With increasingly stringent climate policies and green technologies – like renewable energy and electric transportation – becoming cheaper than fossil fuel equivalent, future economic growth is expected to be more energy efficient and less carbon intensive. We further show the extent to which these changes can reduce the emissions of poverty eradication<sup>24</sup> and estimate the rates of decarbonization that would be required in non-poor countries to offset these emissions.

# **Results**

**How much economic growth is needed to end extreme poverty?** We estimate the historical relationship between growth in GDP per capita and growth in consumption per capita in a random slope regression model, taking into account trends across and within countries. We use data for 168 countries from the World Bank’s 2022 Poverty and Shared Prosperity Report<sup>25</sup> , converting income distributions to consumption distributions where needed. We also winsorize daily per capita consumption at a value of $0.50 as lower values likely reflect measurement error. We find that, on average, when GDP per capita grows by 1%, consumption per capita grows by 0.7%, with variation between countries (the remainder of growth in GDP per capita is likely being allocated to savings which would imply that the savings rate converges to around 30% in the long term). Using the international extreme poverty line at $2.15 in 2017 USD PPP, we focus, in our baseline model, on the poverty target of reducing the share of people living in extreme poverty to 3% or less, the World Bank’s global poverty target and the UN’s interpretation of ending extreme poverty in the SDGs.<sup>3</sup> We estimate the growth necessary to reach this target in each country, assuming to begin with an unchanged distribution of consumption within countries and modeling population growth until 2050 according to UN forecasts.<sup>26</sup>

The per capita GDP growth needed to reduce extreme poverty to 3% ranges from zero to nearly 600% -- a sixfold expansion of the economy (Figure 1, panel A). Non-poor countries require zero growth as the poverty target is already reached. North America is the only region in which all countries have achieved this poverty target, while countries in Sub-Saharan Africa need to grow on average by 215% to reach it (Figure 1, Panel B). Targeting higher poverty lines ($3.65, $6.85 – poverty lines typically of lower and upper-middle income countries respectively<sup>27</sup> ) requires more growth in more countries than targeting extreme poverty, as more countries are considered poor against higher poverty lines (zero to 1117% at $3.65; zero to 2251% at $6.85; Extended Figure 5). A minimum consumption level of $15 per day in all countries would need per capita GDP growth ranging between zero (in 28 countries) and 5140% (Extended Figure 5). We show the implications of targeting poverty rates other than 3% (5%, 4%, 2%, 1%, 0%; Extended Figure 13).

**With historical energy-intensity patterns, how much energy is required for economic growth?** To link GDP growth with greenhouse gas (GHG) emissions, we first relate GDP per capita to energy consumption per capita and then relate energy consumption per capita to greenhouse gas emissions. For this, we combine GDP data from the World Development Indicators (WDI) with data from the Energy Information Administration (EIA) on primary energy consumption and with data on GHG emissions from Climatewatch/CAIT, all for 2010 to 2019 (the latest year the data are available).

We again use a random slope regression to model the relationship between GDP and energy consumption, which also allows for efficiency gains over time. The random slope model exploits both variation between countries and variation within countries, and in this case allows for countries to convert GDP to energy needs at different rates and improve (or deteriorate) in energy efficiency at different rates. We cap the distribution of country-level coefficients at the 10<sup>th</sup> and 90<sup>th</sup> percentiles as the extreme values likely reflect measurement error or historical patterns that are unlikely to continue in the future.

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