The Vehicle Efficiency Incentive Act
is designed to decrease greenhouse gas emissions by increasing the energy
efficiency of the fleet of motor vehicles operating in Rhode Island.
The act would impose fees on consumers who purchase vehicles that emit
large amounts of carbon dioxide per mile traveled and provide rebates
for the purchase of vehicles with lower emissions. (Carbon dioxide is
by far the most important greenhouse gas in vehicle exhaust.) Because
emissions are directly proportional to gasoline consumption, fuel economy
data compiled by the federal government provides all information needed
to assign dollar amounts to each vehicle once a "zero point"
and "slope" are determined.
Specification of these two parameters
is probably the most complex problem in designing the "feebate"
plan. The feebate amount for a particular vehicle is calculated
by (1) subtracting the number of gallons used by that vehicle to travel
one mile from the amount that would be used by a vehicle at the chosen
zero point and then (2) multiplying that difference by the chosen slope.
The choice of a specific slope and zero point will determine the degree
to which the program is effective at reducing emissions, politically
acceptable, and appropriately revenue neutral. Several spreadsheets
that facilitate consideration of the consequences of different choices
of slope and zero point have been developed and made available.
Also under consideration are potential
impacts on specific groups (such as business owners and large families),
and administrative issues (how money would actually be transferred).
These issues and many others have been discussed in separate meetings
with representatives of the American Automobile Association, the Conservation
Law Foundation, the Department of Environmental Management, the Division
of Motor Vehicles, and DEM's Business Roundtable. It is hoped that thorough
and open consideration of all relevant concerns will facilitate eventually
passage and smooth implementation of a Vehicle Efficiency Incentive
Act in Rhode Island.
For a description of work previously done, visit the 2002 VEIA Brown Group website by clicking here . To learn more about our particular contribution to this process scroll down or click on the links in the top left menu.
Four Excel spreadsheets have been created
to facilitate analysis of the Vehicle Efficiency Incentive Act. Clicking
on each link will download an interactive Excel spreadsheet.
(2003
VEIA) See revenue projections based on actual registrations of model
year 2002 vehicles for different rate structures. Graphs and examples
also illustrate other general characteristics of the VEIA and allow
additional comparisons. Detailed instructions are included.
(Vehicle
List) This spreadsheet shows the feebate amount for over one hundred
specific vehicles. The slope and zero point can be adjusted to facilitate
comparisons of the effects. Includes instructions.
(GHG
Reduction Model) If you could decide exactly what cars are purchased
in Rhode Island in each of the next fifteen years, how would you best
use this power to achieve a given level of reduction in greenhouse gas
emissions? This spreadsheet allows you to explore this question. Includes
instructions.
(2002
VEIA) A somewhat different VEIA, based directly on EPA fuel economy,
was proposed in 2002. This spreadsheet describes that version and explains
the importance of basing incentives on fuel consumption instead of fuel
economy.
(Car Comparisons)
This spreadsheet contains comparisons of four functionally similar (but not equivalent) vehicles. Detailed are factors that contribute to purchase decisions including list price, lifetime gas price, tons of carbon emission, and VEIA assessment. This spreadsheet allows for simultaneous display of different VEIA schedules.
(Revenue Calculator) This spreadsheet can help to test the degree to which changes in purchasing behavior and different choices of zero point and slope interact to determine the amount of revenue collected by the VEIA. However, this spreadsheet includes spreadsheet assumptions, but does not make predictions about consumer behavior.