Introduction
Data
Results
Conclusions
HOV Stickers and the Consumer Adoption of Hybrids:
Evidence from California
Kenneth Gillingham and Calanit Kamala
Yale University and UC Berkeley
November 7, 2012
USAEE Conference
Introduction
Data
Results
High Occupancy Vehicle (HOV) Lanes
HOV lanes were originally intended to promote carpooling:
Conclusions
Introduction
Data
Results
Conclusions
HOV Lanes on Many Congested Highways
HOV lanes must be appealing to many commuters:
Introduction
Data
Results
Clean Air Access Stickers for Hybrids
Some states co-opt HOV lanes by allowing hybrids on them:
Conclusions
Introduction
Data
Results
Conclusions
Hybrid Policies in the Literature
Hybrids have been a hot topic recently:
Non-incentive factors influencing adoption: Kahn (2007), Heutel &
Muehlegger (2011)
Incidence of hybrid tax credits: Sallee (2011), Beresteanu & Li
(2011)
Effect of federal or state incentives for hybrids: Diamond (2009),
Chandra, Gulati & Kandilkar (2010), Gallagher & Muehlegger
(2011), Beresteanu & Li (2011)
Market willingness-to-pay for a sticker: Shewmake & Jarvis (2011)
Effect of hybrid sticker program on travel speeds: Bento et al.
(2011), Jang & Cassidy (2011)
Introduction
Data
Results
Research Questions
This paper focuses on California’s CAVS program:
1
What was the program’s effect on hybrid sales?
How many of the stickers were given to free-riders?
2
What was the program’s effect on hybrid prices?
What is the incidence of the policy?
Conclusions
Introduction
Data
Results
California CAVS program dates
Conclusions
Introduction
Data
Results
Data Sources
All new vehicle registrations in CA, 2001-2009 (R.L. Polk).
VIN, make, model, series, subseries, date of purchase, list price,
transaction price, zip code of purchaser.
All 85,000 CAVS stickers, 2005-2007 (CA DMV)
VIN, zip code of purchaser, date of sticker.
Monthly retail gasoline prices in each county in CA (OPIS).
Zip-code demographics (2000 Census).
County-level monthly unemployment (BLS)
Monthly Consumer Confidence Index (Conference Board)
County-level monthly median house prices (CA Realtor’s
Association)
Conclusions
Introduction
Data
Results
Conclusions
Summary statistics
Observation is a zip code-year-month
Variable
number vehicles sold
hybrids sold
eligible hybrids sold
stickered vehicles sold
CAVS time period
transaction price (2010$)
baseline list price (2010$)
county unemployment rate
avg house price (000s 2010$)
gasoline price (2010$)
percent green party
percent yes on Prop 84
percent yes on Prop 87
county avg commute time
zip code density
zip code median income
zip code percent 65+
zip code percent 18-
Mean
73.5
1.75
1.13
0.38
0.28
27346.8
27402.03
6.77
447.07
2.68
0
0.51
0.44
25.91
3.66
61138.64
12.33
23.98
s.d.
