A new Brattle analysis explores how carbon pricing implemented with revenue recycling, clean technology investment, and support technological learning could shape the costs and pace of economy-wide decarbonization.

Achieving deep emissions reductions will require changes well beyond the power sector. In many states, most carbon emissions come from transportation, buildings, industry, and other end uses of fossil fuels – sectors where policymakers have few direct mechanisms for influencing energy-use decisions.

The report, “Assessing Policies to Incentivize End-Use Clean Energy Adoption,” examines how economy-wide carbon pricing could encourage clean energy adoption across these sectors and affect emissions, economic activity, electricity demand, and household energy costs – as well as how revenues generated by carbon pricing can be recycled or reinvested to mitigate economic impacts and accelerate the adoption of clean technologies.

Using a simplified representation of New York State through 2050, the study captures both economy-wide responses to carbon policy and the power-system investments and reliability requirements associated with increased electrification. The analysis is not intended to recommend a particular carbon price or policy for New York. Instead, it is intended to demonstrate the scale of carbon penalties and incentives that are likely to be needed for meaningful changes in energy use, along with how policy-design alternatives can be evaluated through linked macroeconomic and power-system modeling.

Key findings include:

Carbon pricing can materially reduce emissions, but the design of the policy matters significantly to when and where it has most effect.
Deep emissions reductions may require relatively high carbon prices, because the often high residential and commercial costs of appliance conversions suggest that widespread retail clean energy adoption is unlikely to occur broadly without something like carbon pricing to incentivize and subsidize end-use conversions.
How carbon revenues are used can substantially shape the pattern of resulting economic outcomes, e.g., by protecting vulnerable customers from higher costs (and subsidizing their end-use conversions) or alternatively by favoring key technologies or critical industries. For instance, reinvesting a portion of carbon revenues in clean technologies for transportation and buildings can produce greater emissions reductions at similar economic cost than returning all revenues directly to households. These investments can also stimulate learning-by-doing that lowers emerging technology costs – in turn, making more ambitious emissions reductions achievable with lower impacts on GDP, employment, and household welfare.
Deep electrification is likely to substantially increase the level and shape of electricity demand as other fossil energy usage is reduced, requiring additional generation, storage, transmission, and other resources. Modeling these power-sector feedbacks alongside the broader economy is essential to understanding the full cost and feasibility of decarbonization.

In this study the most economically efficient modeled pathway was found to include a carbon price rising from approximately $200 to $400 per metric ton over the next 25 years, combined with investment of carbon revenues in clean technologies and learning-driven cost reductions. Under these assumptions, New York emissions fall from roughly 90 million metric tons in 2030 to approximately 35 million metric tons in 2050, while the increased cost burden on the “energy wallet” of low-income customers is held to less than 1%.

Read the full report – authored by Principal Frank Graves, Managing Energy Associate Dr. Wonjun Change, and Energy Analyst Emine Taha – to explore the scenarios, modeling framework, and implications for designing economy-wide decarbonization policies.

View Report

Experts Involved