We repeat this comparison for each climate model m and each bootstrap j, yielding more than 20,000 realizations of the impact of anthropogenic forcing on economic growth in each country. Because growth effects cumulate, the length of time over which economic impacts are evaluated can meaningfully affect results (4, 12, 14). Furthermore, at a given level of wealth, warmer countries have tended to experience more negative impacts, while cooler countries have tended to experience less negative—or in some cases more positive—impacts. Trade between countries has likely already influenced the impacts of global warming on population-weighted inequality. This expansion over longer periods suggests that the full impact of warming since the Industrial Revolution has been even greater than the impact calculated over the past half century. Thus, our results show that, in addition to not sharing equally in the direct benefits of fossil fuel use, many poor countries have been significantly harmed by the warming arising from wealthy countries’ energy consumption. 21)—would likely have been even greater in poor countries in a no-trade counterfactual, amplifying the impact on between-country inequality. (14), using historical data from 1961 to 2010, and bootstrapping with replacement to estimate a separate response function for each of 1,000 resamples, which we denote fb. We acknowledge the World Climate Research Programme’s Working Group on Coupled Modelling (which is responsible for CMIP), the climate modeling groups for producing and making available their model output, and the Department of Energy’s Program for Climate Model Diagnosis and Intercomparison for access to the CMIP5 data. 1), or to global GDP (12). Likewise, of the 36 countries whose historical emissions are between 10 and 100 ton CO2 per capita, 34 (94%) have suffered negative economic impacts, with a median impact of −24%. (C and D) The probability that historical anthropogenic forcing has resulted in economic damage, calculated as the percentage of the >20,000 realizations that show a decrease in per capita GDP relative to the counterfactual world without anthropogenic forcing. (B) The annual temperature for selected countries from historical observations [black; calculated as in Burke et al. (A) The ratio between the population-weighted 90th percentile and 10th percentile country-level per capita GDP for the historical observed time series and each of the >20,000 realizations of the world without anthropogenic forcing. S3). 3 A and B), the majority of large negative impacts have been concentrated in poor countries (Fig. Although there is uncertainty in whether historical warming has benefited some temperate, rich countries, for most poor countries there is >90% likelihood that per capita GDP is lower today than if global warming had not occurred. is a guest editor invited by the Editorial Board. Scientific evidence suggests that global warming has already increased global economic inequality (35) and influenced immigration waves (36). Note that although the socioeconomic data are available through 2010, the CMIP5 experimental protocol for the Historical and Natural experiments ends in 2005. We thank the editor and two anonymous reviewers for insightful and constructive feedback. As a result, anthropogenic climate forcing has decreased economic growth of countries in the low latitudes and increased economic growth of countries in the high latitudes (Fig. 2019 Nov 5;116(45):22645-22650. doi: 10.1073/pnas.1908683116. and M.B. This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.1073/pnas.1816020116/-/DCSupplemental. Proc Natl Acad Sci U S A. Borrelli P, Robinson DA, Panagos P, Lugato E, Yang JE, Alewell C, Wuepper D, Montanarella L, Ballabio C. Proc Natl Acad Sci U S A. Science. Computational facilities were provided by the Center for Computational Earth and Environmental Science and Stanford Research Computing Center at Stanford University. Both metrics are included among “eight of the most popular” indexes of income inequality identified by Sala-i-Martin (9). Please enable it to take advantage of the complete set of features! (C and D) The probability that historical anthropogenic forcing has resulted in economic damage, calculated as the percentage of the >20,000 realizations that show a decrease in per capita GDP relative to the counterfactual world without anthropogenic forcing. Because the majority of the world’s warmest countries are poor (Fig. As a result, although overall between-country inequality has decreased substantially over the past half century (Fig. Clipboard, Search History, and several other advanced features are temporarily unavailable. For each country c, we first calculate the observed country-level population-weighted mean annual temperature timeseries TObs for the 1961–2010 time period covered by the socioeconomic data, following Burke et al. Country-level economic response to global warming. 14, darker red colors indicate cooler temperature optima and thus greater likelihood of negative impacts from warming. Burke M, Hsiang SM, Miguel E. Global non-linear effect of temperature on economic production. We do not capture any email address. 1B) creates uncertainty in exactly which countries are likely to benefit or be penalized at different levels of warming, and is the largest source of uncertainty in the response of GDP growth to elevated levels of global climate forcing (14). A study finds that imposing a tax on orbiting satellites could increase the value of the satellite industry from $600 billion to $3 trillion by 2040 by decreasing collision risks and space debris. For these countries, it is “very likely” (27) that historical warming has reduced economic growth and lowered per capita GDP (Fig. Enter multiple addresses on separate lines or separate them with commas. The uncertainty in the magnitude of the temperature optimum (Fig. 1B), such an outcome is not determined for historical climate forcing, because internal climate variability creates uncertainty in the sign and magnitude of regional temperature change (e.g., refs. Get the latest research from NIH: https://www.nih.gov/coronavirus. Image credit: Mak Saito (Woods Hole Oceanographic Institution, Woods Hole, MA).
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