Factors Affecting Vehicle 

Use in Multiple-Vehicle 

Households

Rachel West and Don Pickrell

2009 NHTS Workshop

June 6, 2011
Road Map

• Prevalence of multiple-vehicle households

• “Contributions” to total fleet, vehicle use

• Why and how behavior differs from that of singlevehicle households

• Overview of our analysis

• Useful features of NHTS data

• Econometric complications and fixes

• Highlights of estimation results

• Where we’re headed

2
Multiple-Vehicle Households in the 2009 NHTS

3

Number of 

Vehicles

Sample 

Size

Weighted Averages

Household Size # of Drivers Drivers per 

Vehicle Vehicle Age Percent Rural

1 40,464 1.8 1.2 1.2 8.4 16%

2 122,365 2.8 2.0 1.0 7.8 24%

3 75,802 3.1 2.4 0.8 8.8 33%

4 33,480 3.4 2.8 0.7 9.5 40%

5+ 22,298 3.6 3.0 0.6 11.5 48%
One-Vehicle 

Households 

(40,464)

Autos

(N ~ 28,300)

SUVs 

(N ~ 6,100)

Vans

(N ~ 3,000)

Pickups

(N ~ 3,000)

Two-Vehicle 

Households

(122,365)

Autos

(N ~ 61,100)

SUVs

(N ~ 26,200)

Vans

(N ~ 11,000)

Pickups

(N ~ 24,100)

Three-Vehicle 

Households

(75,802)

Autos

(N ~ 35,600)

SUVs

(N ~ 15,800)

Vans

(N ~ 6,300)

Pickups

(N ~ 18,200)

Four-Vehicle 

Households

(33,480)

Autos

(N ~ 15,800)

SUVs

(N ~ 6,700)

Vans

(N ~ 2,400)

Pickups

(N ~ 8,600)

Five-Plus-Vehicle 

Households

(22,298)

Autos

(N ~ 10,500)

SUVs

(N ~ 4,000)

Vans

(N ~ 1,400)

Pickups

(N ~ 6,400)

Households Vehicles by Number and Type

4
Role of Multiple-Vehicle Households

5

Variable 

Percent of Total Accounted for

by Multiple-Vehicle Households 

2

Vehicles

3

vehicles

4

vehicles

5+

vehicles All

U.S. Households 36% 14% 5% 3% 58%

Household Vehicles 39% 23% 11% 10% 83%

Light-Duty Vehicles 35% 21% 10% 8% 74%

Household VMT 42% 23% 11% 7% 83%

Light-Duty VMT 36% 20% 10% 6% 72%

Fuel Consumption 31% 18% 9% 6% 64%

U.S. CO2 Emissions 9% 5% 3% 2% 19%
Why Do Multiple-Vehicle Households Behave 

Differently?

• Mix of vehicle types and sizes allows closer matching of 

vehicle attributes to size and composition of group 

traveling, purpose and duration of trip, etc. 

– Seating capacity, passenger comfort, occupant protection

– Luggage-carrying, cargo, and towing capacity

– Reliability, safety, performance

• Differences in fuel economy provide flexibility in 

responding to variation in fuel prices

• More vehicles per driver accommodates “competitive 

scheduling” of household members’ activities and travel

6
Objectives of Analysis

• Model household and vehicle characteristics affecting 

ownership and use of individual vehicles

– Household characteristics: size, income, drivers, location

– Vehicle attributes: type, age, fuel economy

• Test for differences in factors affecting vehicle use

– Between single- and multiple-vehicle households

– Among two-, three-, and four or more-vehicle households

• Utilize information provided by wide variation in vehicle 

use, including non-use of many vehicles on survey day

• Account for simultaneity among vehicle use, type, and 

fuel economy in vehicle purchase decisions

• Control for influence of survey-related factors

– Wide variation in fuel prices over survey period

– Travel differences between weekdays, weekends

7
Useful Features of 2009 NHTS Data

• Wide variation in fuel prices throughout survey facilitates 

isolating effects of fuel prices and fuel economy

• Vehicle type and make/model identifiers provide controls 

for vehicle attributes

• Vehicle age and ownership duration variables support 

analysis of factors affecting purchase decisions

• Household location useful in identifying effects of intraurban and regional differences in travel behavior

