Insights into the complementarity of natural disaster insurance purchases and risk reduction behavior.

While flooding is the costliest natural disaster risk, public-sector investments provide incomplete protection. Moreover, individuals are in general reluctant to voluntarily invest in measures which limit damage costs from natural disasters. The moral hazard hypothesis argues that insured individuals take fewer other preparedness measures based on their assumption that their losses will be covered anyway. Conversely, the advantageous selection hypothesis argues that individuals view insurance and other risk reduction measures as complements. This study offers a comprehensive assessment of factors related to the separate uptake of natural disaster insurance and the flood-proofing of homes as well as why people may take both of these measures together. We use data from a survey conducted in Paris, France, in 2018, after several flood events, for a representative sample of 2976 residents facing different levels of flood risk. We perform both main effects regressions and interaction analyses to reveal that home adaptation to flooding is positively associated with comprehensive insurance coverage, which includes financial protection against natural disasters. Furthermore, actual and perceived risks, as well as awareness of official information on flood risk, are found to explain some of the relationship between home adaptation and comprehensive insurance purchase. We suggest several recommendations to policymakers based on these insights which aim to address insurance coverage gaps and the failure to take disaster risk reduction measures. In particular, groups in socially vulnerable situations may benefit from subsidized insurance, low interest loans, and decision aids to implement costly adaptation measures.

Anticipating sea-level rise and human migration: A review of empirical evidence and avenues for future research.

Sea-level rise (SLR) threatens millions of people living in coastal areas through permanent inundation and other SLR-related hazards. Migration is one way for people to adapt to these coastal changes, but presents an enormous policy challenge given the number of people affected. Knowledge about the relationship between SLR-related hazards and migration is therefore important to allow for anticipatory policymaking. In recent years, an increasing number of empirical studies have investigated, using survey or census data, how SLR-related hazards including flooding, salinization, and erosion together with non-environmental factors influence migration behavior. In this article, we provide a systematic literature review of this empirical work. Our review findings indicate that flooding is not necessarily associated with increased migration. Severe flood events even tend to decrease long-term migration in developing countries, although more research is needed to better understand the underpinnings of this finding. Salinization and erosion do generally lead to migration, but the number of studies is sparse. Several non-environmental factors including wealth and place attachment influence migration alongside SLR-related hazards. Based on the review, we propose a research agenda by outlining knowledge gaps and promising avenues for future research on this topic. Promising research avenues include using behavioral experiments to investigate migration behavior under future SLR scenarios, studying migration among other adaptation strategies, and complementing empirical research with dynamic migration modeling. We conclude that more empirical research on the SLR-migration nexus is needed to properly understand and anticipate the complex dynamics of migration under SLR, and to design adequate policy responses. This article is categorized under: Climate Economics < Aggregation Techniques for Impacts and Mitigation CostsVulnerability and Adaptation to Climate Change < Learning from Cases and AnalogiesAssessing Impacts of Climate Change < Evaluating Future Impacts of Climate Change.

Lessons for climate policy from behavioral biases towards COVID-19 and climate change risks.

COVID-19 and climate change share several striking similarities in terms of causes and consequences. For instance, COVID-19 and climate change affect deprived and vulnerable communities the most, which implies that effectively designed policies that mitigate these risks may also reduce the widening inequalities that they cause. Both problems can be characterized as low-probability-high consequence (LP-HC) risks, which are associated with various behavioral biases that imply that individual behavior deviates from rational risk assessments by experts and optimal preparedness strategies. One could view the COVID-19 pandemic as a rapid learning experiment about how to cope more effectively with climate change and develop actions for reducing its impacts before it is too late. However, the ensuing question relates to whether the COVID-19 crisis and its aftermath will speed up climate change mitigation and adaptation policies, which depends on how individuals perceive and take action to reduce LP-HC risks. Using insights into behavioral biases in individual decisions about LP-HC risks based on decades of empirical research in psychology and behavioral economics, we illustrate how parallels can be drawn between decision-making processes about COVID-19 and climate change. In particular, we discuss six important risk-related behavioral biases in the context of individual decision making about these two global challenges to derive lessons for climate policy. We contend that the impacts from climate change can be mitigated if we proactively draw lessons from the pandemic, and implement policies that work with, instead of against, an individual's risk perceptions and biases. We conclude with recommendations for communication policies that make people pay attention to climate change risks and for linking government responses to the COVID-19 crisis and its aftermath with environmental sustainability and climate action.

