Why the impacts of climate change on GDP forecasts are important for scenario analysis

GDP forecasts are used as a widespread indicator of economic growth and underpins, both directly and indirectly, the basis of economic budgeting, financial planning and investment decisions of governments, corporates and financial institutions. the inherent use of GDP forecasts in scenarios by institutions such as the IEA needs to be understood, as the Task Force for Climate Related Disclosure framework introduces the use of scenario planning to understand long term climate change risks and opportunities.

Although there is growing recognition of the financial / economic implications of climate related risks, attempts to embed these considerations into mainstream macro-economic indicators have been limited. Failing to account for such a significant risk to future economic stability raises questions about the pricing / valuation of assets (or liabilities) especially where they are contingent upon long-term economic considerations. Institutional investors, with long-term investment horizons (e.g. pension schemes, sovereign wealth funds etc.) are most susceptible to the risks of asset mispricing. However, this is also pertinent for the calculation of decarbonisation pathways, where long-term GDP forecasts are used as a proxy for economic activity and feed into critical assumptions for CO2 projections such as energy service demand.

The impacts of climate change are non-linear, with some markets and regions more susceptible to climate related risks. There is therefore a benefit in disaggregating the impacts of climate change to determine the level of exposure for different regions and markets so that these risks can be assessed and managed accordingly.

This project aims to:

• Conduct a literature review of all significant studies on the impact of climate change on GDP
• Look at the potential feedback mechanism of the impact of climate change on GDP and implications at the industry sector level.
• Implications for scenario analysis.

Since the impacts are non-linear and there is a considerable degree of uncertainty, there is no single model that can capture the full effect of climate change. In order to minimise the uncertainty, this research uses, and soft-links, three multi-region global models - TIAM-UCL, ENGAGE and PAGE - to estimate the economic and non-economic costs of climate change impacts with detailed analysis on various economic sectors and energy systems, and also, quantifies non-economic costs: TIAM-UCL is an energy system model; ENGAGE is a CGE model; and PAGE is a climate impact model.