Abstract
Canadian homeowners are increasingly vulnerable to flooding, due to elevated levels of indebtedness and more frequent and severe weather events associated with changing climate conditions. This vulnerability imposes risks on the broader Canadian financial system, through its potential effects on mortgage holding institutions, insurance companies, and governments. It is therefore important to understand homeowners’ perceptions of flood risk and their efforts to mitigate against possible flood-related losses. Using data from a 2016 national survey of Canada, this chapter evaluates homeowners’ subjective evaluations of residential flooding risk, their likelihood of purchasing sewer backup and overland flood insurance, and their likelihood of undertaking in-home protective actions. Results show a marked difference in how prior flood experience and socioeconomic factors relate to the likelihood of purchasing flood insurance and the likelihood of undertaking in-home protective actions. These findings help to explain variations in homeowner flood mitigating behavior and offer insights into possible housing asset vulnerability that can inform disaster management policy.
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Notes
- 1.
The scale of this latest flooding disaster far surpasses the two most highly publicized floods that occurred in 2013. Reported costs were about $3.4 billion (2018 CDN) for the Calgary flood and $1 billion for the Toronto flood (Davies, 2020).
- 2.
This policy is different from those of France and the U.S. (Davies, 2020; Kousky et al., 2020). In the latter case, the federal government pays for the National Flood Insurance Program, but the program is administered by private insurance companies. Flood hazard maps identify high-risk areas, and buyers in those areas are required to purchase flood insurance to get a mortgage from a federally regulated mortgage lender.
- 3.
Prior to 2015, Canada was alone among most developed countries in not providing flood insurance to homeowners (Sandink et al., 2016).
- 4.
Price et al. (2019) report findings from an analysis of responses to the hypothetical infrastructure questions, which are not the focus of the present analysis.
- 5.
Splitting the sample into these five regions is commonly done when using Canadian data (Statistics Canada, 2016).
- 6.
Since the instrumental variable is zero in some instances, we add a one to its value prior to applying the log transformation.
- 7.
Estimated parameters for the equations used to address possible endogeneity (i.e., Eqs. 3, 5 ,7, and 8) are not reported, but are available upon request. Likelihood-ratio tests confirmed that instrumental variables are strongly correlated with the potentially endogenous variable. In the perceived risk model, for example, the instrumental variable exhibits a strong positive correlation with prior flood experience (χ2 = 36.72, p = 0.0000).
- 8.
Average marginal effects indicate the average predicted probability dependent variable when some covariates are fixed. In this instance, we predict each respondent’s probability of having a non-zero flood risk by setting their age to 30 years old and keeping all other covariates as they are. This process is repeated for ages of 45 and 60 years old.
- 9.
These values are not reported in the table but are calculated from the data.
- 10.
For this model, marginal predicted probabilities for not purchasing insurance are calculated by using the coefficients in Table 5 and setting each household income to $40,000 while keeping all other household covariates as they are. The average of these predictions is 42.7%. This process is repeated for household incomes of $80,000 and $120,000.
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Price, J.I., Dupont, D.P. (2023). Financial Risks Due to Residential Flooding: Incorporating Household Perceptions to Better Understand Behaviors. In: Gramlich, D., Walker, T., Michaeli, M., Esme Frank, C. (eds) Water Risk Modeling. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-031-23811-6_4
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