Details:

Creators:
Paul, Binny ; Kockleman, Kara M. ; Musti, Sashank
Paul, Binny ; Kockleman, Kara M. ; Musti, Sashank Less -
Corporate Creators:
University of Texas at Austin. Center for Transportation Research
Subject/TRT Terms:
[+]
Automobile Ownership--United States--Mathematical Models Carbon Taxes--United States--Mathematical Models Electric Automobiles Electric Vehicles Exhaust Gases Fleet Management Greenhouse Gases Hybrid Automobiles Hybrid Electric Vehicles--United States--Mathematical Models Hybrid Vehicles Plug-in Hybrid Vehicles Polluting Gases Pollution Vehicle Operations Vehicles
Publication/ Report Number:
SWUTC/11/161023-1
Resource Type:
Tech Report
Geographical Coverage:
Texas
Corporate Publisher:
Southwest Region University Transportation Center (U.S.)
Abstract:
The first part of this report relies on stated and revealed preference survey results across a sample of U.S. households to first

ascertain vehicle acquisition, disposal, and use patterns, and then simulate these for a synthetic population over time. Results

include predictions of future U.S. household-fleet composition, use, and greenhouse gas (GHG) emissions under nine different

scenarios, including variations in fuel and plug-in-electric-vehicle (PHEV) prices, new-vehicle feebate policies, and land-usedensity

settings. This work highlights the impacts of various directions consumers may head with such vehicles. For example,

twenty-five-year simulations at gas prices at $7 per gallon resulted in the second highest market share predictions (16.30%) for

PHEVs, HEVs, and Smart Cars (combined) — and the greatest GHG-emissions reductions. The strciter feebate policy (pivot

point at 30 mpg and fee or rebate rate of $400 per mpg) – coupled with gasoline at $5 per gallon – resulted in the highest

market share (16.37%) for PHEVs, HEVs, and Smart Cars, but not as much GHG emissions reduction as the $7 gas price

scenario. Excepting the low PHEV price and two feebate policy simulations, all other scenarios predicted a lower fleet VMT.

While plug-in vehicles are now hitting the market, their adoption and widespread use will depend on thoughtful marketing,

competitive pricing, government incentives, reliable driving-range reports, and adequate charging infrastructure.

The second part of this report relies on data from the U.S. Consumer Expenditure Survey (CEX) to estimate the welfare

impacts of carbon taxes and household-level capping of emissions (with carbon-credit trading allowed). A translog utility

framework was calibrated and then used to anticipate household expenditures across nine consumer goods categories,

including vehicle usage and vehicle expenses. An input-output model was used to estimate the impact of carbon pricing on

goods prices, and a vehicle choice model determined vehicle type preferences, along with each household’s effective travel

costs. Behaviors were predicted under two carbon tax scenarios ($50 per ton and $100 per ton of CO2-equivalents) and four

cap-and-trade scenarios (10-ton and 15-ton cap per person per year with trading allowed at $50 per ton and $100 per ton

carbon price). Carbon taxes were found to relatively regressive than a cap-and-trade setting (in terms of taxes paid per dollar

of expenditure), but a tax-revenue redistribution can be used to offset this regressivity. In the absence of substitution

opportunities (within each of the nine expenditure categories), these results represent highly conservative (worst-case) results,

but they illuminate the behavioral response trends while providing a rigorous framework for future work.


Format:
PDF
Funding:
10727
Collection(s):
US Transportation Collection University Transportation Centers
Main Document Checksum:
[+]
urn:sha256:42cf43061f5e0ce69444ce950fa1f9a48809eefc65ec6ee291fa5a169d3d0a67
Download URL:
https://rosap.ntl.bts.gov/view/dot/23109/dot_23109_DS1.pdf
File Type:

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