Essays on climate, health and economics

Abstract

The impacts of climate change are predicted to continue worsening and developing countries are expected to bear the hardest burden. Extreme temperatures or precipitations, wildfires, floods, and droughts contribute to increasing health problems, leading to adverse impacts on cognitive development, employment, and earnings. Despite the increasing evidence of the link between climate and health, this has yet to be fully explored in developing countries. Thus, this thesis aims to deepen the understanding of the relationship between climate, health, and economics in Africa.

Linking Demographic and Health Surveys (DHS) with climate data, the thesis investigates the long term impact of droughts on women's health and socioeconomic outcomes as well as on the health of their children. The findings indicate that exposure to cumulative droughts during childhood is associated with lower educational attainment and household wealth in adulthood, increased probabilities of having underweight and low birthweight offspring, and a higher likelihood of giving birth to female children. The thesis also finds that the long term effects of droughts are mainly felt by boys than girls.

The thesis further explores the remediating role of positive rainfall shocks on catch-up growth in weight for low birth weight (LBW) children in Kenya. Using the relative and absolute definitions of catch-up growth expressed as a positive change in either WAZ or Weight for Age Difference (WAD), respectively, the paper finds that LBW children experience catch-up growth in weight both at ages 2 and 4 and that positive rainfall shocks, specifically moderate moisture, may improve both WAZ and WAD, serving as a remedial investment.

Finally, the thesis uses anonymised daily Covid-19 case data and Meteorological data to explore the impact of temperature and relative humidity on the incidence of Covid-19 in Cape Town while distinguishing between Low and High socio-economic status (LSE, HSE) areas. Using the distributed-lag nonlinear model (DLNM), the findings show that people from HSE were more vulnerable to cold effects than those from LSE. Heat effects significantly lowered the risk of Covid-19 incidence in LSE; in contrast, heat effects increased the risk in HSE. Relative humidity increased the risk of Covid-19 in all areas.