A N E CONOMIC E STIMATION OF THE P RODUCTION C OSTS OF I
MPROVING A UTOMOBILE F UEL E FFICIENCY Takahiko Kiso August 8, 2011
Camp Resources XVIII
Slide 2
I NTRODUCTION Automobile fuel economy is an important policy
issue Current goal: improve average fuel economy by 40% between
2009 and 2016 $1300 increase in new vehicle prices on average
Economics papers on policies to improve fuel economy Austin and
Dinan (2005) Bento, Goulder, Jacobsen and von Haefen (2009) Klier
and Linn (2010) Coleman and Harrington (2010) etc
Slide 3
I NTRODUCTION Production cost estimates for fuel efficiency
improvement are a crucial factor National Research Council (2002,
2010) provides engineering-based estimates of incremental costs of
fuel efficiency improvement.
Slide 4
I NTRODUCTION Estimated costs ($) of 0.1 gallon per 100 miles
reduction in fuel consumption (NRC, 2002):
Slide 5
I NTRODUCTION Potential shortcomings of NRC estimates Free
lunch for some inexpensive technologies Estimates available only at
vehicle class level Estimates have wide ranges
Slide 6
G OALS Provide alternative/complementary cost estimates based
on economics Estimate hedonic cost function for improving fuel
efficiency through economic models Incremental cost as function of
vehicle attributes (fuel efficiency, weight, etc) Provide cost
estimates for each vehicle (NRC: vehicle class level) Compare
economics-based and engineering-based estimates Simulate and
compare effectiveness of different policies for improving
fleet-wide fuel economy
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O VERVIEW OF RESULTS Cost of reducing fuel consumption per 100
miles by 0.1 gallon is around $50-$80 Overall, comparable to NRCs
estimates Marginal costs vary within and across vehicle classes.
Higher cost of improvement if a vehicle is More fuel efficient
Heavier
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M ODEL F RAMEWORK 1) Estimate discrete choice model of
consumers new vehicle purchases. 2) Express each vehicle models
market share as function of parameters of discrete choice model. 3)
Consider automakers optimization problem under oligopoly, using the
market share function. 4) FOCs imply marginal cost of fuel
efficiency improvement for each model. 5) Estimate hedonic
(marginal) cost function by regressing implied marginal cost on
vehicle attributes. Analogous to 2 nd stage of standard hedonic
pricing model
Slide 9
D ATA 2001 National Household Travel Survey Each surveyed
vehicles make, model, year & annual VMT estimate, owners
individual & household characteristics EPA fuel economy test
data Vehicle attributes (fuel economy, weight, horsepower, etc) Use
model year 2001 vehicles Gas prices were stable back then # of
vehicles in the sample: 5914 # of vehicle models: 492
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D EMAND SIDE Similar to Bento et al. (2009) Simultaneous
estimation of discrete and continuous choices: random parameters
logit model of vehicle choice continuous choice of vehicle miles
traveled (VMT) Discrete and continuous choices are connected by
Roys identity
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Household i s indirect utility function from vehicle j : ni :
random parameter varying over i p j /D : annualized vehicle price.
T =4 (average length of new vehicle ownership) d =0.9 (annual
discount factor) ni D EMAND SIDE vehicle fixed effect income
vehicle price $/100 miles= $/gal gal/100 miles Type I extreme value
error
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D EMAND SIDE By Roys identity, conditional on i choosing j, ni
induces correlation between vehicle and VMT choices Can form
likelihood that i chooses j and drive m ij, as observed in data Due
to random parameters ni, use maximum simulated likelihood estimator
VMT error
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S UPPLY SIDE Vehicle j s unit production costs depend on its
attributes: fuel consumption other attributes
Slide 14
P ROFIT MAXIMIZATION Nash equilibrium : Automaker a sets prices
and fuel consumption rates (as well as other attributes) of its own
vehicles, given prices and all attributes of other firms' vehicles:
Market sales is given by set of a s products sales vehicle price
production cost
Slide 15
F IRST ORDER CONDITIONS Focus on FOCs with respect to vehicle
prices and fuel consumption rates:
Slide 16
M ARGINAL COSTS OF FUEL EFFICIENCY IMPROVEMENT From FOCs, JJ J1
J: Total number of vehicle models in the market
Slide 17
Suppose each vehicle model is produced by a separate firm, then
Eq. (1) simplifies to Dm ij g ij e ij is anticipated total fuel
spending over consumers planning horizon. c j /e j (
R ESULTS : C OST FUNCTION FOR FUEL E FFICIENCY IMPROVEMENT Cost
increase for e 0 e 1 ( e 0 > e 1 )
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D EMAND SIDE (3) With iid type I extreme value distributed
errors, probability that i chooses j, conditional on i, is With
normally distributed errors, probability that R ij is realized,
conditional on i and j, is Conditional probability of i choosing j
and observing R ij is
Slide 29
D EMAND SIDE (4) Unconditional likelihood for i, given i s pdf
f, is Estimation by maximum simulated likelihood, assuming i is
normally distributed Vehicle j s predicted share as a function of
demand side parameters:
