Blind Spots in Economic Models Conceal Catastrophic Climate Risks

2026-02-05 economy

London, Thursday, 5 February 2026.
Experts warn that flawed models ignoring tipping points could trigger a financial collapse, as actuaries predict a staggering 50% global GDP loss by 2090.

The Radar is Broken

Financial markets are currently navigating a climate storm with instruments that are fundamentally defective. A landmark report published this week by the University of Exeter and the Carbon Tracker Initiative warns that the economic models underpinning global financial decisions are drastically underestimating the physical risks of climate change [1][4]. Released on February 4, 2026, the report, titled Recalibrating Climate Risk, aggregates expert judgments from over 60 climate scientists to demonstrate how current forecasting methods overlook extreme weather events and irreversible tipping points [1][7]. Dr. Jesse Abrams, the lead author from the University of Exeter, argues that these models fail to capture “the cascading failures and compounding shocks that define climate risk in a warmer world,” noting that this oversight could undermine the foundations of economic growth itself [1].

The Illusion of Stability

The core of the problem lies in the obsolescence of traditional economic frameworks, particularly those that assume the future will behave like the past [1][7]. Critics point to the Dynamic Integrated model of Climate and the Economy (DICE), developed by Nobel laureate William Nordhaus, as a prime example of this analytical failure [3]. While DICE treats climate change as an optimization problem balancing mitigation costs against future damages, it effectively “smooths” impacts over time and space [3]. This approach suggests that even with warming of 3°C or 4°C, global GDP losses would be minimal—a conclusion that stands in stark contrast to physical science [3]. Furthermore, relying solely on GDP as a metric masks the destruction of capital, increased mortality, and the profound disruption of social wellbeing, leading to what researchers describe as a “blind spot” in financial planning [2].

Quantifying the Uncountable

When the veil of these smoothed averages is lifted, the economic outlook darkens significantly. In January 2025, actuaries predicted that catastrophic climate shocks could result in a 50% loss in global GDP between 2070 and 2090 [1]. This projection aligns with the reality that critical tipping points, such as the collapse of Atlantic currents or the Greenland ice sheet, were already considered to be at or near their breaking points as of late 2023 [1]. Historical precedents illustrate how these shocks manifest in reality rather than in models; for instance, the severe drought in Syria between 2006 and 2010 contributed to the displacement of 1.5 million people and the subsequent civil war, eventually displacing approximately 14 million Syrians [3]. Current economic models often fail to account for such geopolitical instability and cross-border spillovers, which occur even at current warming levels of 1.2°C to 1.5°C [3].

Systemic Risk and Fiduciary Duty

The disconnect between scientific reality and market pricing has created a dangerous complacency among investors. Mark Campanale, CEO of Carbon Tracker, warns that financial institutions are chronically under-pricing climate risks, leaving pension funds and taxpayers “dangerously exposed” [4]. This is not merely a theoretical concern; Hetal Patel of the Phoenix Group, one of the UK’s largest asset owners, emphasized that underestimating physical risk distorts investment decisions and underplays real-world consequences for society [1][4]. The urgency of this paradigm shift was underscored on January 28, 2026, when the UK government released a security assessment on ecosystem collapse, highlighting that the speed and severity of risks are outpacing regulatory action [4][7]. Consequently, there are growing calls for regulators to make the management of climate risk an explicit component of fiduciary duty to prevent a systemic crash [5].

Mathematical Flaws in Modeling

Beyond the data inputs, the mathematical architecture of these economic models is also under scrutiny. Many models utilize a “steady state” assumption, presuming that economies will eventually converge to a stable equilibrium in the long run [6]. However, in the context of environmental collapse, this assumption may be mathematically convenient but dangerously misleading [6]. Furthermore, the practice of “discounting”—reducing the value of future damages to present-day terms—has been criticized for heavily downplaying the long-term costs of climate inaction [3][6]. By prioritizing short-term optimization over long-term survival, these mathematical frameworks provide a “convenient shield” for delaying necessary climate action, creating a false sense of security while the physical risks continue to mount [3].

Sources

Systemic risk Financial modeling