Choice Modeling Externalities: A Conjoint Analysis of Transportation Fuel Preferences Matthew Winden...
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Transcript of Choice Modeling Externalities: A Conjoint Analysis of Transportation Fuel Preferences Matthew Winden...
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
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 RiskVs(2) Natural Resource DepletionVs(3) Environmental Damage
Motivation
Attribute Examples of Attribute ComponentsEnv. Damage: 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 Levels of Attribute ComponentsEnv. Damage 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 DamageNatural Resource UsageHuman Health RiskPrice
Methodology: Conjoint Analysis
Envi-ron-
mental Damage
Natural Resource
Use
Human Health Risk
0
20
40
60
80
100
50 50 50
$[GASPRICE] per gallon
Current Fuel Mix
Methodology: Conjoint Analysis
Envi-ron-
mental Damage
Natural Resource
Use
Human Health Risk
0102030405060708090
100
62.537.5 50
$[GASPRICE] per gallon
Fuel Mix A
Methodology: Conjoint Analysis
RUM frameworkVi
j = V(xij , β) + εi
j
i = individualj = alternativex = vector of attributes and characteristics ε = stochastic error term
Methodology: Conjoint Analysis
RUM Formalized: Linear and IID
Vij = β0 + xi
j β1 + (Mi - pi
j) β2 + εij
M = Incomep = 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
SurveyRepresentative Sample of 857 Ohio AdultsCompleted 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 = $1.88min = $1.00max = $2.99
• Attribute means 49.9(ED), 50.2(NR), 50.3(HH)
ResultsAttribute Conditional Logit Parameter EstimatesPrice -1.722*Env. Damage -0.099Nat. Res. Use -0.427*Hum. Health Risk 0.142(Environmental Damage)2 -0.0003(Nat. Res. Use)2 0.003*(Hum. Health Risk)2 -0.002*EnvDam × NatRes 0.003NatRes × HumHea 0.002HumHea × EnvDam 0.001EnvDam×NatRes×HumHea -0.0001
ResultsAlternative (Difference from Current) WTP ($/Alternative)10% Reduction in Each Attribute $0.84/gal25% Reduction in Each Attribute $2.98/gal
Attribute MP ($/Alternative)Environmental Damage Reduction $0.030/galNatural Resource Use Reduction $0.035/galHuman Health Risk Reduction $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)