We used annual data on population, GDP and carbon emissions for each year from 1960 to 2015 for 161 countries containing over 99% of the world’s population. For population, we used the UN’s 2019 estimates of population for all countries from 1950 to 20159. We produced probabilistic projections for all countries with the model used by the UN for its probabilistic projections36.

GDP per capita data came from the Maddison Project, 2018 version39, using data from 1960 to 2015. This uses purchasing power parity (PPP) rather than market exchange rates, and provides two sets of GDP data, cgdppc for real GDP per capita in 2011US$ with multiple benchmarks, and rgdpnapc for real GDP per capita in 2011US$ with a 2011 benchmark. According to the documentation, rgdpnapc is suitable for cross-country growth comparisons, while cgdppc is more suitable for cross-country income comparisons. Since we are trying to forecast GDP per capita, we use rgdpnapc for GDP.

CO2 emissions data came from the Global Carbon Budget20. We used data from 1960 – 2015.

For historical temperature measures, we used the HadCRUT4 database40, a gridded dataset of historical surface temperature anomalies relative to a 1961–1990 reference period, used by the IPCC3. Data are available for January 1850 onwards and are updated monthly.

We based our forecast on the CMIP 5 model data41. Each experiment on CMIP 5 models includes historical simulations back to 1860, and also provides estimates of future climate changes, either near-term until 2035 or long-term until 2100 or even 2300, under different scenarios.

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