Simulation of subnational projections of poverty and income distribution to support climate risk assessments: A case-study for Ethiopia

van Dijk, M. ORCID: https://orcid.org/0000-0002-5207-7304, Kuiper, M., de Lange, T., Koopman, J.F.L., & van Zeist, W.-J. (2026). Simulation of subnational projections of poverty and income distribution to support climate risk assessments: A case-study for Ethiopia. Climate Services 43 e100668. 10.1016/j.cliser.2026.100668.

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Abstract

The global poor are expected to suffer most from the impact of climate change, in particular the increasing frequency of extreme weather events. To develop targeted climate adaptation strategies, national decision makers need to have detailed information on the quantity, location and profile of the people that are most vulnerable to climate hazards. This study presents an innovative spatial microsimulation modelling framework for projecting subnational income distribution and poverty trends under different scenarios that can be combined with spatial data on climate hazards to support climate risk assessments. The model combines household survey data with subnational projections on key drivers of income to simulate how the distribution of income changes as a consequence of economic development and structural transformation. To illustrate our modelling framework, we provide an application to Ethiopia. We projected changes in poverty headcount and income distribution for 60 different zones and three different socio-economic scenarios for the period 2020–2050. We combined the subnational income projections with heat stress maps to identify the number and profile of the population that are most vulnerable to climate change and found that, depending on the scenario, between 1.4 and 9.4 million poor people (1-5% of the population) will be at risk of heat stress in Ethiopia in 2050. The modelling framework can be combined with spatial data of additional climate hazards, such as floods and droughts, and be applied to other countries and regions, to support national climate information systems and inform climate adaptation strategies and policies.

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