In the realm of economics, few issues are as complex and contentious as estimating the cost of climate change. When William Nordhaus, a future Nobel laureate, first modelled the economic impact of global warming, he described the “damage function” as a wiggly line, an uncertain frontier he aptly named “terra incognita”. Today, despite significant advancements in technology and methodology, the challenge remains formidable. Diego Känzig of Northwestern University and Adrien Bilal of Harvard University, through modelling using historical temperature changes from volcanic eruptions and El Niño events, have suggested that the economic impact of climate change could be far more severe than previously thought. Yet, despite these efforts, arriving at a precise and universally accepted estimate of climate change costs continues to be fraught with difficulties.
One primary obstacle is the intrinsic complexity of the Earth’s climate system. Climate models must account for a myriad of factors, from greenhouse gas emissions to deforestation, and their interactions are not fully understood. For instance, the exact amount of additional warming produced by a tonne of greenhouse gas remains uncertain. The potential for tipping points—critical thresholds beyond which climate change could accelerate rapidly—adds another layer of unpredictability. These tipping points could dramatically alter the climate system, making current models obsolete almost overnight.
Another challenge lies in modelling the economic impacts of these climate changes. Early methods, such as Nordhaus’s comparative approach between hotter and colder countries, provided a rough estimate but left out numerous variables. Norway’s wealth relative to Nigeria, for example, cannot be attributed solely to temperature differences. Modern “top down” strategies, which track regions over time, offer improvements but still struggle with issues like non-stationarity and autocorrelation. Economic growth and temperature both follow upward trends but fluctuate based on past deviations. This makes isolating the impact of temperature changes on economic growth exceedingly difficult and often results in spurious correlations.
The solution proposed by Känzig and Bilal—analyzing global temperature shocks—addresses some issues but introduces new ones. Their approach looks at worldwide temperature variations caused by phenomena like El Niño, correlating these with global economic growth. While this method mitigates the small-area problem, it is limited by the relatively minor historical temperature changes compared to the significant increases projected for the future. Additionally, starting their data set in 1960 means they have fewer observations, complicating efforts to control for concurrent economic shocks like the Latin American debt crisis and the Asian financial crisis.
Alternatively, the Environmental Protection Agency (EPA) employs a ‘bottom-up’ approach, aggregating various indicators of climate damage such as changes in agricultural yields, mortality rates, sea-level rise, and energy demand for cooling. While comprehensive, this method still cannot capture the full spectrum of climate change’s global impacts, such as disrupted trade patterns. It also depends on an exhaustive list of costs, which is inherently challenging to compile and likely to miss critical factors.
Moreover, human adaptation adds another layer of complexity. People might migrate, develop new technologies, or change agricultural practices in response to climate changes, mitigating some damages but introducing new variables into the models. The human element—our ability to innovate and adapt—makes predicting economic impacts even more uncertain. Historical examples show humans thriving in diverse climates, from the frozen expanses of Alaska to the steamy Amazon rainforest, suggesting a capacity for adaptation that is difficult to quantify.
Concluding, the task of estimating the costs of climate change is hampered by the interplay of complex climate dynamics, economic uncertainties, and human adaptability. Even though methodologies have advanced significantly since Nordhaus’s pioneering work, the inherent uncertainties and potential for unforeseen variables ensure that precise cost estimates remain elusive. Nevertheless, one thing is clear: the costs are likely far greater than initially imagined, and the urgency for effective climate policies is more pressing than ever. As we navigate this uncertain terrain, the imperative to reduce greenhouse gas emissions and invest in sustainable technologies becomes ever more critical, guiding us toward a future where the costs of inaction do not outweigh the benefits of a proactive, informed approach.
Photo by Matt Palmer
The Trash Economy 