# 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 single vehicle households • Overview of our analysis
• Useful features of NHTS data
• Econometric complications and fixes • Highlights of estimation results • Where we’re headed

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# 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

(1 22,365 )

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

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# Role of Multiple -Vehicle Households

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## 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. CO 2 

## 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

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# 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

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# 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 intra urban 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

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### 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- plus vehicle 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-vehicl e household regressions 

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# 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-vehicl e household regressions 

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# 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-vehicl e household regressions 

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# 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-vehicl e 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 multiple vehicle 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

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# 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

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# 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

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# 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-vehicl e household regressions 

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# 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-vehicl e household regressions 

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# 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-vehicl e household regressions 

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# 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)