We then aggregate all optimistic country‐level scenarios into a global optimistic scenario, labelled the _prosperity_ scenario. This scenario is consistent with the World Bank twin goals of eradicating extreme poverty and promoting share prosperity: (1) the number of people living below the extreme poverty line is less than 3% of the global population; and (2) consumption growth for the bottom 40% in countries is high. We also assume that the world described in our prosperity scenario provides basic services (electricity, water and sanitation), basic social protection, and health care and coverage to the entire population. Since each country‐level scenario is chosen so that GDP growth is close to the GDP values from the SSP5 and that most countries optimistic scenario have the demographics from the SSP5, our _prosperity_ scenario can be considered as a quantified pathway for poverty in the SSP5. But our _prosperity_ scenario is not the SSP5, and it does not follow the narrative from the SSP5, especially concerning the energy mix and use of fossil fuels.

Similarly, we aggregate all pessimistic country‐level scenarios into a global pessimistic scenario, labelled the _poverty_ scenario. In this scenario, extreme poverty decreases much less, to reach 11% of the global population in 2030, inequality is much larger across and within countries. In this scenario, we also assume that access to basic services, social protection, and health care improves only marginally. This scenario is consistent with the narrative from the SSP4, and our _poverty_ scenario can therefore be considered a quantification of poverty in SSP4.

Figure 9 shows the poverty rate (left panel) and income growth of the bottom 40 percent (right panel) in all countries, in 2007 and in 2030 in the poverty and prosperity scenarios. These two scenarios are representative of successful futures and more pessimistic ones, and can be used to assess the consequence of various shocks and stresses, accounting for the different in vulnerability due to future socioeconomic trends.

It is important to note that these scenarios are not extreme scenarios and they do not provide a range of what is considered possible or plausible: instead, they represent typical scenarios for two possible future, one optimistic and one pessimistic. But it is possible to find in our scenario set some scenarios that are better than the _prosperity_ scenario or worse than the _poverty_ scenario.

# 5. Climate change impacts on poverty

In each country and for each of the two selected socio‐economic scenarios ( _prosperity_ and _poverty_ ) we introduce climate change impacts on food price and production, health, labor productivity, and natural disasters. We add these climate change impacts to the characteristics of each household in the database, following the methodology described in Section 2.

The climate change impacts are not “new” impacts: they mostly correspond to the worsening of existing issues, such as more frequent disasters or more malaria cases. In this analysis, we assume that the impacts due to the current climate are already included in our baseline scenarios, _prosperity_ and _poverty_ . We add to these scenarios the _additional_ impact of climate change. For malaria for instance, the current extent and impacts of the disease are assumed already included in the scenarios presented in Section 4, and we add the costs and lost income from the cases that would not have occurred in the absence of climate change.

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