• “Flags” help to assess reliability of estimated variables

• Large sample size enables precise estimation of many 

effects on vehicle use

8
West and Pickrell – 2009 NHTS 

Workshop

Estimation Procedure

Alternative approaches to control for vehicle type

Dummy variables assume “fixed effects”: only constant 

term differs by vehicle type

Stratification allows effects of all explanatory variables to 

differ by vehicle type

Experiment with alternative MPG measures

EIADMPG is partly constructed from BESTMILE, so 

simultaneity is “definitional”

EPATMPG is notoriously poor predictor of on-road MPG 

for individual drivers

Employ alternative measures of vehicle use

Estimated annual use (BESTMILE) Daily VMT (sum of survey-day trip distances)

Designate each vehicle in turn as “primary” in regression

Each vehicle’s survey-day usage appears once as the 

dependent variable of an observation

Characteristics of other (alternative) household vehicles 

appear as explanatory variables in that observation

Create dataset

Merge data from NHTS household, trip, and vehicle files 

to create a single record for each individual vehicle

Split by household type: one-, two-, three-, four-plusvehicle households
Basic Model Specification

Determinants of 

Vehicle Use Alternative Measures of Determinant

Operating cost

Fuel economy (miles per gallon)

Fuel price ($ per gallon)

Fuel cost per mile ($ per gallon / miles per gallon)

Vehicle

attributes 

Vehicle type

Vehicle age

Household 

characteristics

Income 

Household size, composition, licensed drivers

Location (urban, suburban, rural), region

Substitutability

of other 

vehicles

Vehicle type

Operating cost

Utilization 

Control 

measures

Day of survey (weekday, weekend)

Month/season of year

10
Complications and Fixes

• Discard zero-VMT vehicles and estimate using OLS

• Use Heckman sample selection model

Zero-VMT vehicles: 

almost one-third of 

vehicles not driven on 

survey day

• Use only vehicles with BESTMILE estimated from odometer

• Use all vehicles, check to see how results differ

BESTMILE: 

estimation procedures 

may result in varying 

reliability

•Use Hausman Test for endogeneity of fuel economy

•Use instrumental variable estimation procedures to reduce 

resulting bias, inconsistency in parameter estimates • “Instrument” MPG with household income, fuel prices, etc. 

•Estimate vehicle use and MPG equations jointly using 2SLS

•Particular problem with EIADMPG: construction of variable 

employs BESTMILE

Endogeneity: 

fuel economy may 

depend on expected 

vehicle use
Model 1: Use Fuel Economy and Price Separately

Variable Functional 

Form One-Vehicle HHs Two-Vehicle HHs Three-Vehicle HHs

Fuel Economy (Primary Vehicle) Log 0.089 0.101 0.266

0.039 0.033 0.058

Gas Price Log -0.261 -0.350 -0.273

0.124 0.109 0.191

Vehicle Age Linear -0.024 -0.090 -0.092

0.001 0.001 0.002

Income Log 0.133 - -

0.009 - -

Vehicles per Driver Linear -0.297 -0.161 -0.195

0.028 0.019 0.027

Urban/Suburban Dummy -0.370 -0.260 -0.292

0.016 0.013 0.022

Weekend Dummy -0.079 -0.128 -0.183

0.015 0.013 0.023

Primary Vehicle Type = Van Dummy 0.138 0.118 0.073

0.026 0.022 0.039

Primary Vehicle Type = SUV Dummy 0.155 0.037 0.095

0.021 0.018 0.031

Primary Vehicle Type = Pickup Dummy 0.147 -0.011 0.020

0.028 0.021 0.036

N 31,217 68,911 23,071

Adjusted R-Squared 0.054 0.090 0.083

Red indicates statistical significance at the 10 percent levell in a two-tailed t-test

