Climate change is projected to sharply reduce agricultural productivity in hot developing countries and raise it in temperate regions. Reallocation of labor across sectors could temper the aggregate impacts of these changes if hotter regions shift toward importing food and specializing in manufacturing or exacerbate them if the need to meet subsistence food requirements pushes labor toward agriculture where its productivity suffers most. I quantify these effects in two steps. First, I project changes in the relative productivity between agriculture and non-agriculture by using firm-level micro-data from 17 countries to estimate the effects of extreme temperatures on output per worker in manufacturing and services industries. I find large effects of extremely hot and cold temperatures on non-agricultural output per worker, but treatment effects diminish with income and expectations of temperature such that the projected impact of climate change is larger in agriculture than non-agriculture. Second, I embed my estimates in a global model of labor specialization and trade estimated to mimic key features of the world. I use the model to simulate how climate change is likely to affect the reallocation of labor across sectors, trade in food and non-food, and people’s incomes around the world. My results suggest that subsistence food requirements dominate labor reallocation in response to climate change on average and the global decline in GDP is 12.0% larger, and 52.1% larger for the poorest quartile of the world, when accounting for the change in sectoral specialization that causes more people to work on farms to meet food demand where agricultural productivity suffers most. Trade reduces the welfare costs of climate change by only 7.4% relative to a scenario with no trade largely because poor countries vulnerable to climate change trade very little food. In an alternative scenario with freer trade, the productivity costs of climate change are 30.7% lower, and 68.2% lower for the poorest quartile, as shifting global trade patterns allow agricultural production to move away from the hardest hit regions.

To receive the Zoom log in information for future events, please sign up for the Lunch & Learn mailing list.