household surveys (from the I2D2 database) and micro‐simulation techniques (Olivieri et al. 2014; Bussolo et al. 2008; Bourguignon, Ferreira, and Lustig 2005) and is performed in a framework inspired from robust decision‐making techniques, in which all uncertain parameters are varied systematically to the full range of possible outcomes. We combine assumptions on future demographic changes (How will fertility change over time? How will education levels change?); structural changes (How fast will developing countries grow their manufacturing sector? How will the economies shift to more services?); productivity and economic growth (How fast will productivity grow in each economic sector?); and policies (What will be the level of pensions? How much redistribution will occur?). The range of possible futures of these parameters is determined based on historical evidence, and on the socioeconomic scenarios currently developed for the analysis of climate change, the Shared Socio‐Economic Pathways (SSPs) (Kriegler et al., n.d.; O’Neill et al. 2013). These sets of assumptions are used to generate hundreds of scenarios for the future socioeconomic development of Vietnam.

Then, we select two representative scenarios, one optimistic and one pessimistic in terms of poverty reduction and changes in inequality. Finally, we introduce quantified estimates of the impacts of climate change on agriculture incomes and food prices, on natural hazards, and on malaria, diarrhea and stunting into these two scenarios. Here again the impacts of climate change are uncertain. We thus consider again two cases, one high impact and one low impact, and investigate the potential impact of unmitigated climate change on the number of poor people living in extreme poverty in 2030 in the four cases (optimistic and pessimistic regarding socioeconomic trends, and optimistic and pessimistic regarding climate change impacts).

The results are unequivocal: the impact of climate change on poverty is conditioned by overall development progress. In particular, the impacts of climate change are lower in scenarios with high structural change away from agriculture, high productivity growth in the agriculture sector and high levels of social protection. In scenarios where these conditions are not met, climate change could bring up to 1 million additional people in extreme poverty by 2030.

# Even without climate change, very different futures can be imagined for poverty and development in Vietnam

We explore a wide range of uncertainties on future structural change, productivity growth or demographic changes and create a large number (several hundreds or thousands) of scenarios for future income growth and income distribution in Vietnam (Table 1). We then analyze the resulting space of possible future poverty and income distribution using several indicators like the income of the bottom 20%, the number of people living in extreme poverty, the income share of the bottom 40%, or GDP growth.

Consistently with our goal of exploring the largest possible uncertainty, the range of income growth in our scenarios is much larger than the one explored in other scenario exercises, such as the SSPs (Figure 1). All the hypotheses that were made on the input parameters appear however possible (or at least, non‐ impossible) and based on historical data (see Rozenberg and Hallegatte, 2015).

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