1. Historical & Contemporary Consumer Valuations of Fuel Economy & Other Measures of Vehicle Utility Richard A. Simmons & Wallace E. Tyner Purdue University USAEE 2015 Concurrent Session 40: Transportation Fuels Pittsburgh, PA October 28, 2015

2.  Introduction and Context  Historical trends in vehicle utility and prices  Hedonic price modeling  Insights and implications of 2014 Model Year results  Conclusions Outline 2

3. 3  Vehicle Technologies  Evolutionary efficiency improvements  New vehicle architectures  Alternative fuels  Modal Shifts  Economic Practicability  OEM & consumer attractiveness  Oil & energy prices  GDP impacts  Social Cost of Carbon?  Regulatory Constraints  CAFE standards (MPG, CO2 eq /mile)  Related: RFS (ethanol & advanced biofuels)

4. 4  Financial attractiveness and economic practicability for consumers  No loss of consumer choice in vehicle attributes or overall utility  OEM capability to deliver technologies with sufficient overall value  Feasibility of achieving regulatory requirements  Effectiveness in banking fuel and energy savings  Lifecycle environmental impacts

5. 5 Data source: U.S. Environmental Protection Agency. “Light-Duty Automotive Technology, Carbon Dioxide Emissions, and Fuel Economy Trends. 2013  Success toward compliance, 2011-2015  Challenge to maintain fuel economy trajectory at affordable prices

6.  Performance (power, torque, acceleration, and ride metrics)  Aesthetic value, luxury, comfort and styling  Capacity (passenger & cargo space)  Safety (crash worthiness, ratings)  Fuel economy  Environmental impacts  Standard/Optional equipment  Consumer ratings, personal experience  Cost to operate, maintain and repair  Quality, warranty and reliability  Price & Resale value 6 Challenge: Down-select to a set of objective, representative attributes?

7. 7 What minimum number of objective attributes can lead to a reasonably accurate characterization? Consider these 3: fuel economy, vehicle mass, acceleration time

8. 8 Utility function attributes:  Objective  Representative  Tangible (i.e., “direct” consumer measures)  Continuous rather than categorical  Readily grasped by OEMs and consumers  Historically tracked  Normalized to base year  Can be combined “orthogonally” (i.e., minimize collinearity)

9. 9 Note: Data are normalized to baseline values in the most recent reference year, 2014. Simmons, R.A. and Tyner, W.E., “Fuel economy and vehicle attribute valuation trends via historical and contemporary hedonic pricing analysis” Submitted to the J. of Transportation Research, Part D. In review (Sept 2015).

10. 10 Simmons, R.A. and Tyner, W.E., “Fuel economy and vehicle attribute valuation trends via historical and contemporary hedonic pricing analysis” Submitted to the J. of Transportation Research, Part D. In review (Sept 2015). KEY POINTS:  Objective measures of utility have steadily improved over a 37 year period;  Fuel Consumption (FC) and Acceleration (ACCEL) trends are: correlated to & influenced by regulations

11. 11 Key periods and highlights: FCACCELCWT FC1 ACCEL 0.390 1 CWT0.733-0.3071 1978 through 1996:  FC dominant due to regulations  CWT reduced for quick compliance 1997 through 2014:  ACCEL dominant  CWT increases simultaneously 2014:  FC:ACCEL aligned with physical principles  CWT a proxy for many dimensions of utility FCACCELCWT FC1 ACCEL 0.728 1 CWT-0.624-0.9101 FCACCELCWT FC1 ACCEL -0.832 1 CWT0.644-0.6671  Substantial utility gains enabled by simultaneous technological innovation

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13. 13 KEY POINTS:  Real price of autos in 2014 is approximately the same as it was in 1986;  However, consumer metrics for utility have increased substantially.

14. 14 P i represents the purchase price for vehicle i, inflated using the new vehicle index,  0 represents the intercept,  j are the regressor coefficients representing elasticities of price with respect to a set of up to n continuous variables, X ij and m-n dummy variables, Y ij.  i represents the residual error between the predicted and actual values.

15. 15 P i represents the purchase price for vehicle i, inflated using the new vehicle index;  0 represents the intercept;  j are the regressor coefficients representing elasticities of price with respect to a set of 3 continuous variables, X ij ;  i represents the residual error between the predicted and actual values.   The log-log form yields  j in terms of % change in the dependent variable for a given change in the independent variable, holding others constant.

16. 16 Price elasticities suggest Willingness To Pay (WTP) for key attributes Simmons, R.A. and Tyner, W.E., “Fuel economy and vehicle attribute valuation trends via historical and contemporary hedonic pricing analysis” Submitted to the J. of Transportation Research, Part D. In review (Sept 2015). Time Period 1978-19961997-20141978-20142014 Response Variable ln(Real Price2) ln(MSRP) Estimator WLS Observations 191837814 R2R2 0.9920.9630.9430.722 AttributeCoeff. Param. Est. (Std. Error) Intercept 00 0.41 -3.53 9.97***0.59 (2.054)(3.175)(2.180)(0.527) ln( FC ) 11 -1.95***-0.08 -0.93***-0.26*** (0.163)(0.091)(0.158)(0.049) ln( ACCEL ) 22 -0.05 -0.41*-0.65***-0.70*** (0.073)(0.220)(0.114)(0.051) ln( CWT ) 33 1.95***2.02***0.50*1.59*** (0.314)(0.385)(0.302)(0.063) The ‘dominant two’ by time period: FC CWT ACCEL CWT FC ACCEL CWT

17. 17 Willingness To Pay (WTP) for key attributes by time period Simmons, R.A. and Tyner, W.E., “Fuel economy and vehicle attribute valuation trends via historical and contemporary hedonic pricing analysis” Submitted to the J. of Transportation Research, Part D. In review (Sept 2015). FC WEIGHT  A denotes 3 parameter model;  B denotes 7 parameter model (adds trim & drive) ACCEL

18. 18  Real weighted average prices for autos have remained roughly constant since 1986.  Simultaneous progress achieved on several “counter-acting” technological dimensions.  Simple equal-weight index suggests performance has increased about 2.7% per year while prices remained relatively constant.  Hedonic pricing methodologies quantify the relative WTP for vehicle attribute weightings during times of regulatory constraint.  Authors’ methods accommodate sales-weighting and blocking by footprint; will be useful in projecting future fuel economy responses.  Consumers of 2014 MY cars appear to value acceleration performance between two and three times as much as fuel economy.

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21. 21  Real Price_2 is inflated using the new vehicle price index.

22. 22  Efficiency  Thermochemical, electrical  Weight, friction and drag reductions  Advanced vehicle technology  Internal combustion engine  Advanced powertrain  New architectures  Alternative fuels  Biofuels, Natural gas  Transit systems  Intelligent routing  Modal shifts Source: International Council on Clean Transportation, 2010, M. Kromer and C. Evans Source: International Energy Agency (IEA), Energy Technology Perspectives (ETP), 2012. Clean Vehicle Technology Projections IEA ICCT

23. 23  OEM product offerings & incentives  Consumer response  Driving behavior (VMT)  Transit options  Benefit-Cost  Economy-wide  Oil & energy prices  GDP impacts  Social Cost of Carbon (SCC) Source: RA Simmons, G Shaver, W Tyner, SV Garimella. A benefit-cost assessment of new vehicle technologies and fuel economy in the U.S. market. 2015. Journal of Applied Energy,