A new study from a team of researchers that includes faculty from the University of California San Diego and Princeton University shows how a mix of subsidies for clean energy and taxes on pollution can significantly reduce greenhouse gas emissions that cause climate change.
While these kinds of policy mixes are widely used in the real world, the the study, published in Nature Climate Change is the first to show how the combination of such policies can be simulated in economic models that are the backbone of nearly all climate policy discussions – including the recent United Nations Climate Change Conference in Brazil held Nov. 10-21.
The results reveal that financial incentives can spark rapid adoption of cleaner technologies in the near term, but without policies that also punish polluters it won't be possible to stop climate change.
"This work helps make our climate models more realistic about how governments actually behave," said the study's coauthor David Victor, professor at the School of Global Policy and Strategy and co-director of UC San Diego's Deep Decarbonization Initiative (D2I). "For years, models have told us what's economically efficient — but not what's politically possible. Our goal is to bridge that gap so policymakers can craft strategies that survive real-world politics."
The research provides a rigorous, data-driven look at how policy design and political timing affect the nation's ability to decarbonize its energy system.
A study arriving at a critical moment
The study comes out at a pivotal time for U.S. and global climate policy. The transition to a new U.S. administration in 2025 has cast uncertainty on many clean energy incentives enacted under the Inflation Reduction Act (IRA). At the same time, the federal government has never implemented a meaningful tax on warming pollution, although some states have adopted small tax-like policies.
"In the United States, we are removing the reward policies designed to accelerate decarbonization and it's unlikely this administration will introduce any policies that punish larger emitters," Victor said. " Meanwhile, other countries are taking different paths — China is adding new incentives and some penalties and Europe is leaning heavily on policies that make emissions more expensive. You're seeing a global experiment in real time."
He notes that the paper, while focussing on the U.S., can serve as a "road test" for other nations around the world about which mix of policies will have the biggest impacts reducing fossil fuels.
Testing policy sequences: rewards, penalties and political timing
The paper's modeling also explores what happens when climate policies are added, delayed, or repealed over time. To test how such policy choices shape long-term progress, Victor and coauthors used a multisector, state-level energy systems model (GCAM-USA) to simulate how different approaches affect emissions, technology costs and clean energy adoption across all 50 U.S. states through 2050.
Using real data from federal and state programs, the researchers compared scenarios such as:
Incentives only — Long-term subsidies that make renewable energy and electric vehicles more affordable.
Penalties only — Economy-wide carbon pricing that makes fossil fuels more expensive.
Combined approaches — Starting with incentives, followed by penalties after 10 or 20 years.
Inconsistent policies — Reflecting political instability, with incentives that start, stop and restart over time.
In simpler terms, the researchers created a set of "what-if" policy simulations. Using the "carrot and stick" metaphor that refers to the set of policies of rewards and punishments to encourage decarbonization, the authors describe what happens in a world with "no stick, more carrot," versus "more stick, less carrot," or policies that change mid-course.
"As 'carrots' make it cheaper for companies and consumers to adopt green technologies, those technologies see greater uptake," they write. "Introducing 'sticks' is essential to reach deep decarbonization goals in the long run."
The researchers were surprised by how effective incentives can be at accelerating the clean energy transition in the near term. These policies include tax credits for electric vehicles and renewable power, government grants and loans for clean manufacturing and rebates that help homeowners install heat pumps, rooftop solar panels and energy-saving upgrades.
Consistency will make energy greener and cheaper in the long run
The study also finds that political consistency — keeping incentive programs stable and reliable — is just as important as the size of the subsidies or the stringency of future penalties. When incentives are applied consistently, the researchers found the economy can reach an 80% reduction in energy-related carbon emissions by mid-century. When those incentives are withdrawn or delayed, investment slows and later emissions cuts become more expensive.
"When policy is unpredictable, companies delay investment," Victor said. "That delay can make it politically and economically harder to act later."
Bringing political realism — and durability — into climate models
Victor describes the study as part of a broader research agenda at UC San Diego's Deep Decarbonization Initiative to make climate models more attuned to real-world politics and human behavior. This extension of the initiative involves scholars from around the country, many of whom served as coauthors on this paper.
"For years, analysts and reality have been drifting apart," he said. "This work is part of a larger mission to make studies of climate policy much more realistic about what happens in the real world — how government policies affect investments and emissions."
The authors hope the research can be used as a guide for key decision makers around the globe. They conclude, "Understanding what works — and when — is key to reaching global climate goals."
The lead author is Huilin Luo of Princeton University and the corresponding author is Wei Peng also of Princeton University. Additional coauthors include Allen Fawcett and Gokul Iyer of the University of Maryland; Jessica Green of the University of Toronto; Jonas Meckling of the University of California, Berkeley and Harvard University; and Jonas Nahm of Johns Hopkins University.
Read the full paper, " Modelling the impacts of policy sequencing on energy decarbonization ."
