Combining ambitious climate policies with efforts to eradicate poverty

The Paris Agreement and Sustainable Development Goals (SDGs) set an ambitious agenda for climate change mitigation and sustainable development, with poverty eradication as a key objective. Unabated climate change threatens to undermine poverty reduction efforts, disproportionately affecting the Global South and vulnerable households. Mitigation policies, while necessary, could also negatively impact the poor through increased energy and food prices, potentially hindering progress toward clean energy access and creating poverty traps. Existing integrated assessment models (IAMs) often lack the detail to accurately represent the distributional effects of climate policies, particularly in developing countries. Previous studies considering poverty implications of climate change mitigation are limited in scope, focusing on moderate carbon prices, static frameworks, or a limited number of countries, and often neglecting the impact of land-based mitigation measures. This study addresses these limitations by analyzing the poverty consequences of an ambitious, Paris-compatible mitigation policy using the REMIND-MAgPIE IAM framework. The study focuses on a scenario with differentiated carbon prices and explores the effects of national redistribution policies and international climate finance on poverty alleviation. It assesses the potential trade-off between climate action (SDG 13) and poverty eradication (SDG 1.1) and proposes mechanisms to overcome this trade-off.

The literature highlights the interconnectedness of climate change and poverty. Studies show that unabated climate change will exacerbate poverty, particularly in developing countries, increasing global inequality. Mitigation policies, while crucial, can impose costs on the poor through higher energy and food prices. Existing research often focuses on moderate carbon pricing or lacks comprehensive models capturing the complex interplay between climate policies and poverty. There's a need for integrated assessment models (IAMs) with detailed representation of distributional effects. Previous studies have analyzed the impact of climate change or mitigation policies on poverty but lacked a global perspective, robust modeling, or consideration of different redistribution mechanisms. This paper addresses these gaps by using a state-of-the-art IAM to analyze the impacts of ambitious climate policies on global poverty, incorporating various redistribution strategies and international climate finance.

The study uses the REMIND-MAgPIE integrated assessment model (IAM), a state-of-the-art framework combining energy-economic-climate modeling with a spatially explicit land-system model. The model projects income distribution changes resulting from mitigation policies consistent with a 1.5°C target, implemented through regionally differentiated carbon prices. The Shared Socioeconomic Pathways (SSPs) inform assumptions about GDP, population, and inequality trends. Three SSP scenarios (SSP1, SSP2, and SSP5) are analyzed, representing varying socioeconomic development pathways. The researchers use the model to project changes in income distribution, and subsequently link these changes to poverty outcomes using a regression model calibrated on recent poverty and inequality data. The model's output includes national poverty rates and global poverty headcounts under different scenarios, including those with and without redistribution schemes. Two key redistribution schemes are analyzed: (1) a distributionally neutral approach, where the carbon pricing revenues are redistributed proportionally to income, and (2) a progressive approach, where revenues are distributed as an equal-per-capita climate dividend. The study also explores the effects of additional measures, such as including revenues from land-use emissions and international climate finance, to maximize poverty reduction co-benefits. A Monte Carlo simulation is used to analyze the income distribution, incorporating uncertainties. A regression model links income distribution changes to poverty outcomes, considering average income and the Gini coefficient as drivers, and accounts for uncertainties using 68% prediction intervals. The international poverty line of $1.90/day (PPP 2011) is primarily used, with a sensitivity analysis employing a higher poverty line of $5.50/day to analyze long-term trends.

The study projects that without climate policies, approximately 350 million people will remain in extreme poverty by 2030 (SSP2). Ambitious mitigation policies without progressive redistribution would push an additional 50 million into poverty (SSP2). However, redistributing national carbon pricing revenues as an equal-per-capita climate dividend largely offsets this negative effect, even resulting in a small net reduction in global poverty (-6 million). The study highlights regional variations. Sub-Saharan Africa, with its high poverty rates and modest carbon pricing revenues, demonstrates the need for international climate finance to fully compensate for the negative effects of climate policies. International climate finance, transferring a fraction of carbon pricing revenues from developed to developing countries, substantially reduces poverty, particularly in Sub-Saharan Africa. Additional measures like more progressive redistribution or including revenues from pricing land-use emissions further enhance poverty reduction co-benefits. Long-term analysis (until 2050) using a higher poverty line ($5.50/day) shows that even with redistribution, ambitious mitigation policies might lead to increases in poverty unless complemented by additional measures like utilizing revenue from land-use emissions. The study's sensitivity analysis showed that more stringent mitigation targets (well-below 2°C and 2°C) lead to higher carbon pricing revenues but potentially slightly worsen the net poverty outcome after redistribution due to the faster decline in carbon pricing revenues as CO2 neutrality is approached. The analysis also underscores the importance of considering a higher poverty line for longer-term poverty eradication, revealing the sustained need for substantial efforts, particularly in Sub-Saharan Africa.

The findings demonstrate that ambitious climate policies can be implemented without exacerbating poverty if coupled with effective redistribution mechanisms. Progressive redistribution of carbon pricing revenues is crucial, but international climate finance is necessary to address regional disparities, particularly in Sub-Saharan Africa. The study's emphasis on ambitious mitigation targets highlights the importance of early action and strategic policy design. The model's limitations, such as its aggregate nature and exclusion of climate impacts, should be considered. Future research should explore more detailed sectoral impacts, incorporate climate impacts, and consider other SDG dimensions for a more comprehensive assessment of policy trade-offs. The study's results suggest that integrating poverty considerations into climate policy design is not only ethically imperative but also crucial for achieving broader sustainable development goals.

This study demonstrates that ambitious climate policies compatible with the 1.5°C target can be designed to avoid exacerbating global poverty. Progressive redistribution of carbon pricing revenues, combined with international climate finance, is essential for achieving this. Future research should incorporate a more detailed assessment of the effects of climate change impacts and explore the interaction between climate policies and other sustainable development goals. The findings emphasize the importance of incorporating equity and poverty considerations into climate policy decision-making to ensure a just and sustainable transition.

The study uses an aggregate model and does not capture the heterogeneous effects of climate policies on different income groups within countries. It excludes direct climate impacts on poverty, focusing solely on the distributional effects of mitigation policies. The model's assumptions about redistribution mechanisms and institutional capacity are idealized, potentially overestimating the effectiveness of some policies. The analysis relies on projected income distributions and may not fully capture the complex dynamics of poverty.