Flood Risk Perceptions and Insurance Choice: Do Decisions in the Floodplain Reflect Overoptimism?

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.

Assessment of Public Flood Risk Perception and Influencing Factors: An Example of Jiaozuo City, China

There are many studies showing that public flood risk perception may promote people’s motivation to reduce flood risk and enhance their coping behavior, thus providing useful insights for flood risk management. The purpose of this article is to estimate residents’ flood risk perception in Jiaozuo City and to identify the influencing factors. A questionnaire survey method was used to collect data and a composite index was constructed to measure public risk perception. Each respondent’s grade of flood risk perception was calculated using the relationship between the standard deviation (SD) and the mean value (MV) of flood risk perception index (RPI) scores. Moreover, the hypotheses concerning different groups were tested using an independent sample T-test and one-way ANOVA (analysis of variance), and the group differences in flood risk perception on each observed dependent variable were explored using post hoc tests. The flood risk perception of the total respondents was divided into three levels based on the SD and MV of RPI scores: low (68.4%), moderate (13.7%), and high (17.9%). Respondents with low education, low income, less flood experiences, and who have married, lived in rural areas or near rivers/reservoirs had a higher flood risk perception than others, and respondents who lived in flood storage areas had a lower risk perception. Moreover, the ability to mitigate floods and the trust in flood-control projects were negatively related to the flood risk perception.

Natural hazard insurance demand: A systematic review

The mitigation of natural hazard costs such as loss of property, life, crops and medical costs can be achieved through the adoption of insurance. It is, however, not clear whether there is corresponding demand for insurance given the increasing frequency and veracity of natural hazards, especially in South Africa. This study follows the guideline of Preferred Reporting items for Systematic Review and Meta-analysis Protocols (PRISMA-P) to identify the relevant works on the subject. A total of 645 articles emerged on initial search and after screening, 39 remained which have been reviewed in this study. Reviewing the studies and conflating with the study objectives, the following themes emerged for discussion on demand for natural hazard insurance, is there demand for natural hazard insurance?; psychology of decision-making; risk perception; risk preference and willingness to pay. The study found that studies of demand for insurance have identified that there is low demand for tailor-made insurance products for natural hazards. Further analysis of the demand revealed that normative and descriptive decision-making of buying natural hazard insurance is part of the psychological factors that determine demand. Whilst risk preference and perception have sub-attributes that affect their impact on demand such as experience, age and salience to natural hazards in communities. Whilst willingness to pay is also a broad concept which is analysed using both monetary and non-monetary factors in literature, the results also identified that there is a huge gap in literature in terms of studies that cover risk preference and perception in Africa and in the Southern African Development Community (SADC) region.

Risk Perceptions and Flood Insurance: Insights from Homeowners on the Georgia Coast

Scholars highlight a wide array of factors that can influence individual decision-making under risk. Utilizing survey data, we explore many potential factors that affect risk perception and protective behaviors. Our focus is on coastal Georgia, which has lower historical risk relative to the rest of the Southeast U.S., and which many people perceive as relatively safe, but was recently adversely affected by two major storms. The results indicate a majority of coastal residents expect coastal storms and other hazards to be worse in the future. The regression results suggest perceived damages, risk tolerance, wealth exposure, and flood zone are robust determinants of flood insurance purchase. Other factors, like flood zone awareness and attitudes towards community risk management initiatives—like shoreline armoring, beach replenishment, and coastal retreat—are also indicated to have a high correlation with flood insurance purchase.

Geographic Distributions of Extreme Weather Risk Perceptions in the United States

Weather and climate disasters pose an increasing risk to life and property in the United States. Managing this risk requires objective information about the nature of the threat and subjective information about how people perceive it. Meteorologists and climatologists have a relatively firm grasp of the historical objective risk. For example, we know which parts of the United States are most likely to experience drought, heat waves, flooding, snow or ice storms, tornadoes, and hurricanes. We know less about the geographic distribution of the perceived risks of meteorological events and trends. Do subjective perceptions align with exposure to weather risks? This question is difficult to answer because analysts have yet to develop a comprehensive and spatially consistent methodology for measuring risk perceptions across geographic areas in the United States. In this project, we propose a methodology that uses multilevel regression and poststratification to estimate extreme weather and climate risk perceptions by geographic area (i.e., region, state, forecast area, and county). Then we apply the methodology using data from three national surveys (n = 9,542). This enables us to measure, map, and compare perceptions of risk from multiple weather hazards in geographic areas across the country.

Predicting flood insurance claims with hydrologic and socioeconomic demographics via machine learning: Exploring the roles of topography, minority populations, and political dissimilarity

Current research on flooding risk often focuses on understanding hazards, de-emphasizing the complex pathways of exposure and vulnerability. We investigated the use of both hydrologic and social demographic data for flood exposure mapping with Random Forest (RF) regression and classification algorithms trained to predict both parcel- and tract-level flood insurance claims within New York State, US. Topographic characteristics best described flood claim frequency, but RF prediction skill was improved at both spatial scales when socioeconomic data was incorporated. Substantial improvements occurred at the tract-level when the percentage of minority residents, housing stock value and age, and the political dissimilarity index of voting precincts were used to predict insurance claims. Census tracts with higher numbers of claims and greater densities of low-lying tax parcels tended to have low proportions of minority residents, newer houses, and less political similarity to state level government. We compared this data-driven approach and a physically-based pluvial flood routing model for prediction of the spatial extents of flooding claims in two nearby catchments of differing land use. The floodplain we defined with physically based modeling agreed well with existing federal flood insurance rate maps, but underestimated the spatial extents of historical claim generating areas. In contrast, RF classification incorporating hydrologic and socioeconomic demographic data likely overestimated the flood-exposed areas. Our research indicates that quantitative incorporation of social data can improve flooding exposure estimates.

Insights into Flood Risk Misperceptions of Homeowners in the Dutch River Delta

Flooding is one of the most significant natural disasters worldwide. Nevertheless, voluntary take-up of individual damage reduction measures is low. A potential explanation is that flood risk perceptions of individual homeowners are below objective estimates of flood risk, which may imply that they underestimate the flood risk and the damage that can be avoided by damage reduction measures. The aim of this article is to assess possible flood risk misperceptions of floodplain residents in the Netherlands, and to offer insights into factors that are related with under- or overestimation of perceived flood risk. We analyzed survey data of 1,848 homeowners in the Dutch river delta and examine how perceptions of flood probability and damage relate to objective risk assessments, such as safety standards of dikes, as well as heuristics, including the availability heuristic and the affect heuristic. Results show that many Dutch floodplain inhabitants significantly overestimate the probability, but underestimate the maximum expected water level of a flood. We further observe that many respondents apply the availability heuristic.