Factors Affecting Vehicle Use in Multiple-Vehicle Households

Similar documents
Do U.S. Households Favor High Fuel Economy Vehicles When Gasoline Prices Increase? A Discrete Choice Analysis

Vehicle Scrappage and Gasoline Policy. Online Appendix. Alternative First Stage and Reduced Form Specifications

Vehicle Miles (Not) Traveled: Why Fuel Economy Requirements Don t Increase Household Driving

Investigation of Relationship between Fuel Economy and Owner Satisfaction

Demand for High Fuel Economy Vehicles

2018 Automotive Fuel Economy Survey Report

Use of National Household Travel Survey (NHTS) Data in Assessment of Impacts of PHEVs on Greenhouse Gas (GHG) Emissions and Electricity Demand

Sharif University of Technology. Graduate School of Management and Economics. Econometrics I. Fall Seyed Mahdi Barakchian

A Joint Tour-Based Model of Vehicle Type Choice, Tour Length, Passenger Accompaniment, and Tour Type

Percentage of Children and Youth Ages 0 to 24 years old Using Seat Belts or Restraints, Selected Years,

Who has trouble reporting prior day events?

PROCEDURES FOR ESTIMATING THE TOTAL LOAD EXPERIENCE OF A HIGHWAY AS CONTRIBUTED BY CARGO VEHICLES

An Analytic Method for Estimation of Electric Vehicle Range Requirements, Electrification Potential and Prospective Market Size*

Step on It: Driving Behavior and Vehicle Fuel Economy

ESTIMATION RESULTS: THE DESIGN OF A COMPREHENSIVE MICROSIMULATOR OF HOUSEHOLD VEHICLE FLEET COMPOSITION, UTILIZATION, AND EVOLUTION

The Truth About Light Trucks

September 21, Introduction. Environmental Protection Agency ( EPA ), National Highway Traffic Safety

Background. ezev Methodology. Telematics Data. Individual Vehicle Compatibility

Light-Duty Automotive Technology and Fuel Economy Trends: 1975 Through Appendixes

Passenger seat belt use in Durham Region

DETERMINANTS OF CHOICE OF IRRIGATION TECHNOLOGY AND FARM INCOME

Missouri Seat Belt Usage Survey for 2017

Michigan/Grand River Avenue Transportation Study TECHNICAL MEMORANDUM #18 PROJECTED CARBON DIOXIDE (CO 2 ) EMISSIONS

Kauai Resident Travel Survey: Summary of Results

Optimal Policy for Plug-In Hybrid Electric Vehicles Adoption IAEE 2014

HAS MOTORIZATION IN THE U.S. PEAKED? PART 2: USE OF LIGHT-DUTY VEHICLES

DISCUSSION PAPER. Fuel Costs, Economic Activity, and the Rebound Effect for Heavy-Duty Trucks

Where are the Increases in Motorcycle Rider Fatalities?

Fueling Savings: Higher Fuel Economy Standards Result In Big Savings for Consumers

BUILDING A ROBUST INDUSTRY INDEX BASED ON LONGITUDINAL DATA

An analysis of household vehicle ownership and utilization patterns in the United States using the 2001 National Household Travel Survey

Online appendix for "Fuel Economy and Safety: The Influences of Vehicle Class and Driver Behavior" Mark Jacobsen

Getting Started with Correlated Component Regression (CCR) in XLSTAT-CCR

Table of Contents. 1.0 Introduction Demographic Characteristics Travel Behaviour Aggregate Trips 28

Understanding Traffic Data: How To Avoid Making the Wrong Turn

NEW-VEHICLE MARKET SHARES OF CARS VERSUS LIGHT TRUCKS IN THE U.S.: RECENT TRENDS AND FUTURE OUTLOOK

Transit dependence and choice riders in the NHTS 2009: Improving our understanding of transit markets

Statistics and Facts About Distracted Driving

UNINTENDED CONSEQUENCES OF FUEL-ECONOMY POLICIES

Executive Summary. Light-Duty Automotive Technology and Fuel Economy Trends: 1975 through EPA420-S and Air Quality July 2006

Service Report. 1 Choose a group to display, Contact us today at or for more information.

