Things Are Such
Things are such,
that someone lifting a cup,
or watching the rain,
petting a dog, or singing,
just singing – could be doing as
much for this universe as anyone.
This post I wrote was confirmed this week in Nature.
Growing evidence demonstrates that climatic conditions can have a profound impact on the functioning of modern human societies 1,2, but effects on economic activity appear inconsistent. Fundamental productive elements of modern economies, such as workers and crops, exhibit highly non-linear responses to local temperature even in wealthy countries3,4. In contrast, aggregate macroeconomic productivity of entire wealthy countries is reported not to respond to temperature5 , while poor countries respond only linearly5,6. Resolving this conflict between micro and macro observations is critical to understanding the role of wealth in coupled human–natural systems7,8 and to anticipating the global impact of climate change 9,10. Here we unify these seemingly contradictory results by accounting for non-linearity at the macro scale. We show that overall economic productivity is nonlinear in temperature for all countries, with productivity peaking at an annual average temperature of 13 6C and declining strongly at higher temperatures. The relationship is globally generalizable, unchanged since 1960, and apparent for agricultural and non-agricultural activity in both rich and poor countries. These results provide the first evidence that economic activity in all regions is coupled to the global climate and establish a new empirical foundation for modelling economic loss in response to climate change11,12, with important implications. If future adaptation mimics past adaptation, unmitigated warming is expected to reshape the global economy by reducing average global incomes roughly 23% by 2100 and widening global income inequality, relative to scenarios without climate change. In contrast to prior estimates, expected global losses are approximately linear in global mean temperature, with median losses many times larger than leading models indicate.