Understanding the likely global economic impacts of climate change is of tremendous practical value to both policymakers and researchers. Yet the economics literature has struggled both to provide empirically founded estimates of the economic damages from climate change and to provide quantitative insight into what climate change will mean at the local level for diverse populations. The Climate Impact Lab (a collaboration among Rutgers, UC-Berkeley, the University of Chicago, and the Rhodium Group) is advancing a method based on combining: (1) probabilistic simple climate model projections of the global mean response to forcing, downscaled and pattern-scaled based on CMIP-class models to translate global mean to local responses, and (2) empirical econometric estimates of the historical response of human systems to weather variability, derived from massive, standardized data sets and incorporating cross-sectional variability to estimate the benefits and costs of climate adaptation. This talk will focus on the example of temperature-related mortality and associated adaptation using sub-national data from 40 countries. Our results demonstrate that the temperature-related mortality impacts fall disproportionately on low-income populations, with high-income counties projected in the median to experience a decline in mortality through 2100, even under RCP 8.5, although the economic benefits of this decline are outweighed by the costs of adaptation. Even moderate emissions reductions result in substantial benefits, with median projected global mortality risk in RCP 4.5 (SSP 3 Socioeconomics) about 85% lower than that under RCP 8.5.