Low-carbon fuel standards (LCFS) such as Oregon’s Clean Fuels Program (CFP) rely on market-based credit prices to motivate reductions in the lifecycle carbon intensity (CI) of transportation fuels. In practice, those price signals operate alongside the physical build-out of low-carbon infrastructure, especially electric vehicle (EV) charging networks, which may amplify or dampen the extent to which regulated parties respond to credit-market incentives. Yet it remains unclear whether higher credit prices consistently produce proportionate CI reductions, or whether the credit price–CI relationship changes once prices cross key “turning points,” and whether those turning points depend on the level of EV charging infrastructure in place. This study tests for threshold behavior in the relationship between CFP credit prices, EV charging deployment, and ethanol CI. Using monthly data from January 2018 through December 2024 drawn primarily from Oregon CFP public reports and related market sources, the analysis focuses on ethanol CI (gCO₂e/MJ) as the outcome variable and the average CFP credit price as the main policy variable. Additional controls include B5 and E10 cost indices, measures of EV charging deployment, and lagged CI dynamics.
Empirically, the study applies threshold regression methods in the spirit of Hansen’s endogenous threshold model. The core specifications allow the marginal effect of credit prices on ethanol CI to differ across regimes defined by one or more estimated credit-price thresholds, selected by searching over candidate values and choosing thresholds that improve model fit (e.g., minimizing residual variance and improving AIC/BIC). Linear and quadratic models serve as benchmarks for comparison. The working hypothesis is that the credit price–CI relationship is piecewise: responses may be muted at low prices, strengthened in an intermediate range as incentives become binding, and weakened at very high prices as low-cost abatement options are exhausted. The study further tests whether EV charging infrastructure shifts these regimes by allowing charging variables and their interaction with credit prices to vary across threshold-defined regimes. Robustness checks examine alternative threshold variables and sensitivity to the lag structure and specification. By identifying where credit prices and EV infrastructure most strongly influence CI, the results aim to inform LCFS/CFP design choices, including benchmark setting, banking rules, and cost-containment mechanisms that shape where credit prices tend to fall relative to the most effective range for driving decarbonization.
