{"version":1,"type":"rich","provider_name":"Libsyn","provider_url":"https:\/\/www.libsyn.com","height":90,"width":600,"title":"Modelling Economic Complexity: Insights for Risk Professionals","description":" Hear from Prof. J. Doyne Farmer, Professor of Complex Systems Science at the University of Oxford, as we explore new modelling approaches designed to better capture the complex and chaotic nature of our climate and economy.  We spend a lot of time on this podcast covering the transition to a low carbon economy, which will be driven largely by policies and technological innovation. These policies tend to be based on insights from economics. And our view on the pace of innovation is often informed by expert judgement. But traditional economic models often oversimplify the world, leading to poor policy design. And we tend to underestimate the exponential rate of technological change, making us unduly pessimistic about the transition.&amp;nbsp;  Today\u2019s guest has thought a great deal about both these issues. That\u2019s why in today\u2019s episode we\u2019ll be diving into the world of complexity economics and agent-based modelling, which can help us better navigate the risks and opportunities associated with the transition. We\u2019ll discuss:  How agent-based models are very well suited to modelling complex, non-linear systems, such as the economy;  How past innovation cycles can provide invaluable insights on what we might expect to see in the transition; and   What the models tell us about the appropriate speed of the transition to a net zero world.   To find out more about the Sustainability and Climate Risk (SCR\u00ae) Certificate, follow this link: https:\/\/www.garp.org\/scr  For more information on climate risk, visit GARP\u2019s Global Sustainability and Climate Risk Resource Center: https:\/\/www.garp.org\/sustainability-climate  If you have any questions, thoughts, or feedback regarding this podcast series, we would love to hear from you at: climateriskpodcast@garp.com     Links from today\u2019s discussion:  Making Sense of Chaos: A Better Economics for a Better World:&amp;nbsp;https:\/\/www.penguin.co.uk\/books\/284357\/making-sense-of-chaos-by-farmer-j-doyne\/9780241201978 Santa Fe Institute\u2019s Office of Applied Complexity:&amp;nbsp;https:\/\/www.santafe.edu\/applied-complexity\/office GARP Climate Risk Podcast with Simon Sharpe:&amp;nbsp;https:\/\/www.garp.org\/podcast\/five-times-faster-cr-240321 GARP Climate Risk Podcast with David Stainforth: https:\/\/www.garp.org\/podcast\/predicting-climate-future-cr-241128      Speaker\u2019s Bio(s) Prof. J. Doyne Farmer, Professor of Complex Systems Science, University of Oxford J. Doyne Farmer is Baillie Gifford Professor of Complex Systems Science at the Smith School of Enterprise and the Environment and Director of the Complexity Economics programme at the Institute for New Economic Thinking University of Oxford. He is also External Professor at the Santa Fe Institute and Chief Scientist at Macrocosm. His current research is in economics, including agent-based modelling, financial instability and technological progress. He was a founder of Prediction Company, a quantitative automated trading firm that was sold to UBS in 2006. His past research includes complex systems, dynamical systems theory, time series analysis and theoretical biology. His book, Making Sense of Chaos: A Better Economics for a Better World, was published in 2024. During the 1980s he was an Oppenheimer Fellow and the founder of the Complex Systems Group at Los Alamos National Laboratory. While a graduate student in the 1970s he built the first wearable digital computer, which was successfully used to predict the game of roulette. ","author_name":"Climate Risk Podcast","author_url":"http:\/\/climaterisk.libsyn.com\/website","html":"<iframe title=\"Libsyn Player\" style=\"border: none\" src=\"\/\/html5-player.libsyn.com\/embed\/episode\/id\/34410345\/height\/90\/theme\/custom\/thumbnail\/yes\/direction\/forward\/render-playlist\/no\/custom-color\/88AA3C\/\" height=\"90\" width=\"600\" scrolling=\"no\"  allowfullscreen webkitallowfullscreen mozallowfullscreen oallowfullscreen msallowfullscreen><\/iframe>","thumbnail_url":"https:\/\/assets.libsyn.com\/secure\/content\/182260860"}