accurate measurement and combination of
attribute components into indexes
• Uncertainty of externality impacts
Future Research
• Income element of utility function may be
non-linear
• Fatigue/Learning Effects
• Exploration of demographic differences
(mixed logit)
• Relaxation of IIA (multinomial probit)
Special Thanks
• National Science Foundation
• Agricultural, Environmental, and
Development Economics: The Ohio State
University
• Wisconsin Economic Association