The Impact of Fuel Efficiency Improvement on Driving Behaviors of NYC Taxi Drivers

MEETING GOVERNMENT MANDATES TO REDUCE FLEET SIZE

MAKING USE OF MOBILE6 S CAPABILITIES FOR MODELING START EMISSIONS

APPLICATION OF A PARCEL-BASED SUSTAINABILITY TOOL TO ANALYZE GHG EMISSIONS

MEMORANDUM. Observational survey of car seat use, 2017

Safer or Cheaper? Household Safety Concerns, Vehicle Choices, and the Costs of Fuel Economy Standards

DAILY TRAVEL AND CO 2 EMISSIONS FROM PASSENGER TRANSPORT: A COMPARISON OF GERMANY AND THE UNITED STATES

National Household Travel Survey Add-On Use in the Des Moines, Iowa, Metropolitan Area

2012 Air Emissions Inventory

The U.S. Auto Industry, Washington and New Priorities:

EXPERIENCE IN A COMPANY-WIDE LONG DISTANCE CARPOOL PROGRAM IN SOUTH KOREA

The Value of Travel-Time: Estimates of the Hourly Value of Time for Vehicles in Oregon 2007

Helmet Use and Motorcycle Fatalities in Taiwan

TRAFFIC SAFETY FACTS Fatal Motor Vehicle Crashes: Overview. Research Note. DOT HS October 2017

New Vehicle Feebates: Theory and Evidence

Clean Car Roll-back. Estimated costs for American families if U.S. climate pollution and fuel economy standards are relaxed.

Modelling real choices between conventional and electric cars for home-based journeys

MONTHLY NEW RESIDENTIAL SALES, APRIL 2017

Fuel Economy: How Will Consumers Respond?

Trip Generation and Parking Study New Californian Apartments, Berkeley

Oregon DOT Slow-Speed Weigh-in-Motion (SWIM) Project: Analysis of Initial Weight Data

A COMPARATIVE EVALUATION OF INTERCITY MODAL-SPLIT MODELS

Predicted response of Prague residents to regulation measures

Fuel Economy and Safety

Technical Memorandum Analysis Procedures and Mobility Performance Measures 100 Most Congested Texas Road Sections What s New for 2015

Automated and Connected Vehicles: Planning for Uncertainty

Appendix E Hydrology, Erosion and Sediment Transport Studies

Traffic Data For Mechanistic Pavement Design

CITY OF EDMONTON COMMERCIAL VEHICLE MODEL UPDATE USING A ROADSIDE TRUCK SURVEY

TRANSIT DEMAND IN RURAL DOUGLAS COUNTY: PRELIMINARY BACKGROUND DATA

Life and Death at the CAFE: Predicting the Impact of Fuel Economy Standards on Vehicle Safety

More persons in the cars? Status and potential for change in car occupancy rates in Norway

Distribution Forecasting Working Group

Reducing GHG Emissions from Cars and Light Trucks

Table 2: Ethnic Diversity and Local Public Goods (Kenya and Tanzania) Annual school spending/ pupil, USD

San Diego Metropolitan Transit System. William R. Spraul Chief Operating Officer, Transit Services

The Price Effects of Independent Transmission System Operators in the U.S. Electricity Market

Interstate Freight in Australia,

Consumer Choice Modeling

Road Surface characteristics and traffic accident rates on New Zealand s state highway network

KANSAS Occupant Protection Observational Survey Supplementary Analyses Summer Study

ON-ROAD FUEL ECONOMY OF VEHICLES

2008 Canadian. Vehicle Survey. Update Report

Policy considerations for reducing fuel use from passenger vehicles,

American Driving Survey: Methodology and Year One Results, May 2013 May Saving lives through research and education.

Lecture 7. Stated Preference Methods. Cinzia Cirillo

A Techno-Economic Analysis of BEVs with Fast Charging Infrastructure. Jeremy Neubauer Ahmad Pesaran

Stat 301 Lecture 26. Model Selection. Indicator Variables. Explanatory Variables

Table AC5. Average Consumption for Air-Conditioning by Equipment Type, 2005 kwh per Household

Economy. 38% of GDP in 1970; 33% of GDP in 1998 Most significant decline in Manufacturing 47% to 29%

WLTP DHC subgroup. Draft methodology to develop WLTP drive cycle

CHANGE IN DRIVERS PARKING PREFERENCE AFTER THE INTRODUCTION OF STRENGTHENED PARKING REGULATIONS

UTA Transportation Equity Study and Staff Analysis. Board Workshop January 6, 2018

CRASH ATTRIBUTES THAT INFLUENCE THE SEVERITY OF ROLLOVER CRASHES

Problem Set 3 - Solutions

Outline. Research Questions. Electric Scooters in Viet Nam and India: Factors Influencing (lack of) Adoption and Environmental Implications 11/4/2009

MONTHLY NEW RESIDENTIAL SALES, AUGUST 2017

Vehicle Miles Traveled in Massachusetts: Who is driving and where are they going?

