Essays on the Economics of Natural Disasters

• Auteur / Autrice : Thomas Tveit
• Direction : Andreas Heinen
• Type : Thèse de doctorat
• Discipline(s) : Sciences économiques - EM2PSI
• Date : Soutenance le 22/11/2017
• Etablissement(s) : Cergy-Pontoise
• Ecole(s) doctorale(s) : École doctorale Économie, Management, Mathématiques, Physique et Sciences Informatiques (Cergy-Pontoise, Val d'Oise)
• Partenaire(s) de recherche : Laboratoire : THEMA Théorie économique, modélisation et applications (Cergy ; 2006-)
• Jury : Président / Présidente : Robert F. Elliott
• Jury : Examinateurs / Examinatrices : Andreas Heinen, Eric Strobl
• Jury : Rapporteurs / Rapporteuses : Ingmar Schumacher

Mots clés

Mots clés libres

Natural disasters

Financial impact

Econometric analysis

Non-Economic impact

Résumé

Natural disasters have always been and probably always will be a problem for humans and their settlements. With global warming seemingly increasing the frequency and strength of the climate related disasters, and more and more people being settled in urban centers, the ability to model and predict damage is more important than ever.The aim of this thesis has been to model and analyze a broad range of disaster types and the kind of impact that they have. By modeling damage indices for disaster types as different as hurricanes and volcanic eruptions, the thesis helps with understanding both similarities and differences between how disasters work and what impact they have on societies experiencing them. The thesis comprises four different chapters in addition to this introduction, where all of them include modeling of one or more types of natural disasters and their impact on real world scenarios such as local budgets, birth rates and economic growth.Chapter 2 is titled “Natural Disaster Damage Indices Based on Remotely Sensed Data: An Application to Indonesia". The objective was to construct damage indices through remotely sensed and freely available data. In short, the methodology exploits that one can use nightlight data as a proxy for economic activity. Then the nightlights data is matched with remote sensing data typically used for natural hazard modeling. The data is then used to construct damage indices at the district level for Indonesia, for different disaster events such as floods, earthquakes, volcanic eruptions and the 2004 Christmas Tsunami. The chapter is forthcoming as a World Bank Policy Research Paper under Skoufias et al. (2017a).Chapter 3 utilizes the indices from Chapter 2 to showcase a potential area of use for them. The title is “The Reallocation of District-Level Spending and Natural Disasters: Evidence from Indonesia" and the focus is on Indonesian district-level budgets. The aim was to use the modeled intensity from Chapter 2 to a real world scenario that could affect policy makers. The results show that there is evidence that some disaster types cause districts to move costs away from more general line items to areas such as health and infrastructure, which are likely to experience added pressure due to disasters. Furthermore, volcanic eruptions and the tsunami led to less investment into more durable assets both for the year of the disaster and the following year. This chapter is also forthcoming as a World Bank Policy Research Paper under Skoufias et al. (2017b).The fourth chapter, titled “Urban Global Impact of Earthquakes from 2004 through 2013", is a short chapter focusing on earthquake damage and economic growth. This chapter is an expansion of the index used in the previous two chapters, where we use global data instead of focusing on a single country. Using a comprehensive remotely sensed dataset of contour mapsof global earthquakes from 2004 through 2013 and utilizing global nightlights as an economic proxy we model economic impact in the year of the quakes and the year after. Overall, it is shown that earthquakes negatively impact local urban light emissions by 0.7 percent.Chapter 5 is named “A Whirlwind Romance: The Effect of Hurricanes on Fertility in Early 20th Century Jamaica" and deviates from the prior chapters in that it is a historical chapter that looks at birth rates in the early 1900s. The goal was to use the complete and long-term birth database for Jamaica and match this with hurricane data to check fertility rates. We create a hurricane destruction index derived from a wind speed model that we combine with data on more than 1 million births across different parishes in Jamaica. Analyzing the birth rate following damaging hurricanes, we find that there is a strong and significant negative effect of hurricane destruction on the number of births.