Climate change and the nonlinear impact of precipitation anomalies on income inequality

Abstract

Climate anomalies, such as floods and droughts, as well as gradual temperature changes have been shown to adversely affect economies and societies. Although studies find that climate change might increase global inequality by widening disparities across countries, its effects on within-country income distribution have been little investigated, as has the role of rainfall anomalies. Here, we show that extreme levels of precipitation exacerbate within-country income inequality. The strength and direction of the effect depends on the agricultural intensity of an economy. In high-agricultural-intensity countries, climate anomalies that negatively impact the agricultural sector lower incomes at the bottom end of the distribution and generate greater income inequality. Our results indicate that a 1.5-SD increase in precipitation from average values has a 35-times-stronger impact on the bottom income shares for countries with high employment in agriculture compared to countries with low employment in the agricultural sector. Projections with modeled future precipitation and temperature reveal highly heterogeneous patterns on a global scale, with income inequality worsening in high-agricultural-intensity economies, particularly in Africa. Our findings suggest that rainfall anomalies and the degree of dependence on agriculture are crucial factors in assessing the negative impacts of climate change on the bottom of the income distribution.

Climate damage projections beyond annual temperature

“…While the overall impacts of variability and extremes remain substantially below those of annual temperature changes, they are likely to exacerbate global disparities further, in line with recent research on precipitation impacts 13 .…”

“…Furthermore, econometric-based dose-response functions like the ones used here have several limitations, e.g., the risk of conflating weather impacts with climatic shifts or the extrapolation of impacts to warming levels that go far beyond historical observations 33 --particularly given the unclear role of adaptation 19 . In addition, specification questions can further exacerbate socio-economic uncertainties 20 and uniform dose-response functions for aggregate GDP can mask heterogeneities between countries, sectors and income segments, with precipitation affecting agriculture and poorer households particularly 13 . Moreover, considering impacts in % of GDP implicitly assigns a lower weight to poorer regions within countries that are disproportionately exposed to climate change risks 34 .…”

“…To calculate the impacts of climate change, we compare annual economic impacts against the average impact during the historical baseline period for the same model-scenario pair, such that our impacts represent changes from a hypothetical scenario in which climate remains constant, following previous studies 2,13 . As a baseline period for GDP impacts, we again use the +0.84°C global warming level window for a given climate model m and RCP-SSP pair s for consistency with the calculation of our climate indicators.…”

“…While both approaches come with different advantages and limitations, top-down approaches usually neglect climatic shifts beyond annual temperature changes 10 . To address this shortcoming, recent studies have estimated the relationship between macro-level income and a wider range of climatic indicators, such as total precipitation [11][12][13] , temperature variability 14,15 , or temperature and precipitation extremes and anomalies 12,16,17 . However, these studies do not provide a forward-looking assessment of how much the inclusion of these climate indicators alters previous economic assessments of climate change-which is highly relevant for policy-making and future adaptation.…”

Global economic impact of weather variability on the rich and the poor

“…Econometric studies on inequality and climate change have found regressive effects of heat extremes 28 and increased macro-economic inequality between countries due to anthropogenic greenhouse gas forcing 29 . Further studies find that low income countries and/or population groups are impacted more severely by extreme events than their high income counterparts 30 and rainfall extremes have been shown to enhance inequality within countries 31 . Due to this multitude of impact channels, adaptation research is starting to consider the role of poverty and inequality in adaptation 32;33;34 , e. g. through climate insurance 35 .…”