248.43
5
3.08
1.44
0.45
6972.98
7242.03
2.76
207.66
0.64
0
0.13
0.14
4.62
5.64
29074.57
6.93
7.08
Min
1
0
0
0
0
10000
10030
2.8
94.44
1.25
0
0.1
0
13.4
0
0
0
0
Max
24488
542
541
133
1
100000
109899
31.3
1195.37
5
0.04
1
0.85
43.1
52.18
375000
100
41.3
N
210,531
210,531
210,531
210,531
210,531
199,843
204,746
209,733
209,733
209,606
162,330
162,244
162,244
207,045
161,743
161,138
161,138
161,138
Introduction
Data
Results
Conclusions
0
new vehicles sold
2,000
4,000
6,000
Vehicle Sales
2000m1
2002m1
2004m1
2006m1
month of registration
eligible hybrids
2008m1
sticker recipients
2010m1
Introduction
Data
Results
Conclusions
0
percent of vehicles sold
.02
.04
.06
Percent Hybrid Sales
2000m1
2002m1
2004m1
2006m1
month of registration
eligible hybrids
2008m1
sticker recipients
2010m1
Introduction
Data
Results
Conclusions
0
percent of vehicles sold are eligible hybrids
.02
.04
.06
Sales by Proximity to HOV Lanes
2000m1
2002m1
2004m1
2006m1
month of registration
HOV counties
2008m1
non−HOV counties
2010m1
Introduction
Data
Results
Conclusions
20,000
avg vehicle price (2010$)
25,000
30,000
35,000
Hybrid Prices
2000m1
2002m1
2004m1
2006m1
month of registration
all new vehicles
2008m1
new eligible hybrids
2010m1
Introduction
Data
Results
Conclusions
22,000
eligible hybrid price (2010$)
24,000
26,000
28,000
30,000
Hybrid Prices by Proximity to HOV Lanes
2000m1
2002m1
2004m1
2006m1
month of registration
HOV counties
2008m1
non−HOV counties
2010m1
Introduction
Data
Results
Conclusions
Primary Empirical Specifications
qzt = β0 + β1 CAVSzt ∗ HOVcountyzt + βXzt + µm + εzt
where for zip code z and month t:
qzt is the number/percent of eligible or stickered hybrids sold
CAVSzt is a dummy for 1/2005 - 2/2007
HOVcountyzt is a dummy for the county containing an HOV lane
Xzt is a vector of controls (e.g., gas prices, unemployment,
demographics, quadratic time trend)
µm are month-of-the-year m fixed effects
Also run a specification with hybrid prices as the dependent
variable
Introduction
Data
Results
Conclusions
Identification
Identification of β1 is based on both time series and cross-sectional
variation
E[CAVSzt ∗ HOVcountyzt ∗ εzt ] = 0 relies on no county-specific
shocks during the time period of the program that lead to more
hybrid purchases.
Introduction
Data
Results
Conclusions
Effect of Program on Eligible Hybrid Sales
Dependent variable: eligible hybrids sold in zip code (mean = 1.1 per month)
CAVS*HOVcounty
county unempl rate
avg house price
gasoline price
(1)
base
(2)
demog
(3)
mon-of-yr
dummies
(4)
time
trend
(5)
county
FE
0.238***
(0.050)
-0.015*
(0.006)
0.003***
(0.000)
0.578***
(0.023)
-1.560***
(0.109)
0.658***
(0.065)
-0.027***
(0.007)
0.001**
(0.000)
0.980***
(0.040)
2.921***
(0.745)
-0.015*
(0.007)
0.036***
(0.011)
-3.297***
(0.383)
0.521***
(0.057)
-0.056***
(0.010)
0.001
(0.000)
0.586***
(0.038)
2.842***
(0.739)
-0.016*
(0.007)
0.037***
(0.011)
-2.441***
(0.389)
0.446***
(0.056)
-0.069***
(0.011)
0.000
(0.000)
0.531***
(0.035)
2.870***
(0.739)
-0.016*
(0.007)
0.038***
(0.010)
-97.695***
(9.822)
0.108*
(0.048)
-0.145***
(0.011)
0.004***
(0.000)
0.364***
(0.022)
-0.434
(0.940)
-0.049**
(0.016)
0.017
(0.013)
-34.801***
(5.479)
N
N
N
N
Y
N
N
N
Y
Y
Y
N
Y
Y
Y
N
Y
Y
Y
Y
0.072
209,606
0.167
155,372
0.171
155,372
0.175
155,372
0.193
155,372
% yes on Prop 84
county avg commute
zip code density
constant
zip demographics
month-of-year FE
quadrat. time trend
county FE
R-squared
Observations
