Models typically used to analyse climate-economy interactions have paradoxically ignored much of nature’s value. A new study by Bastien-Olvera and Frances Moore explicitly addresses this issue and reveals feedback loops between nature and the climate system that make climate change more costly.
In their comments on the new research, Professor Diane Coyle and Dr Matthew Agarwala note that by focussing solely on carbon, leading climate-economy models have often overlooked other elements of nature, like ecosystems and biodiversity.
With new extensions to the DICE climate model, Bastien-Olvera and Frances Moore show that climate change undermines the ability of other elements of natural capital to support welfare. This makes climate change more costly and supports higher carbon prices and more aggressive emissions reduction.
The research also shows that investing in other elements of natural capital can actually reduce the optimal carbon price, precisely because these natural assets (e.g. forests, wetlands, healthy soils, etc) help to offset the damages of climate change.
This matters for the Wealth Economy because it shows that ALL natural capital matters, not just climate capital. It shows that the current stock of natural capital is well below the optimal level. And most of all, it shows that enhancing natural capital should be a much higher priority on the climate policy agenda.
About the author
Professor Diane Coyle, Bennett Professor of Public Policy
Professor Coyle co-directs the Institute with Professor Kenny. She is heading research under the progress and productivity themes. Learn more
About the author
Dr Matthew Agarwala, Project Leader: The Wealth Economy
Matthew Agarwala is an environmental economist interested in wealth-based approaches to measuring and delivering sustainable development. The pace of globalisation, innovation, and social, environmental, and economic upheaval leaves no doubt: 20th century statistics can’t capture 21st century progress. Matthew joined the Bennett Institute’s wealth economy ... Learn more