The goals of ending extreme poverty by2030 and working towards a more equal distribution ofincomes are part of the United Nations' SustainableDevelopment Goals. Using data from 166 countries comprising97.5 percent of the world's population, we simulatescenarios for global poverty from 2019 to 2030 under variousassumptions about growth and inequality. We use differentassumptions about growth incidence curves to model changesin inequality, and rely on a machine-learning algorithmcalled model-based recursive partitioning to model howgrowth in GDP is passed through to growth as observed inhousehold surveys. When holding within-country inequalityunchanged and letting GDP per capita grow according to WorldBank forecasts and historically observed growth rates, oursimulations suggest that the number of extreme poor (livingon less than 1.90 US Dollars/day) will remain above 600million in 2030, resulting in a global extreme poverty rateof 7.4 percent. If the Gini index in each country decreasesby 1 percent per year, the global poverty rate could reduceto around 6.3 percent in 2030, equivalent to 89 millionfewer people living in extreme poverty. Reducing eachcountry's Gini index by 1 percent per year has a largerimpact on global poverty than increasing each country'sannual growth 1 percentage points above forecasts. We alsostudy the impact of COVID-19 on poverty and find that thepandemic may have driven around 60 million people intoextreme poverty in 2020. If the virus increased the Gini by2 pecent in all countries, then more than 90 million mayhave been driven into extreme poverty in 2020.
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