High-frequency survey data reveal complex impact pathways of climate-related disasters on household welfare in Malawi

Climate-related disasters often disproportionately impact the welfare of poor or marginalized households. However, the distributional impact of disasters on household welfare i.e., how these impacts vary across socioeconomic groups, remains underexplored in climate risk assessments. Further, existing frameworks often fail to capture the multidimensional nature of these impacts, such as disruptions to education, health services, food, livelihoods, work and well-being. These frameworks also fail to represent the temporal dynamics of impacts, particularly how they evolve during and after a disaster event. These limitations pose a challenge to develop quantitative models that adequately inform equitable policy responses. 

To address this gap, our research examines how multiple impact channels of disasters influence household welfare over time. Using high-frequency, longitudinal survey from Malawi (from the World Bank's Living Standard Measurement Study (LSMS)), this study analyses over 1,600 households across all districts of Malawi over 21 survey rounds (2021-2024). This timeframe includes major events like Cyclone Freddy in February 2023 and widespread floods in February 2024. The survey covers diverse indicators serving as proxies for household welfare, such as access to essential services, employment, food insecurity, price fluctuations (food, fuel, transport), and subjective welfare. Using descriptive statistics, regression models and time series analysis, we aim to highlight the diverse pathways through which disasters exacerbate socio-economic vulnerabilities, examining how these impacts vary across different regions and over time. 

Preliminary results draw attention to the complex relationship between climate-related hazards and differential household-level impacts, both spatially and across households. For example, food price responses show a sharp surge in the cost of domestically produced staples, such as maize, in flood-impacted areas due to Cyclone Freddy. Additionally, subjective welfare responses reveal that households in rural regions were disproportionately affected. Unlike their urban counterparts, rural families struggled to acquire sufficient food, fuel and other essential goods for their households, as higher prices reduced their purchasing power and further undermined their well-being. 

By capturing these spatiotemporal dynamics, our study increases our understanding of disaster impacts on household welfare. Our study paves the way for integrating these impact pathways into quantitative climate risk assessment models, ultimately aiming to make more informed and equitable decisions in disaster risk management. 

Keywords: Climate-related disasters, household welfare, high-frequency data, distributional impact, multidimensional impact pathways, temporal dynamics