Pathways to resilience: adapting to sea level rise in Los Angeles.

Los Angeles (LA) County's coastal areas are highly valued for their natural benefits and their economic contributions to the region. While LA County already has a high level of exposure to flooding (e.g. people, ports, and harbors), climate change and sea level rise will increase flood risk; anticipating this risk requires adaptation planning to mitigate social, economic, and physical damage. This study provides an overview of the potential effects of sea level rise on coastal LA County and describes adaptation pathways and estimates associated costs in order to cope with sea level rise. An adaptation pathway in this study is defined as the collection of measures (e.g., beach nourishment, dune restoration, flood-proofing buildings, and levees) required to lower flood risk. The aim of using different adaptation pathways is to enable a transition from one methodology to another over time. These pathways address uncertainty in future projections, allowing for flexibility among policies and potentially spreading the costs over time. Maintaining beaches, dunes, and their natural dynamics is the foundation of each of the three adaptation pathways, which address the importance of beaches for recreation, environmental value, and flood protection. In some scenarios, owing to high projections of sea level rise, additional technical engineering options such as levees and sluices may be needed to reduce flood risk. The research suggests three adaptation pathways, anticipating a +1 ft (0.3 m) to +7 ft (+2 m) sea level rise by year 2100. Total adaptation costs vary between $4.3 and $6.4 bn, depending on measures included in the adaptation pathway.

Global economic impacts of climate variability and change during the 20th century.

Estimates of the global economic impacts of observed climate change during the 20th century obtained by applying five impact functions of different integrated assessment models (IAMs) are separated into their main natural and anthropogenic components. The estimates of the costs that can be attributed to natural variability factors and to the anthropogenic intervention with the climate system in general tend to show that: 1) during the first half of the century, the amplitude of the impacts associated with natural variability is considerably larger than that produced by anthropogenic factors and the effects of natural variability fluctuated between being negative and positive. These non-monotonic impacts are mostly determined by the low-frequency variability and the persistence of the climate system; 2) IAMs do not agree on the sign (nor on the magnitude) of the impacts of anthropogenic forcing but indicate that they steadily grew over the first part of the century, rapidly accelerated since the mid 1970's, and decelerated during the first decade of the 21st century. This deceleration is accentuated by the existence of interaction effects between natural variability and natural and anthropogenic forcing. The economic impacts of anthropogenic forcing range in the tenths of percentage of the world GDP by the end of the 20th century; 3) the impacts of natural forcing are about one order of magnitude lower than those associated with anthropogenic forcing and are dominated by the solar forcing; 4) the interaction effects between natural and anthropogenic factors can importantly modulate how impacts actually occur, at least for moderate increases in external forcing. Human activities became dominant drivers of the estimated economic impacts at the end of the 20th century, producing larger impacts than those of low-frequency natural variability. Some of the uses and limitations of IAMs are discussed.

Low-probability flood risk modeling for New York City.

The devastating impact by Hurricane Sandy (2012) again showed New York City (NYC) is one of the most vulnerable cities to coastal flooding around the globe. The low-lying areas in NYC can be flooded by nor'easter storms and North Atlantic hurricanes. The few studies that have estimated potential flood damage for NYC base their damage estimates on only a single, or a few, possible flood events. The objective of this study is to assess the full distribution of hurricane flood risk in NYC. This is done by calculating potential flood damage with a flood damage model that uses many possible storms and surge heights as input. These storms are representative for the low-probability/high-impact flood hazard faced by the city. Exceedance probability-loss curves are constructed under different assumptions about the severity of flood damage. The estimated flood damage to buildings for NYC is between US$59 and 129 millions/year. The damage caused by a 1/100-year storm surge is within a range of US$2 bn-5 bn, while this is between US$5 bn and 11 bn for a 1/500-year storm surge. An analysis of flood risk in each of the five boroughs of NYC finds that Brooklyn and Queens are the most vulnerable to flooding. This study examines several uncertainties in the various steps of the risk analysis, which resulted in variations in flood damage estimations. These uncertainties include: the interpolation of flood depths; the use of different flood damage curves; and the influence of the spectra of characteristics of the simulated hurricanes.