December 2025
Authors: Mihaly Fleiner, Márton Simó and Dóra Fazekas

How 2025’s Nobel Prize in Economics reinforces the value of innovation-driven economic modelling for informed climate policymaking

This year’s Nobel Prize in Economic Sciences highlights a shift in how we think about economic growth and its influence on climate policy.  

Those awarded – Joel Mokyr, Philippe Aghion and Peter Howitt - demonstrated the importance of shared knowledge, ‘creative destruction’ by replacing old industries and technologies with innovative, new techniques, and how growth is innovation-driven and not equilibrium-driven.  

For the team at Cambridge Econometrics, the recognition of innovation being the true engine of growth reinforces the principles behind our economic modelling of climate change – that for effective policymaking, economic models need to reflect the real world, not one that is perfectly balanced. 

Decarbonisation can be largely seen as a technological change. If policies are designed so that they support the spread of innovation, lower costs, replace outdated systems, and build on existing capabilities, then the shift to a low-carbon economy can happen faster without hurting competitiveness. 

Innovation-driven growth in climate change mitigation strategies 

Cutting emissions and achieving a low‑carbon economy depends heavily on the adoption of new green technologies, which typically emerge through the process of creative destruction.  

This year’s laureates in economic sciences have shown in different ways how innovation‑driven growth requires policies that encourage knowledge creation, competition, and the diffusion of new ideas while allowing new firms and technologies to replace less productive ones.   

For decarbonisation policy, this is relevant because reducing emissions at scale largely depends on new innovative low-carbon technologies such as EVs, heat pumps or renewable energy generation among others.  

Equally important is understanding the pace and pattern of new technology emergence and adoption, which often follows an S‑curve: new technologies begin as costly and niche, then scale rapidly as learning and deployment drive costs down before eventually approaching saturation.  

We’ve seen this in history before with electricity, cars, and refrigerators - once expensive novelties, now everyday essentials that reshaped economies and lifestyles. Green technologies are following a similar trajectory today, scaling quickly as costs fall and infrastructure improves, leading to a major shift in energy and transportation. 

Path dependency adds another layer of complexity.  

Early choices can have long-term impacts, either accelerating or slowing the transition because policies which encourage the take-up of technologies kickstart learning-by-doing effects. Investing in technologies that are not yet commercially viable but have great potential paves the way for future innovation that reduces costs and enhances effectiveness. This is why the spread of low‑carbon technologies is expected to accelerate in a non‑linear way. As these technologies become more cost-effective, a growing number of investments will flow into them. These investments, in turn, foster further innovation, reducing costs even more and ultimately enabling the replacement of old, polluting technologies with cleaner, more efficient ones. 

For policymakers, this is why it’s important that the economic modelling tools and methods they are using to inform policy development around decarbonisation are capturing these dynamics and allow for non-linear innovation-driven economic growth. 

Traditional economic models often assume static price balances and struggle to capture the speed, uneven adoption, and risks of climate change such as tipping points. If models overstate costs and understate the role of innovation, investment may be delayed - slowing the transition and increasing cumulative risk. 

Modelling approaches for innovation-driven growth in the transition to net zero 

At Cambridge Econometrics our approach to economic modelling means that our models are designed to capture how innovation drives change.  

For instance, our macroeconomic model E3ME includes specific components that track how technology evolves. This modelling approach enables us to assess in detail how policies encourage progress – whether that’s through learning-by-doing, the benefits of scaling up, or shifts across different industries. These are the same ideas highlighted in the 2025 Nobel-winning research on how new technology can drive sustained growth.  

From working with different clients and partners across the world, we know that different modelling assumptions can significantly shape results and the economic impacts of climate policy depend heavily on these assumptions.  

Policymakers need models that reflect both costs and innovation accurately. The research recognised in this year’s Nobel Prize in economic sciences underscores the importance of tools that capture complex, path-dependent dynamics – where policy decisions shape the deployment and adoption of technologies. 

For climate policy, this means recognising how technologies spread in S-curves, how early choices create path dependency, and how creative destruction and the sharing of knowledge drive progress. Policies that embrace these dynamics can deliver faster, cheaper transitions. 

This year’s Nobel Prize in Economics has reminded us of the importance of looking at the economy through an innovation focused, non-equilibrium lens.  

With the EU’s commitment to climate 'neutrality by 2050 and the UK advancing its net zero and industrial strategy, models and policies need to accurately reflect the economy that we have, not one that tends towards a perfect balance.