Real data in climate cost modeling

Climate Change estimates a 12% GDP Hit: Why the Real Cost of Carbon Is 6x Higher Than previous research. New research by Adrien Bilal and Diego Känzig shows that the macroeconomic damage of climate change is six times larger than previously estimated. Global temperature rises—not local ones—are an economic threat, with a 1°C increase slashing global GDP by 12%. Their model sets the Social Cost of Carbon at $1,367/ton— above current policy benchmarks. Abstract: We estimate the macroeconomic damage function of climate change by combining a structural macroeconomic model with a new panel dataset for 174 countries over 1960–2019. Our approach overcomes the attenuation bias from local temperature shocks and separates the effects of persistent global warming from transitory local weather shocks. We find that a 1°C increase in global temperature leads to a 12% decline in world GDP. Damages are heterogeneous, with poorer and hotter countries suffering the most. These effects are driven by persistent productivity losses and are amplified by capital accumulation. Our estimated damage function implies a Social Cost of Carbon (SCC) of $1,385 per ton of carbon dioxide—more than six times the US government’s current estimate. Our results highlight the importance of accounting for macroeconomic persistence and heterogeneity when evaluating climate damages.” And link to paper in comments and below.

Milestone: 20,000 assets are now tracked on Beehive Climate. Employees in flood zones. Data centers facing extreme heat. Offices in wildfire paths. Suppliers underwater. Retail locations in hurricane alleys. 20,000 reasons companies finally understand that climate risk isn't theoretical. Here's what those 20,000 data points taught our customers: A retailer discovered 28% of stores sit in high heat wave areas. That could cost millions in increased pay to comply with OSHA regs. A tech company found 400+ employees live in areas that will see high hurricane risk by 2035. Their "return to office" strategy just got complicated. A tech company found 3/5 data centers in high risk areas. One intense storm could cause a failure worth millions. A VP of Sustainability at a global healthcare company told me last week: "We spent years counting carbon. Meanwhile, the Hawaii fires knocked out our market leadership position there, and the LA fires forced us to leave California entirely." That's the shift. From exclusively measuring your impact on climate (still long-term important) to also measuring climate's impact on you (short-term important). 20,000 assets. Each one represents real people, real operations, real revenue at risk. And we're just getting started.

📢 Research Alert: A Probabilistic Framework for Climate Scenario Analysis 🌍 "Median global warming expected at 2.7°C - well above the #ParisAgreement" As climate risks become central to #financial and #regulatory decision-making, one challenge remains critically unmet: most climate scenarios lack probabilistic grounding. To address this, the EDHEC Climate Institute with Lionel Melin, Riccardo Rebonato, FANGYUAN ZHANG has released a groundbreaking study: 📘 "How to Assign Probabilities to Climate Scenarios" This research proposes an innovative framework to quantify the likelihood of long-term temperature outcomes, enriching narrative-based scenarios with a probabilistic layer essential for asset pricing, risk management, and policy planning. ✅ Key contributions: • Based on 5,900+ Social Cost of Carbon estimates from 207 academic sources • Uses two rigorous methods: an elicitation-based approach and a maximum-entropy framework • Integrates real-world policy constraints and macroeconomic data 🔍 Findings: • 35–40% chance of >3°C warming by 2100 • The 1.5°C target is technologically feasible, but highly improbable • Median expected warming: 2.7°C - well above the Paris Agreement • Physical climate damages outweigh the cost of transition, emphasizing urgent financial realignment 🔗 The study also maps #probabilities onto Oxford Economics’ scenario framework, assigning over 90% likelihood to pathways involving limited or delayed emissions cuts: Climate Catastrophe, Climate Distress, and Baseline. 👉 A must-read for those in climate finance, regulatory strategy, and risk modeling. This research pushes the frontier in integrating uncertainty and feasibility into climate scenario analysis. #ClimateChange and #Mitigation remains both the greatest source of risk and of opportunity of our time. Let’s prepare! radicant bank #InvestInSolutionsNotProblems

I had the privilege to work on developing a quantitative approach to #financialimpacts of #climatechange with Matthew Gardner and the team at Sustainserv. It was a real eye-opener on current state of play! While I am a fan of global climate risk models and have read multiple Nature Climate Change and Science papers over the years, translating these into meaningful real time business decisions is hard. It also doesn't help when climate risk vendors provide results on a qualitative high-medium-low (or deciles) scale. It takes some less than satisfactory assumptions to translate this into a numeric scale. But even more important as we note in the blog, a "down-scaled" global model cannot pick up important location specific conditions. Climate risk is in the tails of the distribution, not in global averages. That's what is critical for facility managers to understand and prepare for. More detailed localized data is essential to provide relevant decision-useful information. Thankfully I found reams of measured data to develop more precise risk models not only for physical risk, but also workforce heat related risks and important local risk multipliers. This information combined with economic and public health research made it possible to estimate financial impacts in a much more direct and transparent way. Enjoy the read! https://lnkd.in/enYwX5Et