Floods affect millions of people each year, with increasing frequency in the past decades. Floods, as any other natural phenomena, do not take place in a vacuum. Their impacts are modulated by the socioeconomic environments they affect, which are far from homogeneous and oftentimes characterized by deep disparities and inequalities. Ensuring sustainable development in a world where climate change is forecasted to increase the frequency and severity of flooding requires a nuanced understanding of these interactions between natural and socioeconomic systems. This dissertation sheds light on the impacts of flooding on economic outcomes of interest in two contrasting settings. First, Chapters 1 and 2 focus on the effects of flooding as a natural disaster in a developed country, the United States. Using evidence from Hurricane Sandy in 2012, these chapters explore how different neighborhoods, with different characteristics, responded to flooding. They conclude that heterogeneous responses led to an increased polarization along property value, racial, and income lines among neighborhoods. Then, Chapter 3 investigates the effects of seasonal flooding in the Malian Sahel. Unlike the previous setting, flooding brings about positive outcomes in this context, as livelihoods in this arid region are heavily dependent on surface water for agriculture. This chapter shows that lower seasonal flooding increases infant mortality. Thus, it provides evidence on the sort of long-term consequences that could affect low-income households after suffering short-lived resources shocks. Overall, this dissertation contributes to our understanding of the heterogeneous impacts of flooding. Increased awareness of these impacts would be key to formulate successful post-flood responses and policies to ensure future sustainable development.
Identifer | oai:union.ndltd.org:columbia.edu/oai:academiccommons.columbia.edu:10.7916/d8-6bnh-4163 |
Date | January 2020 |
Creators | Varela Varela, Ana |
Source Sets | Columbia University |
Language | English |
Detected Language | English |
Type | Theses |
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