What drives households to buy flood insurance? New evidence from Georgia

Atreya, Ajita; Ferreira, Susana; Michel-Kerjan, Erwann

doi:10.1016/j.ecolecon.2015.06.024

Cited by 157 publications

(101 citation statements)

References 42 publications

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“…To explain these results, Gallagher proposes a learning model in which people react to the salient event but forget over time. Atreya et al (2015) also find that prior flooding increases flood insurance take-up, with the effect dissipating over three years.Changing perceptions of the probability of a loss are likely a key driver of these effects. Botzen et al (2015) show that experiencing a flood leads to an increase in the perception of flood risk.…”

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confidence: 78%

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Behavioral Household Finance

Beshears

Choi

Laibson

et al. 2018

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This chapter provides an overview of household finance. The first part summarizes key facts regarding household financial behavior, emphasizing empirical regularities that are inconsistent with the standard classical economic model and discussing extensions of the classical model and explanations grounded in behavioral economics that can account for the observed patterns. This part covers five topics: consumption and savings, borrowing, payments, asset allocation, and insurance. The second part addresses interventions that firms, governments, and other parties deploy to shape household financial outcomes: education and information, peer effects and social influence, product design, advice and disclosure, choice architecture, and interventions that directly target prices or quantities. This chapter is divided into two parts, each of which is further divided into several sections. The first part summarizes key facts regarding household financial behavior, emphasizing empirical regularities that are inconsistent with the standard classical economic model and discussing both extensions of the classical model and explanations grounded in behavioral economics that can account for the observed patterns. This part covers five topics: (I) consumption and savings, (II) borrowing, (III) payments, (IV) asset allocation, and (V) insurance. The second part addresses interventions that firms, governments, and other parties deploy to shape household financial outcomes: (VI) education and information, (VII) peer effects and social influence, (VIII) product design, (IX) advice and disclosure, (X) choice architecture, and (XI) interventions that directly target prices or quantities. The final section of the paper (XII) concludes. John BeshearsWe offer broad coverage of the household finance literature, but we limit the scope of our discussion along some dimensions. We focus on the U.S. institutional context and on empirical work based on U.S. data, although we do bring evidence from other wealthy countries to bear when germane and occasionally reference evidence from developing countries. We address household asset allocation but do not draw out its implications for asset pricing, which are covered by the asset pricing chapter in this handbook. Although household decisions regarding health care are relevant to household finance, we largely omit this literature from our chapter because it is covered in depth in the chapter on behavioral health economics. Finally, there is some overlap between our section on financial product design and the chapter on behavioral industrial organization; we refer readers to that chapter for related material on that topic. Part 1: Facts I. Consumption and SavingsBeginning with the seminal work of Modigliani and Brumberg (1954) and Friedman (1957), economists have embraced the view that households choose to save and borrow to smooth consumption over the lifecycle. Intuitively, if agents have concave utility functions over consumption, then they should spread consumption across time to optimally...

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confidence: 78%

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confidence: 78%

Behavioral Household Finance

Beshears

Choi

Laibson

et al. 2018

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“…Experiment-based studies include Slovic et al (1977), McClelland et al (1993), andGanderton et al (2000). More recently, researchers have analyzed data on actual insurance policies purchased from the NFIP (Browne and Hoyt 2000;Dixon et al 2006;Zahran et al 2009;Michel-Kerjan and Kousky 2010;Kousky 2011b;Atreya et al 2015;Kousky and Michel-Kerjan 2015). These analyses focus on data from different geographic regions, time periods, and units of analysis (individual policies to states).…”

Section: Literaturementioning

confidence: 99%

“…Although about a quarter of NFIP policies are subsidized and homeowners in Special Flood Hazard Areas, SFHAs (i.e., 100-year floodplains) with a federally regulated lender are mandated to buy flood insurance, only half of single-family homes in SFHAs and about 1% outside SFHAs have flood insurance policies (Dixon et al 2006). The NFIP is also deeply in debt-$24 billion as of 7/13 (Atreya et al 2015;Kousky and Michel-Kerjan 2015), and some of the state-run catastrophe insurance pools may also have insufficient funds to cover large-scale disasters (Kousky 2011a).…”

Section: Introductionmentioning

confidence: 98%

Homeowner purchase of insurance for hurricane-induced wind and flood damage

et al. 2017

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Understanding the circumstances under which homeowners will purchase insurance is critical to creating an effective insurance market for hurricane wind and flood loss. This paper contributes to the empirical literature on the subject through an analysis of survey data for homeowners in North Carolina. We develop separate mixed logit models for flood insurance and wind insurance purchasing decisions. The analysis uses stated preference data on the influence of premium and deductible to address some limitations of revealed preference data in which it is difficult to fully decouple effects of premium, deductible, risk, and coverage limit, and mandatory purchase requirements. The results for flood insurance and wind insurance are similar. We find evidence that the following are all significant and associated with higher probability of purchasing insurance-lower premium, lower deductible, more recent previous hurricane experience, location in a floodplain or closer to the coast, higher income, and younger homeowners. However, demand is relatively inelastic with respect to premium and deductible, and the willingness to pay for a $1 reduction in deductible varies throughout the population with some willing to pay more than $1, a behavioral anomaly. The recency of the last hurricane experience is more influential for homeowners who experienced damage than for homeowners who did not. Results suggest that insurance purchase and home retrofits are complements, not substitutes. Finally, the paper presents statistical models that can be used to predict insurance penetration rates for a region under different premium levels.

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“…These studies find that proximity-towater and water-view have positive influences on housing sales prices (Leggett & Bockstael 2000;Samarasinghe & Sharp 2010;Bin et al 2011), while flood and erosion risk associated with the coastal zone diminish housing values (Kriesel, Randall, & Lichtkoppler 1993;Bin & Polasky 2004;Samarasinghe & Sharp 2010;Bin, et al 2011;Rambaldi, et al 2012;Jin et al 2015). Further, evidence suggests that risk perceptions that drive price differentials can be influenced by the occurrence of natural disasters (Hallstrom & Smith 2005;Carbone, Hallstrom, & Smith 2006;Bin & Landry 2013;Atreya, Ferreira, & Kriesel 2013;Atreya & Ferreira 2015).…”

Section: Coastal Housing Marketsmentioning

confidence: 99%

Economics of Coastal Erosion and Adaptation to Sea Level Rise

Gopalakrishnan

Landry

Whitehead

2016

Annu. Rev. Resour. Econ.

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This paper provides a review and synthesis of geo-economic models that are used to analyze coastal erosion management and shoreline change. We outline a generic framework for analyzing risk-mitigating and/or recreation-enhancing policy interventions within a dynamic framework, and we review literature that informs the nature and extent of net benefit flows associated with coastal management. Using stated preference analysis, we present new estimates on household preferences for shoreline erosion management, including costs associated with ecological impacts of management. Lastly, we offer some guidance on directions for future research.

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What drives households to buy flood insurance? New evidence from Georgia

Cited by 157 publications

References 42 publications

Behavioral Household Finance

Behavioral Household Finance

Homeowner purchase of insurance for hurricane-induced wind and flood damage

Economics of Coastal Erosion and Adaptation to Sea Level Rise

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