However, the difference in consumption loss between these two scenarios differs considerably between models; in USREP, the cap-and-regulations scenario is 62 percent more costly than the 50 percent cap-and-trade scenario, whereas in EC-IAM it is 230 percent more costly.
USREP finds larger percentage differences in the low-cost, low-abatement cap-and-trade policies (EV costs are 120 percent less than consumption loss in the 0 percent cap-and-trade scenario, though costs are near zero).
The biggest change occurs in the USREP and NewERA models.
GDP loss shows the most dramatic differences from the other cost metrics, with the largest differences seen in the USREP and US-REGEN models.
For USREP, the CAFE scenario is 600 percent more expensive in GDP loss terms than in consumption loss terms, but the RPS and CES scenarios are only 14 and 23 percent more expensive.
Four of the seven models in this study (USREP, ADAGE, EC-IAM, and GCAM) include non-C[O.sub.2] GHGs.
On the other hand, models with a top-down representation of electricity generation and low-cost abatement options in non-electric sectors (USREP, FARM, EC-IAM) estimate that the regulatory policies for the electricity sector are less efficient than an economy-wide cap-and-trade policy.
The other three models (ADAGE, US-REGEN and USREP) find much smaller cost differences between the two technology assumptions in the cap-and-trade scenarios.
The solution to this problem adopted in USREP is to evaluate a synthetic base-load technology created by combining wind generation capacity together with a 100 percent of back-up capacity, so that the combination is able to be dispatched and a base-load profile of production can be assured.
Rausch & Mowers (2014) embed the ReEDS model within the general equilibrium framework underlying the USREP model by employing a block decomposition algorithm put forward by Bohringer & Rutherford (2009).
USREP with a "top-down" formulation of electricity estimates that NPV welfare costs of a federal CES policy are US$ trillion 2.08 whereas the USREP-ReEDS model suggests slightly lower costs at higher US$ trillion 1.97.
Initial exploratory analysis with the USREP model did find evidence for a strong tax-interaction effect that would make regulatory policies more cost effective.