Table omits interactions between alternative vehicle type and alternative vehicle fuel economy included in two- and three-vehicle household regressions

12
Model 2: Use Fuel Cost per Mile (= fuel price/mpg)

Variable Functional 

Form One-Vehicle HHs Two-Vehicle HHs Three-Vehicle HHs

Fuel Cost per Mile Log -0.006 -0.247 -0.335

0.020 0.026 0.049

Vehicle Age Linear -0.025 -0.089 -0.091

0.001 0.001 0.002

Income Log 0.131 - -

0.009 - -

Vehicles per Driver Linear -0.296 -0.155 -0.186

0.028 0.019 0.026

Urban/Suburban Dummy -0.372 -0.264 -0.295

0.016 0.013 0.022

Weekend Dummy -0.079 -0.128 -0.183

0.015 0.013 0.023

Primary Vehicle Type = Van Dummy 0.121 0.149 0.088

0.025 0.021 0.039

Primary Vehicle Type = SUV Dummy 0.134 0.082 0.117

0.019 0.017 0.029

Primary Vehicle Type = Pickup Dummy 0.120 0.046 0.049

0.026 0.019 0.034

N 31,218 68,912 23,072

Adjusted R-Squared 0.054 0.089 0.083

Red indicates statistical significance at the 10 percent levell in a two-tailed t-test

Table omits interactions between alternative vehicle type and alternative vehicle fuel economy included in two- and three-vehicle household regressions

13
Model 3: Include Use of Secondary Vehicles

Variable Functional 

Form One-Vehicle HHs Two-Vehicle HHs Three-Vehicle HHs

Fuel Economy (Primary Vehicle) Log 0.089 0.127 0.272

0.039 0.032 0.055

Gas Price Log -0.261 -0.184 -0.200

0.124 0.104 0.181

Vehicle Age Linear -0.024 -0.068 -0.068

0.001 0.001 0.002

Income Log 0.133 - -

0.009 - -

Vehicles per Driver Linear -0.297 -0.380 -0.391

0.028 0.019 0.025

Urban/Suburban Dummy -0.370 -0.247 -0.261

0.016 0.013 0.021

Weekend Dummy -0.079 -0.233 -0.312

0.015 0.013 0.022

Primary Vehicle Type = Van Dummy 0.138 0.176 0.151

0.026 0.021 0.037

Primary Vehicle Type = SUV Dummy 0.155 0.080 0.120

0.021 0.017 0.029

Primary Vehicle Type = Pickup Dummy 0.147 0.000 0.020

0.028 0.020 0.034

Daily Use (Alternative 1) Log - -0.083 -0.090

- 0.001 0.002

Daily Use (Alternative 2) Log - - -0.084

- - 0.002

N 31,217 68,910 23,069

Adjusted R-Squared 0.054 0.176 0.180

Red indicates statistical significance at the 10 percent levell in a two-tailed t-test

Table omits interactions between alternative vehicle type and alternative vehicle fuel economy included in two- and three-vehicle household regressions

