Brendon Tankwa, Emilien Ravigné, J. Doyne Farmer
In this paper, we analyse how climate policy reforms have shaped the diffusion of solar and wind technologies across 49 OECD+ countries over the period 1990–2023. Our objective is not simply to test whether policy matters, but to identify which instruments, under what conditions, and at what stage of diffusion, generate measurable acceleration in deployment.
To do so, we combine cross-country capacity data with policy stringency measures from the OECD Climate Actions and Policies Measurement Framework, and estimate event-study difference-in-differences models around policy introductions and strengthenings. These dynamic responses are then embedded into an S-curve diffusion framework, allowing us to translate short-term growth effects into long-term capacity outcomes.
- Policy Design Matters More Than Policy Presence
Our first key result is that not all policies are created equal. We find strong and consistent evidence that deployment-oriented instruments—particularly feed-in tariffs (FITs) with stable pricing and duration, as well as renewable expansion planning—lead to statistically significant increases in the growth rate of installed capacity.
These instruments work through a clear economic channel:
- they improve project bankability
- reduce revenue uncertainty
- and enable faster financial closure and construction
By contrast, widely adopted instruments such as:
- carbon pricing
- emissions trading systems (ETS)
- renewable portfolio standards
do not produce robust short-run increases in deployment speed.
This suggests a critical distinction: Price signals alone are insufficient to trigger rapid infrastructure build-out without complementary deployment support.
Coal phase-out policies occupy an intermediate position. Their effects are positive but delayed, and more pronounced for solar, likely reflecting system rebalancing and substitution dynamics.
- Temporary Growth Effects, Permanent Capacity Gains
A central empirical pattern is that policy interventions do not permanently alter the slope of diffusion curves. Instead, they generate temporary accelerations in growth rates, typically around the time of policy introduction or strengthening. However, these temporary effects accumulate. When mapped into counterfactual S-curve trajectories, we find that:
- the combined policy portfolio roughly doubles solar capacity
- and increases wind capacity by approximately 30% relative to a no-policy baseline
This occurs because policies shift the timing of deployment forward, bringing projects online earlier rather than increasing the ultimate saturation level. In practical terms, policy is less about “how much” capacity is eventually installed, and more about “how fast the transition happens.”
- Timing Dominates: Early Intervention Has Disproportionate Impact
A particularly important finding is that policy effectiveness is highly path-dependent. The same instrument produces very different outcomes depending on when it is introduced along the diffusion curve:
- At low penetration levels, policies generate large proportional increases in growth
- At later stages, the marginal impact declines significantly
This aligns with standard S-curve dynamics, where early-stage constraints—such as financing risk, regulatory uncertainty, and coordination failures—are binding. Once a technology matures, these constraints loosen, and policy becomes less decisive.
- Technology Heterogeneity: Solar vs Wind
We also document systematic differences between technologies. Solar deployment is consistently more responsive to policy interventions than wind. This can be explained by structural characteristics:
- Solar is modular and faster to deploy
- requires lower upfront coordination
- and is more sensitive to short-term financial incentives
Wind, by contrast, involves longer development cycles, more complex permitting, and greater infrastructure dependencies, which dampen immediate policy effects.
- Policy Sequencing and Bundling
Our results also suggest that policies do not operate in isolation. Instead, they form sequences and bundles.
We observe that:
- “anchor” policies (e.g., coal bans)
- and “enabling” policies (e.g., FITs, auctions, planning reforms, grid expansion)
tend to interact in structured ways to accelerate diffusion. While our empirical design does not fully identify optimal sequencing, the evidence
indicates that credible deployment support combined with system-level planning is far more effective than standalone instruments.
- Implications for Climate Strategy and Investment
Our findings challenge the dominant policy narrative that emphasises carbon pricing as the primary lever for decarbonisation.
Instead, we show that:
- deployment-focused, revenue-stable instruments drive near-term capacity growth
- timing is critical—early policy action has outsized effects
- policy impacts are transient in flow terms but persistent in stock terms
For policymakers, this implies that effective climate strategy should prioritise:
- early-stage deployment support
- credible and bankable policy design
- and targeted removal of system bottlenecks
For investors, the message is equally clear:
Policy risk is not just about presence, but about design, credibility, and timing—and these factors directly shape market formation and scaling trajectories.
Publication Note
This article is based on the working paper titled “Climate Policy Reforms and the Acceleration of Solar and Wind Diffusion”, first published on 9 January 2026 as part of the INET Oxford Working Paper Series (No. 2026-01). The study was produced within the research programs of the Institute for New Economic Thinking at the Oxford Martin School and affiliated institutions, and represents ongoing academic work that has not yet undergone formal peer review.
About the Authors
- Brendon Tankwa is a researcher affiliated with the Institute for New Economic Thinking at Oxford University, focusing on technology diffusion, energy transitions, and applied macroeconomic modelling.
- Emilien Ravigné is an economist working at the intersection of environmental policy and innovation systems, with affiliations including Oxford University and the RFF-CMCC European Institute on Economics and the Environment.
- J. Doyne Farmer is Director of the Complexity Economics program at the Institute for New Economic Thinking at Oxford University and a leading figure in the field. He is widely known for his work on financial systems, technological change, and climate–economy modelling. He is also the author of Making Sense of Chaos, in which he reframes economics as a complex, evolving system rather than a static equilibrium model, offering a foundational perspective that closely aligns with the approach taken in this paper.