Climate change is one of the largest challenges for the world economy, and developing economies are particularly exposed to its effects. Middle-income and developing countries are also now a large and increasing contributor to the global emissions with China and India accounting for 38% of global CO2 emissions in 2022.  A transition from fossil-fuel based technologies to green technologies is necessary, but may be slowed by the substantial investment that still exists in fossil fuel-based technologies. These sunk costs create a barrier to adopting new technologies, as a rapid transition may require abandonment of old technologies before the end of their useful life. This project seeks to understand how to discourage the continued use of polluting technologies to motivate businesses in developing economies to invest in new, green technologies.

This project proposes building a comprehensive integrated assessment model that evaluates various policy interventions, such as carbon taxes, subsidies for green R&D, and taxes on dirty investment, which accounts for the fixed nature of existing fossil-fuel-based capital investments. By incorporating the dynamics of putty-clay technology, the model aims to provide realistic quantitative trade-offs between short-term and long-term economic impacts. The model will include a component that captures the damages caused by climate change , helping assess the overall welfare implications of green policies.

This project has the potential to support international climate goals by showing the way in which businesses in developing economies can be pivotal in reducing global emissions. Understanding the investments for these businesses can help in crafting policies that encourage a rapid adoption of green technologies. A detailed understanding of the macroeconomic consequences of green policies can help policymakers design more effective strategies to incentivize the green transition. The insights from the model can also minimise the negative economic impacts of transitioning to green technologies by identifying the least costly policy measures.