14
Heckman Sample Selection Model

15

Variable Functional 

Form One-Vehicle HHs Two-Vehicle HHs Three-Vehicle HHs

Inverse Mills Ratio Linear -2.317 -0.784 0.471

0.119 0.068 0.181

Fuel Economy (Primary Vehicle) Log 0.036 0.106 0.255

0.039 0.033 0.058

Gas Price Log 0.022 -0.476 -0.254

0.124 0.109 0.192

Vehicle Age Linear 0.013 -0.062 -0.125

0.002 0.003 0.013

Income Log 0.087 - -

0.009 - -

Vehicles per Driver Linear -0.255 -0.055 -0.226

0.028 0.022 0.029

Urban/Suburban Dummy -0.377 -0.267 -0.290

0.016 0.013 0.022

Weekend Dummy 0.157 -0.046 -0.229

0.019 0.015 0.029

Primary Vehicle Type = Van Dummy 0.100 0.064 0.109

0.026 0.022 0.042

Primary Vehicle Type = SUV Dummy 0.126 0.028 0.107

0.021 0.018 0.031

Primary Vehicle Type = Pickup Dummy 0.280 0.098 -0.039

0.029 0.023 0.043

N 31,216 68,910 23,070

Adjusted R-Squared 0.066 0.092 0.083

Red indicates statistical significance at the 10 percent levell in a two-tailed t-test

Table omits interactions between alternative vehicle type and alternative vehicle fuel economy included in two- and three-vehicle household regressions

First stage probit model estimates not shown
Highlights of Results

• Effects of fuel economy and price differ from each other, 

but variation by vehicle ownership is more pronounced

• Fuel economy “rebound effect” is prominent, but may be 

overstated due to simultaneity between use and MPG

• Main effect of household income on travel demand works 

through vehicle ownership, not vehicle use

• Association of use with age much stronger in multiplevehicle households: more old ones, but driven less

• Multiple vehicles in household function as substitutes, not 

complements

• “Censoring” of vehicle use (large number of zero-VMT 

vehicles) doesn’t affect estimation results heavily

16
Frustrations

• Instruments for MPG do not adequately control for 

simultaneity between vehicle use and fuel economy

• Fuel prices at time of vehicle purchase, CAFE 

standards, and income should work, but don’t yield 

robust results

• One-day survey produces surprisingly large fraction 

of unused vehicles, complicates identifying factors 

influencing extent of use 

• Lack of fuel purchase data forces reliance on test 

MPG ratings and (possibly outdated) adjustments, 

but NHTS is not intended to duplicate RTECS

17
Next Steps

• Find appropriate instruments for fuel economy; test 

effect on estimated magnitude of elasticity

• Improve ability of “selection probability” model to 

predict which vehicles were driven on survey day

• Extend analysis to four-plus vehicle households

• Replicate all results using 2001 NHTS data

• Calculate composite (weighted average) elasticities 

of vehicle use with respect to fuel price, MPG, etc., 

for all households

18
Don.Pickrell@dot.gov

Rachel.West@dot.gov
Stratified Model Results: OLS Model 1

Variable Functional 

Form

Passenger Cars SUVs

One-Vehicle 

HHs

Two-Vehicle 

HHs

Three-Vehicle 

HHs

One-Vehicle 

HHs

Two-Vehicle 

HHs

Three-Vehicle 

HHs

Fuel Economy (Primary Vehicle) Log 0.170 0.190 0.308 0.023 0.046 0.059

0.046 0.043 0.075 0.097 0.070 0.118

Gas Price Log -0.096 -0.421 -0.322 -0.705 -0.173 -0.419

0.150 0.153 0.274 0.296 0.217 0.378

Vehicle Age Linear -0.024 -0.087 -0.094 -0.020 -0.099 -0.101

0.002 0.002 0.003 0.004 0.003 0.006

Income Log 0.150 - - 0.126 - -

0.011 - - 0.022 - -

Vehicles per Driver Linear -0.355 -0.136 -0.127 -0.167 -0.302 -0.296

0.035 0.027 0.037 0.065 0.045 0.056

Urban/Suburban Dummy -0.390 -0.286 -0.304 -0.329 -0.236 -0.265

0.021 0.020 0.033 0.037 0.026 0.044

Weekend Dummy -0.078 -0.104 -0.236 -0.091 -0.156 -0.160

0.018 0.019 0.034 0.037 0.026 0.045

N 20,772 34,172 11,084 5,480 16,594 5,750

Adjusted R-Squared 0.054 0.094 0.092 0.033 0.075 0.075

Red indicates statistical significance at the 10 percent levell in a two-tailed t-test

