Anticipating the impacts of climate policies on the U.S. light-duty-vehicle fleet, greenhouse gas emissions, and household welfare
| dc.contributor.advisor | Kockelman, Kara | en |
| dc.contributor.committeeMember | Greene, David L. | en |
| dc.creator | Paul, Binny Mathew | en |
| dc.date.accessioned | 2011-07-07T20:13:30Z | en |
| dc.date.accessioned | 2017-05-11T22:22:34Z | |
| dc.date.available | 2011-07-07T20:13:30Z | en |
| dc.date.available | 2017-05-11T22:22:34Z | |
| dc.date.issued | 2011-05 | en |
| dc.date.submitted | May 2011 | en |
| dc.date.updated | 2011-07-07T20:13:42Z | en |
| dc.description | text | en |
| dc.description.abstract | The first part of this thesis 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-use-density settings. The adoption and widespread use of plug-in vehicles will depend on thoughtful marketing, competitive pricing, government incentives, reliable driving-range reports, and adequate charging infrastructure. 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 highest market share predictions (16.30%) for PHEVs, HEVs, and Smart Cars (combined) — and the greatest GHG-emissions reductions. Predictions under the two feebate policy scenarios suggest shifts toward fuel-efficient vehicles, but with vehicle miles traveled (VMT) rising slightly (by 0.96% and 1.42%), thanks to lower driving costs. The stricter of the two feebate policies – 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. Total VMT values under the two feebate scenarios and low-PHEV-pricing scenarios were higher than those under the trend scenario (by 0.56%, 0.96%, and 1.42%, respectively), but only the low-PHEV-pricing scenario delivered higher overall GHG emission estimates (just 0.23% more than trend) in year 2035. The high-density scenario (where job and household densities were quadrupled) resulted in the lowest total vehicle ownership levels, along with below-trend VMT and emissions rates. Finally, the scenario involving a $7,500 rebate on all PHEVs still predicted lower PHEV market share than the $7 gas price scenario (i.e., 2.85% rather than 3.78%). The second part of this thesis 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). Results suggest that low-income households respond the most under a $100-per-ton tax but increase GHG emissions under cap-and-trade scenarios, thanks to increased income via sale of their carbon credits. High-income households respond the most across all the scenarios under a 10-ton cap (per household member, per year) and trading at $100 per ton scenario. Highest overall emission reduction (47.2%) was estimated to be under $100 per ton carbon tax. High welfare loss was predicted for all households (to the order of 20% of household income) under both the policies. Results suggest that a carbon tax will be regressive (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. | en |
| dc.description.department | Civil, Architectural, and Environmental Engineering | en |
| dc.format.mimetype | application/pdf | en |
| dc.identifier.slug | 2152/ETD-UT-2011-05-3630 | en |
| dc.identifier.uri | http://hdl.handle.net/2152/ETD-UT-2011-05-3630 | en |
| dc.language.iso | eng | en |
| dc.subject | Plug-in electric vehicles | en |
| dc.subject | Personal vehicle fleet | en |
| dc.subject | Vehicle ownership | en |
| dc.subject | Travel behavior modeling | en |
| dc.subject | Carbon trading | en |
| dc.subject | Carbon credits | en |
| dc.subject | Cap and trade | en |
| dc.subject | Welfare effects | en |
| dc.subject | Greenhouse gas emissions | en |
| dc.subject | Vehicle miles traveled | en |
| dc.title | Anticipating the impacts of climate policies on the U.S. light-duty-vehicle fleet, greenhouse gas emissions, and household welfare | en |
| dc.type.genre | thesis | en |