DRIVER SPEED COMPLIANCE WITHIN SCHOOL ZONES AND EFFECTS OF 40 PAINTED SPEED LIMIT ON DRIVER SPEED BEHAVIOURS Tony Radalj Main Roads Western Australia

Transcription:

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 Number of Vehicles Sample Size Household Size # of Drivers Weighted Averages 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% 3

Households Vehicles by Number and Type One-Vehicle Households (40,464) Two-Vehicle Households (122,365) Three-Vehicle Households (75,802) Four-Vehicle Households (33,480) Five-Plus-Vehicle Households (22,298) Autos (N ~ 28,300) Autos (N ~ 61,100) Autos (N ~ 35,600) Autos (N ~ 15,800) Autos (N ~ 10,500) SUVs (N ~ 6,100) SUVs (N ~ 26,200) SUVs (N ~ 15,800) SUVs (N ~ 6,700) SUVs (N ~ 4,000) Vans (N ~ 3,000) Vans (N ~ 11,000) Vans (N ~ 6,300) Vans (N ~ 2,400) Vans (N ~ 1,400) Pickups (N ~ 3,000) Pickups (N ~ 24,100) Pickups (N ~ 18,200) Pickups (N ~ 8,600) Pickups (N ~ 6,400) 4

Role of Multiple-Vehicle Households Variable 2 Vehicles Percent of Total Accounted for by Multiple-Vehicle Households 3 4 5+ vehicles vehicles 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% 5

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

Merge data from NHTS household, trip, and vehicle files to create a single record for each individual vehicle Estimation Procedure Create dataset Split by household type: one-, two-, three-, four-plusvehicle households 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 Employ alternative measures of vehicle use Estimated annual use (BESTMILE) Daily VMT (sum of survey-day trip distances) EIADMPG is partly constructed from BESTMILE, so simultaneity is definitional Experiment with alternative MPG measures EPATMPG is notoriously poor predictor of on-road MPG for individual drivers Alternative approaches to control for vehicle type Dummy variables assume fixed effects : only constant term differs by vehicle type West and Pickrell 2009 NHTS Workshop Stratification allows effects of all explanatory variables to differ by vehicle type

Basic Model Specification 10 Determinants of Vehicle Use Operating cost Vehicle attributes Household characteristics Substitutability of other vehicles Control measures Alternative Measures of Determinant Fuel economy (miles per gallon) Fuel price ($ per gallon) Fuel cost per mile ($ per gallon / miles per gallon) Vehicle type Vehicle age Income Household size, composition, licensed drivers Location (urban, suburban, rural), region Vehicle type Operating cost Utilization Day of survey (weekday, weekend) Month/season of year

Complications and Fixes Zero-VMT vehicles: almost one-third of vehicles not driven on survey day Discard zero-vmt vehicles and estimate using OLS Use Heckman sample selection model BESTMILE: estimation procedures may result in varying reliability Use only vehicles with BESTMILE estimated from odometer Use all vehicles, check to see how results differ Endogeneity: fuel economy may depend on expected vehicle use 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

Model 1: Use Fuel Economy and Price Separately Variable Functional Form One-Vehicle Two-Vehicle Three-Vehicle 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 12 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

Model 2: Use Fuel Cost per Mile (= fuel price/mpg) Variable Functional Form One-Vehicle Two-Vehicle Three-Vehicle 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 13 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

Model 3: Include Use of Secondary Vehicles Variable Functional Form One-Vehicle Two-Vehicle Three-Vehicle 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 14 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

Heckman Sample Selection Model Variable Functional Form One-Vehicle Two-Vehicle Three-Vehicle 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 15 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 One-Vehicle Passenger Cars Two-Vehicle Three-Vehicle One-Vehicle SUVs Two-Vehicle Three-Vehicle 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 20 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

Stratified Model Results: OLS Model 2 Variable Functional Form One-Vehicle Passenger Cars Two-Vehicle Three-Vehicle One-Vehicle SUVs Two-Vehicle Three-Vehicle 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 21 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

Stratified Model Results: OLS Model 3 Variable Functional Form One-Vehicle Passenger Cars Two-Vehicle Three-Vehicle One-Vehicle SUVs Two-Vehicle Three-Vehicle 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 22 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

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)