Table omits interactions between alternative vehicle type and alternative vehicle fuel economy included in two- and three-vehicle household regressions

20
Stratified Model Results: OLS Model 2

Variable Functional 

Form

Passenger Cars SUVs

One-Vehicle 

HHs

Two-Vehicle 

HHs

Three-Vehicle 

HHs

One-Vehicle 

HHs

Two-Vehicle 

HHs

Three-Vehicle 

HHs

Fuel Cost per Mile Log 0.004 -0.312 -0.309 -0.081 -0.170 -0.274

0.024 0.036 0.066 0.049 0.055 0.097

Vehicle Age Linear -0.025 -0.086 -0.094 -0.019 -0.097 -0.098

0.002 0.002 0.003 0.004 0.003 0.006

Income Log 0.148 - - 0.127 - -

0.011 - - 0.022 - -

Vehicles per Driver Linear -0.353 -0.128 -0.126 -0.167 -0.300 -0.272

0.035 0.027 0.037 0.065 0.045 0.055

Urban/Suburban Dummy -0.389 -0.292 -0.306 -0.336 -0.236 -0.271

0.021 0.020 0.033 0.037 0.026 0.043

Weekend Dummy -0.078 -0.102 -0.237 -0.090 -0.158 -0.160

0.018 0.019 0.034 0.037 0.026 0.045

N 20,773 34,173 11,085 5,481 16,595 5,751

Adjusted R-Squared 0.054 0.093 0.092 0.032 0.074 0.074

Red indicates statistical significance at the 10 percent levell in a two-tailed t-test

Table omits interactions between alternative vehicle type and alternative vehicle fuel economy included in two- and three-vehicle household regressions

21
Stratified Model Results: OLS Model 3

Variable Functional 

Form

Passenger Cars SUVs

One-Vehicle 

HHs

Two-Vehicle 

HHs

Three-Vehicle 

HHs

One-Vehicle 

HHs

Two-Vehicle 

HHs

Three-Vehicle 

HHs

Fuel Economy (Primary Vehicle) Log 0.170 0.260 0.341 0.023 -0.047 0.054

0.046 0.041 0.071 0.097 0.067 0.111

Gas Price Log -0.096 -0.163 -0.188 -0.705 -0.128 -0.415

0.150 0.146 0.259 0.296 0.206 0.356

Vehicle Age Linear -0.024 -0.065 -0.069 -0.020 -0.078 -0.078

0.002 0.002 0.003 0.004 0.003 0.006

Income Log 0.150 - - 0.126 - -

0.011 - - 0.022 - -

Vehicles per Driver Linear -0.355 -0.350 -0.321 -0.167 -0.505 -0.478

0.035 0.026 0.036 0.065 0.044 0.053

Urban/Suburban Dummy -0.390 -0.274 -0.277 -0.329 -0.227 -0.236

0.021 0.019 0.031 0.037 0.025 0.041

Weekend Dummy -0.091 -0.266 -0.297 -0.091 -0.266 -0.297

0.037 0.025 0.043 0.037 0.025 0.043

Daily Use (VMT of Alternative 1) Log - -0.081 -0.088 - -0.081 -0.088

- 0.002 0.004 - 0.002 0.004

Daily Use (VMT of Alternative 2) Log - - -0.084 - - -0.084

- - 0.004 - - 0.004

N 20,772 34,171 11,082 5,480 16,593 5,748

Adjusted R-Squared 0.054 0.179 0.188 0.033 0.162 0.176

Red indicates statistical significance at the 10 percent levell in a two-tailed t-test

Table omits interactions between alternative vehicle type and alternative vehicle fuel economy included in two- and three-vehicle household regressions

22
Heckman Stage 1 Probit Model Variables

• Gas price (PADD 12 month trailing average)

• Vehicle age

• Household size

• Number of workers in household

• Weekend (dummy)

• Seasonal controls (dummies for spring and summer)

• Vehicle type (dummies for SUV, van, pickup)