[Paper Review] Economists' erroneous estimates of damages from climate change

Stephen P. Keen, Timothy M. Lenton+4 more|arXiv (Cornell University)|Aug 17, 2021

Climate Change Policy and EconomicsEconomics, Econometrics and Finance18 citations

TL;DR

This paper critiques mainstream economic models of climate change damage, arguing they systematically underestimate risks by ignoring climate tipping points and assuming economic resilience to extreme weather. It demonstrates that the influential DICE model cannot simulate economic collapse, rendering its damage estimates scientifically invalid for policy use.

ABSTRACT

Economists have predicted that damages from global warming will be as low as 2.1% of global economic production for a 3$^\circ$C rise in global average surface temperature, and 7.9% for a 6$^\circ$C rise. Such relatively trivial estimates of economic damages -- when these economists otherwise assume that human economic productivity will be an order of magnitude higher than today -- contrast strongly with predictions made by scientists of significantly reduced human habitability from climate change. Nonetheless, the coupled economic and climate models used to make such predictions have been influential in the international climate change debate and policy prescriptions. Here we review the empirical work done by economists and show that it severely underestimates damages from climate change by committing several methodological errors, including neglecting tipping points, and assuming that economic sectors not exposed to the weather are insulated from climate change. Most fundamentally, the influential Integrated Assessment Model DICE is shown to be incapable of generating an economic collapse, regardless of the level of damages. Given these flaws, economists' empirical estimates of economic damages from global warming should be rejected as unscientific, and models that have been calibrated to them, such as DICE, should not be used to evaluate economic risks from climate change, or in the development of policy to attenuate damages.

Motivation & Objective

• To challenge the scientific validity of low damage estimates produced by mainstream climate-economics models.
• To expose methodological flaws in Integrated Assessment Models (IAMs), particularly the DICE model, that ignore climate tipping points and cascading system failures.
• To argue that models calibrated to these flawed estimates—like DICE—should not inform climate policy.
• To highlight the disconnect between scientific projections of climate tipping points and the economic models used in policy formation.
• To advocate for replacing economically biased models with science-based assessments of climate risk and damages.

Proposed method

• Reviewing empirical damage functions in IAMs, especially the DICE model’s damage function, to assess their structural and functional assumptions.
• Analyzing the DICE model’s sensitivity to increasing damage severity, showing it fails to generate economic collapse even under extreme climate scenarios.
• Comparing DICE’s linear or mildly convex damage functions with more realistic convex or capital-damaging functions proposed by Weitzman, Dietz & Stern.
• Evaluating the role of climate tipping points—such as Arctic sea-ice loss and Greenland ice sheet collapse—in triggering irreversible economic and climatic feedbacks.
• Contrasting the scientific consensus on tipping points with the economic literature’s assumption that such thresholds will not be crossed before 2100.
• Using model simulations to demonstrate that even with severe damages, DICE’s equilibrium framework prevents systemic economic collapse, undermining policy relevance.

Experimental results

Research questions

• RQ1 Why do mainstream economic models like DICE produce such low estimates of climate change damages—only 2.1% to 7.9% of global GDP for 3°C to 6°C warming?
• RQ2 How do the assumptions in the DICE model’s damage function fail to reflect known climate tipping points and cascading system failures?
• RQ3 To what extent can the DICE model generate economic collapse under extreme climate damages, and why is this impossible within its framework?
• RQ4 Why have flawed damage estimates from IAMs dominated policy discussions despite scientific evidence of higher risks?
• RQ5 What are the implications of using models that ignore non-linear, irreversible climate impacts for long-term climate policy?

Key findings

• Economists’ damage estimates for climate change—such as 2.1% of GDP loss at 3°C warming—are fundamentally flawed and fail to account for climate tipping points.
• The DICE model is structurally incapable of generating economic collapse, regardless of the level of climate damages, due to its equilibrium-based design.
• Tipping points such as Arctic sea-ice loss and Greenland ice sheet collapse are widely recognized in the scientific literature but are systematically excluded from economic damage functions.
• Even when more realistic damage functions (e.g., convex or capital-damaging) are applied in DICE, the model still fails to produce collapse, though it does increase policy stringency.
• The Social Cost of Carbon (SCC), derived from models like DICE, is therefore misleading and underestimates true climate risks, leading to inadequate policy responses.
• The dominance of these flawed models in policy—especially in U.S. government assessments—has led to paralysis and underestimation of climate risks, favoring inaction over bold mitigation.