*** indicates significant at 1% level, ** significant at 5% level
standard errors clustered on zip code in parentheses
Introduction
Data
Results
Conclusions
Effect of Proximity to HOV Lanes on Stickers
Dependent variable: sticker hybrids sold in zip code (mean = 0.38 per month)
HOVcounty
county unempl rate
avg house price
gasoline price
(1)
base
(2)
demog
(3)
mon-of-yr
dummies
(4)
time
trend
(5)
county
FE
0.893***
(0.067)
0.033***
(0.010)
0.002***
(0.000)
0.239***
(0.025)
-1.507***
(0.172)
1.061***
(0.110)
0.045***
(0.012)
-0.000
(0.000)
0.521***
(0.041)
0.288
(0.613)
-0.008
(0.007)
0.037***
(0.010)
-2.767***
(0.411)
1.061***
(0.111)
0.045***
(0.012)
-0.000
(0.000)
0.518***
(0.038)
0.286
(0.614)
-0.008
(0.007)
0.037***
(0.010)
-2.762***
(0.411)
1.059***
(0.111)
0.040***
(0.012)
-0.000
(0.000)
0.349***
(0.036)
0.233
(0.613)
-0.009
(0.007)
0.037***
(0.010)
-1104.955***
(76.422)
1.306**
(0.447)
0.020***
(0.005)
0.001*
(0.000)
0.395***
(0.034)
-1.348
(0.882)
-0.020
(0.016)
0.014
(0.012)
-1003.460***
(71.028)
N
N
N
N
Y
N
N
N
Y
Y
Y
N
Y
Y
Y
N
Y
Y
Y
Y
0.092
59,835
0.242
41,806
0.242
41,806
0.247
41,806
0.274
41,806
% yes on Prop 84
county avg commute
zip code density
constant
zip demographics
month-of-year FE
quadrat. time trend
county FE
R-squared
Observations
*** indicates significant at 1% level, ** significant at 5% level
standard errors clustered on zip code in parentheses
Introduction
Data
Results
Conclusions
Effect of Program on Eligible Hybrid Prices
Dependent variable: transaction price (mean = 27,347 2010$)
CAVS*HOVcoun*eligible
county unempl rate
avg house price
gasoline price
(1)
base
(2)
demog
(3)
mon-of-yr
dummies
(4)
time
trend
(5)
county
FE
214.017***
(34.171)
-22.521
(16.768)
5.348***
(0.381)
-489.454***
(35.244)
26331.269***
(225.431)
137.483***
(23.157)
-29.082
(18.343)
-0.181
(0.601)
-134.153*
(55.423)
3677.352*
(1528.822)
-54.902***
(12.383)
32.503
(17.174)
22306.374***
(892.706)
89.976***
(23.602)
-45.408
(27.360)
-1.937*
(0.796)
-624.163***
(72.220)
3534.778*
(1507.048)
-53.570***
(12.256)
39.229*
(17.347)
22447.063***
(919.890)
67.094**
(24.933)
-40.947
(28.888)
-2.343**
(0.850)
-702.222***
(67.168)
3552.002*
(1500.791)
-52.367***
(12.245)
41.539*
(17.418)
-1.86e+05***
(26800.418)
38.321
(22.881)
-203.324***
(13.409)
1.873***
(0.285)
-1040.751***
(33.372)
4269.535*
(2012.853)
-32.577
(20.322)
-22.617
(29.487)
-7.26e+04***
(10652.060)
N
N
N
N
Y
N
N
N
Y
Y
Y
N
Y
Y
Y
N
Y
Y
Y
Y
0.032
199,542
0.224
151,989
0.236
151,989
0.239
151,989
0.280
151,989
% yes on Prop 84
county avg commute
zip code density
constant
zip demographics
month-of-year FE
quadrat. time trend
county FE
R-squared
Observations
*** indicates significant at 1% level, ** significant at 5% level
standard errors clustered on zip code in parentheses
Introduction
Data
Results
How Many Free-riders?
We can get a first-order approximation on free-ridership:
All stickers from hybrids purchased before 9/2004 must be
free-riding: 30%
Stickers from hybrids purchased in non-HOV counties may be
free-riding: 7%
Using estimate of induced sales in HOV counties:
Even if there was a 40% increase in sales due to the policy,
free-riding: 38%
These imply free-riding on the order of 75%!
Conclusions
Introduction
Data
Results
Conclusions and Future Work
The CAVS program did have an effect on sales of hybrids
By increasing demand, CAVS also increased prices of hybrids
However, a very high level of free-ridership
Future work:
Estimate the incidence of the policy
Examine the interaction with federal tax incentives
Conclusions